diff --git a/tutorial/1-modelling-patch-clamp.ipynb b/tutorial/1-modelling-patch-clamp.ipynb index 9e5f007..41b30d3 100644 --- a/tutorial/1-modelling-patch-clamp.ipynb +++ b/tutorial/1-modelling-patch-clamp.ipynb @@ -142,7 +142,7 @@ "id": "5597d996", "metadata": {}, "source": [ - "> For more about op amps and difference amplifiers, see [Appendix A1](./appendix-a/1-op-amp.ipynb)." + "> For more about op amps and difference amplifiers, see [Appendix B1](./appendix/b-op-amps/1-op-amp.ipynb)." ] }, { @@ -251,7 +251,7 @@ "metadata": {}, "source": [ "> A detailed analysis of the bandwidth is given in Sigworth 1995a.\n", - "> It involves transfer function representations, which are discussed in [Appendix A2](./appendix-a/2-laplace-and-filters.ipynb)." + "> It involves transfer function representations, which are discussed in [Appendix A1](./appendix/a-laplace/1-laplace-transforms.ipynb)." ] }, { @@ -283,11 +283,11 @@ "id": "86015f66-6523-4cd4-aa65-65614fc4d305", "metadata": {}, "source": [ - "> Further details about these two models are given in [Appendix A3](./appendix-a/3-non-ideal-op-amp.ipynb).\n", + "> Further details about these two models are given in [Appendix B2](./appendix/b-op-amps/2-non-ideal-op-amp.ipynb).\n", "> In short, the equations used by Weerakoon and Lei et al. are a simplification based on Sigworth's analysis.\n", - "> They give rise to slightly different behaviour, as can be seen in [Appendix B1](./appendix-b/1-uncompensated-models.ipynb), but for the analysis of many patch-clamp experiments their influence is overshadowed by the effects of the _series resistance_ and _membrane capacitance_, which are discussed below.\n", + "> They give rise to slightly different behaviour, as can be seen in [Appendix B3](./appendix/b-op-amps/3-resulting-vc-models.ipynb), but for the analysis of many patch-clamp experiments their influence is overshadowed by the effects of the _series resistance_ and _membrane capacitance_, which are discussed below.\n", "> \n", - "> Typical values for $\\tau_a$ are in the order of 10 to 100 ns, as given in [Appendix C3](./appendix-c/3-parameter-values.ipynb)." + "> Typical values for $\\tau_a$ are in the order of 10 to 100 ns." ] }, { @@ -499,10 +499,9 @@ "metadata": {}, "source": [ "> The model above differs subtly from the uncompensated model used in [Lei et al., 2020](https://doi.org/10.1098/rsta.2019.0348).\n", - "> A comparison is provided in [Appendix B1](./appendix-b/1-uncompensated-models.ipynb).\n", + "> A comparison is provided in [Tutorial 4](./4-simplifications.ipynb).\n", ">\n", - "> A list of alternative names and symbols for the components above is given in [Appendix C1](./appendix-c/1-symbols.ipynb).\n", - "> Notably $R_\\text{leak}$ is often called _seal resistance_, while $R_s$ is also referred to as _access resistance_." + "> $R_\\text{leak}$ is often called _seal resistance_, while $R_s$ is also referred to as _access resistance_." ] }, { @@ -522,14 +521,6 @@ "3. We leave out $E_\\text{off}$ and $I_\\text{leak}$, and set $I = 0$ (for now), leaving only the capacitative currents. As a result, at steady state we have $V_p = V_o = V_m$." ] }, - { - "cell_type": "markdown", - "id": "95a7b298-a320-4658-8ef0-de16277ffee1", - "metadata": {}, - "source": [ - "> The parameters used here are representitative of a small-cell experiment, and are given in [appendix C2](./appendix-c/2-parameter-defaults.ipynb)." - ] - }, { "cell_type": "code", "execution_count": 1, @@ -878,7 +869,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.12" } }, "nbformat": 4, diff --git a/tutorial/2-compensation.ipynb b/tutorial/2-compensation.ipynb index 7a6abb7..55ec7ce 100644 --- a/tutorial/2-compensation.ipynb +++ b/tutorial/2-compensation.ipynb @@ -14,15 +14,6 @@ "We will deal mostly with _transient_ distortions of the recorded output signal, which we call _artefacts_, and with transient differences between the true and intended membrane potential, which are an example of _imperfect control_." ] }, - { - "cell_type": "markdown", - "id": "59df3dd5-7aa9-458e-82c0-9c41fc9191eb", - "metadata": {}, - "source": [ - "> Artefacts, imperfect control, and general strategies for dealing with their effects, are discussed in [Appendix D1](./appendix-d/1-strategies.ipynb).\n", - "Stochastic and periodic noise are not discussed here, but a brief discussion is given in [Appendix D2](./appendix-d/2-inspecting-noise.ipynb)." - ] - }, { "cell_type": "markdown", "id": "f2b59884", @@ -78,7 +69,7 @@ "id": "f92327ba-b81c-4eed-9e51-05de94f548b3", "metadata": {}, "source": [ - "> A detailed description of LJP correction and sign conventions is provided in [Appendix D3](./appendix-d/3-liquid-junction-potential.ipynb)." + "> A detailed description of LJP correction and sign conventions is provided in [Appendix E1](./appendix/e-offsets/1-liquid-junction-potential.ipynb) and [Appendix E2](./appendix/e-offsets/2-offset-correction.ipynb)." ] }, { @@ -114,7 +105,7 @@ "id": "e2cbaa02-cd68-4e70-9844-86f1be2fdbcc", "metadata": {}, "source": [ - "> Values of $R_f$ and $C_f$ for different amplifiers are given in [Appendix C3](./appendix-c/3-parameter-values.ipynb)." + "> Values of $R_f$ and $C_f$ for different amplifiers are given in [Appendix Z1](./appendix/z-parameters/1-parameter-values.ipynb)." ] }, { @@ -349,8 +340,8 @@ "id": "9e1174f8-3454-448d-85f6-96d2ac6241aa", "metadata": {}, "source": [ - "> See [Appendix A4](./appendix-a/4-bessel-filters.ipynb) for more about filters.\n", - "> [Appendix C3](./appendix-c/3-parameter-values.ipynb) provides more amplifier values of $\\tau_\\text{rc}$." + "> See [Appendix C](./appendix/) for more about filters.\n", + "> [Appendix Z1](./appendix/z-parameters/1-parameter-values.ipynb) provides more amplifier values of $\\tau_\\text{rc}$." ] }, { @@ -418,7 +409,7 @@ "id": "959a141d-5714-4d3f-8663-e068f528a9c3", "metadata": {}, "source": [ - "> A derivation of the prediction equations from the schematics by Sigworth is given in [appendix B3](./appendix-b/3-sigworth-rs.ipynb)." + "> A derivation of the prediction equations from the schematics by Sigworth is given in [appendix C1](./appendix/c-rs/1-compensation-prediction.ipynb)." ] }, { @@ -573,7 +564,7 @@ "id": "da60337b-c966-4751-90e6-f68009ea6ff2", "metadata": {}, "source": [ - "> Background on Bessel filters is provided in [Appendix A4](./appendix-a/4-bessel-filters.ipynb)." + "> Background on Bessel filters is provided in [Appendix C](./appendix/)." ] }, { @@ -648,7 +639,7 @@ "id": "6b334389-337d-425a-a39b-b085707ef62d", "metadata": {}, "source": [ - "> These equations are derived and discussed in [Appendix A5](./appendix-a/5-bessel-filter-odes.ipynb)." + "> These equations are derived and discussed in [Appendix D2](./appendix/d-filters/2-bessel-filters-ode.ipynb) and summarised in [Appendix D3](./appendix/d-filters/3-bessel-filters-ode-summary.ipynb)." ] }, { @@ -874,7 +865,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.12" } }, "nbformat": 4, diff --git a/tutorial/README.md b/tutorial/README.md index a747278..954b83b 100644 --- a/tutorial/README.md +++ b/tutorial/README.md @@ -6,44 +6,46 @@ The initial exposition draws on a book chapter by [Sigworth (1995a)](https://doi To view the notebooks, use the GitHub or nbviewer links below, or clone the repository and run Jupyter notebook locally. Running locally will require the dependencies from `requirements.txt`. -A list of references and further reading is provided [here](./references.ipynb). +[↩ Back to the main repository](https://github.com/CardiacModelling/VoltageClampModel) -[↩ Back to the main repository](https://github.com/CardiacModelling/VoltageClampModel-new) - -## Modelling patch-clamp experiments +## 1. Modelling patch-clamp experiments [![github](./img/github.svg)](./1-modelling-patch-clamp.ipynb) -[![nbviewer](./img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/1-modelling-patch-clamp.ipynb) +[![nbviewer](./img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/1-modelling-patch-clamp.ipynb) The first notebook describes the uncompensated patch-clamp set up, and derives an ODE model from the electrical schematics. -## Modelling electronic compensation +## 2. Modelling electronic compensation [![github](./img/github.svg)](./2-compensation.ipynb) -[![nbviewer](./img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/2-compensation.ipynb) +[![nbviewer](./img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/2-compensation.ipynb) The model is updated to include the compensation circuitry commonly used in patch-clamp amplifiers. -## Simulating a manual patch clamp experiment +## 3. Simulating a manual patch clamp experiment [![github](./img/github.svg)](./3-simulations.ipynb) -[![nbviewer](./img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/3-simulations.ipynb) +[![nbviewer](./img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/3-simulations.ipynb) We walk through and simulate the early steps of a manual patch-clamp experiment. -## Simplified models +## 4. Simplified models [![github](./img/github.svg)](./4-simplifications.ipynb) -[![nbviewer](./img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/4-simplifications.ipynb) +[![nbviewer](./img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/4-simplifications.ipynb) In the final notebook, we derive simplified models and compare with previous work. ---- +## Resources + +- [![github](./img/github.svg)](./symbols.ipynb) + [![nbviewer](./img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/symbols.ipynb) + **Names and symbols** A table of all symbols, their meanings, and names used in other publications. -## Appendices +- [![github](./img/github.svg)](./tour.ipynb) + [![nbviewer](./img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/tour.ipynb) + **Default parameter values** and comments on how to reparameterise the model, are given in the Model Tour. -Finally, there are several appendices: +- [![github](./img/github.svg)](./references.ipynb) + [![nbviewer](./img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/references.ipynb) + **References** and further reading. -- [Appendix A](./appendix-a/README.md) adds details on electronics and filters. -- [Appendix B](./appendix-b/README.md) looks at details of the model derivation. -- [Appendix C](./appendix-c/README.md) provides default parameter values, and amplifier-specific ones. -- [Appendix D](./appendix-d/README.md) discusses remaining sources of error. -- [Appendix E](./appendix-e/README.md) looks at Rs and Cm estimates. +Finally, there are [several appendices](./appendix), which provide background on electronics and details of the model derivation. diff --git a/tutorial/appendix-a/6-stimulus-filter.ipynb b/tutorial/appendix-a/6-stimulus-filter.ipynb deleted file mode 100644 index e14f854..0000000 --- a/tutorial/appendix-a/6-stimulus-filter.ipynb +++ /dev/null @@ -1,487 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "044506d5-71e4-43da-8603-ce5103279e28", - "metadata": {}, - "source": [ - "# Appendix A6: Stimulus filter (HEKA)\n", - "**Appendix A provides extra background for path clamp electronics.**" - ] - }, - { - "cell_type": "markdown", - "id": "8da3b3fe-426a-4710-a21a-d01126734998", - "metadata": {}, - "source": [ - "In [Appendix A4](./4-bessel-filters.ipynb) and [Appendix A5](./5-bessel-filter-odes.ipynb) we looked at the 2-pole Bessel stimulus filter on HEKA amplifiers.\n", - "We saw it had two settings, labelled \"20 µs\" (default) and \"2 µs\", but that these numbers don't match up to the actual rise time.\n", - "\n", - "In this notebook, we use the ODE equations of a 2-pole and 1-pole filter, and fit them to data measured in a model cell." - ] - }, - { - "cell_type": "markdown", - "id": "5a92ccae-179a-42db-9161-748bc62fbf6e", - "metadata": {}, - "source": [ - "## Model cell recordings\n", - "\n", - "First, we load \"20us\" and \"2us\" data." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "c71df53a-68ab-463a-b8df-8bf6d5f02e00", - "metadata": {}, - "outputs": [], - "source": [ - "import myokit\n", - "import matplotlib.pyplot as plt\n", - "import numpy as np" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "b6aa6083-0d52-4d8d-b266-64b27793da89", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "d0 = myokit.DataLog.load('./res/stimulus-filter.zip').npview()\n", - "\n", - "fig = plt.figure(figsize=(5, 3))\n", - "fig.subplots_adjust(0.14, 0.15, 0.96, 0.98)\n", - "ax = fig.add_subplot()\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.set_ylabel('Command voltage (mV)')\n", - "ax.plot(d0.time(), d0['v20us'], 's-', label=r'Recording, 20$\\mu$s')\n", - "ax.plot(d0.time(), d0['v2us'], 's-', label=r'Recording, 2$\\mu$s')\n", - "ax.legend()\n", - "ax.set_xlim(0.98, 1.12)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "824a7187-4111-45e9-96ce-52b8adc379dc", - "metadata": {}, - "source": [ - "## Guessed rise times\n", - "\n", - "Next, we fit each by postulating rise times of 40 and 4 $\\mu$s." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "e59bf0af-31b1-4d5b-b01f-82ab62857b01", - "metadata": {}, - "outputs": [], - "source": [ - "m = myokit.parse_model(\"\"\"\n", - "[[model]]\n", - "filter.y1 = 0\n", - "filter.y2 = 0\n", - "filter.y3 = 0\n", - "\n", - "[filter]\n", - "pace = 0 bind pace\n", - "time = 0 bind time\n", - "tr = 0.04 [ms] in [ms]\n", - "# Second-order\n", - "a2 = tr * 1.3616 / log(9)\n", - " in [ms]\n", - "dot(y1) = 3 * (pace/a2^2 - y2/a2^2 - y1/a2)\n", - "dot(y2) = y1\n", - "# First-order\n", - "a1 = tr / log(9)\n", - " in [ms]\n", - "dot(y3) = (pace - y3) / a1\n", - "\"\"\")\n", - "\n", - "p = myokit.Protocol()\n", - "p.add_step(level=-100, duration=1)\n", - "p.add_step(level=100, duration=10)\n", - "\n", - "s = myokit.Simulation(m, p)\n", - "s.pre(1)\n", - "d1 = s.run(2, log_interval=1e-3).npview()\n", - "\n", - "s.reset()\n", - "s.set_constant('filter.tr', 0.004)\n", - "s.pre(1)\n", - "d2 = s.run(2, log_interval=1e-3).npview()" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "0e07cd74-39ca-46fe-b38b-8e948691e599", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10, 3))\n", - "fig.subplots_adjust(0.14, 0.15, 0.96, 0.98)\n", - "\n", - "ax = fig.add_subplot(1, 2, 1)\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.set_ylabel('Command voltage (mV)')\n", - "ax.plot(d0.time(), d0['v20us'], 's-', label=r'Recording, 20$\\mu$s')\n", - "ax.plot(d1.time(), d1['filter.y2'], label=r'Simulation, n=2, tr=40 $\\mu$s')\n", - "ax.plot(d1.time(), d1['filter.y3'], label=r'Simulation, n=1, tr=40 $\\mu$s')\n", - "ax.legend()\n", - "ax.set_xlim(0.98, 1.12)\n", - "\n", - "ax = fig.add_subplot(1, 2, 2)\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.plot(d0.time(), d0['v2us'], 's-', label=r'Recording, 2$\\mu$s')\n", - "ax.plot(d1.time(), d2['filter.y2'], label=r'Simulation, n=2, tr=4 $\\mu$s')\n", - "ax.plot(d1.time(), d2['filter.y3'], label=r'Simulation, n=1, tr=4 $\\mu$s')\n", - "ax.legend()\n", - "ax.set_xlim(0.99, 1.03)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "cbd81397-4a43-4898-8297-ea3fd25e960d", - "metadata": {}, - "source": [ - "This shows that, as a first approximation we can use rise times of 40 and 4 $\\mu$s for the stimulus filter.\n", - "\n", - "The equivalent 1-pole time constants are:" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "13f4d738-6c72-49fe-a486-fdbb50174094", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.float64(0.018204784532536746)" - ] - }, - "execution_count": 5, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "0.04 / np.log(9)" - ] - }, - { - "cell_type": "markdown", - "id": "9fb36abd-bfc9-47f7-9090-aef62bd9d11b", - "metadata": {}, - "source": [ - "and" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "38c963ac-e1e0-443c-903f-cc6021a8ec11", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "np.float64(0.0018204784532536748)" - ] - }, - "execution_count": 6, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "0.004 / np.log(9)" - ] - }, - { - "cell_type": "markdown", - "id": "eb4c1024-5d5c-48a6-9ec2-35bfc37e4107", - "metadata": {}, - "source": [ - "## Fitted rise times\n", - "\n", - "Next, we use `fmin` to find the rise times that give the best fits." - ] - }, - { - "cell_type": "markdown", - "id": "be277ef1-743b-425c-8ec3-0688813c87ad", - "metadata": {}, - "source": [ - "### Two-pole fits" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "dec8ec39-ea14-404f-87a9-a135739b1086", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Rise time 0.03838024902343749 ms\n" - ] - } - ], - "source": [ - "from scipy.optimize import fmin\n", - "\n", - "def error(tr):\n", - " s.reset()\n", - " s.set_constant('filter.tr', tr[0])\n", - " d = s.run(2, log_times=d0.time())\n", - " return np.sum((d0['v20us'] - d['filter.y2'])**2)\n", - "\n", - "tr2slow = fmin(error, 0.04, disp=False)[0]\n", - "print(f'Rise time {tr2slow} ms')\n", - "\n", - "s.set_constant('filter.tr', tr2slow)\n", - "s.reset()\n", - "s.pre(1)\n", - "d1 = s.run(2, log_interval=1e-3).npview()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "a0362b03-85f0-4d9f-ad56-65b6dca34bdc", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Rise time 0.005369531250000004 ms\n" - ] - } - ], - "source": [ - "def error(tr):\n", - " s.reset()\n", - " s.set_constant('filter.tr', tr[0])\n", - " d = s.run(2, log_times=d0.time())\n", - " return np.sum((d0['v2us'] - d['filter.y2'])**2)\n", - "\n", - "tr2fast = fmin(error, 0.004, disp=False)[0]\n", - "print(f'Rise time {tr2fast} ms')\n", - "\n", - "s.set_constant('filter.tr', tr2fast)\n", - "s.reset()\n", - "s.pre(1)\n", - "d2 = s.run(2, log_interval=1e-3).npview()" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "9151690b-721a-4b96-8d06-e57fce2d2d21", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10, 3))\n", - "fig.subplots_adjust(0.14, 0.15, 0.96, 0.98)\n", - "\n", - "ax = fig.add_subplot(1, 2, 1)\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.set_ylabel('Command voltage (mV)')\n", - "ax.plot(d0.time(), d0['v20us'], 's-', label=r'Recording, 20$\\mu$s')\n", - "ax.plot(d1.time(), d1['filter.y2'], label=rf'Simulation, n=2, tr={1e3*tr2slow:.0f} $\\mu$s')\n", - "ax.legend()\n", - "ax.set_xlim(0.98, 1.12)\n", - "\n", - "ax = fig.add_subplot(1, 2, 2)\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.plot(d0.time(), d0['v2us'], 's-', label=r'Recording, 2$\\mu$s')\n", - "ax.plot(d1.time(), d2['filter.y2'], label=rf'Simulation, n=2, tr={1e3*tr2fast:.1f} $\\mu$s')\n", - "ax.legend()\n", - "ax.set_xlim(0.99, 1.03)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "008c5e5a-263e-4c4a-a699-d10a44975370", - "metadata": {}, - "source": [ - "### One-pole fits" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "43929c2f-f974-4705-b82d-9731d8a66bef", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Rise time 0.05562500000000001 ms\n", - "Time constant 0.025316028490558917 ms\n" - ] - } - ], - "source": [ - "def error(tr):\n", - " s.reset()\n", - " s.set_constant('filter.tr', tr[0])\n", - " d = s.run(2, log_times=d0.time())\n", - " return np.sum((d0['v20us'] - d['filter.y3'])**2)\n", - "\n", - "tr1slow = fmin(error, 0.04, disp=False)[0]\n", - "print(f'Rise time {tr1slow} ms')\n", - "print(f'Time constant {tr1slow / np.log(9)} ms')\n", - "\n", - "s.set_constant('filter.tr', tr1slow)\n", - "s.reset()\n", - "s.pre(1)\n", - "d3 = s.run(2, log_interval=1e-3).npview()" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "5a5bf86d-33db-47a6-93c3-1bbf9018f54b", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Rise time 0.006590625000000008 ms\n", - "Time constant 0.0029995227014937534 ms\n" - ] - } - ], - "source": [ - "def error(tr):\n", - " s.reset()\n", - " s.set_constant('filter.tr', tr[0])\n", - " d = s.run(2, log_times=d0.time())\n", - " return np.sum((d0['v2us'] - d['filter.y3'])**2)\n", - "\n", - "tr1fast = fmin(error, 0.004, disp=False)[0]\n", - "print(f'Rise time {tr1fast} ms')\n", - "print(f'Time constant {tr1fast / np.log(9)} ms')\n", - "\n", - "s.set_constant('filter.tr', tr1fast)\n", - "s.reset()\n", - "s.pre(1)\n", - "d4 = s.run(2, log_interval=1e-3).npview()" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "7ce3b294-439d-4d07-8655-20c5ba516e21", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(10, 3))\n", - "fig.subplots_adjust(0.14, 0.15, 0.96, 0.98)\n", - "\n", - "ax = fig.add_subplot(1, 2, 1)\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.set_ylabel('Command voltage (mV)')\n", - "ax.plot(d0.time(), d0['v20us'], 's-', label=r'Recording, 20$\\mu$s')\n", - "ax.plot(d3.time(), d3['filter.y3'], label=rf'Simulation, n=1, tau={tr1slow / np.log(9):.3f} ms')\n", - "ax.legend()\n", - "ax.set_xlim(0.98, 1.12)\n", - "\n", - "ax = fig.add_subplot(1, 2, 2)\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.plot(d0.time(), d0['v2us'], 's-', label=r'Recording, 2$\\mu$s')\n", - "ax.plot(d4.time(), d4['filter.y3'], label=rf'Simulation, n=1, tau={tr1fast / np.log(9):.4f} ms')\n", - "ax.legend()\n", - "ax.set_xlim(0.99, 1.03)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "5e1af82c-62ef-49b3-b7a1-7c4e21094982", - "metadata": {}, - "source": [ - "So we can get reasonable approximations with a 1-pole filter with a tau of 25 or 3 $\\mu$s." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.11" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/tutorial/appendix-a/README.md b/tutorial/appendix-a/README.md deleted file mode 100644 index 40a60fa..0000000 --- a/tutorial/appendix-a/README.md +++ /dev/null @@ -1,10 +0,0 @@ -# Appendix A: Electronics - -1. Ideal op amps [![github](../img/github.svg)](1-op-amp.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/appendix-a/1-op-amp.ipynb) -2. Laplace transforms and filters [![github](../img/github.svg)](2-laplace-and-filters.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/appendix-a/2-laplace-and-filters.ipynb) -3. Non-ideal op amps [![github](../img/github.svg)](3-non-ideal-op-amp.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/appendix-a/3-non-ideal-op-amp.ipynb) -4. Bessel low-pass filters [![github](../img/github.svg)](4-bessel-filters.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/appendix-a/4-bessel-filters.ipynb) -5. Bessel filter ODEs [![github](../img/github.svg)](5-bessel-filter-odes.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/appendix-a/5-bessel-filter-odes.ipynb) -6. Stimulus filter [![github](../img/github.svg)](6-stimulus-filter.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/appendix-a/6-stimulus-filter.ipynb) - -[↩ Back to the tutorial index](../README.md) diff --git a/tutorial/appendix-b/1-uncompensated-models.ipynb b/tutorial/appendix-b/1-uncompensated-models.ipynb deleted file mode 100644 index a65cda3..0000000 --- a/tutorial/appendix-b/1-uncompensated-models.ipynb +++ /dev/null @@ -1,1034 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "fc24dbb4", - "metadata": {}, - "source": [ - "# Appendix B1: Models without compensation\n", - "**Appendix B discusses and compares patch clamp model equations**" - ] - }, - { - "cell_type": "markdown", - "id": "aff7c8af", - "metadata": {}, - "source": [ - "Based on the discussion in [Appendix A3](../appendix-a/3-non-ideal-op-amp.ipynb) we now look at models of uncompensated patch clamp, with voltage offset and leak current omitted for simplicity." - ] - }, - { - "cell_type": "markdown", - "id": "7d17c4f4", - "metadata": {}, - "source": [ - "" - ] - }, - { - "cell_type": "markdown", - "id": "5d0303e8", - "metadata": {}, - "source": [ - "We now write an equation for the voltage at every junction, starting bottom left:\n", - "\n", - "\\begin{align}\n", - "1. && C_m\\dot{V}_m = \\frac{V_p - V_m}{R_s} - I\n", - "\\end{align}\n", - "\n", - "where $I$ is the non-capacitative current through the cell membrane." - ] - }, - { - "cell_type": "markdown", - "id": "7f702770", - "metadata": {}, - "source": [ - "Next,\n", - "\n", - "\\begin{align}\n", - "C_p\\dot{V}_p = \\frac{V_o-V_p}{R_f} + C_f\\left(\\dot{V}_o-\\dot{V}_p\\right) - \\frac{V_p-V_m}{R_s}\n", - "\\end{align}\n", - "\n", - "which can be used as a differential equation for either $V_p$\n", - "\n", - "\\begin{align}\n", - "2a. && (C_p + C_f)\\dot{V}_p = \\frac{V_o-V_p}{R_f} + C_f\\dot{V}_o - \\frac{V_p-V_m}{R_s}\n", - "\\end{align}\n", - "or $V_o$\n", - "\\begin{align}\n", - "2b. && C_f\\dot{V}_o = \\frac{V_p-V_o}{R_f} + \\left(C_p+C_f\\right)\\dot{V}_p + \\frac{V_p-V_m}{R_s}\n", - "\\end{align}" - ] - }, - { - "cell_type": "markdown", - "id": "7ff20823", - "metadata": {}, - "source": [ - "Next, we have two options for an op-amp equation:\n", - "\n", - "\\begin{align}\n", - "3a. && \\tau_a\\dot{V}_o = V_c - V_p \\\\\n", - "3b. && \\tau_c\\dot{V}_p = V_c - V_p \\\\\n", - "\\end{align}\n", - "\n", - "where $V_c$ is the command voltage.\n", - "The value $\\tau_c$ is either a constant (80 nanoseconds) or $\\tau_c = \\tau_aC_t/C_f$." - ] - }, - { - "cell_type": "markdown", - "id": "db2a73ec", - "metadata": {}, - "source": [ - "And finally\n", - "\n", - "\\begin{align}\n", - "4a. && R_f I_\\text{obs} \\equiv V_\\text{out} = V_o - V_c\n", - "\\end{align}" - ] - }, - { - "cell_type": "markdown", - "id": "24d3bbca", - "metadata": {}, - "source": [ - "This gives us two models: **(1, 2a, 3a, 4)** and **(1, 2b, 3b, 4)**." - ] - }, - { - "cell_type": "markdown", - "id": "f7e3ea4c", - "metadata": {}, - "source": [ - "## Lei-style model\n", - "\n", - "The model used in Lei et al. (2020) also starts from\n", - "\n", - "\\begin{align}\n", - "1. && C_m\\dot{V}_m = \\frac{V_p - V_m}{R_s} - I && \\text{(Equation S2.10)}\n", - "\\end{align}\n", - "\n", - "and \n", - "\n", - "\\begin{align}\n", - "3b. && \\tau_c\\dot{V}_p = V_c - V_p && \\text{(Equation S2.12)}\n", - "\\end{align}\n", - "\n", - "but then adds the relationship \n", - "\\begin{align}\n", - "5. && R_fC_f \\dot{I}_\\text{obs} = I + C_m\\dot{V}_m + C_p\\dot{V}_p - I_\\text{obs} && \\text{(Equation S2.8, S2.5)}\n", - "\\end{align}\n", - "\n", - "resulting in a model (1, 3b, 5)." - ] - }, - { - "cell_type": "markdown", - "id": "c8ad8948", - "metadata": {}, - "source": [ - "Using equation 4a, we can rewrite this as an ODE for $V_o$:\n", - "\n", - "\\begin{align}\n", - "C_f(\\dot{V}_o - \\dot{V}_c) &= I + C_m\\dot{V}_m + C_p\\dot{V}_p - \\frac{V_o - V_c}{R_f} \\\\\n", - " &= \\frac{V_p - V_m}{R_s} + C_p\\dot{V}_p - \\frac{V_o - V_c}{R_f} \\\\\n", - "\\end{align}\n", - "\n", - "\\begin{align}\n", - "2c. && C_f\\dot{V}_o = \\frac{V_c - V_o}{R_f} + C_p\\dot{V}_p + C_f\\dot{V}_c + \\frac{V_p - V_m}{R_s}\n", - "\\end{align}\n", - "\n", - "for an equivalent formulation (1, 2c, 3b, 4a).\n", - "\n", - "Comparing to\n", - "\\begin{align}\n", - "2b. && C_f\\dot{V}_o = \\frac{V_p-V_o}{R_f} + \\left(C_p+C_f\\right)\\dot{V}_p + \\frac{V_p-V_m}{R_s}\n", - "\\end{align}\n", - "\n", - "we see that the two are equal when $V_c = V_p$ and $\\dot{V}_c = \\dot{V}_p$ (so if we have a perfect op-amp, but some other filtering on the output)." - ] - }, - { - "cell_type": "markdown", - "id": "b0b8ecb8", - "metadata": {}, - "source": [ - "### Alternative formulation\n", - "\n", - "Alternatively, we can define\n", - "\n", - "\\begin{align}\n", - "4b. && R_f I_\\text{obs} = V_o - V_p\n", - "\\end{align}\n", - "\n", - "with which we can derive 2b. from equations S2.8, S2.5, and S2.10:\n", - "\n", - "\\begin{align}\n", - "R_f C_f \\dot{I}_\\text{obs} &= I_\\text{in} - I_\\text{obs} \\\\\n", - " &= I + C_m \\dot{V}_m + C_p \\dot{V}_p - I_\\text{obs} \\\\\n", - " &= \\frac{V_p - V_m}{R_s} + C_p \\dot{V}_p - I_\\text{obs} \\\\\n", - "C_f (\\dot{V}_o - \\dot{V}_p) &= \\frac{V_p - V_m}{R_s} + C_p \\dot{V}_p - \\frac{V_o - V_p}{R_f} \\\\\n", - "C_f \\dot{V}_o &= \\frac{V_p - V_m}{R_s} + \\frac{V_p - V_o}{R_f} + (C_p + C_f) \\dot{V}_p\n", - "\\end{align}\n", - "\n", - "so that we can write the same model as **(1, 2b, 3b, 4b)**." - ] - }, - { - "cell_type": "markdown", - "id": "2154fb47", - "metadata": {}, - "source": [ - "## Three models\n", - "\n", - "Summarising:\n", - "\n", - "\\begin{align}\n", - "1. && C_m\\dot{V}_m = \\frac{V_p - V_m}{R_s} - I\n", - "\\end{align}\n", - "\n", - "\\begin{align}\n", - "2a. && (C_p + C_f)\\dot{V}_p &= \\frac{V_o-V_p}{R_f} + \\frac{V_m-V_p}{R_s} + C_f\\dot{V}_o \\\\\n", - "2b. && C_f\\dot{V}_o &= \\frac{V_p-V_o}{R_f} + \\frac{V_p-V_m}{R_s} + \\left(C_p+C_f\\right)\\dot{V}_p\n", - "\\end{align}\n", - "\n", - "\\begin{align}\n", - "3a. && \\tau_a\\dot{V}_o = V_c - V_p \\\\\n", - "3b. && \\tau_c\\dot{V}_p = V_c - V_p \\\\\n", - "\\end{align}\n", - "\n", - "\\begin{align}\n", - "4a. && R_f I_\\text{obs} = V_o - V_c \\\\\n", - "4b. && R_f I_\\text{obs} = V_o - V_p\n", - "\\end{align}\n", - "\n", - "From the above, we can distill three models:\n", - "\n", - "- **Model A** - A \"Sigworth-style\" model **(1, 2a, 3a, 4a)**.\n", - "- **Model B** - A hybrid model **(1, 2b, 3b, 4a)**\n", - "- **Model C** - A \"Lei-style\" model **(1, 2b, 3b, 4b)**" - ] - }, - { - "cell_type": "markdown", - "id": "6fdd1973", - "metadata": {}, - "source": [ - "## Simulations\n", - "\n", - "We now run simulations for a single step from 0 to 10 mV, using the parameter values given in [appendix C2](../appendix-c/2-parameter-defaults.ipynb)." - ] - }, - { - "cell_type": "markdown", - "id": "c459d6e5", - "metadata": {}, - "source": [ - "### Model A (1, 2a, 3a, 4a)" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "a9d15cd3", - "metadata": {}, - "outputs": [], - "source": [ - "import myokit\n", - "\n", - "import numpy as np\n", - "import matplotlib.pyplot as plt" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "2ac99d20", - "metadata": {}, - "outputs": [], - "source": [ - "mA = myokit.parse_model('''\n", - "[[model]]\n", - "amp.Vm = -80 [mV]\n", - "amp.Vp = -80 [mV]\n", - "amp.Vo = -80 [mV]\n", - "\n", - "[engine]\n", - "time = 0 [ms] in [ms] bind time\n", - "pace = 0 bind pace\n", - "\n", - "[amp]\n", - "Rs = 15e-3 [GOhm] in [GOhm]\n", - "Cm = 25 [pF] in [pF]\n", - "Cp = 5 [pF] in [pF]\n", - "Rf = 0.5 [GOhm] in [GOhm]\n", - "Cf = 0.15 [pF] in [pF]\n", - "tau_amp = 20e-6 [ms] in [ms]\n", - "I = 5 [nS] * Vm\n", - " in [pA]\n", - "Vc = engine.pace * 1 [mV]\n", - " in [mV]\n", - "dot(Vm) = (Vp - Vm) / (Rs * Cm) - I / Cm : Equation 1\n", - " in [mV]\n", - "dot(Vp) = ((Vo - Vp) / Rf + Cf * dot(Vo) - (Vp - Vm) / Rs) / (Cf + Cp) : Equation 2a\n", - " in [mV]\n", - "dot(Vo) = (Vc - Vp) / tau_amp : Equation 3a\n", - " in [mV]\n", - "I_obs = (Vo - Vc) / Rf : Equation 4a\n", - " in [pA]\n", - "''')\n", - "mA.check_units(myokit.UNIT_STRICT)" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "cc2bcc06", - "metadata": {}, - "outputs": [], - "source": [ - "vlo, vhi = -80, 20\n", - "p = myokit.Protocol()\n", - "p.add_step(level=vlo, duration=5)\n", - "p.add_step(level=vhi, duration=10)\n", - "p.add_step(level=vlo, duration=10)" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "b421a959", - "metadata": {}, - "outputs": [], - "source": [ - "tol = 1e-8\n", - "dt = 5e-5\n", - "\n", - "sA = myokit.Simulation(mA, p)\n", - "sA.set_tolerance(tol, tol)\n", - "sA.pre(5)\n", - "dA = sA.run(20, log_interval=dt).npview()" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "7d193dda", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "kw = dict(color='#aaa', ls='--')\n", - "\n", - "fig = plt.figure(figsize=(15, 4))\n", - "fig.subplots_adjust(wspace=0.3)\n", - "\n", - "ax = fig.add_subplot(1, 3, 1)\n", - "ax.set_ylabel('Vm (mV)')\n", - "ax.axhline(vlo, **kw)\n", - "ax.axhline(vhi, **kw)\n", - "ax.plot(dA.time(), dA['amp.Vm'])\n", - "\n", - "ax = fig.add_subplot(1, 3, 2)\n", - "ax.set_ylabel('Vp (mV)')\n", - "ax.plot(dA.time(), dA['amp.Vp'])\n", - "ax = ax.inset_axes((0.4, 0.15, 0.25, 0.7))\n", - "ax.plot(dA.time(), dA['amp.Vp'])\n", - "ax.set_xlim(4.998, 5.01)\n", - "\n", - "ax = fig.add_subplot(1, 3, 3)\n", - "ax.set_ylabel('I obs (pA)')\n", - "ax.plot(dA.time(), dA['amp.I_obs'])\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "58c4e632", - "metadata": {}, - "source": [ - "### Model B (1, 2b, 3b, 4a)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "16b95491", - "metadata": {}, - "outputs": [], - "source": [ - "mB = myokit.parse_model('''\n", - "[[model]]\n", - "amp.Vm = -80 [mV]\n", - "amp.Vp = -80 [mV]\n", - "amp.Vo = -80 [mV]\n", - "\n", - "[engine]\n", - "time = 0 [ms] in [ms] bind time\n", - "pace = 0 bind pace\n", - "\n", - "[amp]\n", - "Rs = 15e-3 [GOhm] in [GOhm]\n", - "Cm = 25 [pF] in [pF]\n", - "Cp = 5 [pF] in [pF]\n", - "Rf = 0.5 [GOhm] in [GOhm]\n", - "Cf = 0.15 [pF] in [pF]\n", - "tau_amp = 20e-6 [ms] in [ms]\n", - "tau_c = tau_amp * (Cf + Cp) / Cf\n", - " in [ms]\n", - "I = 5 [nS] * Vm\n", - " in [pA]\n", - "Vc = engine.pace * 1 [mV]\n", - " in [mV]\n", - "dot(Vm) = (Vp - Vm) / (Rs * Cm) - I / Cm : Equation 1\n", - " in [mV]\n", - "dot(Vo) = (Vp - Vo) / (Rf * Cf) + (Cp + Cf) / Cf * dot(Vp) + (Vp - Vm) / (Rs * Cf) : Equation 2b\n", - " in [mV]\n", - "dot(Vp) = (Vc - Vp) / tau_c : Equation 3b\n", - " in [mV]\n", - "I_obs = (Vo - Vc) / Rf : Equation 4a\n", - " in [pA]\n", - "''')\n", - "mB.check_units(myokit.UNIT_STRICT)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "02fb78e4", - "metadata": {}, - "outputs": [], - "source": [ - "sB = myokit.Simulation(mB, p)\n", - "sB.set_tolerance(tol, tol)\n", - "sB.pre(5)\n", - "dB = sB.run(20, log_interval=dt).npview()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "1745173b", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(15, 4))\n", - "fig.subplots_adjust(wspace=0.3)\n", - "\n", - "ax = fig.add_subplot(1, 3, 1)\n", - "ax.set_ylabel('Vm (mV)')\n", - "ax.axhline(vlo, **kw)\n", - "ax.axhline(vhi, **kw)\n", - "ax.plot(dA.time(), dA['amp.Vm'], label='Model A')\n", - "ax.plot(dB.time(), dB['amp.Vm'], label='Model B')\n", - "ax.legend()\n", - "\n", - "ax = fig.add_subplot(1, 3, 2)\n", - "ax.set_ylabel('Vp (mV)')\n", - "ax.plot(dA.time(), dA['amp.Vp'], label='Model A')\n", - "ax.plot(dB.time(), dB['amp.Vp'], label='Model B')\n", - "ax = ax.inset_axes((0.4, 0.15, 0.25, 0.7))\n", - "ax.plot(dA.time(), dA['amp.Vp'], label='Model A')\n", - "ax.plot(dB.time(), dB['amp.Vp'], label='Model B')\n", - "ax.set_xlim(4.998, 5.005)\n", - "\n", - "ax = fig.add_subplot(1, 3, 3)\n", - "ax.set_ylabel('I obs (pA)')\n", - "ax.plot(dA.time(), dA['amp.I_obs'], label='Model A')\n", - "ax.plot(dB.time(), dB['amp.I_obs'], label='Model B')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "1f76e9e9", - "metadata": {}, - "source": [ - "Both models make very similar predictions, but we can subtract the two models to see the difference:" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "a04d57cd", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(15, 4))\n", - "fig.subplots_adjust(wspace=0.3)\n", - "ax = fig.add_subplot(1, 3, 1)\n", - "ax.set_ylabel('Vm (mV)')\n", - "ax.plot(dA.time(), dA['amp.Vm'] - dB['amp.Vm'], label='A - B')\n", - "ax.legend()\n", - "ax = fig.add_subplot(1, 3, 2)\n", - "ax.set_ylabel('Vp (mV)')\n", - "ax.plot(dA.time(), dA['amp.Vp'] - dB['amp.Vp'], label='A - B')\n", - "ax = fig.add_subplot(1, 3, 3)\n", - "ax.set_ylabel('I obs (pA)')\n", - "ax.plot(dA.time(), dA['amp.I_obs'] - dB['amp.I_obs'], label='A - B')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "ad12b0fd", - "metadata": {}, - "source": [ - "Although small, the smoothness of these curves and their magnitude is indicative of a true physical difference between the two." - ] - }, - { - "cell_type": "markdown", - "id": "45a1d294", - "metadata": {}, - "source": [ - "### Model C (1, 2b, 3b, 4b)" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "1ec11fa6", - "metadata": {}, - "outputs": [], - "source": [ - "mC = myokit.parse_model('''\n", - "[[model]]\n", - "amp.Vm = -80 [mV]\n", - "amp.Vp = -80 [mV]\n", - "amp.Vo = -80 [mV]\n", - "\n", - "[engine]\n", - "time = 0 [ms] in [ms] bind time\n", - "pace = 0 bind pace\n", - "\n", - "[amp]\n", - "Rs = 15e-3 [GOhm] in [GOhm]\n", - "Cm = 25 [pF] in [pF]\n", - "Cp = 5 [pF] in [pF]\n", - "Rf = 0.5 [GOhm] in [GOhm]\n", - "Cf = 0.15 [pF] in [pF]\n", - "tau_amp = 20e-6 [ms] in [ms]\n", - "tau_c = tau_amp * (Cf + Cp) / Cf\n", - " in [ms]\n", - "I = 5 [nS] * Vm\n", - " in [pA]\n", - "Vc = engine.pace * 1 [mV]\n", - " in [mV]\n", - "dot(Vm) = (Vp - Vm) / (Rs * Cm) - I / Cm : Equation 1\n", - " in [mV]\n", - "dot(Vo) = (Vp - Vo) / (Rf * Cf) + (Cp + Cf) / Cf * dot(Vp) + (Vp - Vm) / (Rs * Cf) : Equation 2b\n", - " in [mV]\n", - "dot(Vp) = (Vc - Vp) / tau_c : Equation 3b\n", - " in [mV]\n", - "I_obs = (Vo - Vp) / Rf : Equation 4b\n", - " in [pA]\n", - "\n", - "''')\n", - "mC.check_units(myokit.UNIT_STRICT)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "9743a5c9", - "metadata": {}, - "outputs": [], - "source": [ - "sC = myokit.Simulation(mC, p)\n", - "sC.set_tolerance(tol, tol)\n", - "sC.pre(5)\n", - "dC = sC.run(20, log_interval=dt).npview()" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "c705e87b", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(15, 4))\n", - "fig.subplots_adjust(wspace=0.3)\n", - "\n", - "ax = fig.add_subplot(1, 3, 1)\n", - "ax.set_ylabel('Vm (mV)')\n", - "ax.axhline(vlo, **kw)\n", - "ax.axhline(vhi, **kw)\n", - "ax.plot(dA.time(), dA['amp.Vm'], label='Model A')\n", - "ax.plot(dB.time(), dB['amp.Vm'], label='Model B')\n", - "ax.plot(dC.time(), dC['amp.Vm'], label='Model C')\n", - "ax.legend()\n", - "\n", - "ax = fig.add_subplot(1, 3, 2)\n", - "ax.set_ylabel('Vp (mV)')\n", - "ax.plot(dA.time(), dA['amp.Vp'], label='Model A')\n", - "ax.plot(dB.time(), dB['amp.Vp'], label='Model B')\n", - "ax.plot(dC.time(), dC['amp.Vp'], '--', label='Model C')\n", - "ax = ax.inset_axes((0.4, 0.15, 0.25, 0.7))\n", - "ax.plot(dA.time(), dA['amp.Vp'], label='Model A')\n", - "ax.plot(dB.time(), dB['amp.Vp'], label='Model B')\n", - "ax.plot(dC.time(), dC['amp.Vp'], '--', label='Model C')\n", - "ax.set_xlim(4.998, 5.01)\n", - "\n", - "ax = fig.add_subplot(1, 3, 3)\n", - "ax.set_ylabel('I obs (pA)')\n", - "ax.plot(dA.time(), dA['amp.I_obs'], label='Model A')\n", - "ax.plot(dB.time(), dB['amp.I_obs'], label='Model B')\n", - "ax.plot(dC.time(), dC['amp.I_obs'], '--', label='Model C')\n", - "ax = ax.inset_axes((0.2, 0.10, 0.45, 0.35))\n", - "ax.plot(dA.time(), dA['amp.I_obs'], label='Model A')\n", - "ax.plot(dB.time(), dB['amp.I_obs'], label='Model B')\n", - "ax.plot(dC.time(), dC['amp.I_obs'], '--', label='Model C')\n", - "ax.set_xlim(4.999, 5.005)\n", - "ax.set_ylim(-1000, 500)\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "70188a91", - "metadata": {}, - "source": [ - "Again, the models look very similar.\n", - "\n", - "At the transitions, we see a slight difference between models A and B and model C:\n", - "In A and B, $V_c$ appears in the equation for $I_\\text{obs}$, and so the output changes instantaneously when $V_c$ does.\n", - "In C we observe $V_o - V_p$, both of which change smoothly." - ] - }, - { - "cell_type": "markdown", - "id": "3c33ed65", - "metadata": {}, - "source": [ - "### Model C: (1, 3b, 5)\n", - "\n", - "Just to check our maths, we can implement a model C using the Lei et al. formulation of (1, 3b, 5)." - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "618d13d0", - "metadata": {}, - "outputs": [], - "source": [ - "mD = myokit.parse_model('''\n", - "[[model]]\n", - "amp.Vm = -80 [mV]\n", - "amp.Vp = -80 [mV]\n", - "amp.I_obs = 0 [pA]\n", - "\n", - "[engine]\n", - "time = 0 [ms] in [ms] bind time\n", - "pace = 0 bind pace\n", - "\n", - "[amp]\n", - "Rs = 15e-3 [GOhm] in [GOhm]\n", - "Cm = 25 [pF] in [pF]\n", - "Cp = 5 [pF] in [pF]\n", - "Rf = 0.5 [GOhm] in [GOhm]\n", - "Cf = 0.15 [pF] in [pF]\n", - "tau_amp = 20e-6 [ms] in [ms]\n", - "tau_c = tau_amp * (Cf + Cp) / Cf\n", - " in [ms]\n", - "I = 5 [nS] * Vm\n", - " in [pA]\n", - "Vc = engine.pace * 1 [mV]\n", - " in [mV]\n", - "dot(Vm) = (Vp - Vm) / (Rs * Cm) - I / Cm : Equation 1 (S2.10)\n", - " in [mV]\n", - "dot(Vp) = (Vc - Vp) / tau_c : Equation 3b (S2.12)\n", - " in [mV]\n", - "dot(I_obs) = (I + Cm * dot(Vm) + Cp * dot(Vp) - I_obs) / (Rf * Cf) : Equation 5 (S2.5 and S2.8)\n", - " in [pA]\n", - "''')\n", - "mD.check_units(myokit.UNIT_STRICT)" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "d6729c21", - "metadata": {}, - "outputs": [], - "source": [ - "sD = myokit.Simulation(mD, p)\n", - "sD.set_tolerance(tol, tol)\n", - "sD.pre(5)\n", - "dD = sD.run(20, log_interval=dt).npview()" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "d0c536f7", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", 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" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(15, 4))\n", - "fig.subplots_adjust(wspace=0.4)\n", - "ax = fig.add_subplot(1, 3, 1)\n", - "ax.set_ylabel('Vm (mV)')\n", - "ax.plot(dC.time(), dC['amp.Vm'] - dD['amp.Vm'], 'k', label='Model C - Model D')\n", - "ax.legend()\n", - "ax = fig.add_subplot(1, 3, 2)\n", - "ax.set_ylabel('Vp (mV)')\n", - "ax.plot(dC.time(), dC['amp.Vp'] - dD['amp.Vp'], 'k')\n", - "ax = ax.inset_axes((0.40, 0.11, 0.5, 0.4))\n", - "ax.plot(dC.time(), dC['amp.Vp'] - dD['amp.Vp'], 'k')\n", - "ax.set_xlim(4.994, 5.05)\n", - "ax = fig.add_subplot(1, 3, 3)\n", - "ax.set_ylabel('I obs (pA)')\n", - "ax.plot(dA.time(), dC['amp.I_obs'] - dD['amp.I_obs'], 'k')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "2065123f", - "metadata": {}, - "source": [ - "A very small error is observed, which fluctuates rapidly.\n", - "This suggests the models are the same and the error is due to small differences in the solver's chosen step sizes.\n", - "\n", - "(Adaptive step size algorithms may be a reason to prefer formulation D over C, as they place the output $I_text{obs}$ under the solver's control, instead of calculating it as a function of two error-controlled variables.)" - ] - }, - { - "cell_type": "markdown", - "id": "86d3be68", - "metadata": {}, - "source": [ - "### Cross-comparison\n", - "\n", - "We can get a closer look at the differences by plotting them explicitly.\n", - "For $V_p$ and $I_\\text{out}$ we'll zoom in on the first few $\\mu$s." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "584780c1", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "xlim = -0.005, 0.05\n", - "\n", - "fig = plt.figure(figsize=(15, 12))\n", - "fig.subplots_adjust(wspace=0.3)\n", - "\n", - "ax11 = fig.add_subplot(3, 3, 1)\n", - "ax11.plot(dA.time(), dA['amp.Vm'] - dB['amp.Vm'], label='Model A - Model B')\n", - "ax21 = fig.add_subplot(3, 3, 4); ax.set_ylabel('Vm (mV)')\n", - "ax21.plot(dA.time(), dA['amp.Vm'] - dC['amp.Vm'], label='Model A - Model C')\n", - "ax31 = fig.add_subplot(3, 3, 7); ax.set_ylabel('Vm (mV)')\n", - "ax31.plot(dB.time(), dB['amp.Vm'] - dC['amp.Vm'], label='Model B - Model C')\n", - "ax12 = fig.add_subplot(3, 3, 2); ax.set_ylabel('Vp (mV)')\n", - "ax12.plot(dA.time(), dA['amp.Vp'] - dB['amp.Vp'], label='Model A - Model B')\n", - "ax22 = fig.add_subplot(3, 3, 5); ax.set_ylabel('Vp (mV)')\n", - "ax22.plot(dA.time(), dA['amp.Vp'] - dC['amp.Vp'], label='Model A - Model C')\n", - "ax32 = fig.add_subplot(3, 3, 8); ax.set_ylabel('Vp (mV)')\n", - "ax32.plot(dB.time(), dB['amp.Vp'] - dC['amp.Vp'], label='Model B - Model C')\n", - "ax13 = fig.add_subplot(3, 3, 3); ax.set_ylabel('I obs (mV)')\n", - "ax13.plot(dA.time(), dA['amp.I_obs'] - dB['amp.I_obs'], label='Model A - Model B')\n", - "ax23 = fig.add_subplot(3, 3, 6); ax.set_ylabel('I obs (mV)')\n", - "ax23.plot(dA.time(), dA['amp.I_obs'] - dC['amp.I_obs'], label='Model A - Model C')\n", - "ax33 = fig.add_subplot(3, 3, 9); ax.set_ylabel('I obs (mV)')\n", - "ax33.plot(dB.time(), dB['amp.I_obs'] - dC['amp.I_obs'], label='Model B - Model C')\n", - "\n", - "for ax in (ax11, ax21, ax31):\n", - " ax.set_ylabel('Vm (mV)')\n", - "for ax in (ax11, ax12, ax13, ax21, ax22, ax23, ax31, ax32, ax33):\n", - " ax.legend()\n", - " \n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "0f81a21d", - "metadata": {}, - "source": [ - "Here, we see that\n", - "\n", - "- There are minor differences between Model A and Models B and C, which are only visible when plotting the difference explicitly.\n", - "- In line with their shared equations, models B and C differ only in their prediction of $I_\\text{obs}$ near discontinuities." - ] - }, - { - "cell_type": "markdown", - "id": "f83e9081", - "metadata": {}, - "source": [ - "## Models A and C with a high parasitic capcitance" - ] - }, - { - "cell_type": "markdown", - "id": "6f369cc7", - "metadata": {}, - "source": [ - "For Model A, we can calculate the damping factor as\n", - "\n", - "\\begin{align}\n", - "\\zeta = \\frac{\\tau_a + R_fC_f}{\\sqrt{\\tau_a R_f (C_p+C_f)}}\n", - "\\end{align}" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "f5705ee7", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Zeta: 10.453782146431431\n" - ] - } - ], - "source": [ - "Rf = 0.5 # GOhm\n", - "Cf = 0.15 # pF\n", - "Cp = 5 # pF (pF * GOhm = ms)\n", - "tau_amp = 20e-6 # ms\n", - "\n", - "zeta = (tau_amp + Rf * Cf) / np.sqrt(tau_amp * Rf * (Cf + Cp))\n", - "# (ms + ms) / sqrt(ms * ms) = dimensionless\n", - "\n", - "print(f'Zeta: {zeta}')" - ] - }, - { - "cell_type": "markdown", - "id": "6123c441", - "metadata": {}, - "source": [ - "This is well above 1, so that the system is stable.\n", - "\n", - "To see differences between the models, we can find an unstable situation.\n", - "For example, in a low-gain mode with $R_f = 5\\text{M}\\Omega$ and $C_p = 10$ pF:" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "3544c88d", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Zeta: 0.7642891671576164\n" - ] - } - ], - "source": [ - "Rf = 0.005\n", - "Cp = 10\n", - "zeta = (tau_amp + Rf * Cf) / np.sqrt(tau_amp * Rf * (Cf + Cp))\n", - "print(f'Zeta: {zeta}')" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "62cd5098", - "metadata": {}, - "outputs": [], - "source": [ - "new_Rf = 0.005\n", - "new_Cp = 10\n", - "sA.set_constant('amp.Cp', new_Cp)\n", - "sA.set_constant('amp.Rf', new_Rf)\n", - "sC.set_constant('amp.Cp', new_Cp)\n", - "sC.set_constant('amp.Rf', new_Rf)\n", - "sA.reset()\n", - "sC.reset()\n", - "dA = sA.run(7, log_interval=dt)\n", - "dC = sC.run(7, log_interval=dt)" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "9cd6ad9f", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(15, 4))\n", - "fig.subplots_adjust(wspace=0.35)\n", - "\n", - "ax = fig.add_subplot(1, 3, 1)\n", - "ax.set_ylabel('Vm (mV)')\n", - "ax.axhline(mA.get('amp.Vm').initial_value().eval(), **kw)\n", - "ax.axhline(mA.get('amp.Vc').eval(), **kw)\n", - "ax.plot(dA.time(), dA['amp.Vm'], label='Model A')\n", - "ax.plot(dC.time(), dC['amp.Vm'], label='Model C')\n", - "ax.legend()\n", - "\n", - "ax = fig.add_subplot(1, 3, 2)\n", - "ax.set_ylabel('Vp (mV)')\n", - "ax.plot(dA.time(), dA['amp.Vp'])\n", - "ax.plot(dC.time(), dC['amp.Vp'])\n", - "ax = ax.inset_axes((0.15, 0.20, 0.5, 0.75))\n", - "ax.plot(dA.time(), dA['amp.Vp'])\n", - "ax.plot(dC.time(), dC['amp.Vp'])\n", - "ax.set_xlim(4.998, 5.02)\n", - "\n", - "ax = fig.add_subplot(1, 3, 3)\n", - "ax.set_ylabel('I obs (pA)')\n", - "ax.plot(dA.time(), dA['amp.I_obs'])\n", - "ax.plot(dC.time(), dC['amp.I_obs'])\n", - "ax = ax.inset_axes((0.25, 0.40, 0.4, 0.55))\n", - "ax.plot(dA.time(), dA['amp.I_obs'])\n", - "ax.plot(dC.time(), dC['amp.I_obs'])\n", - "ax.set_xlim(4.998, 5.02)\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "37187c14", - "metadata": {}, - "source": [ - "Now we see the expected ringing behaviour in Model A, while the simplified equations in Model C show a simpler response." - ] - }, - { - "cell_type": "markdown", - "id": "def45ae4", - "metadata": {}, - "source": [ - "## Conclusions\n", - "\n", - "- Model A, which uses the op-amp equation from Sigworth 1995a, exhibits more complicated dynamics than Models B and C, which are based on a dominant-pole approximation of Model A.\n", - "- Model B is a Model A variant with an alternative op-amp equation.\n", - "- Model C can be formulated as a Model B variant with $V_\\text{out} = V_o - V_p$.\n", - "- When using the default settings, the differences between the models appear neglible.\n", - "- Model A can be made to show unstable ringing behaviour." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.11" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/tutorial/appendix-b/README.md b/tutorial/appendix-b/README.md deleted file mode 100644 index 3c3743e..0000000 --- a/tutorial/appendix-b/README.md +++ /dev/null @@ -1,6 +0,0 @@ -# Appendix B: Extended models - -1. Models without compensation [![github](../img/github.svg)](1-uncompensated-models.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/appendix-b/1-uncompensated-models.ipynb) -2. Sigworth 1983/1995 Rs compensation [![github](../img/github.svg)](2-sigworth-rs.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/appendix-b/2-sigworth-rs.ipynb) - -[↩ Back to the tutorial index](../README.md) diff --git a/tutorial/appendix-c/2-parameter-defaults.ipynb b/tutorial/appendix-c/2-parameter-defaults.ipynb deleted file mode 100644 index 4fce183..0000000 --- a/tutorial/appendix-c/2-parameter-defaults.ipynb +++ /dev/null @@ -1,95 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "fc24dbb4", - "metadata": {}, - "source": [ - "# Appendix C2: Default parameter values\n", - "**Appendix C discusses variable names and values**" - ] - }, - { - "cell_type": "markdown", - "id": "e184af6f", - "metadata": {}, - "source": [ - "Here we present the \"default\" values used in these notebooks.\n", - "Other choices are possible." - ] - }, - { - "cell_type": "markdown", - "id": "3e6bd67d", - "metadata": {}, - "source": [ - "## Basic model\n", - "\n", - "| Parameter | Value | Motivation |\n", - "|:----------|:--------------|:-------------------------------------------------------------|\n", - "| $R_s$ | 5 M$\\Omega$ | A 3$\\Omega$ pipette with an additional 2$\\Omega$ at the seal |\n", - "| $C_m$ | 25 pF | A small cell such as a HEK or CHO cell |\n", - "| $C_p$ | 5 pF | Based on own experience |\n", - "| $R_f$ | 0.5 G$\\Omega$ | Similar to HEKA, Axon, and Sutter |\n", - "| $C_f$ | 0.15 pF | Similar to HEKA |\n", - "| $\\tau_a$ | 13e-6 ms | Fit to data |\n", - "\n", - "Values are rounded to reflect uncertainty in the true values.7" - ] - }, - { - "cell_type": "markdown", - "id": "482bff5f", - "metadata": {}, - "source": [ - "## Model with compensation\n", - "\n", - "\n", - "| Parameter | Value | Motivation |\n", - "|:-----------------|:----------|:--------------------------|\n", - "| $\\tilde{C}_f$ | 5e-3 pF | Fit to data |\n", - "| $\\alpha$ | 0.7 | Typical setting |\n", - "| $\\beta$ | 0.7 | Typical setting |\n", - "| $\\tau_\\text{RC}$ | 0.01 ms | Default for HEKA and Axon |\n", - "\n", - "Estimates for $R_s$, $C_m$, and $C_p$ are set at or near their true values" - ] - }, - { - "cell_type": "markdown", - "id": "92f0e461", - "metadata": {}, - "source": [ - "## Filter settings\n", - "\n", - "| Parameter | Value | Meaning | Motivation |\n", - "|:--------------|:---------|:-------------------------------------|-----------------|\n", - "| $\\tau_s$ slow | 0.025 ms | Stimulus filter time constant \"20us\" | Fit to data |\n", - "| $\\tau_s$ fast | 0.003 ms | Stimulus filter time constant \"2us\" | Fit to data |\n", - "| $f_{c1}$ | 10 kHz | F1 cut-off frequency | Typical setting |\n", - "| $f_{c2}$ | 10 kHz | F2 cut-off frequency | Typical setting |" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.9" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/tutorial/appendix-c/README.md b/tutorial/appendix-c/README.md deleted file mode 100644 index 1f528bf..0000000 --- a/tutorial/appendix-c/README.md +++ /dev/null @@ -1,7 +0,0 @@ -# Appendix C: Parameter names and values - -1. Names & symbols [![github](../img/github.svg)](1-symbols.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/appendix-c/1-symbols.ipynb) -2. Default parameter values used in examples [![github](../img/github.svg)](2-parameter-defaults.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/appendix-c/2-parameter-defaults.ipynb) -3. Parameter values, estimates for different amplifiers etc. [![github](../img/github.svg)](3-parameter-values.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/appendix-c/3-parameter-values.ipynb) - -[↩ Back to the tutorial index](../README.md) diff --git a/tutorial/appendix-d/1-strategies.ipynb b/tutorial/appendix-d/1-strategies.ipynb deleted file mode 100644 index d01d516..0000000 --- a/tutorial/appendix-d/1-strategies.ipynb +++ /dev/null @@ -1,134 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Appendix D1: Strategies for dealing with experimental error\n", - "**Appendix D discusses remaining noise and errors**" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this notebook we provide a high-level overview of noise, artefacts, and imperfect control, and discuss general strategies for dealing with them." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Noise and artefacts\n", - "\n", - "The term \"noise\" can mean many things, but in patch-clamp experiments is typically used to mean unwanted _stochastic_ or _periodic_ signals that are present in the applied input, the measured output, or both.\n", - "The term \"artefacts\" (or \"artifacts\") is sometimes used to describe _transient_ signals that appear in the output but are due to the experimental setup rather than the biology." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Imperfect control\n", - "\n", - "Many artefacts in patch clamp data arise not as a distortion of the recorded signal, but through _imperfect control_ of the membrane potential.\n", - "A major part of the \"artefact model\" described here deals with such issues of imperfect membrane potential control.\n", - "\n", - "More generally, we have imperfect control over experimental parameters such as as temperature (often quoted as being in a 1-2 degree bracket) or external solutions (especially with e.g. fast wash-out or wash-in).\n", - "This type of imperfect control can often be modelled by replacing scalar values with probability distributions and using [forward propagation](https://en.wikipedia.org/wiki/Uncertainty_quantification#Forward_propagation) to estimate the effects on the measured signal." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Strategies for dealing with error\n", - "\n", - "Four strategies for dealing with noise, artefacts, and imperfect control are:\n", - "\n", - "- Avoiding it\n", - "- On-line correction, i.e. correcting during the experiment using hardware or software\n", - "- Off-line correction, i.e. post-processing the data to remove errors\n", - "- Creating a noise model\n", - "\n", - "**Avoiding noise** is a major part of experimental setup and hardware design, and can include [shielding](https://en.wikipedia.org/wiki/Faraday_cage), removing sources of electronic inference (e.g. monitors, lights), using special power supplies (or batteries), checking for [ground loops](https://en.wikipedia.org/wiki/Ground_loop_%28electricity%29), and even cooling part of the measurement equipment to reduce [thermal noise](https://en.wikipedia.org/wiki/Johnson%E2%80%93Nyquist_noise).\n", - "\n", - "**On-line correction** using hardware filters is common in patch-clamp experiments, and includes correction of capacitance artefacts, series resistance compensation, \"zeroing\" the current, and low-pass filtering.\n", - "A major downside of on-line correction is that it can only be performed once.\n", - "In addition, some patch-clamp hardware does not provide digital readouts of the controls used to perform on-line correction, so that information about how exactly the signal was modulated is lost.\n", - "\n", - "**Off-line correction** includes leak correction and removal of any remaining capacitance artefacts, but may also include removing endogenous currents by subtracting a second measurement made in the presence of a current-blocking drug.\n", - "A downside of both on-line and off-line correction is that it invariably \"complicates\" the recording.\n", - "For example, to fully model a typical patch-clamp measurement it would be necessary to understand the ionic current, the way the cell and patch-clamp setup contaminate this recording, and the precise way in which hardware and offline software has attempted to remedy these effects.\n", - "\n", - "A different approach then, is to simply leave the noise and artefacts in, and **add them to the model used in the fitting procedure**.\n", - "The most common example of \"modelling\" the noise, is using a root-mean-squared error when fitting the data: statistically this equates to assuming a Gaussian model for the noise (so that the recorded current at any time point equals the ionic current plus a normally distributed random variable).\n", - "More complex modelling approaches are also possible, see for example [Lei et al., 2020](https://royalsocietypublishing.org/doi/10.1098/rsta.2019.0348) and the models introduced in these notebooks." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Modelling experimental error\n", - "\n", - "A central idea in these notebook is to differentiate between the measured current, $I_\\text{measured}$, and the current of interest, which we shall call $I_\\text{ion}$.\n", - "The relationship between $I_\\text{measured}$ and $I_\\text{ion}$ can be captured mathematically in a _noise model_:\n", - "\n", - "\\begin{equation}\n", - "I_\\text{measured} = f(I_\\text{ion})\n", - "\\end{equation}\n", - "\n", - "The simplest such noise models are _additive_, and take the form\n", - "\n", - "\\begin{equation}\n", - "I_\\text{measured} = I_\\text{ion} + I_\\text{unwanted}\n", - "\\end{equation}\n", - "\n", - "But we have also seen more complicated forms.\n", - "\n", - "Similarly, we can model imperfect control by distinguishing between the true membrane potential, $V_m$, and the intended membrane potential $V_\\text{command}$:\n", - "\\begin{equation}\n", - "V_\\text{m} = g \\left( V_\\text{command} \\right)\n", - "\\end{equation}\n", - "but we also have to recognise that the error in the control depends on the ion current:\n", - "\\begin{equation}\n", - "V_\\text{m} = g \\left( V_\\text{command}, I_\\text{ion} \\right)\n", - "\\end{equation}\n", - "If we allow for clever circuitry that uses measurements of $I_\\text{ion}$ or $V_\\text{m}$ to perform corrections, we may even want to write\n", - "\\begin{equation}\n", - "V_\\text{m} = g \\left( V_\\text{command}, I_\\text{ion}, I_\\text{measured}, V_\\text{measured} \\right)\n", - "\\end{equation}\n", - "\n", - "so that our full equation becomes something like\n", - "\n", - "\\begin{equation}\n", - "I_\\text{measured} = f \\left( I_\\text{ion}(g(V_\\text{command}, I_\\text{ion}, I_\\text{measured}, V_\\text{measured})) \\right)\n", - "\\end{equation}\n", - "\n", - "Clearly we will need some kind of simulation to deal with this." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.11.6" - } - }, - "nbformat": 4, - "nbformat_minor": 2 -} diff --git a/tutorial/appendix-d/2-inspecting-noise.ipynb b/tutorial/appendix-d/2-inspecting-noise.ipynb deleted file mode 100644 index e71032e..0000000 --- a/tutorial/appendix-d/2-inspecting-noise.ipynb +++ /dev/null @@ -1,910 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Appendix D2: Stochastic and periodic noise\n", - "**Appendix D discusses remaining noise and errors**" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In this notebook we take a brief look at stochastic noise.\n", - "This type of noise is a _much bigger issue_ for single channel measurements, and much more thorough explorations of noise can be found e.g. in [Sigworth 1995](https://doi.org/10.1007/978-1-4419-1229-9_4), [Benndorf 1995](https://doi.org/10.1007/978-1-4419-1229-9_5), or the [Axon Guide](https://www.moleculardevices.com/en/assets/ebook/dd/cns/axon-guide-to-electrophysiology-and-biophysics-laboratory-techniques).\n", - "\n", - "Reducing noise is also a major point of interest, but will not be discussed in this notebook.\n", - "Instead, we have a quick look at the stochastic and periodic noise we might see in a manual whole-cell patch experiment, and discuss how this relates to uncertainty quantification." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Stochastic noise\n", - "\n", - "We'll start by looking at stochastic noise, using the model:\n", - "\n", - "\\begin{equation}\n", - "I_\\text{measured} = I_\\text{ion} + I_\\text{stochastic} = I_\\text{ion} + \\mathcal{N}(0, \\sigma)\n", - "\\end{equation}\n", - "\n", - "This assumes that\n", - "- the noise is purely _additive_, and does not affect $I_\\text{ion}$ or $I_\\text{measured}$ in more complicated ways.\n", - "- the noise in sample $I_\\text{measured}[i]$ is independent of the noise at $I_\\text{measured}[i-1]$, or at any previous sample $I_\\text{measured}[j < i]$.\n", - "- the noise follows a normal distribution with mean zero and a constant standard deviation $\\sigma$.\n", - "\n", - "This model can be used for noise that is truly stochastic, but perhaps also for processes that change quickly enough to _look_ stochastic, given our sampling rate.\n", - "Noise that _more or less_ matches these assumptions can arise from from the electronics e.g. [thermal noise](https://en.wikipedia.org/wiki/Johnson%E2%80%93Nyquist_noise), and [shot noise](https://en.wikipedia.org/wiki/Shot_noise).\n", - "We can even expect some fluctuations from the stochastic opening and closing of the channels themselves: a 1973 paper by [Anderson and Stevens](https://doi.org/10.1113/jphysiol.1973.sp010410) showed that \"channel noise\" with a high enough amplitude can be analysed to estimate the number of channels in a cell.\n", - "\n", - "It can be worthwhile to examine these assumptions, for example by looking at a \"boring\" part of an experimental result, where the voltage is stable and the channels are assumed to be in or near their steady state." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import matplotlib.pyplot as plt\n", - "import myokit\n", - "import numpy as np\n", - "import pints\n", - "import scipy.stats\n", - "\n", - "# Load Cell 1 from Beattie et al.\n", - "log = myokit.DataLog.load('./res/sine-wave-data/cell-1.zip').npview()\n", - "\n", - "# Isolate a \"flat\" bit of signal, by chopping off everything after t=250\n", - "# During this time, V is fixed at -80mV\n", - "log = log.trim_right(250)\n", - "\n", - "plt.figure(figsize=(8, 3))\n", - "plt.xlabel('Time (ms)')\n", - "plt.ylabel('Current (pA)')\n", - "plt.plot(log.time(), log['current'] * 1000) # Convert from nA to pA\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can try and visually inspect this data, for example to see how it compares to a normal distribution:" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Subtract the mean and show a histogram of this noise:\n", - "\n", - "noise = log['current'] * 1000 # Convert from nA to pA\n", - "offset = np.mean(noise)\n", - "variation = noise - offset\n", - "\n", - "fig = plt.figure(figsize=(16, 3))\n", - "ax = fig.add_subplot(1, 2, 1)\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.set_ylabel('Mean noise (pA)')\n", - "ax.plot(log.time(), np.ones(noise.shape) * offset)\n", - "\n", - "ax = fig.add_subplot(1, 2, 2)\n", - "ax.set_xlabel('Noise amplitude (pA)')\n", - "ax.set_ylabel('Occurence')\n", - "ax.hist(variation, bins=50, density=True, label='Normalised histogram')\n", - "\n", - "x = np.linspace(-25, 25, 100)\n", - "ax.plot(x, scipy.stats.norm.pdf(x, 0, np.std(variation)), label='Normal distribution')\n", - "ax.legend()\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "So the data _looks_ to be normally distributed, although not with a zero offset (more about that later).\n", - "More rigorous tests of normality are available, but for large sample sizes like these, they tend to be _too strict_, and reject the hypothesis that the distribution is normal, for even very minor deviations from normality.\n", - "\n", - "Another thing we can investigate is whether the noise in this cell was [_independent and identically distributed_ (iid)](https://en.wikipedia.org/wiki/Independent_and_identically_distributed_random_variables).\n", - "A quick visual way to do this is to make a plot of the _autocorrelation_, which shows you how much the points at any index $i$ correlate with the points at $i - \\text{lag}$.\n", - "For $\\text{lag} = 0$ this is $1$ by definition, but for higher lags this should be close to zero if the noise is iid.\n", - "One rule of thumb is to plot the lines at $\\pm1.96 \\sqrt{n}$, which corresponds to the 95% confidence interval, and then check that only 5% of the autocorrelations are outside this interval." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import pints.plot\n", - "\n", - "# pints.plot.autocorrelation expects an array of shape (n_samples, n_parameters)\n", - "# See: https://pints.readthedocs.io/en/latest/diagnostic_plots.html#pints.plot.autocorrelation\n", - "n = len(variation)\n", - "reshaped = variation.reshape((n, 1))\n", - "\n", - "fig, ax = pints.plot.autocorrelation(reshaped, max_lags=30)\n", - "fig.set_size_inches(12, 5)\n", - "ax[0].axhline(+1.96 / np.sqrt(n), ls='--', color='#cccccc')\n", - "ax[0].axhline(-1.96 / np.sqrt(n), ls='--', color='#cccccc')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "So it looks like our noise is fairly independent!" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now that we now this, how it help us deal with noise?\n", - "Because the noise is stochastic, we can't model it directly and subtract it from our recordings.\n", - "But we _can_ write a statistical model for our noise, and fit that to the data.\n", - "\n", - "First, we assume that at any point intime the measured current $I_\\text{measured}(t)$ can be modelled as the sum of a current model $m(t|p)$ with parameters $p$ and a random variable from a normal distribution with standard deviation $\\sigma$:\n", - "\n", - "\\begin{equation}\n", - "I_\\text{measured}(t) = m(t|p) + \\mathcal{N}(0, \\sigma)\n", - "\\end{equation}\n", - "\n", - "In the [\"basic fitting\"](basic-fitting.ipynb) notebook, we saw that this lets us write a _probability density function_ $f$ for obtaining a certain measurement _given_ a fixed $p$ and $\\sigma$, and that this could be used to define a _log-likelhood_ for $p$ and $\\sigma$ given a particular measurement $D$:\n", - "\n", - "\\begin{equation}\n", - "\\log l(p, \\sigma|D) = -\\frac{N}{2}\\log(2\\pi) - N\\log(\\sigma) - \\frac{1}{2\\sigma^2} \\sum_{i = 1}^{N} \\left(I_\\text{measured}(t_i) - m(t_i|p)\\right)^2\n", - "\\end{equation}\n", - "\n", - "where $D$ is a digitised set of measurements $D = \\{(t_1, I_\\text{measured}(t_1)), (t_2, I_\\text{measured}(t_2)), ..., (t_N, I_\\text{measured}(t_N))\\}$.\n", - "\n", - "In the basic fitting tutorial we observed that for a fixed value of $\\sigma$ the process of _maximising this log-likelihood_ is the same as _minimising the sum of squared errors_ $I_\\text{measured}(t_i) - m(t_i|p)$, and we proceeded using this approach in most of the tutorial.\n", - "\n", - "However, instead of passing in an [ErrorMeasure](https://pints.readthedocs.io/en/latest/error_measures.html), PINTS optimisers can also operate directly on a [LogLikelihood object](https://pints.readthedocs.io/en/latest/log_likelihoods.html):" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [], - "source": [ - "import myokit.lib.hh\n", - "\n", - "class ModelHHSolver(pints.ForwardModel):\n", - " \"\"\"\n", - " A forward model that runs simulations on step protocols, using an\n", - " analytical solving method for Hodgkin-Huxley models.\n", - " \"\"\"\n", - "\n", - " def __init__(self, protocol):\n", - "\n", - " # Load a model, and isolate the HH ion current model part\n", - " model = myokit.load_model('./res/beattie-2017-ikr-hh.mmt')\n", - " parameters = ['ikr.p' + str(1 + i) for i in range(9)]\n", - " hh_model = myokit.lib.hh.HHModel.from_component(\n", - " model.get('ikr'), parameters=parameters)\n", - "\n", - " # Create an analytical simulation\n", - " self.sim = myokit.lib.hh.AnalyticalSimulation(hh_model, protocol)\n", - "\n", - " # Set the -80mV steady state as the default state\n", - " self.sim.set_default_state(hh_model.steady_state(-80))\n", - "\n", - " def n_parameters(self):\n", - " return 9\n", - "\n", - " def simulate(self, parameters, times):\n", - "\n", - " # Reset, apply parameters, and run\n", - " self.sim.reset()\n", - " self.sim.set_parameters(parameters)\n", - " tmax = times[-1] + (times[-1] - times[-2])\n", - " log = self.sim.run(tmax, log_times=times)\n", - " return log['ikr.IKr']" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Set up a simple fitting problem\n", - "parameters = np.array([3e-4, 0.07, 3e-5, 0.05, 0.09, 9e-2, 5e-3, 0.03, 0.2])\n", - "\n", - "protocol = myokit.load_protocol('./res/simplified-staircase.mmt')\n", - "model = ModelHHSolver(protocol)\n", - "times = np.arange(0, 15400, 0.1)\n", - "values = model.simulate(parameters, times)\n", - "values += np.random.normal(0, 0.05, times.shape)\n", - "problem = pints.SingleOutputProblem(model, times, values)\n", - "\n", - "plt.figure(figsize=(16, 3))\n", - "plt.xlabel('Time (ms)')\n", - "plt.ylabel('Current (pA)')\n", - "plt.plot(times, values, label='Noisy (fake) data')\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Next, we isolate a bit of noise from the start of the signal to estimate sigma:" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Estimated sigma: 0.05080936417687858\n" - ] - } - ], - "source": [ - "noise = values[:1000]\n", - "sigma = np.std(noise)\n", - "print('Estimated sigma: ' + str(sigma))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "And we use this to create and maximise a [pints.GaussianKnownSigmaLogLikelihood](https://pints.readthedocs.io/en/latest/log_likelihoods.html#pints.GaussianKnownSigmaLogLikelihood):" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [], - "source": [ - "# Create a log-likelihood object\n", - "log_pdf = pints.GaussianKnownSigmaLogLikelihood(problem, sigma)\n", - "\n", - "# Choose a slightly random starting point\n", - "x0 = parameters * 2**np.random.normal(0, 0.25, parameters.shape)\n", - "\n", - "# Use an optimiser to maximise it\n", - "opt = pints.OptimisationController(log_pdf, x0)\n", - "opt.set_log_to_screen(False)\n", - "xopt, fopt = opt.run()" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "plt.figure(figsize=(16, 4))\n", - "plt.xlabel('Time (ms)')\n", - "plt.ylabel('Current (pA)')\n", - "plt.plot(times, values, label='Noisy (fake) data')\n", - "plt.plot(times, problem.evaluate(xopt), label='Fitted model')\n", - "plt.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Here we followed a two-step process, first estimating sigma from a small chunk of the data and then using this estimate to do the full fit.\n", - "But there's nothing stopping us from inferring $\\sigma$ along with the rest of the parameters!" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "9\n", - "10\n" - ] - } - ], - "source": [ - "# Create an unknown sigma log-likelihood object\n", - "log_pdf = pints.GaussianLogLikelihood(problem)\n", - "\n", - "# This log likelihood has one more parameter than our model!\n", - "print(model.n_parameters())\n", - "print(log_pdf.n_parameters())" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "As before, we can use an optimiser to maximise this log-likelihood, but now we need to pass in a starting point that also includes an estimate for sigma:" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": {}, - "outputs": [], - "source": [ - "x0_with_sigma = np.concatenate((x0, [0.3]))\n", - "\n", - "opt = pints.OptimisationController(log_pdf, x0_with_sigma)\n", - "opt.set_log_to_screen(False)\n", - "xopt, fopt = opt.run()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now the returned parameter vector includes an extra value for the estimated sigma:" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Estimated sigma: 0.04993591434653721\n" - ] - } - ], - "source": [ - "print('Estimated sigma: ' + str(xopt[-1]))" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This probabilistic approach opens up new possibilities for investigation.\n", - "For example, we could replace the assumption of iid noise with the assumption that the noise is correlated and would be better described by an [Autoregressive AR1 model](https://en.wikipedia.org/wiki/Autoregressive_model).\n", - "We can then replace our Gaussian loglikelihood by a [pints.AR1LogLikelihood](https://pints.readthedocs.io/en/latest/log_likelihoods.html#pints.AR1LogLikelihood) and compare the quality of fit.\n", - "\n", - "Instead of finding the maximum of the proposed likelihood function, we can also use [sampling methods](https://pints.readthedocs.io/en/latest/mcmc_samplers/index.html) to explore the full distribution.\n", - "If the model fits the data extremely well, this can provide an estimate of the uncertainty in the obtained parameters.\n", - "However, if there is a slight _discrepancy_ between the final model predictions and the experimental recording (as is typically the case in ion current electrophysiology), the results of applying a sampling method are much harder to interpret." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Periodic noise" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In addition to stochastic (additive) noise, we might also look for periodic noise.\n", - "An easy way to spot this is by creating and plotting an [FFT](https://en.wikipedia.org/wiki/Fast_Fourier_transform) or [power spectrum](https://en.wikipedia.org/wiki/Spectral_density).\n", - "\n", - "We start by defining a quick function to calculate a power spectrum:" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "metadata": {}, - "outputs": [], - "source": [ - "def spectrum( times, current):\n", - " \"\"\"\n", - " Calculates the power spectrum (or spectral density) of a (regularly spaced)\n", - " time series ``(times, current)``, and returns a tuple ``(freq, power)``\n", - " where ``freq`` contains a list of positive frequencies, and ``power``\n", - " is the associated spectral density (if current is in \"units\", the power will\n", - " be unit \"units**2\").\n", - " \"\"\"\n", - " # Import fft functions\n", - " try:\n", - " # Latest scipy\n", - " from scipy.fft import fft, fftshift, fftfreq\n", - " except ImportError:\n", - " from scipy.fftpack import fft, fftshift, fftfreq\n", - " \n", - " # Length of time series (assuming len(times) == len(current))\n", - " n = len(times)\n", - " \n", - " # Time-step (assuming points are equally spaced)\n", - " dt = times[1] - times[0]\n", - " \n", - " # Points in the FFT\n", - " points = fftshift(fft(current)).real\n", - " \n", - " # Frequency of points in the fft\n", - " frequency = fftshift(fftfreq(n, dt))\n", - " \n", - " # Select positive points\n", - " positive = frequency > 0\n", - " \n", - " return frequency[positive], points[positive]**2\n" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Using this function, we can have a look at the start of Cell 1's data again:" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Load Cell 1 from Beattie et al.\n", - "log = myokit.DataLog.load('./res/sine-wave-data/cell-1.zip').npview()\n", - "\n", - "# Isolate a \"flat\" bit of signal, by chopping off everything after t=250\n", - "# During this time, V is fixed at -80mV\n", - "log = log.trim_right(250)\n", - "\n", - "# Calculate the power spectrum\n", - "times = log.time()\n", - "current = log['current']\n", - "freq, points = spectrum(times * 1e-3, current) # Using time in seconds to get frequency in Hz\n", - "\n", - "# Show the results\n", - "fig = plt.figure(figsize=(16, 4))\n", - "\n", - "ax = fig.add_subplot(1, 2, 1)\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.set_ylabel('Current (pA)')\n", - "ax.plot(times, current * 1e3) # Convert from nA to pA\n", - "\n", - "ax = fig.add_subplot(1, 2, 2)\n", - "ax.set_xlabel('Frequency (Hz)')\n", - "ax.set_ylabel('Spectral density (nA^2)')\n", - "ax.plot(freq, points)\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "So it looks like there's no particular frequencies that dominate the noise in this recording.\n", - "\n", - "Because we recorded at a sample spacing of $0.1\\text{ms} = 10^{-4}\\text{s}$, the highest frequency observable in the signal is half the sampling rate, so $\\frac{1}{2} 1 / 10^{-4}\\text{s} = \\frac{1}{2} 10\\text{kHz} = 5\\text{kHz}$.\n", - "Notice that the [Nyquist-Shannon sampling theory](https://en.wikipedia.org/wiki/Nyquist%E2%80%93Shannon_sampling_theorem) says something stronger than that; it says that _even lower frequency signals_ can't be reconstructed from a digital recording if frequencies higher than half the sampling rate are present in the signal.\n", - "A common way to ensure this is the case, is to use low-pass filtering before digitisation (so this is an example of online filtering that we cannot escape!).\n", - "Looking at the [published raw data files](https://figshare.com/articles/Sinusoidal_voltage_protocols_for_rapid_characterization_of_ion_channel_kinetics_supplementary_experimental_data/4702546/1) for this study, we can inspect the meta data (e.g. using [Myokit's DataLog viewer](https://myokit.readthedocs.io/cmd/log.html)) and see that this signal was indeed low-pass filtered at 5kHz before digitisation." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now let's look at a different recording:" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Load Cell 7 from Beattie et al.\n", - "log = myokit.DataLog.load('./res/sine-wave-data/cell-7.zip').npview()\n", - "\n", - "# Isolate a \"flat\" bit of signal, by chopping off everything after t=250\n", - "# During this time, V is fixed at -80mV\n", - "log = log.trim_right(250)\n", - "\n", - "# Calculate the power spectrum\n", - "times = log.time()\n", - "current = log['current']\n", - "freq, points = spectrum(times * 1e-3, current) # Using time in seconds to get frequency in Hz\n", - "\n", - "# Show the results\n", - "fig = plt.figure(figsize=(16, 4))\n", - "\n", - "ax = fig.add_subplot(1, 2, 1)\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.set_ylabel('Current (pA)')\n", - "ax.plot(times, current * 1e3) # Convert from nA to pA\n", - "\n", - "ax = fig.add_subplot(1, 2, 2)\n", - "ax.set_xlabel('Frequency (Hz)')\n", - "ax.set_ylabel('Spectral density (nA^2)')\n", - "ax.plot(freq, points)\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "This shows some very different characteristics!\n", - "\n", - "In the power spectrum plot on the right, we can clearly see two peaks around $3.2 \\text{kHz}$.\n", - "These are most likely from some piece of electronic equipment in the same room or, if the noise is transmitted through the mains or the grounding, somewhere else in the building!\n", - "\n", - "In the direct plot on the left, we can also see what look like some lower frequency periodic effects.\n", - "We can do a few zoomed plots to get a clearer picture:" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(16, 4))\n", - "\n", - "ax = fig.add_subplot(1, 2, 1)\n", - "ax.set_xlabel('Frequency (Hz)')\n", - "ax.set_ylabel('Spectral density (nA^2)')\n", - "ax.plot(freq, points)\n", - "ax.set_xlim(0, 200)\n", - "ax.set_ylim(0, 20)\n", - "ax.set_xticks(np.arange(0, 210, 10))\n", - "ax.grid(True)\n", - "\n", - "ax = fig.add_subplot(1, 2, 2)\n", - "ax.set_xlabel('Frequency (Hz)')\n", - "ax.set_ylabel('Spectral density (nA^2)')\n", - "ax.plot(freq, points)\n", - "ax.set_xlim(3060, 3240)\n", - "ax.set_xticks(np.arange(3060, 3260, 20))\n", - "ax.grid(True)\n", - "\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Starting on the right again, we see two large peaks at around $3115 \\text{Hz}$ and $3170 \\text{Hz}$.\n", - "If we assume this noise is from something man-made, we might expect the frequencies to be nice round numbers, so it can be worth googling our frequency estimates to see if anyone knows what's causing them!\n", - "Judging from the fact that we see these clear signals in cell 7, but not cell 1, we might suspect it's something that gets switched on and off during the day, but it could also come from something like a fridge which switches itself on from time to time.\n", - "\n", - "On the left, we see a peak of unknown origins at $10 \\text{Hz}$, but also one at $50 \\text{Hz}$, which is a clear example of [\"mains hum\"](https://en.wikipedia.org/wiki/Mains_hum)." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "So how do we use this knowledge?\n", - "\n", - "One option, especially when the peaks are as sharp as shown above, is to digitally filter out one of the frequencies.\n", - "We could also try fitting sine waves and subtracting them from the signal, or including the sine waves in our (noise) model.\n", - "But we could also observe that the strongest peaks are of a much higher frequency than what we expect from the current of interest, and that the lower frequency peaks are quite small.\n", - "So it might be fine to just leave the noise in, avoiding the risk of our \"corrections\" making things worse, and to present the data to our optimisation routine as-is.\n", - "Zooming out and observing the whole signal, this doesn't seem too bad an idea, and indeed this is the approach we took in e.g. [Four ways to fit an ion channel model](https://doi.org/10.1016/j.bpj.2019.08.001)." - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# The full signal for cell 7\n", - "fig = plt.figure(figsize=(16, 4))\n", - "ax = fig.add_subplot(1, 1, 1)\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.set_ylabel('Current (pA)')\n", - "ax.plot(log.time(), log['current'] * 1e3)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "## Uncertainty quantification and model discrepancy\n", - "\n", - "It's quite tempting to use noise models as shown above to defined a likelihood function, explore it with uncertainty quantification (UQ) methods such as [MCMC](https://en.wikipedia.org/wiki/Markov_chain_Monte_Carlo), _and then to interpret the result as information about the certainty of our inferred parameters_.\n", - "\n", - "This works well if there is no _model discrepancy_. In other words, if the model is able to draw a line through the data perfectly, such that all deviations from this line can be attributed to stochastic (or periodic) noise, then we can use UQ to investigate the uncertainty in our parameter estimates due to that noise.\n", - "\n", - "However, in many cases the mismatch between the best-fit model and the data does not look like it was generated by an additive stochastic (or periodic) noise model.\n", - "To illustrate this, we look at the Cell 1 data again, and superimpose a simulated result with parameters obtained from a fitting experiment." - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "metadata": {}, - "outputs": [], - "source": [ - "# Load Cell 1 from Beattie et al.\n", - "log = myokit.DataLog.load('./res/sine-wave-data/cell-1.zip').npview()" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "metadata": {}, - "outputs": [], - "source": [ - "# Load the model\n", - "model = myokit.load_model('./res/beattie-2017-ikr-hh.mmt')\n", - "\n", - "# Load the steps in the sine wave protocol\n", - "protocol = myokit.load_protocol('./res/sine-wave-steps.mmt')\n", - "\n", - "# Update the model to add in sine waves\n", - "c = model.get('membrane')\n", - "v = c.get('V')\n", - "v.set_binding(None)\n", - "vp = c.add_variable('vp')\n", - "vp.set_rhs(0)\n", - "vp.set_binding('pace')\n", - "model.get('membrane.V').set_rhs(\n", - " 'if(engine.time >= 3000.1 and engine.time < 6500.1,'\n", - " + ' - 30'\n", - " + ' + 54 * sin(0.007 * (engine.time - 2500.1))'\n", - " + ' + 26 * sin(0.037 * (engine.time - 2500.1))'\n", - " + ' + 10 * sin(0.190 * (engine.time - 2500.1))'\n", - " + ', vp)')\n", - "\n", - "# Create simulation\n", - "sim = myokit.Simulation(model, protocol)" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "metadata": {}, - "outputs": [], - "source": [ - "# Simulate using the parameters from Beattie et al.\n", - "p = {\n", - " 'ikr.p1': 1.98e-4,\n", - " 'ikr.p2': 0.0593,\n", - " 'ikr.p3': 7.1688e-5,\n", - " 'ikr.p5': 0.0493,\n", - " 'ikr.p5': 0.1048,\n", - " 'ikr.p6': 0.0139,\n", - " 'ikr.p7': 0.0038,\n", - " 'ikr.p8': 0.036,\n", - " 'ikr.p9': 0.1351, \n", - "}\n", - "for k, v in p.items():\n", - " sim.set_constant(k, v)\n", - "d = sim.run(8001, log_times=log.time())" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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SsfeW6jTrzwN6b1GS3hvZTaEB9kqf56Nft+tzv6cUrkwF1l/q1RprOu5ngMqrUOhotVo1cOBAbdy4kdARNQb/SQDeUfRTXpOBNyiH2t5TrLbak5qlejqkMbZpkiRnXHtt339Ui53tdPnof5XvJH7Bir7uLZnT7pBpC1DT6z+V7IH62dFN19t+0SDLcg2wrlaMkaaH82+XVL4gqY2RrEn2DyVJ7S1J6p/7kjIUVKnXuT8t2/39cz9t0nM/bfLYnzjux7M2ZDhTOfkOhSlT/7S/owDD1eMx2MhVmkI0YMy7roMa9lDA2JWSpF6mqQUrP9WF1rWa5jdR4TouP8Ohg2aEfnZ0UyfLDmWa/gru/4Cc1oXS8lvV3pLscc2Wll36ecMB9bX8ocdtn+gdx2DtOJAg+UsZfvEK73CNtOhFKWO/jB53SB2uUe6P49TcslfjbZ/pdpsrXE5TsAocQ93DhcvS57lfPB5/sWKPx+Npq/bqxas7uodvf3Z7D/VuWkeSdDQzT3tSs9ShfoRUrMdg0eHe6/amnbVtpfmjP+kR2/90h81Ve5IzTo0L5+yUpBaWvfppxtNq//3V7m0nXsfRzDztPJKpzg0j1ePZOfrK7xtJ0r7m16vxtS9r9oRdusS6SpucDdQqsbcOBzdWfFaRUXDhDcpVo6PJACn5Az1tf19hhuvf5EjbLKVlj1B44OkDtM9X7D7tMcuTjurRb9Zpa8pxXdOtvv51VcdSjxvx9m9lnuf1eds0un+z016vOq3ZfUz/9/FKtTR26dKJW3X1RT10LDtfHy3dqSYxwfrlgX7lOk92nkOXW5bqPIvr73Bf1iFJpYfQAFARFR5e3b59e+3YsUONG1d+mAMAAKj9yByrl2maajH+e7U2dirJTNC6564ux7NKOv+f8/SO/SMFGnnaFdpZDUfNU3PDUPOKnqjVYBkP7ZBhsUkWV0DU/4qbpR9/0bW2+e7DBluW6cjxXEWH+Jc4hU0FesX+mhKNg7o//07dYD3Z+6iOka7Rtu+0zNlK/7S/owNmpO7Iu1/pOfkKK0dvn16TfzntMSeCpkvaxOmtG7uecnjlL5sO6tYPXL3JNj89SFOX79aE7/+UqmhYZlp2vkL9bZU+b6vHZ2qC7SvFGGna5qyrZmOmSwfXK7xBTyk0rsTxhmHo3wVX6ULrWsUYae7tccYx3WRz9Q79M/EWdQ+J0cWXDdfG3yaqtWWXxznqG4cV7GfTP2yfq7llr54z3tUjBbdJkjJDGio8IFy6c4l0cL3UqI9ksWp3dB81O7rAHThK0l+sS7Ro62H1bxV72teZmnX6hUWKBojXv7NMr1zbSS/N3qKdR07OV7jl6ctOe571e9NO2VPQF37ZdFAXWNa6A0dJ7sDxl4gr9WVKfb3p94rutn6rzsY21THSNd/ZURlZF+mpGVv05YpdqmccVooZqX6W9epm2aJc067GVzwiWSy6ZOLPUtICtarXVbJYlRvZUioMHXNNu/yDY8pVZ9t+10gffOAOHCXpPMtm/bk3Tb2b1fHKz+Kat0722vtixR4l1gnWXf2aacO+dA1+dZFeubaTruhU77TneX7WZg1pn6C4sAAF+p2ix3c1++vri/S0bYputM1VgWnRcwuu04+O83W9dYXMo9KFz2ZrwSOlt1+n09TWlONqFhuitk/M0Ey/74rs5cPlovgQFai8CoeOzzzzjB588EE99dRT6tq1a4mFZMLCznwujrK88cYbev7557V//361bdtWL7/8si644IIqvSZqtgJnxVbmq06f/75LXRtFqn5kkFYUDhsLCbDp0W/WadxlrfTj2v3q1zJGVotFHeqHKzvPoce+Xa/F2w5rYNs4ZeQUqH39cB3PKVB8WIBem7dNuQVV/XpNWeWUVU5Z5JRNDlkKH9sKt1lkyiKnDMM8+b1U+OeJbWaxx67nGYVf7mOMksfolOfwfGyUeo6Sx5z4XjJlSLrD6lSWAvSto08V/yxrLhaSQXlwi161cvIduuK1X7X5YIbaJITJOLBWP/q9rhaWvTpuBuifj87R545+qmOkqUPrlnrh5v6lnmfvsWyPHmFDLUt1iXWl8k2rGt705pmlxzY/j4cJnQYpe7qfAo0897YWlj3adTSr1NBxkOV3DbEulyR97Pec6qgw8Op1t7T0NY2y/aBR+kGSFGsc0zP299VhYrTXe53N3nBQTR6ZoXsHNNerc7d67Au0W5Wdf3JIZ8vHZnrsP5NhmcuTjnoEJpJkyKkEHdVBRWrb5MvL/ctw0Z56HYztusnqWjSm6S1vStFNXV9lmPbMvbrzsSO6xLpSTftcqdX+3RX+y0MabFmuJQEXqP/NzxYWaCh8wFhp3v3KUJD2RJ+v1kd+Vl3jsPJzMtXW2ClJshimLre4XtuxwAaqK0lBUVLjvu5rNrvkDunzBR51dDK26dZ5G8oVOp5gV4Hyi/za8+Ud3XX128tLPXbM1DUltrV47KfTXmPofxZLkn554MIKLV6SfDhT/V5whfC39GqkCZe31eHMXB3KyFXbuhULMcdMXa3v1uyTZKqpsU9T/d6UJH1YcIlufvDf2vHLB4pr1EIXdblGB5fv0o/Tl2qIdbn6WtdJktpYdmr25L1KcQzQz36fqrllrzLMQPnJNUx9UeQwXRwa77qY1S41u/jkxWNaSXtd/xb3mtFqYjl9T1RJMhr0UIYlTKHOdPe2tkay5mTklPt197Os0VXWBfrV2U5THf3lpwK91+eYnl+Srj/Mkj0T/zVzs26/oIkGv7qo8Oe2Rn3KGXCe+Lu67fzGenxom1KPyS1wuN8HhneupyB/qz757WQIP+/BfmpcJ7jU557OrD8PaNTHvytcmbLKqadtX+kGm+vDGJvh1GP2T/WY/VP38Uuyl2p/ynnq9dIySdLyRwcoNjRAr8zZqn/P2aJopclf+brXNl8tLHtPXsg8e39/AlCzVDh0HDRokCTpL3/5i8dNjmmaMgxDDoejjGefmc8//1xjx47VG2+8oT59+uitt97SZZddpg0bNqhhw4ZVdl1UXk6+7//DWr83XRda/tBQy1Jpe5DUtPRfulTYjg9l5Cojt0BX/3ep7ujbRJFBdr2zKEnbUo6X+5pWOeSvfPkrT34qkL+RLz/lyy6HbHLIrgLX90aBfircdnJ7gdoaDs38YJr85dDvq1zHrlWBbIZDveVQX5tD9s0FrufsLJDdcD3/JaNAdrujMAx0ngwDjZPBoOeXo0h46JTFKD1ELHrsifmZzgXhypRUuZ5CtV1KRq5CAmzKL3AqLNAui2HIWkaPG4fTFegW7ZVz4v+NisgrcMpuNWSaOmUPn9wCh+wWi9d6FpmFCSufcp+Zo5l5igi0yzCkLQePa2tKhoa0T1CB05TNYign36kAu+Ws/zkfzcxTkJ9V/rbK11rRtp+eky/TKdmshr5csVsXtIjRxS/O03DLYv3L9rPi/FOVcSRIjfwOuFf9DTFy9LB9qh4unJMxd7tNUx4boNcLhumYghWuTB1XoHLlpzBl6nbrPA22LlegctXMcP3i+bn/lboxtnWlXuMp2QO1PfYStTt0MgBLMI5q0a796tzQc5ERp9PUxdaV7sexxjFJcvXMu/Rp5ez7UwE750mSsoLqKyhrjwZYV6tdwQ49PX2D3l2cJJUxN6NNBXrQ9qV6Wjbod2dLHTQjNcS6TB2jnfrfocb61tFHq8zmssmhXNklGe7AMVjZypdNebIrO79AbY2d6mbZrENmuDabDRSsHDUx9itFEVrpbFFiMZOith86rtx8p/ztFg148WTAZsipvpZ1es/+s5obe7Rf0Tpkhus8y2bFGce034zS+McWaIaju9IV7I75H7ikhTLzHPrvgu1FrmKqi7FV11l/UQfLDjUx9stmODXd0UNDm5Zv+KXFYujNZ590P+4oKa3nd8p2OtU/2DMwrtv3VqlOlELjOyhzxvvSkZ9VzziivCPJshS5j+hjdfUG3W9JUKnxTashUs/R0p7fpUuf0uH3rlYdI13pu9ZJOn3ddhXoNfurGmhdoX3BbfT5sda6LXaTwj76U9P8mun9gsu0wWykpsY+BSpXG8xG2m7WlSS1MXaqoZGi352tdFjh6mZs0kjbz7La/fRLbitlmgFqbdklhyya4eihLaZrOPFFLy5Qq/hQPTqktTo2iNCfe9OVW+BQj8bRevCrP/Tj2v0eNUYrTX+1rFVLyx7tWV5Hw35rov1mtByyKFt+GtS5qbolRmp50lH1aVZHvZpE6899aerYIELLk47q4a/XFt5vm+pl2aAP7NPVy7JB/oXD5jc6G+iWCR9L9kA1Hf64+7rX9WikoUvGadahuQo1shWpDN1j+1aXWFfqkiL/7kILeyCucjbTxXe9esqfdf2WXaTCvHaPpa6anPZvp5DVptArnpd+ekjqdpuci/6tYCNXWakHJJ16VXvTNJWT71R9I0Vv2V+Sv1GgodZlui/yV0U5j8q2MkXn+0szHN3134LL1daSrF6WDVrrbKIPHAPVvHCBGJsKVCCbuj09R4HK0SO2z3Rj02wdjuqqP9KCdHHYbu3Zu1uv7mup7x29lSNXW39vcZIOpudoerG/zxMMOeWnAk1bvVcWOdXM2Kcmxn4dMKN06QueIXjS5MHu/xNM01SB01S+w6m9qdl64Ms/tHaP68MWi5y63jpXv/l/o7jC90NJcpqGPox7WEl792ucbaqCjFxtcdZTonFAva0btOG1i/SMrZkijQz9759f6jtHH0XouF63z9Agy++l39vz6bKHs/vOpHpV5v4d5zbDNCv2jrJgwYIy91944YVnWtMp9ejRQ126dNGbb77p3ta6dWsNGzZMkydPPu3z09PTFR4errS0tCrvkekLy1b/oQe+WF34yPOv1SjxWKfcX5FjS3tcfF90sJ9axIUqO8+hP/YcK/O5nnVU7Lqex5/cF2Ok6QO/k3NQzXd01EJnBx0zg2U1nLIXhn3FA0J/Ff5p5BcGiIXHGAUn9504zjhxvOuYcymYK67AtMhR2IfQWdin0NXP0XB/73TvP3mMKUNO0/OxWerxp37+yXOUcQ339/Lo33jiWFOG2hrJamnZo3cLLtPfn55ajlddDk6nVJAtOfJcN3Kms/Cr6PfOs3o4S0ZugQb9e2E5jqycc/v+pfLv2d44vrjTna8qaih5jZP7L2oZq6gQu75e6ZqPrW29cA1uG6cXft5S5Pmnf43e/7mUfA024+QHSDY55Ff4p91wfYBklaNIH2vX+45DFjlMqwpkkUNWFchauN91zgDlKtzIVJyRqjjjmIKVrRbGHjW1lPxld5ajm8bn/10XWv7Qw/apijdSlW169iws6qgZomDlyN/wXHBjuqOHhk6YXqKnoldkHZXmTJQa99WRr8Yq2sjQ1K5Tde3lnkMAD2Xk6tjzndXcsleOHqNlXfa6JCnv8jfk1/UGKTtVmv9PmRarjAsf1jfPXKu/Wn/VdEdPPZx/u4ZYf9NKZwtNvuMqdW/smov82RkblRgdrN5No/Xzy7d7DD0tS45p1z4zWkcVpkbGQcUYaXKaho4qVDY5FGFknvrlmv5a6Wyu/Wa0Dilch8wIZZhB8isMhRyyyCan4oyjamckK944qkDlKsI4riijfB94FpgWpSlYfzoT3aFnpJEhPxUoW35qbuxVS4vnfIYrnC3UZdxsWYIiynWNytow8x21+e1BLXG00f52/6crN5ZcJGT3pe+oQe9rTnuuXx/vrT7WP/WP/Dv0/DPPl3lsSkaOPnzuHv2jcNGU8kozg+SURZGFP3uHaWibWa/Ez6+4rc562m3G6IAZpQNmlI4oTE4Z7ntFf+Ur0MhVXeOIEo0DijeOypBUR2keQWxRTtPQejNRa51NlC+bsuWvdDNIxxWoGCNNMTqmICNHFplqZuxTG8tOj+evcTZV/dunqk6DFqd93VN+TdLM6V/rNb9XFa7j+srRV02ve1FPfzJDoUaWPpw4Vna/kr2R3dL3SS+5PqRw9B0n60XjT3vN0hx9qpmiHIf0U8+Pddmgv5R6TNEQ/z/2V3W59TfX4kNm4b2WJPmHSbkZpd5XrXE21bP51+se2ze6wLpevzlb65WC4brP9pW6WzafsrZM01/JZrwOmRFKMSO0X1EyZShcmYUf2puyyqFWlt1qYexRkJGrHNMuQ3KHwCocfr7ZrK/DZriOKkwHzQjtN6M93vtNGQpQnqKNdEUqQ1FGhlobu9TMss+jpkNmmCbmj9Trzz6l3UezdMm/ZipQuZr3xJUa+dSb+sjvOYUZWaW8mpMcpqFMBeq/BZdrtO1bBRu52nfzUtVtUnpPztNyOqWCHMlZIJkO12PTITkdrj/Lq4LBp2k6TxmGFQ3KnE5Tp/pcOr9wn9Uw5DBd3xsydP6/5lWoFuCE/90zSA3qxvu6jCpR3nytwqGjr+Tl5SkoKEhffvml/vrXv7q3jxkzRmvWrCk1DM3NzVVubq77cXp6uho0aFArQ0fTNHVoYqK7FwBKV2BaZDOqt/dlgWlRruzKl63wy6oC0+p+XFD4C6Zru2v/ie35hfsKZFOe6fqz5PZi55BNBYUDkR2mpfBXXIvHl1MWFRRud5qWk8er9ONP/EJ88rnFzlG4zVT5htL42l861tX3f7hu2kZd2FRLtx/WH3tOzlH1D9tUjbZ9r1/rXK0+d79b/hPn50g75km7l0kHN0jpe6WMA1Je5smbYADwknQzUG8UXKFfne0UbmTqsBkue0I7/XDvBUoc96MMORWgPGUrQL0t6/WQbao6WXaUeq7Nzvr62HGJksx4hUfX1ev331QtPRn2TO6i+rnbNaPjfzT4rzd77FuXfEBtprRyfZB3/0bp0GaZBbkyWg4q9Vy7NixXwy8ukSQdNsNUx0jXcTNAg/L+qcWTR+ri8W9prG2aDpqRWu1sptf8/uN64vn3uQKT4ylS80ulqCbSxu+lDd9LeRmlXqu4LNNfgU17yZmdpoIDG+T0C1VgXHMd2LlJ8UZqpX8+6WagvnJcqDnOLopTquoaR7TebKwVzhYaYZ2vW20/qb5xuFznyjHt+sHRSz86e2qfGa3PHrlFdUIDK11beWVsmqfQqcOU5IzTyno36ar9LyjdL05heScXNNHo36WY0wdj7z82QrfaZpb5oeAdz7wuS2aKIhPba8LeUQow8uW8+ClZnLnS3tVSg+5S80ukDd9Jqz+Vso5IdZpL9kCZB9bJyC8MaPxCpJA46WiRHqMdr5fCEqSkRa4wK6allHlEzm1zZHGefv7IU/nT2UhrnM1U3zikdpYkRer4KYPIsuSYdn3h6KePHZdopxmn1ZOGKti//APb2jwxUzl5+bLJUeHnSpIWvyzt+k264nUpOLrC9UtS0vN91TjzD/3U8mlddt09JfZ/tmSb/H8aq/OMTVprNtFQ6zI5TUOWOxdJ9iBp/ddSZKLUZph0eIs0+3Fp5xLX31WDnjq27JMyPyRIN4MUdtF9UspGKeeYlNDJNZR87edSavIpn3c6maa/0gIbKjB7vzvQrowMM1AvFFyjqY7+KpBV346+QO0bRJZ67FPTN2jWr8t1heVX2Y0CZZn+6mP5U+db1ilPdv3o7Klhdz6rafsidF5ilBrXCVbGhHiFGtnaf/OvSmjS7tSFmKZ0YK20Y4Hrz6NJrnve3PRThr3AuejZ/Ov0yDP/9XUZVaK8oWOFh1cvXFh2L5e+ffuWub+yDh8+LIfDobg4z8mt4+LidODAgVKfM3nyZE2aNKlK6jnbGIahHNOubJ3skWCesu9fafuMUo8rPLtXzlPZa1b2dRQ9Nt+06bmC67TFrK+/WJeoqbFPocouDOpcoV2u7Mo1bcqVn/JkU67syjPtrj9V+Gfhftc2m3LNk8fmuo+xKzgoSBFhoWpdP1o5TouaxYaoUVSwDENqFhuiOiH+8rNZFGS3KivfoZDCm7qcfIfyHE6F+LkeWyzGGXVhz3c4ZS/H6o7nolev63zKfb+987O0V7KW98eemyEtekn6/T0pN60cTyjKkAxL4ZdR+Lj8f98n2njRdpLvcPUttVktync45XS69hlGYcdKL33WVPzf29mq5tRZ/HH53t9OKnt/Rc93uuPLV0P11+Sx3zx9zd6uoej/K3myFfmQ6eSHQpJKzDFrc0+14ZTVcE1ncUK26ad0BeugGakUM1IZClSqGaqFzg5a/cyVesgwlJqVp6hgP/f7QPEhvE9Nb6xhi9sqVsdUIKuOKUQhylI944gk6bX7btLTsaFl/jyrQqolWvW1XX9u2qzBklIz8/TG/G36vwubKmPXWlkNU+lGmMJCE6SwumX+jTds013zHB3V3/qH6hiu+eFCjBzdZp0h5Y/QR37Pqa5x1OM5/yvor+sunljyZC0HSUP/LeWku3p7Zh2V0vZImYekyEZSdDPJkS8dPyg5CxQU00qy+csqqejyEvGmqU1rftX7X32rOkpz9U4zjilU2cqTXaYkq5yuvxMzROvNRO02Y3TcdA1932rW08bJf9WthqG8AqeslpNTWXy3ppfOn3qZqyesMlXHSFNXyxbVMw4rywzQEYUpTzYFKVfHzBCNHzNGV8fFV/ukIcExiVLhMPqsQ64h7/vj+ipk11cng7Xo8q0I3L5LL2ntTLU0Sl+xeNqUF/V2/pOSn6R9rrekxY62Or/PPSX/b41rK/V/xGOT4ch3LWRjOqX4Dq6w6egOV8gY316q16XU61qyjkp7fldu6j69+cNCxSrV3QZd94d+yi28pzxgRirZjNc+M1oOWWUGx2jaQ39VW7+Tv5Y5nabmbjqg8R/N1QWWdWpoOSirnApSrsKMLIUpU4fNMB0wo5WpADll6LgCNcfRRQsmXqWby7GQUmk2PFl6oF9u5489s+dLygpMkDL/0LEDpQd8G3/8j56yu+ZibKhDkqSpjn66Pr6964ALHzp5cHw76aZvPJ6f0vQWJX16szpbtul3ZwudN/J5fT3leV1pXay9ZrScIz5TWJueJS984Tgp5U8pfb9SDuzWR7OWKqHw/eSYgpUvmxym6/09oXFbXT/scik4xhVcmqaCIxoq2GKVTFPfzF2gpE1rdGD/HtVRuuKNo4ozUj3G30hSnuxKNUN1RKE6ZobqkBmuJZbOWvnMVSrPb7iPD22jx4e2kWneIhX+vjjo5YXaceCo/nZBU40b3E6GYeiauief4zzRgaCsOR03/SjNmywdXFeOKk46MRrKG4OVvXEnW1PuD882/Nwqpkvj8s8/XFtVOHTs16/k/ClFA5GqnNOx+LV0mjkFxo8fr/vvv9/9+ERPx9rq+KhV6ls4ITJO7d8FJW+3376pq1rFhKhZbIgKHE7ZigR1xR97W0iRT5ED7FYF2D1XwzuTniYEjpVjGq6f2+mGWkqSDm2WPhshpbp+kVJYfanZAKluJym8oRQaL/mHSn7Bkj1QsvpJhtX1y08pf7dOp6mdR129LP7zy1ZNW7W3xDFng5/GXKDIID8ZhhQT4q9lSUfVJiFM2w5lyDSlsEC7dh3J0vZDx7XpQIYig/wUFmjTRa1itSc1W7/tOKK6EYHafCBD3RIj1aNxtKKD/ZSalac8h1MH0nK0POmorBZDrRPCNGPdfu1OzVaXhhEKD7QrM7dAzWJDdCwrXzGh/ooM8lNUsJ+2HzquEH+bYkL9tWjrYaVm5WnKr8ka0a2B0rLzdV7jKH3/xz6FBdjkb7Pq0jZxWpZ0VPM3p2hk70RtOpihQW3j9dXKPeraKFI/rt2vzQddPZ1G92+qz3/fo15No5WRk6/QALuSD2cqNMCmyGA/zd+UosvaJ2jj/nT9uS9dFkO6tE281uw+prgwf13YMla/bjusFnGh+m7NXvVoHKUW8aFavPWwDqbn6vDxXEUF+ykiyK7DGbmqHxmk3alZysgpKPXvoFujSK3YefoeVMUXuRjeuZ72HstWp4YRemvByV5v5zero2B/q45m5un35NLP271xlJYnHZWfzSKH05TDWf7b/q/v7KXQALsKHKZaJ4Qqt8CppduPKC07X2nZ+bqmWwM9OX2D/rd8VznOdmr3XNRMt/dtovcXJ+nlOVv17eg+Opieo2dnbPRYjXZoh4RTzsV1QpCfVVNGnqdftx1WnVB/XdGpnjJy8lUvIlAb9qcr32HqyjeXlPpzsFoM9/aLWsXqyPFcBfvbXO0wMUqD2yfogyVJ2ncsR3/sOXbKUWQ392okh9PUmAHNFRsWcMpaS1uEpagTv3yebdLsdaRsKSTfFR5c9tRUDbCuVv9FvTWhiWv+xA3OhupZzv8L/+24Wj0sm2RK+tAxUHfZvtdw6yIdnfuK6hpHlW4GaodZV50s211DLAtu0HWnOpnNXwopXIE3IFyKalzymODTLD5hGGrV+Xz9q/P5kqTDx3P10/oDWrjnmFrGh+mS1nE6mpWnOiF+slstujrE/5Tz0frZPP9Pv6JTvXKtuOtrlnBXohFg5KtB7jbJKu1XrFr0ulP67Q2ZPe6UUc5FR2KbdpbW6uRQ5+xUyWJz/T/rdKpH8useecYRM1SPFPxdC8t7L2W1S3WLfSgZ1cT1VZagKKnFQPlLGtvjb1q3J011Qv0UX+Tf7JHMPNU5zb/TEywWQwPaJGj5czeW2Ffb5xlOt7qmQoi1lP4h7jVW10Iua5xNFaosJZnx+jTsNl1fzvO3aNlWKQ8uVrdnv9H/xg6V4sM0dMIFav/YNF3dq4WeaNOx9CdaLK7gOb69YltID/a9rXwXDCw2fYFh6K8X95MuPvk79aGMXOU5nIoItCuvwKnsfIdiQv097uPPpBNC0efNHFt2ByF3oFRa6OjIl34YK635xPXYFiA16SezfnetzozSpIXpSlewjpuBylSAx4ipmjIa6kydlxipVbtcIw8dTlPDO9fTtNWl38sPaBWruZtSvHbtKzrVLVxIqmJu6dVIHy7dWY4jUVHRwX5acdvF5Tiydqvw8Oq0NM//APLz87V69Wo9/vjjeuaZZzRgwABv1yhVcnh1cbV9TsezyYm5ViKC7FrzxKVSkf8sT+yzWgxtf3ZwtdWiMiaTB4pa+u4D6rXnXS2vM1zd755y6gOP7ZLeGSBlpkjhDaRBz0ktB7tuTMshJ9+h8/85T4eP55bj6LPL5qcHyd9mLceROJfNXH9Aoz5xLUhwJu+/TqfptYWBcHbZ+Nk4td7ypuYGD9GF93+ijZM6q70lWT84eio4qq4uSpum7wKH6YqHPyz3Of/21jzFhfrrwnaN1ParC9XQcsi9b1z+3zXV0V91lK4jCtX6SZdVfAgpKix1UiNFmseUbgYqzMjW+p4vqd3AW10f2EUklvv/zWPHjiriZVf4m3rNN/L//FoVWAMUdu9i6fgh6d2LdNwM0AW5L6udJVnrnYm6a3AP3d633MuawMfWffm02v/5vH4N7K8+D3/ruTPzsPS8a5X183Le0CG5Aj3u773nyIT6ijYytO/6earbokjPXtOUvv67tP4r14fnfe6V+ozRtR9v0m87jpZ1ymplsxgqKPzAr1F0kOpFBGrJ9iOyWgwlhAfovzd2lc1qaNXOY+rVNFqZuQWa/NNGjb+stWLD/PXd6n1qVy9czWJDlO9wKiffoahgP3V6crb7GrQ3wKXKhleHh4eX2HbJJZfI399f9913n1auXFnq886Un5+funbtqtmzZ3uEjrNnz9YVV1xRJdeEdxX/dC7Yj8ACZyezlO9KcDqkL25xBY5x7aWbvz1tj5d9x7LV+7lfvFlqlQr2s+rBgS3VMj5UK5NTtetolr5cWfZE+kBVIHCsvYywBElScN5hfT57kW6wuIZUXm79TRvSXeFCROKpp8MozZT/6y8VhtXPfz5AD1tcc//tdsboa0dfDWlfVz+uM9Q8NoTAsZqk2mIUmX9MYYUrIQfWaeTq7X+6HoTFREREaZczRg0th3R06l1qasmVnLk6MPsVxUe6pgeY7+ykVIVpkbODJOnW80vpoYqzljXUNZVWcP6Rkjt3uHo5bnA2UuPEJvp9VK/qLq/Wcxb2dFy4JUXXFp1mdfk7rsDRYpNGfKqvj7fTA5OWVOoaL13TUY2ig9W5QYQOH88tsxd/VWkVfzIg+fTvJ4fT8wEF4H1eu9OKiYnR5s2nXu3LG+6//37ddNNN6tatm3r16qW3335bu3bt0qhRo6r0uqjZ6kUEau8xFvFA+W1JyVRvSVsPpKv7qQ5a8b60b5VrdcTrp5YZOBbtbesN/jaLRpzXQHf0baI6If46lJGr+pGBMk0pt8CpAHvh8HAvDr3q3bSOkg9nEjoC8Cpb4dDbcMcRRadv9NjXxnQt4OFfr32lzm2xGPrUcZGutC5UXeOIHi8YqXzZ9PoNXfS6F2pH+WX6x0n5W92PA2MaVfpcm80GaqhDHqu3O9Z/I2d0hCyFK7h/fWdvXfnmEn3wt/Pcc2CiZrBHuD6ICHMUTvOx7itp62zp4gkykxbJkLTY2U5/6VS37BOhUk4Mg87IyTu5MfOw9MtTru8vfVqJUxyS/jjlOR4d3Fq3nd+4XB8Y+iJwBFC9Khw6rl271uOxaZrav3+/nnvuOXXseIo5MLxkxIgROnLkiJ588knt379f7dq104wZM9SoUeVvXOA71TUXTS2d8gZV6EhmvmQvY07HgjzXwjGSdNFjUnj9Ug/7euUePfDlqW/Kinv7pq7q2yJGVouhnHyHQss5EXyDqCCpsK0H0oMYQA3iH+WakzDCcVR7UkuurF1gWhTduHKhoySlK0SD8p6TTQ7lyF8PD2p1RvWicnKD4qXCBXsdpqGo+IaVPtcWs74u0SpJ0jEzWP7Kdy2IdPSI8kyr5jk76T+NIhkCWUP5FYaOkc5U6dhuadodkumQnPnK2f2HAiX97myp59rF+7rUWulET0fTWWROx19fca1KHd9Bjb8t/Z536fiLlBAeWF1lAqhBKhw6durUSYZhlFj9tGfPnnr//fe9WVup7rrrLt11111Vfh14B3kfaqITK/edMnTc8K2UsU8KjpW6jiyxe+n2I7rund/KvMbMsRd4DO0ojkWAAJwLAqNcvZVidEyRWa6h1Qsd7dXX6loVdY3ZTO1ioyt9/sToICUfyVJB4S3vHQyd8wlnaF2pcL2EA4pSPf/yLahSmvXOk8OlP3f0U13jiC63uv7PXeTsoOMKOvOC4TOh0a4PIiKN48rf+JPsZuFCaOu/1olIa4WzxWkXz0LllAgd87Ol1R9Lkja1ultmsuf96ZonLlFEkF/1Fwqgxqhw6JiUlOTx2GKxKCYmRgEBdI1GSbV1ZT3UbidW7rOcKnT843+uP8+7zbW6aRHvLU7SU9M3lPq0f4/oqL92Lv0TYgA4F0XG1JPDNGQznKp33DWa5ivHhYo20tXWslMfFlyq/9gr34N71n191fKxme7HDLX1jfXHQ93Tlew3o3Uma27PdXbRSmdzRStdHxQMUltLsjt0/NpxgVfqhe9ERMUqz7TKz3CoYNNPKj7mY6uznlLFgqBV5cQH7+aJsHfjdCk7VWZ4Aw2e6Rno05sYQHlUOHRkKDOA2u5E6FhqT8eso9KOBa7v213lsavb07N1+Hheiad8fWcvdW0UVUXVAkDNZbXZlaJwxeqYEhyuOfrO79VLw3/tpjgjVbvMOP3nDM7vb7Pq0jZx+nnDQU2/53yv1Y2KianbWDro+j5J9dTtDM7VtUm8rtwxyf14vzNKj+X/TU5ZNMPZ48yLhU9ZrBYdMSKUoCMK3OlafG++o6P6WV3T1fzi7OTjCms30zQko0hPx00/SJJeP9LFHUiKwBFABZR7/N4vv/yiNm3aKD09vcS+tLQ0tW3bVosWLfJ2fajh6E+AmujE0BKLUUrouGWma26huPZSnWbuze8u2lEicHz35m5Kfm4IgSMAlOGY1XP4dGyj1sqVn3aZcbqq65n3Dn+78L24Xb3wMz4XKqdnzz7u79c6zqwDw7+u6lBsi6FPHJfoM8cASYbqhjP6qqY7bInxeDy54DrtNaN11Awp/HtGVfEYXl2QK22bK0n62XHyo4Ktz1zms/oA1Dzl7un48ssv6/bbb1dYWMnu7OHh4fq///s/vfTSS7rgAoY1AKjZTkSNpfZ0TF7s+rP5xe5Nh4/n6ukfPVddXTvxUoWVcyGYmsg8xchzoChm2EB5pNuipDzXStVHzRDVjYtV8nNNlVvgkL+NxbFqg5i4uvpH/h1qayTrULMRZ3SuE4unqXAkwQuztmjpjiPubV0T+aCvpjtqj5NyN0mSMk1/bTHr6+Lc52VIyhKhclUy3aGjQ9r1m5R3XGm2aK3LOTmXKvOOA6iIcoeOf/zxh/75z3+ecv+ll16qF154wVt1oZbgF07URGUuJJNc2KM78eQwvW5Pz/E4JGnyYOYzBYBy2lMQ4R5uu8uMVay/6/aUwLF2eWric9p5JEsj40PP+FxFh3Zm5hV47Lu7f7NSnoGaJN0/Qcp1fb/VrC9TFmUXCRsfHdzad8XVcgUqfN91OqTdyyRJC3JbyCy8N97x7GBflgegBir3xxQHDx6U3X7qXjs2m02HDh3yVl2oNU4dvBRfAR04W5xcSMbpuSNtj3Rsl2RYpQaueaNW70r1OGT9pIEEjgBQATvzToZQe8xYxYfRk6k2CrBb1dILgWNxa/ekeTxuHhvi9WugeqXa4tzfb3Y2KLG/S6OIaq7o3JFXuHSP1ZnnDh1XOFu491tYjAtABZU7dKxXr57WrVt3yv1r165VQkKCt+oCAJ85uZBMMftWu/6Mayv5u35x+usbS9y7O9QPV4h/hdfnAoBzWqrl5HDY7WZdfqlFhYy6sKnHY9pPzffl/pNzOi53tiqxPzE6uJorOnfkFQ6EtDpypN2/S5JWFoaOt/ZpXOZzAaA05Q4dBw8erCeeeEI5OTkl9mVnZ2vChAkaOnSot+tDDUeHL9REzlP1dDxQ+MFLvGsS+8VbD3vs/v7u2r0yKv+eAVSFjLCTw2HXOJuWeSxQ3Oj+tJnaZou1qb52XKA5js76ydm9xP7IID+f1HUuyC3s6RiTmyzlpinHtGuT2VCS9MTlbXxcHYCaqNxdch577DFNmzZNLVq00N13362WLVv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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Show the data for cell 1, and superimpose a simulation\n", - "fig = plt.figure(figsize=(16, 4))\n", - "ax = fig.add_subplot()\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.set_ylabel('Current (nA)')\n", - "ax.plot(log.time(), log['current'], label='Cell 1 data')\n", - "ax.plot(d.time(), d['ikr.IKr'], label='Best-fit simulation')\n", - "ax.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Finally, we can plot the residuals:" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "fig = plt.figure(figsize=(16, 4))\n", - "ax = fig.add_subplot()\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.set_ylabel('Remaining mismatch (nA)')\n", - "ax.plot(log.time(), log['current'] - d['ikr.IKr'])\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Clearly, this is not an iid normal noise signal." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "### Interpreting MCMC results\n", - "\n", - "So what does it mean when we explore a fit to data with UQ methods?\n", - "\n", - "Using for example MCMC to calculate the probablity that the data was generated by the sum of a deterministic model (with an imperfect best-fit as shown above) and a stochastic iid noise model, **will** let us confirm that a given set of parameters is more likely than its neighbours.\n", - "Similarly, if we have two similar methods, and one of them provides tighter confidence intervals than the other (defined in the same imperfect way), then we **can** conclude that one method provides more certain estimates.\n", - "\n", - "However, the **absolute values** returned **will not** be informative, because they are the answer to the question: _how likely is it that the residuals shown above were generated by a stochastic iid process_.\n", - "To which the answer is: very unlikely.\n", - "Similarly, the absolute widths of confidence intervals determined in the presence of model discrepancy are not necessarily informative.\n", - "\n", - "Given that biological experiments provide very limited control over experimental parameters (i.e. native processes going on in the cell), and that models are _by definition_ simplifications, model discrepancy is not going anywhere soon.\n", - "Methods to perform and interpret UQ in the presence of model discrepancy are an active topic of research, and will likely remain so for some time to come." - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.11" - } - }, - "nbformat": 4, - "nbformat_minor": 4 -} diff --git a/tutorial/appendix-d/5-leak-correction.ipynb b/tutorial/appendix-d/5-leak-correction.ipynb deleted file mode 100644 index 92d8063..0000000 --- a/tutorial/appendix-d/5-leak-correction.ipynb +++ /dev/null @@ -1,231 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "e7fdae0f", - "metadata": {}, - "source": [ - "# Appendix D5: Leak correction\n", - "**Appendix D discusses remaining noise and errors**" - ] - }, - { - "cell_type": "markdown", - "id": "22f7aaad", - "metadata": {}, - "source": [ - "I don't know!" - ] - }, - { - "cell_type": "markdown", - "id": "866c6899", - "metadata": {}, - "source": [ - "See also:\n", - "- Endogeneous currents\n", - "- Gating currents? (~100x smaller than ionic currents)\n", - "- Protocols to remove or quantify \"leak\"\n", - " - Subtraction protocol\n", - " - Leak ramp" - ] - }, - { - "cell_type": "markdown", - "id": "4a3c522f-0701-4ee2-813d-38b24f338259", - "metadata": {}, - "source": [ - "## Some ideas\n", - "\n", - "Below are three sketches of a patch, and ideas about where leak may arise." - ] - }, - { - "cell_type": "markdown", - "id": "32babedd-5c83-401b-a84a-cff5abc5281a", - "metadata": {}, - "source": [ - "" - ] - }, - { - "cell_type": "markdown", - "id": "f20d5bd2-cd68-4226-9321-5df7479b4981", - "metadata": {}, - "source": [ - "On the left, the pipette (and other electrode components) contribute a resistance $R_e$ or equivalently a conductance $g_e$, which arises mostly in the narrow tip.\n", - "Access to the cell contributes another resistance $R_a$ or equivalently $g_a$.\n", - "When the seal was made, membrane was sucked into and around the pipette, so that any contact with the bath would be at a point between $a$ and $e$, which we've labelled $V_1$.\n", - "The leak is indicated with an orange arrow from this point to the bath.\n", - "\n", - "In the middle sketch the seal is much looser, and part of the \"seal\" is made up of debris.\n", - "In this scenario, there are two leak currents: one from the pipette tip through the debris into the bath, and one from the inside of the cell to the bath.\n", - "In this case, we could also imagine the debris to have a capacitance.\n", - "We could also draw a capacitance for the connection from the cell to the bath, but this would be indistinguishable from a slightly larger $C_m$, so this is left out.\n", - "\n", - "On the right, the pipette and cell still contribute $g_e$ and $g_a$, but now, perhaps because of debris again, the leak current is from the cell interior directly to the bath." - ] - }, - { - "cell_type": "markdown", - "id": "7b50fa7e-9aa4-4567-bf70-a92b6438206c", - "metadata": {}, - "source": [ - "## Equations 1: No $C_1$\n", - "\n", - "Because the left and right schematics are a special case of the centre panel, we'll only treat the more complicated schematic.\n", - "To start, we'll leave out the capacitance $C_1$.\n", - "\n", - "The total leak current is given by\n", - "\\begin{align}\n", - "I_L = g_1 V_1 + g_2 V_m\n", - "\\end{align}\n", - "\n", - "The sum of currents at the $V_m$ node is\n", - "\\begin{align}\n", - "g_a (V_1 - V_m) &= g_2 V_m + C_m \\dot{V}_m + I \\\\\n", - "V_1 &= \\frac{g_a + g_2}{g_a} V_m + \\frac{I + C_m \\dot{V}_m}{g_a}\n", - "\\end{align}\n", - "where $I$ is the current of interest.\n", - "Combining, we find\n", - "\\begin{align}\n", - "I_L &= \\frac{g_1(g_a + g_2)}{g_a} V_m + \\frac{g_1}{g_a}(I + C_m \\dot{V}_m) + g_2 V_m \\\\\n", - " &= \\left(g_1 + g_2 + \\frac{g_1 g_2}{g_a}\\right) V_m + \\frac{g_1}{g_a}(I + C_m \\dot{V}_m)\n", - "\\end{align}\n", - "\n", - "For the **left schematic** we set $g_2 = 0$ to find\n", - "\\begin{align}\n", - "I_L^\\text{left} &= g_1 V_m + \\frac{g_1}{g_a}(I + C_m \\dot{V}_m)\n", - "\\end{align}\n", - "\n", - "For the **centre schematic** we can lump the unknown g's together to find\n", - "\\begin{align}\n", - "I_L^\\text{center} = g_x V_m + g_y (I + C_m \\dot{V}_m) \\\\\n", - "\\end{align}\n", - "\n", - "And for the **right schematic** we set $g_1 = 0$ for\n", - "\\begin{align}\n", - "I_L^\\text{right} = g_1 V_m\n", - "\\end{align}" - ] - }, - { - "cell_type": "markdown", - "id": "5cb75ba4-087c-4b21-b78d-f1ad79067831", - "metadata": {}, - "source": [ - "### Interpretation\n", - "\n", - "- None of these forms introduce a non-zero reversal potential $E_\\text{leak}$.\n", - "- The added term $g I$ would be indistinguishable from a slightly larger current-of-interest, so would be absorbed by the model fit.\n", - "- So in this model only $g \\, C_m \\dot{V}_m$ is a new _and observable_ term.\n", - "\n", - "For a very small current $I$, the derivative $\\dot{V}_m$ would be dominated by membrane charging and discharging, and so this new leak current would appear as positive and negative decaying exponentials after every step change.\n", - "This is not very similar to what we see.\n", - "\n", - "But for larger $I$, would the derivative $\\dot{V}_m$ take on some features of $I$?" - ] - }, - { - "cell_type": "markdown", - "id": "1095caa7-8015-4ee4-91dc-f7c727e721ba", - "metadata": {}, - "source": [ - "## Equations 2: Including $C_1$" - ] - }, - { - "cell_type": "markdown", - "id": "897c6736-ec76-4df7-9635-fcbb05fd1a53", - "metadata": {}, - "source": [ - "In this case we get\n", - "\n", - "\n", - "\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "91442e01-ad23-4035-8a72-9a58646a45f8", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "c1b40bbe-4f94-4909-89f9-27f6732e74a4", - "metadata": {}, - "source": [ - "## Forward simulations\n", - "\n", - "- Foward simulation of sine wave protocol HH IKr, 4-ways params, and $I_L^\\text{centre}$ model without $C_1$\n", - "- Foward simulation of sine wave protocol HH IKr, 4-ways params, and $I_L^\\text{centre}$ model with $C_1$\n", - "- Visual comparison with residuals from published 4-way fits" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "19c68086-d7b4-4ed1-aa0f-1f7af043cb4a", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "f50231d9-187e-4cfd-a430-10b8170f32f8", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ca1f6e7b-1541-4d17-880a-1c438af6b5db", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "7cdb6bca-2e66-4b42-bd7a-5ac0e582b8f2", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "25d825f0-5ec8-4050-90a6-3a017e907e41", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.11" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/tutorial/appendix-d/6-remaining-Cp-artefacts.ipynb b/tutorial/appendix-d/6-remaining-Cp-artefacts.ipynb deleted file mode 100644 index dadeb4b..0000000 --- a/tutorial/appendix-d/6-remaining-Cp-artefacts.ipynb +++ /dev/null @@ -1,44 +0,0 @@ -{ - "cells": [ - { - "cell_type": "markdown", - "id": "7fb2df6f", - "metadata": {}, - "source": [ - "# Appendix D6: Handling remaining capacitance artefacts\n", - "**Appendix D discusses remaining noise and errors**" - ] - }, - { - "cell_type": "markdown", - "id": "e2ffeda4", - "metadata": {}, - "source": [ - "- Cutting out. Take information loss into account in sensitivity analysis (Clerx 2015).\n", - "\n", - "- Just leave in and let the optimiser deal with it?" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3 (ipykernel)", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.13.11" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/tutorial/appendix-d/README.md b/tutorial/appendix-d/README.md deleted file mode 100644 index 78ea995..0000000 --- a/tutorial/appendix-d/README.md +++ /dev/null @@ -1,10 +0,0 @@ -# Appendix D: Remaining noise and errors - -1. Strategies for dealing with experimental error [![github](../img/github.svg)](1-strategies.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/1-strategies.ipynb) -2. Stochastic and periodic noise [![github](../img/github.svg)](2-inspecting-noise.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/2-inspecting-noise.ipynb) -3. Liquid junction potential [![github](../img/github.svg)](3-liquid-junction-potential.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/3-liquid-junction-potential.ipynb) -4. Handling voltage offsets [![github](../img/github.svg)](4-offset-correction.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/4-offset-correction.ipynb) -5. Leak (unfinished) [![github](../img/github.svg)](5-leak-correction.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/5-leak-correction.ipynb) -6. Handling remaining capacitance artefacts (unfinished) [![github](../img/github.svg)](6-remaining-Cp-artefacts.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/6-remaining-Cp-artefacts.ipynb) - -[↩ Back to the tutorial index](../README.md) diff --git a/tutorial/appendix-d/img/leak-extended.png b/tutorial/appendix-d/img/leak-extended.png deleted file mode 100644 index 7b87680..0000000 Binary files a/tutorial/appendix-d/img/leak-extended.png and /dev/null differ diff --git a/tutorial/appendix-d/res/beattie-2017-ikr-hh.mmt b/tutorial/appendix-d/res/beattie-2017-ikr-hh.mmt deleted file mode 100644 index 027d94e..0000000 --- a/tutorial/appendix-d/res/beattie-2017-ikr-hh.mmt +++ /dev/null @@ -1,59 +0,0 @@ -[[model]] -name: Beattie-2017-IKr-HH -author: Michael Clerx -# Initial values -ikr.act = 0 -ikr.rec = 1 - -# -# Simulation engine variables -# -[engine] -time = 0 [ms] - bind time - -# -# Membrane potential -# -[membrane] -V = 0 [mV] - bind pace - label membrane_potential - -[nernst] -EK = -85 [mV] - -# -# Hodgkin-Huxley current model -# -[ikr] -use membrane.V -IKr = g * act * rec * (V - nernst.EK) - in [nA] -dot(act) = (inf - act) / tau - inf = k1 * tau - tau = 1 / (k1 + k2) - in [ms] - k1 = p1 * exp(p2 * V) - in [1/ms] - k2 = p3 * exp(-p4 * V) - in [1/ms] -dot(rec) = (inf - rec) / tau - inf = k4 * tau - tau = 1 / (k3 + k4) - in [ms] - k3 = p5 * exp(p6 * V) - in [1/ms] - k4 = p7 * exp(-p8 * V) - in [1/ms] -p1 = 2.26e-4 [1/ms] -p2 = 0.0699 [1/mV] -p3 = 3.45e-5 [1/ms] -p4 = 0.05462 [1/mV] -p5 = 0.0873 [1/ms] -p6 = 8.91e-3 [1/mV] -p7 = 5.15e-3 [1/ms] -p8 = 0.03158 [1/mV] -p9 = 0.1524 [uS] -g = p9 - diff --git a/tutorial/appendix-d/res/simplified-staircase.mmt b/tutorial/appendix-d/res/simplified-staircase.mmt deleted file mode 100644 index f15b398..0000000 --- a/tutorial/appendix-d/res/simplified-staircase.mmt +++ /dev/null @@ -1,35 +0,0 @@ -[[protocol]] -# V start duration period repeats --80 0 250 0 0 --120 next 50 0 0 --120 next 400 0 0 --80 next 200 0 0 -40 next 1000 0 0 --120 next 500 0 0 --80 next 1000 0 0 --40 next 500 0 0 --60 next 500 0 0 --20 next 500 0 0 --40 next 500 0 0 -0 next 500 0 0 --20 next 500 0 0 -20 next 500 0 0 -0 next 500 0 0 -40 next 500 0 0 -20 next 500 0 0 -40 next 500 0 0 -0 next 500 0 0 -20 next 500 0 0 --20 next 500 0 0 -0 next 500 0 0 --40 next 500 0 0 --20 next 500 0 0 --60 next 500 0 0 --40 next 500 0 0 --80 next 1000 0 0 -40 next 500 0 0 --70 next 10 0 0 --70 next 100 0 0 --120 next 390 0 0 --80 next 500 0 0 - diff --git a/tutorial/appendix-d/res/sine-wave-data/LICENSE b/tutorial/appendix-d/res/sine-wave-data/LICENSE deleted file mode 100644 index d032dd0..0000000 --- a/tutorial/appendix-d/res/sine-wave-data/LICENSE +++ /dev/null @@ -1,49 +0,0 @@ -The data in this directory was taken from: - - https://github.com/mirams/sine-wave/ - -and: - - https://doi.org/10.6084/m9.figshare.4702546.v1 - -See: - - Sinusoidal Voltage Protocols For Rapid Characterization Of Ion Channel - Kinetics - Beattie, Hill, Bardenet, Cui, Vandenberg, Gavaghan, de Boer, Mirams - - doi: https://doi.org/10.1101/100677 - http://biorxiv.org/content/early/2017/03/13/100677 - -------------------------------------------------------------------------------- - -BSD 3-Clause License - -Copyright (c) 2017, Kylie Beattie & Gary Mirams -All rights reserved. - -Redistribution and use in source and binary forms, with or without -modification, are permitted provided that the following conditions are met: - -* Redistributions of source code must retain the above copyright notice, this - list of conditions and the following disclaimer. - -* Redistributions in binary form must reproduce the above copyright notice, - this list of conditions and the following disclaimer in the documentation - and/or other materials provided with the distribution. - -* Neither the name of the copyright holder nor the names of its - contributors may be used to endorse or promote products derived from - this software without specific prior written permission. - -THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" -AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE -IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE -DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE -FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL -DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR -SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER -CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, -OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE -OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - diff --git a/tutorial/appendix-d/res/sine-wave-data/cell-1.zip b/tutorial/appendix-d/res/sine-wave-data/cell-1.zip deleted file mode 100644 index a6e591a..0000000 Binary files a/tutorial/appendix-d/res/sine-wave-data/cell-1.zip and /dev/null differ diff --git a/tutorial/appendix-d/res/sine-wave-data/cell-7.zip b/tutorial/appendix-d/res/sine-wave-data/cell-7.zip deleted file mode 100644 index ed9aef5..0000000 Binary files a/tutorial/appendix-d/res/sine-wave-data/cell-7.zip and /dev/null differ diff --git a/tutorial/appendix-d/res/sine-wave-steps.mmt b/tutorial/appendix-d/res/sine-wave-steps.mmt deleted file mode 100644 index 3151180..0000000 --- a/tutorial/appendix-d/res/sine-wave-steps.mmt +++ /dev/null @@ -1,12 +0,0 @@ -[[protocol]] -# Level Start Length Period Multiplier --80.0 0.0 250.1 0.0 0 --120.0 250.1 50.0 0.0 0 --80.0 300.1 200.0 0.0 0 -40.0 500.1 1000.0 0.0 0 --120.0 1500.1 500.0 0.0 0 --80.0 2000.1 1000.0 0.0 0 --30.0 3000.1 3500.0 0.0 0 --120.0 6500.1 500.0 0.0 0 --80.0 7000.1 1000.0 0.0 0 - diff --git a/tutorial/appendix-e/README.md b/tutorial/appendix-e/README.md deleted file mode 100644 index 20d76b2..0000000 --- a/tutorial/appendix-e/README.md +++ /dev/null @@ -1,6 +0,0 @@ -# Appendix E: Estimating Rs and Cm - -1. Estimating Rs and Cm; a one-shot approach [![github](../img/github.svg)](1-rs-cm-one-shot.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/appendix-e/1-rs-cm-one-shot.ipynb) -2. Estimating Rs and Cm; an iterative approach (unfinished) [![github](../img/github.svg)](2-rs-cm-iterative.ipynb) [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel-new/tree/main/tutorial/appendix-e/2-rs-cm-iterative.ipynb) - -[↩ Back to the tutorial index](../README.md) diff --git a/tutorial/appendix/README.md b/tutorial/appendix/README.md new file mode 100644 index 0000000..0be92d2 --- /dev/null +++ b/tutorial/appendix/README.md @@ -0,0 +1,69 @@ +# Voltage Clamp (VC) Model Tutorial Appendices + +These appendices provide background or technical details that did not fit the main text. + +[↩ Back to the tutorial index](../README.md) + +## A: Laplace transforms and frequency response + +1. [![github](../img/github.svg)](./a-laplace/1-laplace-transforms.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/a-laplace/1-laplace-transforms.ipynb) + The Laplace transform +2. [![github](../img/github.svg)](./a-laplace/2-frequency-response) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/a-laplace/2-frequency-response.ipynb) + Analysing a dynamical system's frequency response + +## B: Op-amps in the VC model + +1. [![github](../img/github.svg)](./b-op-amps/1-op-amp.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/b-op-amps/1-op-amp.ipynb) + Ideal op amps +2. [![github](../img/github.svg)](./b-op-amps/2-non-ideal-op-amp.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/b-op-amps/2-non-ideal-op-amp.ipynb) + Models of an op amp with a finite speed +3. [![github](../img/github.svg)](./b-op-amps/3-resulting-vc-models.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/b-op-amps/3-resulting-vc-models.ipynb) + VC models based on different op-amp models + +## C: Series resistance compensation + +1. [![github](../img/github.svg)](./c-rs/1-compensation-prediction.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/c-rs/1-compensation-prediction.ipynb) + Correction-prediction ODEs +2. [![github](../img/github.svg)](./c-rs/2-rs-cm-one-shot.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/c-rs/2-rs-cm-one-shot.ipynb) + One-shot Rs and Cm estimation +3. [![github](../img/github.svg)](./c-rs/3-rs-cm-iterative.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/c-rs/3-rs-cm-iterative.ipynb) + Iterative Rs and Cm estimation + +## D: Bessel filters + +1. [![github](../img/github.svg)](./d-filters/1-bessel-filters-laplace.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/d-filters/1-bessel-filters-laplace.ipynb) + Bessel low-pass filters in the Laplace domain +2. [![github](../img/github.svg)](./d-filters/2-bessel-filters-ode.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/d-filters/2-bessel-filters-ode.ipynb) + Bessel low-pass filters in ODE form +3. [![github](../img/github.svg)](./d-filters/3-bessel-filter-ode-summary.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/d-filters/3-bessel-filter-ode-summary.ipynb) + Summary of ODE forms +4. [![github](../img/github.svg)](./d-filters/4-stimulus-filter.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/d-filters/4-stimulus-filter.ipynb) + The stimulus filter + +## E: Voltage offsets + +1. [![github](../img/github.svg)](./e-offsets/1-liquid-junction-potential.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/e-offsets/1-liquid-junction-potential.ipynb) + Liquid junction potential +2. [![github](../img/github.svg)](./e-offsets/2-offset-correction.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/e-offsets/2-offset-correction.ipynb) + Offset correction + +## Z: Parameter values + +1. [![github](../img/github.svg)](./z-parameters/1-parameter-values.ipynb) + [![nbviewer](../img/nbviewer.svg)](https://nbviewer.jupyter.org/github/CardiacModelling/VoltageClampModel/tree/main/tutorial/appendix/z-parameters/1-parameter-values.ipynb) + Parameter value estimates from the literature and from different manufacturers + diff --git a/tutorial/appendix/a-laplace/1-laplace-transforms.ipynb b/tutorial/appendix/a-laplace/1-laplace-transforms.ipynb new file mode 100644 index 0000000..e53a75b --- /dev/null +++ b/tutorial/appendix/a-laplace/1-laplace-transforms.ipynb @@ -0,0 +1,610 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "44ff9bab", + "metadata": {}, + "source": [ + "# A1: Laplace transform" + ] + }, + { + "cell_type": "markdown", + "id": "15d86196", + "metadata": {}, + "source": [ + "This notebook discusses the Laplace transform and its use in analysing a system's response to an input signal $u(t)$.\n", + "We'll need this to read classic papers and to model non-ideal op-amps and low-pass filters.\n", + "\n", + "Many details are glossed over, and concrete examples are only presented in later notebooks, so that this text is best used as a reminder, not a first introduction." + ] + }, + { + "cell_type": "markdown", + "id": "efa15e5f-b9a5-459c-be80-15e757e881fe", + "metadata": {}, + "source": [ + "Contents:\n", + "\n", + "- [Impulse response](#Impulse-response)\n", + "- [The Laplace transform](#The-Laplace-transform)\n", + "- [Transfer function](#Transfer-function)\n", + "- [Analysing systems with zeros and poles](#Analysing-systems-with-zeros-and-poles)" + ] + }, + { + "cell_type": "markdown", + "id": "2b01a012", + "metadata": {}, + "source": [ + "## Impulse response\n", + "\n", + "Let $\\delta(t)$ be the [unit impulse](https://en.wikipedia.org/wiki/Dirac_delta_function) or Dirac delta, which is commonly thought of as\n", + "\n", + "\\begin{align}\n", + "\\delta(t - t_0) = \\begin{cases}\n", + "\\infty, &t = t_0\\\\\n", + "0, &t \\neq t_0\\end{cases}\n", + "\\end{align}\n", + "\n", + "but has a more complicated \"proper\" definition as a [generalised function](https://en.wikipedia.org/wiki/Generalized_function) with properties:\n", + "\n", + "1. $$\\int_a^b \\delta(t)dt = 1 \\quad\\text{if } 0 \\in [a, b] $$\n", + "2. $$\\int_a^b \\delta(t)dt = 0 \\quad\\text{if } 0 \\notin [a, b]$$\n", + "3. $$\\int_{-\\infty}^{\\infty} \\delta(t - t_0)g(t)\\,dt = g(t_0)$$\n", + "\n", + "The response to a system driven with $\\delta$ is called the [impulse response](https://en.wikipedia.org/wiki/Impulse_response), and will be denoted here as $h(t)$." + ] + }, + { + "cell_type": "markdown", + "id": "99ecb1cd", + "metadata": {}, + "source": [ + "Impulse responses for common functions can be looked up in tables, but they can also be worked out by hand.\n", + "For example, given a system defined by \n", + "\n", + "\\begin{align}\n", + "\\dot{y}(t) + ay(t) = u(t)\n", + "\\end{align}\n", + "\n", + "where $y$ is the state, $u$ is the input and $a$ is a non-zero constant, we can fill in $u(t)=\\delta(t)$ and $y(t)=h(t)$ (by h's definition) so that \n", + "\n", + "\\begin{align}\n", + "\\dot{h}(t) + ah(t) = \\delta(t)\n", + "\\end{align}\n", + "\n", + "Next, we'll assume that the system has no response for $t < 0$ (the impulse hasn't happened yet).\n", + "At $t > 0$, we have $\\delta(t) = 0$ and so we can separate $\\frac{dh}{dt} = -ah$ as usual to find $h(t) = h_0 e^{-at}$.\n", + "The situation at $t = 0$ is tricky to analyse, but the accepted solution seems to be that (1) $h(t = 0)$ is undefined, (2) its limit approached from the left is 0, and (3) its limit approached from the right is 1.\n", + "Integrating from $0$ to $t$ we then get $h_0 = 1$, so that the full impulse response becomes\n", + "\\begin{align}\n", + "h(t) = \\begin{cases}e^{-at}, &t>0,\\\\0, &t<0\\\\\\text{undefined}, &t=0\\end{cases}\n", + "\\end{align}\n", + "\n", + "More commonly we'll ignore negative time and just write e.g. $h(t)=e^{-at}$." + ] + }, + { + "cell_type": "markdown", + "id": "4adc3514", + "metadata": {}, + "source": [ + "The integral of the unit impulse is the [unit step](https://en.wikipedia.org/wiki/Heaviside_step_function) function:\n", + "\\begin{equation}\n", + "\\theta(t - t_0) = \\begin{cases}1, &t > t_0\\\\0, &t < t_0\\\\\\text{undefined}, &t = t_0\\end{cases}\n", + "\\end{equation}\n", + "(some people use a different definition for the $t=t_0$ case).\n", + "\n", + "Using the unit step, we can write the above equation for $h(t)$ as $h(t) = e^{-at}\\theta(t)$." + ] + }, + { + "cell_type": "markdown", + "id": "724142d8", + "metadata": {}, + "source": [ + "### The superposition principle and linear systems\n", + "\n", + "Next, we introduce the [superposition principle](https://en.wikipedia.org/wiki/Superposition_principle).\n", + "This holds if, when input $u_1(t)$ has response $y_1(t)$ and input $u_2(t)$ has response $y_2(t)$, any **linear combination** of the input signals $u(t) = \\alpha_1 u_1(t) + \\alpha_2 u_2(t)$ results in the same linear combination of responses $y(t) = \\alpha_1 y_1(t) + \\alpha_2 y_2(t)$.\n", + "\n", + "The class of systems satisfying this priniciple are called [linear systems](https://en.wikipedia.org/wiki/Linear_time-invariant_system).\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "id": "4d580eaf", + "metadata": {}, + "source": [ + "### Decomposing arbitrary inputs into impulse responses\n", + "\n", + "For systems where the superposition principle holds, we can analyse the response to any input signal $u(t)$ by decomposing into sub-inputs with known responses.\n", + "If we're willing to do some maths, this can even be an infinite number of sub-inputs, for example sine waves or unit impulses.\n", + "\n", + "Let $\\delta(t - \\tau)$ be a unit impulse input, and $h(t - \\tau)$ the impulse response, we can then write $u(t)$ as a linear combination with an infinite number of terms $u(\\tau)\\delta(t - \\tau)\\,d\\tau$ (where $\\tau$ is a constant):\n", + "\\begin{align}\n", + "u(t) = \\int_{-\\infty}^\\infty u(\\tau)\\delta(t - \\tau)\\,d\\tau\n", + "\\end{align}\n", + "\n", + "writing the same linear combination for the known impulse responses $h(t - \\tau)$ we find:\n", + "\n", + "\\begin{align}\n", + "y(t) = \\int_{-\\infty}^\\infty u(\\tau)h(t - \\tau)\\,d\\tau\n", + "\\end{align}" + ] + }, + { + "cell_type": "markdown", + "id": "3fc400c8", + "metadata": {}, + "source": [ + "These horrible forms are known as \"convolution integrals\", sometimes denoted with a $*$:\n", + "\\begin{align}\n", + "(f * g)(t) = \\int_{-\\infty}^\\infty f(\\tau)g(t - \\tau)\\,d\\tau\n", + "\\end{align}\n", + "where the left hand side notation is meant to convey that this is an operation on _functions_: we are convolving the functions themselves, not their evaluations on some specific value of $t$.\n", + "Convolution is not restricted to time-varying functions: $t$ represents any free variable.\n", + "For people who love properties of things we can add that $(f * g)(t) = (g * t)(t)$." + ] + }, + { + "cell_type": "markdown", + "id": "4f089054", + "metadata": {}, + "source": [ + "In summary:\n", + "\n", + "1. The impulse function is a slightly dubious \"generalised function\" for which $\\int_a^b\\delta(t)dt=1$ if and only if $0\\in[a, b]$.\n", + "2. A system's response to being driven with a unit impulse is called its impulse response, and can be derived or looked up in tables.\n", + "3. If the system obeys the superposition principle, we can write its response to an arbitrary input signal as a convolution integral of the input and the impulse response." + ] + }, + { + "cell_type": "markdown", + "id": "5529fcd3", + "metadata": {}, + "source": [ + "## The Laplace transform\n", + "\n", + "The Laplace transform is a one-to-one mapping between function spaces: it can be applied to a function \"in the time domain\" to yield another \"in the Laplace domain\".\n", + "A typical use case is to apply the Laplace transformation, manipulate the function in ways that would have been harder in the time domain, and then transform back.\n", + "\n", + "For a function $f(t)$ on $t \\geq 0$, its Laplace transformation $F(s)$ is defined as\n", + "\n", + "\\begin{equation}\n", + "F(s) = \\int_0^\\infty f(t) e^{-st} dt\n", + "\\end{equation}\n", + "\n", + "where $s$ is the new free variable, and is a complex number (so we're mapping 1-d functions onto 2-d functions!).\n", + "\n", + "We denote this transfer as $\\mathcal{L}\\{f(t)\\} = F(s)$." + ] + }, + { + "cell_type": "markdown", + "id": "ad3c668d", + "metadata": {}, + "source": [ + "### The inverse transform?\n", + "\n", + "Being a nice one-to-one mapping, the Laplace transformation should have an inverse.\n", + "You can find it on [wikipedia](https://en.wikipedia.org/wiki/Inverse_Laplace_transform), but it's more common to rely on tables when converting back to the time domain, or to end the analysis without ever converting back." + ] + }, + { + "cell_type": "markdown", + "id": "462946d2", + "metadata": {}, + "source": [ + "### Some things are easier in the Laplace domain\n", + "\n", + "The Laplace transform has some very nice properties.\n", + "For starters, **linear combinations** stay the same:\n", + "\n", + "\\begin{align}\n", + "& \\int_0^\\infty \\left[a f(t) + b g(t)\\right] e^{-st} dt \n", + " = a \\int_0^\\infty f(t) e^{-st} dt + b \\int_0^\\infty g(t) e^{-st} dt \n", + " = aF(s) + bG(s)\n", + "\\end{align}" + ] + }, + { + "cell_type": "markdown", + "id": "36fe69b2", + "metadata": {}, + "source": [ + "#### Time-derivatives\n", + "\n", + "More surprisingly, time-derivatives become multiplications by powers of $s$.\n", + "\n", + "Starting from\n", + "\\begin{align}\n", + "\\int_0^\\infty \\dot{f}(t) e^{-st} dt\n", + "\\end{align}\n", + "\n", + "we use integration by parts $\\int U dV = UV - \\int V dU$ with $U=e^{-st}$ and $dV=\\dot{f}(t)dt$ to find\n", + "\n", + "\\begin{align}\n", + "\\int_0^\\infty \\dot{f}(t) e^{-st} dt\n", + "&= \\left[f(t)e^{-st}\\right]_0^\\infty + \\int_0^\\infty f(t)se^{-st} dt \\\\\n", + "&= 0 - f(0)e^0 + s \\int_0^\\infty f(t)e^{-st} dt \\\\\n", + "&= s F(s) - f(0)\n", + "\\end{align}\n", + "\n", + "or\n", + "\n", + "\\begin{align}\n", + "\\mathcal{L}\\{\\dot{f}(t)\\} = s F(s) - f(0)\n", + "\\end{align}\n", + "\n", + "Similarly, for second order time-derivatives we get $\\mathcal{L}\\{\\ddot{f(t)}\\} = s^2F(s) - sf(0) - \\dot{f}(0)$." + ] + }, + { + "cell_type": "markdown", + "id": "3d698bc5", + "metadata": {}, + "source": [ + "#### Convolution and impulse response\n", + "\n", + "Most importantly, ugly convolution becomes multiplication.\n", + "\n", + "To prove this, you start by writing out\n", + "\\begin{align}\n", + "\\mathcal{L}\\{f*g\\} = \\int_0^\\infty \\left(\\int_0^t f(\\tau) g(t-\\tau) \\,d\\tau \\right)e^{-st}dt\n", + "\\end{align}\n", + "and then, if you're _really_ good at integrals, you do several tricks and end up with\n", + "\\begin{align}\n", + "=F(s)G(s)\n", + "\\end{align}\n", + "\n", + "As a result, for a system with input $u$ and impulse response $h(t)$, we can replace\n", + "\\begin{align}\n", + "y(t) = \\int_{-\\infty}^\\infty u(\\tau)h(t - \\tau)\\,d\\tau\n", + "\\end{align}\n", + "with\n", + "\\begin{align}\n", + "Y(s) = H(s) U(s)\n", + "\\end{align}\n", + "\n", + "where $H(s) = Y(s)/U(s)$ is called the system's **transfer function**." + ] + }, + { + "cell_type": "markdown", + "id": "0377e8d8", + "metadata": {}, + "source": [ + "#### More properties\n", + "\n", + "There's a [list on wikipedia](https://en.wikipedia.org/wiki/Laplace_transform#Properties_and_theorems)." + ] + }, + { + "cell_type": "markdown", + "id": "5bae9ee8", + "metadata": {}, + "source": [ + "### Some transformed functions\n", + "\n", + "There are lots of tables of Laplace transforms out there, including the [Laplace transform wikipedia page](https://en.wikipedia.org/wiki/Laplace_transform).\n", + "A few famous ones are given below.\n", + "\n", + "Exponentials:\n", + "$$\\mathcal{L}\\{e^{-at}\\} = \\frac{1}{s + a}$$\n", + "\n", + "Sine & cosine:\n", + "$$\\mathcal{L}\\{\\sin(\\omega t)\\}\n", + " = \\mathcal{L}\\left\\{\\frac{e^{i \\omega t} - e^{i \\omega t}}{2i}\\right\\}\n", + " = \\frac{\\omega}{s^2 + \\omega^2}$$\n", + "\n", + "$$\\mathcal{L}\\{\\cos(\\omega t)\\}\n", + " = \\mathcal{L}\\left\\{\\frac{e^{i \\omega t} + e^{i \\omega t}}{2}\\right\\}\n", + " = \\frac{s}{s^2 + \\omega^2}$$\n", + "\n", + "The impulse function:\n", + "$$\\mathcal{L}\\{\\delta(t)\\} = 1$$\n", + "\n", + "The unit step function:\n", + "$$\\mathcal{L}\\{\\alpha \\theta(t)\\} = \\frac{\\alpha}{s}$$" + ] + }, + { + "cell_type": "markdown", + "id": "a8775509-3894-4249-a57c-3478bd1d3f09", + "metadata": {}, + "source": [ + "## Transfer function\n", + "\n", + "Summarising the above, the output $y(t)$ of a **linear system** driven by an arbitrary input signal $u(t)$ can be found by decomposing $u(t)$ into an infinite series of unit impulses.\n", + "\n", + "The resulting integral becomes a simple multiplication $Y(s) = H(s) U(s)$ in the Laplace domain.\n", + "\n", + "This means we can analyse many systems by finding and inspecting their **transfer function**:\n", + "\n", + "\\begin{align}\n", + "H(s) \\equiv Y(s)/U(s)\n", + "\\end{align}" + ] + }, + { + "cell_type": "markdown", + "id": "e8e8fa9a-1889-4ac5-8b32-8c1dcdfd07fb", + "metadata": {}, + "source": [ + "### Block diagrams\n", + "\n", + "Long transfer functions can sometimes be broken up into _block diagrams_.\n", + "\n", + "In particular, two components **in series** corresponds to a simple multiplication:\n", + "\\begin{align}\n", + "Y(s) = G_2(s) G_1(s) U(s)\n", + "\\end{align}\n", + "\n", + "\n", + "\n", + "For blocks **in parallel** we find\n", + "\\begin{align}\n", + "Y(s) = \\left[G_1(s) + G_2(s)\\right] U(s)\n", + "\\end{align}\n", + "\n", + "\n", + "\n", + "And **negative feedback** reduces to\n", + "\\begin{align}\n", + "Y(s) = \\frac{G_1(s)}{1 + G_1(s)G_2(s)} U(s)\n", + "\\end{align}\n", + "\n", + "" + ] + }, + { + "cell_type": "markdown", + "id": "347d2b70", + "metadata": {}, + "source": [ + "## Analysing systems with zeros and poles\n", + "\n", + "Many systems can be analysed in terms of their _zeros_ (values of $s$ for which $H(s)$ is zero) and _poles_ (a [particular type of singularity](https://en.wikipedia.org/wiki/Zeros_and_poles), see below).\n", + "\n", + "In particular, any n-th order linear differential equation (with all initial conditions set to 0) has a transfer function that can be written as the fraction of two polynomials:\n", + "\n", + "\\begin{align}\n", + "F(s) = \\frac{a_ms^m + a_{m-1}s^{m-1} + ...}{b_ns^n + b_{n-1}s^{n-1} + ...} = k\\frac{\\prod_{i=1}^m(s - z_i)}{\\prod_{i=1}^n(s - p_i)}\n", + "\\end{align}\n", + "\n", + "where $p_i$ are its **poles** and $z_i$ are its **zeroes**.\n", + "\n", + "Analysis of systems written this form is often simplified using [partial fraction decomposition](https://en.wikipedia.org/wiki/Partial_fraction_decomposition) to write $F$ as a sum instead of a product." + ] + }, + { + "cell_type": "markdown", + "id": "37fd5134", + "metadata": {}, + "source": [ + "### Real, imaginary, and complex poles\n", + "\n", + "We can tell a lot by looking at the poles.\n", + "Like $s$, poles can be complex numbers, and the system's behaviour differs depending on whether they are fully real, fully imaginary, or complex.\n", + "\n", + "#### Real poles result in exponential terms\n", + "\n", + "The form \n", + "\\begin{equation}\n", + "F(s) = \\frac{C_1}{s - p_1} + \\frac{C_2}{s - p_2} + ... + \\frac{C_n}{s - p_n}\n", + "\\end{equation}\n", + "where $p_i$ are all real numbers has inverse transform \n", + "$$f(t) = \\left( C_1e^{p_1t} + C_2e^{p_2t} + ... + C_ne^{p_nt} \\right) \\theta(t)$$\n", + "\n", + "Terms like $\\frac{C_i}{(s - p_i)^2}$ become $C_ite^{p_it}$, while $\\frac{C_i}{(s - p_i)^3}$ becomes $C_it^2e^{p_it}$ etc." + ] + }, + { + "cell_type": "markdown", + "id": "94652d8b", + "metadata": {}, + "source": [ + "#### Imaginary poles give oscillations\n", + "\n", + "The form\n", + "\\begin{equation}\n", + "F(s) = \\frac{C_1 + C_2s}{(s - i\\omega)(s + i\\omega)} = \\frac{C_1 + C_2s}{s^2 +\\omega^2}\n", + "\\end{equation}\n", + "has inverse\n", + "\\begin{equation}\n", + "f(t) = \\left( \\frac{1}{\\omega} C_1\\sin(\\omega t) + C_2\\cos(\\omega t)\\right) \\theta(t)\n", + "\\end{equation}" + ] + }, + { + "cell_type": "markdown", + "id": "b3fe2e42", + "metadata": {}, + "source": [ + "#### Complex poles give growing or damped oscillations\n", + "\n", + "The form\n", + "\\begin{equation}\n", + "F(s) = \\frac{C_1 + C_2s}{(s+\\sigma-i\\omega)(s+\\sigma+i\\omega)} \n", + " = \\frac{C_1 + C_2s}{(s + \\sigma)^2 +\\omega^2}\n", + "\\end{equation}\n", + "with poles $-\\sigma + i\\omega$ and $-\\sigma -i\\omega$, has inverse\n", + "\\begin{equation}\n", + "f(t) = \\left(\n", + " \\frac{C_1 - C_2\\sigma}{\\omega}e^{-\\sigma t}\\sin(\\omega t) + C_2e^{-\\sigma t}\\cos(\\omega t)\n", + "\\right) \\theta(t)\n", + "\\end{equation}\n" + ] + }, + { + "cell_type": "markdown", + "id": "e853a336", + "metadata": {}, + "source": [ + "#### Stability and oscillations\n", + "\n", + "In summary, for a system with poles $p_i = \\sigma_i + i \\omega$,\n", + "\n", + "- the system is stable only if all real parts are negative $\\sigma_i < 0$\n", + "\n", + "and\n", + "\n", + "- a system with fully real poles (all $\\omega_i = 0$) exhibits exponential behaviour,\n", + "- a system with fully imaginary poles (all $\\sigma_i = 0$) exhibits pure oscillations,\n", + "- a system with complex poles exhibits damped ($\\sigma_i < 0$) or exponentially growing ($\\sigma_i > 0$) oscillations." + ] + }, + { + "cell_type": "markdown", + "id": "5124c491", + "metadata": {}, + "source": [ + "### Free and forced response\n", + "The ODE\n", + "\\begin{align}\n", + "\\tau \\dot{y} + y(t) = u(t)\n", + "\\end{align}\n", + "\n", + "has Laplace transform \n", + "\n", + "\\begin{align}\n", + "\\tau (s Y(s) - y(0)) + Y(s) = U(s)\n", + "\\end{align}\n", + "\n", + "or\n", + "\n", + "\\begin{align}\n", + "Y(s) = \\frac{\\tau y(0)}{\\tau s + 1} + \\frac{1}{\\tau s + 1} U(s)\n", + "\\end{align}\n", + "\n", + "The first term is called the **free** or **natural response** and represents the system's response to its initial conditions.\n", + "The second term is called the **forced response**." + ] + }, + { + "cell_type": "markdown", + "id": "a120e9cb", + "metadata": {}, + "source": [ + "### First and second order systems with zeroed initial conditions\n", + "\n", + "#### A first order system with y(0) = 0\n", + "\n", + "The ODE\n", + "\\begin{align}\n", + "\\tau \\dot{y} + y(t) = u(t)\n", + "\\end{align}\n", + "\n", + "with $y(0) = 0$ has transfer function\n", + "\n", + "\\begin{align}\n", + "H(s) = \\frac{1}{1 + s\\tau} = \\frac{\\omega}{\\omega + s}\n", + "\\end{align}\n", + "\n", + "and impulse response\n", + "\n", + "\\begin{align}\n", + "h(t) = \\frac{1}{\\tau} e^{-t/\\tau}\n", + "\\end{align}" + ] + }, + { + "cell_type": "markdown", + "id": "766bf705", + "metadata": {}, + "source": [ + "#### A second order system with real & distinct poles\n", + "\n", + "The ODE\n", + "\n", + "\\begin{align}\n", + "a \\ddot{y} + b \\dot{y} + c y(t) = u(t)\n", + "\\end{align}\n", + "\n", + "with $y(0) = 0$ and $\\dot{y}(0) = 0$ has transfer function\n", + "\n", + "\\begin{align}\n", + "H(s) = \\frac{1}{a s^2 + b s + c} = \\frac{k}{(s - p_1)(s - p_2)} = \\frac{C_1}{s - p_1} + \\frac{C_2}{s - p_2}\n", + "\\end{align}\n", + "\n", + "where the last bit is a [partial fraction decomposition](https://en.wikipedia.org/wiki/Partial_fraction_decomposition).\n", + "As a result, it has impulse function\n", + "\n", + "\\begin{align}\n", + "h(t) = C_1 e^{p_1 t} + C_2 e^{p_2 t}\n", + "\\end{align}" + ] + }, + { + "cell_type": "markdown", + "id": "0edde5d4", + "metadata": {}, + "source": [ + "#### A second order system with imaginary poles\n", + "\n", + "The ODE\n", + "\\begin{align}\n", + "\\ddot{y} + 2\\zeta\\omega\\dot{y} + \\omega^2 = u(t)\n", + "\\end{align}\n", + "\n", + "with $y(0) = 0$, $\\dot{y}(0) = 0$, and $\\ddot{y}(0) = 0$, has transfer function\n", + "\n", + "\\begin{align}\n", + "H(s) = \\frac{1}{s^2 + 2\\zeta\\omega s + \\omega^2}\n", + "\\end{align}\n", + "\n", + "we can find the poles by solving $s^2 + 2\\zeta\\omega s + \\omega^2 = 0$ to find\n", + "\\begin{align}\n", + "-\\zeta \\omega \\pm \\omega \\sqrt{\\zeta^2 - 1}\n", + "\\end{align}\n", + "\n", + "If we consider the case where $\\zeta > 1$, then the poles are real and we have the system above.\n", + "For $\\zeta = 1$ we get a slightly different transfer function $\\frac{C_1s + C_2}{(s + \\omega)^2}$.\n", + "But for $0 \\leq \\zeta < 1$ the poles must be imaginary.\n", + "We can make this explicit by multiplying the term inside the square root by $-1$ and writing the poles as\n", + "\n", + "\\begin{align}\n", + "-\\zeta \\omega \\pm i \\omega \\sqrt{1 - \\zeta^2}\n", + "\\end{align}\n", + "for\n", + "\\begin{align}\n", + "H(s) = \\frac{1}{(s + \\zeta \\omega + i \\omega \\sqrt{1 - \\zeta^2})(s + \\zeta \\omega - i \\omega \\sqrt{1 - \\zeta^2})}\n", + " = \\frac{1}{(s + \\zeta \\omega)^2 + \\omega^2 (1 - \\zeta^2)}\n", + "\\end{align}\n", + "\n", + "Using the equation given above under \"poles and zeros\", we see that the impuls response is\n", + "\n", + "\\begin{align}\n", + "f(t) = \\frac{1}{\\omega \\sqrt{1 - \\zeta^2}}e^{-\\zeta\\omega t}\\sin\\left(\\omega \\sqrt{1 - \\zeta^2} t\\right) \\theta(t)\n", + " = \\frac{1}{\\omega_d}e^{-\\zeta\\omega t}\\sin\\left(\\omega_d t\\right) \\theta(t) \n", + "\\end{align}\n", + "\n", + "where $\\zeta$ is the _damping coefficient_, $\\omega$ is the _natural frequency_, and $\\omega_d = \\omega\\sqrt{1 - \\zeta^2}$ is the _damped frequency_." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/tutorial/appendix-a/2-laplace-and-filters.ipynb b/tutorial/appendix/a-laplace/2-frequency-response.ipynb similarity index 97% rename from tutorial/appendix-a/2-laplace-and-filters.ipynb rename to tutorial/appendix/a-laplace/2-frequency-response.ipynb index dbbd3e0..f3b0e9f 100644 --- a/tutorial/appendix-a/2-laplace-and-filters.ipynb +++ b/tutorial/appendix/a-laplace/2-frequency-response.ipynb @@ -5,8 +5,7 @@ "id": "44ff9bab", "metadata": {}, "source": [ - "# Appendix A2: Laplace transforms & filters\n", - "**Appendix A provides extra background for path clamp electronics.**" + "# A2: Frequency response" ] }, { @@ -14,558 +13,36 @@ "id": "15d86196", "metadata": {}, "source": [ - "This notebook discusses laplace transforms and their use in analysing a system's response to an input signal $u(t)$.\n", - "In particular, a _filter's_ response to a (co)sinusoidal input.\n", - "\n", - "It's very long and glosses over a lot of details and so is best used as a reminder, not a first introduction." - ] - }, - { - "cell_type": "markdown", - "id": "2b01a012", - "metadata": {}, - "source": [ - "## The impulse response\n", - "\n", - "Let $\\delta(t)$ be the [unit impulse](https://en.wikipedia.org/wiki/Dirac_delta_function) or Dirac delta, which is commonly thought of as\n", - "\n", - "\\begin{align}\n", - "\\delta(t - t_0) = \\begin{cases}\n", - "\\infty, &t = t_0\\\\\n", - "0, &t \\neq t_0\\end{cases}\n", - "\\end{align}\n", - "\n", - "but has a more complicated \"proper\" definition as a [generalised function](https://en.wikipedia.org/wiki/Generalized_function) with properties:\n", - "\n", - "1. $$\\int_a^b \\delta(t)dt = 1 \\quad\\text{if } 0 \\in [a, b] $$\n", - "2. $$\\int_a^b \\delta(t)dt = 0 \\quad\\text{if } 0 \\notin [a, b]$$\n", - "3. $$\\int_{-\\infty}^{\\infty} \\delta(t - t_0)g(t)\\,dt = g(t_0)$$\n", - "\n", - "The response to a system driven with $\\delta$ is called the [impulse response](https://en.wikipedia.org/wiki/Impulse_response), and will be denoted here as $h(t)$." - ] - }, - { - "cell_type": "markdown", - "id": "99ecb1cd", - "metadata": {}, - "source": [ - "Impulse responses for common functions can be looked up in tables, but they can also be worked out by hand.\n", - "For example, given a system defined by \n", - "\n", - "\\begin{align}\n", - "\\dot{y}(t) + ay(t) = u(t)\n", - "\\end{align}\n", - "\n", - "where $y$ is the state, $u$ is the input and $a$ is a non-zero constant, we can fill in $u(t)=\\delta(t)$ and $y(t)=h(t)$ (by h's definition) so that \n", - "\n", - "\\begin{align}\n", - "\\dot{h}(t) + ah(t) = \\delta(t)\n", - "\\end{align}\n", - "\n", - "Next, we'll assume that the system has no response for $t < 0$ (the impulse hasn't happened yet).\n", - "At $t > 0$, we have $\\delta(t) = 0$ and so we can separate $\\frac{dh}{dt} = -ah$ as usual to find $h(t) = h_0 e^{-at}$.\n", - "The situation at $t = 0$ is tricky to analyse, but the accepted solution seems to be that (1) $h(t = 0)$ is undefined, (2) its limit approached from the left is 0, and (3) its limit approached from the right is 1.\n", - "Integrating from $0$ to $t$ we then get $h_0 = 1$, so that the full impulse response becomes\n", - "\\begin{align}\n", - "h(t) = \\begin{cases}e^{-at}, &t>0,\\\\0, &t<0\\\\\\text{undefined}, &t=0\\end{cases}\n", - "\\end{align}\n", - "\n", - "More commonly we'll ignore negative time and just write e.g. $h(t)=e^{-at}$." - ] - }, - { - "cell_type": "markdown", - "id": "4adc3514", - "metadata": {}, - "source": [ - "The integral of the unit impulse is the [unit step](https://en.wikipedia.org/wiki/Heaviside_step_function) function:\n", - "\\begin{equation}\n", - "\\theta(t - t_0) = \\begin{cases}1, &t > t_0\\\\0, &t < t_0\\\\\\text{undefined}, &t = t_0\\end{cases}\n", - "\\end{equation}\n", - "(some people use a different definition for the $t=t_0$ case).\n", - "\n", - "Using the unit step, we can write the above equation for $h(t)$ as $h(t) = e^{-at}\\theta(t)$." - ] - }, - { - "cell_type": "markdown", - "id": "724142d8", - "metadata": {}, - "source": [ - "### The superposition principle and linear systems\n", - "\n", - "Next, we introduce the [superposition principle](https://en.wikipedia.org/wiki/Superposition_principle).\n", - "This holds if, when input $u_1(t)$ has response $y_1(t)$ and input $u_2(t)$ has response $y_2(t)$, any **linear combination** of the input signals $u(t) = \\alpha_1 u_1(t) + \\alpha_2 u_2(t)$ results in the same linear combination of responses $y(t) = \\alpha_1 y_1(t) + \\alpha_2 y_2(t)$.\n", - "\n", - "The class of systems satisfying this priniciple are called [linear systems](https://en.wikipedia.org/wiki/Linear_time-invariant_system).\n", - "\n" - ] - }, - { - "cell_type": "markdown", - "id": "4d580eaf", - "metadata": {}, - "source": [ - "### Decomposing arbitrary inputs into impulse responses\n", - "\n", - "For systems where the superposition principle holds, we can analyse the response to any input signal $u(t)$ by decomposing into sub-inputs with known responses.\n", - "If we're willing to do some maths, this can even be an infinite number of sub-inputs, for example sine waves or unit impulses.\n", - "\n", - "Let $\\delta(t - \\tau)$ be a unit impulse input, and $h(t - \\tau)$ the impulse response, we can then write $u(t)$ as a linear combination with an infinite number of terms $u(\\tau)\\delta(t - \\tau)\\,d\\tau$ (where $\\tau$ is a constant):\n", - "\\begin{align}\n", - "u(t) = \\int_{-\\infty}^\\infty u(\\tau)\\delta(t - \\tau)\\,d\\tau\n", - "\\end{align}\n", - "\n", - "writing the same linear combination for the known impulse responses $h(t - \\tau)$ we find:\n", - "\n", - "\\begin{align}\n", - "y(t) = \\int_{-\\infty}^\\infty u(\\tau)h(t - \\tau)\\,d\\tau\n", - "\\end{align}" - ] - }, - { - "cell_type": "markdown", - "id": "3fc400c8", - "metadata": {}, - "source": [ - "These horrible forms are known as \"convolution integrals\", sometimes denoted with a $*$:\n", - "\\begin{align}\n", - "(f * g)(t) = \\int_{-\\infty}^\\infty f(\\tau)g(t - \\tau)\\,d\\tau\n", - "\\end{align}\n", - "where the left hand side notation is meant to convey that this is an operation on _functions_: we are convolving the functions themselves, not their evaluations on some specific value of $t$.\n", - "Convolution is not restricted to time-varying functions: $t$ represents any free variable.\n", - "For people who love properties of things we can add that $(f * g)(t) = (g * t)(t)$." - ] - }, - { - "cell_type": "markdown", - "id": "4f089054", - "metadata": {}, - "source": [ - "In summary:\n", - "\n", - "1. The impulse function is a slightly dubious \"generalised function\" for which $\\int_a^b\\delta(t)dt=1$ if and only if $0\\in[a, b]$.\n", - "2. A system's response to being driven with a unit impulse is called its impulse response, and can be derived or looked up in tables.\n", - "3. If the system obeys the superposition principle, we can write its response to an arbitrary input signal as a convolution integral of the input and the impulse response." - ] - }, - { - "cell_type": "markdown", - "id": "5529fcd3", - "metadata": {}, - "source": [ - "## The Laplace transform\n", - "\n", - "The Laplace transform is a one-to-one mapping between function spaces: it can be applied to a function \"in the time domain\" to yield another \"in the Laplace domain\".\n", - "A typical use case is to apply the Laplace transformation, manipulate the function in ways that would have been harder in the time domain, and then transform back.\n", - "\n", - "For a function $f(t)$ on $t \\geq 0$, its Laplace transformation $F(s)$ is defined as\n", - "\n", - "\\begin{equation}\n", - "F(s) = \\int_0^\\infty f(t) e^{-st} dt\n", - "\\end{equation}\n", - "\n", - "where $s$ is the new free variable, and is a complex number (so we're mapping 1-d functions onto 2-d functions!).\n", - "\n", - "We denote this transfer as $\\mathcal{L}\\{f(t)\\} = F(s)$." + "In engineering, unlike in cell electrophysiology, the most interesting part of a system is often how it responds to a sinusoidal input.\n", + "This is called its _frequency response_, and is discussed in this notebook." ] }, { "cell_type": "markdown", - "id": "ad3c668d", + "id": "efa15e5f-b9a5-459c-be80-15e757e881fe", "metadata": {}, "source": [ - "### The inverse transform?\n", + "Contents:\n", "\n", - "Being a nice one-to-one mapping, the Laplace transformation should have an inverse.\n", - "You can find it on [wikipedia](https://en.wikipedia.org/wiki/Inverse_Laplace_transform), but it's more common to rely on tables when converting back to the time domain, or to end the analysis without ever converting back." + "- [Manual calculation example](#Manual-calculation-example)\n", + "- [General frequency response](#General-frequency-response)\n" ] }, { "cell_type": "markdown", - "id": "462946d2", - "metadata": {}, - "source": [ - "### Some things are easier in the Laplace domain\n", - "\n", - "The Laplace transform has some very nice properties.\n", - "For starters, **linear combinations** stay the same:\n", - "\n", - "\\begin{align}\n", - "& \\int_0^\\infty \\left[a f(t) + b g(t)\\right] e^{-st} dt \n", - " = a \\int_0^\\infty f(t) e^{-st} dt + b \\int_0^\\infty g(t) e^{-st} dt \n", - " = aF(s) + bG(s)\n", - "\\end{align}" - ] - }, - { - "cell_type": "markdown", - "id": "36fe69b2", - "metadata": {}, - "source": [ - "#### Time-derivatives\n", - "\n", - "More surprisingly, time-derivatives become multiplications by powers of $s$.\n", - "\n", - "Starting from\n", - "\\begin{align}\n", - "\\int_0^\\infty \\dot{f}(t) e^{-st} dt\n", - "\\end{align}\n", - "\n", - "we use integration by parts $\\int U dV = UV - \\int V dU$ with $U=e^{-st}$ and $dV=\\dot{f}(t)dt$ to find\n", - "\n", - "\\begin{align}\n", - "\\int_0^\\infty \\dot{f}(t) e^{-st} dt\n", - "&= \\left[f(t)e^{-st}\\right]_0^\\infty + \\int_0^\\infty f(t)se^{-st} dt \\\\\n", - "&= 0 - f(0)e^0 + s \\int_0^\\infty f(t)e^{-st} dt \\\\\n", - "&= s F(s) - f(0)\n", - "\\end{align}\n", - "\n", - "or\n", - "\n", - "\\begin{align}\n", - "\\mathcal{L}\\{\\dot{f}(t)\\} = s F(s) - f(0)\n", - "\\end{align}\n", - "\n", - "Similarly, for second order time-derivatives we get $\\mathcal{L}\\{\\ddot{f(t)}\\} = s^2F(s) - sf(0) - \\dot{f}(0)$." - ] - }, - { - "cell_type": "markdown", - "id": "3d698bc5", - "metadata": {}, - "source": [ - "#### Convolution and impulse response\n", - "\n", - "Most importantly, ugly convolution becomes multiplication.\n", - "\n", - "To prove this, you start by writing out\n", - "\\begin{align}\n", - "\\mathcal{L}\\{f*g\\} = \\int_0^\\infty \\left(\\int_0^t f(\\tau) g(t-\\tau) \\,d\\tau \\right)e^{-st}dt\n", - "\\end{align}\n", - "and then, if you're _really_ good at integrals, you do several tricks and end up with\n", - "\\begin{align}\n", - "=F(s)G(s)\n", - "\\end{align}\n", - "\n", - "As a result, for a system with input $u$ and impulse response $h(t)$, we can replace\n", - "\\begin{align}\n", - "y(t) = \\int_{-\\infty}^\\infty u(\\tau)h(t - \\tau)\\,d\\tau\n", - "\\end{align}\n", - "with\n", - "\\begin{align}\n", - "Y(s) = H(s) U(s)\n", - "\\end{align}\n", - "\n", - "where $H(s) = Y(s)/U(s)$ is called the system's **transfer function**." - ] - }, - { - "cell_type": "markdown", - "id": "0377e8d8", - "metadata": {}, - "source": [ - "#### More properties\n", - "\n", - "There's a [list on wikipedia](https://en.wikipedia.org/wiki/Laplace_transform#Properties_and_theorems)." - ] - }, - { - "cell_type": "markdown", - "id": "5bae9ee8", - "metadata": {}, - "source": [ - "### Some transformed functions\n", - "\n", - "There are lots of tables of Laplace transforms out there, including the [Laplace transform wikipedia page](https://en.wikipedia.org/wiki/Laplace_transform).\n", - "A few famous ones are given below.\n", - "\n", - "Exponentials:\n", - "$$\\mathcal{L}\\{e^{-at}\\} = \\frac{1}{s + a}$$\n", - "\n", - "Sine & cosine:\n", - "$$\\mathcal{L}\\{\\sin(\\omega t)\\}\n", - " = \\mathcal{L}\\left\\{\\frac{e^{i \\omega t} - e^{i \\omega t}}{2i}\\right\\}\n", - " = \\frac{\\omega}{s^2 + \\omega^2}$$\n", - "\n", - "$$\\mathcal{L}\\{\\cos(\\omega t)\\}\n", - " = \\mathcal{L}\\left\\{\\frac{e^{i \\omega t} + e^{i \\omega t}}{2}\\right\\}\n", - " = \\frac{s}{s^2 + \\omega^2}$$\n", - "\n", - "The impulse function:\n", - "$$\\mathcal{L}\\{\\delta(t)\\} = 1$$\n", - "\n", - "The unit step function:\n", - "$$\\mathcal{L}\\{\\alpha \\theta(t)\\} = \\frac{\\alpha}{s}$$" - ] - }, - { - "cell_type": "markdown", - "id": "347d2b70", - "metadata": {}, - "source": [ - "## Analysing systems with zeros and poles\n", - "\n", - "Many systems can be analysed in terms of their _zeros_ (values of $s$ for which $H(s)$ is zero) and _poles_ (a [particular type of singularity](https://en.wikipedia.org/wiki/Zeros_and_poles)).\n", - "\n", - "In particular, any n-th order linear differential equation (with all initial conditions set to 0) has a transfer function that can be written as the fraction of two polynomials:\n", - "\n", - "\\begin{align}\n", - "F(s) = \\frac{a_ms^m + a_{m-1}s^{m-1} + ...}{b_ns^n + b_{n-1}s^{n-1} + ...} = k\\frac{\\prod_{i=1}^m(s - z_i)}{\\prod_{i=1}^n(s - p_i)}\n", - "\\end{align}\n", - "\n", - "where $p_i$ are its **poles** and $z_i$ are its **zeroes**.\n", - "\n", - "Analysis of systems written this form is often simplified using [partial fraction decomposition](https://en.wikipedia.org/wiki/Partial_fraction_decomposition) to write $F$ as a sum instead of a product." - ] - }, - { - "cell_type": "markdown", - "id": "37fd5134", - "metadata": {}, - "source": [ - "### Real, imaginary, and complex poles\n", - "\n", - "We can tell a lot by looking at the poles.\n", - "Like $s$, poles can be complex numbers, and the system's behaviour differs depending on whether they are fully real, fully imaginary, or complex.\n", - "\n", - "#### Real poles result in exponential terms\n", - "\n", - "The form \n", - "\\begin{equation}\n", - "F(s) = \\frac{C_1}{s - p_1} + \\frac{C_2}{s - p_2} + ... + \\frac{C_n}{s - p_n}\n", - "\\end{equation}\n", - "where $p_i$ are all real numbers has inverse transform \n", - "$$f(t) = \\left( C_1e^{p_1t} + C_2e^{p_2t} + ... + C_ne^{p_nt} \\right) \\theta(t)$$\n", - "\n", - "Terms like $\\frac{C_i}{(s - p_i)^2}$ become $C_ite^{p_it}$, while $\\frac{C_i}{(s - p_i)^3}$ becomes $C_it^2e^{p_it}$ etc." - ] - }, - { - "cell_type": "markdown", - "id": "94652d8b", - "metadata": {}, - "source": [ - "#### Imaginary poles give oscillations\n", - "\n", - "The form\n", - "\\begin{equation}\n", - "F(s) = \\frac{C_1 + C_2s}{(s - i\\omega)(s + i\\omega)} = \\frac{C_1 + C_2s}{s^2 +\\omega^2}\n", - "\\end{equation}\n", - "has inverse\n", - "\\begin{equation}\n", - "f(t) = \\left( \\frac{1}{\\omega} C_1\\sin(\\omega t) + C_2\\cos(\\omega t)\\right) \\theta(t)\n", - "\\end{equation}" - ] - }, - { - "cell_type": "markdown", - "id": "b3fe2e42", - "metadata": {}, - "source": [ - "#### Complex poles give growing or damped oscillations\n", - "\n", - "The form\n", - "\\begin{equation}\n", - "F(s) = \\frac{C_1 + C_2s}{(s+\\sigma-i\\omega)(s+\\sigma+i\\omega)} \n", - " = \\frac{C_1 + C_2s}{(s + \\sigma)^2 +\\omega^2}\n", - "\\end{equation}\n", - "with poles $-\\sigma + i\\omega$ and $-\\sigma -i\\omega$, has inverse\n", - "\\begin{equation}\n", - "f(t) = \\left(\n", - " \\frac{C_1 - C_2\\sigma}{\\omega}e^{-\\sigma t}\\sin(\\omega t) + C_2e^{-\\sigma t}\\cos(\\omega t)\n", - "\\right) \\theta(t)\n", - "\\end{equation}\n" - ] - }, - { - "cell_type": "markdown", - "id": "e853a336", - "metadata": {}, - "source": [ - "#### Stability and oscillations\n", - "\n", - "In summary, for a system with poles $p_i = \\sigma_i + i \\omega$,\n", - "\n", - "- the system is stable only if all real parts are negative $\\sigma_i < 0$\n", - "\n", - "and\n", - "\n", - "- a system with fully real poles (all $\\omega_i = 0$) exhibits exponential behaviour,\n", - "- a system with fully imaginary poles (all $\\sigma_i = 0$) exhibits pure oscillations,\n", - "- a system with complex poles exhibits damped ($\\sigma_i < 0$) or exponentially growing ($\\sigma_i > 0$) oscillations." - ] - }, - { - "cell_type": "markdown", - "id": "5124c491", - "metadata": {}, - "source": [ - "### Free and forced response\n", - "The ODE\n", - "\\begin{align}\n", - "\\tau \\dot{y} + y(t) = u(t)\n", - "\\end{align}\n", - "\n", - "has Laplace transform \n", - "\n", - "\\begin{align}\n", - "\\tau (s Y(s) - y(0)) + Y(s) = U(s)\n", - "\\end{align}\n", - "\n", - "or\n", - "\n", - "\\begin{align}\n", - "Y(s) = \\frac{\\tau y(0)}{\\tau s + 1} + \\frac{1}{\\tau s + 1} U(s)\n", - "\\end{align}\n", - "\n", - "The first term is called the **free** or **natural response** and represents the system's response to its initial conditions.\n", - "The second term is called the **forced response**." - ] - }, - { - "cell_type": "markdown", - "id": "e8e8fa9a-1889-4ac5-8b32-8c1dcdfd07fb", - "metadata": {}, - "source": [ - "## Block diagrams\n", - "\n", - "Long transfer functions can sometimes be broken up into _block diagrams_.\n", - "\n", - "In particular, two components **in series** corresponds to a simple multiplication:\n", - "\\begin{align}\n", - "Y(s) = G_2(s) G_1(s) U(s)\n", - "\\end{align}\n", - "\n", - "\n", - "\n", - "For blocks **in parallel** we find\n", - "\\begin{align}\n", - "Y(s) = \\left[G_1(s) + G_2(s)\\right] U(s)\n", - "\\end{align}\n", - "\n", - "\n", - "\n", - "And **negative feedback** reduces to\n", - "\\begin{align}\n", - "Y(s) = \\frac{G_1(s)}{1 + G_1(s)G_2(s)} U(s)\n", - "\\end{align}\n", - "\n", - "" - ] - }, - { - "cell_type": "markdown", - "id": "a120e9cb", - "metadata": {}, - "source": [ - "### First and second order systems with zeroed initial conditions\n", - "\n", - "#### A first order system with y(0) = 0\n", - "\n", - "The ODE\n", - "\\begin{align}\n", - "\\tau \\dot{y} + y(t) = u(t)\n", - "\\end{align}\n", - "\n", - "with $y(0) = 0$ has transfer function\n", - "\n", - "\\begin{align}\n", - "H(s) = \\frac{1}{1 + s\\tau} = \\frac{\\omega}{\\omega + s}\n", - "\\end{align}\n", - "\n", - "and impulse response\n", - "\n", - "\\begin{align}\n", - "h(t) = \\frac{1}{\\tau} e^{-t/\\tau}\n", - "\\end{align}" - ] - }, - { - "cell_type": "markdown", - "id": "766bf705", - "metadata": {}, - "source": [ - "#### A second order system with real & distinct poles\n", - "\n", - "The ODE\n", - "\n", - "\\begin{align}\n", - "a \\ddot{y} + b \\dot{y} + c y(t) = u(t)\n", - "\\end{align}\n", - "\n", - "with $y(0) = 0$ and $\\dot{y}(0) = 0$ has transfer function\n", - "\n", - "\\begin{align}\n", - "H(s) = \\frac{1}{a s^2 + b s + c} = \\frac{k}{(s - p_1)(s - p_2)} = \\frac{C_1}{s - p_1} + \\frac{C_2}{s - p_2}\n", - "\\end{align}\n", - "\n", - "where the last bit is a [partial fraction decomposition](https://en.wikipedia.org/wiki/Partial_fraction_decomposition).\n", - "As a result, it has impulse function\n", - "\n", - "\\begin{align}\n", - "h(t) = C_1 e^{p_1 t} + C_2 e^{p_2 t}\n", - "\\end{align}" - ] - }, - { - "cell_type": "markdown", - "id": "0edde5d4", + "id": "8aedf673", "metadata": {}, "source": [ - "#### A second order system with imaginary poles\n", + "## Manual calculation example\n", "\n", - "The ODE\n", - "\\begin{align}\n", - "\\ddot{y} + 2\\zeta\\omega\\dot{y} + \\omega^2 = u(t)\n", - "\\end{align}\n", + "The straightforward way to find a frequency response is to write out the system as $Y(s) = H(s) U(s)$, fill in the Laplace transform of a sine or cosine for $U(s)$, multiplying, and then then working out the inverse transform.\n", "\n", - "with $y(0) = 0$, $\\dot{y}(0) = 0$, and $\\ddot{y}(0) = 0$, has transfer function\n", + "We will do this below, and work out several important concepts along the way.\n", + "Then, in the next section, we will find a much easier method.\n", "\n", - "\\begin{align}\n", - "H(s) = \\frac{1}{s^2 + 2\\zeta\\omega s + \\omega^2}\n", - "\\end{align}\n", - "\n", - "we can find the poles by solving $s^2 + 2\\zeta\\omega s + \\omega^2 = 0$ to find\n", - "\\begin{align}\n", - "-\\zeta \\omega \\pm \\omega \\sqrt{\\zeta^2 - 1}\n", - "\\end{align}\n", - "\n", - "If we consider the case where $\\zeta > 1$, then the poles are real and we have the system above.\n", - "For $\\zeta = 1$ we get a slightly different transfer function $\\frac{C_1s + C_2}{(s + \\omega)^2}$.\n", - "But for $0 \\leq \\zeta < 1$ the poles must be imaginary.\n", - "We can make this explicit by multiplying the term inside the square root by $-1$ and writing the poles as\n", - "\n", - "\\begin{align}\n", - "-\\zeta \\omega \\pm i \\omega \\sqrt{1 - \\zeta^2}\n", - "\\end{align}\n", - "for\n", - "\\begin{align}\n", - "H(s) = \\frac{1}{(s + \\zeta \\omega + i \\omega \\sqrt{1 - \\zeta^2})(s + \\zeta \\omega - i \\omega \\sqrt{1 - \\zeta^2})}\n", - " = \\frac{1}{(s + \\zeta \\omega)^2 + \\omega^2 (1 - \\zeta^2)}\n", - "\\end{align}\n", - "\n", - "Using the equation given above under \"poles and zeros\", we see that the impuls response is\n", - "\n", - "\\begin{align}\n", - "f(t) = \\frac{1}{\\omega \\sqrt{1 - \\zeta^2}}e^{-\\zeta\\omega t}\\sin\\left(\\omega \\sqrt{1 - \\zeta^2} t\\right) \\theta(t)\n", - " = \\frac{1}{\\omega_d}e^{-\\zeta\\omega t}\\sin\\left(\\omega_d t\\right) \\theta(t) \n", - "\\end{align}\n", - "\n", - "where $\\zeta$ is the _damping coefficient_, $\\omega$ is the _natural frequency_, and $\\omega_d = \\omega\\sqrt{1 - \\zeta^2}$ is the _damped frequency_." - ] - }, - { - "cell_type": "markdown", - "id": "8aedf673", - "metadata": {}, - "source": [ - "## Frequency response example: a low-pass filter\n", - "\n", - "In engineering (unlike in cell electrophysiology) the most interesting part of a system is often how it responds to a (co)sinusoidal input.\n", + "The example we use is a [low-pass filter](https://en.wikipedia.org/wiki/Low-pass_filter), for example the schematic below:\n", "\n", - "We can obtain this by filling in the laplace transform of a sine or cosine for U(s), carrying out the multiplication with H(s), and then working out the inverse transform.\n", - "We'll do this below for illustrative purposes, but skip to the next section to see why people usually don't." + "" ] }, { @@ -575,10 +52,6 @@ "source": [ "### Deriving a transfer function\n", "\n", - "The example we use is a [low-pass filter](https://en.wikipedia.org/wiki/Low-pass_filter), for example the schematic below:\n", - "\n", - "\n", - "\n", "Using Kirchoff's laws we write a differential equation for $V$ in terms of $V_\\text{in}$\n", "\n", "\\begin{align}\n", @@ -607,8 +80,7 @@ "\n", "\\begin{align}\n", "H(s) &= \\frac{\\omega}{s + \\omega}\n", - "\\end{align}\n", - "\n" + "\\end{align}" ] }, { @@ -878,7 +350,7 @@ "id": "adc1c4cc", "metadata": {}, "source": [ - "### Equations for cos and sin" + "### The low-pass filter's response to cosine and sine" ] }, { @@ -910,7 +382,7 @@ "id": "29c1de4a", "metadata": {}, "source": [ - "### Let's simulate\n", + "### Simulating a low-pass filter\n", "\n", "We now use Myokit to simulate three cases: $\\lambda = 1/2$, $\\lambda = 1$, and $\\lambda = 2$.\n", "\n", @@ -1252,17 +724,27 @@ "source": [ "## General frequency response\n", "\n", - "To see how the above examples generalise, we start with an impulse response $h(t)$ **for a stable system** and a cosine input\n", + "To see how the above examples generalise, we start with an impulse response $h(t)$ **for a stable system**, a cosine input, and $t >= 0$:\n", "\n", "$$u(t) = \\cos(\\omega t)$$\n", "to get output\n", "$$y(t) = \\int_0^t h(\\tau)\\cos(\\omega(t - \\tau))d\\tau$$\n", - "which we can write as\n", - "$$y(t) = \\int_0^\\infty h(\\tau)\\cos(\\omega(t - \\tau))d\\tau - \\int_t^\\infty h(\\tau)\\cos(\\omega(t - \\tau))d\\tau$$\n", "\n", - "This seems like a crazy thing to do, but recall that this is an equation _for a single value_ $y$ of $t$.\n", - "Because the system is _stable_, its impulse response $h(t)$ will dampen out for increasing values of $t$.\n", - "As a result, the multiplication by $h(\\tau)$ will cause **the second term to get very small for large values of the starting point of the integral, $t$**:" + "Next, we change the integration bounds to rewrite this as\n", + "\n", + "$$y(t) = \\int_0^\\infty h(\\tau)\\cos(\\omega(t - \\tau))d\\tau - \\int_t^\\infty h(\\tau)\\cos(\\omega(t - \\tau))d\\tau$$" + ] + }, + { + "cell_type": "markdown", + "id": "0ba317ac-8d75-487e-b660-7b5975fff31c", + "metadata": {}, + "source": [ + "The advantage of this formulation becomes apparent by considering the role of $h(\\tau)$ in both terms.\n", + "Because we defined our system as _stable_, its impulse response $h$ should be greatest at $t=0$ and then dampen out.\n", + "As a result, the second integral should become smaller and smaller as we start at larger $t$.\n", + "\n", + "For example, if the impulse response is a decaying exponential in the time domain:" ] }, { @@ -1399,12 +881,24 @@ "\\end{align}" ] }, + { + "cell_type": "markdown", + "id": "20fb7cbe", + "metadata": {}, + "source": [ + "## Frequency response of filters\n", + "\n", + "A general strategy to analyse filters is to look at $H(i\\omega)$, work out $|H(i\\omega)|$ and $\\angle H(i\\omega)$, and then make a Bode plot.\n", + "\n", + "Below, we show this for three simple filters." + ] + }, { "cell_type": "markdown", "id": "dba28c61", "metadata": {}, "source": [ - "### The low-pass filter again\n", + "### The first-order low-pass filter\n", "\n", "We now apply this general procedure to the low-pass filter we analysed before.\n", "Because we used $\\omega$ for its filter frequency, we'll use $\\phi$ for the input frequency and $H(i\\phi)$ for the frequency response.\n", @@ -1440,22 +934,12 @@ "\\end{align}" ] }, - { - "cell_type": "markdown", - "id": "20fb7cbe", - "metadata": {}, - "source": [ - "## More filters!\n", - "\n", - "A general strategy to analyse filters is to look at $H(i\\omega)$, work out $|H(i\\omega)|$ and $\\angle H(i\\omega)$, and then make a Bode plot." - ] - }, { "cell_type": "markdown", "id": "fd49d887", "metadata": {}, "source": [ - "### A first-order low-pass filter, one last time" + "To make the bode plot:" ] }, { @@ -1525,6 +1009,14 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "id": "f05ef4ce-56bf-4f42-82d6-26946020b98f", + "metadata": {}, + "source": [ + "For most purposes, the top panel is the most interesting: showing how the gain starts at 1 but then rapidly decreases for higher frequencies." + ] + }, { "cell_type": "markdown", "id": "159edacf", @@ -1569,6 +1061,14 @@ "plt.show()" ] }, + { + "cell_type": "markdown", + "id": "46a05f40-9663-4394-aa3a-9a85306cf868", + "metadata": {}, + "source": [ + "Here we see a very similar phase shift, but now the filter has gain 1 for high frequencies, and the gain decreases as the frequency is _lowered_." + ] + }, { "cell_type": "markdown", "id": "4291ad50", @@ -1576,11 +1076,13 @@ "source": [ "### A second-order system as a filter\n", "\n", - "Starting from\n", + "Second order systems arise in many situations.\n", + "\n", + "Starting from a form found in the previous notebook\n", "\\begin{align}\n", "H(s) = \\frac{1}{s^2 + 2 \\zeta \\omega s + \\omega^2}\n", "\\end{align}\n", - "(see above) we can derive\n", + "we can derive\n", "\\begin{align}\n", "|H(i\\phi)| &= \\frac{1}{\\sqrt{(\\omega^2 - \\phi^2)^2 + (2\\zeta\\omega\\phi)^2}} \\\\\n", "\\angle H(i\\phi) &= \\operatorname{atan2} \\left(2\\zeta\\omega\\phi, \\omega^2 + \\phi^2 \\right)\n", @@ -1634,7 +1136,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.12" } }, "nbformat": 4, diff --git a/tutorial/appendix-a/img/block-diagram-1-series.png b/tutorial/appendix/a-laplace/img/block-diagram-1-series.png similarity index 100% rename from tutorial/appendix-a/img/block-diagram-1-series.png rename to tutorial/appendix/a-laplace/img/block-diagram-1-series.png diff --git a/tutorial/appendix-a/img/block-diagram-2-parallel.png b/tutorial/appendix/a-laplace/img/block-diagram-2-parallel.png similarity index 100% rename from tutorial/appendix-a/img/block-diagram-2-parallel.png rename to tutorial/appendix/a-laplace/img/block-diagram-2-parallel.png diff --git a/tutorial/appendix-a/img/block-diagram-3-negative-feedback.png b/tutorial/appendix/a-laplace/img/block-diagram-3-negative-feedback.png similarity index 100% rename from tutorial/appendix-a/img/block-diagram-3-negative-feedback.png rename to tutorial/appendix/a-laplace/img/block-diagram-3-negative-feedback.png diff --git a/tutorial/appendix-a/img/rc-1-simple.png b/tutorial/appendix/a-laplace/img/rc-1-simple.png similarity index 100% rename from tutorial/appendix-a/img/rc-1-simple.png rename to tutorial/appendix/a-laplace/img/rc-1-simple.png diff --git a/tutorial/appendix-a/1-op-amp.ipynb b/tutorial/appendix/b-op-amps/1-op-amp.ipynb similarity index 95% rename from tutorial/appendix-a/1-op-amp.ipynb rename to tutorial/appendix/b-op-amps/1-op-amp.ipynb index 3a7f40b..1452d27 100644 --- a/tutorial/appendix-a/1-op-amp.ipynb +++ b/tutorial/appendix/b-op-amps/1-op-amp.ipynb @@ -4,8 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Appendix A1: Ideal op amps\n", - "**Appendix A provides extra background for path clamp electronics.**" + "# B1: Ideal op amps" ] }, { @@ -166,7 +165,7 @@ "source": [ "## A difference amplifier\n", "\n", - "The second active component we introduced was a differential or [_difference amplifier_](https://en.wikipedia.org/wiki/Differential_amplifier), as shown in the left panel below:" + "The second active component we introduced into the voltage clamp model, was a differential or [_difference amplifier_](https://en.wikipedia.org/wiki/Differential_amplifier), as shown in the left panel below:" ] }, { @@ -232,7 +231,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.12" } }, "nbformat": 4, diff --git a/tutorial/appendix-a/3-non-ideal-op-amp.ipynb b/tutorial/appendix/b-op-amps/2-non-ideal-op-amp.ipynb similarity index 99% rename from tutorial/appendix-a/3-non-ideal-op-amp.ipynb rename to tutorial/appendix/b-op-amps/2-non-ideal-op-amp.ipynb index a76669c..29e78b8 100644 --- a/tutorial/appendix-a/3-non-ideal-op-amp.ipynb +++ b/tutorial/appendix/b-op-amps/2-non-ideal-op-amp.ipynb @@ -5,8 +5,7 @@ "id": "730357a8", "metadata": {}, "source": [ - "# Appendix A3: Non-ideal op amps\n", - "**Appendix A provides extra background for path clamp electronics.**" + "# B2: Non-ideal op amps" ] }, { @@ -14,7 +13,7 @@ "id": "11447cae", "metadata": {}, "source": [ - "In this notebook we go a little bit further than [Appendix A1](./1-op-amp.ipynb) and consider the _speed_ of an op amp, using some of the concepts from [Appendix A2](./2-laplace-and-filters.ipynb).\n", + "In this notebook we consider the _speed_ of an op amp, using some of the concepts from Appendix A.\n", "\n", "Analysis of non-ideal op amps is usually divided into two parts:\n", "- In the _small signal_ range the amplifier acts \"linearly\": its gain within this range does not depend on the absolute values of $V_+$ and $V_-$, and there are no history effects.\n", @@ -99,7 +98,7 @@ "Op-amps are complex devices that have a very non-trivial transfer function.\n", "However, to simplify their analysis and use, they are commonly designed to have a _dominant pole_, so that we can approximate their transfer function with a _dominant pole approximation_.\n", "\n", - "For op-amps, a commonly used approximate transfer function is that of a low-pass filter (see [Appendix A2](./2-laplace-and-filters.ipynb)), with an additional amplification factor $A_0$:\n", + "For op-amps, a commonly used approximate transfer function is that of a low-pass filter (see Appendix A), with an additional amplification factor $A_0$:\n", "\n", "\\begin{align}\n", "H(s) = \\frac{V_\\text{out}}{V_\\text{in}} = A_\\text{OL}(s) = \\frac{A_0}{1 + s/\\omega_c}\n", @@ -377,7 +376,7 @@ "\n", "Given the equation above, we now repeat the analysis of the patch clamp amplifier's \"bandwidth\" shown in [Sigworth 1995a](https://doi.org/10.1007/978-1-4419-1229-9_4), but using the symbols shown below:\n", "\n", - "" + "" ] }, { @@ -432,7 +431,7 @@ "#### The patch-clamp amp as a damped harmonic oscillator\n", "\n", "We described $C_f$ as a \"stray capacitance\", but mentioned that [Weerakoon et al., 2009](https://doi.org/10.1109/TBCAS.2008.2005419) introduced an extra $C_f$ as a stability measure.\n", - "To see why, we can equate the transfer function above to the damped harmonic oscillator equation (see [Appendix A2](./2-laplace-and-filters.ipynb)):\n", + "To see why, we can equate the transfer function above to the damped harmonic oscillator equation (see Appendix A):\n", "\n", "$$ H(s) = R_f \\frac{1}{\\tau_0^2s^2 + 2\\zeta\\tau_0s + 1} $$\n", "with\n", @@ -647,7 +646,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.12" } }, "nbformat": 4, diff --git a/tutorial/appendix/b-op-amps/3-resulting-vc-models.ipynb b/tutorial/appendix/b-op-amps/3-resulting-vc-models.ipynb new file mode 100644 index 0000000..66a7877 --- /dev/null +++ b/tutorial/appendix/b-op-amps/3-resulting-vc-models.ipynb @@ -0,0 +1,1021 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "fc24dbb4", + "metadata": {}, + "source": [ + "# B3: Models without compensation" + ] + }, + { + "cell_type": "markdown", + "id": "aff7c8af", + "metadata": {}, + "source": [ + "At least two models of op-amp speed are found in the literature, and a different choice of op-amp model results in a different voltage clamp model.\n", + "Here we compare two models.\n", + "For simplicity, we focus on uncompensated patch clamp, without voltage offset or leak current." + ] + }, + { + "cell_type": "markdown", + "id": "7d17c4f4", + "metadata": {}, + "source": [ + "" + ] + }, + { + "cell_type": "markdown", + "id": "5d0303e8", + "metadata": {}, + "source": [ + "We now write an equation for the voltage at every junction, starting bottom left:\n", + "\n", + "\\begin{align}\n", + "1. && C_m\\dot{V}_m = \\frac{V_p - V_m}{R_s} - I\n", + "\\end{align}\n", + "\n", + "where $I$ is the non-capacitative current through the cell membrane." + ] + }, + { + "cell_type": "markdown", + "id": "7f702770", + "metadata": {}, + "source": [ + "Next,\n", + "\n", + "\\begin{align}\n", + "C_p\\dot{V}_p = \\frac{V_o-V_p}{R_f} + C_f\\left(\\dot{V}_o-\\dot{V}_p\\right) - \\frac{V_p-V_m}{R_s}\n", + "\\end{align}\n", + "\n", + "which can be used as a differential equation for either $V_p$\n", + "\n", + "\\begin{align}\n", + "2a. && (C_p + C_f)\\dot{V}_p = \\frac{V_o-V_p}{R_f} + C_f\\dot{V}_o - \\frac{V_p-V_m}{R_s}\n", + "\\end{align}\n", + "or $V_o$\n", + "\\begin{align}\n", + "2b. && C_f\\dot{V}_o = \\frac{V_p-V_o}{R_f} + \\left(C_p+C_f\\right)\\dot{V}_p + \\frac{V_p-V_m}{R_s}\n", + "\\end{align}" + ] + }, + { + "cell_type": "markdown", + "id": "7ff20823", + "metadata": {}, + "source": [ + "Next, we have two options for an op-amp equation:\n", + "\n", + "\\begin{align}\n", + "3a. && \\tau_a\\dot{V}_o = V_c - V_p \\\\\n", + "3b. && \\tau_c\\dot{V}_p = V_c - V_p \\\\\n", + "\\end{align}\n", + "\n", + "where $V_c$ is the command voltage.\n", + "The value $\\tau_c$ is either a constant (80 nanoseconds) or $\\tau_c = \\tau_aC_t/C_f$." + ] + }, + { + "cell_type": "markdown", + "id": "db2a73ec", + "metadata": {}, + "source": [ + "And finally\n", + "\n", + "\\begin{align}\n", + "4a. && R_f I_\\text{obs} \\equiv V_\\text{out} = V_o - V_c\n", + "\\end{align}" + ] + }, + { + "cell_type": "markdown", + "id": "24d3bbca", + "metadata": {}, + "source": [ + "This gives us two models: **(1, 2a, 3a, 4)** and **(1, 2b, 3b, 4)**." + ] + }, + { + "cell_type": "markdown", + "id": "f7e3ea4c", + "metadata": {}, + "source": [ + "## Lei-style model\n", + "\n", + "The model used in Lei et al. (2020) also starts from\n", + "\n", + "\\begin{align}\n", + "1. && C_m\\dot{V}_m = \\frac{V_p - V_m}{R_s} - I && \\text{(Equation S2.10)}\n", + "\\end{align}\n", + "\n", + "and \n", + "\n", + "\\begin{align}\n", + "3b. && \\tau_c\\dot{V}_p = V_c - V_p && \\text{(Equation S2.12)}\n", + "\\end{align}\n", + "\n", + "but then adds the relationship \n", + "\\begin{align}\n", + "5. && R_fC_f \\dot{I}_\\text{obs} = I + C_m\\dot{V}_m + C_p\\dot{V}_p - I_\\text{obs} && \\text{(Equation S2.8, S2.5)}\n", + "\\end{align}\n", + "\n", + "resulting in a model (1, 3b, 5)." + ] + }, + { + "cell_type": "markdown", + "id": "c8ad8948", + "metadata": {}, + "source": [ + "Using equation 4a, we can rewrite this as an ODE for $V_o$:\n", + "\n", + "\\begin{align}\n", + "C_f(\\dot{V}_o - \\dot{V}_c) &= I + C_m\\dot{V}_m + C_p\\dot{V}_p - \\frac{V_o - V_c}{R_f} \\\\\n", + " &= \\frac{V_p - V_m}{R_s} + C_p\\dot{V}_p - \\frac{V_o - V_c}{R_f} \\\\\n", + "\\end{align}\n", + "\n", + "\\begin{align}\n", + "2c. && C_f\\dot{V}_o = \\frac{V_c - V_o}{R_f} + C_p\\dot{V}_p + C_f\\dot{V}_c + \\frac{V_p - V_m}{R_s}\n", + "\\end{align}\n", + "\n", + "for an equivalent formulation (1, 2c, 3b, 4a).\n", + "\n", + "Comparing to\n", + "\\begin{align}\n", + "2b. && C_f\\dot{V}_o = \\frac{V_p-V_o}{R_f} + \\left(C_p+C_f\\right)\\dot{V}_p + \\frac{V_p-V_m}{R_s}\n", + "\\end{align}\n", + "\n", + "we see that the two are equal when $V_c = V_p$ and $\\dot{V}_c = \\dot{V}_p$ (so if we have a perfect op-amp, but some other filtering on the output)." + ] + }, + { + "cell_type": "markdown", + "id": "b0b8ecb8", + "metadata": {}, + "source": [ + "### Alternative formulation\n", + "\n", + "Alternatively, we can define\n", + "\n", + "\\begin{align}\n", + "4b. && R_f I_\\text{obs} = V_o - V_p\n", + "\\end{align}\n", + "\n", + "with which we can derive 2b. from equations S2.8, S2.5, and S2.10:\n", + "\n", + "\\begin{align}\n", + "R_f C_f \\dot{I}_\\text{obs} &= I_\\text{in} - I_\\text{obs} \\\\\n", + " &= I + C_m \\dot{V}_m + C_p \\dot{V}_p - I_\\text{obs} \\\\\n", + " &= \\frac{V_p - V_m}{R_s} + C_p \\dot{V}_p - I_\\text{obs} \\\\\n", + "C_f (\\dot{V}_o - \\dot{V}_p) &= \\frac{V_p - V_m}{R_s} + C_p \\dot{V}_p - \\frac{V_o - V_p}{R_f} \\\\\n", + "C_f \\dot{V}_o &= \\frac{V_p - V_m}{R_s} + \\frac{V_p - V_o}{R_f} + (C_p + C_f) \\dot{V}_p\n", + "\\end{align}\n", + "\n", + "so that we can write the same model as **(1, 2b, 3b, 4b)**." + ] + }, + { + "cell_type": "markdown", + "id": "2154fb47", + "metadata": {}, + "source": [ + "## Three models\n", + "\n", + "Summarising:\n", + "\n", + "\\begin{align}\n", + "1. && C_m\\dot{V}_m = \\frac{V_p - V_m}{R_s} - I\n", + "\\end{align}\n", + "\n", + "\\begin{align}\n", + "2a. && (C_p + C_f)\\dot{V}_p &= \\frac{V_o-V_p}{R_f} + \\frac{V_m-V_p}{R_s} + C_f\\dot{V}_o \\\\\n", + "2b. && C_f\\dot{V}_o &= \\frac{V_p-V_o}{R_f} + \\frac{V_p-V_m}{R_s} + \\left(C_p+C_f\\right)\\dot{V}_p\n", + "\\end{align}\n", + "\n", + "\\begin{align}\n", + "3a. && \\tau_a\\dot{V}_o = V_c - V_p \\\\\n", + "3b. && \\tau_c\\dot{V}_p = V_c - V_p \\\\\n", + "\\end{align}\n", + "\n", + "\\begin{align}\n", + "4a. && R_f I_\\text{obs} = V_o - V_c \\\\\n", + "4b. && R_f I_\\text{obs} = V_o - V_p\n", + "\\end{align}\n", + "\n", + "From the above, we can distill three models:\n", + "\n", + "- **Model A** - A \"Sigworth-style\" model **(1, 2a, 3a, 4a)**.\n", + "- **Model B** - A hybrid model **(1, 2b, 3b, 4a)**\n", + "- **Model C** - A \"Lei-style\" model **(1, 2b, 3b, 4b)**" + ] + }, + { + "cell_type": "markdown", + "id": "6fdd1973", + "metadata": {}, + "source": [ + "## Simulations\n", + "\n", + "We now run simulations for a single step from 0 to 10 mV, using the parameter values given in [appendix C2](../appendix-c/2-parameter-defaults.ipynb)." + ] + }, + { + "cell_type": "markdown", + "id": "c459d6e5", + "metadata": {}, + "source": [ + "### Model A (1, 2a, 3a, 4a)" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "a9d15cd3", + "metadata": {}, + "outputs": [], + "source": [ + "import myokit\n", + "\n", + "import numpy as np\n", + "import matplotlib.pyplot as plt" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "2ac99d20", + "metadata": {}, + "outputs": [], + "source": [ + "mA = myokit.parse_model('''\n", + "[[model]]\n", + "amp.Vm = -80 [mV]\n", + "amp.Vp = -80 [mV]\n", + "amp.Vo = -80 [mV]\n", + "\n", + "[engine]\n", + "time = 0 [ms] in [ms] bind time\n", + "pace = 0 bind pace\n", + "\n", + "[amp]\n", + "Rs = 15e-3 [GOhm] in [GOhm]\n", + "Cm = 25 [pF] in [pF]\n", + "Cp = 5 [pF] in [pF]\n", + "Rf = 0.5 [GOhm] in [GOhm]\n", + "Cf = 0.15 [pF] in [pF]\n", + "tau_amp = 20e-6 [ms] in [ms]\n", + "I = 5 [nS] * Vm\n", + " in [pA]\n", + "Vc = engine.pace * 1 [mV]\n", + " in [mV]\n", + "dot(Vm) = (Vp - Vm) / (Rs * Cm) - I / Cm : Equation 1\n", + " in [mV]\n", + "dot(Vp) = ((Vo - Vp) / Rf + Cf * dot(Vo) - (Vp - Vm) / Rs) / (Cf + Cp) : Equation 2a\n", + " in [mV]\n", + "dot(Vo) = (Vc - Vp) / tau_amp : Equation 3a\n", + " in [mV]\n", + "I_obs = (Vo - Vc) / Rf : Equation 4a\n", + " in [pA]\n", + "''')\n", + "mA.check_units(myokit.UNIT_STRICT)" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "cc2bcc06", + "metadata": {}, + "outputs": [], + "source": [ + "vlo, vhi = -80, 20\n", + "p = myokit.Protocol()\n", + "p.add_step(level=vlo, duration=5)\n", + "p.add_step(level=vhi, duration=10)\n", + "p.add_step(level=vlo, duration=10)" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "b421a959", + "metadata": {}, + "outputs": [], + "source": [ + "tol = 1e-8\n", + "dt = 5e-5\n", + "\n", + "sA = myokit.Simulation(mA, p)\n", + "sA.set_tolerance(tol, tol)\n", + "sA.pre(5)\n", + "dA = sA.run(20, log_interval=dt).npview()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "7d193dda", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "kw = dict(color='#aaa', ls='--')\n", + "\n", + "fig = plt.figure(figsize=(15, 4))\n", + "fig.subplots_adjust(wspace=0.3)\n", + "\n", + "ax = fig.add_subplot(1, 3, 1)\n", + "ax.set_ylabel('Vm (mV)')\n", + "ax.axhline(vlo, **kw)\n", + "ax.axhline(vhi, **kw)\n", + "ax.plot(dA.time(), dA['amp.Vm'])\n", + "\n", + "ax = fig.add_subplot(1, 3, 2)\n", + "ax.set_ylabel('Vp (mV)')\n", + "ax.plot(dA.time(), dA['amp.Vp'])\n", + "ax = ax.inset_axes((0.4, 0.15, 0.25, 0.7))\n", + "ax.plot(dA.time(), dA['amp.Vp'])\n", + "ax.set_xlim(4.998, 5.01)\n", + "\n", + "ax = fig.add_subplot(1, 3, 3)\n", + "ax.set_ylabel('I obs (pA)')\n", + "ax.plot(dA.time(), dA['amp.I_obs'])\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "58c4e632", + "metadata": {}, + "source": [ + "### Model B (1, 2b, 3b, 4a)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "16b95491", + "metadata": {}, + "outputs": [], + "source": [ + "mB = myokit.parse_model('''\n", + "[[model]]\n", + "amp.Vm = -80 [mV]\n", + "amp.Vp = -80 [mV]\n", + "amp.Vo = -80 [mV]\n", + "\n", + "[engine]\n", + "time = 0 [ms] in [ms] bind time\n", + "pace = 0 bind pace\n", + "\n", + "[amp]\n", + "Rs = 15e-3 [GOhm] in [GOhm]\n", + "Cm = 25 [pF] in [pF]\n", + "Cp = 5 [pF] in [pF]\n", + "Rf = 0.5 [GOhm] in [GOhm]\n", + "Cf = 0.15 [pF] in [pF]\n", + "tau_amp = 20e-6 [ms] in [ms]\n", + "tau_c = tau_amp * (Cf + Cp) / Cf\n", + " in [ms]\n", + "I = 5 [nS] * Vm\n", + " in [pA]\n", + "Vc = engine.pace * 1 [mV]\n", + " in [mV]\n", + "dot(Vm) = (Vp - Vm) / (Rs * Cm) - I / Cm : Equation 1\n", + " in [mV]\n", + "dot(Vo) = (Vp - Vo) / (Rf * Cf) + (Cp + Cf) / Cf * dot(Vp) + (Vp - Vm) / (Rs * Cf) : Equation 2b\n", + " in [mV]\n", + "dot(Vp) = (Vc - Vp) / tau_c : Equation 3b\n", + " in [mV]\n", + "I_obs = (Vo - Vc) / Rf : Equation 4a\n", + " in [pA]\n", + "''')\n", + "mB.check_units(myokit.UNIT_STRICT)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "02fb78e4", + "metadata": {}, + "outputs": [], + "source": [ + "sB = myokit.Simulation(mB, p)\n", + "sB.set_tolerance(tol, tol)\n", + "sB.pre(5)\n", + "dB = sB.run(20, log_interval=dt).npview()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "1745173b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(15, 4))\n", + "fig.subplots_adjust(wspace=0.3)\n", + "\n", + "ax = fig.add_subplot(1, 3, 1)\n", + "ax.set_ylabel('Vm (mV)')\n", + "ax.axhline(vlo, **kw)\n", + "ax.axhline(vhi, **kw)\n", + "ax.plot(dA.time(), dA['amp.Vm'], label='Model A')\n", + "ax.plot(dB.time(), dB['amp.Vm'], label='Model B')\n", + "ax.legend()\n", + "\n", + "ax = fig.add_subplot(1, 3, 2)\n", + "ax.set_ylabel('Vp (mV)')\n", + "ax.plot(dA.time(), dA['amp.Vp'], label='Model A')\n", + "ax.plot(dB.time(), dB['amp.Vp'], label='Model B')\n", + "ax = ax.inset_axes((0.4, 0.15, 0.25, 0.7))\n", + "ax.plot(dA.time(), dA['amp.Vp'], label='Model A')\n", + "ax.plot(dB.time(), dB['amp.Vp'], label='Model B')\n", + "ax.set_xlim(4.998, 5.005)\n", + "\n", + "ax = fig.add_subplot(1, 3, 3)\n", + "ax.set_ylabel('I obs (pA)')\n", + "ax.plot(dA.time(), dA['amp.I_obs'], label='Model A')\n", + "ax.plot(dB.time(), dB['amp.I_obs'], label='Model B')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "1f76e9e9", + "metadata": {}, + "source": [ + "Both models make very similar predictions, but we can subtract the two models to see the difference:" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "a04d57cd", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(15, 4))\n", + "fig.subplots_adjust(wspace=0.3)\n", + "ax = fig.add_subplot(1, 3, 1)\n", + "ax.set_ylabel('Vm (mV)')\n", + "ax.plot(dA.time(), dA['amp.Vm'] - dB['amp.Vm'], label='A - B')\n", + "ax.legend()\n", + "ax = fig.add_subplot(1, 3, 2)\n", + "ax.set_ylabel('Vp (mV)')\n", + "ax.plot(dA.time(), dA['amp.Vp'] - dB['amp.Vp'], label='A - B')\n", + "ax = fig.add_subplot(1, 3, 3)\n", + "ax.set_ylabel('I obs (pA)')\n", + "ax.plot(dA.time(), dA['amp.I_obs'] - dB['amp.I_obs'], label='A - B')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "ad12b0fd", + "metadata": {}, + "source": [ + "Although small, the smoothness of these curves and their magnitude is indicative of a true physical difference between the two." + ] + }, + { + "cell_type": "markdown", + "id": "45a1d294", + "metadata": {}, + "source": [ + "### Model C (1, 2b, 3b, 4b)" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "1ec11fa6", + "metadata": {}, + "outputs": [], + "source": [ + "mC = myokit.parse_model('''\n", + "[[model]]\n", + "amp.Vm = -80 [mV]\n", + "amp.Vp = -80 [mV]\n", + "amp.Vo = -80 [mV]\n", + "\n", + "[engine]\n", + "time = 0 [ms] in [ms] bind time\n", + "pace = 0 bind pace\n", + "\n", + "[amp]\n", + "Rs = 15e-3 [GOhm] in [GOhm]\n", + "Cm = 25 [pF] in [pF]\n", + "Cp = 5 [pF] in [pF]\n", + "Rf = 0.5 [GOhm] in [GOhm]\n", + "Cf = 0.15 [pF] in [pF]\n", + "tau_amp = 20e-6 [ms] in [ms]\n", + "tau_c = tau_amp * (Cf + Cp) / Cf\n", + " in [ms]\n", + "I = 5 [nS] * Vm\n", + " in [pA]\n", + "Vc = engine.pace * 1 [mV]\n", + " in [mV]\n", + "dot(Vm) = (Vp - Vm) / (Rs * Cm) - I / Cm : Equation 1\n", + " in [mV]\n", + "dot(Vo) = (Vp - Vo) / (Rf * Cf) + (Cp + Cf) / Cf * dot(Vp) + (Vp - Vm) / (Rs * Cf) : Equation 2b\n", + " in [mV]\n", + "dot(Vp) = (Vc - Vp) / tau_c : Equation 3b\n", + " in [mV]\n", + "I_obs = (Vo - Vp) / Rf : Equation 4b\n", + " in [pA]\n", + "\n", + "''')\n", + "mC.check_units(myokit.UNIT_STRICT)" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "9743a5c9", + "metadata": {}, + "outputs": [], + "source": [ + "sC = myokit.Simulation(mC, p)\n", + "sC.set_tolerance(tol, tol)\n", + "sC.pre(5)\n", + "dC = sC.run(20, log_interval=dt).npview()" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "c705e87b", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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HoHDeT5PJRERERImYouenpqYSExNT4vVjYmJ8MRebOXNmqatdixpywTnF6cwkTVMRQlSPgCmyCXGxM+fSGP/JAPZb3OhVlSG0ZurwxQQH2bROTdQwg2IAFTy+5SiEEEIIIQKDx+Ohe/fuzJgxA4AuXbqwd+9eFixYwAMPnF9ntyKrVJcVU1q8rHbtP0zq+Umiz+aUXvgUQgSWKk/9LoQW8gry+MvHN7Hf7CbY42Fa4zG8OOpTKbDVE+c72aTIJoSohHJ0IwpRHv+MyGVg43h+LjisdSoigDRs2JD27dsX29auXTuOHz8OF61SfaELV6mOi4vD4XCQkZFxyZhTp06VeP3Tp09fcrXrsLCwYjdRc8bkRHNDbh4A2flntE5HCFENpMgmAtL0D+/mV4sDi0flb62e4K4bntA6JVGLDEVFNpmTTQhRFf62AowIOJl6lWSjAQcurVMRAaRPnz4cOHCg2Lbff/+dpk29c/tduEp1kaJVqnv37g1At27dMBqNxWJSUlLYs2ePLyYxMZHMzEy2bdvmi/nxxx/JzMz0xQjt3Z+ZzeunTtPBHqR1KkKIaiDDRUXAWfHd26zWHwEUHgy/icHXPqR1SqKWGaSTTQhRBdfqW/HYoZXsDu6jdSpCiHroiSeeoHfv3syYMYNhw4axbds23nnnHd555x0oHOJ5uVWqbTYbY8aM4cknn6RBgwZERkYyZcoUOnXq5FtttF27dgwaNIixY8fy9ttvA/Dwww8zZMgQWVnUj3QrXGhii92pdSpCiGogRTYRUArsBSw5/AaqSeEaRziP3vGq1ikJDRj0JgA8yJAvIUTFGRQ9waqKSRr6hRAa6NGjB59++ilTp07l+eefp3nz5syZM4f77rvPF1OeVapnz56NwWBg2LBh5Ofnc/3117N48WL0er0v5sMPP+Txxx/3rUJ666238sYbb9TyOxZlWRWUwdsh0dydlUOIXVZyFaIukCKbCChzV07iiAlC3R6eHfyO1ukIjRj1ZgDcinSyCSGEECLwDBkyhCFDhpT5eHlWqbZYLMybN4958+aVGRMZGcnSpUurnK+oGSf0DrZZrNgVhevz0+ipdUJCiCqTIpsIGAX2Av6XuxGMCjebrqJpfDutUxIaMei9w0VdMlxUCFEJ+92pfBEVSRhZdNU6GSGEEPXeTxYLTtJ5oByxQgj/JuMkRMB49/P/R7JRIcztYfwts7ROR2jIqLcA4JbhokKISkhRM/ksNIT9pgKtUxFCCCEAKFBkARUh6gIpsomAsSF9DQD9dK2JtDXUOh2hIZOhaLioFNmEEEJoJ9qlo6XDgVUxaZ2KECLA5elkhIYQdYEMFxUBYcvu/7Hf7EZRVe6/bprW6QiNFXWyuaSTTQghhIYePRdMB8chdsY30zoVIUSAy9PJea0QdYF0somA8Nn2uQB0cphp16KH1ukIjZ3vZNM6EyFEYJIvMqJ6qfI7JYSoolxFQVXls0SIQCdFNuH3VFXlV89hAK6J6qd1OsIPmIxWAFwyXFQIIYQQQgSoC7+MO3QKmTkZGmYjhKgOUmQTfm/DrtWcMCoYVJU/93tC63SEHygqsrm1TkQIIUS99lZ4Lrc3iuMXx1GtUxFCBKBHs6P55chxdIUdbKfOHtc6JSFEFcmcbMLvfffrBwC0c5iIjmysdTrCD1hMRZ1sWmcihBCiPjtt8HDYZKJAdWidihAiQOmAF86kY/V4IF8+S4QIdNLJJvzePvs+ADoHd9Y6FeEnTAbvwgdOKbIJISqhj74l3x87wejsKK1TEUIIIbg1J5cb8/JR83K1TkUIUUVSZBN+7cy5NA6aXAAM6PqA1ukIP2ExBwHgQqpsQoiKMysGojweglW91qkIIYSox76yZvJ4TBQ/WL0XkB0557ROSQhRRTJcVPi1NT8uw6UoRLk8dGkrix4IL1+RTWpsQgghhBAiQP1hsLPdEkSox0OeToc76wgydkeIwCadbMKv/XpyHQCt3DYUnfy6Ci+rKRgAj6LgcNi1TkcIEWB+95xiRmQEP1iytU5FCCGEYFVoCE/FRLEn54DWqQghqkiqFsKvHXEeA6BNWAetUxF+xGwK8v2cZ5cvyUKIijnhOcdHtlB2G/O1TkUIIYTwyXVmaZ2CEKKKpMgm/FZuQS6HTU4Aere9Ret0hB+xWoJ9P+cVyASxQoiKUrVOQNQRNreOeKcLEzK/nxCi8gyq97iU75KLx0IEOimyCb+15dfV2HUKQR4PvTrfpHU6wo9YzeeLbAX2PE1zEUIIUX89di6Eb04k08XUQutUhBABLNhTWGRzS4e1EIFOimzCb/16xDsfW1OnEb3eqHU6wo8YDEbfFT+7Q4psQgghhBAicAV7vP9boBZonYoQooqkyCb81rGs/QA01sdonYrwQ/rC0V75UmQTQgghhBABzOrxfi3PRxb0EiLQGbROQIiynFTPANDC1l7rVIQfMqoqdhTsDpmTTQhRN3k8HpKTkwkNDUVRFK3TCTiqqpKdnU18fDy6GlqhfKEtlxRDLAMdx+heI68ghKjLxmVF83bKBj6wXcFscx4FuLROSQhRRVJkE37J7nRw3OgEdHRp+Set0xF+qOjDy+6QuSuEEHVTcnIyCQkJWqcR8JKSkmjcuHGN7DvV4Gav2cw1qnSfCCEqzoCCEWjisfHc6SRUT5TWKQkhqkiKbMIv/bR/Hfk6HWaPSo8ON2qdjvBDhsLhog6nzF0hhKiYXrrm3J+0ioPWRK1TuaTQ0FAoLBKFhYVpnU7AycrKIiEhwffvKIQQ/ipcH8EN53JJwap1KkKIKpIim/BL+45uBSDepWAyycFGlFQ0J5vdKZ1sQoiKCVJMJLjcpKn+fRpUNEQ0LCxMimxVIENthRD+ao01k4+DGnCFXqU7EKLKNChCBDr/PrsU9dbxDO+iBzFqiNapCD9lwPulyeGSTjYhhBBCCBF4Dhjt7LAEY/PAZquFTEWhv6MAi8midWpCiEqSIpvwS2n2k2CGWGOs1qkIP2VQvUU2pxTZhBAVdNCdxqaIcEy6HLppnYyoG1RV6wyEEIHMYOGRuBgAPj97gmYNW2mdkRCikmpmqSUhqug0mQA0Dm+tdSrCT+kL/9fpcmiciRAi0BxTM1gUHsbP5jytUxFCCCHQ6Y0EeTwAnM44oXU6QogqkCKb8Dset5tkg3f56isa99A6HeGn9EWdbG5Z0U0IIYQ2gjwKEW43BkVOqYUQVRPkrbGRnpWidSpCiCqQMwLhdw6d3E+2XoeiqnS9or/W6Qg/pS/8+JLhokKI2jZz5kx69OhBaGgoMTEx3H777Rw4cKBYjKqqTJ8+nfj4eKxWK/369WPv3r2a5SxqxqSMMH44fpLuJhnaJYSommCP9wJyRnaa1qkIIapAimzC7/x6aAMA0W4VW2i01ukIP+Vb+EA62YQQtWz9+vVMmDCBrVu3snbtWlwuFwMGDCA39/yqcK+88gqvv/46b7zxBtu3bycuLo4bb7yR7OxsTXMXQgjhn6yqdzKUzLwzWqcihKgCWfhA+J0TZ7zdANFuk9apCD+mV73XCNwep9apCCHqmdWrVxe7v2jRImJiYti5cyfXXXcdqqoyZ84cpk2bxtChQwFYsmQJsbGxLFu2jEceeUSjzKufw+HgbOoxss6mcij9N1LzksmzZ5HvzMHlduBR3XhUN27VzZ88zTCoHvC4+ZlkjivnC44XLxsw0JWAVfWepv6qO8NhXRYKaok4gBucjQnBCKjs1aXzu847r6s931Wj710IIapKueBTzfuZ5yCnIEPTnIQQVSNFNuF30nKPgw4iCNE6FeHHfMNF3bLwgRBCW5mZ3qJOZGQkAEeOHCE1NZUBAwb4YsxmM3379mXz5s1lFtnsdjt2+/nu3KysrBrPvSJOph3jv5sWcOjszyS70zijd/BN0kkaKioNgXejG/BNSHCZz59yfDWhhatwromK5OvQso/zTyVvJsbtBmBjZDjf2MLKjH0s9UeaurwFtZ0RNtaE2wBwFz6/Ji0NyyVNH0M/ZxLda/zVhBB1zcNZDZhzagu/tr2PP9gHOMh1ZGqdlhCiCqTIJvxOhvM0mKGBMUrrVIQf0xdOMu3ySJFNCKEdVVWZPHky11xzDR07dgQgNTUVgNjY2GKxsbGxHDt2rMx9zZw5k+eee66GM64Yj9vNh2tm8c3xT9hrtuNSFDDivaEjU68Q6taRoYQT4QqilV3BjB4Tegzo0aFDh4IOHb9EtMeimFB1eqIN57jemVPstZTCaQAA9kf14JjiPU216c5yoyu7zNhD0T1Jw4gChOjSGegq7GRzudjP/hr99zludLPHbKGrR1aqFUJUnBkdYR4Vo6KntzuWQaeP4Yko+2KFEML/SZFN+J0M1XvSHRvaVOtUhB/T4523wiXDRYUQFXS1ril3HfuCo0E9q7yviRMn8uuvv7Jx48YSjymKUuy+qqoltl1o6tSpTJ482Xc/KyuLhISEKudYWYf3/MiCdeP4JtQFFgCFxk6VNmosTULb0K5xL5wDrsEQ24wYnZ5pFdh3RdYOr0jshd1kWVlZvPGYrQLPFkII7VxhSKBXzvdsKVpmVAgRkKTIJvxOut7pPZGPaqt1KsKPFRXZ3B6Zc0cIUTGhiok2TifZHmOV9vPYY4+xatUqfvjhBxo3buzbHhcXB4UdbQ0bNvRtT0tLK9HddiGz2YzZbK5STtXlx0/foMuuvzPWpLA5KJaenkbcffUT9Op8k9apCSFEnfE/azb/tUTSwp1KW4t3WLzeIQvkCBHIZHVR4VfyCwo4XVj6bZvQRet0hB87P1xUOtmEEJVVdlfZpaiqysSJE1m5ciXfffcdzZs3L/Z48+bNiYuLY+3atb5tDoeD9evX07t37ypnXdO++WAqPX+ZhklxUWDoxvIb/s3sh9ZIgU2IGjJz5kwURWHSpEm+baqqMn36dOLj47FarfTr14+9e/cWe57dbuexxx4jKiqK4OBgbr31Vk6cOFEsJiMjgxEjRmCz2bDZbIwYMYJz587V2nsTl7bHWMCKsBBS1EyyzSY2Wy38oZ7WOi0hRBVIkU34lf1Hd+BSFAyqSpsmUmQTZfN1sqlSZBNCVMwfnrMsCA9juymnHNElTZgwgaVLl7Js2TJCQ0NJTU0lNTWV/Px8KBwmOmnSJGbMmMGnn37Knj17GDVqFEFBQQwfPrya3031mvefKfzNtYr1VgtbG42i05SvaNKkvdZpCVFnbd++nXfeeYfOnTsX2/7KK6/w+uuv88Ybb7B9+3bi4uK48cYbyc4+3+U0adIkPv30U5YvX87GjRvJyclhyJAhxRb9GD58OLt27WL16tWsXr2aXbt2MWLEiFp9j6J8DhpyeCQuhhXBZ7VORQhRBVJkE37l0IldAES7wGD0jyEzwj/pCyfEdqkyXFQIUTFH1LPMjwhnh7lyRbYFCxaQmZlJv379aNiwoe/28ccf+2KefvppJk2axPjx4+nevTsnT55kzZo1hIaGVuM7qV5bfl3N+9mrydfp+G+DK+n10Bx0er3WaQlRZ+Xk5HDffffx7rvvEhER4duuqipz5sxh2rRpDB06lI4dO7JkyRLy8vJYtmwZFK5qvHDhQl577TVuuOEGunTpwtKlS9m9ezfffvstAPv372f16tX861//IjExkcTERN59912++OILDhw4oNn7FqVRCA1qAECBIue2QgQyKbIJv5KcfgiAyCrOkyPqPkNhkc2tui8bK4QQ1UlV1VJvo0aN8sUoisL06dNJSUmhoKCA9evX+1Yf9Ucet5vXtj5DgU6hg93AK6O+hEss0iC8jCpYPR50lRx6LOq3CRMmMHjwYG644YZi248cOUJqaioDBgzwbTObzfTt25fNmzcDsHPnTpxOZ7GY+Ph4Onbs6IvZsmULNpuNnj3PL/LSq1cvbDabL+ZidrudrKysYjdRO2xB0QDk6VStUxFCVIEU2YRfSc9PAcCGLF0tLk3vK7LJ1T4hhKiqt/77Vw6YPVg8Kn/tvwCDQS52lcdT6Ta2HTtBT1NrrVMRAWb58uX89NNPzJw5s8RjqampACUWSomNjfU9lpqaislkKtYBV1pMTExMif3HxMT4Yi42c+ZM3/xtNptN0xWO6xMFiAzzLpqTp0iRTYhAJkU24VcyHekAhOnDtE5F+Lnzw0Wlk00IIarC4bDz3/QvARhAazq37qV1SkLUaUlJSfzlL39h6dKlWCyWMuOUi7pJVVUtse1iF8eUFn+p/UydOpXMzEzfLSkpqRzvSFSH6Ih4AHJ1Ci6XXEQWIlBJkU34lWyPdzLXCHO01qkIP2fQebss3EiRTQghqmLx1y+SbFQIdXuYdPubWqcjRJ23c+dO0tLS6NatGwaDAYPBwPr165k7dy4Gg8HXwXZxt1laWprvsbi4OBwOBxkZGZeMOXXqVInXP336dIkuuSJms5mwsLBiN1E7Yht4uwZVReF0ZorW6QghKqlOFtnmz59P8+bNsVgsdOvWjQ0bNmidkiinLMW7Mlt0aCOtUxF+TopsIhDI8UgEghPHv0avqlxDM18nhSifT0JzGR8bzT7nCa1TEQHk+uuvZ/fu3ezatct36969O/fddx+7du2iRYsWxMXFsXbtWt9zHA4H69evp3fv3gB069YNo9FYLCYlJYU9e/b4YhITE8nMzGTbtm2+mB9//JHMzExfjNDWg1kRfHv8JL0MLbCFNMDk8Q4VTUs/qXVqQohKMmidQHX7+OOPmTRpEvPnz6dPnz68/fbb3HTTTezbt48mTZponZ64jEydG1CIi2iudSrCzxl0BvCAW/VonYoQpZLjkR9TZb6bIif/2MvzZw8yMUNP9gMfaZ1OwDlsdLHbYuUKT+VWqhX1U2hoaImFUIKDg2nQoIFv+6RJk5gxYwatW7emdevWzJgxg6CgIIYPHw6AzWZjzJgxPPnkkzRo0IDIyEimTJlCp06dfAsptGvXjkGDBjF27FjefvttAB5++GGGDBlC27Zta/19i5JCVR2xbjdHFSMoCuPT8wlX89HlF2idmhCikupcJ9vrr7/OmDFjeOihh2jXrh1z5swhISGBBQsWlBovK+j4D7fLTbre+3Oz2HZapyP8nF5nAulkE36sIscjORbVru66BD5MTuX23AZap6K54+sWA3DKeCUtm3XSOh0hRKGnn36aSZMmMX78eLp3787JkydZs2YNoaGhvpjZs2dz++23M2zYMPr06UNQUBCff/45er3eF/Phhx/SqVMnBgwYwIABA+jcuTMffPCBRu9KlM07R97AHCN35uSiz7NrnZAQopLqVCebw+Fg586dPPvss8W2DxgwoMxlqmfOnMlzzz1XSxmKSzmWehiHznuAaZkgJ/ri0gy+Ipt0sgn/U9HjkRyLapdNsdLZ7sBhMmmdiuZCk70LHhS0v0vrVISo19atW1fsvqIoTJ8+nenTp5f5HIvFwrx585g3b16ZMZGRkSxdurRacxXVZ70llzWWcBq70+gJ5OtDwAX2nIxyPFsI4Y/qVCfbmTNncLvdl1zu+mKygo7/+CN5DwA2t4egIJvW6Qg/Z9QXFtlkmXPhhyp6PJJjkdDCtt3fMryxjgfiYml13Z+1TkcIIeqdn835LLWFcVL1FtUOm61stlpIyTqmdWpCiEqqU51sRSqy3LXZbMZsNtdSZuJSUs4cBCDcXadqv6KGGPXev1vpZBP+rLzHIzkW1a5jajoHwkJxGXLprnUyGlr7yweoioJDF0xERIzW6QQktfTTSyGEqJR/21xsM8dwd+5ubtY6GSFEpdSpakZUVBR6vf6Sy10L/5WW7e3csHlk+I64PENRJxvSySb8jxyP/NtBz2lmNYhgi7l+z323L9fbQd7OcoXWqQghhACClSAAcpyZWqcihKikOlVkM5lMdOvWrdhS1gBr166VZaoDwLn8NABCFavWqYgAYDJ4u35cinSyCf8jxyPh7/IKcjlg8k6s3bf9MK3TEUIIAQQbvAtb5LhkxWIhAlWdGy46efJkRowYQffu3UlMTOSdd97h+PHjjBs3TuvUxGXkuM6BEUL0IVqnIgKAyeAtxrq0TkSIMsjxSPiz73f8G7tOIczt4ZqrhmidTsCamh5O54Kd7OjaVutUhBB1QJgpHFyQp+ZpnYoQopLqXJHt7rvv5uzZszz//POkpKTQsWNHvvrqK5o2bap1auIycjy5AIQaw7VORQQAi9HbTu+ShQ+En5LjkfBnO494uyxbuoIwGIxapyOEEPWagneCx1BLFORAruLQOiUhRCXVuSIbwPjx4xk/frzWaYgKylXzAbBZorRORQQAs8lbZHNKkU34MTkeCX/1R95BsEALc0utU6kTVFWORUKIqosIjoEcyFNkrIYQgapOzckmAluuzglAZEhDrVMRAcDiK7JpnYkQImCVsfJ4fXB9djq3ZefQs9kArVMJaJ+F5DI5JooDrmStUxFCBKAHsiP4PCmZHoZmAETZGgOQrZM5h4UIVHWyk00EJu/BREd04cFFiEuxmINBimxCCFFhZ1KPMyLnNO5sBUf3u7ROJ6AdMDr51RJEU0+21qkIIQJQpEdPM5eLNMW7oFfzmLZM3ppBuAtUjwdFJz0xQgQaKbIJv+Bxu8nSeaslcQ2aaZ2OCABBZu/qS06kyiaEqJiuusbcePIbUq31c3685N+2EwWc0DeiaXCo1ukIIYQo1Di2JaMzvUX7nNwsQkJlrmohAo2UxoVfOHUuFXthka1pwzZapyMCgNXi/WLo0Cl43G6t0xFCBJBIJYieBXYauc1ap6KJg8d+4HejkdTg1lqnUgfIhR4hROVtsuQyN8LGEfdpAKxBYdhV72I0WWdPaZydEKIypMgm/MKJU4cAMHtUIkJjtU5HBIAga5jv53y7LHMuhBDl9ZV9G3c2bsiXUfWzyCiEEP5iuzmfd8NtJHkyAFB0On4y2dhktZB65g+t0xNCVIIU2YRfKDqIhHlUmXtAlEuINcT3c05+lqa5CCECS5J6jo9DQ9hrzNU6FU0k67xDkVrHdNE6FSGEEBRvip0RE8S4uBj2ndmtZUZCiEqSaobwC6ezTgAQ6pFfSVE+IVab7+e8AplwWghRfr95TvFiVCQbzfWvQJ9XkEtK4Yy8XVr31zodIYQQFwn2eD+kM3JStU5FCFEJUtEQfuFcrnfOgRCPSetURIAwGIwYVBWAPOlkE0KIctl14AfcioLV46F98+5apyOEEPWaWsq0jsF4h/JnFZyt/YSEEFUmRTbhFzILzgAQrFi0TkUEEGNhkS3fnqN1KkIIERB+O74NgIYuHTq9Xut0At4TGTZ+PJrE1YaWWqcihKgjgnRWAHIc57RORQhRCVJkE34hx5kJQLAuWOtURAAxeWtsUmQTQohyOp7xGwBRashlY8XlmVAIUlUMihQshRDVI0QfCkCOW0ZqCBGIpMgm/EK+x7s6ZLBBTvpF+Rl8Rbb6OXm5EEJUVFpBMgAxxhitUxFCCFE4KuNCYeYoAHI8cn4rRCAyaJ2AEAD5agEAwUbbZWOFKGIsnMiiwJmndSpCCBEQ/pRZQFfDOUKbysqi1eHL4Dw+DomkgyuFHlonI4QIOPdn2/jr2V9IbtPMty0yOA4yIVuxa5qbEKJypMgm/EI+DgBCLBFapyICSNEHmN2Rr3EmQggRGPrlphJFFr83k5VFq8Mek4NfLSFEe2RYlxCi4mLcBq5wOMm6YF7qK6I68cSR9wl1yQgfIQKRFNmEX8jXuQCwWaO0TkUEEENhJ5vDJZ1sQojyu0qJ59rUbzljaaJ1KrWqID+XKLwTacc0aat1OkIIIUrROv5K+mZmk6c6UD0eFJ3M8CREIJG/WOEXchUPABEhMkeMKL+i4aJ2p3SyCSHKL1oJoV9+Ps3cNb+i9fz582nevDkWi4Vu3bqxYcOGGn/NsvxxZBfrrFb2GIKwRcrxVgghtPajJZ93bWEkuc/6toXHxAMQpNjJyZYVRoUINFJkE34ht/A3McoWr3UqIoDoCz/CHK4CrVMRQogSPv74YyZNmsS0adP4+eefufbaa7nppps4fvy4JvnsStrMY3HRPB3bQDojhBDCD2y05DE3MpyjnvNFtqCQcH4xBvOD1UJS8gFN8xNCVJycYQnN2e0F5Oi9v4oxkQlapyMCiMFXZJNONiFE+SWrWawKCeZ3Q80ONX/99dcZM2YMDz30EO3atWPOnDkkJCSwYMGCGn3dsiRnHAYg0mPW5PWFEEKUz9OxkUyIi2F/ys9apyKEqCApsgnNnUo/6fs5PqrZJWOFuJBB9X6EOd2y+pIQovz2qClMi27AOktmjb2Gw+Fg586dDBgwoNj2AQMGsHnz5lKfY7fbycrKKnarTmfykgEI14VV636FEEJUjlLG9jCPHoC0zKRazUcIUXVSZBOaS033DpuxeFSs1lCt0xEBxID3BESKbEKIyinr603VnTlzBrfbTWxsbLHtsbGxpKamlvqcmTNnYrPZfLeEhOrt7k53eYcjRZqiq3W/Qgghqka56HAUinfO0PTcFG0SEkJUmhTZhObOnPNeWQ/xqFqnIgKMQSkssnkcWqcihBClUi765qSqaoltRaZOnUpmZqbvlpRUvR0M58gFICakfq2qWpMeO2dj/bETXG1soXUqQog6JFQJASDTcfaysUII/2LQOgEhMnK8V/SDPFLzFRWjR4psQgj/FBUVhV6vL9G1lpaWVqK7rYjZbMZsrrn50tJ1TkBHQoM2NfYa9U2QqiPS48GoyCm1EKL6hBnCgTSyXTU3rYEQomZIVUNoLjPvNABBql7rVESAMRR+qXF5nFqnIoQQxZhMJrp168batWuLbV+7di29e/eu9Xw8bjdnDd4OuubxHWv99YUQQpRfuDUGgOzCDmQhROCQy25CczkF6QBYMWqdiggw54ts0skmhPA/kydPZsSIEXTv3p3ExETeeecdjh8/zrhx42o9l7NnUnjh9FnO6PW0bNyp1l+/rloTlMeq4AhauU7RQ+tkhBAB557sUJ5IP8bZ1sXn4IyxNYW0jWQqco4rRKCRIpvQXI7D2wZtpeaGyIi6qajI5lSlk00I4X/uvvtuzp49y/PPP09KSgodO3bkq6++omnTprWeS86ZkwzJzSODUIKDZJGh6rLLbOcXSyhjPOe0TkUIEYAauY1caXewXRdUbHv7+O5M+u0NYpwy0keIQCNFNqG5fFc2GCBIZ9U6FRFgjIoJALfq0joVIUQA6aw05Oq078g01/wCAOPHj2f8+PE1/jqXk3PmJADndJFEaJ2MEEKIQqUv/Na2eTe6ZWYDkJ2ZTqgtspbzEkJUlszJJjSX584DIEgfonUqIsAYdN4hxi4psgkhKiBOCWVQbh4tXfXn4s6xM/tZb7Vw0BKudSpCCCEK7TQX8EFYKCc8GcW2h4RFkEUwAGeT/9AoOyFEZUiRTWiuQC0AIMgow1dExRh03k42F26tUxFCBBK19M6Bumxbzi9MjIthRbhH61TqpHr4KyWqYObMmfTo0YPQ0FBiYmK4/fbbOXDgQLEYVVWZPn068fHxWK1W+vXrx969e4vF2O12HnvsMaKioggODubWW2/lxIkTxWIyMjIYMWIENpsNm83GiBEjOHdOhjf7i++s+bzSIIIj7jMlHvvVFMV6q4XDJ3ZpkpsQonKkyCY0V4B3Pq1gU5jWqYgAY9IXFtlUKbIJIcovVc1mbZCVPwwFWqdSa7Ic3kWGwvRyrBVCa+vXr2fChAls3bqVtWvX4nK5GDBgALm551eSfOWVV3j99dd544032L59O3Fxcdx4441kZ2f7YiZNmsSnn37K8uXL2bhxIzk5OQwZMgS3+/x50fDhw9m1axerV69m9erV7Nq1ixEjRtT6exYV904DExPjYth5ZpvWqQghKkDmZBOasyveoX7BZpvWqYgAY9B5F8uQTjYhREX8qqbw79hoEu0ZDNM6mVqS5ckBwGaK0joVIeq91atXF7u/aNEiYmJi2LlzJ9dddx2qqjJnzhymTZvG0KFDAViyZAmxsbEsW7aMRx55hMzMTBYuXMgHH3zADTfcAMDSpUtJSEjg22+/ZeDAgezfv5/Vq1ezdetWevbsCcC7775LYmIiBw4coG3bthq8e1FeNl0oYOdsforWqQghKkA62YTmChTv0JVgi0zFLCrGqC8ssilSZBNCiEvJVrxdew2CG2qdihDiIpmZmQBERnontz9y5AipqakMGDDAF2M2m+nbty+bN28GYOfOnTidzmIx8fHxdOzY0RezZcsWbDabr8AG0KtXL2w2my/mYna7naysrGI3oY2Iwosi51wZl40VQvgPKbIJzRUV2WxBDbRORQQYk8ECgBuZY0gIIS4lU+ftGo8Jb6p1KnXKw5lhrE46STdjc61TEQFKVVUmT57MNddcQ8eOHQFITU0FIDY2tlhsbGys77HU1FRMJhMRERGXjImJiSnxmjExMb6Yi82cOdM3f5vNZiMhIaGa3qmoqOjgxgCcI/eysUII/yFFNqG5/MLfQluIDGERFVNUZHOVsfy5EEIIr0y993MyPqqF1qnUKTbVQCOXG4ti1DoVEaAmTpzIr7/+ykcffVTiMUVRit1XVbXEtotdHFNa/KX2M3XqVDIzM323pKSkCrwbUXFln8M2buAdzpuuc9RiPkKIqpIim9CUx+0mT+c9yEeGxV42XogLmQxBALgU6WQTQoiyZOVkkKfznvI1jmmjdTpCiEKPPfYYq1at4vvvv6dx48a+7XFxcXBBR1uRtLQ0X3dbXFwcDoeDjIyMS8acOnWqxOuePn26RJdcEbPZTFhYWLGb0Ea75t5hvmkGhdxcGbYrRKCQIpvQVFZeJq7CK2kNbHFapyMCjNno7WRzSiebEEKUKSvjNDPSzvDk2XPERzXROp06ZZ01j9ciwjniTtM6FRFAVFVl4sSJrFy5ku+++47mzYsPN27evDlxcXGsXbvWt83hcLB+/Xp69+4NQLdu3TAajcViUlJS2LNnjy8mMTGRzMxMtm07vzrljz/+SGZmpi9GaOvP2SG8nZpGB0PjEo+1SeiM1ePBoyj8cmiTJvkJISpOVhcVmkrLOOn7uYFNOtlExZiNRZ1sWmcihBD+y34unVty8ziLDb1BTv2q03aznV8sYYx2y8TkovwmTJjAsmXL+O9//0toaKivY81ms2G1WlEUhUmTJjFjxgxat25N69atmTFjBkFBQQwfPtwXO2bMGJ588kkaNGhAZGQkU6ZMoVOnTr7VRtu1a8egQYMYO3Ysb7/9NgAPP/wwQ4YMkZVF/URzl5ErCwrYpgsu8ZhOr2dUhoEW7jTUtJIdiUII/yRnWkJTGZneA0aQx4PBaNY6HRFgLCbvCYlLkU42IUT5tVdieD7tLLnm+tHVlX/Oe6zN1oUhSwzVFDkOifJbsGABAP369Su2fdGiRYwaNQqAp59+mvz8fMaPH09GRgY9e/ZkzZo1hIaG+uJnz56NwWBg2LBh5Ofnc/3117N48WL0er0v5sMPP+Txxx/3rUJ666238sYbb9TSOxVV1cvThK65R9madlzrVIQQ5SRFNqGpc9mnAbDKlFqiEqzmEAAc0skmhKiAxoqNXjm5bNeX7Byoi05kHOKs1UKBEkozrZMRQqCqly/KKorC9OnTmT59epkxFouFefPmMW/evDJjIiMjWbp0aaVzFTXrF7Odg8ZgTO5zpT5uD2sOOT+gZByp9dyEEJUjc7IJTWXmnQHAqkqVRFRcsMU7Ga8U2YQQomw/Z+9hYlwMy21yRUsIIfzJN0F5PBfVgMNlzOtob9CYH6wW9jgP1HpuQojKkSKb0FROvveqjcUjv4qi4kKCwgGwKwqqR748CiHK57SaywarhSR9gdap1Ipsh/dYG6xYtU5FCCFEBaRHhDIhLoaPwmR1USEChVQ2hKZy7d6Jgs3oLxsrxMWCrTYAPIpCvj1X63SEEAHiJ/Uk4+Ni+MaSrnUqtSLX5f1yFmwIvWysEEKI2qeUMSqjc+vrAEjTQ8Y5WcVYiEAgRTahqVyH98TfglHrVEQACgsJ9/2cmVM/viwLIURF5ap5AIQawy8bK4QQwn+0SuhAhNuDqihs2fO11ukIIcpBimxCUwXOHADMmLRORQSgUKsNpXDy4Oy8DK3TEUIIv5SLHYAwi6wtWt1GZ4Xx6YkUuhhlSQkhRM2Id5kB2H9iq9apCCHKQVYXFZrKd+eCHiyKucr7crvdOJ3OaslLVB+j0VhsKfnqpNPrMalgVyAnP7tGXkMIIQJdruI9NkYEx2mdSp0T5THQyukkvRrOY4QQojQNddHsJZmknENapyKEKAcpsglN2d35oAezvvKTMauqSmpqKufOlb70tdBeeHg4cXFxKGVNOFEFZlXFjkJefma171sIIeqCHJ0H0BFla6R1KkIIISooIbQ1FCST6jmjdSpCiHKQIpvQVIHqHcJi0QdVeh9FBbaYmBiCgoJqpJAjKkdVVfLy8khL807U2rBhw2p/DZN3tCi5BbLqkhCivFStE6hVj53NJs/gpnmvK7ROpc7ZbMlnk9lGjOs0V2udjBAi4NyRE8yDmSdxtoovM6Z9QiIcXM8JgwOP242uhkaICCGqR0AU2Y4ePcoLL7zAd999R2pqKvHx8dx///1MmzYNk+n8XF7Hjx9nwoQJfPfdd1itVoYPH86sWbOKxQj/YlcdAFgNIZV6vtvt9hXYGjSQuWb8kdXq7VJMS0sjJiam2oeOmlRvUTXfLsNFRc2T45EINA57AXfkeTt9M6Nl3rDqttmSzy6LjdGes1qnIiopKSmJo0ePkpeXR3R0NB06dMBsluG/ona0cRrpXJDPdl1YmTG9Ot3E85uepp3TTtrJw8Q1aVOrOQohKiYgimy//fYbHo+Ht99+m1atWrFnzx7Gjh1Lbm4us2bNgsJiy+DBg4mOjmbjxo2cPXuWkSNHoqoq8+bN0/otiDLY8c4TE2wKrdTzi+ZgCwqqfCecqHlF/32cTme1F9mMviJbTrXuV4jSyPGobriCGJ49uwGnsYnWqdS4nMyzRBb+HBIWoXE2QviHY8eO8dZbb/HRRx+RlJSEqp7vbjWZTFx77bU8/PDD3Hnnneh0sk6c0FZ4aCQdC2Jp7T7MT3s3SZFNCD8XEEW2QYMGMWjQIN/9Fi1acODAARYsWOD7UrNmzRr27dtHUlIS8fHedtvXXnuNUaNG8dJLLxEWVvrVAbvdjt1u993PypIhZ7XJrrgBsJrLvnpTHjJE1L/V5H8fb5FNpcCRW2OvIUSRmjoeybGodjVVwumVlcN2W+W6qANJ2tnj7LFaMLmN9DIExGmfEDXqL3/5C4sWLWLAgAE8//zzXH311TRq1Air1Up6ejp79uxhw4YN/O1vf+O5555j0aJF9OjRQ+u0RR211+QgSR+E4rn0cf9sxJW0PnMY59GtwOhay08IUXFVvjRz4ZeC2pSZmUlkZKTv/pYtW+jYsaPvCw3AwIEDsdvt7Ny5s8z9zJw5E5vN5rslJCTUeO7iPIfiASCokp1sQhgLP8YKnFJkE9qojuORHItETTl89gAT4mL4vxib1qkI4RdMJhOHDx/mP//5Dw888ABXXHEFoaGhGAwGYmJi+NOf/sTf//53fvvtN1555RWOHTumdcqiDvsiOI9nY6I46Eq9ZFxuo058GBbCatf2WstNCFE5FS6yffPNN4waNYqWLVtiNBoJCgoiNDSUvn378tJLL5GcnFwzmV7g8OHDzJs3j3Hjxvm2paamEhsbWywuIiICk8lEamrZH1pTp04lMzPTd0tKSqrR3EVxdsXbnh9skZP/mrBu3ToURanQyqvNmjVjzpw5NZpXdTKq3uGndle+1qmIeqi6jkdyLKpd6WoeOyxmUnTaXCisTedyvAvPWFUZ8iYEwKuvvkp0dHS5Ym+++Wb+/Oc/13hOQlxOSKvO/KNBJP8NdZCTm6l1OkKISyj3Gddnn31G27ZtGTlyJDqdjqeeeoqVK1fyzTffsHDhQvr27cu3335LixYtGDduHKdPn77sPqdPn46iKJe87dixo9hzkpOTGTRoEHfddRcPPfRQscdKG5Kmquolh6qZzWbCwsKK3UTtOV9kq3/zxIwaNQpFUYp9OS8yfvx4FEVh1KhRmuRWHidOnMBkMnHFFdquVmfEW2RzSJGt3rHb7WzYsIEPPviAt99+m5UrV3LkyJFK7Uvr45Eci2rXNk4wumEsX1nPaJ1KjcvK807Ib1VlNTohyiMjI4N58+Zx1VVXaZ2KED492vcnwu3BqSis3f6R1ukIIS6h3JNzzJgxg1mzZjF48OBSJwAdNmwYACdPnuSf//wn77//Pk8++eQl9zlx4kTuueeeS8Y0a3Z+Jazk5GT69+9PYmIi77zzTrG4uLg4fvzxx2LbMjIycDqdJToKhP8oKPxVCgsO1zoVTSQkJLB8+XJmz57tW4WzoKCAjz76iCZN/HtC7sWLFzNs2DB++OEHNm3aRJ8+fTTJw1BUZHMXaPL6ovZt3ryZefPm8dlnn+FwOAgPD/fNpWO322nRogUPP/ww48aNIzS0fEPR5Xgk6qpsewYAVtWodSpC+LVvv/2WhQsX8tlnnxEVFcXQoUO1TknUA6qiliMKdHo9rZ1hbNPnsO3I19zRr+RFeiGEfyh3kW3btm3limvUqBGvvPJKuWKjoqKIiooqV+zJkyfp378/3bp1Y9GiRSUKfYmJibz00kukpKTQsGFDKJx82mw2061bt3K9hqhdHrebgsKuDltwg2rbr6qq5Dvd1ba/irAa9RWa5L9r16788ccfrFy5kvvuuw+AlStXkpCQQIsWLYrF2u12nnrqKZYvX05WVhbdu3dn9uzZxSbj/eqrr5g0aRJJSUn06tWLkSNHlnjNzZs38+yzz7J9+3aioqK44447mDlzJsHBweXOW1VVFi1axPz582ncuDELFy7UrMhmVLwfYw6PFNnqg9tuu43t27czfPhwvvnmG7p3715sdeE//viDDRs28NFHH/H666/z/vvvc+ONN152v3I8EnVVnsM7mbZVMWudSp00PNvGM2d/5VQb/74wJkp3/PhxFi1axKJFi8jJySEjI4NPPvmEO++8U+vURH1Tjq8P7W1d2GbfwAFn5br2hRC1o0LLTE2aNImHHnqIjh071lxGpUhOTqZfv340adKEWbNmFRuKGhcXB8CAAQNo3749I0aM4NVXXyU9PZ0pU6YwduxYGXbjp7LzM/EUFdlCy/fltjzynW7a/79vqm1/FbHv+YEEmSq2etvo0aNZtGiRr8j23nvv8eCDD7Ju3bpicU8//TQrVqxgyZIlNG3alFdeeYWBAwdy6NAhIiMjSUpKYujQoYwbN45HH32UHTt2lOgm3b17NwMHDuSFF15g4cKFnD59mokTJzJx4kQWLVpU7py///578vLyuOGGG2jcuDE9e/bkn//8Z7m7hqqTUfF2ZzjddX9uJeH9rP/3v/+NyWQq9fEWLVrQokULRo4cyd69e6t9nlA5HtUR5WscKNXRo0d54YUX+O6770hNTSU+Pp7777+fadOmFfu9PH78OBMmTOC7777DarUyfPhwZs2aVebvbk3JdWWDASw6a62+bn3R0G2go8NBnmLROhVRAZ988gn/+te/2LRpEzfffDP//Oc/uemmmwgODqZdu3ZapydEqW7s+gCLt2zgkMlDUupBEuJaa52SEKIUFZoFd/Xq1Vx55ZVcffXVvPPOO2RlXXqp4eqyZs0aDh06xHfffUfjxo1p2LCh71ZEr9fz5ZdfYrFY6NOnD8OGDeP2229n1qxZtZKjqLiMrPNz4UTaYjTNRUsjRoxg48aNHD16lGPHjrFp0ybuv//+YjG5ubksWLCAV199lZtuuon27dvz7rvvYrVaWbhwIQALFiygRYsWzJ49m7Zt23LfffeVmNPt1VdfZfjw4UyaNInWrVvTu3dv5s6dy/vvv09BQfk7wRYuXMg999yDXq+nQ4cOtGrVio8//ria/kUqxlBYZHN4HJq8vqhdEyZMKHXKgtJ06NChXF1sFSHHo7qm/J3HRX777Tc8Hg9vv/02e/fuZfbs2bz11lv89a9/9cW43W4GDx5Mbm4uGzduZPny5axYseKy02jUhHxPHgBWffm7lYWo64YPH0737t1JTU3l3//+N7fddlutF8CFqKjObXrRxKGiKgqrNi3QOh0hRBkq1HLz22+/sWnTJt577z2mTJnC5MmTGTp0KA899BDXXXddjSU5atSock0A36RJE7744osay0NUr8xsbweIUVUxm6rvCrvVqGff8wOrbX8Vfe2KioqKYvDgwSxZsgRVVRk8eHCJYWuHDx/G6XQWG5JpNBq5+uqr2b9/PwD79++nV69exYarJiYmFtvPzp07OXToEB9++KFvm6qqeDwejhw5Uq6rt+fOnWPlypVs3LjRt+3+++/nvffeKzH5e20w6bxDoJyqFNnqi4YNGzJy5EgefPBB2rdvX6uvLccjMWjQIAYNGuS736JFCw4cOMCCBQt8hdQ1a9awb98+kpKSiI+PB+C1115j1KhRvPTSS7Xa0dg7z0xidjrEXF9rr1mfbDfn87MplDB3OldrnYwotwcffJD58+ezfv16RowYwd13301ERP1bhEto75acIIZnHkZp2bAc0dBB35xk9QhnUrfWeG5CiMqp8Hruffr0YeHChaSmpjJv3jyOHj1Kv379aN26Nf/4xz+qfWiOqLuy8ryTMVs8VRi3UwpFUQgyGTS5VWQ+tgs9+OCDLF68mCVLlvDggw+WeFxVVd97u3h70baimEvxeDw88sgj7Nq1y3f75ZdfOHjwIC1btixXrsuWLaOgoICePXtiMBgwGAw888wzbNmyhX379pXzHVcfo8575dmlumr9tYU2Jk+ezOeff06nTp1ITExk4cKF5OTkaJ2WqMcyMzOJjIz03d+yZQsdO3b0FdgABg4ciN1uZ+fOnWXux263k5WVVexWVR3zXdyXlUObkFZV3pcoaYM1j9cjIzjqOV2OaOEv3nnnHVJSUnj44Yf56KOPaNiwIbfddpvvwqMQtaWDw8SQ3Dxi9OW7+HJv10msO36SqWm/kX2u7q+QLUQgqnCRrUhQUBCjR4/mhx9+4ODBgwwbNoxXXnml2OprQlxKdm5hka16a2wBadCgQTgcDhwOBwMHluzCa9WqFSaTqVj3mNPpZMeOHb7us/bt27N1a/GrWhff79q1K3v37qVVq1YlbuUdJrFw4UKefPLJEoW6/v37895771XyX6DyTHrvPDhOpMhWX0ydOpUDBw6wbt06rrjiCiZNmkTDhg0ZPXo0mzZt0jo9EQDa0IBJ6Rl0d1S9o+zw4cPMmzePcePOr/SWmppaYiXZiIgITCYTqampZe5r5syZ2Gw23y0hIaHK+Zld2QAYgurnKt5ClMVqtTJy5EjWr1/P7t27ad++PbGxsfTp04fhw4ezcuVKrVMUooSrrvwT6TTGpLg58N0HWqcjhChFpYtsRXJzc1m/fj3r16/n3Llz5e6GESK3IBMAs1q57q+6RK/Xs3//fvbv349eX3LIaXBwMI8++ihPPfUUq1evZt++fYwdO5a8vDzGjBkDwLhx4zh8+DCTJ0/mwIEDLFu2jMWLFxfbT1HH2YQJE9i1axcHDx5k1apVPPbYY+XKc9euXfz000++BVAuvN177728//77OJ3OavpXKR9jUZFNOtnqnWuvvZZFixaRmprKnDlzOHToENdeey1t27Yt9yrXon5qoUQyJjObK13nF2uZPn06iqJc8rZjx45i+0lOTmbQoEHcddddJYbLl9bZfGH3cWmmTp1KZmam75aUlFTl9/q7MYefzSY8QSFV3pcQdVXr1q2ZOXMmSUlJLF26lLy8PO69916t0xL1wEGDg/8FWUn3lK8jX1EUUprdAUDegSV43O4azlAIUVGVLrL98MMPjB49mri4OP7yl7/Qpk0bNmzY4JsfSojLybN7i2wmKbIBEBYWdsl5ev7xj39w5513MmLECLp27cqhQ4f45ptvfHOINGnShBUrVvD5559z5ZVX8tZbbzFjxoxi++jcuTPr16/n4MGDXHvttXTp0oW//e1vxSZtv5SFCxfSvn17rrjiihKP3X777aSnp/P5559X+L1XhVnvnc/PiZxk1FfBwcGMGTOGDRs28Pnnn3PmzBmmTp2qdVoiwEycONF3saOs24WrqycnJ9O/f38SExN55513iu0rLi6uRMdaRkYGTqezRIfbhcxms+9YcLljQnnNioIH4uPIMNbuBZB6o5LTRAj/pNPpuOWWW/jss8+qpcgtxOWsCM1jUmw0v7tSyv2ctoPG8WhMDBPi3aza8G6N5ieEqLgKLXxw4sQJlixZwuLFizl8+DA9e/Zk9uzZ3HPPPYSEyBVSUTF5Du8QFpNa8cUC6oKLu8wu9tlnnxW7b7FYmDt3LnPnzi3zOUOGDGHIkCHFto0ePbrY/R49erBmzZoy93H06NEyH5s3b16Zj0VHR+Ny1X43mclohQJwKVJkq6/y8vL4+OOPWbRoEZs2baJly5Y89dRTWqcl/FimWsBek5EzuvMLpkRFRZVYdKYsJ0+epH///nTr1o1FixaVWPE2MTGRl156iZSUFN9FjDVr1mA2m+nWrVs1v5tLy9V5i0CRtrhafV0hAsWBAweYN28e+/fvR1EUrrjiCh577DHatm2rdWpClKpBTDw6Q0MggxUH/sXt/caV41lCiNpSoU62Zs2aMXfuXG677Tb27t3Lli1beOihh6TAJiol3+Fti66vRTZRPSzGIACcyETF9c2GDRt48MEHiYuLY+LEiTRv3pzvv/+e33//nWeffVbr9IQf28xx7mnUkFWWik9Wn5ycTL9+/UhISGDWrFmcPn2a1NTUYp1rAwYMoH379owYMYKff/6Z//3vf0yZMoWxY8fW6sqiBfY87IVFtgZhZXfQCVFf/ec//6Fjx47s3LmTK6+8ks6dO/PTTz/RsWNH/v3vf2udnhBluq/X/2FQVXZZ7Kz47g2t0xFCXKBCnWyffPIJt956KwZDhZ4mRKnsrlwATIr8PonKsxiDAXAosoJGfTFjxgxfR3X37t159dVXuffee2u1eCHqrzVr1nDo0CEOHTpE48aNiz1WtMqzXq/nyy+/ZPz48fTp0wer1crw4cOZNWtWreZ6OuN84S8qvHzTAghRnzz99NNMnTqV559/vtj2v//97zzzzDPcddddmuUmxKX07jyAa7ZGs858hiWH3+bm3qOxWoK1TksIUdEi29ChQ4vdT0tLIy0trcRS1507d66e7ESdVuDKB8CEUetURACzmrwTlzulyFZvzJ49m/vvv58xY8YUmyNLiIqqzKfGqFGjGDVq1GXjmjRpwhdffFGpvKpLRtYpAIyqSnBQ6GXjRcXdlRPGY+nHyGjZuBzRwt+kpqbywAMPlNh+//338+qrr2qSkxDlNXHAHH76bjhHTDpe+Og+Zoz+rBzPEkLUtEq1EO3cuZORI0eyf/9+31VbRVF8q2a5ZZUTUQ4Odz7owaSYtE5FBLAgixTZ6pvk5GSMRinOC3E553LSAAjyyOdjTUlwGbmqwM42XZDWqYhK6NevHxs2bKBVq1bFtm/cuJFrr71Ws7yEKI+2za7k3rCbeDv3G75QDtH6i+cYPeTvWqclRL1XqSLb6NGjadOmDQsXLiQ2NvaSy9ELURa7p0CKbKLKiopsDvkYqjcuLLBt27aNdevWldpV/frrr2uQnRD+IzPnDAAWmbJSiFLdeuutPPPMM+zcuZNevXoBsHXrVv7973/z3HPPsWrVqmKxQvibCUNfYd+/dnBQf4ruu95ir+1KOlx7u9ZpCQ3YC/Jw2AsItUVqnUq9V6ki25EjR1i5cmWJqz5CVIRD9a7qZtZbtE5FBLAgs3ceLrsU++udGTNm8H//93+0bdu2xAUfufgjBNhcBp4+m0EOcsJdU3aZCtivD8HqydA6FVEJ48ePB2D+/PnMnz+/1McoPKbISB1REwblWrgjJxVri8otTqPodLw64kt2zLuFTq5kHN8+yLbk/XT/89Po9LK4XH2S/4/WhJND9hNHpNCmsUoV2a6//np++eUXKbKJKpEim6gOIUE2AOwKeNxuOaGoR/75z3/y3nvvlWt+LCHqo1AnjMjK5jdjgtap1FnfW3P5yRLJSHea1qmISri4A1qI2tbFbqKTPZcd+vBK7yPYGkzPx79k+xv30iPne04mzeO1hR/zQPvHGXzNg9War/Bf4eQAcHzPFjr0Gax1OvVapYps//rXvxg5ciR79uyhY8eOJebGkXZqUR5O1QWA2SDzmIjKCw3xXqlRFYWcgkzCguXKTX2h0+no06eP1mmIANSSSB7JyMRgbKJ1KjXKlZ8NgEMvx9maIrPdCSH8gcVipdsTK1i3/EXmFHxMusHNs4dns3DfHHoEd+VPne+lR/sb5GK0ELWgUkW2zZs3s3HjRr7++usSj0k7tSgvB94im8Ugy02LyosMi/b9fC7rjBTZ6pEnnniCN998kzlz5midiggwrZUoEs9lsi08TOtUatTp/FR+Nps4bTIh674L4bV8+XLuueeecsUmJSVx/PjxOnFBZ/78+bz66qukpKTQoUMH5syZI4s7+IE/jC6yFQt5ntwq70un19Pvvr8ze//1vPvDVLaYMzhohoOunSz7aScNtnnoVRDMHbouEN4Eg60hx6wFxIQ3wRbcgPDQKMJtMQRbQtHpdNXy/oSojypVZHv88ccZMWIEf/vb34iNrdz4cSEcircYazWGaJ1KnbVu3Tr69+9PRkYG4eHla0Nv1qwZkyZNYtKkSTWeX3WwmoMwqipOReFc9hmaNGyjdUqilkyZMoXBgwfTsmVL2rdvX6KreuXKlZrlJoQ/2Oo4wKfxcfSx5zBA62SE8BMLFixg+vTpjB49mltvvZV27doVezwzM5NNmzaxdOlSvv32WxYuXKhZrtXl448/ZtKkScyfP58+ffrw9ttvc9NNN7Fv3z6aNKnbHb3+7qOwPPaaY3jEdZIbqmmfXdtdw4J2Gzhw7Fc+Xv8yewr2csjk4qxBh9WTRs/Ty+EU5CoKo5olwPHiz9erKkYVBuYU8NTZPDzoyVN03Nc4BB2gVxV0wIWz33bLVxmXfn749cONyu6Y61gAE9PP9wH/JU4pYwEzhdYOeOLs+S3PxEJOGfW/Jk545sz5+3+LgfQy0mjogv87ff7+i9GQUkZlJNINL1wwI8DLUXC8jEXuQzzw8qnz9+c0gINlrPFnUmF26vn78yNhr7n0WIA3U87//K8I+PmiGZdMjeJob3dwryo91lqrVJHt7NmzPPHEE1JgE1XiK7KZQ7VORROjRo1iyZIlPPLII7z11lvFHhs/fjwLFixg5MiRLF68WLMcSzN9+nSee+453/2wsDA6d+7Miy++SN++fTXJyeJRceoVsnLTNXl9oY3HHnuM77//nv79+9OgQQNZ7ECUW7aazx9GA+cUp9ap1KgCVz4YwKJc4qxdVA/5ThMw1q9fzxdffMG8efP461//SnBwMLGxsVgsFjIyMkhNTSU6OprRo0ezZ88eYmJitE65yl5//XXGjBnDQw89BMCcOXP45ptvWLBgATNnztQ6PVFD2jbtzP974EMAzmae5oefP8WTdpwt+jRMuSnku0/TyJlDlk6lQKfgLDyPcisKbgVQ3NjwdtiZUDhrKLv7u4M9jwT1fDXsxCWmY2juzKep53yF66SxMQVldM7Fugto5jlf4UoxNiKjjCGvoaqdZp7zFa40QzzJxtLLHUYcNPOcr3CdMcRx3FR6NczldNHMk+y7n2GI5bip9ONqhNtNM89J3/1MfQzHTaXPP271eGjmOeG7n6OP5rjJWmosQDPP+Wponj6K46aLp4Iwcchk4rbgSpV4RDWq1H+BoUOH8v3339OyZcvqz0jUGw5FBRSCzTatU9FMQkICy5cvZ/bs2Vit3g/VgoICPvroI7++stihQwe+/fZbANLT05k1axZDhgzhxIkT2Gy1/9/TokI2kJMnq7vVJ++//z4rVqxg8GCZ3FVUzEaO82TjeK6xn6rTHV52Tz4AJn3ZJ+1C1EdDhgxhyJAhnD17lo0bN3L06FHy8/OJioqiS5cudOnSpc4Ml3M4HOzcuZNnn3222PYBAwawefPmEvF2ux273e67n5WVVSt51ldKLVXoG9iiuaPfwyW2r77g57z8XDKyTnMu9zQFBXkY0XNMH4LqceFwOpmVewSX24Xb7cCtervWFFVFBUL1Qew3xwIqqgrT8/7wXX1QL+qsCtZZ2HtlQwof5Jn8I3j3ol4Q6/1fq87Cno7xvuc+nn8Ul1r61FRWnZk97Rv77j9ScAyHx1VqrEVnYk+784sCjSpIosDjKDXWpDOw54qmvvv3Fpwg32MvNdag6NnTppnv/lD7SQa6C0qN1SkKe1q38N0fbE/hOndeqbEAey6ovdxgT+Vqd/Ehxq+eXIhDp2CwylRMWqtUka1NmzZMnTqVjRs30qlTpxJDdB5//PHqyk/UYfaiIpulmufEUVVwlv0BVaOMQVCBbpquXbvyxx9/sHLlSu677z4oHOKWkJBAixYtisXa7Xaeeuopli9fTlZWFt27d2f27Nn06NHDF/PVV18xadIkkpKS6NWrFyNHjizxmps3b+bZZ59l+/btREVFcccddzBz5kyCg8v/gWwwGIiLiwMgLi6O5557jkWLFvH7778Xy6e2mFXvv3lOfmatv7bQTmRkpFzsEeIS7Kr3S4BFFj4QolQNGjTgtttu0zqNGnXmzBncbneJEUixsbGkpqaWiJ85c2axEQuitmjfjR9kDSbIGkwjmpX6eBsSy72v9hV43Q4ViO0osWXGdnzxFcyKE9M1lV+pVlSPSq8uGhISwvr161m/fn2xxxRFkSKbKJeisfdWczXPyebMgxnx5QisAX9NBlPFrh6MHj2aRYsW+Yps7733Hg8++CDr1q0rFvf000+zYsUKlixZQtOmTXnllVcYOHAghw4dIjIykqSkJIYOHcq4ceN49NFH2bFjB08++WSxfezevZuBAwfywgsvsHDhQk6fPs3EiROZOHEiixYtqtRbttvtLF68mPDwcNq2bVupfVSVqbDIluuQIlt9Mn36dP7+97+zaNEigoKkiCDExeyqdzisVRYYqjG35Ybx0Lnj5DbX6LxDiHK6eEoFVVVLnWZh6tSpTJ482Xc/KyuLhISEEnFCCP/SwukmSHGSrCtjwjhRaypVZDty5Ej1ZyLqnaIiW7C1/g4XBRgxYgRTp07l6NGjKIrCpk2bWL58ebEiW25uLgsWLGDx4sXcdNNNALz77rusXbuWhQsX8tRTT7FgwQJatGjB7NmzURSFtm3bsnv3bl5++WXffl599VWGDx/uW9SgdevWzJ07l759+7JgwQIsltLnDLjY7t27CQnxFkfz8vIIDQ3l448/JixMm5X6TKoecJNvz9Hk9YU25s6dy+HDh4mNjaVZs2Yluqp/+uknzXITwh/YKSyymern3Ke1oYXLRJf8ArbpZBEn4Z+ioqLQ6/UlutbS0tJKnV/bbDZjNss8jkIIUVkyK57QhMftxl549SykuotsxiBvR5kWjBXvpomKimLw4MEsWbIEVVUZPHgwUVFRxWIOHz6M0+kstoS80Wjk6quvZv/+/QDs37+fXr16FbsqmZhYvK17586dHDp0iA8//NC3TVVVPB4PR44cKbHCVlnatm3LqlWrAMjOzubjjz/mrrvu4vvvv6d79+4V/jeoKl+RzZld668ttHP77bdrnYIQfs1euMBQkEmbCyBCCO2ZTCa6devG2rVrueOOO3zb165dW+eHygpRnywOD0JRzPzJKU0HWit3ke0f//gHjz/+eLmG5Pz444+cOXNGJqMWZcq35+EpLAYFB0dU784VpcJDNrX24IMPMnHiRADefPPNEo8XTQJ6qVb/iycVLY3H4+GRRx4pdUh3RRZaMJlMtGrVyne/S5cufPbZZ8yZM4elS5eWez/VxYQBcFDgzC1HtKgr/v73v2udghB+bXC2hxvyztGscenz64iq22cs4FhIMDqPTFcg/NfkyZMZMWIE3bt3JzExkXfeeYfjx48zbtw4rVOr927ItXBzThLhtmitUxEBbnF4MPk6HT1d8n1Ia+Uusu3bt48mTZpw1113ceutt9K9e3eio70fBi6Xi3379rFx40aWLl1KSkoK77//fk3mLQJcVt4538+2EJmccdCgQTgc3hVtBg4cWOLxVq1aYTKZ2LhxI8OHDwfA6XSyY8cO39DP9u3b89lnnxV73tatW4vd79q1K3v37i1WIKsuer2e/Pz8at9veZgU7zBBu0ub1xf+q6w5Z4SoD27OzieOLA7YmmudSp21JiiHnywNeMBdcgJ5EXjcbje7d++madOmRERU80VgDd19992cPXuW559/npSUFDp27MhXX31F06ZNy/FsUZN6FpjoaM9mh77u/L4JUd+Ve23q999/n++++w6Px8N9991HXFwcJpOJ0NBQzGYzXbp04b333mPUqFH89ttvXHvttTWbuQhoWbnpULjsc4ilfs/JRmGBav/+/ezfvx+9Xl/i8eDgYB599FGeeuopVq9ezb59+xg7dix5eXmMGTMGgHHjxnH48GEmT57MgQMHWLZsGYsXLy62n2eeeYYtW7YwYcIEdu3axcGDB1m1ahWPPfZYhfJ1uVykpqaSmprKwYMHefHFF9m3b59mww58RTaPFNnqunbt2rFs2TJfUbosBw8e5NFHHy02J6EQRZoRzgOZWXRw1u25yqx4V9q2BMtxVojSTJo0iYULF0Jhga1v37507dqVhISEEgtQBbrx48dz9OhR7HY7O3fu5LrrrtM6JXEhuSAoRJ1RoTnZOnfuzNtvv81bb73Fr7/+ytGjR8nPzycqKoqrrrqqxDxSQpQlNz8LAJMKulKKSvXR5RYN+Mc//oHH42HEiBFkZ2fTvXt3vvnmG9+V1iZNmrBixQqeeOIJ5s+fz9VXX82MGTN48MEHffvo3Lkz69evZ9q0aVx77bWoqkrLli25++67K5Tr3r17adiwIQBBQUG0bNmSBQsW8MADD1TqvVeVSfFO0Otw2zV5fVF73nzzTZ555hkmTJjAgAED6N69O/Hx8VgsFjIyMnxd1fv27WPixImMHz9e65SFH2pHFInp59gWXreLT4dMHkJUIyHWwJpCQYja8p///If7778fgM8//5wjR47w22+/8f777zNt2jQ2bdqkdYoB60zqcQ68P4a3bBllxnRwmBmU5100xIHKvPD0MmPbOk0MyfVeGFFRef0Ssc2dJobmnr+I8s/wdFyUPq1KgsvIsJzz5+DzbRnkK55SY+PcBu7LPn/ceDcsgyxd6bEN3HpGZZ8frbM47Bxnde4Sca4GWTyWYSEv73SZ70eIivCUYwqh6pKVnU5WWgrZZ06Sn5HM+szt5DqzsbvzcbjzcXgcuFQ3Kh4auA0MLohCUV0oqoelQalkKS48pfxtRnr0jMiJoOih90MzSNe5isUUPSvMo+ehC/7WloVkkqp3lvoXb1V1jM+MwHnFbfS4rea+I1Rq4QNFUbjyyiu58sorqz8jUS/k5nvnLjHV4oeAv7m4y+xiFw/9tFgszJ07l7lz55b5nCFDhjBkyJBi20aPHl3sfo8ePVizZk2Z+zh69Ogl85o+fTrTp0+/ZExtM+m9q6LaVSmy1XV/+tOf2L59O5s3b+bjjz9m2bJlxS74dOnShQceeID777+f8HAZii4uow53Dtjt+Yxq5J3W4wtTuQcuCFGvnDlzhri4OAC++uor7rrrLtq0acOYMWMueb4lLs+Rn8cVBTvYFdu4zJimzrNcle8tluUpCrssCWXGxrjSuSp/LxR+ud4VV/ZcwqGec75YgD0xjSnQlf45aMzP5Kr8fb77v0U3IqOMBoCO9iyuyt/vu38wKp4UQ+lfp1s6HFyV/5vv/pHIhvxhMpYSaeaRuBieSfkemFbmexJCa5k5GXy9eQk/n/gfJ5zJnNIX0NJp5+1T5wvEf2nSiHNFfz/6wluh9nY7z53b5rs/LSyeZGPpfz8tHE665J7/u3wuIo7DJlOpsfFOF1flnf+7fDk8lj1lrJAc4XZzVf4BtqSVb7G/ypLVRYUmLuxkE6KqzHoLqOBQLz2EUNQdvXv3pnfv3lqnIQJUHk5S9HpyFFc5ogNTRvZZ38+20EhNcxHCX8XGxrJv3z4aNmzI6tWrmT9/PgB5eXmlTt8hyi+sQSy/dPg/RrsOlxkTa7WxPd5b5HSpHka7DpYZG2UNZXvDeCicb3W06/cyYyOswWy/oLh3n/P3UrtlAGzWILbHnC/u3eU8hJOSHWcAIVYL26POz2N3m/Mwdko/jgRZTGxvcH4+zJucR8ij5Hlq86TPiHK7CVIalfl+hNDS2h//w2e/vMFPhtPk6HUXFM90hKl68lUT6boIsg0N6Gx3U6DXY8KASTFj1pnRKwZ0io5wk5UtzZuj6A2oioGB6jHsigedokOh+EVPq8nEjx2aQ+H2G11H6XPx30/hhVKL2cC2Ti19sf1cx+iuFvjuXxCKET3bO7ciqkXXGv03kyKb0ES+PRsAk1p3uwhE7THrg8AFTrXufmEWQlSf9RxlUpNGXGtP5U9aJ1NDsnLPQOHcp2FBMqG2EKUZPXo0w4YNo2HDhiiKwo033gjAjz/+yBVXXKF1egEtJCyCPnc+SZ8KPCexArFXVyC2hz/HTv8QgJ+D5DuR8C+pJ45wfPkkXgv/nZNmA6Aj0uWhrdtGq5D2tI7vTve212ONa0WjwirWmxXYf0X+3ntWILYinw01RYpsQhMFTu/SwlJkE9XBbAgGFzjKuJoohBD1TVaOdwiWRVVl7lMhyjB9+nQ6duxIUlISd911F+bCIUZ6vZ5nn31W6/SEEKLc5iefw6w4COlT9QtrO9d8SMvNT3M1OTxKMKvCmjCoxb0M7T8evb60Yc/iQlJkE5oosHuLbEYpsolqEGQKgQJwKKW39wshRH2TneedbNwi0zLUqJvzQhmemYSzaUOtUxGV9Oc//7nEtpEjR2qSi6i/HMHxWqcgAlw7h4tgxcFJXelzl5XXP5Y9TO/jqwgnn8OGlnQe9Aa3dZQpWipCZsIVmihwFRbZ5FdQVAOrybuClBTZhBDCK6dogaHSF74T1aSN08zAvHyidaHliBb+6H//+x9DhgyhZcuWtGrViiFDhvDtt99qnZaoJ3b/6X22h99Eu/te0ToVIZj3nyf50LmFKbEN+CpqIE2e3kxzKbBVWKU62QoKCpg3bx7ff/89aWlpeDzFz+B++umn6spP1FF2Zx4ARlWGsIiqC7J4l1O3K9KyIYQQALkFRat4S8d4zZJ/30D2xhtv8MQTT/DnP/+Zv/zlLwBs3bqVm2++mddff52JEydqnaKo4zpddxtcd5vWaYg64OMwKzrFSKIru1LP/3LTUhZnfwM6hT7ueAY9+pFMN1FJlSqyPfjgg6xdu5Y///nPXH311SiKnGCIinG48gEwSCebqAYhlnCQIlu95Ha7+fTTT9m/fz+KonDFFVdw++23YzDIbAiifotQLYzPOEcBUVqnUqf9brSTFmTF4cnSOhVRCTNnzmT27NnFimmPP/44ffr04aWXXpIim8amT5/Oc889V2xbbGwsqampULjK6HPPPcc777xDRkYGPXv25M0336RDhw6+eLvdzpQpU/joo4/Iz8/n+uuvZ/78+TRu3LjE6wkRyN6ODCZPp+M9Z8WLbJk56by57x84TApdCyy8MvoLKbBVQaW+hXz55Zd89dVX9OlTkfVihDjP7i4AwKjIF2FRdSFBRUU2rTMRtWnPnj3cdtttpKam0rZtWwB+//13oqOjWbVqFZ06ddI6ReGv1LrfgBTlMjLwXBZ7TU21TqVO+zoom52WaEa4k7lF62REhWVlZTFo0KAS2wcMGMAzzzyjSU6iuA4dOhQbvqu/4Iv/K6+8wuuvv87ixYtp06YNL774IjfeeCMHDhwgNNQ7hHvSpEl8/vnnLF++nAYNGvDkk08yZMgQdu7cWWxfQtRn//hkNEkmhQiXhxdu/RCjyax1SgGtUm1EjRo18n1wCVEZTk9hkU3W3hDVICw4EoB8XR3/1iyKeeihh+jQoQMnTpzgp59+4qeffiIpKYnOnTvz8MMPa52e8GNNsDEsK5s2rhCtU6kxbod3WgaX3qp1KkL4rVtvvZVPP/20xPb//ve/3HKLlE39gcFgIC4uzneLjo6Gwi62OXPmMG3aNIYOHUrHjh1ZsmQJeXl5LFu2DIDMzEwWLlzIa6+9xg033ECXLl1YunQpu3fvlnn3hCh04Ogu/qccAuC+yCE0adhG65QCXqUqHK+99hrPPPMMb731Fk2byhVSUXFOtwP0YFRkCeCatG7dOvr3709GRgbh4eHlek6zZs2YNGkSkyZNqvH8qkt4iHc4lEtRKLDnYjEHa52SqAW//PILO3bsICLi/FLlERERvPTSS/To0UPT3IR/60gMD53NYFtE1Ze591eZ9nQOGY1kGOQ4K8SF5s6d6/u5Xbt2vPTSS6xbt47ExEQonJNt06ZNPPnkkxpmKYocPHiQ+Ph4zGYzPXv2ZMaMGbRo0YIjR46QmprKgAEDfLFms5m+ffuyefNmHnnkEXbu3InT6SwWEx8fT8eOHdm8eTMDBw4s9TXtdjt2u9133+PxkJ6eToMGDWSaJFEpqqqSnZ1NfHw8Op1/TZe0aM0z5Jt1tLYrjL11htbp1AmVKrJ1796dgoICWrRoQVBQEEZj8RO49PT06spP1FEOT1GRrWpLDAeyUaNGsWTJEh555BHeeuutYo+NHz+eBQsWMHLkSBYvXqxZjmXJysri5ZdfZsWKFRw9epTw8HA6duzI+PHjueOOO2r9BCQiLNr3c3rWaeKjpchWH7Rt25ZTp04Vm3sFIC0tjVatWmmWl6g/7HY7PXv25JdffuHnn3/mqquu8j12/PhxJkyYwHfffYfVamX48OHMmjULk6l2jnub7b8xuXFD+tiz6FcrryhEYJg9e3ax+xEREezbt499+/b5toWHh/Pee+/xf//3fxpkKIr07NmT999/nzZt2nDq1ClefPFFevfuzd69e33zssXGxhZ7TmxsLMeOHQMgNTUVk8lU7GIcF83rVpqZM2eWmAtOiOqQlJTkV/MBnjubxrSTPzMgWEdO17/JPGzVpFJFtnvvvZeTJ08yY8YMYmNjpaIvKsypOgAw6upvkQ0gISGB5cuXM3v2bKxW75CegoICPvroI5o0aaJ1eqU6d+4c11xzDZmZmbz44ov06NEDg8HA+vXrefrpp/nTn/5U7q656hJiDUWvqrgVhXNZZ4iPblarry+0MWPGDB5//HGmT59Or169oLAD4fnnn+fll18mK+v8RORhYWEaZir8jR0X53Q6CnBXaT9PP/008fHx/PLLL8W2u91uBg8eTHR0NBs3buTs2bOMHDkSVVWZN29eFbMvnwJPAeikY1yIix05ckTrFEQ53XTTTb6fO3XqRGJiIi1btmTJkiW+4/7F30NVVb3sd9PLxUydOpXJkyf77mdmZtKkSROSkpJq9Hxi/49raPfdgxxX4mny7LYaex1R+7KyskhISPC7Kbf2fbWA3oqd5gVNafanR7VOp86oVJFt8+bNbNmyhSuvvLL6MxL1gkt1AmDUVf+kiqqqkl+4emltsxqsFSo6d+3alT/++IOVK1dy3333AbBy5UoSEhJo0aJFsVi73c5TTz3F8uXLycrKonv37syePbvYsLivvvqKSZMmkZSURK9evRg5cmSJ19y8eTPPPvss27dvJyoqijvuuIOZM2cSHFy+7q+//vWvHD16lN9//534+Hjf9jZt2nDvvfdisVjK/f6ri06vJ8ijkq1XOJeTVuuvL7QxZMgQAIYNG+b7u1NV7wqzRXPpFJ1Iu91VK6aIuuVb/mBi08Zca0/hukru4+uvv2bNmjWsWLGCr7/+uthja9asYd++fSQlJfk+J1977TVGjRrFSy+9VCtFX6fbDjow1eOOcSEqouj4Ic0D/is4OJhOnTpx8OBBbr/9dijsVmvYsKEvJi0tzdfdFhcXh8PhICMjo1g3W1paGr179y7zdcxmM2Zzye8oYWFhNfr5fdZzilMhJlCtcnGwjqqNzxfVU744j9tNoz+WA3Cmw0ia+9kw1kBWqSLbFVdcQX6+NkUMUTc4VRcARn31n/znu/Lpuaxnte+3PH4c/iNBxqAKPWf06NEsWrTIV2R77733ePDBB1m3bl2xuKeffpoVK1awZMkSmjZtyiuvvMLAgQM5dOgQkZGRJCUlMXToUMaNG8ejjz7Kjh07Sswnsnv3bgYOHMgLL7zAwoULOX36NBMnTmTixIksWrTosrl6PB6WL1/OfffdV6zAViQkRLtJxC0qZAOZOWc1y0HUru+//17rFEQ9derUKcaOHctnn31GUFDJz/wtW7bQsWPHYp+TAwcOxG63s3PnTvr371/qfi+eB+jCbsyKcqje/Zj0tX/hQ4hA8v777/Pqq69y8OBBKLxo+NRTTzFixAitUxMXsdvt7N+/n2uvvZbmzZsTFxfH2rVr6dKlCwAOh4P169fz8ssvA9CtWzeMRiNr165l2LBhAKSkpLBnzx5eeeUVTd9Laead/g8nGjdk2mkTHbVORgScV1OzsCh2Ik3lG1G0eutyZjeGwdmRPDxwTI3nV59Uqsj2j3/8gyeffJKXXnqJTp06lZiTTSrv4nKceItscvIPI0aMYOrUqRw9ehRFUdi0aRPLly8vVmTLzc1lwYIFLF682Nc6/+6777J27VoWLlzIU089xYIFC2jRogWzZ89GURTatm3L7t27fScaAK+++irDhw/3LWrQunVr5s6dS9++fVmwYMFlu9DOnDlDRkYGV1xxRY39e1SW1eO9+pKZe1rrVEQN27VrF1dddRV9+/bVOhVRD6mqyqhRoxg3bhzdu3fn6NGjJWJSU1NLzBMUERGByWSqtXmAHIUd4yadHGdr0o35odyefQIlIU7rVEQlvP766/ztb39j4sSJ9OnTB1VV2bRpE+PGjePMmTM88cQTWqdYr02ZMoVbbrmFJk2akJaWxosvvkhWVhYjR45EURQmTZrEjBkzaN26Na1bt2bGjBkEBQUxfPhwAGw2G2PGjOHJJ5+kQYMGREZGMmXKFDp16sQNN9yg9dsrwVE4nY5Bqf6RPqLu61LgJFSxc0Jfvt+fb/d/QKrRwK9BsQSF1O5UP3VdpYpsgwYNAuD6668vtl2G5YjychbOg2M2WKt931aDlR+H/1jt+y3va1dUVFQUgwcPZsmSJaiqyuDBg4mKiioWc/jwYZxOJ3369PFtMxqNXH311ezfvx+A/fv306tXr2JtyEUrZRXZuXMnhw4d4sMPP/RtU1UVj8fDkSNHaNeu3SVz9eehFBZVB3jIKcjQOhVRw7p27UqXLl146KGHGD58ODabTeuURB0wffr0yxa4tm/fzubNm8nKymLq1KmXjC3tc7Ki8wAVzeFSGUVFNksNHGfFee2dFrrk5vKjTj6HAtG8efNYsGABDzzwgG/bbbfdRocOHZg+fboU2TR24sQJ7r33Xs6cOUN0dDS9evVi69atNG3aFApHeeTn5zN+/HgyMjLo2bMna9asKTbv1ezZszEYDAwbNoz8/Hyuv/56Fi9ejN4PJ3i3e7yf23q5OCJqmMft5hclCdCRGHt9OZ4hKqJSRTYZoiOqyqV4B4ubDRUbWlkeiqJUeMim1h588EEmTpwIwJtvvlni8bKKWxd+YSuKuRSPx8MjjzzC448/XuKx8iy0EB0dTUREhK+w50/M6AEPufZMrVMRNWzTpk289957PPvsszz55JMMHTqUMWPGlDkET4iLqZT8vJw4cSL33HPPJZ/XrFkzXnzxRbZu3Vpivp7u3btz3333sWTJEuLi4vjxx+IXezIyMnA6nSU63C5U1jxAlVHUMV4Tx1lRinIcg4X/SUlJKXVurt69e5OSkqJJTuK85cuXX/JxRVGYPn0606dPLzPGYrEwb968Wlt0piochZ/bRkWKbKLiVoVa0Ct6rnLlXjZ23U//Jc2gw+xRuetPcjGhulWoyCZDdER1KepksxjLN9l+XTdo0CAcDm+L+MCBA0s83qpVK0wmExs3bvS1wDudTnbs2OEb+tm+fXs+++yzYs/bunVrsftdu3Zl7969tGrVqlJ56nQ67r77bj744AP+/ve/l5iXLTc3F7PZjMFQqfp9lZhVI+Akz1H5OYxEYEhMTCQxMZG5c+fyySefsGjRIm644QaaNWvGgw8+yMiRI/1qeXThxy64bhEVFVWii7g0c+fO5cUXX/TdT05OZuDAgXz88cf07OmdDzQxMZGXXnqJlJQU34Tca9aswWw2061bt5p4JyX0ytdxpT2LBFvJ+TNF9TlicJBttZDjydE6FVEJrVq14pNPPuGvf/1rse0ff/wxrVu31iwvUT85VBcooNdLB7KouHkNgsnV6fiX8/LfhTbsXwFAW6eZ8NDLn/uIiqnQEhJdu3alW7duLFiwgMxM6RYRledUvFd8LSYpsgHo9Xr279/P/v37S21fDw4O5tFHH+Wpp55i9erV7Nu3j7Fjx5KXl8eYMd6JKseNG8fhw4eZPHkyBw4cYNmyZSxevLjYfp555hm2bNnChAkT2LVrFwcPHmTVqlU89thj5c51xowZJCQk0LNnT95//3327dvHwYMHee+997jqqqvIydHmi4alcAW9fFeeJq8vap/VamXkyJGsW7eO33//nXvvvZe3336b5s2bc/PNN9f469vtdq666ioURWHXrl3FHjt+/Di33HILwcHBREVF8fjjj/sK6SKwNWnShI4dO/pubdq0AaBly5a+4u6AAQNo3749I0aM4Oeff+Z///sfU6ZMYezYsbU2b+2NOSpT0s/ROqRlrbxeffV5UCYT4mLY7TmpdSqiEp577jn+3//7fwwaNIgXXniBF198kUGDBvHcc8/x/PPPa52eqEecHifuwu9HJoN8PxKVV1q3/sV+y/eOSrrCeumpgkTlVKjItmnTJrp27cqzzz5Lw4YNuf/++2t96Kh8qakbHIUHEatJu9Uo/c3llgX/xz/+wZ133smIESPo2rUrhw4d4ptvvvEtSd6kSRNWrFjB559/zpVXXslbb73FjBkziu2jc+fOrF+/noMHD3LttdfSpUsX/va3vxVb+vxyIiIi2Lp1K/fffz8vvvgiXbp04dprr+Wjjz7i1Vdf1Wx+LHNha31BOVqkRd3TsmVLnn32WaZNm0ZYWBjffPNNjb/m008/Xeoqu263m8GDB5Obm8vGjRtZvnw5K1asKLHar9BOI8K4JTuXlq6aGUqp1+v58ssvsVgs9OnTh2HDhnH77bcza9asGnm90hg93tVFDWYZLipEWe68805+/PFHoqKi+Oyzz1i5ciVRUVFs27aNO+64Q+v0RD1id51fWdooRTZRg85ln+V3k7dG0r/DMK3TqZMqNKbLH4boFH2p+eWXX4ptL/pSEx0dzcaNGzl79iwjR45EVdWAGINf33g72RSs9biT7eIus4tdPPTTYrEwd+5c5s6dW+ZzhgwZwpAhQ4ptGz16dLH7PXr0YM2aNWXuo7SV8i5ms9mYOXMmM2fOvGxsbbEUttYXePK1TkXUsvXr1/Pee++xYsUK9Ho9w4YN83V41pSvv/6aNWvWsGLFCr7++utij61Zs4Z9+/aRlJTkK8K99tprjBo1ipdeeklW4PYDVxHLo2fOsi2yQZX31axZs1LnxGzSpAlffPFFlfdfWWf1BVgUPVhk2JEQl9KtWzeWLl2qdRqintMpOm4piCHSfghjmDQhiJqzf9d33JKTy2Gjhd5XDtY6nTqpQp1sRbQaolP0paa0K8FFX2qWLl1Kly5duOGGG3jttdd49913ycoqe1yy3W4nKyur2E3UPEfhPDhBFvmyKaqHpXByb7sq3av1QVJSEi+88AItW7akf//+HD58mHnz5pGcnMy7775Lr169auy1T506xdixY/nggw8ICirZJbRlyxY6duxYrMtt4MCB2O12du7cWeo+5VgkqtvkOCMDmjQiTZXfJSGE8HdBxiCG5tiYkn4OxSQdyKLilPKuv3NkN9PPpjM5uyU6P1xlty6oVJHtQrU1RKcmvtQAzJw5E5vN5rslJCTUSP6iuPNFNlnyXlQPq8G7XHuBar9srAhsN954I82bN2f+/Pn8+c9/Zv/+/WzcuJHRo0cTHFyz3bGqqjJq1CjGjRtH9+7dS41JTU0tsYJkREQEJpOJ1NTUUp8jx6La5cJDgaLgwqN1KjXGXniGF2IN1zoVIYQQ5aB3e0djKEbpQBY1x5zqrY044mpnIab6qEpFtvXr1zNy5Eji4uJ4+umnGTp0KJs2baq+7ArV1JcagKlTp5KZmem7JSUlVXv+oiSH4q2yBVtDtU5F1BFBJm/B1q64tE5F1DCr1cqKFSs4ceIEL7/8Mm3btq3yPqdPn46iKJe87dixg3nz5pGVlcXUqVMvuT9FUUpsU1W11O3IsajWfcNhejRLYJml7k5Wby/8XQsNjtA6lTqu9L9pIYSoiDxnHqeUXE7p9eikk03UEI/bTb5rH07A1iZR63TqrArNyUbhEJ3FixezePFijhw5Qu/evZk3bx7Dhg2rcAfB9OnTee655y4Zs337djZv3lwjX2oAzGYzZrO5AlmLqrLbC3AX/jcJskiRTVSPELMNcqFAcWudiqhhq1atqvZ9Tpw4kXvuueeSMc2aNePFF19k69atJY4b3bt357777mPJkiXExcXx448/Fns8IyMDp9NZ4mJQETkWiepUYM/zHWdDrDItgxBC+Lu9Z/fyVEwGzR0xTJcFa0QlPHc6GzN2Ik1lX1z75eAWxjUKIdgTxLcdetZqfvVJhYpsN954I99//z3R0dE88MADPPjgg1XqIND6S43QRm7B+flhgoOqZ2LP0iadFv6jNv77hARFQjoUKHV3+JeoOVFRUURFRV02bu7cubz44ou++8nJyQwcOJCPP/6Ynj29JyuJiYm89NJLpKSk+FbuXbNmDWazmW7dpDXfL6h1uwEpO++c7+eQIBkuWpOuKwhhQM4JzI2itU5FCBHAClwFAFhUFb10solK6JXvJIwCknSmMmN2/LYagBiXjpAQ6XSvKRUqshUN0RkyZAj6apgkT77U1E+5eZm+n4OrOCeb0WgEIC8vD6tV5i/wV3l5eXDBf6+aEB7s/SzJL/esn0JUXJMmTYrdDwnxXiho2bKlb3XtAQMG0L59e0aMGMGrr75Keno6U6ZMYezYsbKyqJ9R62ilLTsnw/dzaLAU2WrSlQ4rXXNz+FEnX1YCydChQ8sVt3LlyhrPRQiAAre3yGZVPRjMNTu/rKirLn9OczR9D+ghXpVzg5pUoSJbTQzRKQ/5UlO35BXkAKCoKhZT1Qpjer2e8PBw0tLSAAgKCrrk8GBRu1RVJS8vj7S0NMLDw6ulOF8WW0hhka3Ky7kIUTV6vZ4vv/yS8ePH06dPH6xWK8OHDy91ZWwhakJOQTYARlXFYKi5ixtCBCqbTRbeEv7F18nmUTFapcgmKm5tsAmDAm1deWXGJDtTvEU2a5MyY0TVVXhONn8lX2oCR67dW2QzqaDoql4RiYuLA/AV2oT/CQ8P9/13qimRNu/+83U6nA47RpPMbyVqXrNmzUodDt2kSRO++OILTXISQudyc39mFva6c5rnt07oHbgtZjLUsr/UCP+zaNEirVMQoph8l3dlUYuqYjTL6BxRca81CCZbH8o7znNlxiTrcwGF1jFdazW3+iYgz77kS01gK/AV2apnWJ+iKDRs2JCYmBicTme17FNUH6PRWKMdbEWiIxr6fj6bdYq4KLlCI4Son4LcBp5JP8cZZDhITfs0OJMdDWK5z53EIK2TEUIErAvnZDNZq2fOaiEudDbzFCmF1Z8e7QZonU6dFpBFNhHYCuy5ABiqeeosvV5fK8Uc4Z9CrTYMqopLUThzLlmKbEKIMsURzA25ecTpGmudSo1wObwdEU5kqKgQQgSCok42q6pisshwUVH9tu5ejaooRLg9tGrSSet06jSZvUjUunxH4ST4Wici6hSdXk+wx1u5zciSocNCiLJ1oyGz087Qz3H5xZcCUV5+Fml6PRn6slcYE0Jo4+jRo4wZM4bmzZtjtVpp2bIlf//733E4HMXijh8/zi233EJwcDBRUVE8/vjjJWJ2795N3759sVqtNGrUiOeff77EaJ/169fTrVs3LBYLLVq04K233qqV9ykqpl34FYzIzKJXfoF0sokaoZw6yePp5xiUK0XcmiadbKLW2QuLbAZVFigQ1cvqUcjUQ0aOFNmEEPXXnqz9jGjSiOYO0GbJKiFEWX777Tc8Hg9vv/02rVq1Ys+ePYwdO5bc3FzfXNJut5vBgwcTHR3Nxo0bOXv2LCNHjkRVVebNmwdAVlYWN954I/3792f79u38/vvvjBo1iuDgYJ588kkAjhw5ws0338zYsWNZunQpmzZtYvz48URHR3PnnXdq+u8girsyrAPXpXvn0nIESZFNVF5ZMzJFpJ/i5swsfmxwfW2nVO9IkU3UOnvhiidGKbKJahZU+Dt1TopsQoh6rMBZdJyVAQtC+JtBgwYxaND5GfxatGjBgQMHWLBgga/ItmbNGvbt20dSUhLx8fEAvPbaa4waNYqXXnqJsLAwPvzwQwoKCli8eDFms5mOHTvy+++/8/rrrzN58mQUReGtt96iSZMmzJkzB4B27dqxY8cOZs2aJUU2P+PM906n41YVjEbpQhYVd7mZmMyZR7xxkc1rJZ/6TM6+RK2zOwvnZEOKbKJ6WT3e6wZZ+We0TkUI4ce+5BCdmyXwgSVJ61RqhO9ilpzm1Z5qnmdW1C+ZmZlERkb67m/ZsoWOHTv6CmwAAwcOxG63s3PnTl9M3759MZvNxWKSk5M5evSoL2bAgOITnA8cOJAdO3aUuViY3W4nKyur2E3UvJSsE6Tq9ZxTzCg6+ewW1e+45zh/GA0YY1pqnUqdJ3/BotY5ClfPkeGiorpZ8V75yy7I0DoVIYQfU1FRFYW6eq3H7vROoG2QTjYh/N7hw4eZN28e48aN821LTU0lNja2WFxERAQmk4nU1NQyY4ruXy7G5XJx5kzpFyRnzpyJzWbz3RISEqrpnYpLeeP3d7mxSSM+Cw3VOhURoKaeyeXVtDNEGkuuLO5xu5kZ7eS2xvHkR8nK4zVNzr5ErXO47AAY5NdPVDOrYgEg1ylXXYUQ9ZfTXXgxC1lxu6b1KQhhcnoGLXV1cxENUX7Tp09HUZRL3nbs2FHsOcnJyQwaNIi77rqLhx56qNhjilLyKoCqqsW2XxxTtOhBRWMuNHXqVDIzM323pKS62fHrb/J9F0fkc1tUTt88B4Ny8wgyWEs8dujEHvJ0OnSqypVtrtEkv/pE5mQTte58J5sU2UT1suq8B5U8V47WqQghhGaKimxGRU7zalpXRxBdc7P5MT6yHNGiLps4cSL33HPPJWOaNWvm+zk5OZn+/fuTmJjIO++8UywuLi6OH3/8sdi2jIwMnE6nrzMtLi7O17FWJC3NOyft5WIMBgMNGjQoNUez2VxsCKqoHQUub5FNj1HrVEQdtOePzQBEu1RCg6WTrabJ2ZeodS53USebXKkR1StI712NKd+Tp3UqQgihGYdHjrNC1LaoqCiiosrX0Xjy5En69+9Pt27dWLRoEbqL5uBKTEzkpZdeIiUlhYYNG0LhYghms5lu3br5Yv7617/icDgwmUy+mPj4eF8xLzExkc8//7zYvtesWUP37t0xGqWY40/shZ/bevl6LippY5ARI1aaFBZsL3QkbQ8AMW4poNcGaSUStc7pdgCgV+TkX1SvYJMNgHzsWqcihBCaaeS2MjQ7h9YeuVpd007pnewxmchSC7RORQSI5ORk+vXrR0JCArNmzeL06dOkpqYW6zgbMGAA7du3Z8SIEfz888/873//Y8qUKYwdO5awsDAAhg8fjtlsZtSoUezZs4dPP/2UGTNm+FYWBRg3bhzHjh1j8uTJ7N+/n/fee4+FCxcyZcoUzd6/KJ3dXVRkk5VFReXMiArhydhozjhKzk19Jtc77DtSF6ZBZvWPlMpFrXOqcoVd1IxQSyTkQD4OrVMRQgjNXOkI4ZEz6WyNbaR1KnXev4Mz2N4gjvvcx7hR62REQFizZg2HDh3i0KFDNG7cuNhjRfOl6fV6vvzyS8aPH0+fPn2wWq0MHz6cWbNm+WJtNhtr165lwoQJdO/enYiICCZPnszkyZN9Mc2bN+err77iiSee4M033yQ+Pp65c+dy55131uI7FuXhUL2rveoU6TQS1S/DlQ56iDBFa51KvSBFNlHrnG4H6MAgnWyimoUFRUEO5ClurVMRQvixaILok5dPvFJycuC6QCnsiFANFq1TEUJcZNSoUYwaNeqycU2aNOGLL764ZEynTp344YcfLhnTt29ffvrppwrnKWpXUZHNoEgnm6h+59RcAKKDGl82VlSdDBcVtc5VdBCRGq+oZuEh3ol+c3UerVMRQvixnjTirVOnud5ZN6/oFrjzyFEU3Eb5slbjSl+gUQjhZ+bPn0/z5s2xWCx069aNDRs2aJ1SMb2VptyZnUOwEqx1KiLgqSW2/Dkzn8fTz9E+posmGdU3UmQTtc7lKbpSIxOuiuoVZYsHIFc+2YQQl6KWPAGtSz60HCexWQLf6U5onYoQQmju448/ZtKkSUybNo2ff/6Za6+9lptuuonjx49rnZrPUHdrpp9Jx6YL0ToVUceoHje35J5hbGYW7ZtcrXU69YJ8FRW1zqW6ADDopMgmqldMRAIAeTodBfZcrdMRQvi9utmG5MJ7nDXqZW4fIYR4/fXXGTNmDA899BDt2rVjzpw5JCQksGDBAq1T81ELV4RU9TLMX1Sv9NPJmBUnHlUhKr6Z1unUC1JkE7XOV2STTjZRzRpGN/X9nHrmmKa5CCH819fKYXo2bcxyc5LWqdQIp+qdl9JsqJtzzgkhRHk5HA527tzJgAEDim0fMGAAmzdvLvU5drudrKysYrea5FE9ZDozydIpuI1SZBNVdFG3/h/Hf2WD1cLPpghMZvn9qg1SZBO1zl10hV0nc8WI6hVkCSLI452P7VR63fzyLISoOjce8nQ6nErdHDbqKlz8xSgdEUKIeu7MmTO43W5iY2OLbY+NjSU1NbXU58ycORObzea7JSQk1GiOmfZMngraTp+mCahycURU0l/O5vH86bNEGG3Ftv+cvIXxcTHMiA7VLLf6Ropsota58J78G6TIJmpASOGaB2cyk7VORQghNOHE+0FoNsqXtZrWwx7MoxmZNNVFap2KEOISFKX49ACqqpbYVmTq1KlkZmb6bklJNXvh1l64IrRBVdEbg2r0tUTddWOukztycgkxFF88Iy3LO7onXJVzgtoiyzuKWudSi66wS5FNVL8gj/faQUb2Ka1TEUIITTgVb5HNYpRV6mpaT3swXXMy+bFhlNapCCFKERUVhV6vL9G1lpaWVqK7rYjZbMZsrr05LQtcBQBYPSqKRYpsonql29PACDZ9uNap1BvSySZqXVEnm0zILGpCkOq9dpCZd1rrVIQQddiXX35Jz549sVqtREVFMXTo0GKPHz9+nFtuuYXg4GCioqJ4/PHHcTgctZKbE+8wWLN0RAgh6jmTyUS3bt1Yu3Ztse1r166ld+/emuX1/9u78/imynx/4J+TPS1tKd3SQjeQvYjQIhbQCo5FRBRBhGF+HZjrMCLgVhkvqDNURxaH6nh19DLjgjrOvThedFRgtNVqFQEtq1gYQCm2QMvSlqZr1uf3R9rQ0KZNl+S0zefNKy+Sk2+S7zlNzpPzzfM8p7mmnmxaISCxBzJ10l6dCl/qdaiz1bssr7Y55hTsr+GPQb7Cnmzkc9bGX9g1nHOAvCBQaAFYcameRTYi8o6tW7diyZIlWLduHaZNmwYhBA4fPuy832azYebMmYiIiMDOnTtRXl6ORYsWQQiBF1980ev5Tay3YbTZhHB9pNdfy9+VK6z4Qa1GjTDJnQoRuZGZmYmMjAykpKQgNTUVf/3rX1FcXIylS5fKnRoAoMHm6MmmFQIKLX8coc55MjIQVcogvGyqcFleDcf7KzTQIFNm/odFNvI5K5qKbOzJRt0vUBEAoBbV5kq5UyGiPshqteLBBx/Exo0bcc899ziXDx8+3Hk9JycHR44cQUlJCWJiYgAAzz77LBYvXoy1a9ciODjYqzkuq6hHBCrxY3CCV1+HgP8NrERBWDQW2k7hJrmTIaJWzZ8/H+Xl5XjqqadQWlqKpKQk7NixA/Hx8R482vuahovqhB1KDYts1L2MCgsACRFB3j2BB13G4aLkc9bGs7lpVDzrGXW/fkrHmXNqbNVyp0JEPdQA6DC+oQGR9o7/2LN//36cOXMGCoUC48aNQ3R0NGbMmIHCwkJnzO7du5GUlOQssAHA9OnTYTKZsG/fPrfPbTKZYDQaXS6doYFjWKqKPSJ8qG+eqZaor1i2bBlOnTrl3A/fcMMNcqfk1Hy4qFLDkT7UVa7t0SWl43ZM+BCZ8vE/LLKRz1nRVGTjl3/qfkFaxxneau11cqdCRD3UJDEIb5aex3Rz65Net+XkyZMAgKysLDzxxBPYtm0bQkNDkZaWhooKxxCNsrKyFhNqh4aGQqPRtJh8u7n169cjJCTEeYmN7dyvznZYYAOg1vJgjYiop4vQR+DmajvS6hqg0vGENdR9Gupr8J8VlXioohJDB42ROx2/wSIb+VxTTzYtJ/YkLwjRRwAAaiTfTDBORH1DVlYWJElq87J3717Y7Y4pDx5//HHMnTsXycnJ2Lx5MyRJwrvvvut8PkmSWryGEKLV5U1Wr16Nqqoq56WkpKTD62G32ZCWEIVrEuNQLfhjAxFRTzcybCQevdiAZZeqoGJPNupGVRdKcUdNLTIu1cMQHid3On6Dc7KRzzl6sknQcc4B8oKwfjFANVCjsMqdChH1IitWrMCCBQvajElISEB1tWMo+qhRo5zLtVotBg8ejOLiYgCAwWDAN9984/LYyspKWCyWFj3cmtNqtdBquzZfqdlqgmgs5AXo+nXpuYiIyDe0jcP81ToeH1H3qbp4BlEAKqT+MCjYv8pXWGQjnzM3/oivVbM7NHW/yNA4oBQwKjg/DhG17hOpCKviBuJa6xlMbFwWHh6O8PD2T2+fnJwMrVaLY8eOYcqUKQAAi8WCU6dOOSfRTk1Nxdq1a1FaWoro6Gig8WQIWq0WycnJXlwzoLb+8jxuAfogr74WERF1XYO1ATaYYQOgYZGNulHxuaM4r9fBKvqD5xb1HRbZyOesjUU2PeccIC8YGOGY1NOoVMBsroeG3e6J6AomWFGhVKLBZuvwY4ODg7F06VKsWbMGsbGxiI+Px8aNGwEA8+bNAwCkp6dj1KhRyMjIwMaNG1FRUYGVK1diyZIlXj+zaF395ZO+BOq9+1pERNR1fyv8G15IjMSd1TW4n8dH1En3VjRAKTUgVB3iXHbg0gG8ZYjEuAYFbpQ1O//CIhv5nLlxGItey1/YqfvFGoY6r58+9wMGx3KSTyLqXhs3boRKpUJGRgbq6+sxceJE5OXlITQ0FACgVCqxfft2LFu2DJMnT4Zer8fChQuRnZ3t9dzqGmoAAJIQ0Ki6NvSU2jfOrMfohlJERQyQOxUi6qXqLLVA49lFNSyyUSfdVmNGKGrwk+ryVBGXGi4CCiBIYg9JX2KRjXzO0tiTLVDLuWKo+wXoAhBss8OoVOD0+R9ZZCOibqdWq5Gdnd1m0SwuLg7btm3zaV4AUG92HKxpBKBQKn3++v5msikI42su4ZuoCLlTIaJeqrbB0QNZZxfQ6lkMoa4RuDxlTpX1EqABglX9Zc3J37DIRj7VYKqDnRMyk5cF2yUYlcC5ymK5UyEi8ql6k6Mnm1pwXkpfEHB/tlgiIk/UOX8cEdBqOc0Jdc5hrRJ6SYsgm8m5rEY4vhOEaMNkzMz/sMhGPsUJmckX+tlVAGyoqD4jdypERD6ltAncXFsHIfgVzxeMkg1nVErU2c1yp0JEvVS9uQ4AoLYrIPEMkNRJT0QFolIZhD+bLmBE47JaOApuoYE87YEv8RsY+VTzCZkDOCEzeUmg0ACoR2X9eblTIaIere/1QgpFIJ47fxHnwF+tfeHtfhfxbfhALLAXYarcyRBRr9RgcRTZlGCBjbpXjcIGQEJov2i5U/Er/CSTTzXNFSMJAS0nZCYvCVI4hiJfMl2UOxUi6oFChBYjTWYMEBq5U+l2NovjV2uLpJY7FSIi8kC9tR4AoBScR5O6V43CMXVEeP+BcqfiV9iTjXyqwdwAAFBzQmbyomBVKIALqLJckjsVIuqB0kQsVp39GN+ET5I7lW5nMddDALCyyEZE1CsM18aif+0eRFr73g8/JB+7zYZHyitxSanA4MgRHjyCuguLbORTpsaebCpwQmbyngF6A2A6DqOokzsVIiKfOmg8gl8kxGKoWYGtcidDRETturVfKsac/28UKRLkToX6kJpL5Zhd6zj2NkcNljsdv8LhouRTJrOjO7SKNTbyoojgWABAlYITURORfzFZ6yGkvjfXHBFRX2VrPPGBRcGebNR1ovHs4saKMgBAjdBDo9XJnJV/YZGNfKqBRTbygZjwoQCAS0q73KkQUQ/0qXQKtwyKwT81fe8MxBarY042TqBNRNQ7NJiMEAAsCs5XTd3nbPlJ7NTrcEgbIncqfoffwMinLFbHnGwcp0zeNDhmDACgSqlAbV2V3OkQUQ9TJ1lxRq1CrWSVO5VuZ7E1trOCX/GIiHqD1eVv4urEOBzTcr5q6ryMShMerqhEf3UwAODIxcO4zxCJjeEs3voav4GRT5ktTT3ZOJSFvCfeMAQau6O75I8l38mdDhGRz1hs7MnmS6Mtesw3VmOQxJ4CRNQ5ZmEBACglDhelzptTbcZ/VFUjpLHIdqnuHAAgUPBESL7Gb2DkUyaL4xd2JYeLkhcpVUoMsDmunzr3b7nTIaIep+82Qk1FNhXYI8IX0kwheKK8EsMVkXKnQkS9lAWOXtVKBefNou5jbKgAAARI7Mnmaxy1Rz7VNIxFCfZkI+8KsStRBjvKKovkToWIyGcsdscJX9iTjYioe/3m9Ruh0bv+gHFbXRCGWhxFjH+rTfhXQLXbx99S1w8jLY5C2o8qEz4MdMTW6xxFNhWLbNQFJzQKlEEDZeOPbTXWKkAJBEqBcqfmd1hkI59y/sLO4aLkZcFCD6AWF6v73sTmRETuhNo1mFxXj2iwZ5Uv1Et2VCgUMIm+N78fEbn6TtcApc61yLaoqgTj6hzT4ZwNDMABXbjbx88znsa4OseZRCsD9Digi3Dep7PbEaDQey136vsejQpEpSoI/2U6jxEAamw1jiKbKkju1PwOi2zkU2Zr0y/sLLKRdwUrggDUotJ0Qe5UiIh8JtkWjhXnLuCbsElyp+IX3uh3Ad+EDcIC+0mkyZ0MEXnVz9UTodO4zptmSojBtwpHEcNuN+KXtlL3TxBvwLcKx/yNDfZqZFQfxuBLuwAAI01mVA/o5830yV8IOwCgzu4o/gZpQmVOyP+wyEY+ZeWEzOQjA7SRgChDpa1S7lSoD9q+fTueeuopfPfddwgMDMQNN9yA9957z3l/cXExli9fjry8POj1eixcuBDZ2dnQaDipcU/QT2iQaLYguC9OBtzYzkLRB9eNiEhGD877LwQHB7cZM6sDz3djTRUCsuOct/eoOFyUuk+t5OjcEqwPkzsVv9OrKh3bt2/HxIkTodfrER4ejjlz5rjcX1xcjFmzZiEwMBDh4eF44IEHYDabZcuXWrp81jP2ZCPvigpOBABUoFbuVKiP2bp1KzIyMvCrX/0Khw4dwtdff42FCxc677fZbJg5cyZqa2uxc+dObNmyBVu3bsUjjzwia9502TQRhw/PlGKWOUbuVLqdZHOcpU4oOdExUU9nMplwzTXXQJIkHDx40OU+T45rDh8+jLS0NOj1egwcOBBPPfUUhHA9sUt+fj6Sk5Oh0+kwePBgbNq0ySfrRu0L6BeCOnF5Xy3ULLJR95lTZcMj5ZUY2n+E3Kn4nV7Tk23r1q1YsmQJ1q1bh2nTpkEIgcOHDzvvbzqoiYiIwM6dO1FeXo5FixZBCIEXX3xR1tzpMpu98RTVolfVd6kXio9KAqo+wEWVTe5UqA+xWq148MEHsXHjRtxzzz3O5cOHD3dez8nJwZEjR1BSUoKYGEcR59lnn8XixYuxdu3adn8FJ+qKfyhP4MH4QUi3n8V1cidDRG169NFHERMTg0OHDrks9+S4xmg04uabb8bUqVNRUFCA48ePY/HixQgMDHT+qFNUVIRbb70VS5Yswdtvv42vv/4ay5YtQ0REBObOnSvLOpOrS4oQBIjzAABJzTnZqPOu7MJyc60R4ajGD+EssvlaryiyefOgxmQywWQyOW8bjUavrou/s9gcv8CpoGw3lqgrRiZcCxwHKpUKVFVfQEhQhAePImrb/v37cebMGSgUCowbNw5lZWW45pprkJ2djdGjRwMAdu/ejaSkJGdbBADTp0+HyWTCvn37MHXq1BbPy7aIuotJWFCnUMDeuwYrEPmdf/3rX8jJycHWrVvxr3/9y+U+T45r/v73v6OhoQFvvPEGtFotkpKScPz4cTz33HPIzMyEJEnYtGkT4uLi8PzzzwMARo4cib179yI7O9ttkY3tkW/VKPsDVhbZqHsJux3BohqQgMD+PAbytV7xDezKg5ro6GjMmDEDhYWFzpj2DmrcWb9+PUJCQpyX2NhYr6+PP7M29mRTSL3irUe9WJwhEf1sjok/v//xG7nToT7i5MmTAICsrCw88cQT2LZtG0JDQ5GWloaKigoAQFlZGaKiolweFxoaCo1Gg7Kyslafl22Rb30uFePOgQZs17QxQXUvZYPjLJcqzslG1GOdO3cOS5Yswd/+9jcEBAS0uN+T45rdu3cjLS0NWq3WJebs2bM4deqUMyY9Pd3luadPn469e/fCYrG0mltPaY8SEhIgSZLLZdWqVS4x3TWkVk716suT0itYZKNuUltXhYIANb7TahAQMkDudPxOr6h0eOugBgBWr16Nqqoq56WkpMTLa+PfrPams4v2irce9WKSJCHC5nifnSz9Tu50qIfLyspq8WX+ysvevXthtzsKt48//jjmzp2L5ORkbN68GZIk4d1333U+nyS1nHdSCNHqcrAt8rlqmPCDRoMqqfWDzN7MKhxD5NUKnmTDp3rQQTv1bEIILF68GEuXLkVKSkqrMZ4c17QW03S7vRir1YqLFy+2+to9qT166qmnUFpa6rw88cQTzvs8mf+0aUhtTEwMCgoK8OKLLyI7OxvPPfecTGvUkkl7eVJ6haZlwZXIU/OMZiytrEKIKhhnL57CUkMk/l90FAIDQ+ROze/IOlw0KysLTz75ZJsxBQUFLQ5qAGDz5s0YNGgQ3n33Xdx7771AJw5qAECr1br8AkTeZRONv7BzuCj5QKhdjyLU42zlj3KnQj3cihUrsGDBgjZjEhISUF1dDQAYNWqUc7lWq8XgwYNRXFwMADAYDPjmG9fek5WVlbBYLC0Odpo/B9si6g42OL4zqZQssvnCcIseUeYyGPpzrkV/5+lxza5du2A0GrF69eo2Yz05rrkypqmHVkdjmutJ7VFQUBAMBkOr93XXkFq52fQDgEuO60ote7JR5y2oMiMcVTipDkFp5VkAQKBdQKXqFTOE9SmybnG5D2rI96x2K6AAlBKLbOR9oYoQAPW4UH9G7lSohwsPD0d4eHi7ccnJydBqtTh27BimTJkCALBYLDh16hTi4+MBAKmpqVi7di1KS0sRHR0NNB4MaLVaJCcne3lNyN9Z4ejJpuHZRX1iWkMIkqsrsGdA64UA8h+eHtc8/fTT2LNnT4tCVkpKCn7xi1/gzTff9Oi4xmAwtBitc/68Y26v9mJUKhXCwsLQ0z3zzDP4wx/+gNjYWMybNw+//e1vodE4fkDwZP5Td0NqV69ejVOnTiExMbHV1/XlvHRS4OX5slQaFtmoe1QYHZ/7ACF/IdkfyVpk40GN/7GKxrOLsicb+UC4Lhqwl6HcViF3KtRHBAcHY+nSpVizZg1iY2MRHx+PjRs3AgDmzZsHAEhPT8eoUaOQkZGBjRs3oqKiAitXrsSSJUt4ZlHyOqvU2JONw0WJfMrT45oXXngBTz/9tPP22bNnMX36dLzzzjuYOHEi4OFxTWpqKh577DGYzWZn4SknJwcxMTFISEhwxnz00Ucur5+Tk4OUlBSo1T173sYHH3wQ48ePR2hoKL799lusXr0aRUVFePXVV4EODKlt2hZNmg+pdVdkW79+fbu9EruLsl+zIpuWw0Wp80pUClRJKljsFlTVXQAABNhZZJNDr5gYq/lBTU5ODo4dO4b77rsPcHNQc+DAAXz22Wc8qOmBbHbHcFGlxG6r5H2xAxy9X89L9XKnQn3Ixo0bsWDBAmRkZGDChAn46aefkJeXh9BQx+TFSqUS27dvh06nw+TJk3H33Xdj9uzZyM7Oljt18gNxFgnjGhoQ2mwybfIeM+yokyRYhV3uVKiXiIuLQ1JSkvMybNgwAMCQIUMwaNAgwMPjmoULF0Kr1WLx4sX4/vvv8f7772PdunUuwyCXLl2Kn376CZmZmTh69Chef/11vPbaa1i5cqUs6+7p/KcA8PDDDyMtLQ1XX301fv3rX2PTpk147bXXUF5e7ny+7hpSeyVfzkunDblcKGSRjbri4egAzB4UgzMNZaiuc3xO9ILH3HLoNVt948aNUKlUyMjIQH19PSZOnNjqQc2yZcswefJk6PV6LFy4kAc1PYytcRiLUtFr3nrUiyUNngJc/DvOqgXM5npo2A2fuoFarUZ2dnab7UtcXBy2bdvm07yIAOA/KpUYbj2Pg4OHyp2KX3i933nsCY/FfPsPmCJ3MtRneHJcExISgtzcXCxfvhwpKSkIDQ1FZmYmMjMznTGJiYnYsWMHHn74Ybz00kuIiYnBCy+84Jzj2tc8HVLbmuuuuw4A8MMPPyAsLKzbhtS2xpfz0ulDL+eh1gX65DWp76sxVQIA9KJn91jtq3pNpYMHNX2D88QHEj/w5H1jrroWuj0CDQoJh45/hQlJ6R48ioj6Oj1UMFitCOiDv/CqGqdlUKg5JxtRb5CQkODsXdWcJ8c1Y8aMwZdfftlmTFpaGvbv39/lPLuDp0NqW3PgwAEAcA6f7a4htXILCot2XlfzxAfUTWotjnkEdRK/C8ihVwwXpb7DJhp7snG4KPmARq1BtMUxHOD7U7vlToeIeoh0ewJyS85itnmg3Kl0O6WzyMY52Yiod9q9ezf+9Kc/4eDBgygqKsI//vEP3Hvvvbj99tsRFxcHdOOQWrn1D79cZFPyLJDUDezCjpEmPVaWV2K84El55MBPMvlU01nPVBwuSj4SKfqhCDUorjgqdypERF6XaRCoVA7ESusFJMmdDBFRJ2i1Wrzzzjt48sknYTKZEB8fjyVLluDRRx91xnTXkFq56fSB2J24HGioRuqgIXKnQ31EokngWmM1doX0jB6b/oaVDvIpO3jWM/KtSHU0gBMoazgjdypE1EMItBya1RHHjx/Hb3/7W3z99dcwm80YM2YMnn76aUydOtUZU1xcjOXLlyMvL8/l4K9pyJK3XFICF1VKKDlc1CdEK9eIqGvGjx+PPXv2tBvXXUNq5Za6aJ3cKVAfozQ7hotKuhC5U/FLHC5KPmUTTUU2zslGvjGov2Py7zJUyZ0KEfUQ+YrTWBgdhU80ZR5EtzRz5kxYrVbk5eVh3759uOaaa3Dbbbc5J9i22WyYOXMmamtrsXPnTmzZsgVbt27FI4880s1r0lLjCHloNTxLHRERkT86KyrwnVaDBj3n+ZMDi2zkU5eHi7LIRr5xzZCbAADFajtMplq50yGiHuASTDis06JcMnf4sRcvXsQPP/yAVatW4eqrr8bQoUOxYcMG1NXVobCwEGicWPvIkSN4++23MW7cOPzsZz/Ds88+i1deeQVGo9ELa3SZtfF/Hc+mTERE5DdmVVuwqMqIEFUQ3gquwi9iDDihvCR3Wn6Jw0XJp2xSY082JYeLkm9MGD0VAfvtqFMo8E1hDm4Yf6fcKRFRLxYWFoaRI0firbfewvjx46HVavGXv/wFUVFRzjPa7d69G0lJSYiJiXE+bvr06TCZTNi3b5/LsNLmTCYTTCaT83ZTQS717xOh1CtdYpUA9hWddt5+OCoMnwfoIZSO30/12n7dvObUmsFWHYJrzyMymNubiIjk88tLZkTgEn7UhKJesgGQEBzQubP5UtewJxv5lL1xzhK1knPFkG+oVWrEWxw9Jw/++Lnc6RBRLydJEnJzc3HgwAEEBQVBp9PhT3/6Ez7++GP0798fAFBWVoaoqCiXx4WGhkKj0TiHlLZm/fr1CAkJcV5iY2MBAEKSWl4AKCThvDTFAUC0RWBo7FgvbgVqkt4QiufOX8TVihgPoomIiLyvTuH4XhAaFCl3Kn6JPdnIp6xNJz5gkY18KEaKwFGUoaiKZxglotZlZWXhySefbDOmoKAAycnJWLZsGSIjI/HVV19Br9fj1VdfxW233YaCggJER0cDjcW4KwkhWl3eZPXq1S5nvTMajYiNjcXbU15Fv6CWPaUuakOd1x+21GC53QIAGBQ1BAG6QA/XnIiIiHq7C0oJFkkJi82M2sauVAOC+QOQHFhkI5+yOXuycbgo+U5C8CigoQyn7RfkToWIeqgVK1ZgwYIFbcYkJCQgLy8P27ZtQ2VlJYKDgwEAL7/8MnJzc/Hmm29i1apVMBgM+Oabb1weW1lZCYvF0qKHW3NarRZabcsfoa6KS3K+ljscEEJEROS/lscE4KKqH56p/hF1CkeVLTJ0oNxp+SUW2cinrI1DWjQq9mQj3xk75GdAYR6K1FbU11dDrw+SOyUi6mHCw8MRHt5+qaqurg4AoFC4zrihUChgtzt6a6empmLt2rUoLS119mzLycmBVqt1zttGfcNf+pXhV+FxmG87juvkToaIiPxeVe1F5/XIMBbZ5MA52cinLvdk08mdCvmR66+5FSE2O0wKCXl735E7HSKSmVooEGKzQdOJr0GpqakIDQ3FokWLcOjQIRw/fhy//e1vUVRUhJkzZwIA0tPTMWrUKGRkZODAgQP47LPPsHLlSixZsqTdHmlEREREnVVdXwEA0NsF9DzTuCxYZCOfsjVORaNVs8hGvqNSKXGVxTE/UUFRjtzpEJHMbrUnYGfxGdxlju3wY8PDw/Hxxx+jpqYG06ZNQ0pKCnbu3IkPPvgAY8c6TjagVCqxfft26HQ6TJ48GXfffTdmz56N7OxsL6wNyco5xZ6QNw8iIiIAGrMZK8sr8YtLFrlT8VscLko+5RguKkGtYpGNfGuwfjj2iYP4oeFHuVMhoh5CwP1JCNqSkpKCTz75pM2YuLg4bNu2rZOZEREREXVcoMmCecZq/KgIkzsVv8WebORT1sb/NWp2XSXfmnDVDADACXUDGky1cqdDRERERETUvcw1AIAGZcuzkpNvsMhGPtU0XFTH8eHkY9Mm3IX+NjvqFAps2/mq3OkQkYx2Ks7iHkMk8tRlcqdCRERE1G0uWSpwWKNBmSZA7lT8FoeLkk9ZmuZkY5GNfEyr1mC0ZQC+Vl7CrlPbcRcelDslIpLJBake3+p1CDI3yJ1Km4RwzPNlNBrlTqVXatpuTduRiIior7q5xgq7woRj6nK8MNCAiaY63CR3Un6KRTbyKWvj/DdaDhclGVwTmYavjR/ge3EWwm6HpGBnXiLquaqrqwEAsbEdP0EDXVZeXo6QkBCvPHecVQu17TzC+gV65fmJiIg88etKMyJRiTURBgCATuIc6HJhkY18qqknm07L7qvke3fccB9e+fCfKFVL+GLfu5g6Yb7cKRERuRUTE4OSkhIEBQVBkjw7SYPRaERsbCxKSkoQHBzs9Rx7sqqqKsTFxWHAgAFee40ZDQOQYtyPPcEDvfYaREREnjIJEwBAr+TxtlxYZCOfMZtNEI0HCXoNf/El34sOG4ix5n4o0NXiw0OvsshGRD2aQqHAoEGDOvXY4OBgvy+yNVGw1zIREfVxRgWghgK1kgWAhABVkNwp+S1+6yCfqTNVO6/rdCyykTymxMwCABQozqK+vrrdeCLqizhHFxEREfUd9w4MwA3xg1Coc3zHCVDzhza5sMhGPlPXUOu8ruPZTkgmP7/5EYRZ7ahSKvD6jjVyp0NERL3Y64FluDZ+ED6zH5c7FSIiItQ2VniCdP3lTsVvschGPtPQUOO8rteyJxvJQ6/TYbJiJADgXxW5sNkscqdERD6mhASt3Q6F1Pe+Bmm1WqxZswZarVbuVGTni21hkQTqFQrY2DuSiIh6gLrGKRKC9GFyp+K3+t63S+qxTJYGAIBKCKhUarnTIT/2m1v+iAC7HT9pgLd2/EHudIjIx263Dcben07jbnO83Kl0O61Wi6ysLBbZuC2IiMiPNP3Uc7exGr+prEJc/8EyZ+S/WGQjn6k31wEAVPyxl2QWHz0YN9gSAQD/e+49VNdWyp0SERERERFRl8yprsH9l6qQGDZU7lT8Fots5DMms2NONpVglY3kl3nnXxBmtaNULWHdP34pdzpERERERETdQh8cKncKfotFNvIZk7keAKCUOxEiANFhAzGvv+NMo9ulIrz76XNyp0REPrJbUYoVURH4UnVO7lSIiIiIus1hrRZFahX6BQ2QOxW/xSIb+YzZOSeb3JkQOSybsx5TGgZASBL+VPwaPi/4h9wpEZEPlEl1yA/Q46yiXu5UiIiIiLrshlobrq1vwNrwAZg7MBo6fYDcKfktFtnIZ0wWx8EMi2zUU0iShKcXbMVwkwLVSgWeOPwktua9IHdaRETUS8TYNEipb0Ao9HKnQkREfuy+CjP+s9wxz3Q/u4AkSXKn5LdYZCOfsdrMAAAl+IGnniMsJBx/uuMDXGWSYFQq8Ifiv+I/X78Nl4wX5E6NiLyll8wNmpWVBUmSXC4Gg6HNx+Tn5yM5ORk6nQ6DBw/Gpk2bWsRs3boVo0aNglarxahRo/D+++97cS26hze2RWFhIebOnYuEhARIkoTnn3++w3nNqg/D5rLzmKCI7fBjifzV2rVrMWnSJAQEBKB///6txhQXF2PWrFkIDAxEeHg4HnjgAZjNZpeYw4cPIy0tDXq9HgMHDsRTTz0FccX+3ZN9IlFfICChWuEo7wTYebwtJxbZyGfMVsdwUWXvOLYhPxIblYBX5+fhuoYg2CQJO5Q/4Y53b8SaN+/G0ZN75U6PiPzY6NGjUVpa6rwcPnzYbWxRURFuvfVWXH/99Thw4AAee+wxPPDAA9i6daszZvfu3Zg/fz4yMjJw6NAhZGRk4O6778Y333zjozXqvO7eFnV1dRg8eDA2bNjQbsGuXb2kcEvUE5jNZsybNw/33Xdfq/fbbDbMnDkTtbW12LlzJ7Zs2YKtW7fikUceccYYjUbcfPPNiImJQUFBAV588UVkZ2fjuecuz7HryX6AqK8wScAFlWP28wA7yzxyUsmdAPkPi9UEsCcb9VBhIeH462++xl8/WIN3L27FObUC7+Eo3vvqVxj6qYRERQyGhY/DyNhrMeaqSQgNiZI7ZSLyAyqVyuMC0KZNmxAXF+fskTVy5Ejs3bsX2dnZmDt3LgDg+eefx80334zVq1cDAFavXo38/Hw8//zz+N///V8vrknXdfe2mDBhAiZMmAAAWLVqVSez4ncaoo568sknAQBvvPFGq/fn5OTgyJEjKCkpQUxMDADg2WefxeLFi7F27VoEBwfj73//OxoaGvDGG29Aq9UiKSkJx48fx3PPPYfMzExIkuTRfqA1JpMJJpPJebuqqgpoLOwRdUbTe+fKnpbd6T8G6XBe5ZiHTSdY5pETt343+duODSirKoJAsw9Osw9R0/L27kez++0CLZa5fjBbPqfzeqvP3ewxzdNo7fEur9m0xH7l07h/DFref9FyHtACKsEvpNQzSZKEe2c/hf9X/yhe+fAJ7Kz6HMc1NpzQAidwBjlVZ4CqbcD3QH+bHUE2CYFChQChhlbSQC2poIIKKkkNlULd+L8KgASFJAFQOIY5QYLUeN2xXIIkKdB0DzycQ0Hy4OBOrdTiobs5zxxRb3XixAnExMRAq9Vi4sSJWLduHQYPHtxq7O7du5Genu6ybPr06XjttddgsVigVquxe/duPPzwwy1iOjNU0te6e1t0h78FnkNm/4GYYf8R13XLMxLR7t27kZSU5CywofHzazKZsG/fPkydOhW7d+9GWloatFqtS8zq1atx6tQpJCYmdno/sH79emchsLnYWA4Lp64pLy9HSEiI119HB43XX4PcY5Gtm3xS8i4O6cweRPZCrR3Hd6ZO1tgG6vi2ox4uUN8PD81/Hg8BKDy5H58UvI6TVYU4jXKcV9lQrVTgklKBS0oAsDVeGtp+0pa1aJ8IstnxkG9fkoi6ycSJE/HWW29h2LBhOHfuHJ5++mlMmjQJhYWFCAsLaxFfVlaGqCjXXrZRUVGwWq24ePEioqOj3caUlZV5fX26whvbojs0SHZUKpWwwNYtz0f+Y/v27Xjqqafw3XffITAwEDfccAPee+895/3FxcVYvnw58vLyoNfrsXDhQmRnZ0OjuXzwfPjwYaxYsQLffvstBgwYgHvvvRe/+93vXCY8z8/PR2ZmJgoLCxETE4NHH30US5cu9fn6dkRrn9/Q0FBoNBrnvqqsrAwJCQkuMU2PKSsrQ2JiYqf3A6tXr0ZmZqbztt1uR0VFBcLCwrwymbzRaERsbCxKSkoQHBzc7c/fE/nbOldVVSEuLg4DBgzwyevpJa0HUeQtrHZ0k3hNHJQNp4E2epe0ttxlP93Yw0tyE+C8Jprf3cpztvP60hVLW8a5ey7Jbc6uy1vJufG5JCgwc8w9reZH1BONHjweowePd94WQuB02Un8+6d9KDeewaXa8zA2lKPOYoTVZoFVWGCxm2EVVliFFbbGAy/R+M95XQjHx0cICElAiCt7nbbN01iN1D29NYj6kjtsg7GhZCf2RPbsvkczZsxwXh8zZgxSU1MxZMgQvPnmmy4HgM1d+b2gqQd88+WtxfT0s5B5a1sQyWHr1q1YsmQJ1q1bh2nTpkEI4TLHYNOcZBEREdi5cyfKy8uxaNEiCCHw4osvAs3mJJs6dSoKCgpw/PhxLF68GIGBgc65y5rmJFuyZAnefvttfP3111i2bBkiIiLaHC7ZGVlZWa32/mquoKAAKSkpHj1fa5/TK/dVnd3fuXv+Jlqt1qWHHAC3J2joTsHBwX5RcGrO39ZZofD+XGmT6+oxWslpbeTEIls3Wfurnn9mLiLqOkmSEBs9BLHRQ+ROhYg6SQEJisb/e5PAwECMGTMGJ06caPV+g8HQokfa+fPnoVKpnL293MVc2dujp+uObUEkB6vVigcffBAbN27EPfdc/uF5+PDhzutyz0nWGStWrMCCBQvajLmy55k7BoOhxclYKisrYbFYnPsqd59xNOvRxv0A+ROp8ff3FZVVqI5OlDsdv8bTThARERH1AiaTCUePHnU7xCk1NRW5ubkuy3JycpCSkuKce8hdzKRJk7yYeffrjm1BJIf9+/fjzJkzUCgUGDduHKKjozFjxgwUFhY6Y9qbk6wpprU5yc6ePYtTp045Y1qbk2zv3r2wWCyt5mcymWA0Gl0unggPD8eIESPavOh0Oo+eKzU1Fd9//z1KS0udy3JycqDVapGcnOyM+fLLL2E2m11iYmJinMU87gfIX0k67/e8JPdYZCMiIiK/8q3iHFZGhGGX6oLcqbRp5cqVyM/PR1FREb755hvcddddMBqNWLRoEdA4b9Avf/lLZ/zSpUvx008/ITMzE0ePHsXrr7+O1157DStXrnTGPPjgg8jJycEzzzyDf//733jmmWfw6aef4qGHevbsjd7YFmazGQcPHsTBgwdhNptx5swZHDx4ED/88IMs60j+4eTJk0Dj8MonnngC27ZtQ2hoKNLS0lBRUQF0YE6y1uYba7qvrZimOclas379eoSEhDgv3pjsv7i4GAcPHkRxcTFsNpvzc1hTUwMASE9Px6hRo5CRkYEDBw7gs88+w8qVK7FkyRLn0MKFCxdCq9Vi8eLF+P777/H+++9j3bp1zl588HA/0BNotVqsWbOmxRDVvszf1tmX63tKrYJNF+j11yH3WGQjIiIiv3JaqsEn/QJRoqiVO5U2nT59Gj//+c8xfPhwzJkzBxqNBnv27EF8fDwAoLS0FMXFxc74xMRE7NixA1988QWuueYa/OEPf8ALL7zgMixs0qRJ2LJlCzZv3oyrr74ab7zxBt555x1MnDhRlnX0lDe2xdmzZzFu3DiMGzcOpaWlyM7Oxrhx4/DrX/9alnWk3i0rK8txBvE2Lnv37oXdbgcAPP7445g7dy6Sk5OxefNmSJKEd9991/l8cs1Jtnr1alRVVTkvJSUlndwi7v3+97/HuHHjsGbNGtTU1Dg/h3v37gUAKJVKbN++HTqdDpMnT8bdd9+N2bNnIzs72/kcISEhyM3NxenTp5GSkoJly5YhMzPTZY5GT/YDPYFWq0VWVpbfFJzgh+vsi/WdUO/Yt6yODMcJ1SWvvQ61j3OyEREREfVAW7ZsafP+N954o8WytLQ07N+/v83H3XXXXbjrrru6nJ8veWNbJCQkOAsOnRVuU2O0yYRgnX8cKJJ7ns5JVl1dDQAYNWqUc7lWq8XgwYOdhWI55yRrbdL/7vbGG2+0+pltLi4uDtu2bWszZsyYMfjyyy/bjPFkn0jUFzxYbsEhvUCJWo3gwEi50/FrLLIREREREXXC7IYITKg6gD1XxcmdCsksPDwc4eHh7cYlJydDq9Xi2LFjmDJlCgDAYrHg1KlTzp6ZqampWLt2LUpLS53zDrY2J9ljjz0Gs9kMjUbjjLlyTrKPPvrI5fU5JxlR32VsPHtpWP+Bcqfi1zhclIiIiIiIyAeCg4OxdOlSrFmzBjk5OTh27Bjuu+8+AMC8efMAP5yTjIi6g9VZZIsJHyJ3Mn6NPdmIiIiIiIh8ZOPGjVCpVMjIyEB9fT0mTpyIvLw8hIaGAs3mJFu2bBkmT54MvV6PhQsXtjon2fLly5GSkoLQ0FC3c5I9/PDDeOmllxATE9Mj5yQjoq67PT4QorHAPigqUe50/BqLbEREREREnbBFfw5PBMXgJnsRrpM7Geo11Go1srOzXYpmV+KcZETUEfWKy4MU9Vq9rLn4Ow4XJSIiIiLqhBqFDWfVKtTDIncqRORlrZ1B1mAwtPmY/Px8JCcnQ6fTYfDgwdi0aVOLmK1bt2LUqFHQarUYNWoU3n///RYxL7/8MhITE6HT6ZCcnIyvvvrK5X4hBLKyshATEwO9Xo8bb7wRhYWFvXJ9169fjwkTJiAoKAiRkZGYPXs2jh075hKzePHiFrldd13Xf+qQa509eV1v/I3JO1hkIyIi6oDjx4/jjjvuQHh4OIKDgzF58mR8/vnnLjHFxcWYNWsWAgMDER4ejgceeABms1m2nMnVLFsC9pwqwRxLvNypEBFRLzJ69GiUlpY6L4cPH3YbW1RUhFtvvRXXX389Dhw4gMceewwPPPAAtm7d6ozZvXs35s+fj4yMDBw6dAgZGRm4++67Xc4u+8477+Chhx7C448/jgMHDuD666/HjBkznGejBYA//vGPeO655/DnP/8ZBQUFMBgMuPnmm51ns+1N65ufn4/ly5djz549yM3NhdVqRXp6Ompra11e75ZbbnHJbceOHV1aVznX2ZPX9fRv/LOaum7ZDtQFopc4duyYuP3220VYWJgICgoSkyZNEnl5eS4xP/30k7jttttEQECACAsLE/fff78wmUwdep2qqioBQFRVVXXzGhAR9R7cF7p31VVXiVtvvVUcOnRIHD9+XCxbtkwEBASI0tJSIYQQVqtVJCUlialTp4r9+/eL3NxcERMTI1asWOHxa3D7e9euv6wQYk2w2P3yb+ROhXq53/xlkkh6I0lkvblA7lT6JO4L5ce/wWVr1qwRY8eO9Tj+0UcfFSNGjHBZdu+994rrrrvOefvuu+8Wt9xyi0vM9OnTxYIFl/cp1157rVi6dKlLzIgRI8SqVauEEELY7XZhMBjEhg0bnPc3NDSIkJAQsWnTpg6soSu51vdK58+fFwBEfn6+c9miRYvEHXfc4XFunpJrndt7XU/+xtNfGSGS3kgSn60b6nH+5LmO7At7zZxsM2fOxLBhw5CXlwe9Xo/nn38et912G3788UcYDAbYbDbMnDkTERER2LlzJ8rLy7Fo0SIIIfDiiy92+PWsViusVmuL5ZIkQalUusS5461YAFCpVJ2KtdlsEEL06FilUuk8K5K3Yu12O+x2e4+OVSgUUDSOre8JsUII2Gy2Hh3b/HPkrVjI9Ln39T6ivcf4q4sXL+KHH37A66+/jquvvhoAsGHDBrz88ssoLCyEwWBATk4Ojhw5gpKSEsTExAAAnn32WSxevBhr1651nhnOW8rPnUal6RLsovXPtlJSIEQT4rxdZa6CzU2sQlKgv0usETbR+mdFgoRQbX/nbaO5Glbh/n00QBvqvF5tqYbF7llsjaUGZrv7oXmhmv7O/WyNpRZme8sehNXWKtQ1xhB1hzrbJZirTkOj1AAAGmwm1FhqW8TZ7YDFZkegKhAapRoCgMlmRo2lBgKAEAAEICAgBCAABCj10Ci1EAIw2y2osdS4zSNApYdOqQMAWOwWVLcRq1fqoVc5Yq12K4wW9z1e9Eod9CrHHD82uw1VFqPbWJ1SiwBVgCNW2FBlNkKjUCM0MBwhAyLcPo6oNzhx4gRiYmKg1WoxceJErFu3DoMHD241dvfu3UhPT3dZNn36dLz22muwWCxQq9XYvXs3Hn744RYxzz//PADAbDZj3759WLVqlUtMeno6du3aBTT2piorK3N5La1Wi7S0NOzatQv33ntvr1nf1lRVVQEABgwY4LL8iy++QGRkJPr374+0tDSsXbsWkZGRnV7XJnKtc1uv25G/sVEVCpJXryiyefOgxmQywWQyOW8bjY4vDR999BECAgJaxBsMBlx//fXO2x9++KHbg/OIiAjceOONztvbt293O1woNDQUP/vZz5y3P/nkE9TVtd7VMzg4GNOnT3fe/uyzz5x5XykgIAAzZ8503v78889RWVnZaqxGo8Edd9zhvP3VV1/hwoULrcYqlUrMmTPHeXvXrl0oKytrNRbNTkkOAN9++y1Onz7tNvbOO+90HvTv27cPP/30k9vY22+/HVqtFgBw6NAh/Pjjj25jb731VgQGBgIADh8+jOPHj7uNTU9PR0iI48Dy6NGjOHLkiNvYm266ybnTP3HiBL777ju3sWlpac6d/8mTJ3HgwAG3sVOmTEF0dDTQOPSsoKDAbex1112H2NhYAMCZM2ewZ88et7ETJkxAQkICAODcuXPYuXOn29hx48bhqquuAgBcuHAB+fn5bmOvvvpqDB8+HABQWVmJzz77zG3sqFGjMHr0aKDxM5eTk+M2dtiwYRg7diwAoK6urs2u4EOGDMH48eOBxi8lH374odvY+Ph4XHvttUBjYam1+S+aDBo0CKmpqc7bbcX2lX2Eu+f2d2FhYRg5ciTeeustjB8/HlqtFn/5y18QFRWF5ORkoPELV1JSkrMtQuOXKZPJhH379mHq1KktntddW9QZiv9OxbLYfihVtd7EDzGb8c8zl/fX9wyMxkmNutXYgRYrPj591nl7RUwUChv3uVcaYLMhv/iM8/ZKQyT26XWtxurtdnz70+V24HdREdgZ4H6S3sNFl4fErIsMR25gy/a5ybenSqBv/MHlT+ED8GFQv5ZBgcD1UjhGKC9ysnrqFjsUp3HrpmSk1TcAAHL6BeLxiDC38RvPX8QttY797NcBejwS5b749NSFctxZ4yjYfaXXYZnB/UHk6osVWFjtKKzt1Wnxq+got7EPVVTinipHYa1Qo8GCge7nHbq3sgorLjkOdE+qVZg7KMZt7KIqI1ZWXAIAlCqVmBs3ENNq6/DrqjiMWf2528cR9XQTJ07EW2+9hWHDhuHcuXN4+umnMWnSJBQWFiIsrOXnvaysDFFRrp/BqKgoWK1WXLx4EdHR0W5jmo6rLl68CJvN1mZM0/+txbR1HNUT1/dKQghkZmZiypQpSEpKci6fMWMG5s2bh/j4eBQVFeF3v/sdpk2bhn379jmPDXvTOrf3up78jc+pHD/G12u7XmikrukVRTZvHdSgcWLFJ5980mfrQkREvZckScjNzcUdd9yBoKAgKBQKREVF4eOPP0b//o5eXK19mQoNDYVGo3H7JbI72yIBQBKA5LZnrwS7cO3F5T4WrrFtPa9wjZU68Lwdim1z3RyxdufdktvYfTotrotKdvs8RJ4YFXod9td8ApME2Jt9tkS779PL72vRxvsUuPJ5244VHYkVl2Pt7eSLZp9DezvP23xf0DxWsPco9XIzZsxwXh8zZgxSU1MxZMgQvPnmm8jMzGz1MdIV7/umUTfNl7cWc+Wy7orpCDnXt8mKFSvw3XfftegUMH/+fOf1pKQkpKSkID4+Htu3b3fpCNJRcq2zp6/b1vMMM6lwRGdD4Lg7O7ze1L16RZHNWwc1ALB69WqXN67RaERsbCxmzZrVau+3K9/Yt99+e5t5N9e8t0h7sc17obTnpptu8jh26tSpbQ6pbO7666/3OHbSpEkex1577bWYMGGC2/ubD4lLTk529kxqL3bs2LHOno7txY4ZM8bZk6q92JEjRzp7aLUXO3ToUAwZMsSj2MGDBzt7lLVG0ew0zHFxcRg0aJBHsQMHDsSdd7rfuTaPjYqK8jg2IiLC49jQ0FCPY4ODgz2ODQgIaDO2+edIo9F4HKtUKj2ORWNvS09je+s+ois9qXqjrKysdotcBQUFSE5OxrJlyxAZGYmvvvoKer0er776Km677TYUFBQ4e5+29mWxrS+R7tqizhiQVYJPOhD/QQdit3QgdnMHYl/uQOyzHYhd23gh8pYH5z2L+VVr8cP5GjRYbMhXSlArFIhWKfCWSgGNUgGNSgGtyvG/RqmASilBIUlokBzDrNMk4FsAUuNtx/+O/YjUtLxx33EDAPf95V1N6EDsmA7EXtWB2IEdiCXqbQIDAzFmzBicOHGi1fsNBkOL49Dz589DpVI5e0W5i2k6rg0PD4dSqWwzpukslGVlZc7vIVfGdAdfrG9z999/Pz788EN8+eWXbR4HAUB0dDTi4+Pd5tZZvl5nd6/ryd/4j7f/H06d/h5pE2Z3en2pe8haZJP7oAaNY5lb61KqUqlc5ilyx5OYnhTbvMjjz7HN5/lirGexkiR5/F7ry7HoIZ9lb+8jOvKYvmDFihVYsGBBmzEJCQnIy8vDtm3bUFlZ6fwh5uWXX0Zubi7efPNNrFq1CgaDocUZoyorK2GxWNx+oXLXFhFRz2cI0cEQ0vrQaCLqu0wmE44ePeoyTUhzqamp+Oijj1yW5eTkICUlBWq12hmTm5vrMmdXTk4OJk2aBDT+aJycnIzc3FyXH3mbOqAAQGJiIgwGA3JzczFu3DigcdqU/Px8PPPMM71qfdF4/H7//ffj/fffxxdffIHExMR2cysvL0dJSYlLAao7+Gqd23tdT/7G8dFXIT76qm5Ya+oyn5yKwY0LFy6Io0ePtnmpr68Xn376qVAoFC3O5HDVVVeJ9evXCyGE+N3vfieuvvpql/srKioEgBZnIW0Lz6BDRMR9oTsffvihUCgUorq62mX5sGHDxNq1a4UQQuzYsUMoFApx9uxZ5/1btmwRWq3W4+3J7U9ExH1hT8C/wWWPPPKI+OKLL8TJkyfFnj17xG233SaCgoLEqVOnhBBCrFq1SmRkZDjjT548KQICAsTDDz8sjhw5Il577TWhVqvF//3f/zljvv76a6FUKsWGDRvE0aNHxYYNG4RKpRJ79uxxxmzZskWo1Wrx2muviSNHjoiHHnpIBAYGOl9XCCE2bNggQkJCxHvvvScOHz4sfv7zn4vo6GhhNBp73fred999IiQkRHzxxReitLTUeamrqxNCCFFdXS0eeeQRsWvXLlFUVCQ+//xzkZqaKgYOHNil9ZVzndt7XeGlvzF5riP7QlmLbJ7y1UGNYENCRCQE94VuXbhwQYSFhYk5c+aIgwcPimPHjomVK1cKtVotDh48KIQQwmq1iqSkJHHTTTeJ/fv3i08//VQMGjRIrFixwuPX4fYnIuK+sCfg3+Cy+fPni+joaKFWq0VMTIyYM2eOKCwsdN6/aNEikZaW5vKYL774QowbN05oNBqRkJAg/vu//7vF87777rti+PDhQq1WixEjRoitW7e2iHnppZdEfHy80Gg0Yvz48SI/P9/lfrvdLtasWSMMBoPQarXihhtuEIcPH+6V69s4vWyLy+bNm4UQQtTV1Yn09HQREREh1Gq1iIuLE4sWLRLFxcVdWl8517m91xVe+huT5zqyL5SEpxNpyejixYsYMWIE0tLS8Pvf/x56vR6vvPIK/uu//gsFBQUYO3YsbDYbrrnmGkRFRWHjxo2oqKjA4sWLMXv2bLz44osev5bRaERISAiqqqrcnpGUiKiv477Qvb179+Lxxx/H3r17YbFYMHr0aPz+9793mbS2uLgYy5YtQ15eHvR6PRYuXIjs7GyPh4Ry+xMRcV/YE/BvQETUsX1hr5h0Jzw8HB9//DEef/xxTJs2zXlQ88EHH2Ds2LFA4zxC27dvx7JlyzB58mSXgxoiIqLukpKSgk8+afvUAnFxcdi2bZvPciIiIiIiIvn1iiIbeFBDREREREREREQ9mGenFSQiIiIiIiIiIiK3WGQjIiIiIiIiIiLqIhbZiIiIiIiIiIiIuohFNiIiIiIiIiIioi5ikY2IiIiIiIiIiKiLes3ZRX1FCAEAMBqNcqdCRCSbpn1g0z6RfIttERER26KegO0REVHH2iMW2a5QXV0NAIiNjZU7FSIi2VVXVyMkJETuNPwO2yIiosvYFsmH7RER0WWetEeS4E9DLux2O86ePYugoCBIkuTx44xGI2JjY1FSUoLg4GCv5tibcTu1j9vIM9xO7evKNhJCoLq6GjExMVAoOLOAr3W2LQI/Gx7jdmoft1H7uI0809ntxLZIfmyPvIvbyDPcTu3jNmqfr46N2JPtCgqFAoMGDer044ODg/mm9gC3U/u4jTzD7dS+zm4j9hqQT1fbIvCz4TFup/ZxG7WP28gzndlObIvkxfbIN7iNPMPt1D5uo/Z5+9iIPwkRERERERERERF1EYtsREREREREREREXcQiWzfRarVYs2YNtFqt3Kn0aNxO7eM28gy3U/u4jfwT/+6e4XZqH7dR+7iNPMPt5J/4d28ft5FnuJ3ax23UPl9tI574gIiIiIiIiIiIqIvYk42IiIiIiIiIiKiLWGQjIiIiIiIiIiLqIhbZiIiIiIiIiIiIuohFNiIiIiIiIiIioi5ikY2IiIiIiIiIiKiLWGTrJi+//DISExOh0+mQnJyMr776Su6UeoysrCxIkuRyMRgMcqcluy+//BKzZs1CTEwMJEnCP//5T5f7hRDIyspCTEwM9Ho9brzxRhQWFsqWrxza20aLFy9u8d667rrrZMtXDuvXr8eECRMQFBSEyMhIzJ49G8eOHXOJ4XvJv7A9co/tUevYHrWP7VH72B5Rc2yL2sb2qCW2RZ5he9Q+udsjFtm6wTvvvIOHHnoIjz/+OA4cOIDrr78eM2bMQHFxsdyp9RijR49GaWmp83L48GG5U5JdbW0txo4diz//+c+t3v/HP/4Rzz33HP785z+joKAABoMBN998M6qrq32eq1za20YAcMstt7i8t3bs2OHTHOWWn5+P5cuXY8+ePcjNzYXVakV6ejpqa2udMXwv+Q+2R+1je9QS26P2sT1qH9sjasK2yDNsj1yxLfIM26P2yd4eCeqya6+9VixdutRl2YgRI8SqVatky6knWbNmjRg7dqzcafRoAMT777/vvG2324XBYBAbNmxwLmtoaBAhISFi06ZNMmUpryu3kRBCLFq0SNxxxx2y5dQTnT9/XgAQ+fn5QvC95HfYHrWN7VH72B61j+2RZ9ge+S+2Re1je9Q2tkWeYXvkGV+3R+zJ1kVmsxn79u1Denq6y/L09HTs2rVLtrx6mhMnTiAmJgaJiYlYsGABTp48KXdKPVpRURHKyspc3ldarRZpaWl8X13hiy++QGRkJIYNG4YlS5bg/Pnzcqckq6qqKgDAgAEDAL6X/ArbI8+wPeoY7kM8x/bIFdsj/8S2yHNsjzzH/UfHsD1y5ev2iEW2Lrp48SJsNhuioqJclkdFRaGsrEy2vHqSiRMn4q233sInn3yCV155BWVlZZg0aRLKy8vlTq3Hanrv8H3VthkzZuDvf/878vLy8Oyzz6KgoADTpk2DyWSSOzVZCCGQmZmJKVOmICkpCeB7ya+wPWof26OO4z7EM2yPXLE98l9sizzD9qhjuP/wHNsjV3K0R6ouPwMBACRJcrkthGixzF/NmDHDeX3MmDFITU3FkCFD8OabbyIzM1PW3Ho6vq/aNn/+fOf1pKQkpKSkID4+Htu3b8ecOXNkzU0OK1aswHfffYedO3e2uI/vJf/Bv7V7bI86j++rtrE9csX2iPh3bhvbo87h+6p9bI9cydEesSdbF4WHh0OpVLaoeJ4/f75FZZQcAgMDMWbMGJw4cULuVHqsprML8X3VMdHR0YiPj/fL99b999+PDz/8EJ9//jkGDRrkXM73kv9ge9RxbI/ax31I57A9Ynvkr9gWdQ7bo7Zx/9F5bI983x6xyNZFGo0GycnJyM3NdVmem5uLSZMmyZZXT2YymXD06FFER0fLnUqPlZiYCIPB4PK+MpvNyM/P5/uqDeXl5SgpKfGr95YQAitWrMB7772HvLw8JCYmutzP95L/YHvUcWyP2sd9SOewPWJ75K/YFnUO26O2cf/ReWyPfN8ecbhoN8jMzERGRgZSUlKQmpqKv/71ryguLsbSpUvlTq1HWLlyJWbNmoW4uDicP38eTz/9NIxGIxYtWiR3arKqqanBDz/84LxdVFSEgwcPYsCAAYiLi8NDDz2EdevWYejQoRg6dCjWrVuHgIAALFy4UNa8famtbTRgwABkZWVh7ty5iI6OxqlTp/DYY48hPDwcd955p6x5+9Ly5cvxP//zP/jggw8QFBTk/EUmJCQEer0ekiTxveRH2B61je1R69getY/tUfvYHlETtkXtY3vUEtsiz7A9ap/s7VGXz09KQgghXnrpJREfHy80Go0YP3688/SwJMT8+fNFdHS0UKvVIiYmRsyZM0cUFhbKnZbsPv/8cwGgxWXRokVCNJ5aeM2aNcJgMAitVituuOEGcfjwYbnT9qm2tlFdXZ1IT08XERERQq1Wi7i4OLFo0SJRXFwsd9o+1dr2ASA2b97sjOF7yb+wPXKP7VHr2B61j+1R+9geUXNsi9rG9qgltkWeYXvUPrnbI6kxCSIiIiIiIiIiIuokzslGRERERERERETURSyyERERERERERERdRGLbERERERERERERF3EIhsREREREREREVEXschGRERERERERETURSyyERERERERERERdRGLbERERERERERERF3EIhsREREREREREVEXschGRERERERERETURSyyERERERERERERdRGLbERERERERERERF30/wGBrHU8pafingAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(15, 4))\n", + "fig.subplots_adjust(wspace=0.3)\n", + "\n", + "ax = fig.add_subplot(1, 3, 1)\n", + "ax.set_ylabel('Vm (mV)')\n", + "ax.axhline(vlo, **kw)\n", + "ax.axhline(vhi, **kw)\n", + "ax.plot(dA.time(), dA['amp.Vm'], label='Model A')\n", + "ax.plot(dB.time(), dB['amp.Vm'], label='Model B')\n", + "ax.plot(dC.time(), dC['amp.Vm'], label='Model C')\n", + "ax.legend()\n", + "\n", + "ax = fig.add_subplot(1, 3, 2)\n", + "ax.set_ylabel('Vp (mV)')\n", + "ax.plot(dA.time(), dA['amp.Vp'], label='Model A')\n", + "ax.plot(dB.time(), dB['amp.Vp'], label='Model B')\n", + "ax.plot(dC.time(), dC['amp.Vp'], '--', label='Model C')\n", + "ax = ax.inset_axes((0.4, 0.15, 0.25, 0.7))\n", + "ax.plot(dA.time(), dA['amp.Vp'], label='Model A')\n", + "ax.plot(dB.time(), dB['amp.Vp'], label='Model B')\n", + "ax.plot(dC.time(), dC['amp.Vp'], '--', label='Model C')\n", + "ax.set_xlim(4.998, 5.01)\n", + "\n", + "ax = fig.add_subplot(1, 3, 3)\n", + "ax.set_ylabel('I obs (pA)')\n", + "ax.plot(dA.time(), dA['amp.I_obs'], label='Model A')\n", + "ax.plot(dB.time(), dB['amp.I_obs'], label='Model B')\n", + "ax.plot(dC.time(), dC['amp.I_obs'], '--', label='Model C')\n", + "ax = ax.inset_axes((0.2, 0.10, 0.45, 0.35))\n", + "ax.plot(dA.time(), dA['amp.I_obs'], label='Model A')\n", + "ax.plot(dB.time(), dB['amp.I_obs'], label='Model B')\n", + "ax.plot(dC.time(), dC['amp.I_obs'], '--', label='Model C')\n", + "ax.set_xlim(4.999, 5.005)\n", + "ax.set_ylim(-1000, 500)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "70188a91", + "metadata": {}, + "source": [ + "Again, the models look very similar.\n", + "\n", + "At the transitions, we see a slight difference between models A and B and model C:\n", + "In A and B, $V_c$ appears in the equation for $I_\\text{obs}$, and so the output changes instantaneously when $V_c$ does.\n", + "In C we observe $V_o - V_p$, both of which change smoothly." + ] + }, + { + "cell_type": "markdown", + "id": "3c33ed65", + "metadata": {}, + "source": [ + "### Model C: (1, 3b, 5)\n", + "\n", + "Just to check our maths, we can implement a model C using the Lei et al. formulation of (1, 3b, 5)." + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "618d13d0", + "metadata": {}, + "outputs": [], + "source": [ + "mD = myokit.parse_model('''\n", + "[[model]]\n", + "amp.Vm = -80 [mV]\n", + "amp.Vp = -80 [mV]\n", + "amp.I_obs = 0 [pA]\n", + "\n", + "[engine]\n", + "time = 0 [ms] in [ms] bind time\n", + "pace = 0 bind pace\n", + "\n", + "[amp]\n", + "Rs = 15e-3 [GOhm] in [GOhm]\n", + "Cm = 25 [pF] in [pF]\n", + "Cp = 5 [pF] in [pF]\n", + "Rf = 0.5 [GOhm] in [GOhm]\n", + "Cf = 0.15 [pF] in [pF]\n", + "tau_amp = 20e-6 [ms] in [ms]\n", + "tau_c = tau_amp * (Cf + Cp) / Cf\n", + " in [ms]\n", + "I = 5 [nS] * Vm\n", + " in [pA]\n", + "Vc = engine.pace * 1 [mV]\n", + " in [mV]\n", + "dot(Vm) = (Vp - Vm) / (Rs * Cm) - I / Cm : Equation 1 (S2.10)\n", + " in [mV]\n", + "dot(Vp) = (Vc - Vp) / tau_c : Equation 3b (S2.12)\n", + " in [mV]\n", + "dot(I_obs) = (I + Cm * dot(Vm) + Cp * dot(Vp) - I_obs) / (Rf * Cf) : Equation 5 (S2.5 and S2.8)\n", + " in [pA]\n", + "''')\n", + "mD.check_units(myokit.UNIT_STRICT)" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "d6729c21", + "metadata": {}, + "outputs": [], + "source": [ + "sD = myokit.Simulation(mD, p)\n", + "sD.set_tolerance(tol, tol)\n", + "sD.pre(5)\n", + "dD = sD.run(20, log_interval=dt).npview()" + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "d0c536f7", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(15, 4))\n", + "fig.subplots_adjust(wspace=0.4)\n", + "ax = fig.add_subplot(1, 3, 1)\n", + "ax.set_ylabel('Vm (mV)')\n", + "ax.plot(dC.time(), dC['amp.Vm'] - dD['amp.Vm'], 'k', label='Model C - Model D')\n", + "ax.legend()\n", + "ax = fig.add_subplot(1, 3, 2)\n", + "ax.set_ylabel('Vp (mV)')\n", + "ax.plot(dC.time(), dC['amp.Vp'] - dD['amp.Vp'], 'k')\n", + "ax = ax.inset_axes((0.40, 0.11, 0.5, 0.4))\n", + "ax.plot(dC.time(), dC['amp.Vp'] - dD['amp.Vp'], 'k')\n", + "ax.set_xlim(4.994, 5.05)\n", + "ax = fig.add_subplot(1, 3, 3)\n", + "ax.set_ylabel('I obs (pA)')\n", + "ax.plot(dA.time(), dC['amp.I_obs'] - dD['amp.I_obs'], 'k')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "2065123f", + "metadata": {}, + "source": [ + "A very small error is observed, which fluctuates rapidly.\n", + "This suggests the models are the same and the error is due to small differences in the solver's chosen step sizes.\n", + "\n", + "(Adaptive step size algorithms may be a reason to prefer formulation D over C, as they place the output $I_text{obs}$ under the solver's control, instead of calculating it as a function of two error-controlled variables.)" + ] + }, + { + "cell_type": "markdown", + "id": "86d3be68", + "metadata": {}, + "source": [ + "### Cross-comparison\n", + "\n", + "We can get a closer look at the differences by plotting them explicitly.\n", + "For $V_p$ and $I_\\text{out}$ we'll zoom in on the first few $\\mu$s." + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "584780c1", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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+ "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "xlim = -0.005, 0.05\n", + "\n", + "fig = plt.figure(figsize=(15, 12))\n", + "fig.subplots_adjust(wspace=0.3)\n", + "\n", + "ax11 = fig.add_subplot(3, 3, 1)\n", + "ax11.plot(dA.time(), dA['amp.Vm'] - dB['amp.Vm'], label='Model A - Model B')\n", + "ax21 = fig.add_subplot(3, 3, 4); ax.set_ylabel('Vm (mV)')\n", + "ax21.plot(dA.time(), dA['amp.Vm'] - dC['amp.Vm'], label='Model A - Model C')\n", + "ax31 = fig.add_subplot(3, 3, 7); ax.set_ylabel('Vm (mV)')\n", + "ax31.plot(dB.time(), dB['amp.Vm'] - dC['amp.Vm'], label='Model B - Model C')\n", + "ax12 = fig.add_subplot(3, 3, 2); ax.set_ylabel('Vp (mV)')\n", + "ax12.plot(dA.time(), dA['amp.Vp'] - dB['amp.Vp'], label='Model A - Model B')\n", + "ax22 = fig.add_subplot(3, 3, 5); ax.set_ylabel('Vp (mV)')\n", + "ax22.plot(dA.time(), dA['amp.Vp'] - dC['amp.Vp'], label='Model A - Model C')\n", + "ax32 = fig.add_subplot(3, 3, 8); ax.set_ylabel('Vp (mV)')\n", + "ax32.plot(dB.time(), dB['amp.Vp'] - dC['amp.Vp'], label='Model B - Model C')\n", + "ax13 = fig.add_subplot(3, 3, 3); ax.set_ylabel('I obs (mV)')\n", + "ax13.plot(dA.time(), dA['amp.I_obs'] - dB['amp.I_obs'], label='Model A - Model B')\n", + "ax23 = fig.add_subplot(3, 3, 6); ax.set_ylabel('I obs (mV)')\n", + "ax23.plot(dA.time(), dA['amp.I_obs'] - dC['amp.I_obs'], label='Model A - Model C')\n", + "ax33 = fig.add_subplot(3, 3, 9); ax.set_ylabel('I obs (mV)')\n", + "ax33.plot(dB.time(), dB['amp.I_obs'] - dC['amp.I_obs'], label='Model B - Model C')\n", + "\n", + "for ax in (ax11, ax21, ax31):\n", + " ax.set_ylabel('Vm (mV)')\n", + "for ax in (ax11, ax12, ax13, ax21, ax22, ax23, ax31, ax32, ax33):\n", + " ax.legend()\n", + " \n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "0f81a21d", + "metadata": {}, + "source": [ + "Here, we see that\n", + "\n", + "- There are minor differences between Model A and Models B and C, which are only visible when plotting the difference explicitly.\n", + "- In line with their shared equations, models B and C differ only in their prediction of $I_\\text{obs}$ near discontinuities." + ] + }, + { + "cell_type": "markdown", + "id": "f83e9081", + "metadata": {}, + "source": [ + "## Models A and C with a high parasitic capcitance" + ] + }, + { + "cell_type": "markdown", + "id": "6f369cc7", + "metadata": {}, + "source": [ + "For Model A, we can calculate the damping factor as\n", + "\n", + "\\begin{align}\n", + "\\zeta = \\frac{\\tau_a + R_fC_f}{\\sqrt{\\tau_a R_f (C_p+C_f)}}\n", + "\\end{align}" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "f5705ee7", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Zeta: 10.453782146431431\n" + ] + } + ], + "source": [ + "Rf = 0.5 # GOhm\n", + "Cf = 0.15 # pF\n", + "Cp = 5 # pF (pF * GOhm = ms)\n", + "tau_amp = 20e-6 # ms\n", + "\n", + "zeta = (tau_amp + Rf * Cf) / np.sqrt(tau_amp * Rf * (Cf + Cp))\n", + "# (ms + ms) / sqrt(ms * ms) = dimensionless\n", + "\n", + "print(f'Zeta: {zeta}')" + ] + }, + { + "cell_type": "markdown", + "id": "6123c441", + "metadata": {}, + "source": [ + "This is well above 1, so that the system is stable.\n", + "\n", + "To see differences between the models, we can find an unstable situation.\n", + "For example, in a low-gain mode with $R_f = 5\\text{M}\\Omega$ and $C_p = 10$ pF:" + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "3544c88d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Zeta: 0.7642891671576164\n" + ] + } + ], + "source": [ + "Rf = 0.005\n", + "Cp = 10\n", + "zeta = (tau_amp + Rf * Cf) / np.sqrt(tau_amp * Rf * (Cf + Cp))\n", + "print(f'Zeta: {zeta}')" + ] + }, + { + "cell_type": "code", + "execution_count": 19, + "id": "62cd5098", + "metadata": {}, + "outputs": [], + "source": [ + "new_Rf = 0.005\n", + "new_Cp = 10\n", + "sA.set_constant('amp.Cp', new_Cp)\n", + "sA.set_constant('amp.Rf', new_Rf)\n", + "sC.set_constant('amp.Cp', new_Cp)\n", + "sC.set_constant('amp.Rf', new_Rf)\n", + "sA.reset()\n", + "sC.reset()\n", + "dA = sA.run(7, log_interval=dt)\n", + "dC = sC.run(7, log_interval=dt)" + ] + }, + { + "cell_type": "code", + "execution_count": 20, + "id": "9cd6ad9f", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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d2pkjhBBCimwN4uai5ui8KIc9d135+voyduxY1qxZg6IojB07Fl9fX7uY06dPU1ZWZrck08XFhXvuuYdjx44BcOzYMYYOHWr3xhsWFmb3OCkpKZw6dYp169bZblMUBbPZzJkzZ+jd++abtefm5rJp0yZ2795tu+3JJ5/k448/liKbcLjLOVmc+vwVBlz+D11UJlDBcc2dlA2cTO8R0dyj0dbiUYRwrMZY1lQVWUokWjsFWS8q6qdDhw706dPH7rbevXuzceNGAAICLLuzZmdn06FDB1tMTk6OrYMsICAAo9GIXq+362bLyclh2LBhtpiLFy9Wev5Lly7ZPc6+ffvsjuv1esrKyuxirF1t1z8PVXTbWWm1WrvlpUKI5iPbGbR8UmRrAJVKVeclm472zDPPMH36dADef//9SserO3N1/Rmv2gyhMJvNTJkyhZkzZ1Y6VttBC+vXr6e0tNRurwlroe7o0aOV/oARojmYTWb2bl5Gn8NvMVRVACo46joAl1H/yx2DRjo6PSHqpDGWNVVFlhIJIW5X4eHhpKWl2d124sQJOnfuDEDXrl0JCAhg27Zt9O/fHwCj0UhiYqJtVcjAgQNxcXFh27ZtTJgwAYCsrCxSU1N56623oOIEd15eHvv37+eee+4BYN++feTl5dkKcWFhYcyfP5+srCxbQS8hIQGtVmvbdzMsLIxXXnkFo9GIRqOxxQQGBlZaRiqEEOLmZA3TbWbMmDEYjUaMRiNRUZW78Hr06IFGo7HrHisrK+Onn36ydZ/16dOHpKQku/vdeH3AgAEcOXKEHj16VLpY38BvZuXKlcyePZuDBw/aLr/88gsjRozg448/rucrIET9XchIJ/WtkYSn/hVvVQFn1Z05Nnotff7yPT2lwCZaIbPZzIABA4iPj6d///5MmTKFyZMns3z5cru4ui5rmjNnDnl5ebZLRkZGk/0MQgjRkrzwwgskJSURHx/PqVOnWL9+PStWrGDatGlQ8ft01qxZxMfHs3nzZlJTU4mNjcXd3Z3o6GgAdDodkyZNYvbs2ezYsYMDBw7w5JNP0rdvX9u00d69ezNmzBgmT55MUlISSUlJTJ48mXHjxhESEgJAZGQkffr0ISYmhgMHDrBjxw5efPFFJk+ebNv/Kzo6Gq1WS2xsLKmpqWzevJn4+HiHTRa9cOECTz75JO3atcPd3Z27776blJQU23FFUZg7dy6BgYG4ubkxfPhwjhw5YvcYBoOBGTNm4Ovri4eHB+PHj+f8+fN2MXq9npiYGHQ6HTqdjpiYGHJzc+1izp07x0MPPYSHhwe+vr7MnDkTo9FoF3P48GEiIiJwc3OjY8eOzJs3r1YNCY3tx1OXefnfh0jLLmj25xZC2JMi221GrVZz7Ngxjh07hlpdecmph4cHf/rTn/jzn//M1q1bOXr0KJMnT6a4uJhJkyYB8Nxzz3H69Gni4uJIS0tj/fr1rF692u5xXn75Zfbu3cu0adM4ePAgJ0+e5Msvv2TGjBm1yvPgwYP8/PPPPPvss4SGhtpd/vCHP/DJJ59QVlbWSK+KEDd34L//xnXl/fQz/EyJouGnns8T9Jef6B3+kKNTE6LeqlvWdO7cObhhWdP1rl/WVBWtVmvbxFk2cxatkSzHEfU1ePBgNm/ezGeffUZoaCj/93//x5IlS2yDx6gYMjZr1iymTp3KoEGDuHDhAgkJCXbDZBYvXswjjzzChAkTCA8Px93dnS1bttj9/b5u3Tr69u1LZGQkkZGR9OvXj08//dR2XK1W8/XXX+Pq6kp4eDgTJkzgkUceYeHChbYYnU7Htm3bOH/+PIMGDWLq1KnExcXZ7bnWXKzDeFxcXPj22285evQo77zzTpXDeJYtW0ZycjIBAQGMHj2agoJrxaVZs2axefNmNmzYwO7duyksLGTcuHGYTCZbTHR0NAcPHmTr1q1s3bqVgwcPEhMTYztuMpkYO3YsRUVF7N69mw0bNrBx40a7YW/5+fmMHj2awMBAkpOTWbp0KQsXLmTRokXN8npZ5RSUMmlNMp//lMEzq5MpN5mb9fmFEDdQhJ28vDwFUPLy8iodKykpUY4ePaqUlJQ4JLf6mjhxovLwww9Xe/zhhx9WJk6caLteUlKizJgxQ/H19VW0Wq0SHh6u7N+/3+4+W7ZsUXr06KFotVrlvvvuUz7++GMFUPR6vS1m//79yujRo5U2bdooHh4eSr9+/ZT58+fbjnfu3FlZvHhxlTlNnz5d6dOnT5XHcnJyFLVarWzcuLHSsdb630i0XGaTSfl+1WuK6f/pFOU1L+XM/92lXDhxwNFpNUhNv+dEy9UU/93+8Ic/KPfee6/dbbNmzVLCwsIURVEUs9msBAQEKG+++abtuMFgUHQ6nfL3v//dobkLUZP6/j/X+eWvlM4vf6W8+e2xJstNVE9+V7ROjfXf7eWXX670nnQ963vS3/72N9ttpaWldu9Jubm5iouLi7JhwwZbzIULFxQnJydl69atiqIoytGjRxVASUpKssXs3btXAZTjx48riqIo33zzjeLk5KRcuHDBFvPZZ58pWq3W9nN+8MEHik6nU0pLS20xCxYsUAIDAxWz2Vzlz1BaWqrk5eXZLhkZGQ1+7dYmpdt+d3V++StlZ1pOvR9LNL2Gvj89tXJfk+UmqleX/26ta0MxUS83dpnd6IsvvrC77urqynvvvcd7771X7X3GjRvHuHHj7G57+umn7a4PHjyYhISEah8jPT292mNLly6t9lj79u0pLy+v9rgQjaW8rIx9HzzLcP0XoIKUdg/R99kP0bh5ODo1IRrFCy+8wLBhw4iPj2fChAns37+fFStWsGLFCrhhWVPPnj3p2bMn8fHxdsuaWoN//ZTByt1n6Orrwevj78TPq3YTrsXtywGr5IS47TXGMJ6UlBTKysrsYgIDAwkNDWXPnj1ERUWxd+9edDqd3b7PQ4cORafTsWfPHkJCQti7dy+hoaEEBgbaYqKiojAYDKSkpDBixAj27t1LRESE3RCIqKgo5syZQ3p6Ol27dq30MzbFnqWJaZfsriccySaiV/tGfQ4hRO3JclEhhKiCwWjkpyWPE67/ArOi4mDvFxk4/VMpsIlbSmMta2rJvjhwgT//+xDHswv4NjWbx1ckUWyUEzVCCNHSWIfx9OzZk++++47nnnuOmTNn8sknn8B1WxdUNYzHeiw7OxuNRmM3lbWqGD8/v0rP7+fnZxdz4/N4e3uj0WhqjLFev3GbBaum2LP0QIZlL7ln77UU9Q6cy73JPURrJrsZtHzSySaEEDcoKyvjwHu/Z2jRDsoUNUeHLebuqImOTkuIJlFVZ/L1VCoVc+fOZe7cuc2aV2MoMZr4v6+OAvDI3YEk/XqVM5eLeHf7Seb8prej0xMtmOzJJkTzM5vNDBo0iPj4eAD69+/PkSNHWL58OU899ZQtrq7DeKqKqSq+MWKsQw+qy0er1dp1vjVUbrGRSwUGAH5/TzD/2H2G49n5FBnK8dDKR30hHEE62YQQ4jpmk5l9709iaKGlwHYqYil3SYFNiFbpq0OZXCky0snbjbcfu4v5vw0F4JO9Z7lSaHB0ekIIIa7TGMN4AgICMBqN6PX6GmMuXrxY6fkvXbpkF3Pj8+j1esrKymqMycnJgSq67ZrKyZxCADq2daOHXxt822gxK3D6UmGzPL8QojIpsgkhxHV2ffIa9+b+B7Oi4lj4Eno/8EQt7iWEaIn+lXIegD/cE4yL2okH7vCjb0cdJWUmNv583tHpCSGEuE54eDhpaWl2t504cYLOnTsD0LVrVwICAti2bZvtuNFoJDExkWHDhgEwcOBAXFxc7GKysrJITU21xYSFhZGXl8f+/fttMfv27SMvL88uJjU1laysLFtMQkICWq2WgQMH2mJ27dqF0Wi0iwkMDKRLly6N/vpU5VRFka2HXxsAurW3bGsiRTYhHEeKbEIIUWH/t58y/Kxl4Mfh0JfoF/nUTe8jhGiZ8orLSDlr6WQYf5dl42qVSsUf7gkGYGPKBduyHiFuJP9nCNH8XnjhBZKSkoiPj+fUqVOsX7+eFStWMG3aNLhhGM/mzZtJTU0lNjbWbhiPTqdj0qRJzJ49mx07dnDgwAGefPJJ+vbty6hRo6CiO27MmDFMnjyZpKQkkpKSmDx5MuPGjSMkJASAyMhI+vTpQ0xMDAcOHGDHjh28+OKLTJ48GS8vLwCio6PRarXExsaSmprK5s2biY+PJy4u7qbLVxvLBX0JAME+7gB0b28ptv16qahZnl8IUZkU2YQQAjiVlsodSS8BkOL3P9z1uzmOTkkI0QC7Tl7CZFbo6deGoIoPHwBj+3ZA4+xE2sUCjmTmOzRHIYQQ1zTWMJ7FixfzyCOPMGHCBMLDw3F3d2fLli2o1WpbzLp16+jbty+RkZFERkbSr18/Pv30U9txtVrN119/jaurK+Hh4UyYMIFHHnmEhQsX2mJ0Oh3btm3j/PnzDBo0iKlTpxIXF0dcXFyzvF4AmbmWIltgWzcAuld0skmRTQjHkd0QhRC3vdLSEsr/GYuXqphTmt7cPfnv0ExnIIUQTSPp1ysA3N+rvd3tOncXRt7hx7ep2Xx3JJvQjjoHZSiEEOJGjTGMx9XVlaVLl7J06dJqY3x8fFi7dm2NuQQHB/PVV1/VGNO3b1927dpVY0xTumArsrnCdZ1sslz01iVd+C2fdLIJIW57yav+zB2mk+TRBp+Ja1G7aBydkhCigaxLRQd38a50bFRvy4bUO47lNHteonWQzzBCiNbAWmTrWNHJZt2T7czlIinGCOEgUmQTjWLnzp2oVCpyc3NrfZ8uXbqwZMmSJs1LiJs5uO97wrLXAZBx75v4dOzh6JSEEA1UUFpG2sUCAAYEVy6yDQ9pj0oFR7Pyyc4rdUCGQgghRMMoisLFfMt7WIDO0skW2NYNlQoM5WauFBlv8ghCiKYgRbbbQGxsLCqViueee67SsalTp6JSqYiNjXVIbjeTn5/Pq6++yh133IGrqysBAQGMGjWKTZs2ydkZ0WClpaW0+e4FnFVmDrcdSeioJx2dkhCiEaReyEdRLGf2/bxcKx1v10bL3UFtAfg+TbrZRGWyY4AQoqXLLymnzGT5POTbRguAi9oJf0/L+551vzYhRPOSItttIigoiA0bNlBScu2XbWlpKZ999hnBwcEOza06ubm5DBs2jE8++YQ5c+bw888/s2vXLh5//HFeeukl8vLyHJ2iaOWSP3uDHuYz5OJJl6fed3Q6QohGkpZtGWjQu4NntTH397Ts1bbn9JVmy0u0HnIeTwjR0l0pMgDgqXXG1eXaUAfr/mxSZBPCMaTIdpsYMGAAwcHBbNq0yXbbpk2bCAoKon///naxBoOBmTNn4ufnh6urK/feey/Jycl2Md988w29evXCzc2NESNGkJ6eXuk59+zZw/3334+bmxtBQUHMnDmToqLaT7p55ZVXSE9PZ9++fUycOJE+ffrQq1cvJk+ezMGDB2nTpk29XgshADIy0umf/g8A0ge+gqdPB0enJIRoJNaloncEeFUbE9a9HVQMSJDOaCGEEK2NdTmoTxv7vYStk0Yv5Mp2CEI4ghTZGkJRwFjkmEs9PhA8/fTTrFq1ynb9448/5plnnqkU99JLL7Fx40bWrFnDzz//TI8ePYiKiuLq1asAZGRk8Oijj/Kb3/yGgwcP8uyzz/KXv/zF7jEOHz5MVFQUjz76KIcOHeLzzz9n9+7dTJ8+vVa5ms1mNmzYwBNPPEFgYGCl423atMHZWYbjivo7++9XaKMq4VeXXtw1doqj0xFCNKLj2ZYiW0hA9Z1sdwe1RePsxKUCA79erv0JICGEEKIluFJo6WRr52FfZLMOQZBONiEcQ6oUDVFWDPGVC0DN4pVM0HjU6S4xMTHMmTOH9PR0VCoVP/74Ixs2bGDnzp22mKKiIpYvX87q1at58MEHAfjoo4/Ytm0bK1eu5M9//jPLly+nW7duLF68GJVKRUhICIcPH+bNN9+0Pc7bb79NdHQ0s2bNAqBnz5689957REREsHz5clxdK++Rc73Lly+j1+u544476vjCCHFzab/sZVjuN6ACp9/8DZWTuhb3EkK0Bmazwolsaydb9UU2Vxc1A4LbkvTrVZJ+vUL39tIdLa5RkO5GIUTLZu1ka1exH5tVoBTZhHAoKbLdRnx9fRk7dixr1qxBURTGjh2Lr6+vXczp06cpKysjPDzcdpuLiwv33HMPx44dA+DYsWMMHToU1XW7AoeFhdk9TkpKCqdOnWLdunW22xRFwWw2c+bMGXr37l1jrtalOyrZeVg0MkVRyP92Hk4qhYNew7m7/0hHpySEaEQXcksoMprQqJ3o4lvzyaiwbr4k/XqVvaev8MSQzs2WoxBCCNFQVworimwe1S0XlSKbEI4gRbaGcHG3dJQ56rnr4ZlnnrEt2Xz//cobvVdX3FIUxXZbbfauMZvNTJkyhZkzZ1Y6VptBC+3bt8fb29tW2BOisfzy024Gl+7BrKgIePh1R6cjhGhkp3IKAejW3gMXdc27Ygzt5gPAvjNX7d7nhBBCiJbOtlz0hj3ZAiqmal/Mlz3ZhHAE2ZOtIVQqy5JNR1zq+UFgzJgxGI1GjEYjUVFRlY736NEDjUbD7t27bbeVlZXx008/2brP+vTpQ1JSkt39brw+YMAAjhw5Qo8ePSpdNBr7N4KqODk58fjjj7Nu3ToyMysXMouKiigvL6/Tzy4EQNl//wZAqvdIArrf7eh0hBCNLP2KZX+1rjfpYgO4K6gtzk4qLhUYOK+XM/5CCCFaD9tyUQ/75aLtPS3XLxcaMZll6bsQzU2KbLcZtVrNsWPHOHbsGGp15X2oPDw8+NOf/sSf//xntm7dytGjR5k8eTLFxcVMmjQJgOeee47Tp08TFxdHWloa69evZ/Xq1XaP8/LLL7N3716mTZvGwYMHOXnyJF9++SUzZsyoda7x8fEEBQUxZMgQPvnkE44ePcrJkyf5+OOPufvuuyksLGyEV0TcTk4c2s/gkt2YFRXtx/6vo9MRQjSBs1eKAQhud/OOb1cXNX0CLRNID2TkNnluohWRz6VCiBbOtlz0hk423zYaVCowmRWuVhTihBDNR4pstyEvLy+8vLyqPf63v/2N//mf/yEmJoYBAwZw6tQpvvvuO7y9vaFiuefGjRvZsmULd911F3//+9+Jj4+3e4x+/fqRmJjIyZMnue++++jfvz9//etf6dChQ63z9Pb2JikpiSeffJI33niD/v37c9999/HZZ5/x9ttvo9PpGvAqiNvRpW2LADjkdT8devZ3dDriFrVgwQJUKpVt8AsVy+znzp1LYGAgbm5uDB8+nCNHjjg0z1vV2YpOts4+tRsONCDY8t7281l9k+YlhBBCNCZrAc3nhj3ZnNVOtn3aLhUYHJKbELcz2ZPtNnBjl9mNvvjiC7vrrq6uvPfee7z33nvV3mfcuHGMGzfO7rann37a7vrgwYNJSEio9jHS09NvkjnodDoWLFjAggULbhorRE3Onz/HoPztoALvkS84Oh1xi0pOTmbFihX069fP7va33nqLRYsWsXr1anr16sUbb7zB6NGjSUtLw9Oz+gmYou7OXrV0snWuRScbQP/gtqzeAwfOSZFNXEe25xNCtHD5pWUAtHWrvBVPe09XLhcaySkopQ/VN1cIIRqfdLIJIW4Lp79dilZVxq8uveh813BHpyNuQYWFhTzxxBN89NFHts5fKrrYlixZwquvvsqjjz5KaGgoa9asobi4mPXr1zs051uNyaxw/qplb7XaFtmsnWxHMvMpLTM1aX6iFZHlokKIFi6/xFJk83Kr3Ddj3ZctRzrZhGh2UmQTQtzySktL6HPhXwAUDfhjvQeHCFGTadOmMXbsWEaNGmV3+5kzZ8jOziYyMtJ2m1arJSIigj179lT7eAaDgfz8fLuLqFlWXglGkxkXtYoOOrda3aeTtxu+bbSUmxVSL+Q1eY5CCCFEQ5WbzBQZLSeGvFxdKh33qyiyyXJRIZqfFNmEELe8g9s/oz16LuNNn1FPOTodcQvasGEDP//8c5VL27OzswHw9/e3u93f3992rCoLFixAp9PZLkFBQU2QeeXnbM37yZ2rGHoQ5O2O2ql2xXSVSsWA4LYA/CxLRoUQQrQCBaXltu89XSt3skmRTQjHkSKbEOKW53zIsiTvbNAjqF20N40Xoi4yMjJ4/vnnWbt2La6urtXGqW7ooFQUpdJt15szZw55eXm2S0ZGRqPmfaOb7Se3bNkykpOTCQgIYPTo0RQUFDRpPvVxXm9ZKtrJp3ZLRa0GdLYOP5AJo8JCVosKIVoy635sHho1zurKH+n9bMtFS5s9N9G0FHmDavGkyCaEuKWdOXOS/oafAOg66o+OTkfcglJSUsjJyWHgwIE4Ozvj7OxMYmIi7733Hs7OzrYOthu71nJycip1t11Pq9XapkHfbCp0QzX2fnKOWuqamWcpsnVsW32xsyr9g651siny16sQQogWLr/E0snm5VZ5qSiAn5flfTAnXzrZhGhuUmSrB/kDvOWS/zbiRue+X4VapXBSeyc+nfs4Oh1xCxo5ciSHDx/m4MGDtsugQYN44oknOHjwIN26dSMgIIBt27bZ7mM0GklMTGTYsGEOzd2qsfeTc8RSV4CsXMsZ+wCv2u3HZtWvU1vUTipyCgxk5slZfyFE/c2dOxeVSmV3CQgIsB2vzRJ8g8HAjBkz8PX1xcPDg/Hjx3P+/Hm7GL1eT0xMjO33bExMDLm59t24586d46GHHsLDwwNfX19mzpyJ0Wi0izl8+DARERG4ubnRsWNH5s2bJ39PtwLWTraq9mNDBh8I4VCVF3CLarm4uKBSqbh06RLt27evcZmPaH6KonDp0iVUKhUuLlW/4Yjbi9lkpkvGFwAU3/kHR6cjblGenp6Ehoba3ebh4UG7du1st8+aNYv4+Hh69uxJz549iY+Px93dnejoaAdlfY11P7nk5ORKx2raT+7s2bPVPuacOXOIi4uzXc/Pz2+WQpu1k61DHTvZ3DRqenfwJPVCPgfP5dKxbd2KdOLWI0UG0RB33nkn27dvt11Xq9W2761L8FevXk2vXr144403GD16NGlpaXh6ekLFe8aWLVvYsGED7dq1Y/bs2YwbN46UlBTbY0VHR3P+/Hm2bt0KwB//+EdiYmLYsmULACaTibFjx9K+fXt2797NlStXmDhxIoqisHTpUqj43Tx69GhGjBhBcnIyJ06cIDY2Fg8PD2bPnt2sr5mom5omiyLLRYVwKCmy1YFaraZTp06cP3+e9PR0R6cjqqBSqejUqZPdHzPi9nUkJZG+ygWKFS0hD8Q4Oh1xG3vppZcoKSlh6tSp6PV6hgwZQkJCgu0DlaNY95NLSEho1P3ktFotWm3z73+YVdGFFljLyaLX6x/kTeqFfA6c0zO2X4cmyE4Icbtwdna2616zunEJPsCaNWvw9/dn/fr1TJkyhby8PFauXMmnn35q6y5eu3YtQUFBbN++naioKI4dO8bWrVtJSkpiyJAhAHz00UeEhYWRlpZGSEgICQkJHD16lIyMDAIDAwF45513iI2NZf78+Xh5ebFu3TpKS0tZvXo1Wq2W0NBQTpw4waJFi4iLi5OGghbsZp1s7dpY3oNLy8wUG8tx18jHfiGai/xrq6M2bdrQs2dPysrKHJ2KqIKLi4sU2ITNlf3/BOCkbhh3tWnr6HTEbWTnzp1211UqFXPnzmXu3LkOy6kq1+8nZ2Uymdi1axfLli0jLS0NKjraOnS4Vni62X5yjqAoClm59etkA+gf3JZPk85yIEOGHwghGubkyZMEBgai1WoZMmQI8fHxdOvW7aZL8KdMmUJKSgplZWV2MYGBgYSGhrJnzx6ioqLYu3cvOp3OVmADGDp0KDqdjj179hASEsLevXsJDQ21FdgAoqKiMBgMpKSkMGLECPbu3UtERITdSZGoqCjmzJlDeno6Xbt2rfLnMxgMGAzXliE2176b4pqb7cnmoVGjdXbCUG7mSqERdx/52C9Ec5F/bfWgVqulkCNEC1dWbqLnZcseWK53/4+j0xGiRbLuJ3e9p59+mjvuuIOXX37Zbj+5/v37w3X7yb355psOyrpq+aXlFBlNUM9Otrsrhh+kXsjDWG5G4yzb1goh6m7IkCF88skn9OrVi4sXL/LGG28wbNgwjhw5Uqsl+NnZ2Wg0GrshNNYY6/2zs7Px8/Or9Nx+fn52MTc+j7e3NxqNxi6mS5culZ7Heqy6ItuCBQt4/fXX6/jKiMZ0rZOt6o/zKpWKdh4aMvNKuVJkJKiOU7eFEPUnRTYhxC3pyE+J3M0lStDSI/xRR6cjRIvU2veTu15WxX5sbd1dcNPU/URYV18PdG4u5JWUcTw7n36dpPtVCFF3Dz74oO37vn37EhYWRvfu3VmzZg1Dhw6FeizBryqmqvjGiLHuR1hTPo7ad1Ncc21Ptur3ofZpYymyXS2S4QdCNCc5TSuEuCUV/PwvAE7owlFrPRydjhCt1ksvvcSsWbOYOnUqgwYN4sKFCy1iP7kbWSeLdqhHFxsVHyj7B1sKawfOyZJRIUTj8PDwoG/fvpw8edK2T5u1k8zq+iX4AQEBGI1G9Hp9jTEXL16s9FyXLl2yi7nxefR6PWVlZTXG5OTkQBXddtfTarV4eXnZXUTzyi+tWC5azZ5sAO08LMuArxQaq40RQjQ+KbIJIW45ZpOZbjmWqV7q0EccnY4QrcrOnTtZsmSJ7bp1P7msrCxKS0tJTEys1P3WEliHHnTQ1X0/Nqv+QZblWQdlXzYhRCMxGAwcO3aMDh060LVrV9sSfCvrEvxhw4YBMHDgQFxcXOxisrKySE1NtcWEhYWRl5fH/v37bTH79u0jLy/PLiY1NZWsrCxbTEJCAlqt1rYPZ1hYGLt27cJoNNrFBAYGVlpGKlqWgooiW5tqlosCtPPQAHC1SIpsQjQnKbIJIW45x1P305EcShUXeob/1tHpCCGawaUCy3IYf6/6TzW929bJpr9prLi1VayYE6LOXnzxRRITEzlz5gz79u3jd7/7Hfn5+UycOBGVSmVbgr9582ZSU1OJjY21W4Kv0+mYNGkSs2fPZseOHRw4cIAnn3ySvn372qaN9u7dmzFjxjB58mSSkpJISkpi8uTJjBs3jpCQEAAiIyPp06cPMTExHDhwgB07dvDiiy8yefJkW+dZdHQ0Wq2W2NhYUlNT2bx5M/Hx8TJZtBUoMliKbB7a6otsPhVFtitSZBOiWcmebEKIW87Fn/5DH+B0mwHc6S5LGIS4HVwqtHSytW/TgCJbxT5s6VeKuVpktH1AEUKI2jp//jx/+MMfuHz5Mu3bt2fo0KEkJSXRuXNnqFiCX1JSwtSpU9Hr9QwZMqTSEvzFixfj7OzMhAkTKCkpYeTIkaxevdpu8Nq6deuYOXOmbQrp+PHjWbZsme24Wq3m66+/ZurUqYSHh+Pm5kZ0dDQLFy60xeh0OrZt28a0adMYNGgQ3t7exMXF2e23JlqmYmNFka2GPUh92lQU2WS5qBDNSopsQohbjm/mTgDMPUY7OhUhRDOxdrK196x/kU3n7kL39h6cvlTEwQw9D9xR/Z5EQghRlQ0bNtR43LoEf+7cudXGuLq6snTpUpYuXVptjI+PD2vXrq3xuYKDg/nqq69qjOnbty+7du2qMUa0PNZp2u6a6j/O+1bsySaDD24tCtJq3dLJclEhxC0lKzuL3uXHAeg8VJaKCnG7aIwiG0D/4Ip92WT4wW1NPsII4VgLFiywLa+1UhSFuXPnEhgYiJubG8OHD+fIkSN29zMYDMyYMQNfX188PDwYP34858+ft4vR6/XExMSg0+nQ6XTExMSQm2v/O//cuXM89NBDeHh44Ovry8yZM+32rgM4fPgwERERuLm50bFjR+bNm2ebztrUim3LRWvoZJPlokI4xC1ZZPvggw/o2rUrrq6uDBw4kB9++MHRKQkhmsmZfVtwVpk5pw7Gq0MPR6cjhGgmlwobp8h2d1DFvmwy/EAIIRwiOTmZFStW0K9fP7vb33rrLRYtWsSyZctITk4mICCA0aNHU1BQYIuZNWsWmzdvZsOGDezevZvCwkLGjRuHyWSyxURHR3Pw4EG2bt3K1q1bOXjwIDExMbbjJpOJsWPHUlRUxO7du9mwYQMbN25k9uzZtpj8/HxGjx5NYGAgycnJLF26lIULF7Jo0aImf324rpOtxj3ZZLmoEA5xyy0X/fzzz5k1axYffPAB4eHhfPjhhzz44IMcPXqU4ODgWj9OeXk55eXllW5XqVR2+yFUFdPUsQDOzs71ijWZTDWeYWkJsWq12rbZalPFms1mzGZzi451cnLCycmpxcQqimL3B0pLjFWpVKhPJQCQE3A/gbX8N1erx3Xwv/vG/B1xs/sK0dooinKtk61N/aeLAvSvGH5w8FwuZrOCk5Ns/i2EEM2lsLCQJ554go8++og33njDdruiKCxZsoRXX32VRx99FIA1a9bg7+/P+vXrmTJlCnl5eaxcuZJPP/3UNiRi7dq1BAUFsX37dqKiojh27Bhbt24lKSmJIUOGAPDRRx8RFhZGWloaISEhJCQkcPToUTIyMggMDATgnXfeITY2lvnz5+Pl5cW6desoLS1l9erVaLVaQkNDOXHiBIsWLWqWwRHX9mSrzXJRKbIJ0ZxuuSLbokWLmDRpEs8++ywAS5Ys4bvvvmP58uUsWLCgUrzBYMBguLZOPT8/H4AtW7bg7u5eKT4gIID77rvPdv3LL7+s9sN5+/btGT58uO36119/XanN2Mrb29v2ZgDw3XffUVxcXGWsl5cXUVFRtus7duyw5X0jd3d3xo4da7v+/fffo9dXPTVNo9Hw8MMP267/8MMPXLp0qcpYtVpte4MD2LNnD9nZ2VXGAjz22GO27/fv31+pbft6v/3tb20FgpSUFM6ePVtt7Pjx49FqLW8gv/zyC6dPn6429je/+Q0eHh5Q0d594sSJamMjIyPR6XQAHDt2jKNHj1YbO3LkSHx8fAA4efIkhw4dqjY2IiICPz8/AH799VcOHDhQbey9995Lhw4doKJlPTk5udrYoUOHEhQUBMCFCxdISkqqNnbw4MG2sewXL15k9+7d1cb279+fHj0s3WCXLl0iMTGx2th+/frZJlrp9Xp27NhRbWyfPn248847oeLfXEJCQrWxvXr14q677gKguLiYb775ptrYLl260r3AMs7eo3cUmzdvrja2c+fO3HPPPVBRoK0ptlOnToSFhdmu1xTbGn5HVHc/IVqrQkM5pWWWEwa+ng0bVhDi74mbi5oCQzmnLxXS09+zFvcStxqZLiqEY0ybNo2xY8cyatQouyLbmTNnyM7Otg16ANBqtURERLBnzx6mTJlCSkoKZWVldjGBgYGEhoayZ88eoqKi2Lt3LzqdzlZgo+LvaJ1Ox549ewgJCWHv3r2EhobaCmwAUVFRGAwGUlJSGDFiBHv37iUiIsL2OcQaM2fOHNLT0+natWuVP191nz3rwlBuosxk+SXlXtNy0YpOtpIyE8XG8hr3bxNCNJ5barmo0WgkJSXF7hcrFQWTPXv2VHmfBQsW2Nbj63Q6W6FCCNH6XLxwGl/yKMWFzndFODodIUQzsXaxtdE6N/hDhLPaiX6dLCdZZMno7auJm1CEEFXYsGEDP//8c5WNEdaT+f7+9gNp/P39bceys7PRaDR4e3vXGGM94X09Pz8/u5gbn8fb2xuNRlNjjPV6TY0HjfHZs9hw7eStu0v1RTYPjRqNs+XjviwZFaL53FLl7MuXL2MymWr85XujOXPm2I2pzs/PJygoiIceeggvL69K8Te2/o4fP77afG6Mvb6j7Gax13eh3MzIkSNrHTtixIhab8h533331Tp22LBhtY695557GDx4cLXHr18SN3DgQAYMGFCr2LvuuqvS3g3Vxfbt29fWSXWz2N69e9s6tG4W27NnT7p3716r2G7dutk6yqpiXSJJxXSoTp061Sq2Y8eO/Pa31W/4f32sv79/rWPbt29f61hvb+9ax3p5edU61t3dvcbYXessf5SdcevHHW1qftzr/82p1epax1LRbVnb2Jb4O6I+Z02FaMmsRTbfNg3rYrO6O7gt+85c5cC5XCYMkpNvtyPpZBOieWVkZPD888+TkJCAq2v1y/5v/HtIUZSbLs28Maaq+MaIsX4Wqimf6j571kVRxVJRrbMTzurqe2ZUKhXtPDRk5ZVytchIkE/lVVqi9ZH3p5bvliqyWdXll69Wq7Vr87Vydna229OoOrWJaUmx1xd5bufY6/f5ktjaxapUqlr/v+ao2DaZlo5VQ9C9TZYDLeTfckNi63JfIVqDxhp6YNU/yNIFceBc1dsrCCGEaFwpKSnk5OQwcOBA220mk4ldu3axbNky0tLSoKJLzLqdCkBOTo6twSIgIACj0Yher7frZsvJyWHYsGG2mIsXL1Z6/kuXLtk9zr59++yO6/V6ysrK7GJubOLIycmBKrrtrlfdZ8+6KK7F0AOrdm2uFdmEEM3jllou6uvri1qtrvIXXk2/7IQQrV+pwUiv0l8A8O076qbxQohbh23oQWMV2SqGH5y4WECRQQaFCCFEUxs5ciSHDx/m4MGDtsugQYN44oknOHjwIN26dSMgIIBt27bZ7mM0GklMTLQV0AYOHIiLi4tdTFZWFqmpqbaYsLAw8vLy2L9/vy1m37595OXl2cWkpqaSlZVli0lISECr1dqKgGFhYezatctuL92EhAQCAwNrXKnSGKzvS+6amzcY+FQMP7giRTYhms0tVWTTaDQMHDjQ7hcrwLZt22y/NIUQt6aTh/bSVlVEIW507BNWi3sIIW4Vl62dbG0ap8jm7+VKx7ZumBX45bzsy3Y7UpD1OEI0J09PT0JDQ+0uHh4etGvXjtDQUFQqFbNmzSI+Pp7NmzeTmppKbGws7u7uREdHA6DT6Zg0aRKzZ89mx44dHDhwgCeffJK+ffvahkf17t2bMWPGMHnyZJKSkkhKSmLy5MmMGzfOtj1MZGQkffr0ISYmhgMHDrBjxw5efPFFJk+ebNtOKDo6Gq1WS2xsLKmpqWzevJn4+Phmmixq6WRrU5tONg/LNgpXCg03jRVCNI5bbs1QXFwcMTExDBo0iLCwMFasWMG5c+d47rnnHJ2aEKIJ5R21TDM943E3fdUujk5HCNGMGruTDWBAZ28u5JaQfEbPsO6+jfa4Qggh6uell16ipKSEqVOnotfrGTJkCAkJCXh6XpsCvXjxYpydnZkwYQIlJSWMHDmS1atX220rs27dOmbOnGkbljd+/HiWLVtmO65Wq/n666+ZOnUq4eHhuLm5ER0dzcKFC20xOp2Obdu2MW3aNAYNGoS3tzdxcXF2+601lcI6dLJZi2yyXFSI5nPLFdkef/xxrly5wrx588jKyiI0NJRvvvmGzp07Ozo1IUQTcs9KAsDQSbpWhbjdNEWRbWg3H7b8kknSr1d4np6N9riidZCNpYVwvJ07d9pdV6lUzJ07l7lz51Z7H1dXV5YuXcrSpUurjfHx8WHt2rU1PndwcDBfffVVjTF9+/Zl165dNcY0heKKwQe12ZPNp2IgkCwXFaL53HJFNoCpU6cydepUR6chhGgmZeUmupYcBRX43Tnc0ekIIZqZdfCBbyMtFwUY2q0dAD+f01NaZsLVpfbDdYQQQoimUmSwLBd116gh7zykrIEu4dCt8t/AslxUiOZ3S+3JJoS4PaUdPYi3qoBSXOjUe4ij0xFCNLMrhZYz9I1ZZOvm64FvGy2GcjO/ZMi+bEIIIVoGaydbW+dy+ORh2PUWfPpbOLWjUqx18MHV4rJmz1OI25UU2YQQrd7lY5ZW/XOud+Dk0ngfsoUQLZ+iKLa9Znwqztg3BpVKxdBuPgAk/Xq10R5XCCGEaAhrJ9vgkh/gyinLjYoZvnsFzGa7WB8Pyz7FelkuKkSzuSWXiwohbi/OF5IBKPIb4OhUhBDNrKTMhKHc8qHCuxGLbFQsGf3qUBb7zlwBB+3LVmYyk5ZdwHl9CfklZWicnWjr7kIPvzZ0bOvW5FPshBBCtCxFFYMP7sqv2LNuyJ/g4Dq4dBzO7oau99tibZ1sUmQTotlIkU0I0ep1KDgEgHs3GXogxO3G+sFBo3bCoxaT1urCui9bylk9hnITWufm2ZdNURR+PHWFz5LPsePYRUrLzFXGebk6c0/XdkSEtGd4r/YE+bg3S35CCCEcp8hoAhSCCn+x3HDX41BWDD+vgUP/tC+yuVtOPhUaypv1fUyI25ksFxVCtGo5ORfprmQA0KlfhKPTEaJVWbBgAYMHD8bT0xM/Pz8eeeQR0tLS7GIURWHu3LkEBgbi5ubG8OHDOXLkiMNyvpG+yLLPjI+HptG7urq398DP07IvW/IZfaM+dnWOZ+fz+IdJPLlyH18fyqK0zIzOzYX+wW0ZHtKe8B7tCPH3xEWtIr+0nO3HLvLXL1K5763vGbNkF+8kpHHofC6KjMdsEHn9hBAtVbGxnGBVDq7lBaDWgt+d0G+C5eDRL8F0bf81LzdnnJ0s743W90shRNOSTjYhRKt27lAifsAFpw509Ong6HSEaFUSExOZNm0agwcPpry8nFdffZXIyEiOHj2Kh4cHAG+99RaLFi1i9erV9OrVizfeeIPRo0eTlpaGp6eno38ErhZbOtkae6koFfuyRfRqz79SzrMzLYd7e/o2+nNYKYrCRz/8ysLvTmA0mdE4O/H7wUE8NjCIOwO9cHKyLyAay80cz87nh5OXSUy7RMo5PcezCzieXcDS/56ig86VUb39Gd3Hn6Hd2qFxlvOqQghxKygymOirOmO54n8nOGsgeBi4+UDJVTj/E3QOg4r3MW8PDZcKDFwpMhCgc3Vs8kLcBqTIJoRo1UrP7APgolc/Ojo6GSFama1bt9pdX7VqFX5+fqSkpHD//fejKApLlizh1Vdf5dFHHwVgzZo1+Pv7s379eqZMmeKgzK+5WmSA6zZ3bmzDQ/wsRbYTl/jfJnkGMJSb+Mu/DvDtL+dwpYxxvbz5y+hu+LmrwJQJF9Oh3Ajmcsvm1ooZjWKmn2KmX5CZaZ0UCkoVDmfo+SXjKkcv5GEsKOfyfoXP9ytscVHRp4MnfTvp6OnXBp1bRUGyym6tajq4bohVUDCUmSgylFNktHwtNpooNJRTaiyn3KxQZjLbLiZTxZJXlQoVgAqcUKFCQaVS4aQCJ6eKryqV5eJ03fcqFerrrqtUoHayHrN8kLQcd8JJBcWlpY38X0kIIVqGYmM5vVWZlit+fSxfnZyg+whI3Qind9iKbFQsGb1UYJBONiGaiRTZhBCtmvtly35sBMrQAyEaKi8vDwAfH8tUzTNnzpCdnU1kZKQtRqvVEhERwZ49e6otshkMBgwGg+16fn5+k+V8teJDg7d743eyAdzb0xe1k4pTOYVkXC2u3b5nZjMUZsPVM1CQBYU5UJRj+Vp8BQwFYMgHQyGKoQBVcT6LMbLY2mBwDlhZtzw9gWEVF5yAG1+O7IpLI1EBrhWXdo33sI0m39Cw5Z6yWFQI0VIVGU10dsqxXPHpcu1A95GWItup7fDAtdNC1snbV4oMlR5LCNH4pMgmhGi1TGaFoNIToALfkCGOTkeIVk1RFOLi4rj33nsJDQ0FIDvbUpXx9/e3i/X39+fs2bPVPtaCBQt4/fXXmzhjC33F4IN2TbBcFEDn5sLAYG/2p19lZ1oOMWFd7ANK9JB5oOJyEK6cshTXyktq9fiqKuphAKg1lr121C7gXPHVyRlUalA53XBRVXGb5aKoVBQazVwpKkdfZKSorNyugqRQeR+7qm6rNn+VEy5qFc5qy1cXtRPOTipUTk6Vus9uLFxZryuKCgUFRbHcpihKxddre6OZFfvbscYplq46s+02y/UCczmQWOuf40br9p1j3sOh9b6/EEI0lWJDOcGqi5Yr3l2vHej+gOVr5kEovgrulhNm1iKbXiaMCtEspMgmhGi1fj1zip6qXEyKio533OPodIRo1aZPn86hQ4fYvXt3pWM3DhRQFKXGIQNz5swhLi7Odj0/P5+goKBGztiiKfdks3qgtx/706+y9Ug2MUOC4fx+OLnN0i2QdbDqOzk5Q9tg8OoIHu2hjZ/l4u4Lrl6YXdqwaFcW204XUe7sztvR4QzoFlBRXHOxFM4agaqiy80T6FKxzCgtu4C07AKy8kq5mF/K5UIDhnIzhnLL0k6N2gk3jRo3FzXuGmd822jw8dDQro2Wdm00+Hpo8fZwoZ2HFrdGnujaWPLz8+H/dPW+v8ksvWxCiJappMxEsKqik+36IptXB/ANgctpcG4v3DEWriuyXZUimxDNQopsQohWKydtHz2BTJdggrQejk5H3KYWLFjApk2bOH78OG5ubgwbNow333yTkJAQW4yiKLz++uusWLECvV7PkCFDeP/997nzzjsdmrvVjBkz+PLLL9m1axedOnWy3R4QEAAVHW0dOlwbLJKTk1Opu+16Wq0WrVbbxFlbWM/M+zRhke03oR1Yu/UHhqT/C9OSyajzz9kHeHeFwP6Wi18faNcNdEGWYlk13vnuOO+fMqJRt+ejmEEM6NW+yfK/nrvGmf7B3vQP9m6W5xNCCNG4yoxGAlQVE6/bBtsf7BxmKbKd3WMrsnnblotKke1WIMOvWz4ZNSWEaLXKMg4AcNWrj6NTEbcx64TOpKQktm3bRnl5OZGRkRQVFdlirBM6ly1bRnJyMgEBAYwePZqCggKH5q4oCtOnT2fTpk3897//pWvXrnbHu3btSkBAANu2bbPdZjQaSUxMZNiwYQ7IuDLrh4am2pONnGME75xJovYFZjpvthTYtF4Q+jt45O8w+wQ8fxAeWwXhM6HnKPDpVmOBbcsvmbz//WkA3vxdXyKaqcAmhBCi9WtTfhUAxckZ3G/YFTO4YuDBub22m6zbKeiLpcgmRHOQTjYhRKvV5uphAJQOdzk6FXEba80TOqdNm8b69ev5z3/+g6enp20PNp1Oh5ubGyqVilmzZhEfH0/Pnj3p2bMn8fHxuLu7Ex0d7bC8r9dknWzFV+H7+fDTx6CYUQM/mEL5ud04np82C1zc6vWwRzLz+PO/fwHgj/d347f9O930PkIIIYSVV/kVcAGzux9qpxt6ZqxFtqxfwFgEGo9rgw8KpcgmRHOQIpsQolVSFIUgwwkA2nYf7Oh0hLBpTRM6ly9fDsDw4cPtbl+1ahWxsbEAvPTSS5SUlDB16lTbUteEhAQ8PT0bPZ/6sJ6Zb9QiW9q38J9plkmgAHeM42L/mcSsugzZ8HCemS6+dX/YK4UG/vhJCqVlZu7v1Z6Xx9zReDmLRtFJdYl5zqvwVhWS9kbzDO+4VeXq7mDIjE8cnYbDLViwgFdeeYXnn3+eJUuWQC23EDAYDLz44ot89tlnlJSUMHLkSD744AO7Jf16vZ6ZM2fy5ZdfAjB+/HiWLl1K27ZtbTHnzp1j2rRp/Pe//8XNzY3o6GgWLlyIRnPtd+bhw4eZPn06+/fvx8fHhylTpvDXv/61xr03hWOUmcy0UyxLRZU2VWzbYN0LNP8CnP8JukVcG3wgnWxCNAspsgkhWqXM82fpiB6zoiJQhh6IFqK1TehUarGxh0qlYu7cucydO7dJc6kPs1lBX1wGjVVkM5VDwquw7++W6+17w2/egq734w9E9NpP4olLrNt3llfH1m2ZurHczJ/W/cyF3BK6+nqw9Pf9UTvJB9iW5kn1Nh5QVwyzKHd0Nq3b0fzql0zfLpKTk1mxYgX9+vWzu926hcDq1avp1asXb7zxBqNHjyYtLc12AmPWrFls2bKFDRs20K5dO2bPns24ceNISUlBrbYMHImOjub8+fO2juo//vGPxMTEsGXLFgBMJhNjx46lffv27N69mytXrjBx4kQURWHp0qVQcQJn9OjRjBgxguTkZE6cOEFsbCweHh7Mnj27mV8xcTOlZSb8VLkAqDwDKgeoVJZuttR/W5aMXldkk8EHQjQPKbIJIVqlrOP76AicV3ci2N3L0ekIAa14QmdrVVBabpsC2da9gR/oDQXw72fgZILleth0GPn/wPnaAIenwjqTeOIS//zpPHGjQ+o0WXPeV0fYf+YqbbTOfPTUQHQNzVc0iXZYOkZ/MvfC+b4XHJ1Oq+bq1a4WUbeuwsJCnnjiCT766CPeeOMN2+212UIgLy+PlStX8umnnzJq1CgA1q5dS1BQENu3bycqKopjx46xdetWkpKSGDJkCAAfffQRYWFhpKWlERISQkJCAkePHiUjI4PAwEAA3nnnHWJjY5k/fz5eXl6sW7eO0tJSVq9ejVarJTQ0lBMnTrBo0SLi4uKkm62FKSkz4Vcx9MDJq4oiGxXDD1L/bRl+cN1JKH1xGWazgpOc4BGiSUmRTQjRKpVkWPY0uuIZQvBNo4Voeq15QmdrdaXIspy2jdYZrXPtC16VGArg09/C+WRwdoNHV0Cf8ZXChof40cnbjfP6Ev7983lihnau1cOv23eWtUnnUKlgyeN308OvZSy1FZWpVWYAtpoG87+jW8a+g6J1mjZtGmPHjmXUqFF2RbbabCGQkpJCWVmZXUxgYCChoaHs2bOHqKgo9u7di06nsxXYAIYOHYpOp2PPnj2EhISwd+9eQkNDbQU2gKioKAwGAykpKYwYMYK9e/cSERFh934TFRXFnDlzSE9PrzQQh2bazkBUzVBmxhvL0CSVRzX7FgRXDCY6nwymMttgIJNZIb+0jLZNNShICAEyXVQI0Vq5XDkOgLm97GkkHOtWmNDZWln3l/H2aEBXmLEY1j9u+TDi2hZiv6qywAagdlIx+b5uACzdcZISo+mmD5/06xVe+88RAF6MDGFUn+oLq8LxnLH8NzXJn8iiATZs2MDPP//MggULKh2raQsB67Hs7Gw0Gg3e3t41xvj5+VV6fD8/P7uYG5/H29sbjUZTY4z1ujXmRgsWLECn09ku0mXdfErKTLRVVUwvd/OuOqj9HZb3s7JiyD6ExtkJT62lt0aWjArR9OQvCCFEq9Su+BQAnp1lsqhwrGnTprF27VrWr19vm9CZnZ1NSUkJVCwTtU7o3Lx5M6mpqcTGxraoCZ2tVW7Ffmze9T0rryjwxXNw9kfQekHMJug0qMa7/P6eIDq2dSOnwMDynadqjD18Po9n1/xEuVlhbL8OTB3evX55imajriiylcliD1FPGRkZPP/886xduxZXV9dq4+q6hUBVMVXFN0aMdb/O6vKZM2cOeXl5tktGRkaNeYvGU1pmQsdNimxOThA81PL92b0A+LSRfdmEaC5SZBNCtDq5BUV0Np8HILDnQEenI25zy5cvJy8vj+HDh9OhQwfb5fPPP7fFvPTSS8yaNYupU6cyaNAgLly40KImdLZW1iKbzq2enWy7F8PR/4CTM/xhA3S8+e8TrbOaV37TG4D3d57mwDl9lXGpF/KYuGo/hYZyhnT14Z3H7pK9jVoBZyzLRaWTTdRXSkoKOTk5DBw4EGdnZ5ydnUlMTOS9997D2dm52i6x67cQCAgIwGg0otfra4y5ePFipee/dOmSXcyNz6PX6ykrK6sxJicnB6rotrPSarV4eXnZXUTzKDGaaKsqtFxxbVt9YHCY5es5S5HNejLqihTZhGhy8heEEKLVyTh5GI3KRDGutPHv5uh0xG1OUZQqL7GxsbYY64TOrKwsSktLSUxMtE0fFfWXV9KAIlv6j7BjnuX7B9+CLuG1vuvYfh0Y268DJrPCpDU/cSzr2n5EiqLwn4MXeOzve7laZKRfJx3/mDgIV5cG7Bknmo11uWg58t9L1M/IkSM5fPgwBw8etF0GDRrEE088wcGDB+nWrdtNtxAYOHAgLi4udjFZWVmkpqbaYsLCwsjLy2P//v22mH379pGXl2cXk5qaSlZWli0mISEBrVbLwIEDbTG7du3CaDTaxQQGBtKlS5cmfa1E3ZWWm/GydbLVpsiWBIpCO+vwAymyCdHkpBdeCNHq5J61DD3I1HSlh3SGCHHbyq1vkc1YBP+ZCihwVzQMeqbOz/23R/ty7koxhy/k8fCyH/ndoE74ttGy68QlDmbkAnBfT1/ef2IAnq4ySbS1sO3Jpsh5aFE/np6elU6ieHh40K5dO9vt1i0EevbsSc+ePYmPj7fbQkCn0zFp0iRmz55Nu3bt8PHx4cUXX6Rv3762aaO9e/dmzJgxTJ48mQ8//BCAP/7xj4wbN46QkBAAIiMj6dOnDzExMbz99ttcvXqVF198kcmTJ9u6z6Kjo3n99deJjY3llVde4eTJk8THx/P//t//k+7bFsiuk6265aIAgXeDsysUX4Yrp2wTRqWTTYimJ0U2IUSro1y0bCJeoOvl6FSEEA6UX1Fka+texyLW9tdBnw5eHeHBv0E9Pkh6urrwyTP3MPtfv/Df4zms33fOdkyjdmLqiO5MH9EDZ7UUa1oTtXSyiWbw0ksvUVJSwtSpU9Hr9QwZMqTSFgKLFy/G2dmZCRMmUFJSwsiRI1m9ejVq9bX/N9etW8fMmTNtU0jHjx/PsmXLbMfVajVff/01U6dOJTw8HDc3N6Kjo1m4cKEtRqfTsW3bNqZNm8agQYPw9vYmLi6OuLi4Zns9RO0Zysqu7clW03JRZ61lC4SzP8LZPfh43APSySZEs5AimxCi1XHPTbN849fH0akIIRwot2K6aJ062bIOwf4Vlu/Hvweuuno/v7eHhpUTB/HDycvsTLtESZmJHn5teOiuDvh5Vr/huWi5nFXWPdmkyCYaz86dO+2uW7cQmDt3brX3cXV1ZenSpSxdurTaGB8fH9auXVvjcwcHB/PVV1/VGNO3b1927dpVY4xoGcqL81GrLIMpalwuSsWS0bM/wrkkfHzuBRl8IESzkCKbEKLVCSj9FWSyqBC3PeuebG3dajldVFEg4X8ty0TvfBR6jGpwDiqVivt7tef+Xu0b/FjC8WzLRWXbYiFEC6SUWIZhGFUaNC5uNQfb9mXbg3dQxXTRYimyCdHU5C8IIUSrotdfpROWqVcdeg5wdDpCCAeyFtm8atvJdmo7nEkEtQZGvda0yYlWSYWlQ8SM7EUlhGh5lBLLnp8l6lpMdA26B1ROoE+ng5OlOCedbEI0PSmyCSFalcxThwC4Qls8vKseLS+EuD3UafCBosD2iqVZQ6aAt0zNE0II0bo4lVqKZaXOnjeNxdUL/O8EoGO+ZWjYlUIpsgnR1KTIJoRoVXIzLEMPLmmDHZ2KEMLB6jT44OQ2uJgKmjZwr2zoLYQQovVxMuQBYHCu5X6iwcMA8L36MwB6WS7a6ikVHdei5ZIimxCiVSnPOQFAiVc3R6cihHAgRVHILa5DJ9vuRZavg54Gd58mzk4IIURdLViwgMGDB+Pp6Ymfnx+PPPIIaWlpdjGKojB37lwCAwNxc3Nj+PDhHDlyxC7GYDAwY8YMfH198fDwYPz48Zw/f94uRq/XExMTg06nQ6fTERMTQ25url3MuXPneOihh/Dw8MDX15eZM2diNNoXqQ4fPkxERARubm507NiRefPmoShNVwRRVxTZylxq0ckGEDwUAI/sZACKjSZKy0xNlp8QQopsQohWRpt3GgBV+56OTkUI4UDFRhPlZssHmZt2smUkw7m9lr3Yhk5rngRFq6SSDgEhHCYxMZFp06aRlJTEtm3bKC8vJzIykqKiIlvMW2+9xaJFi1i2bBnJyckEBAQwevRoCgoKbDGzZs1i8+bNbNiwgd27d1NYWMi4ceMwma4Vl6Kjozl48CBbt25l69atHDx4kJiYGNtxk8nE2LFjKSoqYvfu3WzYsIGNGzcye/ZsW0x+fj6jR48mMDCQ5ORkli5dysKFC1m0aFGTvUaqMstrYXLxqN0dKoYfOF06gre6BGRfNiGanEwXFUK0Ku1KzgLg2bGPo1MRQjiQdT82F7UKNxd1zcE/rbR8Df0deHVohuxEa6fI4AMhmt3WrVvtrq9atQo/Pz9SUlK4//77URSFJUuW8Oqrr/Loo48CsGbNGvz9/Vm/fj1TpkwhLy+PlStX8umnnzJqlGWC9Nq1awkKCmL79u1ERUVx7Ngxtm7dSlJSEkOGDAHgo48+IiwsjLS0NEJCQkhISODo0aNkZGQQGBgIwDvvvENsbCzz58/Hy8uLdevWUVpayurVq9FqtYSGhnLixAkWLVpEXFwcKlXj/x5RlxUDYHJpU7s7eHUA766o9GcY7naazYWhXC0yEtj2JpNJhRD1Jp1sQohWo7DUSJCSBYBf11BHpyOEcKA821JRTc0fZIqvQuomy/eDJzVTdkIIIRoqL8+yNNLHx7LE/8yZM2RnZxMZGWmL0Wq1REREsGfPHgBSUlIoKyuziwkMDCQ0NNQWs3fvXnQ6na3ABjB06FB0Op1dTGhoqK3ABhAVFYXBYCAlJcUWExERgVartYvJzMwkPT29yp/JYDCQn59vd6kLp/KKrj5NLTvZALreD8B96lSQTjYhmpwU2YQQrcaF9BO4qsow4oxnQHdHpyOEcKDcEsuHBJ3bTZryf/kMTAbw7wsdBzZPckIIIRpEURTi4uK49957CQ21nFjNzs4GwN/ffrq8v7+/7Vh2djYajQZvb+8aY/z8/Co9p5+fn13Mjc/j7e2NRqOpMcZ63RpzowULFtj2gdPpdAQFBdXpdXEut3SyUdvlogDdRwAw2HQIpMjWao132sMGzf+hM+kdnYq4CSmyCSFaDf05y8a22eqO4HST5WFCiFuadbLoTYceHFxv+TpwIjTB0h0hhBCNb/r06Rw6dIjPPvus0rEbu5cVRbnp0swbY6qKb4wY69CD6vKZM2cOeXl5tktGRkaNed/IxWTZV02lrUsnWwSgIqg8nfbouSJFtlbpPc0yhjodIzp/paNTETchRTYhRKthyLZMmMp17+zoVIS47XzwwQd07doVV1dXBg4cyA8//ODQfPIqimxt3TXVB+Uch4up4OQCof/TfMmJVsv6sTgqVPbuE8JRZsyYwZdffsn3339Pp06dbLcHBARAFV1iOTk5tg6ygIAAjEYjer2+xpiLFy9Wet5Lly7Zxdz4PHq9nrKyshpjcnJyoIpuOyutVouXl5fdpS5czJZONpW2lnuygWWidoe7ALjXKRW9FNlaNQ+l0NEpiJuQIpsQotVwvnoSgLK2slRUiOb0+eefM2vWLF599VUOHDjAfffdx4MPPsi5c+ccllNucS062VL/bfnaY5TlQ4YQN6FRW/407h/c1tGpCHHbURSF6dOns2nTJv773//StWtXu+Ndu3YlICCAbdu22W4zGo0kJiYybNgwAAYOHIiLi4tdTFZWFqmpqbaYsLAw8vLy2L9/vy1m37595OXl2cWkpqaSlZVli0lISECr1TJw4EBbzK5duzAajXYxgYGBdOnSpQleIdBUdLI5aT3rdseKJaP3qg9LJ1srp8gQ7BZPimxCiFbDs8iyiayzfy9HpyLEbWXRokVMmjSJZ599lt69e7NkyRKCgoJYvny5w3LKu9lyUUWBw/+yfN/3d82YmWjVZEWxEA4zbdo01q5dy/r16/H09CQ7O5vs7GxKSiqWSKpUzJo1i/j4eDZv3kxqaiqxsbG4u7sTHR0NgE6nY9KkScyePZsdO3Zw4MABnnzySfr27WubNtq7d2/GjBnD5MmTSUpKIikpicmTJzNu3DhCQkIAiIyMpE+fPsTExHDgwAF27NjBiy++yOTJk23dZ9HR0Wi1WmJjY0lNTWXz5s3Ex8c32WRRAK3Z8lqoXeuwXBSg23CwdrIVGpoiNdFMVEiVraW7yW7BQgjRcgSUWfat8Op0p6NTEeK2YTQaSUlJ4S9/+Yvd7ZGRkbYpbDcyGAwYDNf+iK/r9LTayL1ZkS37EOjTwdkNQh5s9OcXQgjRuKwnboYPH253+6pVq4iNjQXgpZdeoqSkhKlTp6LX6xkyZAgJCQl4el7r7Fq8eDHOzs5MmDCBkpISRo4cyerVq1Grr+3nu27dOmbOnGmbQjp+/HiWLVtmO65Wq/n666+ZOnUq4eHhuLm5ER0dzcKFC20xOp2Obdu2MW3aNAYNGoS3tzdxcXHExcU12WvkqliKbM5udexkCxqKyUmLvzkXj7wTwKCmSVAIIUU2IUTroNfr8cOyv0ZAVymyCdFcLl++jMlkqnGa240WLFjA66+/3qR53bSTLW2r5Wv3B0BTxzP+4rYlHQJCOI5Si3VwKpWKuXPnMnfu3GpjXF1dWbp0KUuXLq02xsfHh7Vr19b4XMHBwXz11Vc1xvTt25ddu3bdNO/G4qqUggqcXeu2lxsuruQHDMU7M5E+hXuA6KZKUYjbniwXFUK0ClnnLEMP8vHATefr6HSEuO3UZZpbQ6en1UZesXXwQTVFthPfWr6GjGn05xa3A1k3KoRoedwpBcDFrQ6DDyoYulveD+8xJDV6XkKIa6TIJoRoFXLPnwDgskugo1MR4rbi6+uLWq2ucZrbjRo6Pa02auxky8+CzAOWQkkvKbIJIYRo/cpNZluRTeNW9/dV5z6/AaAvJzHlZd00XrRMcgqo5ZMimxCiVTBeOgVAoXuQo1MR4rai0WgYOHCg3aQ2gG3bttmmsDmCtchWZSfbiYqloh0HQhu/Zs5MCCGEaHzGsjLcVJbJoC7uddyTDdD5BXPQ3B2A0iNfN3p+QggLKbIJIVoFlf4sAOa2nR2dihC3nbi4OP7xj3/w8ccfc+zYMV544QXOnTvHc88957CccostHzSq7GQ7/V/L115RzZyVEEII0TQMxYW27zV1HXwAuKid2OU02HLluBTZhGgqMvhACNEqtCm27Onk4tvd0akIcdt5/PHHuXLlCvPmzSMrK4vQ0FC++eYbOnd2TNHbZFYoMJQD4HVjkc1shvQfLN93G17FvYWoiXXjdVmQI4RoWcpKCixfFTUuGtd6PcYBt3Ao2YDb+d1Qogc370bOUjQ9GdDT0kknmxCiVfAtywSgTYeejk5FiNvS1KlTSU9Px2AwkJKSwv333++wXApLy7EOoavUyXbxsOWDg8YTAgc4JD8hhBCisZWV5AFQjCtUM3joZvI9u3PcHIST2QhHv2zkDIUQSJFNCNEaFJYY6KDkAOAbHOLodIQQDpZfatmPTePshNZZbX/w10TL187DQC0N+0IIIW4NplLLctESVf262AC8PbRsNt1ruXLo88ZKTQhxnVZRZEtPT2fSpEl07doVNzc3unfvzmuvvYbRaLSLO3fuHA899BAeHh74+voyc+bMSjFCiNYnK+M0GpWJMtR4+AY7Oh0hhIMVlFYsFXWtooh2Zpfla7eIZs5KCCGEaDrlFUU2QwOKbO08NHxpGoaCCs7+CLnnGjFDIQStZU+248ePYzab+fDDD+nRowepqalMnjyZoqIiFi5cCIDJZGLs2LG0b9+e3bt3c+XKFSZOnIiiKCxdutTRP4IQogHyLqQBcFEdQCcn9U3jhRC3toKKTjZP1xuWiprK4ewey/ddHbecVbReshObEKKlMhmKATCotPV+DG8PDVm0I92zP10LfoZD/4T7X2zELIUQraLINmbMGMaMGWO73q1bN9LS0li+fLmtyJaQkMDRo0fJyMggMDAQgHfeeYfY2Fjmz5+Pl5dXlY9tMBgwGAy26/n5+U3+8wgh6qYk51cA8rSd6OToZIQQDmftZPO8sZMt5wiUFYFWB353OiY5cWuo535HQgjRVEzGEgDKVJp6P0Y7D8t993qMthTZfv4E7n0B5CS2EI2mVSwXrUpeXh4+Pj6263v37iU0NNRWYAOIioqybdBcnQULFqDT6WyXoKCgJs9dCFFHV88AUOop/z6FEFBgsHay3VBky9hv+dppEDi12j9xhBCNJCMjgx9++IHvvvuOn3/+2e7EuhCtja3I5tSwTjaAHepwcG0LuWfhZEKj5SiEaKVFttOnT7N06VKee+45223Z2dn4+/vbxXl7e6PRaMjOzq72sebMmUNeXp7tkpGR0aS5CyHqzrXwLACKd1dHpyKEaAFsnWzaG5aLWotsQfc4ICshREtw9uxZ5syZQ5cuXejSpQsRERE8+OCDDBo0CJ1Ox+jRo/nXv/6F2Wxukudfvnw5/fr1w8vLCy8vL8LCwvj2229txxVFYe7cuQQGBuLm5sbw4cM5cuSI3WMYDAZmzJiBr68vHh4ejB8/nvPnz9vF6PV6YmJibI0CMTEx5Obm2sXUZr/qw4cPExERgZubGx07dmTevHko1vHNokUxVxTZTA1YLmrtZLtY6gQDnrLcuO/DxklQCAGOLrLNnTsXlUpV4+Wnn36yu09mZiZjxozhscce49lnn7U7pqqitV9RlCpvt9JqtbY3QetFCNGy6EozAdC27+boVIRokA8++ICuXbvi6urKwIED+eGHHxydUqtU7XLRjH2Wr1JkE+K29Pzzz9O3b19OnjzJvHnzOHLkCHl5eRiNRrKzs/nmm2+49957+etf/0q/fv1ITk5u9Bw6derE3/72N3766Sd++uknHnjgAR5++GFbIe2tt95i0aJFLFu2jOTkZAICAhg9ejQFBQW2x5g1axabN29mw4YN7N69m8LCQsaNG4fJZLLFREdHc/DgQbZu3crWrVs5ePAgMTExtuPW/aqLiorYvXs3GzZsYOPGjcyePdsWk5+fz+jRowkMDCQ5OZmlS5eycOFCFi1a1Oivi2g4c1kpAOXq+hfZfCqKbFcLjTD4WVA5wa/fw6W0RstTNC0VUgRv6Rq8J5vBYECrrd8/9OnTp/P73/++xpguXbrYvs/MzGTEiBGEhYWxYsUKu7iAgAD27dtnd5ter6esrKxSh5sQovVQFIV25TmggraB3R2djhD19vnnnzNr1iw++OADwsPD+fDDD3nwwQc5evQowcEyNbcu8isGH3i5XdfJVphjWfaCCjoOclxyolVTSQdPq6bRaDh9+jTt27evdMzPz48HHniABx54gNdee41vvvmGs2fPMnjw4EbN4aGHHrK7Pn/+fJYvX05SUhJ9+vRhyZIlvPrqqzz66KMArFmzBn9/f9avX8+UKVPIy8tj5cqVfPrpp4waNQqAtWvXEhQUxPbt24mKiuLYsWNs3bqVpKQkhgwZAsBHH31EWFgYaWlphISE1Gq/6nXr1lFaWsrq1avRarWEhoZy4sQJFi1aRFxcXI2NCqL5KWUVnWwNWC5qLbJdKTKitA1GFfIbOP4V7F4Cv13eaLkKcTurcyfbd999R2xsLN27d8fFxQV3d3c8PT2JiIhg/vz5ZGZm1vqxfH19ueOOO2q8uLpaRhRfuHCB4cOHM2DAAFatWoXTDXuthIWFkZqaSlZWlu22hIQEtFotAwcOrOuPKYRoIa7m5tJOZRlI0r5jD0enI0S9LVq0iEmTJvHss8/Su3dvlixZQlBQEMuXyx+1dVVlJ5t1qahfb3CVrnTRQFJcaJXefvvtKgtsVfnNb37D7373uybNx2QysWHDBoqKiggLC+PMmTNkZ2cTGRlpi9FqtURERLBnj2UyckpKCmVlZXYxgYGBhIaG2mL27t2LTqezFdgAhg4dik6ns4u52X7Ve/fuJSIiwq5hIioqiszMTNLT06v9uQwGA/n5+XYX0QysRbYGdLL5trHc11BupsBQDvfFWQ4c+hyunG6cPIW4zdW6yPbFF18QEhLCxIkTcXJy4s9//jObNm3iu+++Y+XKlURERLB9+3a6devGc889x6VLlxotyczMTIYPH05QUBALFy7k0qVLZGdn2+21FhkZSZ8+fYiJieHAgQPs2LGDF198kcmTJ8sSUCFasZzzlsmiRbjh6ulz03hx+zIYDPzwww98+umnfPjhh2zatIkzZ844Oi0AjEYjKSkpdh+aqHjvsn4gupF8iKnetSLbdZ1smQcsXzvKiTUhRNX0ej1Lly7l7rvvbtLnOXz4MG3atEGr1fLcc8+xefNm+vTpY/vscuMqG39/f9ux7OxsNBoN3t7eNcb4+flVel4/Pz+7mJvtV11VjPV6TXtay+A4x1DKLYM7zGrXej+Gm0aNp9ZygupSgcHyntkzChQTJL7VaLkKcTur9XLR+Ph4Fi5cyNixYyt1kQFMmDABKjrO3n33XT755BO7Nf8NkZCQwKlTpzh16hSdOnWyO2bdmFOtVvP1118zdepUwsPDcXNzIzo6moULFzZKDkIIx8jLshTZrqj98JDOAlGFPXv2sHTpUr744guMRiNt27bFzc2Nq1evYjAY6NatG3/84x957rnn8PT0dEiOly9fxmQy1fjB6kYLFizg9ddfb6YMW5eC0iqmi2b9Yvna4S4HZSWEaKm2b9/OypUr+eKLL/D19bUt1WwqISEhHDx4kNzcXDZu3MjEiRNJTEy0Hb9xGebN9pCuKqY2e1HXJ8b62aqmfObMmUNcXJzten5+vhTamoGq3NLJpjSgkw2gvaeWAkM5lwoMdG/fBob/BU5+B4c2wD1/hE5yskqIhqh1kW3//v21iuvYsSNvvdW4VfDY2FhiY2NvGhccHMxXX33VqM8thHCsksuW5QqFrh0cnYpogR5++GGSk5OJjo7mu+++Y9CgQbi7u9uO//rrr/zwww989tlnLFq0iE8++YTRo0c7LN+6fLCSDzHVs3ayeV1fZMs+ZPnaoWk7VIQQrcO5c+dYtWoVq1atorCwEL1ezz//+U/+53/+p8mfW6PR0KOHZYuLQYMGkZyczLvvvsvLL78MFV1iHTpc+7smJyfHdhImICAAo9GIXq+362bLyclh2LBhtpiLFy9Wet5Lly7ZPc7N9qsOCAiodKInJycHqui2u55Wq633ntyiAcotgw8U5/p3slFRZPv1chE5BZbOODoOgH6/txTZvn0JJm2DKppqhBC1U6d/PbNmzSI1NbXpshFCiBvlZgBgbBN401Bx+4mMjCQ9PZ2FCxdy//332xXYALp168bEiRPZunUr27dvd1ievr6+qNXqKj/MVPdBRqZfVy+/xNrJVrFctCAbCi9apqT53+nY5ESrdm1qm3ROt1b//Oc/iYyMpHfv3qSmpvLuu++SmZmJk5MTvXv3dkhOiqJgMBjo2rUrAQEBbNu2zXbMaDSSmJhoK6ANHDgQFxcXu5isrCxSU1NtMWFhYeTl5dk1Qezbt4+8vDy7mJvtVx0WFsauXbswGo12MYGBgXbD50TLoDJZimKNUWTDulzUatRc0LSBCz9B8kcNS1Q0KXl3avnqVGTbunUrd911F/fccw8rVqyQ/WGEEE1OU1QxTEUnHTyismnTplW5hUFV7rzzTod1sWk0GgYOHGj3oQlg27Zttg9EovYqDT7Iquhi8+0FGvca7imEuNVFR0czaNAgsrOz+de//sXDDz+MRqNptud/5ZVX+OGHH0hPT+fw4cO8+uqr7Ny5kyeeeAKVSsWsWbOIj49n8+bNpKamEhsbi7u7O9HR0QDodDomTZrE7Nmz2bFjBwcOHODJJ5+kb9++tmmjvXv3ZsyYMUyePJmkpCSSkpKYPHky48aNIyQkBGq5X3V0dDRarZbY2FhSU1PZvHkz8fHxMlm0hXKydbI1rIvQz9NSpMspKL12o1cHGPma5ftt/w8unWjQc4imJFOwW7o6FdmOHz/Orl276Nu3Ly+++CKBgYE89dRT7Nq1q+kyFELc1jxLLWdgXdoFOzoV0UJ16NCBF198kaNHjzo6lRrFxcXxj3/8g48//phjx47xwgsvcO7cOZ577jlHp9bqXNuTraKTTfZjE0JUeOaZZ/jggw8YM2YMf//739Hr9c36/BcvXiQmJoaQkBBGjhzJvn372Lp1q+0kz0svvcSsWbOYOnUqgwYN4sKFCyQkJNjtGbp48WIeeeQRJkyYQHh4OO7u7mzZsgW1Wm2LWbduHX379iUyMpLIyEj69evHp59+ajtu3a/a1dWV8PBwJkyYwCOPPGK3X7VOp2Pbtm2cP3+eQYMGMXXqVOLi4uy2KhAth1NFJxvObg16nCo72QAGPwvdH7AsS904CYzFDXoeIW5Xtd6TzSo8PJzw8HCWLl3K559/zqpVqxg+fDjdu3dn0qRJPPXUU3ajooUQoiF8TJa9QTz9ujk6FdFCxcXFsXr1ahYvXsw999zDs88+y+OPP06bNm0cnZqdxx9/nCtXrjBv3jyysrIIDQ3lm2++oXPnzo5OrVUxmRWKjCa4vpMtW4psQgiLFStW8O677/LPf/6Tjz/+mFmzZhEVFYWiKJjN5iZ//pUrV9Z4XKVSMXfuXObOnVttjKurK0uXLmXp0qXVxvj4+LB27doan6s2+1X37dtXGiZaCXVFkU3l0rDlon7VFdmcnODhD2D5MMs+p5unwGNrGrw/m8mskFtspI2rM1pndS3uIWqiyILRFq/e/2Lc3d15+umn2bVrFydPnmTChAm89dZbsn5fCNFoiksN+CtXAPDuKEU2UbU5c+aQlpbGzp07ueOOO5g1axYdOnTg6aef5scff3R0enamTp1Keno6BoOBlJQU7r//fken1OoUViwVxa7IdtjyNaCvg7ISQrQkbm5utomehw8fpk+fPvj7+xMeHk50dDSbNm1ydIpC1JnabFne2dAiW7WdbFQsG/39OnBygWNfwnevgFK/5YlXi4z89YtU7p6XwMA3thP62nfErNxH4olLDcr/dqeS5aItXoPHhhQVFZGYmEhiYiK5ubl07969cTITQtz2Lmaew0VlolxxwtNX9mQTNbvvvvtYtWoV2dnZLFmyhFOnTnHfffcREhLS6FOvhePkVywV1Tg7Wc6IG4tBf9Zy0K+PY5MTtw7Zj+qW0bNnTxYsWEBGRgZr166luLiYP/zhD45OS4g6U5stAyqcXBq292iNRTaAzsPg4WWW7/cth29ehDp2gZ7KKWDsez/wadJZ2z6qZSaFH05eZuLH+5m27meuFhlv+jhCtEb1LrLt2rWLp59+moCAAJ5//nl69erFDz/8wLFjxxo3QyHEbSsv+1cALjv5gpO0l4va8fDwYNKkSfzwww9s2bKFy5cvM2fOHEenJRqJ9Y91L2sX2+UTlk2A3X3Bw9exyYlbhpTYbj1OTk489NBDfPHFF2RkZDg6HSHqzNlsKYo5aRpnueiVIiNlpmqKZ3f9Hh56z/LbMPkfsCEaSnJr9fg5+aVM/DiZrLxSurX3YP2zQzg5/0G+f3E4T4d3Qe2k4uvDWYxftpu07IIG/SxCtER1KrKdP3+e+fPn07NnT4YPH87x48dZvHgxWVlZfPzxx4SHhzddpkKI207JpXQAcjX+jk5FtCLFxcWsWrWK+++/n/Hjx9OuXTvmz5/v6LRanPT0dCZNmkTXrl1xc3Oje/fuvPbaaxiN9meWz507x0MPPYSHhwe+vr7MnDmzUkxzqjT04NJxy9f2dzgsJyFEy5SWlsb06dMZOXIko0aNYvr06aSlpeHn5+fo1ISoM5eKIpu6gVO0vd01ODtZTiVcKazh/XzgRPiff4BaCye+hQ/vh9P/rfGxFUXhxX8f4kJuCd18Pdj43DCG9fDFRe1EV18PXnvoTv4zLZzO7dw5ry/h0Q9+lOWj4pZTpyJbly5deO+993j44Yc5cuQIe/fu5dlnn21xm0sLIW4N5XrLmeZitw6OTkW0Aj/88APPPPMMAQEBTJ8+na5du/L9999z4sQJ/vKXvzg6vRbn+PHjmM1mPvzwQ44cOcLixYv5+9//ziuvvGKLMZlMjB07lqKiInbv3s2GDRvYuHEjs2fPdlje1k42235sORUd9H5SZBNCXPPvf/+b0NBQUlJSuOuuu+jXrx8///wzoaGh/Otf/3J0ekLUmYtiKYipNQ2bLurkpMK3zU2WjFr1/R1MSoC2wZB7Fj79Lfz7Gbh8qsrwTT9fYNeJS2icnfho4iC8PTSVYkI76vhiajhDu/lQZDTxzOpk/vmTdJfWluzJ1vLVabroP//5T8aPH4+zc52HkgohRJ2p888DUN6mo6NTES1YfHw8q1ev5vTp0wwaNIi3336bP/zhD3h5eTk6tRZtzJgxjBkzxna9W7dupKWlsXz5chYuXAhAQkICR48eJSMjwzY5/J133iE2Npb58+c75DUuMFg72Sr+FpFONtGIrn14kQWjrd1LL73EnDlzmDdvnt3tr732Gi+//DKPPfaYw3IToj6sRTZnbcOWi1KxL1t2fik5BaWArubgwLvhuR/hv2/A/hWQuhGObIY+D8OAp6BrBDipKS0z8fZ3aQDMGtWT7u2rb8Tx9tDwyTNDeHnjITYfuMBL/z7EBX0Js0b1RCV7YopWrk7VskcffdTuek5ODjk5OZXGYffr169xshNC3Na0xdkAqL07OToV0YItXryYJ598kkmTJhEaGurodFq1vLw8fHx8bNf37t1LaGiorcAGEBUVZZuOOmLEiCofx2AwYDBcOzuen5/faDnaOtm0FctFrZ1sUmQTQlwnOzubp556qtLtTz75JG+//bZDchKiITSKdbmoR4Mfy7ov28X8m3SyWbl6wW/egrujYeffLMtHj2y2XDwDoVcke8r6UpLvSQedL5Pu7XrTh9Q4O7Fowl0EtnXl/e9P8+6Ok2TmlhD/aF9c1A2ezyiEw9SrJS0lJYWJEydy7NgxlIqRviqVCkVRUKlUmEymxs5TCHEbamO07NHg5iOTRUX1MjMzcXFxcXQard7p06dZunQp77zzju227Oxs/P3t90T09vZGo9GQnZ1d7WMtWLCA119/vUnytFsuaiyC3HOWA369m+T5hBCt0/Dhw/nhhx/o0aOH3e27d+/mvvvuc1he4tbzwQcf8Pbbb5OVlcWdd97JkiVLGv//MUVBg6WTuzE62QJ0lsfIziup2x0D74boDZB9GFJWw+F/QUEmpKzmAeAXVyh0CkS7cRC0DwHvLuDdFdoGWQYU3bCfnEql4s9Rd9CxrTv/+8Vh/pVynosFBj54YgBttLJ6TrRO9fo/9+mnn6ZXr16sXLkSf39/aekUQjQ6RVHwNl0BFXj6SZFNVO/6Atv+/fvZuXNnlV3WixYtckB2zW/u3Lk3LXAlJyczaNAg2/XMzEzGjBnDY489xrPPPmsXW9V7vPWkWnXmzJlDXFyc7Xp+fj5BQY3z7zi/YvCBl5uLTBYVQlRr/PjxvPzyy6SkpDB06FAAkpKS+Ne//sXrr7/Ol19+aRcrRH18/vnnzJo1iw8++IDw8HA+/PBDHnzwQY4ePUpwcHDjPZGpDDWWv2tctA0bfAAQ2Nayr1tmXmn9HiCgL4x9ByLnQ/oPnN3/JWVp2+nhlEmbkkw49iUcq+J+zm6W92t3H9B6gYs7uLgRrfHg/jsVvjtRQOGvzmxe7M5v7upEO093cHKuuKgrLhXXVU6Wpf0q1bUl/qobvqLCaFbI0Jdw5lIR2fkGckvKySspo6TMTLlJocwMCgouajUuzk44q9VonZ3Qujjj6uKEq4va8tVZbfle44xbxe1aFyfcXNS4Oqtxrui+UxTsdk1TUGFWzJjMCiYz5BUW1e81tz2g7MnW0tWryHbmzBk2bdpU6cyQEEI0lvziUtphGRXu26GLo9MRrUB8fDz/+7//S0hISKUTQLfTyaDp06fz+9//vsaYLl2u/ZvKzMxkxIgRhIWFsWLFCru4gIAA9u3bZ3ebXq+nrKysUofb9bRaLVqttt4/Q03sOtkuH7Hc6NurSZ5LCNF6TZ06FSq6jD744IMqj1Hx/iCrcER9LVq0iEmTJtlOUC1ZsoTvvvuO5cuXs2DBgsZ7ovJrxTAX14YX2TpUdLJl1bWT7UYurtBzNP+7y4sfjGN4PtyPF0JLIOsXuPor6NMtl7zzYDJCeQnkZVguN+gETHKqGM1YCuyr8hnrTAN0r7jUyAwVzYJNKt8gRbJbXb2KbCNHjuSXX36RIpsQoslcyjqHTqVQhhq3tgGOTke0Au+++y4ff/wxsbGxjk7FoXx9ffH1rV1X14ULFxgxYgQDBw5k1apVODnZ74ESFhbG/PnzycrKokMHy5TfhIQEtFotAwcObJL8b+Zakc0Frp623Nium0NyEbce6+ADRQYftHo3djML0diMRiMpKSmVJphHRkayZ8+eKu9T7Z6lCzqB9ua/d8yKCq22YdNFATroLI+RlVvPTrbrpF8u4oeTl1Gp4Hfhd4KPO3S93z5IUcBYCEWXofiK5WIogLISKCu2XIyWr0XFRew7fYmLuUU4Y8LVWaFzWy0dPJ3x0qrQOJlRmc2YzeUYy0wUGcopNJZTVFpGYWkZ5SbLv30VoFIpqFBwdnLCU6vGQ6vGRe2ERg3OTqqKGMvvfrNZQVHMmBXL9yazYvlesfw+MSvW28BsVjArZsxmMCmWOEWpevLnteewXCnGBKQ2+HUXLVe9imz/+Mc/mDhxIqmpqYSGhlbaC0daroUQDZV38SwAepUPfk6y+am4OScnJ8LDwx2dRquRmZnJ8OHDCQ4OZuHChVy6dMl2LCDAUtiOjIykT58+xMTE8Pbbb3P16lVefPFFJk+e7LDprQWl100XPVtRZPO56flpIYQQolFdvnwZk8lUqbPb39+/2n1LG7pn6T5zb3q6qOt9f6vAtpZOtsy8kptuAXEz/zmYCcC9PXwJ8qmmy06lAq2n5eJT81AED2CEovDN4WyWbD/ByZxCyMZyAdROKjRqJ0rKqu5A1aiduLOjF3cHtaV/sDf9g9rSydutxaxqyM/Ph7/dZKKraNXqVWTbs2cPu3fv5ttvv610TFquhRCNofjKeQAKXNrh5+hkRKvwwgsv8P7777NkyRJHp9IqJCQkcOrUKU6dOkWnTvYTfK1DjdRqNV9//TVTp04lPDwcNzc3oqOjWbhwoYOyvtbJ5uXqfF0nmxTZRONqIZ/FRB1t2LDhpsvlrTIyMjh37pycnBENdmPxpqaiVXV7ll6dtI8yT89qn2P3ycvM++ooV/HkkHPDTz5bBx+UlpnRF5fh46Gp1+MoisKXv1wA4OG7OzY4LyuVSsXYfh14MDSAXScv8fWhLFLO6jlzpQiTWaHEbKk3uKhV9PDzpE8HL+4M9KJ/cFv6BHqhdW54IVKI+qpXkW3mzJnExMTw17/+tcY9WYQQor7Kcy1nxUpc5XeMqJ0XX3yRsWPH0r17d/r06VOpy3rTpk0Oy60lio2NrdXS2uDgYL766qtmyak2rnWyucAV6WQTQlyzfPly5s6dy9NPP8348ePp3dt+6nBeXh4//vgja9euZfv27axcudJhuYrWz9fXF7VaXalrLScnp9rPyNXtWerj17HGDnFdroYrWIpZjVFA0jqr8W2j4XKhkczcknoX2Y5nF3D6UhEaZyci72z8v9mdnFQMD/FjeIjllHuJ0UReSRmGchNt3TR4uTm3mA41IazqVQa/cuUKL7zwghTYhBBNRlWYBUCZh+zHJmpnxowZfP/99/Tq1Yt27dqh0+nsLuLWYO1ka0shlFqGo9xs6YkQdScf2lqjxMREFi5cyH//+19CQ0Px8vKiZ8+e9O3bl06dOtGuXTsmTZpEly5dSE1N5aGHHnJ0yqIV02g0DBw4kG3bttndvm3bNoYNG9aoz+WuudYb46JunN9P1gmjWfWdMAps+cVyUnxESHu8XF1uGt9Qbho1ATpXOrfzQOfuIgU20SLVq5Pt0Ucf5fvvv6d7dzlzLIRoGpriirOCnh0cnYpoJT755BM2btzI2LFjHZ2KaELWIpt3acVkMs8OoPFwbFJCiBZj3LhxjBs3jitXrrB7927S09MpKSnB19eX/v37079//0pDXoSor7i4OGJiYhg0aJBtSve5c+d47rnnGvV5+nXS0bGtGx3bNt7eYh10rhw6n1fvCaOKovDVIctJ8YfuCmyUnMTNSVmx5atXka1Xr17MmTOH3bt307dv30pLcmbOnNlY+QkhblMeBssm7C7ejbe/g7i1+fj4yMmfW5zJrFBoqJguWmwZjiJLRYUQVWnXrh0PP/ywo9MQt7jHH3+cK1euMG/ePLKysggNDeWbb76hc+fOjfo8ri5qdv55OE6N2LllnTCaWc8Jo2kXCzh3tRitsxMP3CE7KAthVe/pom3atCExMZHExES7YyqVSopsQogG8yq7DIB7u043jRUCYO7cubz22musWrUKd/dqpluJVs1aYANwK0i3fNOum+MSEkIIcdubOnUqU6dObfLncVE3bgemdcJofTvZdhzLASC8h6/dclYhbnf1+tdw5syZxs9ECCEqmMwKvspVUIGXX7Cj0xGtxHvvvcfp06fx9/enS5culbqsf/75Z4flJhpHfoll6IHG2QlnfcXfItLJJoQQQtTZtU62+hXZ/nvcUmSTLrbmpUJxdAriJqTkLIRoca7qr9BeZXnDb+svRTZRO4888oijUxBNzLofm5erM+Ral4vK0APReGwfXmQzbSHELa6jt6XIlnG17kW2K4UGfj6nB2BkbymyCXG9WhfZ/va3vzFz5sxaLcHZt28fly9fls2nhRD1os8+S3ugEHfauFU/zlyI67322muOTkE0sYJSSyebp6sL5FYMPtAFOTYpIYQQohXq0s4yNCg7v5TSMhOuLupa33dn2iUUBfp08LJ1xAkhLGq9sPvo0aMEBwfzpz/9iW+//ZZLly7ZjpWXl3Po0CE++OADhg0bxu9//3u8vOSDsRCifoounQNAr/ZxdCriFqMo0mLfmlk72Xy0ZiismEDctnE3lxZC3JpMJhMHDx5Er9c7OhUhWgRvdxdLZzhw7mpxne5rXSo6SrrYhKik1kW2Tz75hP/+97+YzWaeeOIJAgIC0Gg0eHp6otVq6d+/Px9//DGxsbEcP36c++67r2kzF0Lcskr1mQAUuLR3dCqihevduzfr16/HaDTWGHfy5En+9Kc/8eabbzZbbqLxFRgsnWxdnK9abnDxAHcpxgshKps1axYrV66EigJbREQEAwYMICgoiJ07dzo6PSEcTqVS0cXX0s2Wfrmo1vczlptJPGFpuHmgt3+T5SeqIyeMW7o67cnWr18/PvzwQ/7+979z6NAh0tPTKSkpwdfXl7vvvhtfX9+my1QIcdsw5VmKbKWucnZM1Oz999/n5ZdfZtq0aURGRjJo0CACAwNxdXVFr9dz9OhRdu/ezdGjR5k+fXqzTP8STcfayRbsZJk+TNtg2TtLNKprG0rL/1et3b///W+efPJJALZs2cKZM2c4fvw4n3zyCa+++io//vijo1MUwuE6t/Pg0Pk8zl6pfSdbcvpVCg3l+LbR0q+jrknzE6I1qtfgA5VKxV133cVdd93V+BkJIUSh5eyY2UOKbKJmDzzwAMnJyezZs4fPP/+c9evX250A6t+/P0899RRPPvkkbdu2dXS6ooGsRbaOVGxZ0VYGowghqnb58mUCAgIA+Oabb3jsscfo1asXkyZN4r333nN0ekK0CF3aWfZbP3Ol9p1sO45ZloqOCGmPk5OckBDiRrVeLiqEEM3FpcTy5q3ylBZ0UTvDhg3j3Xff5cCBA+j1ekpLSzl//jxbtmxh+vTpUmC7ReRXDD4IUKTIJoSomb+/P0ePHsVkMrF161ZGjRoFQHFxMWp17Td4r6sFCxYwePBgPD098fPz45FHHiEtLc0uRlEU5s6dS2BgIG5ubgwfPpwjR47YxRgMBmbMmIGvry8eHh6MHz+e8+fP28Xo9XpiYmLQ6XTodDpiYmLIzc21izl37hwPPfQQHh4e+Pr6MnPmzEpbLBw+fJiIiAjc3Nzo2LEj8+bNkz1MbxOdK4YfnK1Dke2/xy8CMFKWigpRJSmyCSFaHDfjFQA0ug6OTkUI0YJYO9l8TdahBzJZVAhRtaeffpoJEyYQGhqKSqVi9OjRAOzbt4877rijyZ43MTGRadOmkZSUxLZt2ygvLycyMpKiomtFjLfeeotFixaxbNkykpOTCQgIYPTo0RQUFNhiZs2axebNm9mwYQO7d++msLCQcePGYTKZbDHR0dEcPHiQrVu3snXrVg4ePEhMTIztuMlkYuzYsRQVFbF79242bNjAxo0bmT17ti0mPz+f0aNHExgYSHJyMkuXLmXhwoUsWrSoyV4j0XJ09bV0sqVfrt1y0V8vFZJ+pRgXtYp7e8pWUUJUpV7LRYUQoim1Kbdsau7hI0U2IcQ11iKbt9FaZJNONiFE1ebOnUtoaCgZGRk89thjaLVaANRqNX/5y1+a7Hm3bt1qd33VqlX4+fmRkpLC/fffj6IoLFmyhFdffZVHH30UgDVr1uDv78/69euZMmUKeXl5rFy5kk8//dTWgbd27VqCgoLYvn07UVFRHDt2jK1bt5KUlMSQIUMA+OijjwgLCyMtLY2QkBASEhI4evQoGRkZBAYGAvDOO+8QGxvL/Pnz8fLyYt26dZSWlrJ69Wq0Wi2hoaGcOHGCRYsWERcXh0r2vbyldfVtA0BmXglFhnI8tDWXB6xTRYd0bUebm8QKcbuSTjYhRItiMit4my1LHbzad3R0OkKIFqSgYrmoZ2mW5QYpsolGZht8IIWFW8Lvfvc7XnjhBTp16mS7beLEiTz88MPNlkNeXh4APj6WSchnzpwhOzubyMhIW4xWqyUiIoI9e/YAkJKSQllZmV1MYGAgoaGhtpi9e/ei0+lsBTaAoUOHotPp7GJCQ0NtBTaAqKgoDAYDKSkptpiIiAhbEdIak5mZSXp6epU/k8FgID8/3+4iWicfDw3tPbUoCpy4WHDTeGuR7YE7ZN9kIaojRTYhRItyJb8Ab1UhAG2lyCaEuE5BaTkaynA3WP7Ip21nR6ckhGjBduzYwbhx4+jevTs9evRg3LhxbN++vdmeX1EU4uLiuPfeewkNDQUgO9vSievvb7+flb+/v+1YdnY2Go0Gb2/vGmP8/CoXOvz8/Oxibnweb29vNBpNjTHW69aYGy1YsMC2D5xOpyMoSJbut2a9O3gBcCyr5iJbfmkZ+89YVptIkc1xrk3BFi1VvYpspaWlvP322/zmN79h0KBBDBgwwO4ihBD1dfViJgDlqHH2aOfodISoUXp6OpMmTaJr1664ubnRvXt3XnvttUqbStdm42lxcwWlZQSoLH/g4+wG7vI7QghRtWXLljFmzBg8PT15/vnnmTlzJl5eXvzmN79h2bJlzZLD9OnTOXToEJ999lmlYzcuw1QU5aZLM2+MqSq+MWKsQw+qy2fOnDnk5eXZLhkZGTXmLVq23gGeABzPrrkjcffJy5SbFbq196CLr0czZSdE61OvhdTPPPMM27Zt43e/+x333HOPrNUXQjSaoquWIluuqi2+TtJsK+rGZDKxefNmjh07hkql4o477uCRRx7B2blp9g05fvw4ZrOZDz/8kB49epCamsrkyZMpKipi4cKFtpzGjh1L+/bt2b17N1euXGHixIkoisLSpUubJK9bVUFpOcFUFNm8AmVJn2h00h9w61iwYAGLFy9m+vTptttmzpxJeHg48+fPt7u9KcyYMYMvv/ySXbt22S1XDQgIgIousQ4dru09m5OTY+sgCwgIwGg0otfr7brZcnJyGDZsmC3m4sWLlZ730qVLdo+zb98+u+N6vZ6ysjK7mBs71nJyLN3CN3a4WWm1WrvlpaJ1u6NDRZHtJp1sO45VLBUNkS42IWpSr08dX3/9Nd988w3h4eGNn9H/b+/e46Kq8/+Bv87MwHAfR0dBEkRtMxFNhTI0I0sxU7OyzGxJ9mvs+lVTQ7fVahNLNAPNR+5q6a5mv3bTb0t2UVNYL5SJN7zkpbJSAxVSERmuM8PM+f0xcHLkzlzODLyej8c85Jx5n5n3OQPzcd7zuRBRu1ZVbJ1rqVSlBdcsopY4deoUxo8fj8LCQvTu3RsAcPbsWXTu3Bmff/45+vXr5/DnfPjhh/Hwww9L2z179sQPP/yANWvWSEW25kw8Tc1TWlWNYOGmIhuR07CA6+n0er3N+3Ot+Ph4/OUvf3Ha84qiiBdeeAFbtmzB3r170aNHD5v7e/TogZCQEGRlZWHgwIEAAKPRiOzsbCxbtgwAEB0dDS8vL2RlZWHixIkAgIKCApw6dQpvvfUWACA2NhYlJSU4dOgQ7rnnHqBm5dSSkhKpEBcbG4vU1FQUFBRIBb3MzEyo1WpER0dLMS+//DKMRiO8vb2lmNDQUERERDjtOpH7kIaLFuob7FFZbbZg9/fWou6DfVhkI2pMq7qJ3HbbbQgMDHR8NkTU7lXrrd+mVnqzxEYt8/zzz6Nv3764ePEijh49iqNHjyI/Px/9+/fHH//4R5flUVJSIk1wjWZOPF0fTixty2wRUWaoRtfaIlsgVx8mx6v9aMlOkp7v0UcfxZYtW+rs/+yzzzBu3DinPe+MGTPw4Ycf4t///jcCAwNRWFiIwsJCVFZWAjVDMOfMmYMlS5Zgy5YtOHXqFBITE+Hn54fJkycDADQaDaZOnYq5c+di165dOHbsGH7/+9+jX79+0mqjffr0wcMPP4ykpCQcOHAABw4cQFJSEsaOHSt90RQfH4/IyEgkJCTg2LFj2LVrF+bNm4ekpCTpC57JkydDrVYjMTERp06dwpYtW7BkyRKuLNqO9NQFwFupQGlVNfKuV9Qbk3OuCMUVJnTy98Y9ER3rjSHX4F+l+2tVT7bly5fjL3/5C9599110785Jh4nIccQya1d0ow/nWqKWOXHiBI4cOWIztEar1SI1NRV33323S3L4+eefsWrVKixfvlza15yJp+uzdOlSLFq0yKn51jIYDBg8eDBOnDiBY8eOYcCAAdJ9eXl5mDFjBnbv3g1fX19MnjwZ6enpUo8HVykzVAPAb3OysScbEd3inXfekX7u06cPUlNTsXfvXsTGxgIADhw4gG+++QZz5851Wg5r1qwBADzwwAM2+zds2IDExEQAwEsvvYTKykpMnz4dxcXFGDx4MDIzM206Mbz99ttQqVSYOHEiKisr8dBDD+H999+HUqmUYv71r39h1qxZ0iqkjz76qM18c0qlEtu2bcP06dMxdOhQm/fwWhqNBllZWZgxYwZiYmKg1WqRnJyM5ORkp10jci/eKgX6ddMg95diHDp/Hd071Z1vbdu31pEmo6JCoFJyOheixrSqyBYTE4Oqqir07NkTfn5+8PLysrn/+vXrjsqPiNoZZYW1yGbxZ1d0apnevXvj119/Rd++fW32X7lyBbfffnuLHislJaXJAtfhw4cRExMjbV++fBkPP/wwnnrqKTz//PM2sc2ZePpWCxYssPmQo9frnbaC20svvYTQ0FCcOHHCZr87zSdXWmUCAHRVFFt3sMhGRLd4++23bba1Wi3OnDmDM2fOSPs6dOiA9evX49VXX3VKDrWLBjRGEASkpKQgJSWlwRgfHx+sWrWq0ffajh074sMPP2z0ucLDw7F169ZGY/r164evvvqqybyp7bo7oiNyfynG4QvX8VSM7f81TGYLdpy2fik4th97kRM1pVVFtmeeeQaXLl3CkiVLEBwczK7EROQw3lVFAAAhsP7JdokasmTJEsyaNQspKSm49957gZpeC6+//jqWLVtmM9yyqXnQZs6ciUmTJjUac/NcNZcvX8bw4cMRGxuLtWvX2sQ1Z+Lp+rhqYukvv/wSmZmZyMjIwJdffmlzX2vnkzMYDDAYDNK2I4a6llZZe7LdxiIbETXg/PnzcqdA5JEG9+iId7N/xsHzdTvLfHX2Km7UDhXtwaGi8uMSPe6uVUW2/fv3IycnB3fddZfjMyKids3PaC2yeWtC5E6FPMzYsWMBABMnTpS+/KntUVA7/05t7zGz2dzoY+l0Ouh0zZsX8NKlSxg+fDiio6OxYcMGKG5ZFbc5E0/L5ddff0VSUhI+/fRT+Pn51bm/qfnkhg8fXu/jOmOoa22RLVi4bv3/ZSCLbOR4gvThhV8gtyW1bQE7BhDVLyZCCy+lgF+KKvDTlTLc3iVAuu/DA78AAB4feBuHihI1Q6uKbHfeeac0eScRkSMFVVu/QfPV8gM0tcyePXtc/pyXL1/GAw88gPDwcKSnp+Pq1avSfSEh1kLxzRNPp6Wl4fr163UmnpaDKIpITEzEtGnTEBMTgwsXLtSJae18cs4Y6lpaZYICFnQS2ZONiJrngw8+QFpaGn788UcAwB133IE///nPSEhIkDs1IrcS6OOF+27XYc8PV/HlyQK88NDvAAD51yuw96z1/zbP3su52N0Dvyxwd60qsr355puYO3cuUlNT0a9fvzpzssn5oYGIPJcoitCKNwABCOjEOR+oeY4fP44BAwYgLi7O5c+dmZmJn376CT/99BO6detmc19tz4nmTDztSM2dT27//v3Q6/VYsGBBo7GtmU/OGUNdS6uqoUMJlLAAghII4LyNRNSwFStW4K9//StmzpyJoUOHQhRFfPPNN5g2bRquXbuGF198Ue4UidzK6H5dseeHq9hy/BJmDL8dCoWAv+/5CaIIDPudDj10dRdEIKK6WlVke/jhhwEADz30kM3+5g7DISKqT0lpKToI1qXDNV26NRlPBACDBg3CwIED8fzzz2Py5MnQaDQue+7ExERptbjGNGfiaUdp7nxyixcvxoEDB+oUw2JiYvDss89i48aNrZ5PzhlKq0zoKliHkyMgGFAomzqEiNqxVatWYc2aNXjuueekfePHj0ffvn2RkpLCIhvRLUZHheCNL87g3NVybD1ZgO4d/fB/R/IBAHNG/E7u9EjCOdncXauKbHIMySGitu/G1cvoAMAAL6j9tXKnQx7im2++wfr16zF//nzMnTsXTzzxBKZOndrgfGFtXXPnk3vnnXewePFiafvy5csYNWoUNm/ejMGDBwNuNp+cvqoaIQKHipKT8bNLm1FQUIAhQ4bU2T9kyBAUFBTIkhOROwv08cLzw3ri7f+exZ8/PgGVQoBFBMb274ro7lzwwF0IzVjBmOTVopkLjx8/DgCIi4tr9OZMBoMBAwYMgCAIUj618vLyMG7cOPj7+0On02HWrFkwGo1OzYeIHKfs2iUAwA2hA8DJiamZYmNjsW7dOhQWFmLNmjW4ePEiRowYgV69eiE1NRUXL16UO0W3FB4ejqioKOl2xx13AAB69eolDX29eT65Y8eOYdeuXbLNJ6evMlkXPQCAIA4nJ+eoXfhAZBvk8W6//Xb83//9X539mzdvxu9+x145RPX53wd6IbZnJxiqLSg3mtG/mwapj/eTOy2ywSKbu2tRTzY5h+TUeumllxAaGooTJ07Y7DebzRgzZgw6d+6Mffv2oaioCFOmTIEoili1apXL8ySilqu8YZ1IvVTZAa4diEZtga+vL6ZMmYIpU6bg559/xoYNG/Dee+8hJSUFI0eOxPbt2+VO0eO4ej65xpRWVSOstsjGlUWJqAmLFi3C008/ja+++gpDhw6FIAjYt28fdu3aVW/xjYgAb5UCH0y9B3t/uAqLKGJ47y7wVnFFUaKWaFGRTe4hOV9++SUyMzORkZGBL7/80ua+zMxMnDlzBvn5+QgNtf7ne/ny5UhMTERqamqD37gbDAYYDAZpW6/XO/ksiKghRv0VAECVN4eKkn169eqF+fPnIywsDC+//DJ27twpd0puLyIiQlqs4WaunE+uMaVV1egslFg3AlmGJ6LGTZgwAQcPHsTbb7+NTz/9FKIoIjIyEocOHcLAgQPlTo/IbXkpFRgZyXbWXbGftftrUVlaziE5v/76K5KSkvD//t//g5+fX537c3JyEBUVJRXYAGDUqFEwGAzIzc1t8HGXLl0KjUYj3cLCwpx2DkTUOHPZNQCASc15H6j1srOzMWXKFISEhOCll17CE088gW+++UbutMhOpVUm6FBTZAvgf/6JqGnR0dH48MMPkZubi6NHj+LDDz9kgY2IPJrA4aJur1V9P2uH5Ozduxdnz57FM888g/feew89evTAI4884vAkRVFEYmIipk2bhpiYmHpjCgsL66x0ptVq4e3tjcLCwgYfe8GCBSgpKZFu+fn5Ds+fiJqp3LpyoNm3k9yZkIfJz8/HG2+8gV69emH48OH4+eefsWrVKly+fBnr1q3DvffeK3eKZCdrT7Yb1g0W2cjp2FeAiIjcEYts7q5Vq4vezJ4hOSkpKVi0aFGjMYcPH8b+/fuh1+uxYMGCRmOFeiapFUWx3v211Go11Gp1s3MmIudRVVmLbIqApldGJKo1cuRI7NmzB507d8Zzzz2H//mf/0Hv3r3lToscrLTK9NtwUf/OcqdDRERE5HL8Csj92VVky87Oxvr165GRkQGlUomJEydi6tSpzT5+5syZmDRpUqMxERERWLx4MQ4cOFCnGBYTE4Nnn30WGzduREhICA4ePGhzf3FxMUwmU50ebkTkntTGYgCAVwA/QFPz+fr6IiMjA2PHjoVSqZQ7HXKS8koDOqJm3lT2ZCMiIiIiN9TiIlt+fj7ef/99vP/++zh//jyGDBmCVatWYeLEifD392/RY+l0Ouh0TfdYeeedd7B48WJp+/Llyxg1ahQ2b96MwYMHAzXzxaWmpqKgoABdu3YFahZDUKvViI6ObulpEpEMfKutQ8F8OnSROxXyIJ9//rncKZALKA03oBIsECFA8GdvVyIi8ny1Cw5x8b32o/a1rm+xqebgnGzur0VFNrmG5ISHh9tsBwQEADVDVbt16wYAiI+PR2RkJBISEpCWlobr169j3rx5SEpKanBlUSJyL4HmEkAA/LTspUJEvzFbRPgZiwA1IPp2hKD0kjslIiIiu5WWlgIAF99rh4qKiqDRaFp8HEts7q9FRTZ3HpKjVCqxbds2TJ8+HUOHDoWvry8mT56M9PR0uVMjomaoMpmhrRkKFqQNkTsdInIjZYZq6GrnYwtgT1dyHvYQ8HxPPPFEs+I++eQTp+dC1JTQ0FDk5+cjMDCw0XnEUdMDKiwsDPn5+W22E0l7OMeSkhKEh4ejY8eOrTqe7ZT7a1GRzV2G5ERERNTbvTI8PBxbt26VJSciss8NfSlChCoAQEAn9mQjot+UVpnQGdbh5IpAvj8QUcNa0zOESC4KhUIamdVcQUFBbbYAVas9nKNCoWjVcSyyuT+7VxclInIEfdGvCAFQDSVUPh3kToeI3EhpVTU6C9YiG/zZk42cr4kOJeTGNmzYIHcKRETUjrWufEpE5GAVNwoBACVCED/dEJGN0qpq6ITalUVZZCMiIqL2SWBHNrfHIhsRuYWqG1cAAGVKDvMgIlulVabferIFcLgouQC/7CEiN6NWq7Fw4UKo1Wq5U3EanmNzsMrm7jhclIjcQnWptchW6aWVOxUicjOlVdXSnGzsyUbOxLluiMhdqdVqpKSkyJ2GU/Ecm8Z2yv2xJxsRuQVzWREAwODdupV2iKjtKq0ycbgoERERtXvsZ+3+WGQjIrcgVF4DAJh92JONiGzpb174gMNFiYiIqJ1iPzb3xyIbEbkFZeV1AIDop5M7FSJyM2WVBmhRZt3w7yx3OkRERESy4HBR98ciGxG5BW+jtcimCGCRjYhsmcuKoKhdTsuXQ8rJ+UQOyCEiIjfEIpv7Y5GNiNyCr8k6FMwrkPMtEdEtKmrmbFQFAUqu2UTOww8vRETk3thOuTsW2YjILQSYrUU2tYY92YjIllBZU2RTsxcbORc/upAjfPXVVxg3bhxCQ0MhCAI+/fRTm/tFUURKSgpCQ0Ph6+uLBx54AKdPn7aJMRgMeOGFF6DT6eDv749HH30UFy9etIkpLi5GQkICNBoNNBoNEhIScOPGDZuYvLw8jBs3Dv7+/tDpdJg1axaMRqNNzMmTJxEXFwdfX1/cdttteP311yGK/GtwlpSUFAiCYHMLCQlp9Jjs7GxER0fDx8cHPXv2xLvvvlsnJiMjA5GRkVCr1YiMjMSWLVuceBZNc8Z5nj59GhMmTEBERAQEQcDKlSudfBaNc8Y5rlu3DsOGDYNWq4VWq8WIESNw6NAh6X72s3Z/LLIRkVvQWKwrB/prG2+YiKj9UVVZh5NzYRRyFYEfY8gO5eXluOuuu/C3v/2t3vvfeustrFixAn/7299w+PBhhISEYOTIkSgtLZVi5syZgy1btmDTpk3Yt28fysrKMHbsWJjNZilm8uTJOH78OHbs2IEdO3bg+PHjSEhIkO43m80YM2YMysvLsW/fPmzatAkZGRmYO3euFKPX6zFy5EiEhobi8OHDWLVqFdLT07FixQqnXR8C+vbti4KCAul28uTJBmPPnz+PRx55BMOGDcOxY8fw8ssvY9asWcjIyJBicnJy8PTTTyMhIQEnTpxAQkICJk6ciIMHD7rojOrn6POsqKhAz5498eabbzZZzHIVR5/j3r178cwzz2DPnj3IyclBeHg44uPjcUlvcdEZkd1EslFSUiICEEtKSuROhajdqKwyiObXNKK4MEjUX7sodzptHt/nPJOzXretW7eK99xzj+jj4yN26tRJfPzxx23u/+WXX8SxY8eKfn5+YqdOncQXXnhBNBgMLs195dL5orgwSCxa90Srjqf2p7W/c78svEMUFwaJ53J3OS03alhbbJ8AiFu2bJG2LRaLGBISIr755pvSvqqqKlGj0YjvvvuuKIqieOPGDdHLy0vctGmTFHPp0iVRoVCIO3bsEEVRFM+cOSMCEA8cOCDF5OTkiADE77//XhRFUdy+fbuoUCjES5cuSTEfffSRqFarpWu8evVqUaPRiFVVVVLM0qVLxdDQUNFisTTrHNvi6+ZMCxcuFO+6665mx7/00kvinXfeabPvT3/6k3jvvfdK2xMnThQffvhhm5hRo0aJkyZNckDGreOM87xZ9+7dxbffftvuPO3h7HMURVGsrq4WAwMDxY2P+VjbpzcG2JUztU5L3ufYk42IZFdy/VdpUvMADVcOJHKVjIwMJCQk4A9/+ANOnDiBb775BpMnT5bub04vCFfwMRVbf+Dqw+Rk7L9Gznb+/HkUFhYiPj5e2qdWqxEXF4f9+/cDAHJzc2EymWxiQkNDERUVJcXk5ORAo9Fg8ODBUsy9994LjUZjExMVFYXQ0FApZtSoUTAYDMjNzZVi4uLioFarbWIuX76MCxcu1HsOBoMBer3e5kYt8+OPPyI0NBQ9evTApEmTcO7cuQZjc3JybH4XUPMaHTlyBCaTqdGY2t8FuTj6PN2Rs8+xoqICJpMJHX2tLRTnDnV/LLIRkez0xVcBAKXwg6Dyljsdonahuroas2fPRlpaGqZNm4Y77rgDvXv3xpNPPinFZGZm4syZM/jwww8xcOBAjBgxAsuXL8e6detc+qHKr9o6x5AyoJPLnpOIyBkKCwsBAMHBwTb7g4ODpfsKCwvh7e0NrVbbaEyXLnUXi+rSpYtNzK3Po9Vq4e3t3WhM7XZtzK2WLl0qzQOn0WgQFhbWwqvQvg0ePBgffPABdu7ciXXr1qGwsBBDhgxBUVFRvfENvUbV1dW4du1aozENvYau4IzzdDeuOMf58+fjtttuw4ieNQs/cb5Et8ciGxHJruKGtVEpEwLlToWo3Th69CguXboEhUKBgQMHomvXrhg9erTN5NvN6QVRH0f2cqg2WxBoKQEAeAVx9WEiahsEwbbfpCiKdfbd6taY+uIdEVO76EFD+SxYsAAlJSXSLT8/v9G8ydbo0aMxYcIE9OvXDyNGjMC2bdsAABs3bmzwmOa8Rq35nXImZ52nO3H2Ob711lv46KOP8Mknn8BHxZ5snoJFNiKSXZXe2pOtQhUkdypE7UbtcIaUlBS8+uqr2Lp1K7RaLeLi4nD9unWhgeb0gqiPI3s5lBmq0RHWycC9gzicnIg8W+1k7be+h165ckV6vw0JCYHRaERxcXGjMb/++mudx7969apNzK3PU1xcDJPJ1GjMlStXgHp629VSq9UICgqyuVHr+fv7o1+/fvjxxx/rvb+h10ilUqFTp06NxjT0GsrBEefp7hx5junp6ViyZAkyMzPRv39/p+ZNjsUiGxHJzlRm/UBvUGnkToXI49W3nPyttyNHjsBisa5S9corr2DChAmIjo7Ghg0bIAgCPv74Y+nxmtML4laO7OVQWlUNrWAtsqkCWGQjF3HTXhPk+Xr06IGQkBBkZWVJ+4xGI7KzszFkyBAAQHR0NLy8vGxiCgoKcOrUKSkmNjYWJSUlOHTokBRz8OBBlJSU2MScOnUKBQUFUkxmZibUajWio6OlmK+++gpGo9EmJjQ0FBEREU69FmRlMBjw3XffoWvXrvXeHxsba/O7gJrXKCYmBl5eXo3G1P4uuANHnKe7c9Q5pqWl4Y033sCOHTsQExNjE8/Wyf2xyEZEsjOXW+ctMKlZZCPPZTAYMGDAAAiCgOPHj9vcl5eXh3HjxsHf3x86nQ6zZs2y+UDjSDNnzsR3333X6C0qKkr6D2BkZKR0rFqtRs+ePZGXlwc0sxdEfRzZy0FfZULHmiIb/Dzjm2zyXByGQ45QVlaG48ePS23B+fPncfz4ceTl5UEQBMyZMwdLlizBli1bcOrUKSQmJsLPz09aeEaj0WDq1KmYO3cudu3ahWPHjuH3v/+9NCQNAPr06YOHH34YSUlJOHDgAA4cOICkpCSMHTsWvXv3BgDEx8cjMjISCQkJOHbsGHbt2oV58+YhKSlJel+ePHky1Go1EhMTcerUKWzZsgVLlixBcnKy2w7R83Tz5s1DdnY2zp8/j4MHD+LJJ5+EXq/HlClTgJovqp577jkpftq0afjll1+QnJyM7777DuvXr8c///lPzJs3T4qZPXs2MjMzsWzZMnz//fdYtmwZ/vvf/2LOnDmynCOcdJ5Go1H62zIajbh06RKOHz+On376qc2c41tvvYVXX30V69evR0REBAoLC1FYWIgyY237xHbK7blkvVMPwiWoiVxv7+oXRHFhkHh09R/kTqVd4Pucc8yaNUscPXq0CEA8duyYtL+6ulqMiooShw8fLh49elTMysoSQ0NDxZkzZ7bo8R39upWUlIhqtVr8xz/+Ie0zGo1ily5dxPfee08URVHcvn27qFAoxMuXL0sxmzZtEtVqdYvysCf3/T9dEyte04niwiBRvH6+xcdT+9Ta37n8hb8TxYVB4rmju52WGzWsrbRPe/bsEWs+CdvcpkyZIoqiKFosFnHhwoViSEiIqFarxfvvv188efKkzWNUVlaKM2fOFDt27Cj6+vqKY8eOFfPy8mxiioqKxGeffVYMDAwUAwMDxWeffVYsLi62ifnll1/EMWPGiL6+vmLHjh3FmTNnilVVVTYx3377rThs2DBRrVaLISEhYkpKimixWJp9vm3ldXOVp59+Wuzatavo5eUlhoaGik888YR4+vRp6f4pU6aIcXFxNsfs3btXHDhwoOjt7S1GRESIa9asqfO4H3/8sdi7d2/Ry8tLvPPOO8WMjAyXnE9DnHGe58+fr/dv69bHcRVnnGP37t3rPceFcd6iuDBIzHu9r8vOj37Tkvc5QRS5PMXN9Ho9NBoNSkpKOL8AkYt8vXIKht34FEcjkjAoMV3udNo8vs853pdffonk5GRkZGSgb9++OHbsGAYMGCDdN3bsWOTn50sLCGzatAmJiYm4cuVKs18DZ7xuc+bMwX/+8x+sX78e3bt3R1paGr744gt8//330Gq1MJvNGDBgAIKDg5GWlobr168jMTERjz32GFatWtXs57En910nzuGhLQOtGwsuAmoukEJNa+3v3MWUO9ANv+L8+E/RY+Bwp+ZIdbF98kx83YhcIMU64idfGYawv56SO5t2pyXvcyqXZUVE1ACV8QYAQOnfUe5UiFrs119/RVJSEj799FP4+fnVub+pFTqHD6//g7zBYIDBYJC27VmhsyFpaWlQqVRISEhAZWUlBg8ejN27d0Or1QIAlEoltm3bhunTp2Po0KHw9fXF5MmTkZ7uumK4UW9dfdgEL3h5B7jseam94zA5IiJyP2yd3B+LbEQkO29jCQDAK4DzLZFnEUURiYmJmDZtGmJiYnDhwoU6Mfas0Llo0SKn5F3Ly8sL6enpjRbNwsPDsXXrVqfm0RhTqXWVuzKVBlrOD0ROJs3Jxl81IiJyQ5w71P1x4QMikp2/2dpDxztIJ3cqREALVuhctWoV9Ho9FixY0Ojjyb1CpycTaxZGqVR1kDsVIiIiIpmxyObu2JONiGQXYCkFBMA3iD3ZyD3MnDkTkyZNajQmIiICixcvxoEDB6BWq23ui4mJwbPPPouNGzciJCQEBw8etLm/uSt03vq47ZFYYS2yGby1cqdCRERERNQoFtmISFbVZguCUAYA8NN0ljsdIgCATqeDTtd0z8p33nkHixcvlrYvX76MUaNGYfPmzRg8eDAAIDY2FqmpqSgoKEDXrl0BAJmZmVCr1YiOjnbiWbQNispiAIBJzZ5sREREROTeWGQjIlnpK6rQUagAAARqu8idDlGLhIeH22wHBFgn5u/Vqxe6desGAIiPj0dkZCQSEhKkFTrnzZuHpKQkrsLWDMqahVFEH/ZkI1fipGxEROR+OCeb++OcbEQkq9Ib16SfVX78EE1tT+0KnT4+Phg6dCgmTpyIxx57zKUrdHoyVc3CKPBhTzYiIiIicm/syUZEsiq/YV05sBR+CFTyLYk8W0REBESx7jeMcq/Q6cnUJmuRTWARnoiIiNo59mRzf+zJRkSyqtJbJzUvUwTKnQoRuSHf6lIAgMq/o9ypEBEREclKqOfLXHIvLLIRkayMpdbhohVKjdypEJEb8jVbi2xeASyyEREREZF7Y5GNiGRVXXYdAGBQcQJ4IqorQLQW2XyCml7tlchhuO4BERG5IWO1We4UqAksshGRrCwV1iKb0Zs92YjIVpXJjCCUAwB8gzrJnQ61A7Vz3bDGRkRE7ojtk/tjkY2IZCVUWotsZh9Oak5EtkorTeiAMgCAH3uyERERUTsnCJyTzd2xyEZEslJU3QAAWHw6yJ0KEbmZstIbUAkWAICCq4sSERERkZtjkY2IZKUylgAAFL6c1JyIbFWUWBdGMcAL8PKVOx1qTwQOyCEiIqKWY5GNiGSlNlmLbMoAzrdERLYMNasPlwmBLHqQS9TOyUZEROSO2E65PxbZiEhWfmY9AMCbRTYiuoWprBgAUKEMkDsVIiIiIqImschGRLLyrymyqblyIBHdwlRWBACoVAbJnQoRERGR7NiTzf2xyEZEsgoQywEAfkGck42IbFkqrAujGL1YZCMiIiLi5Bnuj0U2IpJNlbEaAagAAAR0YE82IrIlVF4HAJi8NXKnQu0OP8YQERFRy7HIRkSyKdXfgFKwdnn2D2SRjYhsCQZrTzazuoPcqVA7wdIaERG5Mw4XdX8sshGRbEpLrPMtmaCEwttX7nSI2p2zZ89i/Pjx0Ol0CAoKwtChQ7Fnzx6bmLy8PIwbNw7+/v7Q6XSYNWsWjEajS/JTGqyrD4s+LLKRq7HcRkRE7odFNvfHIhsRyaZCbx0KVg5/QOAHGiJXGzNmDKqrq7F7927k5uZiwIABGDt2LAoLCwEAZrMZY8aMQXl5Ofbt24dNmzYhIyMDc+fOdUl+XkZrkQ2+Wpc8HxEREZE74ycm96eSOwEiar8qa4psFcoAsJ8KkWtdu3YNP/30E9avX4/+/fsDAN58802sXr0ap0+fRkhICDIzM3HmzBnk5+cjNDQUALB8+XIkJiYiNTUVQUEtW5Dgu4OZCPD3a3a8xlAAAFD6schGLsYvfoiIyA2xJ5v7Y5GNiGRjKLfOt2RQ+sudClG706lTJ/Tp0wcffPABBg0aBLVajffeew/BwcGIjo4GAOTk5CAqKkoqsAHAqFGjYDAYkJubi+HDh9f72AaDAQaDQdrW6/UAgD67/wdB6pYXL1QBXH2YiKitKTdU49uLJbinR0coFSxsEzWHGq6ZsoNaj0U2IpKNqabIZlQFyp0KUbsjCAKysrIwfvx4BAYGQqFQIDg4GDt27ECHDta+pYWFhQgODrY5TqvVwtvbWxpSWp+lS5di0aJFdfbnCbchUKFsUZ4l3iG4/e74Fh1D1HrsIUDt0+rVq5GWloaCggL07dsXK1euxLBhw5z6nH94/zAOnb+Ovzx8J/73gV5OfS6itiJIqJQ7BWqCRxXZtm3bhtdffx3ffvst/P39cf/99+OTTz6R7s/Ly8OMGTOwe/du+Pr6YvLkyUhPT4e3t7eseRNR/SwV1iJbtReLbESOkpKSUm+B62aHDx9GdHQ0pk+fji5duuDrr7+Gr68v/vGPf2Ds2LE4fPgwunbtCtQU424limK9+2stWLAAycnJ0rZer0dYWBjC5x9s8RBTIiJyrs2bN2POnDlYvXo1hg4divfeew+jR4/GmTNnEB4e7rTnPXTeOm3IR4fyWGQjaoGClNtxwzsY5b5dUR3YDYoOYfDp2A0+HYIRoA1GB10IfP01EBScgl8OHlNky8jIQFJSEpYsWYIHH3wQoiji5MmT0v21kzN37twZ+/btQ1FREaZMmQJRFLFq1SpZcyei+olVNSsHqvmhm8hRZs6ciUmTJjUaExERgd27d2Pr1q0oLi6WCl+rV69GVlYWNm7ciPnz5yMkJAQHDx60Oba4uBgmk6lOD7ebqdVqqNVqB50RERE504oVKzB16lQ8//zzAICVK1di586dWLNmDZYuXer05zdb2IOUqCk/W7qil8I6V21XXEVX41XAeAooAXCxbrxB9MINIQgVykAYFH4wKf1gUvnDrPKHxdsfFq8AQB0IhZcaguq3m9LbBwovNRQqXyi9vKH09oHS2wdeKi8IShUUCiUEhQoKpQIKpQpKhQqCUgmlUiXtV6qscUqlqma/otEvZ9sajyiyVVdXY/bs2UhLS8PUqVOl/b1795Z+bu3kzA3NG0NEzicYrH9vLLIROY5Op4NOp2syrqKiAgCguOVbToVCAYvFAgCIjY1FamoqCgoKpJ5tmZmZUKvV0rxtRG1T+/kwQO2b0WhEbm4u5s+fb7M/Pj4e+/fvr/cYR31++p1wEfNU/4eA8kqcWurVqscgai+6C9YRQK+Y/ge/H/8Iyq+ch+l6HhQl+fCpuAw/YxECzSXoIJbARzBBLZgQjCLAXASYAZjkPgPAIlrbVhGAiNqfb17KQbDZFmu2cdP2rceIEKTFim59XNz0uDfTK4LQ/bXTTjhDK48osh09ehSXLl2CQqHAwIEDUVhYiAEDBiA9PR19+/YF7JicuaF5Y4jI+RTGUgCA4KOROxWidic2NhZarRZTpkzBa6+9Bl9fX6xbtw7nz5/HmDFjgJoPWZGRkUhISEBaWhquX7+OefPmISkpicM+qU3iqm3U3ly7dg1ms7lO7+Tg4OAG59501OenPyq3YpTyiHXD0FQ0UTtXUyc6aemBPveMbDBMtFhQXq5HybVClBUXolJfBHNVKaorS2GpKgUMZRCNZVAYy6AwlUOwGKA0G6GwGKEUTVBajFCJJqgsJqhE689eMEEJMxSwQCFaoITF+jOsPyuF5rWdCps4+dpb0eLcx/eIItu5c+eAmnlmVqxYgYiICCxfvhxxcXE4e/YsOnbs2OrJmRuaN4aInM+r2lpkU/iyyEbkajqdDjt27MArr7yCBx98ECaTCX379sVnn32Gu+66CwCgVCqxbds2TJ8+HUOHDrWZ75SIiNqOW4dyNTb3pqM+P/kLVQCAHHMkvAb/ocXHE7UnH+z/BQViR3wr9mw0TlAo4B/YAf6BHYAed7okN9FigWixwGyphrm6GhZLNcxmCyxmM0RzNcwWM0RRhAgRgghAFK29zkRr3zNRtEAUYS28WX+4aV9NvLRhgVgzxFyEKFXMRFG8Kd5S81g3l/Ju6i+nUMGZ69bLWmRr7uTMtcNWXnnlFUyYMAEAsGHDBnTr1g0ff/wx/vSnPwGtnJyZ88YQyUddU2RT+nWQOxWidikmJgY7d+5sNCY8PBxbt251WU5E7qAdTR1D7ZxOp4NSqazTKeHKlSsNzr3pqM9PXQK8gEpA0X8CYsb+0e7HI2rLnty3Te4UGiQoFBAUCiigghfXnJS3yNbcyZlLS60fxCMjI6X9arUaPXv2RF5eHgC0enJmIpKPj7kcAODtzyIbERG5E1bZqH3w9vZGdHQ0srKy8Pjjj0v7s7KyMH78eKc+twLWjhQqpdKpz0NE5EqyFtmaOzlzdHQ01Go1fvjhB9x3330AAJPJhAsXLqB79+4AJ2cm8kh+ljJAANQBWrlTISIiImqXkpOTkZCQgJiYGMTGxmLt2rXIy8vDtGnTnPq8itphXgKLbETUdnjEnGxBQUGYNm0aFi5ciLCwMHTv3h1paWkAgKeeegrg5MxEHsdiEeEP6+qGvoHOHBVPRETUPOy/Ru3R008/jaKiIrz++usoKChAVFQUtm/fLnVmcBYBZuu/t6xyTUTkyTyiyAYAaWlpUKlUSEhIQGVlJQYPHozdu3dDq7X2gOHkzESepcxYjcCaIptfEHuyEREREcll+vTpmD59ukufU6idpZw92YioDfGYIpuXlxfS09MbLZpxcmYiz6Evq0A3wbpeuzqAPdmIiIiI2hNBtPZkg4JFNiJqO9g3l4hkUVF647cNdaCcqRAREdni8qJETle78IHAvzciakM8picbEbUtlfrr1n/hA1+ll9zpENll27ZteP311/Htt9/C398f999/Pz755BPp/ry8PMyYMQO7d++2mc7A27t9rHMu1gwJ0uv1cqdC7UTt71rt7x4RuR+hZuEDKPiRlIjaDr6jEZEsDGXFAIAKhT985U6GyA4ZGRlISkrCkiVL8OCDD0IURZw8eVK632w2Y8yYMejcuTP27duHoqIiTJkyBaIoYtWqVbLm7iqlpaUAgLCwMLlToXamqKgIGo2m2fECWJQjchWhticbFz4gojaERTYikoWh3Fpkq1L4y50KUatVV1dj9uzZSEtLw9SpU6X9vXv3ln7OzMzEmTNnkJ+fj9DQUADA8uXLkZiYiNTU1AZXwDYYDDAYDNK2J/cCCw0NRX5+PgIDA1s0LEiv1yMsLAz5+flcKbwevD4NKykpQXh4ODp25JyfRO5KUduTjQsfEFEbwiIbEcmiusI6J1uVKkDuVIha7ejRo7h06RIUCgUGDhyIwsJCDBgwAOnp6ejbty8AICcnB1FRUVKBDQBGjRoFg8GA3NxcDB8+vN7HXrp0KRYtWuSyc3EmhUKBbt26tfr4oKAgFpEawevTMEWre8hwjigiZ6vtyQaBPdmIqO3gOxoRycJSWQIAMKm46AF5rnPnzgEAUlJS8Oqrr2Lr1q3QarWIi4vD9evWeQcLCwsRHBxsc5xWq4W3tzcKCwsbfOwFCxagpKREuuXn5zv5bIiIiFyndk42hZI92Yio7WCRjYhkIdYU2cxeLLKR+0lJSYEgCI3ejhw5AovF+gHhlVdewYQJExAdHY0NGzZAEAR8/PHH0uPVN0RSFMVGh06q1WqphxJ7KhG5CudkI3KVGwE98aPydqgDOKybiNoODhclInkYrPNLWdQsHJD7mTlzJiZNmtRoTEREhDShf2RkpLRfrVajZ8+eyMvLAwCEhITg4MGDNscWFxfDZDLV6eFGttRqNRYuXAi1Wi13Km6J16dhvDZE7u/uFz9uRhQRkWdhkY2IZKGoKbKJLLKRG9LpdNDpdE3GRUdHQ61W44cffsB9990HADCZTLhw4QK6d+8OAIiNjUVqaioKCgrQtWtXoGYxBLVajejoaCefiWdTq9VISUmROw23xevTMF4bIiIikgOLbEQkC5XJ2gNI8NXInQpRqwUFBWHatGlYuHAhwsLC0L17d6SlpQEAnnrqKQBAfHw8IiMjkZCQgLS0NFy/fh3z5s1DUlISh4ASuSuue0BEREStwCIbEcnCq9paZFOwyEYeLi0tDSqVCgkJCaisrMTgwYOxe/duaLVaAIBSqcS2bdswffp0DB06FL6+vpg8eTLS09PlTp2IiIiIiByIRTYikoW6ugwA4OXXQe5UiOzi5eWF9PT0Rotm4eHh2Lp1q0vzIqKWYwc2IiIisgdXFyUiWfhaygEA3gFauVMhIiIiIiIishuLbEQkC7+aIptPAHuyEbUHKSkpEATB5hYSEtLoMdnZ2YiOjoaPjw969uyJd999t05MRkYGIiMjoVarERkZiS1btjjxLJzDGdfm9OnTmDBhAiIiIiAIAlauXOnks3AeZ1yfdevWYdiwYdBqtdBqtRgxYgQOHToEQKyJYJ82IiIiajkW2YjI5UxmCwJgLbL5BnaUOx0icpG+ffuioKBAup08ebLB2PPnz+ORRx7BsGHDcOzYMbz88suYNWsWMjIypJicnBw8/fTTSEhIwIkTJ5CQkICJEyfi4MGDLjojx3H0tamoqEDPnj3x5ptvNlmQ8gSOvj579+7FM888gz179iAnJwfh4eGIj49Hgb7aRWdEREREbRHnZCMilyurNCEQFQAAvyAW2YjaC5VK1eyCz7vvvovw8HCpB1afPn1w5MgRpKenY8KECQCAlStXYuTIkViwYAEAYMGCBcjOzsbKlSvx0UcfOfFMHM/R1+buu+/G3XffDQCYP3++EzN3DUdfn3/96182x6xbtw7/+c9/8PV5A/rdBQjsyEZEREStwJ5sRORyZWWl8BbMABc+IGpXfvzxR4SGhqJHjx6YNGkSzp0712BsTk4O4uPjbfaNGjUKR44cgclkajRm//79TjoD53H0tWlrnH19KioqYDKZ0MGX/zUmIiKi1uP/JIjI5cpLrwMAzFAA3gFyp0NELjB48GB88MEH2LlzJ9atW4fCwkIMGTIERUVF9cYXFhYiODjYZl9wcDCqq6tx7dq1RmMKCwudeCaO54xr05a44vrMnz8ft912G+J6+jjlHIiIiKh94HBRInK5ytJiAEAFfBGoYK2fqD0YPXq09HO/fv0QGxuLXr16YePGjUhOTq73GOGWMXuiKNbZX1/MrfvcnbOuTVvh7Ovz1ltv4aOPPsLevXvh88nY2kdw6DkQERFR+8BPt0TkcoYya5GtUuEvdypEJBN/f3/069cPP/74Y733h4SE1OmRduXKFahUKnTq1KnRmFt7MXkaR1ybtsyR1yc9PR1LlixBZmYm+vfv79S8iYiIqO1jkY2IXM5UfgMAUKnkUFGi9spgMOC7775D165d670/NjYWWVlZNvsyMzMRExMDLy+vRmOGDBnixMydzxHXpi1z1PVJS0vDG2+8gR07diAmJgYAIEB0cvZERETUlrHIRkQuZ66wFtmMKhbZiNqLefPmITs7G+fPn8fBgwfx5JNPQq/XY8qUKUDNyqDPPfecFD9t2jT88ssvSE5OxnfffYf169fjn//8J+bNmyfFzJ49G5mZmVi2bBm+//57LFu2DP/9738xZ84cWc6xtZxxbYxGI44fP47jx4/DaDTi0qVLOH78OH766SdZztEezrg+b731Fl599VWsX78eERERKCwsRGFhIcqMFlnOkYiIiNoGzslGRC5nriwBAJi8guROhYhc5OLFi3jmmWdw7do1dO7cGffeey8OHDiA7t27AwAKCgqQl5cnxffo0QPbt2/Hiy++iL///e8IDQ3FO++8gwkTJkgxQ4YMwaZNm/Dqq6/ir3/9K3r16oXNmzdj8ODBspxjaznj2ly+fBkDBw6UttPT05Geno64uDjs3bvXxWdoH2dcn9WrV8NoNOLJJ5+0ea6X4gKx7AHOx0ZEREStI4i1M8ESAECv10Oj0aCkpARBQSwAEDnDrnUv46FLf8fJTqPR74VNcqfT7vB9zjPxdSNyvuspYegIPfIm7UL4nTFyp9Pu8H3OM/F1I3K+iPnbpJ8vvDlG1lzao5a8z3G4KBG5nMKkBwBYvAPlToWIiIiIiIjIIVhkIyKXUxhKAQCij0buVIiIiG5SO8CDQ0apdVJTUzFkyBD4+fmhQ4cO9cbk5eVh3Lhx8Pf3h06nw6xZs2A0Gm1iTp48ibi4OPj6+uK2227D66+/jlsHIGVnZyM6Oho+Pj7o2bMn3n333TrPlZGRgcjISKjVakRGRmLLli11YlavXo0ePXrAx8cH0dHR+Prrr+2+DkRE7RWLbETkcl7V1iKb4MMhBURERNR2GI1GPPXUU/jf//3feu83m80YM2YMysvLsW/fPmzatAkZGRmYO3euFKPX6zFy5EiEhobi8OHDWLVqFdLT07FixQop5vz583jkkUcwbNgwHDt2DC+//DJmzZqFjIwMKSYnJwdPP/00EhIScOLECSQkJGDixIk4ePCgFLN582bMmTMHr7zyCo4dO4Zhw4Zh9OjRNvMcEhFR83HhAyJyOW+Ttcim9GVPNiIicj8ie7JRKy1atAgA8P7779d7f2ZmJs6cOYP8/HyEhoYCAJYvX47ExESkpqYiKCgI//rXv1BVVYX3338farUaUVFROHv2LFasWIHk5GQIgoB3330X4eHhWLlyJQCgT58+OHLkCNLT06VFPlauXImRI0diwYIFQM1KvNnZ2Vi5ciU++ugjAMCKFSswdepUPP/889IxO3fuxJo1a7B06VIXXDEioraFPdmIyOV8zGUAAKVf/cMoiIiIiNqinJwcREVFSQU2ABg1ahQMBgNyc3OlmLi4OKjVapuYy5cv48KFC1JMfHy8zWOPGjUKR44cgclkajRm//79QE2vu9zc3Dox8fHxUkx9DAYD9Hq9zY2IiKxYZCMil/OxlAMAvPxZZCMiIvfB/mvkbIWFhQgODrbZp9Vq4e3tjcLCwgZjarebiqmursa1a9cajal9jGvXrsFsNjcaU5+lS5dCo9FIt7CwsBZfByKitopFNiJyOT/RWmRTB2jlToWIiIioUSkpKRAEodHbkSNHmv14glC3nCuKos3+W2NqFz1wRMyt+5oTc7MFCxagpKREuuXn5zcYS0TU3nBONiJyKVEUESiWAwKLbEREROT+Zs6ciUmTJjUaExER0azHCgkJsVl4AACKi4thMpmkHmUhISF1epJduXIFuKlHW0MxKpUKnTp1ajSm9jF0Oh2USmWjMfVRq9U2Q1mJiOg3LLI5wI1rhTj3/h/rv1MQINyy3HadEDR+f1OaPr7h++1+7ibOrbHnbt7zN3F8o3c797lhz7mLzYxrKKbJQ5q6bmKjEbXXpuEYsd4fbz2+oZBIoRIA4KvRNZonERGRPDhwlH6j0+mg0znm/yyxsbFITU1FQUEBunbtCtQshqBWqxEdHS3FvPzyyzAajfD29pZiQkNDpWJebGwsvvjiC5vHzszMRExMDLy8vKSYrKwsvPjiizYxQ4YMAQB4e3sjOjoaWVlZePzxx6WYrKwsjB8/3iHnS0TU3rDI5gCGqnIMKsuWOw0ij3IdQdAEdZY7DSIiIiKHycvLw/Xr15GXlwez2Yzjx48DAG6//XYEBAQgPj4ekZGRSEhIQFpaGq5fv4558+YhKSkJQUFBAIDJkydj0aJFSExMxMsvv4wff/wRS5YswWuvvSYN45w2bRr+9re/ITk5GUlJScjJycE///lPadVQAJg9ezbuv/9+LFu2DOPHj8dnn32G//73v9i3b58Uk5ycjISEBMTExCA2NhZr165FXl4epk2b5vJrR0TUFrDI5gABmk442GfBTR2bbuoFJNbuaeIb0UbmPWjW8fXcf/NDNt1Xyo7nF4RGj2469ybUe22EBn6u5/mbuLbNSMDmKWweTRDqv/Y2Pwh199f8XJubUP/RTTzvb3tt77s5rP5zF4R6gm3vsHnkhi5hg49v83j1x3S9czCUKr4FERGR+7C3hz/Ra6+9ho0bN0rbAwcOBADs2bMHDzzwAJRKJbZt24bp06dj6NCh8PX1xeTJk5Geni4do9FokJWVhRkzZiAmJgZarRbJyclITk6WYnr06IHt27fjxRdfxN///neEhobinXfewYQJE6SYIUOGYNOmTXj11Vfx17/+Fb169cLmzZsxePBgKebpp59GUVERXn/9dRQUFCAqKgrbt29H9+7dXXC1iIjaHkEUmxzz1q7o9XpoNBqUlJRI3yYREbUlfJ/zTHzdiJzvRspt6IAy5D2zF+G9B8qdTrvD9znPxNeNyPki5m+Tfr7w5hhZc2mPWvI+x9VFiYiIiIhuZncveCIiImqPWGQjIiIiIiIiIiKyE4tsREREREREREREdmKRjYiIiIiICx8QERGRnVhkIyIiIiIiIiIishOLbERERHY4e/Ysxo8fD51Oh6CgIAwdOhR79uyxicnLy8O4cePg7+8PnU6HWbNmwWg0ypYzERERERE5HotsREREdhgzZgyqq6uxe/du5ObmYsCAARg7diwKCwsBAGazGWPGjEF5eTn27duHTZs2ISMjA3PnznVJfr8UlePjI/mwWDgMjoiIiIjImVRyJ0BEROSprl27hp9++gnr169H//79AQBvvvkmVq9ejdOnTyMkJASZmZk4c+YM8vPzERoaCgBYvnw5EhMTkZqaiqCgIKfmuGD536CEBecOBuGRqK5OfS4iT9dTNAOC3FkQERGRp2KRjYiIqJU6deqEPn364IMPPsCgQYOgVqvx3nvvITg4GNHR0QCAnJwcREVFSQU2ABg1ahQMBgNyc3MxfPjweh/bYDDAYDBI23q9vlU5rvNaDn/BAFwFsKcZBxC1ZzUFNkGhlDsTIiIi8kAsshEREbWSIAjIysrC+PHjERgYCIVCgeDgYOzYsQMdOnQAABQWFiI4ONjmOK1WC29vb2lIaX2WLl2KRYsW2Z3j92I4fETr/G8+XiwcEDXlesAdiOnZV+40iIiIyAN5TJHt7Nmz+POf/4xvvvkGRqMR/fr1w+LFi216AOTl5WHGjBnYvXs3fH19MXnyZKSnp8Pb21vW3ImIyLOkpKQ0WeA6fPgwoqOjMX36dHTp0gVff/01fH198Y9//ANjx47F4cOH0bWrdXimINQdfyaKYr37ay1YsADJycnStl6vR1hYWIvPZYLReh7LJvTD03eHt/h4ovaml9wJEBERkcfymCLbmDFjcMcdd0gFtJUrV2Ls2LH4+eefERISIk0s3blzZ+zbtw9FRUWYMmUKRFHEqlWrWvx81dXVqK6urrNfEAQolUqbuIY4KxYAVCpVq2LNZjNEseHJr90hVqlUSh88nRVrsVhgsVjcOlahUEChULhNrCiKMJvNbh1789+Rs2Ih09+9I98jmjqWgJkzZ2LSpEmNxkRERGD37t3YunUriouLpbnVVq9ejaysLGzcuBHz589HSEgIDh48aHNscXExTCZTnR5uN1Or1VCr1Q46o/oLfURERERE5DgeUWRz5sTSDc1588UXX8DPz69OfEhICIYNGyZtf/755w1+OO/cuTMeeOABaXvbtm0wGo31xmq1WowYMULa3rlzJyoqKuqNDQoKwqhRo6TtXbt2NThXj5+fH8aMGSNt79mzB8XFxfXGent7Y/z48dL2119/jatXr9Ybq1Qq8cQTT0jb+/fvb3TY01NPPSX9fOjQIVy8eLHB2Mcff1wqEOTm5uKXX35pMPbRRx+VPoSeOHECP//8c4OxjzzyCPz9/QEAJ0+exNmzZxuMjY+Ph0ajAQB89913OHPmTIOxDz30EDp27AgA+PHHH/Htt982GBsXF4cuXboAAM6dO4djx441GHvfffdJvWDy8vJw+PDhBmPvvfdeqYfLpUuXcODAgQZj7777bkRERAAAfv31V+zbt6/B2IEDB+L2228HAFy9ehXZ2dkNxvbv3x+9e/cGagoIu3btajA2MjISfftah+Lo9XpkZmY2GHvHHXfgrrvuAgBUVFRg+/btDcb26tULgwYNAgAYjUZ8/vnnDcZ2794d99xzD1BToN2yZUuDsd26dUNsbKy03VisJ7xHNHQc/Uan00Gn0zUZV3stawvBtRQKhVTAjo2NRWpqKgoKCqS/6czMTKjVamneNldQsMhGRERERORUimbEyO7miaXLy8tRXV3d4omlG7J06VJoNBrp1pqhOERE1D7FxsZCq9ViypQpOHHihDS1wfnz56UvOOLj4xEZGYmEhAQcO3YMu3btwrx585CUlOT0lUVvFt1d67LnIiIiIiLHeWyAtc4xLY6TGrg7QWxsfJ0buXTpEsaPH4+jR49KE0tv27YNAwYMAAD88Y9/xIULF+r0iFGr1Xj//ffxzDPP1Pu49fVkCwsLQ1FRUb0ffjxhKFhjsRwuyuGiHC5qXyzawHBRvV6PTp06oaSkxKVFnrbqyJEjeOWVV3DkyBGYTCb07dsXr732GkaPHi3F5OXlYfr06XXmDG3JcFC9Xg+NRtPi162ozICiciPuCA5s8bkREblSa9/nSF583Yicz1htwanLJbirWwcoFRyd4GoteZ+TdbioO0ws3dCcNyqVyuZDakOaE+NOsTd/SG/PsTcXbhjbvFhBEJr9u9aWY+Emf8v2xLbkWGpaTEwMdu7c2WhMeHg4tm7d6rKcbtYpQI1OAY6b242IiIiIXMtbpcCgcI5K8ASyftJyh4mliYiIiIiIiIiI7CVrka0tTixNRERERERERETtj0csfOBJE0sTEREREREREVH74xFFNp1Ohx07dqCsrAwPPvggYmJisG/fPnz22We46667gJr5uLZt2wYfHx8MHToUEydOxGOPPYb09HS50yciIiIiIiIiojbOY2a/dveJpYmIiIiIiIiIqP3yiJ5sRERERERERERE7oxFNiIiIiIiIiIiIjuxyEZERERERERERGQnFtmIiIiIiIiIiIjsxCIbERERERERERGRnTxmdVFXEUURAKDX6+VOhYjIKWrf32rf78gzsH0ioraO7ZNnYvtERG1dS9onFtluUVpaCgAICwuTOxUiIqcqLS2FRqOROw1qJrZPRNResH3yLGyfiKi9aE77JIj8qsiGxWLB5cuXERgYCEEQmn2cXq9HWFgY8vPzERQU5NQc2zJeR/vxGjpGW76OoiiitLQUoaGhUCg4a4CnYPskL15H+/EaOkZbvo5snzwT2yd58Traj9fQMdrydWxJ+8SebLdQKBTo1q1bq48PCgpqc79QcuB1tB+voWO01evIHgKeh+2Te+B1tB+voWO01evI9snzsH1yD7yO9uM1dIy2eh2b2z7xKyIiIiIiIiIiIiI7schGRERERERERERkJxbZHEStVmPhwoVQq9Vyp+LReB3tx2voGLyO1Fbwd9kxeB3tx2voGLyO1Fbwd9kxeB3tx2voGLyOVlz4gIiIiIiIiIiIyE7syUZERERERERERGQnFtmIiIiIiIiIiIjsxCIbERERERERERGRnVhkIyIiIiIiIiIishOLbERERERERERERHZikc0BVq9ejR49esDHxwfR0dH4+uuv5U7JoyxduhR33303AgMD0aVLFzz22GP44Ycf5E7Loy1duhSCIGDOnDlyp+JxLl26hN///vfo1KkT/Pz8MGDAAOTm5sqdFlGrsY1qPbZPzsE2qnXYPlFbw/ap9dg+OQfbp9ZjG/UbFtnstHnzZsyZMwevvPIKjh07hmHDhmH06NHIy8uTOzWPkZ2djRkzZuDAgQPIyspCdXU14uPjUV5eLndqHunw4cNYu3Yt+vfvL3cqHqe4uBhDhw6Fl5cXvvzyS5w5cwbLly9Hhw4d5E6NqFXYRtmH7ZPjsY1qHbZP1NawfbIP2yfHY/vUemyjbAmiKIpyJ+HJBg8ejEGDBmHNmjXSvj59+uCxxx7D0qVLZc3NU129ehVdunRBdnY27r//frnT8ShlZWUYNGgQVq9ejcWLF2PAgAFYuXKl3Gl5jPnz5+Obb77hN6nUZrCNciy2T/ZhG9V6bJ+orWH75Fhsn+zD9sk+bKNssSebHYxGI3JzcxEfH2+zPz4+Hvv375ctL09XUlICAOjYsaPcqXicGTNmYMyYMRgxYoTcqXikzz//HDExMXjqqafQpUsXDBw4EOvWrZM7LaJWYRvleGyf7MM2qvXYPlFbwvbJ8dg+2Yftk33YRtlikc0O165dg9lsRnBwsM3+4OBgFBYWypaXJxNFEcnJybjvvvsQFRUldzoeZdOmTTh69Ci//bPDuXPnsGbNGvzud7/Dzp07MW3aNMyaNQsffPCB3KkRtRjbKMdi+2QftlH2YftEbQnbJ8di+2Qftk/2YxtlSyV3Am2BIAg226Io1tlHzTNz5kx8++232Ldvn9ypeJT8/HzMnj0bmZmZ8PHxkTsdj2WxWBATE4MlS5YAAAYOHIjTp09jzZo1eO655+ROj6hV2EY5Btun1mMbZT+2T9QWsX1yDLZPrcf2yTHYRtliTzY76HQ6KJXKOt+4XLlypc43M9S0F154AZ9//jn27NmDbt26yZ2OR8nNzcWVK1cQHR0NlUoFlUqF7OxsvPPOO1CpVDCbzXKn6BG6du2KyMhIm319+vThJLzkkdhGOQ7bJ/uwjbIf2ydqS9g+OQ7bJ/uwfXIMtlG2WGSzg7e3N6Kjo5GVlWWzPysrC0OGDJEtL08jiiJmzpyJTz75BLt370aPHj3kTsnjPPTQQzh58iSOHz8u3WJiYvDss8/i+PHjUCqVcqfoEYYOHVpn+fOzZ8+ie/fusuVE1Fpso+zH9skx2EbZj+0TtSVsn+zH9skx2D45BtsoWxwuaqfk5GQkJCQgJiYGsbGxWLt2LfLy8jBt2jS5U/MYM2bMwL///W989tlnCAwMlL7V0mg08PX1lTs9jxAYGFhnDgZ/f3906tSJczO0wIsvvoghQ4ZgyZIlmDhxIg4dOoS1a9di7dq1cqdG1Cpso+zD9skx2EbZj+0TtTVsn+zD9skx2D45BtuoW4hkt7///e9i9+7dRW9vb3HQoEFidna23Cl5FAD13jZs2CB3ah4tLi5OnD17ttxpeJwvvvhCjIqKEtVqtXjnnXeKa9eulTslIruwjWo9tk/Owzaq5dg+UVvD9qn12D45D9un1mEb9RtBtP6REhERERERERERUStxTjYiIiIiIiIiIiI7schGRERERERERERkJxbZiIiIiIiIiIiI7MQiGxERERERERERkZ1YZCMiIiIiIiIiIrITi2xERERERERERER2YpGNiIiIiIiIiIjITiyyERERERERERER2YlFNiIiIiIiIiIiIjuxyEZERERERERERGQnFtmIiIiIiIiIiIjs9P8BnT7fUbj0TrYAAAAASUVORK5CYII=", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(15, 4))\n", + "fig.subplots_adjust(wspace=0.35)\n", + "\n", + "ax = fig.add_subplot(1, 3, 1)\n", + "ax.set_ylabel('Vm (mV)')\n", + "ax.axhline(mA.get('amp.Vm').initial_value().eval(), **kw)\n", + "ax.axhline(mA.get('amp.Vc').eval(), **kw)\n", + "ax.plot(dA.time(), dA['amp.Vm'], label='Model A')\n", + "ax.plot(dC.time(), dC['amp.Vm'], label='Model C')\n", + "ax.legend()\n", + "\n", + "ax = fig.add_subplot(1, 3, 2)\n", + "ax.set_ylabel('Vp (mV)')\n", + "ax.plot(dA.time(), dA['amp.Vp'])\n", + "ax.plot(dC.time(), dC['amp.Vp'])\n", + "ax = ax.inset_axes((0.15, 0.20, 0.5, 0.75))\n", + "ax.plot(dA.time(), dA['amp.Vp'])\n", + "ax.plot(dC.time(), dC['amp.Vp'])\n", + "ax.set_xlim(4.998, 5.02)\n", + "\n", + "ax = fig.add_subplot(1, 3, 3)\n", + "ax.set_ylabel('I obs (pA)')\n", + "ax.plot(dA.time(), dA['amp.I_obs'])\n", + "ax.plot(dC.time(), dC['amp.I_obs'])\n", + "ax = ax.inset_axes((0.25, 0.40, 0.4, 0.55))\n", + "ax.plot(dA.time(), dA['amp.I_obs'])\n", + "ax.plot(dC.time(), dC['amp.I_obs'])\n", + "ax.set_xlim(4.998, 5.02)\n", + "\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "37187c14", + "metadata": {}, + "source": [ + "Now we see the expected ringing behaviour in Model A, while the simplified equations in Model C show a simpler response." + ] + }, + { + "cell_type": "markdown", + "id": "def45ae4", + "metadata": {}, + "source": [ + "## Conclusions\n", + "\n", + "- Model A, which uses the op-amp equation from Sigworth 1995a, exhibits more complicated dynamics than Models B and C, which are based on a dominant-pole approximation of Model A.\n", + "- Model B is a Model A variant with an alternative op-amp equation.\n", + "- Model C can be formulated as a Model B variant with $V_\\text{out} = V_o - V_p$.\n", + "- When using the default settings, the differences between the models appear neglible.\n", + "- Model A can be made to show unstable ringing behaviour." + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/tutorial/appendix-a/img/op-amp-1.png b/tutorial/appendix/b-op-amps/img/op-amp-1.png similarity index 100% rename from tutorial/appendix-a/img/op-amp-1.png rename to tutorial/appendix/b-op-amps/img/op-amp-1.png diff --git a/tutorial/appendix-a/img/op-amp-2-no-load.png b/tutorial/appendix/b-op-amps/img/op-amp-2-no-load.png similarity index 100% rename from tutorial/appendix-a/img/op-amp-2-no-load.png rename to tutorial/appendix/b-op-amps/img/op-amp-2-no-load.png diff --git a/tutorial/appendix-a/img/op-amp-3-diff-amp.png b/tutorial/appendix/b-op-amps/img/op-amp-3-diff-amp.png similarity index 100% rename from tutorial/appendix-a/img/op-amp-3-diff-amp.png rename to tutorial/appendix/b-op-amps/img/op-amp-3-diff-amp.png diff --git a/tutorial/appendix-a/img/op-amp-4-generic.png b/tutorial/appendix/b-op-amps/img/op-amp-4-generic.png similarity index 100% rename from tutorial/appendix-a/img/op-amp-4-generic.png rename to tutorial/appendix/b-op-amps/img/op-amp-4-generic.png diff --git a/tutorial/appendix-a/img/op-amp-5-inverting.png b/tutorial/appendix/b-op-amps/img/op-amp-5-inverting.png similarity index 100% rename from tutorial/appendix-a/img/op-amp-5-inverting.png rename to tutorial/appendix/b-op-amps/img/op-amp-5-inverting.png diff --git a/tutorial/appendix-b/2-sigworth-rs.ipynb b/tutorial/appendix/c-rs/1-compensation-prediction.ipynb similarity index 97% rename from tutorial/appendix-b/2-sigworth-rs.ipynb rename to tutorial/appendix/c-rs/1-compensation-prediction.ipynb index 90cafb9..8b85648 100644 --- a/tutorial/appendix-b/2-sigworth-rs.ipynb +++ b/tutorial/appendix/c-rs/1-compensation-prediction.ipynb @@ -5,8 +5,7 @@ "id": "8cb8168d", "metadata": {}, "source": [ - "# Appendix B2: Sigworth 1983/1995 Rs compensation\n", - "**Appendix B discusses and compares patch clamp model equations**\n", + "# C1: Series resistance correction and prediction\n", "\n", "In this notebook, we take a detailed look at the $R_s$ compensation and slow capacitance transient cancellation scheme in figures 18 and 19 of [Sigworth 1995a](https://doi.org/10.1007/978-1-4419-1229-9_4), and re-derive the equations found in [Lei, Clark et al. 2024](https://doi.org/10.1101/2024.07.23.604780v1)." ] @@ -191,7 +190,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/tutorial/appendix-e/1-rs-cm-one-shot.ipynb b/tutorial/appendix/c-rs/2-rs-cm-one-shot.ipynb similarity index 99% rename from tutorial/appendix-e/1-rs-cm-one-shot.ipynb rename to tutorial/appendix/c-rs/2-rs-cm-one-shot.ipynb index 8efa814..dc07080 100644 --- a/tutorial/appendix-e/1-rs-cm-one-shot.ipynb +++ b/tutorial/appendix/c-rs/2-rs-cm-one-shot.ipynb @@ -5,8 +5,7 @@ "id": "7fb2df6f", "metadata": {}, "source": [ - "# Appendix E1: Estimating Rs and Cm; a one-shot approach\n", - "**Appendix E describes Rs and Cm estimation methods**" + "# C2: Estimating $R_s$ and $C_m$ - the one-shot approach" ] }, { @@ -15,8 +14,7 @@ "metadata": {}, "source": [ "During a patch clamp experiment, estimates of $R_s$ and $C_m$ must be made to facilitate slow capacitance and series resistance compensation.\n", - "In this appendix, we will review a \"one-shot\" method that uses current measured during a test pulse without $R_s$ or $C_m$ compensation to make a single prediction.\n", - "In the next appendix, we wil look at an \"iterative\" method that uses currents measured during successive test pulses while $R_s$ and $C_m$ compensations are refined.\n", + "In this notebook, we review a \"one-shot\" method that uses current measured during a test pulse without $R_s$ or $C_m$ compensation to make a single prediction.\n", "\n", "The approach described here is explained in Axon's pCLAMP manual, where it is attributed to Dr. Fernando Garcia-Diaz.\n", "As reference we shall use the pCLAMP 9 User Guide Rev D (later versions are missing equation numbers), as available from [Molecular devices](https://support.moleculardevices.com/s/article/pCLAMP-Software-Manual-Download-Page), starting on page 229." @@ -1368,7 +1366,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/tutorial/appendix-e/2-rs-cm-iterative.ipynb b/tutorial/appendix/c-rs/3-rs-cm-iterative.ipynb similarity index 77% rename from tutorial/appendix-e/2-rs-cm-iterative.ipynb rename to tutorial/appendix/c-rs/3-rs-cm-iterative.ipynb index fe19848..66559fd 100644 --- a/tutorial/appendix-e/2-rs-cm-iterative.ipynb +++ b/tutorial/appendix/c-rs/3-rs-cm-iterative.ipynb @@ -5,8 +5,7 @@ "id": "7fb2df6f", "metadata": {}, "source": [ - "# Appendix E2: Estimating Rs and Cm; an iterative approach\n", - "**Appendix E describes Rs and Cm estimation methods**" + "# C3: Estimating $R_s$ and $C_m$ - iterative approach" ] }, { @@ -14,9 +13,9 @@ "id": "e2ffeda4", "metadata": {}, "source": [ - "Having reviewed the \"one-shot\" approach used in Axon's pCLAMP, we now turn to the iterative method employed in HEKA devices such as the EPC-10.\n", + "In this notebook, we describe the iterate method of estimating $R_s$ and $C_m$ employed in HEKA devices such as the EPC-10.\n", "\n", - "As reference we shall use the EPC-10 hardware manual version 3.1, as available from [HEKA](http://www.heka.com/downloads/downloads_main.html#down_pca), starting on page 57, but more importantly - [Sigworth 1995c](https://doi.org/10.1016/0165-0270(94)00129-5), section 3." + "As reference we shall use the EPC-10 hardware manual version 3.1, as available from [HEKA](http://www.heka.com/downloads/downloads_main.html#down_pca), starting on page 57, and [Sigworth 1995c](https://doi.org/10.1016/0165-0270(94)00129-5), section 3." ] }, { @@ -78,7 +77,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.9" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/tutorial/appendix-e/img/rscm-1-circuit.png b/tutorial/appendix/c-rs/img/rscm-1-circuit.png similarity index 100% rename from tutorial/appendix-e/img/rscm-1-circuit.png rename to tutorial/appendix/c-rs/img/rscm-1-circuit.png diff --git a/tutorial/appendix-e/img/rscm-2-protocol.png b/tutorial/appendix/c-rs/img/rscm-2-protocol.png similarity index 100% rename from tutorial/appendix-e/img/rscm-2-protocol.png rename to tutorial/appendix/c-rs/img/rscm-2-protocol.png diff --git a/tutorial/appendix-a/4-bessel-filters.ipynb b/tutorial/appendix/d-filters/1-bessel-filters-laplace.ipynb similarity index 74% rename from tutorial/appendix-a/4-bessel-filters.ipynb rename to tutorial/appendix/d-filters/1-bessel-filters-laplace.ipynb index 58d8908..dc20bcd 100644 --- a/tutorial/appendix-a/4-bessel-filters.ipynb +++ b/tutorial/appendix/d-filters/1-bessel-filters-laplace.ipynb @@ -5,8 +5,7 @@ "id": "044506d5-71e4-43da-8603-ce5103279e28", "metadata": {}, "source": [ - "# Appendix A4: Bessel low-pass filters\n", - "**Appendix A provides extra background for path clamp electronics.**" + "# D1: Bessel low-pass filters in the Laplace domain" ] }, { @@ -15,9 +14,9 @@ "metadata": {}, "source": [ "[Bessel filters](https://en.wikipedia.org/wiki/Bessel_filter) are popular for low-pass filtering in patch clamp hardware.\n", - "Compared to other filter types, they have very little _overshoot_: when you pass a voltage step through a Bessel filter it gets smoothed, but the filtered voltage _almost_ doesn't go beyond the intended step (graphs below!).\n", + "Compared to other filter types, they have very little _overshoot_: when you pass a voltage step through a Bessel filter it gets smoothed, but the filtered voltage _almost_ doesn't go beyond the intended step.\n", "\n", - "In this notebook, we build on the concepts reviewed in [Appendix A2](./2-laplace-and-filters.ipynb) to explore Bessel filters in detail." + "In this notebook, we look at the transfer functions and frequency response of Bessel low-pass filters and explore their effects with SciPy." ] }, { @@ -379,7 +378,7 @@ "id": "b37ae7b1-a52a-4994-a1fc-27ce4472d556", "metadata": {}, "source": [ - "We can then use the method from [Appendix A2](./2-laplace-and-filters) to create a Bode plot:" + "We can then use the method we defined earlier to create a Bode plot." ] }, { @@ -404,7 +403,7 @@ "\n", "# Import function from shared library\n", "import sys\n", - "sys.path.insert(0, '../src')\n", + "sys.path.insert(0, '../../src')\n", "from library import bode\n", "\n", "axes = bode(mag, arg)\n", @@ -524,9 +523,24 @@ "id": "8c58a7e8-c2f2-4424-a7a2-6c9fa7be2815", "metadata": {}, "source": [ - "## Emulating an analog filter\n", + "## Offline analysis: Emulating filters\n", "\n", - "We can also use SciPy to simulate the effects of an analog filter (i.e. a fitler implemented in electronics) on an analog signal (some fluctuating voltage on a wire).\n", + "To understand filters a bit better, we now take a brief detour into filtering signals _offline_.\n", + "In other words, applying filters to digitally stored data." + ] + }, + { + "cell_type": "markdown", + "id": "67882abe-d34a-4989-815d-e0e1b1a7ca12", + "metadata": {}, + "source": [ + "### Emulating an analog filter with SciPy\n", + "\n", + "An _analog filter_ is a filter implemented in electronics, that acts on an analog signal (a fluctuating voltage in a wire).\n", + "\n", + "\n", + "\n", + "SciPy can _emulate_ the effects of an analog filter (i.e. a filter implemented in electronics) on an analog signal (a fluctuating voltage on a wire).\n", "\n", "For this, we use the method [lsim](https://docs.scipy.org/doc/scipy/reference/generated/scipy.signal.lsim.html)." ] @@ -605,9 +619,9 @@ "id": "3a3c0e89-4181-47c0-9a4d-44e443600e36", "metadata": {}, "source": [ - "## Applying a digital filter\n", + "### Applying a digital filter\n", "\n", - "We can also apply a digital filter.\n", + "We can also use SciPy to _apply_ a digital filter (no emulation needed here!)\n", "\n", "This time we use:\n", "\n", @@ -704,584 +718,6 @@ "ax.legend(ncol=4, framealpha=1)\n", "plt.show()" ] - }, - { - "cell_type": "markdown", - "id": "b473031f-6a1b-4177-b1b8-18ff14f37ae2", - "metadata": {}, - "source": [ - "## Two-pole bessel: the stimulus filter\n", - "\n", - "The HEKA EPC-10 uses a second order Bessel filter in its \"stimulus filter\", which is applied to voltage steps to reduce capacitative transients.\n", - "So we'll have a look at this filter in detail.\n", - "\n", - "First, we'll look at it the conventional way: as a low-pass filter over a _periodic_ signal, analysed in terms of its _frequency response_." - ] - }, - { - "cell_type": "markdown", - "id": "025a8499-c97e-4296-ba5f-99f6210fabaf", - "metadata": {}, - "source": [ - "### Frequency response\n", - "\n", - "The standard equation for a 2-pole Bessel is\n", - "\\begin{align}\n", - "H(s) = \\frac{3}{s^2 + 3s + 3}\n", - "\\end{align}\n", - "\n", - "For the _magnitude_ of its frequency response, we find\n", - "\\begin{align}\n", - "|H(i\\phi)| = \\left| \\frac{3}{(i\\phi)^2 + 3i\\phi + 3} \\right| \n", - " = 3 \\left| \\frac{1}{3 - \\phi^2 + 3\\phi i} \\right|\n", - "\\end{align}\n", - "To calculate this, we use\n", - "\\begin{align}\n", - "\\left| \\frac{1}{a + bi} \\right|\n", - " = \\left| \\frac{a - bi}{a^2 + b^2} \\right|\n", - " = \\sqrt{\\frac{a^2 + b^2}{(a^2 + b^2)^2}}\n", - " = \\frac{1}{\\sqrt{a^2 + b^2}}\n", - "\\end{align}\n", - "for\n", - "\\begin{align}\n", - "|H(i\\phi)| = \\frac{3}{\\sqrt{(3 - \\phi^2)^2 + 9\\phi^2}}\n", - " = \\frac{3}{\\sqrt{\\phi^4 + 3\\phi^2 + 9}}\n", - "\\end{align}" - ] - }, - { - "cell_type": "markdown", - "id": "be6603e6-b235-4c0e-b07f-0cf8670dca35", - "metadata": {}, - "source": [ - "The frequency at which this filter's gain is $1/\\sqrt(2)$ (the 3dB point) is found from:\n", - "\\begin{align}\n", - "\\frac{3}{\\sqrt{\\phi^4 + 3\\phi^2 + 9}} &= \\frac{1}{\\sqrt{2}} \\\\\n", - "\\sqrt{\\phi^4 + 3\\phi^2 + 9} &= 3\\sqrt{2}\\\\\n", - "\\phi^4 + 3\\phi^2 - 9 &= 0 \\\\\n", - "\\phi^2 = \\frac{-3 \\pm \\sqrt{9 + 4\\cdot9}}{2} &= \\frac{3}{2}\\left(-1 \\pm \\sqrt{5} \\right) \\\\\n", - "\\phi = \\pm \\sqrt{\\frac{3}{2}\\left(-1 \\pm \\sqrt{5} \\right)}\n", - "\\end{align}\n", - "By only allowing real and positive numbers, this becomes a single solution, which we'll call $\\omega_0$:\n", - "\\begin{align}\n", - "\\omega_0 = \\sqrt{\\frac{3}{2}\\left(-1 + \\sqrt{5} \\right)} \\approx 1.36\n", - "\\end{align}\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "7a77efcb-d58d-4ce0-b55a-8f04aebaab4d", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "w = np.linspace(0, 10, 100)\n", - "\n", - "fig = plt.figure(figsize=(12, 3))\n", - "fig.subplots_adjust(hspace=0.2)\n", - "\n", - "# Make a log-log plot, as used in a Bode diagram\n", - "ax = fig.add_subplot(1, 2, 1)\n", - "ax.set_xscale('log')\n", - "ax.set_yscale('log')\n", - "ax.set_ylabel('Gain')\n", - "ax.set_xlabel('Angular frequency (rad/s)')\n", - "ax.grid()\n", - " \n", - "# Plot, letting Numpy work out the absolute value\n", - "ax.plot(w, np.abs(3 / ((w*1j)**2 + 3*(w*1j) + 3)))\n", - " \n", - "# Plot, using the equation we derived\n", - "ax.plot(w, 3 / np.sqrt(w**4 + 3*w**2 + 9), '--')\n", - "\n", - "# Draw lines for w=w0 and gain=1/sqrt(2)\n", - "kw = dict(color='k', lw=1, ls='--')\n", - "ax.axhline(1 / np.sqrt(2), **kw)\n", - "ax.axvline(np.sqrt(3/2 * (np.sqrt(5) - 1)), **kw)\n", - "\n", - "# Show \"negative frequencies\", in an unscaled plot\n", - "w = np.linspace(-10, 10, 100)\n", - "ax = fig.add_subplot(1, 2, 2)\n", - "ax.set_xlabel('Positive and negative frequencies')\n", - "ax.grid()\n", - "ax.plot(w, 3 / np.sqrt(w**4 + 3*w**2 + 9))\n", - "ax.axhline(1 / np.sqrt(2), **kw)\n", - "ax.axvline(np.sqrt(3/2 * (np.sqrt(5) - 1)), **kw)\n", - "ax.axvline(-np.sqrt(3/2 * (np.sqrt(5) - 1)), **kw)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "2bbd7916-2d02-4982-aa38-6cd7d7869e15", - "metadata": {}, - "source": [ - "Now, we scale the filter to place this point at a user-defined cut-off frequency $\\omega_c=10\\,\\text{kHz}=2\\cdot10^4/\\pi\\,\\text{rad}/\\text{s}$:" - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "5bf77ab3-a043-4225-adf5-8e6efdf74877", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "w = np.logspace(3, 5.2, 1000)\n", - "w0 = np.sqrt(3 / 2 * (np.sqrt(5) - 1))\n", - "z = w * w0 / (2e4 * np.pi)\n", - "\n", - "fig = plt.figure(figsize=(9, 3))\n", - "ax = fig.add_subplot()\n", - "ax.set_xscale('log')\n", - "ax.set_yscale('log')\n", - "ax.set_ylabel('Gain')\n", - "ax.set_xlabel('Angular frequency (rad/s)')\n", - "ax.grid()\n", - "ax.plot(w, 3 / np.sqrt(z**4 + 3*z**2 + 9))\n", - "kw = dict(color='k', lw=1, ls='--')\n", - "ax.axhline(1 / np.sqrt(2), **kw)\n", - "ax.axvline(2e4 * np.pi, color='r', label='10 kHz')\n", - "ax.legend()\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "282f4725-b77b-4d25-87a4-a10d6d442716", - "metadata": {}, - "source": [ - "### Step response and rise time" - ] - }, - { - "cell_type": "markdown", - "id": "58b0cc02-af3d-4433-a6f8-bf21812bfa51", - "metadata": {}, - "source": [ - "The HEKA stimulus filter is described as having a [rise time](https://en.wikipedia.org/wiki/Rise_time) of either 20$\\mu$s or 2$\\mu$s.\n", - "See e.g. the EPC-10 hardware manual:\n", - "\n", - "> Two degrees of filtering, specified as the rise times (time from 10% to 90% of the amplitude of a step change) are available in the\n", - "software: 2 µs, which is the minimum required to avoid non-linearity in the internal circuitry, and 20 µs, which is preferable for all but the fastest measurements, to reduce the capacitive transients\n", - "\n", - "To find the transfer function scalings for these settings, we start by working out the _step response_:\n" - ] - }, - { - "cell_type": "markdown", - "id": "1250c164-88d3-4c0b-8204-db88b9d38816", - "metadata": {}, - "source": [ - "From [Appendix A2](./2-laplace-and-filters) we get the step function and its Laplace transform\n", - "\\begin{align}\n", - "u(t) = \\delta(t) && U(s) = \\frac{1}{s}\n", - "\\end{align}\n", - "for output\n", - "\\begin{align}\n", - "Y(s) = H(s)U(s) = \\frac{3}{s(s^2 + 3s + 3)}\n", - "\\end{align}\n", - "\n", - "To solve this, we split into partial coefficients while keeping the second-order term together:\n", - "\n", - "\\begin{align}\n", - "Y(s) = \\frac{3}{s(s^2 + 3s + 3)} \n", - " = \\frac{A}{s} + \\frac{B + Cs}{s^2 + 3s + 3}\n", - "\\end{align}\n", - "\n", - "\\begin{align}\n", - "3 &= A(s^2 + 3s + 3) + Bs + Cs^2 \\\\\n", - " &= (A + C)s^2 + (3A + B)s + 3A\n", - "\\end{align}\n", - "\\begin{align}\n", - "A = 1 && B = -3 && C = -1\n", - "\\end{align}\n", - "\n", - "\\begin{align}\n", - "Y(s) = \\frac{1}{s} + \\frac{-3 - s}{s^2 + 3s + 3}\n", - " = \\frac{1}{s} - \\frac{3 + s}{s^2 + 3s + 3}\n", - "\\end{align}\n", - "\n", - "To save time, we could also have [asked a website](https://www.wolframalpha.com/input?i=partial+fractions+3%2F%28s%28s%5E2+%2B+3s+%2B+3%29%29) or used [SymPy](https://docs.sympy.org/latest/modules/polys/reference.html#sympy.polys.partfrac.apart):" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "f2272c3f-1f19-4018-bf08-e27819d5eb2f", - "metadata": {}, - "outputs": [ - { - "data": { - "text/latex": [ - "$\\displaystyle - \\frac{s + 3}{s^{2} + 3 s + 3} + \\frac{1}{s}$" - ], - "text/plain": [ - "-(s + 3)/(s**2 + 3*s + 3) + 1/s" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "from sympy.polys.partfrac import apart\n", - "from sympy.abc import s\n", - "\n", - "apart(3 / (s * (s**2 + 3 * s + 3)))" - ] - }, - { - "cell_type": "markdown", - "id": "cf198535-bb93-4ef0-8a0a-5ff3b2a4fc6e", - "metadata": {}, - "source": [ - "To get the inverse transform, we can write this in pole-zero form:\n", - "\\begin{align}\n", - "Y(s) = \\frac{1}{s} - \\frac{3 + s}{(s + \\sigma - i\\omega)(s + \\sigma + i\\omega)},\n", - "&& \\sigma = 3/2,\n", - "&& \\omega = \\sqrt{3}/2\n", - "\\end{align}\n", - "\n", - "This has the advantage that we can look up the standard solution, e.g. in [Appendix A2](./2-laplace-and-filters)\n", - "\\begin{align}\n", - "F(s) &= \\frac{C_1 + C_2 s}{(s + \\sigma - i\\omega)(s + \\sigma + i\\omega)} \\\\\n", - "f(t) &= \\left( \\frac{C_1 - C_2\\sigma}{\\omega}e^{-\\sigma t} \\sin(\\omega t) + C_2 e^{-\\sigma t} \\cos(\\omega t) \\right) \\theta(t)\n", - "\\end{align}\n", - "\n", - "to find\n", - "\\begin{align}\n", - "y(t) &= \\theta(t) - \\left( \\frac{C_1 - C_2\\sigma}{\\omega}e^{-\\sigma t} \\sin(\\omega t) + C_2 e^{-\\sigma t} \\cos(\\omega t) \\right) \\theta(t) \\\\\n", - "&= \\theta(t) \\left[1 - \\frac{3 - 3/2}{\\sqrt{3}/2}e^{-3/2t} \\sin(\\sqrt{3}/2 t) + e^{-3/2 t} \\cos(\\sqrt{3}/2 t) \\right] \\\\\n", - "&= \\theta(t) \\left[1 - (\\sqrt{3} \\sin(\\sqrt{3}/2 t) + \\cos(\\sqrt{3}/2 t))e^{-3/2t} \\right]\n", - "\\end{align}\n", - "\n", - "Let's plot it:" - ] - }, - { - "cell_type": "code", - "execution_count": 17, - "id": "5cf0d88e-a6cf-4abb-b24c-2092a60bd581", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "t = np.linspace(-5, 10, 1000)\n", - "\n", - "def bessel2_step(t):\n", - " theta = 1 * (t >= 0)\n", - " s = np.sqrt(3)\n", - " return theta * (1 - (s * np.sin(s/2*t) + np.cos(s/2*t)) * np.exp(-3/2*t))\n", - "\n", - "y = bessel2_step(t)\n", - "\n", - "fig = plt.figure(figsize=(9, 3))\n", - "fig.subplots_adjust(hspace=0.2)\n", - "ax = fig.add_subplot(1, 2, 1)\n", - "ax.update(dict(xlabel='Time', ylabel='Stimulus'))\n", - "ax.plot(t, y)\n", - "ax = fig.add_subplot(1, 2, 2)\n", - "ax.set_xlabel('Time')\n", - "ax.axhline(1, color='grey', ls='--', lw=1)\n", - "ax.plot(t, y)\n", - "ax.set_xlim(0, 8)\n", - "ax.set_ylim(0.98, 1.02)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "41011a4c-fe8f-41a9-8654-876546e323f6", - "metadata": {}, - "source": [ - "This looks good! And we can see the near lack of overshoot that makes Bessel filters popular.\n", - "\n", - "We can use the equations above to work out the rise time, but it's probably not a lovely expression so we'll just do it numerically:" - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "cb51e2bd-e386-4f81-8c78-c6560157c24d", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.2999218750000007 0.10001114060500294\n", - "1.8783203124999999 0.8999978202201413\n" - ] - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from scipy.optimize import fmin\n", - "t10 = fmin(lambda x: (bessel2_step(x) - 0.1)**2, 0.1, disp=False)[0]\n", - "t90 = fmin(lambda x: (bessel2_step(x) - 0.9)**2, 2, disp=False)[0]\n", - "print(t10, bessel2_step(t10))\n", - "print(t90, bessel2_step(t90))\n", - "fig = plt.figure(figsize=(5, 3))\n", - "ax = fig.add_subplot()\n", - "ax.update(dict(xlabel='Time', ylabel='Stimulus'))\n", - "ax.axvline(t10, color='grey', ls='--', lw=1)\n", - "ax.axvline(t90, color='grey', ls='--', lw=1)\n", - "ax.plot(t, y)\n", - "ax.text(4, 0.4, f'Rise time: {t90 - t10:.4}s')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "3f4b2b36-dfb5-4147-b978-b8f3a0f2d251", - "metadata": {}, - "source": [ - "To emulate a rise time of 20$\\mu$s, we scale $t$:" - ] - }, - { - "cell_type": "code", - "execution_count": 19, - "id": "27ab72c2-4304-4024-9dc1-6434d26ce6b3", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.0038124999999999843 0.10029671636557969\n", - "0.0238125 0.8996055239892486\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "t = np.linspace(-0.05, 0.1, 1000)\n", - "\n", - "def bessel2_step(t, x):\n", - " theta = 1 * (t >= 0)\n", - " s = np.sqrt(3)\n", - " t = t / 2 * x\n", - " return theta * (1 - (s * np.sin(s*t) + np.cos(s*t)) * np.exp(-3*t))\n", - "\n", - "f = 78.8\n", - "y = bessel2_step(t, f)\n", - "\n", - "t10 = fmin(lambda x: (bessel2_step(x, f) - 0.1)**2, 0.01, disp=False)[0]\n", - "t90 = fmin(lambda x: (bessel2_step(x, f) - 0.9)**2, 0.02, disp=False)[0]\n", - "print(t10, bessel2_step(t10, f))\n", - "print(t90, bessel2_step(t90, f))\n", - "\n", - "fig = plt.figure(figsize=(5, 3))\n", - "ax = fig.add_subplot()\n", - "ax.update(dict(xlabel='Time (ms)', ylabel='Stimulus'))\n", - "ax.axvline(t10, color='grey', ls='--', lw=1)\n", - "ax.axvline(t90, color='grey', ls='--', lw=1)\n", - "ax.plot(t, y)\n", - "ax.text(0.04, 0.4, f'Rise time: {t90 - t10:.4}ms')\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "ec352afe-15bf-47c6-b807-08dda17e8432", - "metadata": {}, - "source": [ - "### Does this match what we measure?\n", - "\n", - "The HEKA EPC-9 has a [paper describing its hardware](), which contains a nice block diagram (Fig 1).\n", - "This shows us that\n", - "\n", - "1. The stimulus filter is applied to the command potential before any other additions (e.g. Cm and Rs compensation)\n", - "2. The \"V monitor\" is read directly from the stimulus filter output, again without any interference from other components.\n", - "\n", - "As a result, we should be able to see the effects of the stimulus filter on a recorded \"V monitor\" signal.\n", - "Here's a recording made using an EPC-10:" - ] - }, - { - "cell_type": "code", - "execution_count": 20, - "id": "28bc68e8-3152-428e-b7ae-56f030c1a6bb", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import myokit\n", - "d = myokit.DataLog.load('./res/stimulus-filter.zip')\n", - "d = d.npview()\n", - "\n", - "fig = plt.figure(figsize=(5, 3))\n", - "fig.subplots_adjust(0.14, 0.15, 0.96, 0.98)\n", - "ax = fig.add_subplot()\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.set_ylabel('Command voltage (mV)')\n", - "\n", - "ax.plot(d.time(), d['v20us'], 's-', label='Recording')\n", - "\n", - "t = d.time()\n", - "y = -100 + 200 * bessel2_step(t - 1, 78.8)\n", - "ax.plot(t, y, label=r'Rise time 20$\\mu$s')\n", - "y = -100 + 200 * bessel2_step(t - 1, 78.8 / 2)\n", - "ax.plot(t, y, label=r'Tweaked 40$\\mu$s')\n", - "\n", - "ax.legend()\n", - "ax.set_xlim(0.9, 1.15)\n", - "plt.show()" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "id": "bf5acb58-1e78-45f5-87f3-ec480feb2cd1", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "0.03943750000000005\n" - ] - } - ], - "source": [ - "f = 40\n", - "t10 = fmin(lambda x: (bessel2_step(x, f) - 0.1)**2, 0.01, disp=False)[0]\n", - "t90 = fmin(lambda x: (bessel2_step(x, f) - 0.9)**2, 0.02, disp=False)[0]\n", - "assert abs(bessel2_step(t10, f) - 0.1) < 1e-2\n", - "assert abs(bessel2_step(t90, f) - 0.9) < 1e-2\n", - "print(t90 - t10)" - ] - }, - { - "cell_type": "markdown", - "id": "ca357231-a3f2-45e0-9b7e-75f55db23f4e", - "metadata": {}, - "source": [ - "It seems the rise time is roughly twice what is advertised." - ] - }, - { - "cell_type": "markdown", - "id": "e3a94057-262f-4645-a459-dd9d21ef64a9", - "metadata": {}, - "source": [ - "### Can we use a first order approximation for the stimulus filter?\n", - "\n", - "The 2-pole Bessel was easy enough to implement, but having 2 state variables is maybe a bit over the top.\n", - "What does it look like if we approximate with a single-order filter?" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "b20cbe38-3107-4f0a-86a2-c0cb4a15588c", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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- "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "def y(t, tau):\n", - " t[t < 0] = 0\n", - " return 100 + (-100 - 100) * np.exp(-t / tau)\n", - "\n", - "tau = fmin(lambda tau: np.sum((y(d.time() - 1, tau) - d['v20us'])**2), 0.02, disp=False)[0]\n", - "\n", - "fig = plt.figure(figsize=(5, 3))\n", - "fig.subplots_adjust(0.14, 0.15, 0.96, 0.98)\n", - "ax = fig.add_subplot()\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.set_ylabel('Command voltage (mV)')\n", - "\n", - "ax.axvline(1 + t10, color='grey', lw=1, ls='--')\n", - "ax.axvline(1 + t90, color='grey', lw=1, ls='--')\n", - "ax.plot(d.time(), d['v20us'], 's-', label='Recording')\n", - "\n", - "t = np.linspace(0, 2, 2000)\n", - "ax.plot(t, y(t - 1, tau), label=f'tau={tau:.4}')\n", - "ax.legend(loc=(1.1, 0.5))\n", - "ax.set_xlim(0.99, 1.15)\n", - "plt.show()" - ] - }, - { - "cell_type": "markdown", - "id": "8f698264-d3a8-4e93-b5cb-798f51e241c7", - "metadata": {}, - "source": [ - "This is not far off at all, and any discrepancies only last for 0.1ms. Compared to e.g. fast-capacitance compensation, it is unlikely that approximating as first order will cause any problems." - ] } ], "metadata": { @@ -1300,7 +736,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.12" } }, "nbformat": 4, diff --git a/tutorial/appendix-a/5-bessel-filter-odes.ipynb b/tutorial/appendix/d-filters/2-bessel-filters-ode.ipynb similarity index 85% rename from tutorial/appendix-a/5-bessel-filter-odes.ipynb rename to tutorial/appendix/d-filters/2-bessel-filters-ode.ipynb index 3710fa1..9f6efe2 100644 --- a/tutorial/appendix-a/5-bessel-filter-odes.ipynb +++ b/tutorial/appendix/d-filters/2-bessel-filters-ode.ipynb @@ -5,8 +5,7 @@ "id": "044506d5-71e4-43da-8603-ce5103279e28", "metadata": {}, "source": [ - "# Appendix A5: Bessel low-pass filter ODEs\n", - "**Appendix A provides extra background for path clamp electronics.**" + "# D2: Bessel low-pass filter in ODE form\n" ] }, { @@ -14,17 +13,15 @@ "id": "8da3b3fe-426a-4710-a21a-d01126734998", "metadata": {}, "source": [ - "In [Appendix A4](./4-bessel-filters.ipynb) we explored Bessel filters analytically and filtered signals using SciPy.\n", - "In this notebook, we will rewrite some common Bessel filters as ODEs, allowing us to embed them in ODE models.\n", + "In this notebook, we derive the ODE form of Bessel low-pass filters commonly used in patch-clamp amplifiers.\n", "\n", - "In particular, we will focus on 2, 4, and 6-pole filters.\n", + "We will focus on 1, 2, 3, 4, and 6-pole filters.\n", "\n", "- The HEKA EPC-10 uses a 6-pole Bessel filter as part of the voltage-clamp circuitry (filter1), an additional 4-pole Bessel as optional output filtering (filter2, run in series with filter1 for a 10-pole combined filter), and a 2-pole Bessel filter over the command voltage to reduce capacitative transients.\n", "- The HEKA EPC-9 uses a 3-pole Bessel filter (filter1), a 4-pole Bessel filter (filter2), and a 2-pole stimulus filter.\n", "- The Axon Axopatch 200B uses a 4-pole Bessel filter over voltage and a 3-pole Bessel filter over current output.\n", "\n", - "We'll start simple, with the 1-pole filter.\n", - "These results will mainly be useful when we want to approximate a higher-order filter with a first-order one." + "We start with the 1-pole filter, which will be useful both to understand the higher order filters and later approximate them." ] }, { @@ -93,7 +90,7 @@ "id": "37285b2f-39be-4fb4-8dc7-1c81524392f8", "metadata": {}, "source": [ - "We can now write a 1-pole Bessel filter with cut-off $f_c$ as:" + "This form fits in a Myokit or CellML model:" ] }, { @@ -391,9 +388,7 @@ "metadata": {}, "source": [ "This scaling factor will change the filter's frequency, relative to its _natural frequency_ (the $\\alpha = 1$ case).\n", - "To find the natural cut-off, we can try solving $|H_2(i\\phi)|=1/\\sqrt{2}$, but it's easier* to just use rootfinding:\n", - "\n", - "(*See [Appendix 4](./4-bessel-filters.ipynb) for some background on the scipy functions involved.)" + "To find the natural cut-off, we can try solving $|H_2(i\\phi)|=1/\\sqrt{2}$, but it's easier* to just use rootfinding:" ] }, { @@ -500,115 +495,12 @@ "\\end{align}" ] }, - { - "cell_type": "code", - "execution_count": 9, - "id": "3420e006-2404-4c9c-a055-b223cbee89c9", - "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "8.742478814151495\n" - ] - } - ], - "source": [ - "fc = np.log(9) / (2 * np.pi * 0.04)\n", - "print(fc)" - ] - }, - { - "cell_type": "markdown", - "id": "62121ad3-18da-43f3-9f14-34517251ad1d", - "metadata": {}, - "source": [ - "This lets us compare 1st and 2nd order filters with the recordings from an EPC-10 again (see [appendix A4](./4-bessel-filters.ipynb)):" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "id": "06745c87-9c2a-46e2-ae20-2d84f00a0ff5", - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "text/plain": [ - "np.float64(0.018204784532536746)" - ] - }, - "execution_count": 10, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Load the \"20us\" data, which appears to have a rise time of 40us instead\n", - "d0 = myokit.DataLog.load('./res/stimulus-filter.zip')\n", - "d0 = d0.npview()\n", - "\n", - "m = myokit.parse_model(\"\"\"\n", - "[[model]]\n", - "filter.y1 = 0\n", - "filter.y2 = 0\n", - "filter.y3 = 0\n", - "\n", - "[filter]\n", - "pace = 0 bind pace\n", - "time = 0 bind time\n", - "tr = 0.04 [ms] in [ms]\n", - "# Second-order\n", - "a2 = tr * 1.3616 / log(9)\n", - " in [ms]\n", - "dot(y1) = 3 * (pace/a2^2 - y2/a2^2 - y1/a2)\n", - "dot(y2) = y1\n", - "# First-order\n", - "a1 = tr / log(9)\n", - " in [ms]\n", - "dot(y3) = (pace - y3) / a1\n", - "\"\"\")\n", - "\n", - "p = myokit.Protocol()\n", - "p.add_step(level=-100, duration=1)\n", - "p.add_step(level=100, duration=10)\n", - "\n", - "s = myokit.Simulation(m, p)\n", - "s.pre(1)\n", - "d1 = s.run(2, log_interval=1e-3).npview()\n", - "\n", - "fig = plt.figure(figsize=(5, 3))\n", - "fig.subplots_adjust(0.14, 0.15, 0.96, 0.98)\n", - "ax = fig.add_subplot()\n", - "ax.set_xlabel('Time (ms)')\n", - "ax.set_ylabel('Command voltage (mV)')\n", - "ax.plot(d0.time(), d0['v20us'], 's-', label='Recording')\n", - "ax.plot(d1.time(), d1['filter.y2'], label=f'Simulation, n=2, tr=40 us')\n", - "ax.plot(d1.time(), d1['filter.y3'], label=f'Simulation, n=1, tr=40 us')\n", - "ax.legend()\n", - "ax.set_xlim(0.99, 1.15)\n", - "plt.show()\n", - "\n", - "m.get('filter.a1').eval()" - ] - }, { "cell_type": "markdown", "id": "feeca2f6-b0b5-4b09-a40f-69bf84effebd", "metadata": {}, "source": [ - "### Third-order Bessel" + "## The 3-pole Bessel filter" ] }, { @@ -627,7 +519,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 9, "id": "200e7078-8509-4b2a-8aca-3aab79389512", "metadata": {}, "outputs": [ @@ -665,17 +557,17 @@ "Using the pole-zero representation, we can write the filter as\n", "\\begin{align}\n", "H_3(s) &= 15 \\frac{1}{s + \\sigma_2} \\, \\frac{1}{(s + \\sigma_1 - \\omega_1 i)(s + \\sigma_1 + \\omega_1 i)} \\\\\n", - " &= 15 \\frac{1}{s + \\sigma_2} \\, \\frac{1}{s^2 + (2 \\sigma_1) s + (\\sigma_1^2 + \\omega_1^2)}\n", + " &= 15 \\frac{1}{s + \\sigma_2} \\, \\frac{1}{s^2 + 2 \\sigma_1 s + (\\sigma_1^2 + \\omega_1^2)}\n", "\\end{align}\n", "where we represented each pole as either $-\\sigma$ (real) or $-\\sigma \\pm \\omega$.\n", "\n", "By design $\\sigma_2 \\cdot (\\sigma_1^2 + \\omega_1^2)$ equals the gain $K = 15$, which means we can write\n", "\\begin{align}\n", - "H_3(s) = \\frac{\\sigma_2}{s + \\sigma_2} \\frac{\\sigma_1^2 + \\omega_1^2}{s^2 + (2 \\sigma_1) s + (\\sigma_1^2 + \\omega_1^2)}\n", + "H_3(s) = \\frac{\\sigma_2}{s + \\sigma_2} \\frac{\\sigma_1^2 + \\omega_1^2}{s^2 + 2 \\sigma_1 s + (\\sigma_1^2 + \\omega_1^2)}\n", "\\end{align}\n", "\n", "This shows that we can write a 3-pole bessel as the product of a first and a second-order filter.\n", - "As a result, we can treat it **as two filters in series** (see [Appendix A2](./2-laplace-and-filters.ipynb) \"Block diagrams\").\n", + "As a result, we can treat it **as two filters in series** (see Appendix A, \"Block diagrams\").\n", "In fact, the standard way to create a 2n-pole filter in electronics, is to build a _cascade_ of n 2-pole filters placed in series.\n", "So this should be similar to what we find in real amplifiers." ] @@ -690,7 +582,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 10, "id": "7dca88fa-8af5-431b-9779-76d5ceeb8574", "metadata": {}, "outputs": [ @@ -718,7 +610,7 @@ "source": [ "And with these we can break down the 3-pole low-pass Bessel filter into a first-order filter\n", "\\begin{align}\n", - "H(s) = \\frac{2.3222}{s + 2.3222} && \\rightarrow && \\dot{y} = \\frac{u(t) - y(t)}{1 / 2.32}\n", + "H(s) = \\frac{2.3222}{s + 2.3222} && \\rightarrow && \\dot{y} = \\frac{u(t) - y(t)}{1 / 2.3222}\n", "\\end{align}\n", "and a second order filter\n", "\\begin{align}\n", @@ -732,7 +624,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 11, "id": "dc77099e-cd0e-4ae2-bb99-6ba46c327f68", "metadata": {}, "outputs": [ @@ -778,17 +670,71 @@ }, { "cell_type": "markdown", - "id": "7fc8e5bb-7551-462b-9a9b-0c325546ca8f", + "id": "71061271-ad40-4c2e-97e4-74c39747b268", "metadata": {}, "source": [ - "Is this correct?\n", - "We can compare with a SciPy filtered signal to find out, but first we'll need to work out what the natural cut-off frequency for this filter is." + "We can compare this to a SciPy filter with the natural cut-off point:" ] }, { "cell_type": "code", - "execution_count": 14, - "id": "f4883c77-5786-4a27-bc4a-e43c048e6a36", + "execution_count": 12, + "id": "fb522c5e-6740-467f-bc91-a253b2026ab5", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "def low_pass_natural(time, data, n=3):\n", + " \"\"\" Emulate an analog Bessel low-pass filter with its natural cut-off point. \"\"\"\n", + " b, a = scipy.signal.bessel(n, 1, analog=True, norm='delay')\n", + " t, y, _ = scipy.signal.lsim((b, a), data, time)\n", + " return t, y\n", + "\n", + "t, u, y = e.time(), e['f.u'], e['f.y3']\n", + "\n", + "fig = plt.figure(figsize=(15, 4))\n", + "ax = fig.add_subplot()\n", + "ax.plot(t, u, label='Noisy (0.2 Hz + 5Hz)')\n", + "ax.plot(t, y, label='Simulated')\n", + "ax.plot(*low_pass_natural(t, u, n=3), 'k:', label='SciPy, natural cut-off')\n", + "ax.legend(framealpha=1)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "3b2564be-3b5b-4814-a4a2-5e315e35a3d9", + "metadata": {}, + "source": [ + "As before, we add a scaling factor to make it tuneable:\n", + "\n", + "\\begin{align}\n", + "H(s) = \\frac{2.3222}{\\alpha s + 2.3222} && \\rightarrow && \\dot{y} = \\frac{u(t) - y(t)}{\\alpha / 2.3222}\n", + "\\end{align}\n", + "and\n", + "\\begin{align}\n", + "H(s) = \\frac{6.4594}{(\\alpha s)^2 + 3.6778 \\alpha s + 6.4594}\n", + "&& \\rightarrow && \n", + "\\ddot{y}(t) = \\frac{6.4594}{\\alpha^2}u(t) - \\frac{3.6778}{\\alpha}\\dot{y}(t) - \\frac{6.4594}{\\alpha^2}y(t),\\quad y(0)=0, \\quad \\dot{y}(0)=0\n", + "\\end{align}\n", + "\n", + "Which will scale relative to the natural frequency of:" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "523d0889-d663-4cb9-9115-abc8f5656c76", "metadata": {}, "outputs": [ { @@ -807,23 +753,26 @@ }, { "cell_type": "markdown", - "id": "bb3333e3-3b32-4837-8715-15274c2e82f9", + "id": "892fa1b6-c13b-4695-811a-3801255bc3e7", "metadata": {}, "source": [ - "We didn't apply any scaling in the simulation, so this should be a 0.2794 Hz filter:" + "So we can write a scalable version using\n", + "\\begin{align}\n", + "\\alpha = \\frac{1.7557}{2 \\pi f_c}\n", + "\\end{align}" ] }, { "cell_type": "code", - "execution_count": 15, - "id": "8623c83a-fb61-4575-833e-c0ae9a85691f", + "execution_count": 14, + "id": "2ef31809-0f98-4a00-8da1-971fa761bafc", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ - "
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" ] }, "metadata": {}, @@ -831,38 +780,52 @@ } ], "source": [ - "t, u, y = e.time(), e['f.u'], e['f.y3']\n", + "m = myokit.parse_model(\"\"\"\n", + "[[model]]\n", + "f.y1 = 0\n", + "f.y2 = 0\n", + "f.y3 = 0\n", "\n", - "fig = plt.figure(figsize=(15, 4))\n", + "[f]\n", + "fc = 1\n", + "pi = 3.14159\n", + "t = 0 bind time\n", + "u = sin(2 * pi * t / 5) + sin(2 * pi * t * 5)\n", + "alpha = 1.7557 / (2 * pi * fc)\n", + "dot(y1) = (u - y1) * 2.3222 / alpha\n", + "dot(y2) = (6.4594 / alpha^2) * (y1 - y3) - (3.6778 / alpha) * y2\n", + "dot(y3) = y2\n", + " desc: The 3-pole filtered output\n", + "\"\"\")\n", + "s = myokit.Simulation(m)\n", + "e = s.run(10, log_interval=0.001)\n", + "\n", + "fig = plt.figure(figsize=(9, 3))\n", "ax = fig.add_subplot()\n", - "ax.plot(t, u, label='Noisy (0.2 Hz + 5Hz)')\n", - "ax.plot(t, y, label='Simulated')\n", - "ax.plot(*low_pass(t, u, f=0.2794, n=3), 'k:', label='Filtered 0.2794 Hz, n=3')\n", - "ax.legend(framealpha=1)\n", + "ax.set_xlabel('Time')\n", + "ax.plot(e.time(), e['f.u'], label='u')\n", + "ax.plot(e.time(), e['f.y3'], label='y3')\n", + "ax.legend(loc='right')\n", "plt.show()" ] }, { "cell_type": "markdown", - "id": "ec548f34-0cb0-467f-9805-44908f99c494", + "id": "f49294b7-3f2f-4e71-b915-497e826938a8", "metadata": {}, "source": [ - "Note that we obtained the pole information in the \"natural\" setting by calling `bessel` with `Wn=1, norm='delay'`.\n", - "Here `Wn` is interpreted as a parameter related to \"group delay\" and the canonical results are obtained for `Wn=1`.\n", - "But we filtered using `Wn=w, norm='mag'`.\n", - "Here `Wn` is interpreted as the cut-off frequency.\n", - "Alternatively, we could have used the \"natural\" call again, to obtain an unscalable filter:" + "which we can compare with SciPy again:" ] }, { "cell_type": "code", - "execution_count": 16, - "id": "e3b8893b-1196-48c8-9814-36a1a9a263bd", + "execution_count": 15, + "id": "0de3fcf0-cdba-439b-acbb-367a8b043d24", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", "text/plain": [ "
" ] @@ -872,17 +835,13 @@ } ], "source": [ - "def low_pass_natural(time, data, n=3):\n", - " \"\"\" Emulate an analog Bessel low-pass filter with its natural cut-off point. \"\"\"\n", - " b, a = scipy.signal.bessel(n, 1, analog=True, norm='delay')\n", - " t, y, _ = scipy.signal.lsim((b, a), data, time)\n", - " return t, y\n", + "t, u, y = e.time(), e['f.u'], e['f.y3']\n", "\n", "fig = plt.figure(figsize=(15, 4))\n", "ax = fig.add_subplot()\n", "ax.plot(t, u, label='Noisy (0.2 Hz + 5Hz)')\n", "ax.plot(t, y, label='Simulated')\n", - "ax.plot(*low_pass_natural(t, u, n=3), 'k:', label='SciPy, natural cut-off')\n", + "ax.plot(*low_pass(t, u, f=1, n=3), 'k:', label='Filtered 1 Hz, n=3')\n", "ax.legend(framealpha=1)\n", "plt.show()" ] @@ -892,7 +851,7 @@ "id": "b7141a07-01fa-4cb4-9d23-e661624336a7", "metadata": {}, "source": [ - "### Fourth-order Bessel, and general Bessel filters with an even number of poles\n", + "## Fourth-order Bessel, and general Bessel filters with an even number of poles\n", "\n", "Based on the idea of decomposing higher order filters, we can now write down the equations for a 4 pole filter, along with the more general equations for Bessel low-pass filters with an even number of poles.\n", "\n", @@ -914,7 +873,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 16, "id": "7a8dd05e-bd98-42b5-a90e-903cd51a2277", "metadata": {}, "outputs": [ @@ -943,7 +902,7 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 17, "id": "03983e75-bdd8-4a22-b5e1-c706d778f7e8", "metadata": {}, "outputs": [ @@ -998,7 +957,7 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 18, "id": "d5289c70-30f7-4a30-af4f-c1ed0359139e", "metadata": {}, "outputs": [ @@ -1038,7 +997,7 @@ "id": "f7bd8a04-1b26-4c78-888a-a968bc432eda", "metadata": {}, "source": [ - "#### Scalable filter with even number of poles\n", + "### Scalable filter with even number of poles\n", "\n", "Finally, we'll work out how to make this 4-pole filter scalable, and write the results in a way that extends to any even-numbered order low-pass Bessel filter.\n", "\n", @@ -1067,7 +1026,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 19, "id": "a78c6470-0896-41ba-8117-c4aac389ce95", "metadata": {}, "outputs": [ @@ -1093,7 +1052,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 20, "id": "076c4a3f-1155-4062-bcf1-1f00e9b37a01", "metadata": {}, "outputs": [ @@ -1155,14 +1114,14 @@ "id": "957681ff-0882-4141-8457-89e0d0b76dff", "metadata": {}, "source": [ - "### Six pole Bessel filters\n", + "## Six pole Bessel filters\n", "\n", "Applying the same methods for a six pole filter we obtain:" ] }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 21, "id": "6eb455f1-3ba2-43e9-8abb-a1c4d9f36a20", "metadata": {}, "outputs": [ @@ -1186,7 +1145,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 22, "id": "9b76c99b-cb1f-420e-8580-d074b1f8c205", "metadata": {}, "outputs": [ @@ -1212,7 +1171,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 23, "id": "48686b58-6027-4937-ba4d-e5afe94c7f08", "metadata": {}, "outputs": [ @@ -1284,7 +1243,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 24, "id": "a6ed5de2-aec1-4f3c-bee9-0f457c3b5936", "metadata": {}, "outputs": [ @@ -1353,7 +1312,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 25, "id": "8f130c8b-3a8e-4b96-aa9f-556e93540de9", "metadata": {}, "outputs": [ @@ -1421,7 +1380,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.12" } }, "nbformat": 4, diff --git a/tutorial/appendix/d-filters/3-bessel-filters-ode-summary.ipynb b/tutorial/appendix/d-filters/3-bessel-filters-ode-summary.ipynb new file mode 100644 index 0000000..860bfbc --- /dev/null +++ b/tutorial/appendix/d-filters/3-bessel-filters-ode-summary.ipynb @@ -0,0 +1,145 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "044506d5-71e4-43da-8603-ce5103279e28", + "metadata": {}, + "source": [ + "# D3: Bessel low-pass filter in ODE form - summary" + ] + }, + { + "cell_type": "markdown", + "id": "8da3b3fe-426a-4710-a21a-d01126734998", + "metadata": {}, + "source": [ + "Here, we summarise the 1, 2, 3, 4, and 6-pole Bessel filter ODEs." + ] + }, + { + "cell_type": "markdown", + "id": "2bd7b385-6681-4a14-94d9-ad5b5c8dfc13", + "metadata": {}, + "source": [ + "## The 1-pole Bessel low-pass filter\n", + "\n", + "\\begin{align}\n", + "\\dot{y}(t) = \\frac{u(t) - y(t)}{\\alpha}\n", + "\\end{align}\n", + "\n", + "where\n", + "\n", + "\\begin{align}\n", + "\\alpha &= \\frac{t_r}{\\log 9} = \\frac{1}{2 \\pi f_c} \n", + "\\quad \\rightarrow \\quad\n", + "f_c = \\frac{\\log 9}{2 \\pi t_r}\n", + "\\end{align}\n", + "\n", + "for **cut-off frequency** $f_c$ and **rise time** $t_r$.\n", + "\n", + "Simulating with $t$ in ms, $t_r$ is in ms and $f_c$ is in kHz." + ] + }, + { + "cell_type": "markdown", + "id": "a40adc02-4047-49e0-bdbd-c68959058f02", + "metadata": {}, + "source": [ + "## The 2-pole Bessel low-pass filter\n", + "\n", + "\\begin{align}\n", + "\\dot{y_1} &= \\frac{3}{\\alpha^2}u(t) - \\frac{3}{\\alpha^2}y_2 - \\frac{3}{\\alpha}y_1 \\\\\n", + "\\dot{y_2} &= y_1\n", + "\\end{align}\n", + "where $y_2(t)$ is the filter's output, and\n", + "\\begin{align}\n", + "\\alpha \\approx \\frac{1.3616}{2 \\pi f_c}\n", + "\\end{align}\n", + "\n", + "In the voltage clamp model, we also set alpha based on the **first order** rise time (which approximates the more complex second order rise time)\n", + "\\begin{align}\n", + "\\alpha \\approx \\frac{1.3616}{\\log 9} t_r\n", + "\\end{align}" + ] + }, + { + "cell_type": "markdown", + "id": "feeca2f6-b0b5-4b09-a40f-69bf84effebd", + "metadata": {}, + "source": [ + "## The 3-pole Bessel low-pass filter\n", + "\n", + "\\begin{align}\n", + "\\dot{y_1} &= \\frac{u(t) - y}{\\alpha / 2.32} \\\\\n", + "\\dot{y_2} &= \\frac{6.4594}{\\alpha^2}u - \\frac{3.6778}{\\alpha}\\dot{y}(t) - \\frac{6.4594}{\\alpha^2}y \\\\\n", + "\\dot{y_3} &= y_2\n", + "\\end{align}\n", + "where $y_3(t)$ is the filter's output, and\n", + "\\begin{align}\n", + "\\alpha \\approx \\frac{1.7557}{2 \\pi f_c}\n", + "\\end{align}" + ] + }, + { + "cell_type": "markdown", + "id": "b7141a07-01fa-4cb4-9d23-e661624336a7", + "metadata": {}, + "source": [ + "## The 4-pole Bessel low-pass filter\n", + "\n", + "\\begin{align}\n", + "\\dot{y_1} &= \\frac{11.488}{\\alpha^2} (u(t)- y_2) - \\frac{4.2076}{\\alpha} y_1 \\\\\n", + "\\dot{y_2} &= y_1 \\\\\n", + "\\dot{y_3} &= \\frac{9.1401}{\\alpha^2} (y_2 - y_4) - \\frac{5.7924}{\\alpha} y_3 \\\\\n", + "\\dot{y_4} &= y_3\n", + "\\end{align}\n", + "where $y_4(t)$ is the filter's output, and\n", + "\\begin{align}\n", + "\\alpha \\approx \\frac{2.114}{2 \\pi f_c}\n", + "\\end{align}" + ] + }, + { + "cell_type": "markdown", + "id": "957681ff-0882-4141-8457-89e0d0b76dff", + "metadata": {}, + "source": [ + "## The 6-pole Bessel low-pass filter\n", + "\n", + "\\begin{align}\n", + "\\dot{y_1} &= \\frac{26.514}{\\alpha^2} (u(t)- y_2) - \\frac{5.0319}{\\alpha} y_1 \\\\\n", + "\\dot{y_2} &= y_1 \\\\\n", + "\\dot{y_3} &= \\frac{20.853}{\\alpha^2} (y_2 - y_4) - \\frac{7.4714}{\\alpha} y_3 \\\\\n", + "\\dot{y_4} &= y_3 \\\\\n", + "\\dot{y_5} &= \\frac{18.801}{\\alpha^2} (y_4 - y_6) - \\frac{8.4967}{\\alpha} y_5 \\\\\n", + "\\dot{y_6} &= y_5\n", + "\\end{align}\n", + "where $y_6(t)$ is the filter's output, and\n", + "\\begin{align}\n", + "\\alpha \\approx \\frac{2.7034}{2 \\pi f_c}\n", + "\\end{align}" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/tutorial/appendix/d-filters/4-stimulus-filter.ipynb b/tutorial/appendix/d-filters/4-stimulus-filter.ipynb new file mode 100644 index 0000000..5a902ef --- /dev/null +++ b/tutorial/appendix/d-filters/4-stimulus-filter.ipynb @@ -0,0 +1,736 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "b473031f-6a1b-4177-b1b8-18ff14f37ae2", + "metadata": {}, + "source": [ + "# D4 The two-pole stimulus filter\n", + "\n", + "The HEKA EPC-10 uses a second order Bessel filter in its \"stimulus filter\", which is applied to voltage steps to reduce capacitative transients.\n", + "\n", + "Unlike the output filters, this filter is configured by settings [rise time](https://en.wikipedia.org/wiki/Rise_time) of either 20$\\mu$s or 2$\\mu$s.\n", + "\n", + "Below, we (1) create a filter with these rise times, but then (2) show that the rise time in modern amplifiers no longer matches 20 or 2$\\mu$s, (3) perform fits to find replacement values, and finally (4) compare with a 1-pole approximation." + ] + }, + { + "cell_type": "markdown", + "id": "1250c164-88d3-4c0b-8204-db88b9d38816", + "metadata": {}, + "source": [ + "## 1. Working out the rise time\n", + "\n", + "We start by working out the filter's _step response_, i.e. the response to\n", + "\\begin{align}\n", + "u(t) = \\delta(t) && U(s) = \\frac{1}{s}\n", + "\\end{align}\n", + "for the system\n", + "\\begin{align}\n", + "Y(s) = H(s)U(s) = \\frac{3}{s(s^2 + 3s + 3)}\n", + "\\end{align}\n", + "\n", + "To solve this, we split into partial coefficients while keeping the second-order term together:\n", + "\n", + "\\begin{align}\n", + "Y(s) = \\frac{3}{s(s^2 + 3s + 3)} \n", + " = \\frac{A}{s} + \\frac{B + Cs}{s^2 + 3s + 3}\n", + "\\end{align}\n", + "\n", + "\\begin{align}\n", + "3 &= A(s^2 + 3s + 3) + Bs + Cs^2 \\\\\n", + " &= (A + C)s^2 + (3A + B)s + 3A\n", + "\\end{align}\n", + "\\begin{align}\n", + "A = 1 && B = -3 && C = -1\n", + "\\end{align}\n", + "\n", + "\\begin{align}\n", + "Y(s) = \\frac{1}{s} + \\frac{-3 - s}{s^2 + 3s + 3}\n", + " = \\frac{1}{s} - \\frac{3 + s}{s^2 + 3s + 3}\n", + "\\end{align}\n", + "\n", + "To save time, we could also have [asked a website](https://www.wolframalpha.com/input?i=partial+fractions+3%2F%28s%28s%5E2+%2B+3s+%2B+3%29%29) or used [SymPy](https://docs.sympy.org/latest/modules/polys/reference.html#sympy.polys.partfrac.apart):" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "f2272c3f-1f19-4018-bf08-e27819d5eb2f", + "metadata": {}, + "outputs": [ + { + "data": { + "text/latex": [ + "$\\displaystyle - \\frac{s + 3}{s^{2} + 3 s + 3} + \\frac{1}{s}$" + ], + "text/plain": [ + "-(s + 3)/(s**2 + 3*s + 3) + 1/s" + ] + }, + "execution_count": 1, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "from sympy.polys.partfrac import apart\n", + "from sympy.abc import s\n", + "\n", + "apart(3 / (s * (s**2 + 3 * s + 3)))" + ] + }, + { + "cell_type": "markdown", + "id": "cf198535-bb93-4ef0-8a0a-5ff3b2a4fc6e", + "metadata": {}, + "source": [ + "To get the inverse transform, we can write this in pole-zero form:\n", + "\\begin{align}\n", + "Y(s) = \\frac{1}{s} - \\frac{3 + s}{(s + \\sigma - i\\omega)(s + \\sigma + i\\omega)},\n", + "&& \\sigma = 3/2,\n", + "&& \\omega = \\sqrt{3}/2\n", + "\\end{align}\n", + "\n", + "This has the advantage that we can look up the standard solution, e.g. in Appendix A\n", + "\\begin{align}\n", + "F(s) &= \\frac{C_1 + C_2 s}{(s + \\sigma - i\\omega)(s + \\sigma + i\\omega)} \\\\\n", + "f(t) &= \\left( \\frac{C_1 - C_2\\sigma}{\\omega}e^{-\\sigma t} \\sin(\\omega t) + C_2 e^{-\\sigma t} \\cos(\\omega t) \\right) \\theta(t)\n", + "\\end{align}\n", + "\n", + "to find\n", + "\\begin{align}\n", + "y(t) &= \\theta(t) - \\left( \\frac{C_1 - C_2\\sigma}{\\omega}e^{-\\sigma t} \\sin(\\omega t) + C_2 e^{-\\sigma t} \\cos(\\omega t) \\right) \\theta(t) \\\\\n", + "&= \\theta(t) \\left[1 - \\frac{3 - 3/2}{\\sqrt{3}/2}e^{-3/2t} \\sin(\\sqrt{3}/2 t) + e^{-3/2 t} \\cos(\\sqrt{3}/2 t) \\right] \\\\\n", + "&= \\theta(t) \\left[1 - (\\sqrt{3} \\sin(\\sqrt{3}/2 t) + \\cos(\\sqrt{3}/2 t))e^{-3/2t} \\right]\n", + "\\end{align}\n", + "\n", + "Let's plot it:" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "5cf0d88e-a6cf-4abb-b24c-2092a60bd581", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import numpy as np\n", + "import matplotlib.pyplot as plt\n", + "\n", + "t = np.linspace(-5, 10, 1000)\n", + "\n", + "def bessel2_step(t):\n", + " theta = 1 * (t >= 0)\n", + " s = np.sqrt(3)\n", + " return theta * (1 - (s * np.sin(s/2*t) + np.cos(s/2*t)) * np.exp(-3/2*t))\n", + "\n", + "y = bessel2_step(t)\n", + "\n", + "fig = plt.figure(figsize=(9, 3))\n", + "fig.subplots_adjust(hspace=0.2)\n", + "ax = fig.add_subplot(1, 2, 1)\n", + "ax.update(dict(xlabel='Time', ylabel='Stimulus'))\n", + "ax.plot(t, y)\n", + "ax = fig.add_subplot(1, 2, 2)\n", + "ax.set_xlabel('Time')\n", + "ax.axhline(1, color='grey', ls='--', lw=1)\n", + "ax.plot(t, y)\n", + "ax.set_xlim(0, 8)\n", + "ax.set_ylim(0.98, 1.02)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "41011a4c-fe8f-41a9-8654-876546e323f6", + "metadata": {}, + "source": [ + "This looks good! And on the right we can see the near lack of overshoot that makes Bessel filters popular.\n", + "\n", + "We can use the equations above to work out the rise time, but it's probably not a lovely expression so we'll just do it numerically:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "cb51e2bd-e386-4f81-8c78-c6560157c24d", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.2999218750000007 0.10001114060500294\n", + "1.8783203124999999 0.8999978202201413\n" + ] + }, + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from scipy.optimize import fmin\n", + "t10 = fmin(lambda x: (bessel2_step(x) - 0.1)**2, 0.1, disp=False)[0]\n", + "t90 = fmin(lambda x: (bessel2_step(x) - 0.9)**2, 2, disp=False)[0]\n", + "print(t10, bessel2_step(t10))\n", + "print(t90, bessel2_step(t90))\n", + "fig = plt.figure(figsize=(5, 3))\n", + "ax = fig.add_subplot()\n", + "ax.update(dict(xlabel='Time', ylabel='Stimulus'))\n", + "ax.axvline(t10, color='grey', ls='--', lw=1)\n", + "ax.axvline(t90, color='grey', ls='--', lw=1)\n", + "ax.plot(t, y)\n", + "ax.text(4, 0.4, f'Rise time: {t90 - t10:.4}s')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "3f4b2b36-dfb5-4147-b978-b8f3a0f2d251", + "metadata": {}, + "source": [ + "To emulate a rise time of 20$\\mu$s, we scale $t$:" + ] + }, + { + "cell_type": "code", + "execution_count": 23, + "id": "27ab72c2-4304-4024-9dc1-6434d26ce6b3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Time, filter value\n", + "0.0038124999999999843 0.10029671636557969\n", + "0.0238125 0.8996055239892486\n" + ] + }, + { + "data": { + "image/png": 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77vQmH+rhj0BvldRxiFo8FkoiJ6LTCf1MPE+bcUkIETUdCyWRBfz8/DBz5kz4+flJsv9TVwtxs6gSXm5KjA43fhlVQ6TOTuSsJD9HSeRMXFxcjF6v21y+OnMTABB9fxBULgqL1pU6O5GzYo+SyAJFRUX4+uuvUVRU1Oz71uoEEs7WXtrxRD/LC56U2YmcGQslkQXKy8tx6tQplJeXN/u+f7qSj7zSKvi0ccGD3Sw/fCpldiJnxkJJ5CS+vHPYdez9QXBR8KNL1Fz4aSNyAjVaHb755c5h176chYqoObFQEjmB45fycLu8Bu08XDG0S1up4xC1KiyURBbw8PDA0KFD4eHh0az7PXCnNzm2dxCUVh52lSo7kbPj5SFEFvD29saYMWOadZ9ancDh8zkAgDH3B1m9HSmyE7UE7FESWaC6uhrXrl1DdXV1s+0z9Voh8kqr4eWmxNAu7azejhTZiVoCFkoiC+Tn52Pr1q3Iz89vtn0eOlfbmxzZKwCuSus/slJkJ2oJWCiJHFxiWm2hjL7PsinriMg2WCiJHNil3FJcySuDi0KGkT39pY5D1CqxUBI5sEPnake7Rnb1g5fKReo4RK0SCyWRBeRyOdq0aQO5vHk+OonnbHfYtbmzE7UUMiGEkDpEcyouLoZarUZRURG8vb2ljkPUoPzSKgxaeRhCAP+OewRBat6kmciWzK0H/GpJ5KCO/ZYHIYDwYG8WSSIJsVASWSA3NxfvvfcecnNz7b6vIxdq9zGih20G8TRndqKWhIWSyAJarRaFhYXQarV23Y9OJ/DDb3kAYLPRrs2VnailYaEkckBnbxShoKx2Np6IUF+p4xC1aiyURA7oyIVbAIDh3fx470kiifETSOSAjl68c36SkwwQSY6FksgCbdu2xfPPP4+2be13T8jb5dVIvXYbsOH5STRTdqKWiLfZIrKAm5sbunXrZtd9/PBbHnQC6BnohWC1u8222xzZiVoi9iiJLFBSUoIjR46gpKTEbvs4euf8pK3ndm2O7EQtEQslkQVKS0tx9OhRlJaW2mX7Qgj8eKm2UD5ko+sn69g7O1FLZVWhrKioQHl5uf751atXsW7dOhw6dMiW2Yhancu3ypBTXAVXpZyXhRA5CKsK5fjx4/Hxxx8DAG7fvo0hQ4bg73//O8aPH4/4+HhbZyRqNZIu104yMCjUFyoXhdRxiMjaQnn69GlERUUBAD777DMEBgbi6tWr+Pjjj/Hee+/ZOiNRq3H8Uj5w5/pJInIMVhXK8vJyeHl5AQAOHTqEp556CnK5HEOHDsXVq1ct2tb69esRFhYGlUqFiIgIHDt2zGT7qqoqLFmyBKGhoXBzc0PXrl2xdetWa94GkcVUKhX69OkDlcr2k5RrdQJJV2oLZWTXdjbfvj2zE7VkVl0e0q1bN3z++ed48skncfDgQSxatAi4M+myJbeu2rVrFxYuXIj169dj+PDh+PDDDxETE4Nz586hU6dORteZNGkScnJysGXLFnTr1g25ubnQaDTWvA0ii/n6+uKpp56yy7bPZxWjqKIGXm5K9O2gtvn27ZmdqCWzqke5dOlSvPLKK+jcuTOGDBmCyMhI4E7vcsCAAWZvZ+3atZg+fTpmzJiB8PBwrFu3DiEhIQ2e5zxw4ACOHj2KhIQEjB49Gp07d8bgwYMxbNgwa94GkcU0Gg0KCgrs8uXs+KXa85NDurSF0g7T1tkzO1FLZtWn8emnn0ZmZiZOnTqFAwcO6Jc/8sgj+Mc//mHWNqqrq5GcnIzo6GiD5dHR0Thx4oTRdfbv349BgwbhnXfeQYcOHdCjRw+88sorqKioaHA/VVVVKC4uNngQWevWrVv45z//iVu3btl828cv1x12tc/5SXtmJ2rJrJ6ZJygoCEFBQQbLBg8ebPb6eXl50Gq1CAwMNFgeGBiI7Oxso+tcuXIFP/74I1QqFfbt24e8vDzMnTsXBQUFDZ6nXL16NV5//XWzcxFJoVqjw3/SCwAAw7vZ/vwkEVnPqkI5atQoyGSyBl//7rvvzN7WvdsRQjS4bZ1OB5lMhk8//RRqde05nLVr1+Lpp5/GBx98AHf3+tN9xcXFITY2Vv+8uLgYISEhZucjag6p126jokaLdh6u6BnoJXUcIrqLVYWyf//+Bs9ramqQmpqKX375BVOnTjVrG35+flAoFPV6j7m5ufV6mXWCg4PRoUMHfZEEgPDwcAghcP36dXTv3r3eOm5ubnBzczPznRFJ48Sd6ycju7Yz+SWUiJqfVYWyofOQy5cvN3t6LFdXV0RERCAxMRFPPvmkfnliYiLGjx9vdJ3hw4dj9+7dKC0thaenJwDg4sWLkMvl6NixozVvhcgh/HSl9rCrPS4LIaKmkQkhhK02dunSJQwePBgFBQVmtd+1axemTJmCDRs2IDIyEhs3bsSmTZuQlpaG0NBQxMXF4caNG/pZgEpLSxEeHo6hQ4fi9ddfR15eHmbMmIERI0Zg06ZNZu2zuLgYarUaRUVFFl3KQmQv1Rod+r5+EJU1OhyOfQjdAnjolag5mFsPbHqbraSkJIsuZp48eTLy8/OxYsUKZGVloXfv3khISEBoaCgAICsrC5mZmfr2np6eSExMxPz58zFo0CC0a9cOkyZNwptvvmnLt0HUrM7eKEJljQ5tPVzR1d9T6jhEdA+rCuW9Fy0LIZCVlYVTp07htddes2hbc+fOxdy5c42+tm3btnrLevXqhcTERAsTE9lGXl4evvjiC4wfPx5+fra5jOM/GbVHYB7o7GvX85P2yE7UGlhVKO8eTAMAcrkcPXv2xIoVK+pdF0nUktTU1OD69euoqamx2TZPptcVyrY226Yx9shO1BpYVSg/+ugj2ychaoW0OqHvUQ4Os2+hJCLr8MbNRBK6kF2CkkoNPFwVuC+Yg8uIHJHZPUpfX/PPn5g76pWotavrTQ4M9bXL/K5E1HRmF8p169bZNwmRE/Dx8cGTTz4JHx8fm2yv7vzkkGY47Grr7ESthdmF0twZd4haMnd3d/Tt29cm2xJC4GRG8wzkgY2zE7UmVg3mufvaRmMaupckkbMrKytDWloa7r//fnh4eDRpWxn55bhVUgVXhRz9Quzfy7NldqLWxKpC2blzZ5PnK7VabVMyETms4uJifPPNNwgJCWlysam7W0i/EDVULgobJWyYLbMTtSZWFcqUlBSD5zU1NUhJScHatWuxcuVKW2UjatF+aqbrJ4moaawqlP369au3bNCgQWjfvj3efffdejP3EFF9yVdZKImcgU3Ho/fo0QP/+c9/bLlJohYpv7QKGfnlAICBnXyljkNEJljVoywuLjZ4XjfX6/Lly43eE5KopXB1dUXXrl3h6urapO2kZN4GAHT194C6jYuN0plmq+xErY1VhdLHx6feYB4hBEJCQrBz505bZSNyOO3atcMf/vCHJm8n5Voh0My9SVtlJ2ptrCqU33//vcFzuVwOf39/dOvWDUqlTe/cReRQdDodampq4OLiArnc+jMXp6/W9igHhjZfobRVdqLWxqqqNmLECNsnIXICOTk52LhxI2bOnIng4GCrtqHR6vDz9TuFshl7lLbITtQaWd39u3HjBo4fP47c3FzodDqD1xYsWGCLbEQt0oWcEpRXa+HlpkT3AN6omcjRWX2brdmzZ8PV1RXt2rUzOF8pk8lYKIlMOH1nIE//Tj6Qy+13o2Yisg2rCuXSpUuxdOlSxMXF8VwHkYVSrtYO5BnAy0KInIJVVa68vBzPPPMMiySRFU5n1o145V08iJyBVZVu+vTp2L17t+3TEDm4gIAAvPLKKwgICLBq/bsnGhgQ0rw9yqZmJ2qtrDr0unr1ajzxxBM4cOAA+vTpAxcXwwum165da6t8RA5FoVA0aULxuokGugV4NttEA3Wamp2otbKqUK5atQoHDx5Ez549gTsDeOqYuqsIkbMrKCjAwYMHMWbMGLRta/kcrVIedm1qdqLWyqpCuXbtWmzduhXTpk2zfSIiB1ZVVYWLFy9i5MiRVq3/30LZ/AN5mpqdqLWy6hylm5sbhg8fbvs0RC2YRqvDz9eKgGaekYeImsaqQvnyyy/jn//8p+3TELVgv2aXoKJGCy+VEt38OdGAtWQyGT7//PNm3ee0adMwYcKEZt0nOQ6rCuXJkyexfft2dOnSBePGjcNTTz1l8CCi+uqmresfwokGjJk2bRpkMhlkMhmUSiU6deqEOXPmoLCw0KBdVlYWYmJi7JIhIyMDMpkMqampBsv/93//F9u2bbPLPq2xfv16hIWFQaVSISIiAseOHWt0naNHjyIiIgIqlQpdunTBhg0bDF7ftGkToqKi4OvrC19fX4wePRonT56047twHlYVSh8fHzz11FMYMWIE/Pz8oFarDR5ELZWXlxeio6Ph5eVl8bo/X6stlP06SnP9ZFOyN5exY8ciKysLGRkZ2Lx5M7788kvMnTvXoE1QUBDc3NyaNZdarYaPj2Nc97pr1y4sXLgQS5YsQUpKCqKiohATE4PMzMwG10lPT8djjz2GqKgopKSk4K9//SsWLFiAPXv26NscOXIEzz77LL7//nskJSWhU6dOiI6Oxo0bN5rpnTkw0coUFRUJAKKoqEjqKNTKjPnHURH66lfi4C9ZUkdxSFOnThXjx483WBYbGyvatm1rsAyA2LdvnxBCiKqqKjFv3jwRFBQk3NzcRGhoqFi1apW+7e3bt8Wf/vQn4e/vL7y8vMSoUaNEampqgxkAGDxGjBhhNNuIESPESy+9JF5++WXh4+MjAgICxIcffihKS0vFtGnThKenp+jSpYtISEgw2H5aWpqIiYkRHh4eIiAgQPzhD38Qt27dsuj3NHjwYDF79myDZb169RKLFy9ucJ2//OUvolevXgbLZs2aJYYOHdrgOhqNRnh5eYnt27c36X0XFBSI5557Tvj5+QmVSiW6desmtm7datF7thdz6wGn1iGyQEVFBdLS0lBRUWHReuXVGlzMKQEA9AuRpmdibXapXLlyBQcOHKh3nfbd3nvvPezfvx//+te/cOHCBXzyySfo3LkzcOceuY8//jiys7ORkJCA5ORkDBw4EI888ggKCgqMbq/uUOPhw4eRlZWFvXv3Nrjv7du3w8/PDydPnsT8+fMxZ84c/P73v8ewYcNw+vRpjBkzBlOmTEF5ee0EE1lZWRgxYgT69++PU6dO4cCBA8jJycGkSZP029y2bZvJS+yqq6uRnJyM6Ohog+XR0dE4ceJEg+slJSXVW2fMmDE4deoUampqjK5TXl6OmpqaepcSWfq+X3vtNZw7dw7ffPMNzp8/j/j4ePj5+TWY1SGZW3kHDBggCgoKhBBC9O/fXwwYMKDBhyNjj5Ka4ubNm2L58uXi5s2bFq3305V8EfrqV2LIysN2y9YYa7M3l6lTpwqFQiE8PDyESqXS9+rWrl1r0O7uHuX8+fPFww8/LHQ6Xb3tffvtt8Lb21tUVlYaLO/atav48MMPjWZIT08XAERKSkq9bPf2KB988EH9c41GIzw8PMSUKVP0y7KysgQAkZSUJIQQ4rXXXhPR0dEG27127ZoAIC5cuCCEEGLv3r2iZ8+eDf6Obty4IQCI48ePGyxfuXKl6NGjR4Prde/eXaxcudJg2fHjxwWABv8e5s6dK7p27SoqKiqa9L7HjRsnXnzxxQazScncemD2dZTjx4/XnxcYP368zSYWWL9+Pd59911kZWXh/vvvx7p16xAVFdXoesePH8eIESPQu3fveifeiRxN3fnJvh15Dt+UUaNGIT4+HuXl5di8eTMuXryI+fPnN9h+2rRpePTRR9GzZ0+MHTsWTzzxhL7nlJycjNLSUrRr185gnYqKCly+fLnJWfv27av/WaFQoF27dujTp49+WWBgIAAgNzdXn+f777+Hp2f9Ec+XL19Gjx498OSTT+LJJ59sdN/3/vsrhGj032Rj6xhbDgDvvPMOduzYgSNHjkClUhm8Zun7njNnDiZOnIjTp08jOjoaEyZMwLBhwxp9j47E7EK5bNky/c/Lly+3yc7rTkqvX78ew4cPx4cffoiYmBicO3cOnTp1anC9oqIivPDCC3jkkUeQk5NjkyxE9lQ34lWqw67OwsPDA926dQPuHFYdNWoUXn/9dbzxxhtG2w8cOBDp6en45ptvcPjwYUyaNAmjR4/GZ599Bp1Oh+DgYBw5cqTeerYYmHPvIWGZTGawrK4A1d2vV6fTYdy4cXj77bfrbcvcG2n7+flBoVAgOzvbYHlubq6+QBkTFBRkdB2lUlnvi8SaNWuwatUqHD582KAo1rH0fcfExODq1av4+uuvcfjwYTzyyCOYN28e1qxZY9Z7dgRWnaPs0qUL8vPz6y2/ffs2unTpYvZ21q5di+nTp2PGjBkIDw/HunXrEBISgvj4eJPrzZo1C8899xwiIyOtiU/U7M5cr51oQKoRr85q2bJlWLNmDW7evNlgG29vb0yePBmbNm3Crl27sGfPHhQUFGDgwIHIzs6GUqlEt27dDB4NnSNzdXUFAGi1Wpu/l4EDByItLQ2dO3eul8fcOXhdXV0RERGBxMREg+WJiYkme2mRkZH11jl06BAGDRpkUOTeffddvPHGGzhw4AAGDRpk8XtsiL+/P6ZNm4ZPPvkE69atw8aNG2227eZgVaHMyMgw+odUVVWF69evm7UNa09Kf/TRR7h8+bJBD5eouSiVSgQFBUGpNH/2x4KyamQW1A5s6CPhoVdrsktt5MiRuP/++7Fq1Sqjr//jH//Azp078euvv+LixYvYvXs3goKC4OPjg9GjRyMyMhITJkzAwYMHkZGRgRMnTuBvf/sbTp06ZXR7AQEBcHd31w+0KSoqstl7mTdvHgoKCvDss8/i5MmTuHLlCg4dOoQ//vGP+n9P9+3bh169epncTmxsLDZv3oytW7fi/PnzWLRoETIzMzF79mx9m7i4OLzwwgv657Nnz8bVq1cRGxuL8+fPY+vWrdiyZQteeeUVfZt33nkHf/vb37B161Z07twZ2dnZyM7ORmlpaZPe99KlS/HFF1/g0qVLSEtLw1dffYXw8PAmbbO5WfSJ2b9/v/7ngwcPGlwzqdVq8e233yIsLMysbeXl5UGr1dY7XBAYGFjvEEGd3377DYsXL8axY8fM/rBXVVWhqqpK/7y4uNis9YiM8ff3x6xZsyxa58ydw65d/Dygdm/eO4bczZrsjiA2NhYvvvgiXn31VYSEhBi85unpibfffhu//fYbFAoFHnjgASQkJOjvlZuQkIAlS5bgj3/8I27duoWgoCA89NBDDR6mVCqVeO+997BixQosXboUUVFRRg/dWqN9+/Y4fvw4Xn31VYwZMwZVVVUIDQ3F2LFj9XmLiopw4cIFk9uZPHky8vPzsWLFCmRlZaF3795ISEhAaGiovk1WVpbBdZVhYWFISEjAokWL8MEHH6B9+/Z47733MHHiRH2b9evXo7q6Gk8//bTB/pYtW9ak022urq6Ii4tDRkYG3N3dERUVhZ07d1q9PUlYMkJIJpMJmUwm5HK5/ue6h6urq+jRo4f48ssvzdpW3eitEydOGCx/8803jY760mg0YtCgQSI+Pl6/bNmyZaJfv34m97Ns2bJ610Zx1Cs1p3WJF0Xoq1+JhTtTzGhNRM3FLtdR6nQ66HQ6dOrUCbm5ufrnOp0OVVVVuHDhAp544gmztmXpSemSkhKcOnUKL730EpRKJZRKJVasWIGff/4ZSqUS3333ndH9xMXFoaioSP+4du2aJW+ZyEBWVhbefPNNZGVlmb1OXY9S6hGv1mQnIgvPUf7000/45ptvkJ6erj8Z/vHHHyMsLAwBAQGYOXOmwWFOUyw9Ke3t7Y2zZ88iNTVV/5g9ezZ69uyJ1NRUDBkyxOh+3Nzc4O3tbfAgagpLBnoIIRxqxKs9BqkQtXQWnaNctmwZRo0apZ+Q+OzZs5g+fTqmTZuG8PBwvPvuu2jfvr3Zx7NjY2MxZcoUDBo0CJGRkdi4caPBSem4uDjcuHEDH3/8MeRyOXr37m2wfkBAAFQqVb3lRI7iZlEl8kqroZTLcF8wv6QROSOLCuXPP/+MN998U/98586dGDJkCDZt2gQACAkJsejEb2Mnpe89IU3kbOomGugV7AWVi0LqOERkBYsKZWFhocH5w6NHj2Ls2LH65w888IDF5wDnzp1b7+4AdRq7rc3y5cttNvkBkT38rD8/Kf1hVyKyjkXnKAMDA5Geng7cuQ7y9OnTBhf9l5SUmJzAmMjZ+fn5Yc6cOWZP6vzfW2tJP3WdpdmJqJZFhXLs2LH66xjj4uLQpk0bg3lZz5w5g65du9ojJ5FDcHFxQUBAgFlfCHU6gV9u1F636wgDeSzJTkT/ZVGhfPPNN6FQKDBixAhs2rQJmzZt0k/5BABbt26tN9MOUUty+/Zt7N+/H7dv32607ZW8UpRWaeDuokA3//oTYTc3S7IT0X9ZdI7S398fx44dQ1FRETw9PaFQGA5O2L17t9GZ8YlaioqKCqSkpOCBBx5odGLt1Gu105/16aCGUiH9rV8tyU5E/2XVpI93T113t3tv8EnUmjnKRANE1DTSf80laqH0A3kc4PwkEVmPhZLIDqo0WpzPKgF4ay0ip8dCSWQBDw8PDB8+vNH7B/6aVYJqrQ6+bVwQ0ta92fKZYm52IjLkPDemI3IA3t7eGD16dKPtztyoHcjTt6OP/o7vUjM3OxEZYo+SyAJVVVXIyMhodPL/M9ccbyCPudmJyBALJZEFCgoKsH37dhQUFJhsd/auHqWjMDc7ERlioSSysfJqDS7m1A7kcaQeJRFZh4WSyMbSbhZDJ4BAbzcEequkjkNETcRCSWRjZ67XzcjjOIddich6LJREFpDL5fDy8oJc3vBHp25GHke4Y8jdzMlORPXx8hAiCwQGBiI2NtZkm7N1PUoHK5TmZCei+vjVksiGiipqcCWvDHCwEa9EZD0WSiIL5OTkYO3atcjJyTH6etqdy0I6+rqjrYer0TZSaSw7ERnHQklkAZ1Oh5KSEuh0OqOv/3znsKsjzu/aWHYiMo6FksiGeGstopaHhZLIhs446EAeIrIeCyWRjeSXVuHG7QoAQJ8OLJRELQULJZEF2rZti6lTp6Jt27b1Xqu7Y0gXfw94qVwkSGeaqexE1DBeR0lkATc3N3Tu3Nnoa2euOe5AHjSSnYgaxh4lkQWKi4tx+PBhFBcX13vt7I3agTyOetjVVHYiahgLJZEFysrKcPz4cZSVlRksF0L899KQEMcslA1lJyLTWCiJbCCnuAq3SqqgkMtwX7BjFkoisg4LJZEN/Hzn+snuAZ5wd1VIHYeIbIiFksgGONEAUcvFQklkAXd3dwwYMADu7u4Gy+smGnDkidAbyk5EpvHyECIL+Pj44He/+53BMiEEzt6oK5SO26M0lp2IGid5j3L9+vUICwuDSqVCREQEjh071mDbvXv34tFHH4W/vz+8vb0RGRmJgwcPNmteat1qamqQm5uLmpoa/bJrBRW4XV4DV4UcvYK8Jc1nirHsRNQ4SQvlrl27sHDhQixZsgQpKSmIiopCTEwMMjMzjbb/4Ycf8OijjyIhIQHJyckYNWoUxo0bh5SUlGbPTq1TXl4e4uPjkZeXp19WN5AnPNgLrkrJv3s2yFh2ImqcpJ/qtWvXYvr06ZgxYwbCw8Oxbt06hISEID4+3mj7devW4S9/+QseeOABdO/eHatWrUL37t3x5ZdfNnt2ojp1A3k4ETpRyyRZoayurkZycjKio6MNlkdHR+PEiRNmbaPu/nqm5q6sqqpCcXGxwYPIllIyawtl/xBfqaMQkR1IVijz8vKg1WoRGBhosDwwMBDZ2dlmbePvf/87ysrKMGnSpAbbrF69Gmq1Wv8ICQlpcnaiOjVanX4gz4BOjjvilYisJ/kJFZlMZvBcCFFvmTE7duzA8uXLsWvXLgQEBDTYLi4uDkVFRfrHtWvXbJKbWi+F4r8TCvyaVYIqjQ7eKiXC2nlImsscd2cnIvNIdnmIn58fFApFvd5jbm5uvV7mvXbt2oXp06dj9+7dGD16tMm2bm5ucHNzs0lmouDgYPztb3/TP0+9VggA6N/JF3J541/wpHRvdiIyj2Q9SldXV0RERCAxMdFgeWJiIoYNG9bgejt27MC0adPw//7f/8Pjjz/eDEmJGvbf85M87ErUUkl66DU2NhabN2/G1q1bcf78eSxatAiZmZmYPXs2cOew6QsvvKBvv2PHDrzwwgv4+9//jqFDhyI7OxvZ2dkoKiqS8F1Qa3Lr1i18+OGHuHXrFgAg9VptoXSG85P3Zici80g6M8/kyZORn5+PFStWICsrC71790ZCQgJCQ0MBAFlZWQbXVH744YfQaDSYN28e5s2bp18+depUbNu2TZL3QK2LRqNBdnY2NBoNbpdX40pe7S2r+jvw1HV17s5OROaTfAq7uXPnYu7cuUZfu7f4HTlypJlSETWurjcZ5ucBXw9XqeMQkZ1IPuqVyFnx/CRR68BCSWSluh4lCyVRy8ZCSWQBHx8fPP3001Cr1U41kAd3ZffxcY68RI6ChZLIAu7u7rj//vuRXaZDUUUNXJWOfceQu9Vl5/0oiSzDQklkgdLSUiQlJSHpYu1EGX06qB36jiF3q8teWloqdRQip+Icn3AiB1FSUoJDhw7hpyu1t6oa1Nl5JkKvy15SUiJ1FCKnwkJJZIXUm7W9sgdCG75zDRG1DCyURBaqFEpkFlYBACJCnadHSUTWYaEkslCOzhMA0D3AkxMNELUCLJREFnBzc0ONuvaepg+EOddhVzc3N/To0YN30yGykORT2BE5k7Zt26JYFQjgNh5wooE8uJP92WeflToGkdNhj5LIAiUVVUi7UXu3mkFONpBHq9WirKwMWq1W6ihEToWFksgCR89ehUYnEODpgo6+znXhfm5uLtasWYPc3FypoxA5FRZKIguk3Ki9BrFfe0/IZDKp4xBRM2ChJLLAqWu1hTIixEvqKETUTFgoicxUVqXBL9m1N2oexEJJ1GqwUBKZ6WRGAbQ6wFNWhQ5qXmJB1Frw8hAiM524VDu/a8yAMAQGBkodx2KBgYFYvHgxXFxcpI5C5FRYKInMdPxSPgAgqmcg5HLnOxgjl8s52QCRFZzv004kgYKyapzLKgYA3Ez5Hvn5+VJHslh+fj4++eQTp8xOJCUWSiIz/HDxFgCgu587cq5eQnV1tdSRLFZdXY3Lly87ZXYiKbFQEpnh8PkcAMDwMLXUUYiombFQEjWiRqvD0Ts9ShZKotaHhZKoEf/JKEBJpQbtPFwRHthG6jhE1MxYKIkacfhc7dyoo3oFwNdHjZiYGHh7e0sdy2Le3t5Om51ISrw8hMgErU7g67M3AQDR9wXCw8MDgwcPljqWVZw5O5GU2KMkMuFkegFyiqvgrVJiRE9/VFRU4MyZM6ioqJA6msWcOTuRlFgoiUzY//MNAMBjfYLhplTg9u3b2LdvH27fvi11NIs5c3YiKbFQEjWgskaLr89kAQB+17+91HGISCIslEQN+CL1BoorNejg444hYe2kjkNEEmGhJDJCCIGPjmcAAKYOC4VCzps0E7VWkhfK9evXIywsDCqVChERETh27JjJ9kePHkVERARUKhW6dOmCDRs2NFtWaj0O/JKNX7NL4O6iwKRBIfrlLi4u6Nixo1PegcOZsxNJSdJCuWvXLixcuBBLlixBSkoKoqKiEBMTg8zMTKPt09PT8dhjjyEqKgopKSn461//igULFmDPnj3Nnp1arsoaLd4+8CsA4E9RYfBp46p/zc/PD9OnT4efn5+ECa3jzNmJpCQTQgipdj5kyBAMHDgQ8fHx+mXh4eGYMGECVq9eXa/9q6++iv379+P8+fP6ZbNnz8bPP/+MpKQks/ZZXFwMtVqNoqIiXnhN9Wh1Aq/uOYPPkq/Dz9MNR/48Ep5uvNyYqCUytx5I9i9AdXU1kpOTsXjxYoPl0dHROHHihNF1kpKSEB0dbbBszJgx2LJlC2pqaoweUqqqqkJVVZX+eXFxcdOza3QY988fzWorYP73EEu+sljy7cbc70IWfWOSOKsl27Xk91papUFBWTVkMuDvk/rVK5JZWVnYuHEjZs6cieDgYPM37ACcOTuRlCQrlHl5edBqtfXuFB8YGIjs7Gyj62RnZxttr9FokJeXZ/TDv3r1arz++us2zS4gcCGnxKbbJMfh5abEqqf6YEQPf6mjEJEDkPyYkkxmOJpQCFFvWWPtjS2vExcXh9jYWP3z4uJihISEGG1rLhe5HJ/OGGJWW7PHSprZUGZmQxO/Qmt2a/L/iX33a7utmbMtGYDugV483EpEepL9a+Dn5weFQlGv95ibm1uv11gnKCjIaHulUol27Yxf5+bm5gY3NzcbJgfkchmGd+OACCKi1kCyUa+urq6IiIhAYmKiwfLExEQMGzbM6DqRkZH12h86dAiDBg3ikHciIrILSUe97tq1C1OmTMGGDRsQGRmJjRs3YtOmTUhLS0NoaCji4uJw48YNfPzxx8Cdy0N69+6NWbNm4U9/+hOSkpIwe/Zs7NixAxMnTjRrnxz1Sk2h0WhQXFwMb29vKJXOdXjWmbMT2YPDj3oFgMmTJyM/Px8rVqxAVlYWevfujYSEBISGhgJ3RundfU1lWFgYEhISsGjRInzwwQdo37493nvvPbOLJFFTKZVKtG3bVuoYVnHm7ERSkrRHKQX2KKkpCgsL8f3332PUqFHw9fWVOo5FnDk7kT2YWw8kn8KOyJlUVlbi7NmzqKyslDqKxZw5O5GUWCiJiIhMYKEkIiIyodUNfas7JWuLqeyo9SkpKUFlZSVKSkrg4eEhdRyLOHN2InuoqwONDdVpdYN5rl+/3uSZeYiIqOW4du0aOnbs2ODrra5Q6nQ63Lx5E15eXmZPyyaFuqn2rl275lSjc501N5hdMswuDWav7UmWlJSgffv2kMsbPhPZ6g69yuVyk98cHI23t7fT/RHDiXOD2SXD7NJo7dnVanWjbTiYh4iIyAQWSiIiIhNYKB2Um5sbli1bZvM7n9ibs+YGs0uG2aXB7OZrdYN5iIiILMEeJRERkQkslERERCawUBIREZnAQklERGQCC6VECgsLMWXKFKjVaqjVakyZMgW3b982uY4QAsuXL0f79u3h7u6OkSNHIi0trcG2MTExkMlk+Pzzzx0+e0FBAebPn4+ePXuiTZs26NSpExYsWICioqImZV2/fj3CwsKgUqkQERGBY8eOmWx/9OhRREREQKVSoUuXLtiwYUO9Nnv27MF9990HNzc33Hfffdi3b1+TMjZX9k2bNiEqKgq+vr7w9fXF6NGjcfLkSafIfredO3dCJpNhwoQJdkhun+y3b9/GvHnzEBwcDJVKhfDwcCQkJDhF9nXr1qFnz55wd3dHSEgIFi1aZJdbtVmSPSsrC8899xx69uwJuVyOhQsXGm1ns8+qIEmMHTtW9O7dW5w4cUKcOHFC9O7dWzzxxBMm13nrrbeEl5eX2LNnjzh79qyYPHmyCA4OFsXFxfXarl27VsTExAgAYt++fQ6f/ezZs+Kpp54S+/fvF5cuXRLffvut6N69u5g4caLVOXfu3ClcXFzEpk2bxLlz58TLL78sPDw8xNWrV422v3LlimjTpo14+eWXxblz58SmTZuEi4uL+Oyzz/RtTpw4IRQKhVi1apU4f/68WLVqlVAqleLf//631TmbK/tzzz0nPvjgA5GSkiLOnz8vXnzxRaFWq8X169cdPnudjIwM0aFDBxEVFSXGjx9v09z2yl5VVSUGDRokHnvsMfHjjz+KjIwMcezYMZGamurw2T/55BPh5uYmPv30U5Geni4OHjwogoODxcKFCyXNnp6eLhYsWCC2b98u+vfvL15++eV6bWz5WWWhlMC5c+cEAIP/YUlJSQKA+PXXX42uo9PpRFBQkHjrrbf0yyorK4VarRYbNmwwaJuamio6duwosrKybF4o7Z39bv/617+Eq6urqKmpsSrr4MGDxezZsw2W9erVSyxevNho+7/85S+iV69eBstmzZolhg4dqn8+adIkMXbsWIM2Y8aMEc8884xVGZsz+700Go3w8vIS27dvt1HqWvbKrtFoxPDhw8XmzZvF1KlT7VIo7ZE9Pj5edOnSRVRXV9s8793skX3evHni4YcfNmgTGxsrHnzwQUmz323EiBFGC6UtP6s89CqBpKQkqNVqDBkyRL9s6NChUKvVOHHihNF10tPTkZ2djejoaP0yNzc3jBgxwmCd8vJyPPvss3j//fcRFBTkVNnvVVRUBG9vbyiVlk9JXF1djeTkZIN9AkB0dHSD+0xKSqrXfsyYMTh16hRqampMtjH1Phwl+73Ky8tRU1ODtm3bOkX2FStWwN/fH9OnT7dZ3ubIvn//fkRGRmLevHkIDAxE7969sWrVKmi1WofP/uCDDyI5OVl/iP7KlStISEjA448/Lml2c9jys9rqJkV3BNnZ2QgICKi3PCAgANnZ2Q2uAwCBgYEGywMDA3H16lX980WLFmHYsGEYP368zXPDztnvlp+fjzfeeAOzZs2yKmdeXh60Wq3RfZrKaay9RqNBXl4egoODG2zT0DYdKfu9Fi9ejA4dOmD06NEOn/348ePYsmULUlNTbZa1ubJfuXIF3333HZ5//nkkJCTgt99+w7x586DRaLB06VKHzv7MM8/g1q1bePDBByGEgEajwZw5c7B48WKb5LY2uzls+Vllj9KGli9fDplMZvJx6tQpADB6iy8hRKO3/rr39bvX2b9/P7777jusW7fO6bLfrbi4GI8//jjuu+8+LFu2zOL3Ys0+TbW/d7ml27SWPbLXeeedd7Bjxw7s3bsXKpXKZplNZbE2e0lJCf7whz9g06ZN8PPzs3lWc7I05feu0+kQEBCAjRs3IiIiAs888wyWLFmC+Ph4h89+5MgRrFy5EuvXr8fp06exd+9efPXVV3jjjTckz96c22SP0oZeeuklPPPMMybbdO7cGWfOnEFOTk69127dulXvG1CdusOo2dnZBr2D3Nxc/TrfffcdLl++DB8fH4N1J06ciKioKBw5csRhs9cpKSnB2LFj4enpiX379sHFxcVkpob4+flBoVDU+/ZobJ935zTWXqlUol27dibbNLRNR8peZ82aNVi1ahUOHz6Mvn372iy3vbKnpaUhIyMD48aN07+u0+kAAEqlEhcuXEDXrl0dMjsABAcHw8XFBQqFQt8mPDwc2dnZqK6uhqurq8Nmf+211zBlyhTMmDEDANCnTx+UlZVh5syZWLJkicl7ONozuzls+Vllj9KG/Pz80KtXL5MPlUqFyMhIFBUVGQzN/+mnn1BUVIRhw4YZ3XZYWBiCgoKQmJioX1ZdXY2jR4/q11m8eDHOnDmD1NRU/QMA/vGPf+Cjjz5y6Oy405OMjo6Gq6sr9u/f36SejqurKyIiIgz2CQCJiYkN5oyMjKzX/tChQxg0aJC+YDfUpqFtOlJ2AHj33Xfxxhtv4MCBAxg0aJDNMtsze69evXD27FmDv+vf/e53GDVqFFJTUxESEuKw2QFg+PDhuHTpkr64A8DFixcRHBxskyJpz+zl5eX1iqFCocCdgaCSZTeHTT+rFg//IZsYO3as6Nu3r0hKShJJSUmiT58+9S6x6Nmzp9i7d6/++VtvvSXUarXYu3evOHv2rHj22WcbvDykjr0uD7F19uLiYjFkyBDRp08fcenSJZGVlaV/aDQaq3LWDTnfsmWLOHfunFi4cKHw8PAQGRkZQgghFi9eLKZMmaJvXzdcftGiReLcuXNiy5Yt9YbLHz9+XCgUCvHWW2+J8+fPi7feesuul4fYMvvbb78tXF1dxWeffWbw+y0pKXH47Pey16hXe2TPzMwUnp6e4qWXXhIXLlwQX331lQgICBBvvvmmw2dftmyZ8PLyEjt27BBXrlwRhw4dEl27dhWTJk2SNLsQQqSkpIiUlBQREREhnnvuOZGSkiLS0tL0r9vys8pCKZH8/Hzx/PPPCy8vL+Hl5SWef/55UVhYaNAGgPjoo4/0z3U6nVi2bJkICgoSbm5u4qGHHhJnz541uR97FEp7ZP/+++8FAKOP9PR0q7N+8MEHIjQ0VLi6uoqBAweKo0eP6l+bOnWqGDFihEH7I0eOiAEDBghXV1fRuXNnER8fX2+bu3fvFj179hQuLi6iV69eYs+ePVbna87soaGhRn+/y5Ytc/js97JXobRX9hMnToghQ4YINzc30aVLF7Fy5UqrvwA2Z/aamhqxfPly0bVrV6FSqURISIiYO3duvc+7FNmN/S2HhoYatLHVZ5W32SIiIjKB5yiJiIhMYKEkIiIygYWSiIjIBBZKIiIiE1goiYiITGChJCIiMoGFkoiIyAQWSiIiIhNYKIkczPLly9G/f3/J9v/aa69h5syZdtt+bm4u/P39cePGDbvtg8iWODMPUTNq7BY/U6dOxfvvv4+qqqp6d/1oDjk5OejevTvOnDmDzp07220/sbGxKC4uxubNm+22DyJbYaEkakZ33/Zn165dWLp0KS5cuKBf5u7uDrVaLVE6YNWqVTh69CgOHjxo1/2cPXsWgwcPxs2bN+Hr62vXfRE1FQ+9EjWjoKAg/UOtVkMmk9Vbdu+h12nTpmHChAlYtWoVAgMD4ePjg9dffx0ajQZ//vOf0bZtW3Ts2BFbt2412NeNGzcwefJk+Pr6ol27dhg/fjwyMjJM5tu5cyd+97vfGSwbOXIk5s+fj4ULF8LX1xeBgYHYuHEjysrK8OKLL8LLywtdu3bFN998o1+nsLAQzz//PPz9/eHu7o7u3bsb3OqtT58+CAoKwr59+2zwWyWyLxZKIifw3Xff4ebNm/jhhx+wdu1aLF++HE888QR8fX3x008/Yfbs2Zg9ezauXbsG3LmP4KhRo+Dp6YkffvgBP/74Izw9PTF27FhUV1cb3UdhYSF++eUXo/ep3L59O/z8/HDy5EnMnz8fc+bMwe9//3sMGzYMp0+fxpgxYzBlyhSUl5cDd85znjt3Dt988w3Onz+P+Ph4+Pn5GWxz8ODBOHbsmF1+X0Q2ZdU9R4ioyT766COhVqvrLV+2bJno16+f/vnUqVNFaGio0Gq1+mU9e/YUUVFR+ucajUZ4eHiIHTt2CCGE2LJli+jZs6fQ6XT6NlVVVcLd3V0cPHjQaJ6UlBQBQGRmZhosHzFihHjwwQfr7evu+wNmZWUJACIpKUkIIcS4cePEiy++aPL9L1q0SIwcOdJkGyJHoJS6UBNR4+6//36DO80HBgaid+/e+ucKhQLt2rVDbm4uACA5ORmXLl2Cl5eXwXYqKytx+fJlo/uoqKgAAKhUqnqv9e3bt96++vTpY5AHd0a0AsCcOXMwceJEnD59GtHR0ZgwYUK9O8u7u7vre6BEjoyFksgJuLi4GDyXyWRGl+l0OgCATqdDREQEPv3003rb8vf3N7qPukOjhYWF9do0tv+60bx1+4+JicHVq1fx9ddf4/Dhw3jkkUcwb948rFmzRr9OQUFBg1mIHAnPURK1QAMHDsRvv/2GgIAAdOvWzeDR0Kjarl27wtvbG+fOnbNJBn9/f0ybNg2ffPIJ1q1bh40bNxq8/ssvv2DAgAE22ReRPbFQErVAzz//PPz8/DB+/HgcO3YM6enpOHr0KF5++WVcv37d6DpyuRyjR4/Gjz/+2OT9L126FF988QUuXbqEtLQ0fPXVVwgPD9e/Xl5ejuTkZERHRzd5X0T2xkJJ1AK1adMGP/zwAzp16oSnnnoK4eHh+OMf/4iKigp4e3s3uN7MmTOxc+dO/SFUa7m6uiIuLg59+/bFQw89BIVCgZ07d+pf/+KLL9CpUydERUU1aT9EzYETDhCRnhACQ4cOxcKFC/Hss8/abT+DBw/GwoUL8dxzz9ltH0S2wh4lEenJZDJs3LgRGo3GbvvIzc3F008/bddCTGRL7FESERGZwB4lERGRCSyUREREJrBQEhERmcBCSUREZAILJRERkQkslERERCawUBIREZnAQklERGQCCyUREZEJ/x+MsEH42liOUgAAAABJRU5ErkJggg==", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "t = np.linspace(-0.05, 0.1, 1000)\n", + "\n", + "def bessel2_step(t, x):\n", + " theta = 1 * (t >= 0)\n", + " s = np.sqrt(3)\n", + " t = t / 2 * x\n", + " return theta * (1 - (s * np.sin(s*t) + np.cos(s*t)) * np.exp(-3*t))\n", + "\n", + "f = 78.8\n", + "y = bessel2_step(t, f)\n", + "\n", + "t10 = fmin(lambda x: (bessel2_step(x, f) - 0.1)**2, 0.01, disp=False)[0]\n", + "t90 = fmin(lambda x: (bessel2_step(x, f) - 0.9)**2, 0.02, disp=False)[0]\n", + "\n", + "print('Time, filter value')\n", + "print(t10, bessel2_step(t10, f))\n", + "print(t90, bessel2_step(t90, f))\n", + "\n", + "fig = plt.figure(figsize=(5, 3))\n", + "ax = fig.add_subplot()\n", + "ax.update(dict(xlabel='Time (ms)', ylabel='Stimulus'))\n", + "ax.axvline(t10, color='grey', ls='--', lw=1)\n", + "ax.axvline(t90, color='grey', ls='--', lw=1)\n", + "ax.plot(t, y)\n", + "ax.text(0.04, 0.4, f'Rise time: {t90 - t10:.5}ms')\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "ec352afe-15bf-47c6-b807-08dda17e8432", + "metadata": {}, + "source": [ + "## 2. Comparing with measured values\n", + "\n", + "The HEKA EPC-9 has a [paper describing its hardware](), which contains a nice block diagram (Fig 1).\n", + "This shows us that\n", + "\n", + "1. The stimulus filter is applied to the command potential before any other additions (e.g. Cm and Rs compensation)\n", + "2. The \"V monitor\" is read directly from the stimulus filter output, again without any interference from other components.\n", + "\n", + "As a result, we should be able to see the effects of the stimulus filter on a recorded \"V monitor\" signal." + ] + }, + { + "cell_type": "markdown", + "id": "366e277f-efb2-4326-9ec1-9149a4e45c9b", + "metadata": {}, + "source": [ + "Below is a recording made using an EPC-10:" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "28bc68e8-3152-428e-b7ae-56f030c1a6bb", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import myokit\n", + "d = myokit.DataLog.load('./res/stimulus-filter.zip')\n", + "d = d.npview()\n", + "\n", + "fig = plt.figure(figsize=(8, 3))\n", + "fig.subplots_adjust(0.14, 0.15, 0.96, 0.98)\n", + "ax = fig.add_subplot()\n", + "ax.set_xlabel('Time (ms)')\n", + "ax.set_ylabel('Command voltage (mV)')\n", + "\n", + "ax.plot(d.time(), d['v20us'], 's-', label='Recording')\n", + "\n", + "t = d.time()\n", + "y = -100 + 200 * bessel2_step(t - 1, 78.8)\n", + "ax.plot(t, y, label=r'Rise time 20$\\mu$s')\n", + "y = -100 + 200 * bessel2_step(t - 1, 78.8 / 2)\n", + "ax.plot(t, y, label=r'Rise time 40$\\mu$s')\n", + "\n", + "ax.legend()\n", + "ax.set_xlim(0.97, 1.12)\n", + "plt.show()" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "bf5acb58-1e78-45f5-87f3-ec480feb2cd1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0.03943750000000005\n" + ] + } + ], + "source": [ + "f = 40\n", + "t10 = fmin(lambda x: (bessel2_step(x, f) - 0.1)**2, 0.01, disp=False)[0]\n", + "t90 = fmin(lambda x: (bessel2_step(x, f) - 0.9)**2, 0.02, disp=False)[0]\n", + "assert abs(bessel2_step(t10, f) - 0.1) < 1e-2\n", + "assert abs(bessel2_step(t90, f) - 0.9) < 1e-2\n", + "print(t90 - t10)" + ] + }, + { + "cell_type": "markdown", + "id": "ca357231-a3f2-45e0-9b7e-75f55db23f4e", + "metadata": {}, + "source": [ + "It seems the rise time is roughly twice what is advertised." + ] + }, + { + "cell_type": "markdown", + "id": "0a9102d0-4c65-4135-956f-c2c98aa56c8d", + "metadata": {}, + "source": [ + "## 3. Fitting rise times\n", + "\n", + "To fit the data, we start by writing the model in ODE form using Myokit, and comparing with recorded data for the 2$\\mu$s and 20$\\mu$s settings.\n", + "\n", + "This means we need to specify a value for the filter's scaling factor $\\alpha$.\n", + "For other filters, we've related this to cut-off frequency, but to stay closer to the amplifier settings, we'll try to relate it to rise time instead.\n", + "And to simplify this, we will use the equation for **first order** rise time:\n", + "\n", + "\\begin{align}\n", + "\\alpha \\approx \\frac{1.3616}{\\log 9} t_r\n", + "\\end{align}\n" + ] + }, + { + "cell_type": "code", + "execution_count": 24, + "id": "2ca45865-f842-492c-8a18-9e65f7f65e0c", + "metadata": {}, + "outputs": [], + "source": [ + "m = myokit.parse_model(\"\"\"\n", + "[[model]]\n", + "filter.y1 = 0\n", + "filter.y2 = 0\n", + "\n", + "[filter]\n", + "pace = 0 bind pace\n", + "time = 0 bind time\n", + "tr = 0.04 [ms] in [ms]\n", + "a2 = tr * 1.3616 / log(9)\n", + " in [ms]\n", + "dot(y1) = 3 * (pace/a2^2 - y2/a2^2 - y1/a2)\n", + "dot(y2) = y1\n", + "\"\"\")" + ] + }, + { + "cell_type": "markdown", + "id": "4e43df05-ebf9-40ea-9dad-60be3312ca57", + "metadata": {}, + "source": [ + "Next, we set up the same experiment we performed on a real amplifier, and compare the results **using our guesses of two times the given value**, and **using the first order rise time approximation**." + ] + }, + { + "cell_type": "code", + "execution_count": 28, + "id": "96673271-b5c9-4a78-81fb-659ae88912af", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(10, 3))\n", + "fig.subplots_adjust(0.14, 0.15, 0.96, 0.98)\n", + "\n", + "ax = fig.add_subplot(1, 2, 1)\n", + "ax.set_xlabel('Time (ms)')\n", + "ax.set_ylabel('Command voltage (mV)')\n", + "ax.plot(d0.time(), d0['v20us'], 's-', label=r'Recording, 20$\\mu$s')\n", + "ax.plot(d1.time(), d1['filter.y2'], label=r'Simulation, tr=40 $\\mu$s')\n", + "ax.legend()\n", + "ax.set_xlim(0.98, 1.12)\n", + "\n", + "ax = fig.add_subplot(1, 2, 2)\n", + "ax.set_xlabel('Time (ms)')\n", + "ax.plot(d0.time(), d0['v2us'], 's-', label=r'Recording, 2$\\mu$s')\n", + "ax.plot(d1.time(), d2['filter.y2'], label=r'Simulation, tr=4 $\\mu$s')\n", + "ax.legend()\n", + "ax.set_xlim(0.99, 1.03)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "6ee9f1a9-5159-4b91-b33f-dc4a098f0160", + "metadata": {}, + "source": [ + "This fits very well! \n", + "\n", + "But we can use an optimiser to find the best approximations:" + ] + }, + { + "cell_type": "code", + "execution_count": 29, + "id": "3251fa45-5ba1-40fb-b315-429cd58a5fff", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Rise time 0.03838024902343749 ms\n" + ] + } + ], + "source": [ + "from scipy.optimize import fmin\n", + "\n", + "def error(tr):\n", + " s.reset()\n", + " s.set_constant('filter.tr', tr[0])\n", + " d = s.run(2, log_times=d0.time())\n", + " return np.sum((d0['v20us'] - d['filter.y2'])**2)\n", + "\n", + "tr2slow = fmin(error, 0.04, disp=False)[0]\n", + "print(f'Rise time {tr2slow} ms')\n", + "\n", + "s.set_constant('filter.tr', tr2slow)\n", + "s.reset()\n", + "s.pre(1)\n", + "d1 = s.run(2, log_interval=1e-3).npview()" + ] + }, + { + "cell_type": "code", + "execution_count": 30, + "id": "494ab669-799b-4834-af64-23ce6dc94b68", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Rise time 0.005369531250000004 ms\n" + ] + } + ], + "source": [ + "def error(tr):\n", + " s.reset()\n", + " s.set_constant('filter.tr', tr[0])\n", + " d = s.run(2, log_times=d0.time())\n", + " return np.sum((d0['v2us'] - d['filter.y2'])**2)\n", + "\n", + "tr2fast = fmin(error, 0.004, disp=False)[0]\n", + "print(f'Rise time {tr2fast} ms')\n", + "\n", + "s.set_constant('filter.tr', tr2fast)\n", + "s.reset()\n", + "s.pre(1)\n", + "d2 = s.run(2, log_interval=1e-3).npview()" + ] + }, + { + "cell_type": "markdown", + "id": "d0c44aa4-304e-453b-8ae3-966f99a4a6cd", + "metadata": {}, + "source": [ + "Summing up, in the two-pole formulation\n", + "\n", + "**The 20$\\mu$s setting is replicated by `tr=0.03838[ms]` or `tr=0.04[ms]`.**\n", + "\n", + "**The 2$\\mu$s setting is replicated by `tr=0.005369[ms]` or `tr=0.005[ms]`.**" + ] + }, + { + "cell_type": "markdown", + "id": "e3a94057-262f-4645-a459-dd9d21ef64a9", + "metadata": {}, + "source": [ + "## 4. A first order approximation\n", + "\n", + "Finally, we approximate with a 1-pole filter, and perform the same fits." + ] + }, + { + "cell_type": "code", + "execution_count": 31, + "id": "2c2ec42d-aae2-4592-8faf-4e7c19776c65", + "metadata": {}, + "outputs": [], + "source": [ + "m = myokit.parse_model(\"\"\"\n", + "[[model]]\n", + "filter.y1 = 0\n", + "filter.y2 = 0\n", + "filter.y3 = 0\n", + "\n", + "[filter]\n", + "pace = 0 bind pace\n", + "time = 0 bind time\n", + "tr = 0.04 [ms] in [ms]\n", + "# Second-order\n", + "a2 = tr * 1.3616 / log(9)\n", + " in [ms]\n", + "dot(y1) = 3 * (pace/a2^2 - y2/a2^2 - y1/a2)\n", + "dot(y2) = y1\n", + "# First-order\n", + "a1 = tr / log(9)\n", + " in [ms]\n", + "dot(y3) = (pace - y3) / a1\n", + "\"\"\")\n", + "\n", + "p = myokit.Protocol()\n", + "p.add_step(level=-100, duration=1)\n", + "p.add_step(level=100, duration=10)\n", + "\n", + "s = myokit.Simulation(m, p)\n", + "s.pre(1)\n", + "d1 = s.run(2, log_interval=1e-3).npview()\n", + "\n", + "s.reset()\n", + "s.set_constant('filter.tr', 0.004)\n", + "s.pre(1)\n", + "d2 = s.run(2, log_interval=1e-3).npview()" + ] + }, + { + "cell_type": "code", + "execution_count": 32, + "id": "81ffda3f-c3e5-40a0-b086-8189f4ed6384", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "fig = plt.figure(figsize=(10, 3))\n", + "fig.subplots_adjust(0.14, 0.15, 0.96, 0.98)\n", + "\n", + "ax = fig.add_subplot(1, 2, 1)\n", + "ax.set_xlabel('Time (ms)')\n", + "ax.set_ylabel('Command voltage (mV)')\n", + "ax.plot(d0.time(), d0['v20us'], 's-', label=r'Recording, 20$\\mu$s')\n", + "ax.plot(d1.time(), d1['filter.y2'], label=r'Simulation, n=2, tr=40 $\\mu$s')\n", + "ax.plot(d1.time(), d1['filter.y3'], label=r'Simulation, n=1, tr=40 $\\mu$s')\n", + "ax.legend()\n", + "ax.set_xlim(0.98, 1.12)\n", + "\n", + "ax = fig.add_subplot(1, 2, 2)\n", + "ax.set_xlabel('Time (ms)')\n", + "ax.plot(d0.time(), d0['v2us'], 's-', label=r'Recording, 2$\\mu$s')\n", + "ax.plot(d1.time(), d2['filter.y2'], label=r'Simulation, n=2, tr=4 $\\mu$s')\n", + "ax.plot(d1.time(), d2['filter.y3'], label=r'Simulation, n=1, tr=4 $\\mu$s')\n", + "ax.legend()\n", + "ax.set_xlim(0.99, 1.03)\n", + "plt.show()" + ] + }, + { + "cell_type": "markdown", + "id": "341de105-ff75-4f8b-9d56-4a3c72643bbe", + "metadata": {}, + "source": [ + "This is not far off at all, and any discrepancies only last for 0.1ms. Compared to e.g. fast-capacitance compensation, it is unlikely that approximating as first order will cause any problems.\n", + "\n", + "As above, we'll use an optimiser to find time constants that match best:" + ] + }, + { + "cell_type": "code", + "execution_count": 33, + "id": "0fe54edc-eaeb-4d99-92ab-f4707f6689c1", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Rise time 0.05562500000000001 ms\n", + "Time constant 0.025316028490558917 ms\n" + ] + } + ], + "source": [ + "def error(tr):\n", + " s.reset()\n", + " s.set_constant('filter.tr', tr[0])\n", + " d = s.run(2, log_times=d0.time())\n", + " return np.sum((d0['v20us'] - d['filter.y3'])**2)\n", + "\n", + "tr1slow = fmin(error, 0.04, disp=False)[0]\n", + "print(f'Rise time {tr1slow} ms')\n", + "print(f'Time constant {tr1slow / np.log(9)} ms')\n", + "\n", + "s.set_constant('filter.tr', tr1slow)\n", + "s.reset()\n", + "s.pre(1)\n", + "d3 = s.run(2, log_interval=1e-3).npview()" + ] + }, + { + "cell_type": "code", + "execution_count": 34, + "id": "07c5b7a7-f2a3-4a6b-a9c5-e85575d18547", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Rise time 0.006590625000000008 ms\n", + "Time constant 0.0029995227014937534 ms\n" + ] + } + ], + "source": [ + "def error(tr):\n", + " s.reset()\n", + " s.set_constant('filter.tr', tr[0])\n", + " d = s.run(2, log_times=d0.time())\n", + " return np.sum((d0['v2us'] - d['filter.y3'])**2)\n", + "\n", + "tr1fast = fmin(error, 0.004, disp=False)[0]\n", + "print(f'Rise time {tr1fast} ms')\n", + "print(f'Time constant {tr1fast / np.log(9)} ms')\n", + "\n", + "s.set_constant('filter.tr', tr1fast)\n", + "s.reset()\n", + "s.pre(1)\n", + "d4 = s.run(2, log_interval=1e-3).npview()" + ] + }, + { + "cell_type": "markdown", + "id": "d9b48297-0c16-4c73-8534-05fbc0282148", + "metadata": {}, + "source": [ + "Summing up, in the one-pole approximation\n", + "\n", + "**The 20$\\mu$s setting is replicated by `tau=0.025[ms]`.**\n", + "\n", + "**The 2$\\mu$s setting is replicated by `tr=0.003[ms]`.**" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.13.12" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/tutorial/appendix-a/res/stimulus-filter.zip b/tutorial/appendix/d-filters/res/stimulus-filter.zip similarity index 100% rename from tutorial/appendix-a/res/stimulus-filter.zip rename to tutorial/appendix/d-filters/res/stimulus-filter.zip diff --git a/tutorial/appendix-d/3-liquid-junction-potential.ipynb b/tutorial/appendix/e-offsets/1-liquid-junction-potential.ipynb similarity index 98% rename from tutorial/appendix-d/3-liquid-junction-potential.ipynb rename to tutorial/appendix/e-offsets/1-liquid-junction-potential.ipynb index c0e621a..3eeffaa 100644 --- a/tutorial/appendix-d/3-liquid-junction-potential.ipynb +++ b/tutorial/appendix/e-offsets/1-liquid-junction-potential.ipynb @@ -4,8 +4,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Appendix D3: Liquid junction potential\n", - "**Appendix D discusses remaining noise and errors**" + "# E1: Liquid junction potential" ] }, { @@ -250,7 +249,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/tutorial/appendix-d/4-offset-correction.ipynb b/tutorial/appendix/e-offsets/2-offset-correction.ipynb similarity index 98% rename from tutorial/appendix-d/4-offset-correction.ipynb rename to tutorial/appendix/e-offsets/2-offset-correction.ipynb index c040238..4779133 100644 --- a/tutorial/appendix-d/4-offset-correction.ipynb +++ b/tutorial/appendix/e-offsets/2-offset-correction.ipynb @@ -4,9 +4,13 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Appendix D4: Handling voltage offsets\n", - "**Appendix D discusses remaining noise and errors**\n", - "\n", + "# E2: Handling voltage offsets" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ "Following on from the Appendix on the liquid junction potential (LJP), this notebook discusses how to deal with the LJP and other offsets when fitting models or otherwise analysing experimental data.\n", "\n", "Because everybody gets confused about the sign conventions, we'll go through this excruciatingly slowly.\n", @@ -243,7 +247,7 @@ "source": [ "## Case B: A priori LJP correction\n", "\n", - "Some other day." + "**To be added at a later date**" ] } ], @@ -263,7 +267,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/tutorial/appendix-d/img/ljp-1-increase.png b/tutorial/appendix/e-offsets/img/ljp-1-increase.png similarity index 100% rename from tutorial/appendix-d/img/ljp-1-increase.png rename to tutorial/appendix/e-offsets/img/ljp-1-increase.png diff --git a/tutorial/appendix-d/img/ljp-2-electrode.png b/tutorial/appendix/e-offsets/img/ljp-2-electrode.png similarity index 100% rename from tutorial/appendix-d/img/ljp-2-electrode.png rename to tutorial/appendix/e-offsets/img/ljp-2-electrode.png diff --git a/tutorial/appendix-d/img/ljp-3-ljp.png b/tutorial/appendix/e-offsets/img/ljp-3-ljp.png similarity index 100% rename from tutorial/appendix-d/img/ljp-3-ljp.png rename to tutorial/appendix/e-offsets/img/ljp-3-ljp.png diff --git a/tutorial/appendix-d/img/ljp-4-vm.png b/tutorial/appendix/e-offsets/img/ljp-4-vm.png similarity index 100% rename from tutorial/appendix-d/img/ljp-4-vm.png rename to tutorial/appendix/e-offsets/img/ljp-4-vm.png diff --git a/tutorial/appendix-d/img/ljp-5-correction.png b/tutorial/appendix/e-offsets/img/ljp-5-correction.png similarity index 100% rename from tutorial/appendix-d/img/ljp-5-correction.png rename to tutorial/appendix/e-offsets/img/ljp-5-correction.png diff --git a/tutorial/appendix-c/3-parameter-values.ipynb b/tutorial/appendix/z-parameters/1-parameter-values.ipynb similarity index 99% rename from tutorial/appendix-c/3-parameter-values.ipynb rename to tutorial/appendix/z-parameters/1-parameter-values.ipynb index 3dfb26b..d50149f 100644 --- a/tutorial/appendix-c/3-parameter-values.ipynb +++ b/tutorial/appendix/z-parameters/1-parameter-values.ipynb @@ -5,8 +5,7 @@ "id": "44ff9bab", "metadata": {}, "source": [ - "# Appendix C3: Parameter values\n", - "**Appendix C discusses variable names and values**" + "# Z1: Parameter values" ] }, { @@ -344,7 +343,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.11" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/tutorial/appendix-c/1-symbols.ipynb b/tutorial/symbols.ipynb similarity index 97% rename from tutorial/appendix-c/1-symbols.ipynb rename to tutorial/symbols.ipynb index 0beeb71..63d9d69 100644 --- a/tutorial/appendix-c/1-symbols.ipynb +++ b/tutorial/symbols.ipynb @@ -5,8 +5,7 @@ "id": "d0146af1", "metadata": {}, "source": [ - "# Appendix C1: Names & symbols\n", - "**Appendix C discusses variable names and values**" + "# Names & symbols" ] }, { @@ -91,7 +90,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.13.2" + "version": "3.13.9" } }, "nbformat": 4, diff --git a/tutorial/tour.ipynb b/tutorial/tour.ipynb index ef4bc03..061fb78 100644 --- a/tutorial/tour.ipynb +++ b/tutorial/tour.ipynb @@ -71,6 +71,10 @@ "| $\\beta$ | - | Fraction of $R_s$ prediction, read from amplifier | 0.7 |\n", "| $E^\\dagger_\\text{off}$ | mV | Remaining voltage offset after zeroing | 0 mV |\n", "\n", + "The $C_m$ value corresponds to a small cell, e.g. a HEK or CHO cell.\n", + "\n", + "The $R_s$ value corresponds to a 3M$\\Omega$ pipette, with an additional 3M$\\Omega$ resistance at the seal.\n", + "\n", "In a simple simulation $E^\\dagger_\\text{off}$ is chosen by the user.\n", "In inference settings it may be a parameter inferred from the data." ] @@ -215,10 +219,13 @@ "\n", "To estimate $\\tau_s$ in a real amplifier, you can record the filtered output voltage and fit to it.\n", "The value above corresponds to the \"slow\" (default) setting on a HEKA EPC-10.\n", + "The value for the \"fast\" setting is 0.003ms.\n", "\n", "To estimate $\\tau_o$, you can use $\\tau_o \\approx \\frac{1}{2 \\pi f}$, where $f$ is the filter's cut-off frequency in kHz.\n", "\n", - "Note that exact values of $\\tau_s$ and $\\tau_o$ are seldom crucial." + "Note that exact values of $\\tau_s$ and $\\tau_o$ are seldom crucial.\n", + "\n", + "The given $R_f$ value is typical for Axon, HEKA, and Sutter." ] }, { @@ -310,6 +317,7 @@ "| $C^*_p$ | pF | Estimated pipette capacitance, read from amplifier | 5 pF |\n", "| $\\tilde{C}_f$ | pF | Compensated stray capacitance on measuring resistor, unknown | 5e-3 pF |\n", "| $\\tau_a$ | ms | Time constant of measurement op-amp, unknown | 13e-6 ms |\n", + "| $t_r$ | ms | Stimulus filter setting | 0.04 ms |\n", "\n", "The given values of $\\tilde{C}_f$ and $\\tau_a$ were estimated by fitting to model cell experiments with a Heka EPC-10." ]