diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml
new file mode 100644
index 00000000..ae87c822
--- /dev/null
+++ b/.github/workflows/test.yml
@@ -0,0 +1,27 @@
+name: Tests
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.12", "3.13"]
+
+    steps:
+      - uses: actions/checkout@v4
+      - name: Install uv and set the python version
+        uses: astral-sh/setup-uv@v5
+        with:
+          version: "0.5.16"
+          python-version: ${{ matrix.python-version }}
+      - name: Install the project
+        run: uv sync
+      - name: Run tests
+        run: uv run pytest tests
\ No newline at end of file
diff --git a/.gitignore b/.gitignore
index 531c704b..621dcc23 100644
--- a/.gitignore
+++ b/.gitignore
@@ -6,4 +6,7 @@
 *.venv
 logs_tensorboard
 *.hdf5
-*.lock
\ No newline at end of file
+*.lock
+.python-version
+.DS_Store
+.idea
\ No newline at end of file
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
deleted file mode 100644
index 85bdac78..00000000
--- a/.pre-commit-config.yaml
+++ /dev/null
@@ -1,5 +0,0 @@
-repos:
-  - repo: https://github.com/astral-sh/uv-pre-commit
-    rev: '0.10.11'
-    hooks:
-      - id: uv-lock
diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
deleted file mode 100644
index cdb96ac3..00000000
--- a/CONTRIBUTING.md
+++ /dev/null
@@ -1,61 +0,0 @@
-# Package Management with uv
-
-If you intend to modify existing dependencies or add new ones, please **read this document carefully!**
-
-Our build system, as specified in [`pyproject.toml`](pyproject.toml), is based on [uv](https://docs.astral.sh/uv/), a fast Python package and project manager. We use `uv` for dependency resolution and virtual environment management.
-
-## Installing uv
-
-Install uv by following the [official instructions](https://docs.astral.sh/uv/getting-started/installation/).
-
-## Setting Up the Development Environment
-
-Assuming you have cloned the package and navigated to the root of the repository:
-
-```bash
-git clone git@github.com:PtyLab/PtyLab.py.git
-cd PtyLab.py
-```
-
-Install the project and all development dependencies:
-
-```bash
-uv sync --extra dev
-pre-commit install
-```
-
-This creates a `.venv` virtual environment, installs all packages pinned in `uv.lock`, and sets up pre-commit hooks. Select this environment from your IDE interpreter.
-
-### GPU Support with CuPy
-
-Install with the appropriate extra based on your CUDA toolkit version:
-
-```bash
-uv sync --extra dev,cuda12  # for CUDA 12.x
-uv sync --extra dev,cuda13  # for CUDA 13.x
-```
-
-## Modifying Packages
-
-To add a new package from [PyPI](https://pypi.org/):
-
-```bash
-uv add <package-name>
-```
-
-This installs the package, resolves all dependencies, and updates both `pyproject.toml` and `uv.lock`. To remove a package:
-
-```bash
-uv remove <package-name>
-```
-
-To add a package only to a specific extra (e.g., `dev`):
-
-```bash
-uv add --optional dev <package-name>
-```
-
-For more information, refer to the [uv documentation](https://docs.astral.sh/uv/reference/cli/). Ensure that you increment the package version (at least a minor version change) when modifying dependencies.
-
-> [!WARNING]
-> When a dependency is changed, `uv.lock` updates. The pre-commit `uv-lock` hook will verify the lock file is consistent. Stage `uv.lock` along with any `pyproject.toml` changes for the commit to proceed.
diff --git a/PtyLab/Engines/test/__init__.py b/PtyLab/Engines/test/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/PtyLab/Engines/test/test_baseReconstructor.py b/PtyLab/Engines/test/test_baseReconstructor.py
deleted file mode 100644
index b338fadf..00000000
--- a/PtyLab/Engines/test/test_baseReconstructor.py
+++ /dev/null
@@ -1,36 +0,0 @@
-from unittest import TestCase
-
-from PtyLab.Reconstruction.Reconstruction import Reconstruction
-from PtyLab.FixedData.DefaultExperimentalData import ExperimentalData
-from PtyLab.Engines.BaseEngine import BaseEngine
-
-
-class TestBaseReconstructor(TestCase):
-    def setUp(self) -> None:
-        # For almost all reconstructor properties we need both a data and an reconstruction object.
-        self.experimentalData = ExperimentalData("test:nodata")
-        self.optimizable = Reconstruction(self.experimentalData)
-        self.BR = BaseEngine(self.optimizable, self.experimentalData)
-
-    def test_change_optimizable(self):
-        """
-        Make sure the reconstruction can be changed
-        :return:
-        """
-        optimizable2 = Reconstruction(self.experimentalData)
-        self.BR.changeOptimizable(optimizable2)
-        self.assertEqual(self.BR.reconstruction, optimizable2)
-
-    def test_setPositionOrder(self):
-        """
-        Make sure the position of positionIndices is set 'sequential' or 'random'
-        :return:
-        """
-        pass
-
-    def test_getErrorMetrics(self):
-        """
-        Dont know how to test it
-        :return:
-        """
-        pass
diff --git a/PtyLab/Engines/test/test_ePIE.py b/PtyLab/Engines/test/test_ePIE.py
deleted file mode 100644
index e35619ff..00000000
--- a/PtyLab/Engines/test/test_ePIE.py
+++ /dev/null
@@ -1,17 +0,0 @@
-from unittest import TestCase
-
-from PtyLab.Reconstruction.Reconstruction import Reconstruction
-from PtyLab.FixedData.DefaultExperimentalData import ExperimentalData
-from PtyLab.Engines.ePIE import ePIE
-
-
-class TestEPIE(TestCase):
-    def setUp(self) -> None:
-        # For almost all reconstructor properties we need both a data and an reconstruction object.
-        self.experimentalData = ExperimentalData("test:nodata")
-        # self.experimentalData = FixedData('example:simulation_fpm')
-        self.optimizable = Reconstruction(self.experimentalData)
-        self.ePIE = ePIE(self.optimizable, self.experimentalData)
-
-    def test_init(self):
-        pass
diff --git a/PtyLab/Engines/test/test_propagator.py b/PtyLab/Engines/test/test_propagator.py
deleted file mode 100644
index 26bab417..00000000
--- a/PtyLab/Engines/test/test_propagator.py
+++ /dev/null
@@ -1,43 +0,0 @@
-import unittest
-from unittest import TestCase
-from numpy.testing import assert_almost_equal
-from PtyLab.FixedData.DefaultExperimentalData import ExperimentalData
-from PtyLab.Reconstruction.Reconstruction import Reconstruction
-from PtyLab.Engines import ePIE, mPIE, qNewton
-from PtyLab.Monitor.Monitor import Monitor as Monitor
-
-
-class TestPropagator(TestCase):
-    def test_FresnelPropagator(self):
-        exampleData = ExperimentalData()
-        exampleData.loadData("example:simulation_ptycho")
-        exampleData.operationMode = "CPM"
-
-        # now, all our experimental data is loaded into experimental_data and we don't have to worry about it anymore.
-        # now create an object to hold everything we're eventually interested in
-        optimizable = Reconstruction(exampleData)
-        optimizable.npsm = 1  # Number of probe modes to reconstruct
-        optimizable.nosm = 1  # Number of object modes to reconstruct
-        optimizable.nlambda = 1  # Number of wavelength
-        optimizable.initializeObjectProbe()
-
-        # this will copy any attributes from experimental data that we might care to optimize
-        # # Set monitor properties
-        monitor = Monitor()
-
-        # Compare mPIE to ePIE
-        # ePIE_engine = ePIE.ePIE_GPU(reconstruction, experimentalData, monitor)
-        ePIE_engine = ePIE.ePIE(optimizable, exampleData, monitor)
-        ePIE_engine.propagatorType = "ASP"
-        ePIE_engine.numIterations = 1
-        ePIE_engine.reconstruct()
-
-        A = optimizable.esw
-        ePIE_engine.object2detector()
-        ePIE_engine.detector2object()
-
-        assert_almost_equal(A, optimizable.esw)
-
-
-if __name__ == "__main__":
-    unittest.main()
diff --git a/PtyLab/Engines/test_BaseEngine.py b/PtyLab/Engines/test_BaseEngine.py
deleted file mode 100644
index 8eeed946..00000000
--- a/PtyLab/Engines/test_BaseEngine.py
+++ /dev/null
@@ -1,97 +0,0 @@
-from unittest import TestCase
-import unittest
-import logging
-import numpy as np
-
-logging.basicConfig(level=logging.DEBUG)
-import PtyLab
-
-try:
-    import cupy as cp
-except ImportError:
-    cp = None
-
-
-class TestBaseEngine(TestCase):
-    def setUp(self) -> None:
-        (
-            experimentalData,
-            reconstruction,
-            params,
-            monitor,
-            ePIE_engine,
-        ) = PtyLab.easyInitialize("example:simulation_cpm", operationMode="CPM")
-
-        self.reconstruction = reconstruction
-        self.ePIE_engine = ePIE_engine
-
-    def test__move_data_to_cpu(self):
-        """
-        Move data to CPU even though it's already there. This should not give us an error.
-        """
-        self.ePIE_engine.reconstruction.logger.setLevel(logging.DEBUG)
-        self.ePIE_engine._move_data_to_cpu()
-        self.ePIE_engine._move_data_to_cpu()
-        # test that things are actually on the CPU
-        assert type(self.ePIE_engine.reconstruction.object) is np.ndarray
-        # print(type(self.ePIE_engine.reconstruction.object))
-
-    @unittest.skipIf(cp is None, "no GPU available")
-    def test__move_data_to_gpu(self):
-        self.ePIE_engine.reconstruction.logger.setLevel(logging.DEBUG)
-        self.ePIE_engine._move_data_to_gpu()
-        self.ePIE_engine._move_data_to_gpu()
-        assert type(self.ePIE_engine.reconstruction.object) is cp.ndarray
-
-
-    def test_position_correction(self):
-        import time
-        rowShifts = np.array([-2, -2, -2, -2, -2, -1, -1, -1, -1, -1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 2, 2, 2, 2, 2])
-        # self.colShifts = dx.flatten()#np.array([-1, 0, 1, -1, 0, 1, -1, 0, 1])
-        colShifts = np.array([-2, -1,  0,  1,  2] * 5)
-        xp = cp
-
-        Opatch = xp.random.rand(513,513)
-        O = xp.roll(Opatch, axis=(-2,-1), shift=(1,-1))
-
-        t0 = time.time()
-        for i in range(100):
-            cc = xp.zeros((len(rowShifts), 1))
-            for shifts in range(len(rowShifts)):
-                tempShift = xp.roll(Opatch, rowShifts[shifts], axis=-2)
-                # shiftedImages[shifts, ...] = xp.roll(tempShift, self.colShifts[shifts], axis=-1)
-                shiftedImages = xp.roll(tempShift, colShifts[shifts], axis=-1)
-                cc[shifts] = xp.squeeze(
-                    xp.sum(shiftedImages.conj() * O, axis=(-2, -1))
-                )
-                del tempShift, shiftedImages
-            cc = abs(cc)
-            cc = cc.reshape(5,5).get()
-        t1 = time.time()
-        print('CC: ', t1 - t0)
-
-        # new code
-        # time it
-
-        t0 = time.time()
-        for i in range(100):
-            rowShifts, colShifts = xp.mgrid[-2:3, -2:3]
-            rowShifts = rowShifts.flatten()
-            colShifts = colShifts.flatten()
-            print(dy, dx)
-            FT_O = xp.fft.fft2(O)
-            FT_Op = xp.fft.fft2(Opatch)
-            xcor = xp.fft.ifft2(FT_O*FT_Op.conj())
-            xcor = abs(xp.fft.fftshift(xcor))
-            dy, dx = xp.unravel_index(xp.argmax(xcor), xcor.shape)
-            dx = dx.get()
-        t1 = time.time()
-        print('FT: ', t1-t0)
-        N = xcor.shape[-1]
-        sy = slice(N//2-len(cc)//2, N//2-len(cc)//2+len(cc))
-        print(' Xcor:')
-        print(xcor[sy, sy])
-
-        xp.testing.assert_allclose(xcor[sy, sy], cc)
-
-
diff --git a/PtyLab/ExperimentalData/ExperimentalData.py b/PtyLab/ExperimentalData/ExperimentalData.py
index 0922d1d7..dc3c6fab 100644
--- a/PtyLab/ExperimentalData/ExperimentalData.py
+++ b/PtyLab/ExperimentalData/ExperimentalData.py
@@ -98,6 +98,22 @@ def loadData(self, filename=None):
         """
         import os
 
+        if str(filename) == "test:nodata":
+            self.filename = filename
+            # Set minimal stub data so the object is usable without a file
+            self.ptychogram = np.zeros((1, 16, 16), dtype=np.float32)
+            self.encoder = np.zeros((1, 2), dtype=np.float64)
+            self.wavelength = 500e-9
+            self.dxd = 6.5e-6
+            self.zo = 0.1
+            # optional fields
+            self.entrancePupilDiameter = None
+            self.spectralDensity = None
+            self.theta = None
+            self.emptyBeam = None
+            self._setData()
+            return
+
         if not os.path.exists(filename) and str(filename).startswith("example:"):
             self.filename = filename
             from PtyLab.io.readExample import examplePath
diff --git a/PtyLab/ExperimentalData/test/__init__.py b/PtyLab/ExperimentalData/test/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/PtyLab/ExperimentalData/test/test_experimentalData.py b/PtyLab/ExperimentalData/test/test_experimentalData.py
deleted file mode 100644
index af9e1e7f..00000000
--- a/PtyLab/ExperimentalData/test/test_experimentalData.py
+++ /dev/null
@@ -1,13 +0,0 @@
-from unittest import TestCase
-
-#
-# class TestExperimentalData(TestCase):
-#     def test_initialize_attributes(self):
-#         self.fail()
-#
-#     def test_load_data(self):
-# Todo: Tomas: Please put a minimal version of your example script here
-#         self.fail()
-#
-#     def test__checkdata(self):
-#         self.fail()
diff --git a/PtyLab/Monitor/test/__init__.py b/PtyLab/Monitor/test/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/PtyLab/Monitor/test/test_TensorboardMonitor.py b/PtyLab/Monitor/test/test_TensorboardMonitor.py
deleted file mode 100644
index 7664941a..00000000
--- a/PtyLab/Monitor/test/test_TensorboardMonitor.py
+++ /dev/null
@@ -1,28 +0,0 @@
-import matplotlib
-
-matplotlib.use("qt5agg")
-import matplotlib.pyplot as plt
-import unittest
-from PtyLab.Monitor.TensorboardMonitor import center_angle
-from scipy import ndimage
-import numpy as np
-
-
-class AngleStuff(unittest.TestCase):
-    def test_center_angle(self):
-        N = 128
-        Ein = np.fft.fftshift(ndimage.fourier_shift(np.ones((N, N)), [5, 0]))
-
-        Ein_c = center_angle(Ein)
-
-        # print('hoihoi')
-        plt.subplot(121)
-        plt.imshow(np.angle(Ein), cmap="hsv", clim=[-np.pi, np.pi])
-        plt.subplot(122)
-        # print(Ein_c)
-        plt.imshow(np.angle(Ein_c), cmap="hsv", clim=[-np.pi, np.pi])
-        plt.show()
-
-
-if __name__ == "__main__":
-    unittest.main()
diff --git a/PtyLab/Monitor/test/test_matplotlib_monitor.py b/PtyLab/Monitor/test/test_matplotlib_monitor.py
deleted file mode 100644
index 0b0ffca3..00000000
--- a/PtyLab/Monitor/test/test_matplotlib_monitor.py
+++ /dev/null
@@ -1,54 +0,0 @@
-from unittest import TestCase
-from PtyLab.Monitor.Plots import ObjectProbeErrorPlot
-import time
-import numpy as np
-import unittest
-
-from PtyLab.Engines import BaseEngine
-
-from PtyLab.Reconstruction.Reconstruction import Reconstruction
-from PtyLab.FixedData.DefaultExperimentalData import ExperimentalData
-from PtyLab.Engines.BaseEngine import BaseEngine
-
-# To run the tests in this file, set this to TRUE
-VISUAL_TESTS = False
-
-
-@unittest.skipUnless(
-    VISUAL_TESTS,
-    "Visual tests are disabled by default. To turn them on, set VISUAL_TESTS to true",
-)
-class TestMatplotlib_monitor(TestCase):
-    def setUp(self):
-        self.monitor = ObjectProbeErrorPlot()
-
-    def test_createFigure(self):
-        pass
-
-    def test_live_update(self):
-        error_metrics = []
-        for k in range(100):
-            error_metrics.append(np.random.rand())
-            self.monitor.updateObject(np.random.rand(100, 100))
-            self.monitor.updateError(error_metrics)
-            self.monitor.drawNow()
-
-
-@unittest.skipUnless(
-    VISUAL_TESTS,
-    "Visual tests are disabled by default. To turn them on, set VISUAL_TESTS to true",
-)
-class TestPlotFromBaseReconstructor(TestCase):
-    def setUp(self):
-        # For almost all reconstructor properties we need both a data and an reconstruction object.
-        self.experimentalData = ExperimentalData("example:simulationTiny")
-        self.optimizable = Reconstruction(self.experimentalData)
-        self.optimizable.initializeObjectProbe()
-        self.BR = BaseEngine(self.optimizable, self.experimentalData)
-
-    def test_showReconstruction(self):
-        self.BR.reconstruction.initializeObjectProbe()
-        self.BR.figureUpdateFrequency = 20
-        self.BR.showReconstruction(0)
-        for i in range(1000):
-            self.BR.showReconstruction(i)
diff --git a/PtyLab/Monitor/test_TensorboardMonitor.py b/PtyLab/Monitor/test_TensorboardMonitor.py
deleted file mode 100644
index aac2f6dc..00000000
--- a/PtyLab/Monitor/test_TensorboardMonitor.py
+++ /dev/null
@@ -1,50 +0,0 @@
-from unittest import TestCase
-from PtyLab.Monitor.TensorboardMonitor import TensorboardMonitor
-import numpy as np
-
-
-class Test(TestCase):
-    def setUp(self):
-        self.monitor = TensorboardMonitor(name="testing purposes only")
-
-    def test_diffractionData(self):
-        import imageio
-
-        estimated = imageio.imread("imageio:camera.png")
-        measured = np.fliplr(estimated)
-        for i in range(10):
-            self.monitor.i = i
-            self.monitor.updateDiffractionDataMonitor(estimated, measured)
-
-    def test_UpdateObjectProbe(self):
-        object_estimate = np.random.rand(1, 1280, 1280)
-        probe_estimate = np.random.rand(1, 64, 64) * 1j
-        for i in range(10):
-            self.monitor.updatePlot(object_estimate, probe_estimate)
-
-    def test_updateError(self):
-        errors = np.random.rand(100).cumsum()[::-1]
-        for e in errors:
-            self.monitor.i += 1
-            self.monitor.updateObjectProbeErrorMonitor(e)
-            # this often happens in various optimizers for some unclear reason
-            self.monitor.updateObjectProbeErrorMonitor([e])
-
-    def test_update_z(self):
-
-        z = np.random.rand(100) / 100
-        z[0] = 10
-        z[30:50] = 0
-        z[80:120] = 0
-        z = z.cumsum()
-        for zi in z:
-            self.monitor.i += 1
-            self.monitor.update_z(zi)
-        # .cumsum()[::-1]
-
-    def test_update_positions(self):
-        positions = np.random.rand(100, 2).cumsum(axis=1)
-        positions = np.cos(positions)
-        scaling = 1.5
-        other_positions = positions + np.random.rand(*positions.shape) * 1e-2
-        self.monitor.update_positions(positions, scaling * other_positions, scaling)
diff --git a/PtyLab/Operators/test/__init__.py b/PtyLab/Operators/test/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/PtyLab/Operators/test/test_operators.py b/PtyLab/Operators/test/test_operators.py
deleted file mode 100644
index accc513a..00000000
--- a/PtyLab/Operators/test/test_operators.py
+++ /dev/null
@@ -1,39 +0,0 @@
-from unittest import TestCase
-from PtyLab.Operators.Operators import aspw, scaledASP, scaledASPinv, fresnelPropagator
-import numpy as np
-from PtyLab.utils.utils import circ
-from numpy.testing import assert_almost_equal
-import unittest
-
-
-class TestOperators(TestCase):
-    def setUp(self) -> None:
-        self.dx = 5e-6
-        N = 100
-        x = np.arange(-N / 2, N / 2) * self.dx
-        X, Y = np.meshgrid(x, x)
-        self.E_in = circ(X, Y, N / 2 * self.dx)
-        self.wavelength = 600e-9
-        self.z = 1e-4
-        self.L = self.dx * N
-
-    def test_aspw(self):
-        E_1, _ = aspw(self.E_in, 0, self.wavelength, self.L)
-        E_2, _ = aspw(E_1, self.z, self.wavelength, self.L)
-        E_3, _ = aspw(E_2, -self.z, self.wavelength, self.L)
-        assert_almost_equal(self.E_in, E_1)
-        assert_almost_equal(abs(E_1), abs(E_3))
-
-    def test_scaledASP(self):
-        E_1, _, _ = scaledASP(self.E_in, self.z, self.wavelength, self.dx, self.dx)
-        E_2, _, _ = scaledASP(E_1, -self.z, self.wavelength, self.dx, self.dx)
-        assert_almost_equal(abs(E_2), abs(self.E_in))
-
-    @unittest.skip()
-    def test_fresnelPropagator(self):
-        E_out = fresnelPropagator(self.E_in, 0, self.wavelength, self.L)
-        assert_almost_equal(self.E_in, E_out)
-
-
-if __name__ == "__main__":
-    unittest.main()
diff --git a/PtyLab/Operators/test_Operators.py b/PtyLab/Operators/test_Operators.py
deleted file mode 100644
index c6f11bae..00000000
--- a/PtyLab/Operators/test_Operators.py
+++ /dev/null
@@ -1,128 +0,0 @@
-from unittest import TestCase
-
-from numpy.testing import assert_allclose
-
-from PtyLab import Operators, easyInitialize
-import numpy as np
-from numpy.testing import assert_allclose
-import time
-
-
-def test_caching_aspw():
-    try:
-        import cupy as cp
-
-        xp = cp
-    except ImportError:
-        xp = np
-    E = xp.random.rand(10, 1, 3, 512, 512)
-    z = 1e-3
-    wl = 512e-9
-    pixel_pitch = 10e-6
-    L = pixel_pitch * E.shape[-1]
-
-    from cupyx import time as timer
-
-    # run this to warm up the GPU
-    timer.repeat(Operators.Operators.aspw, (E, z, wl, L), {}, n_repeat=200, n_warmup=50)
-
-    t0 = time.time()
-    for i in range(100):
-        E_prop = Operators.Operators.aspw_cached(E, z, wl, L)
-    if xp is not np:
-        E_prop = xp.asnumpy(E_prop)
-    t1 = time.time()
-    t_cached = t1 - t0
-    for i in range(100):
-        E_prop2 = Operators.Operators.aspw(E, z, wl, L)[0]
-    if xp is not np:
-        E_prop2 = E_prop2.get()
-    t2 = time.time()
-    t_noncached = t2 - t1
-    print(f"\n\nNon-cached took: {t_noncached}", f"Cached took {t_cached}s")
-    # E_prop = np.squeeze(E_prop)
-
-    assert_allclose(E_prop, E_prop2)
-
-
-def test_object2detector():
-    experimentalData, reconstruction, params, monitor, engine = easyInitialize(
-        "example:simulation_cpm"
-    )
-    params.gpuSwitch = True
-    reconstruction._move_data_to_gpu()
-    _doit(reconstruction, params)
-
-    params.gpuSwitch = False
-    reconstruction._move_data_to_cpu()
-    _doit(reconstruction, params)
-
-
-def _doit(reconstruction, params):
-    for operator_name in Operators.Operators.forward_lookup_dictionary:
-        params.propagatorType = operator_name
-        reconstruction.esw = reconstruction.probe
-        print("\n")
-        import time
-
-        for i in range(3):
-            t0 = time.time()
-            Operators.Operators.object2detector(
-                reconstruction.esw, params, reconstruction
-            )
-            # out = operator(reconstruction.probe, params, reconstruction)
-            t1 = time.time()
-            print(operator_name, i, 1e3 * (t1 - t0), "ms")
-
-
-def test__propagate_fresnel():
-    experimentalData, reconstruction, params, monitor, engine = easyInitialize(
-        "example:simulation_cpm"
-    )
-
-    reconstruction.initializeObjectProbe()
-    reconstruction.esw = 2
-    for operator in [
-        Operators.Operators.propagate_fresnel,
-        Operators.Operators.propagate_ASP,
-        Operators.Operators.propagate_scaledASP,
-        Operators.Operators.propagate_twoStepPolychrome,
-        Operators.Operators.propagate_scaledPolychromeASP,
-    ]:
-        params.gpuSwitch = True
-        reconstruction._move_data_to_gpu()
-
-        import time
-
-        for i in range(3):
-            t0 = time.time()
-            out = operator(reconstruction.probe, params, reconstruction)
-            t1 = time.time()
-            print(i, 1e3 * (t1 - t0), "ms")
-
-        params.gpuSwitch = False
-        reconstruction._move_data_to_cpu()
-
-        import time
-
-        for i in range(10):
-            t0 = time.time()
-            out = operator(reconstruction.probe, params, reconstruction)
-            t1 = time.time()
-            print(i, 1e3 * (t1 - t0), "ms")
-
-
-def test_aspw_cached():
-    assert False
-
-
-class TestASP(TestCase):
-    def test_propagate_asp(self):
-        experimentalData, reconstruction, params, monitor, engine = easyInitialize(
-            "example:simulation_cpm"
-        )
-        reconstruction.esw = None
-        a = reconstruction.probe
-        P1 = Operators.Operators.propagate_ASP(a,params, reconstruction,z=1e-3, fftflag=False)[1]
-        P2 = Operators.Operators.propagate_ASP(a, params, reconstruction, z=1e-3, fftflag=True)[1]
-        assert_allclose(P1, P2)
diff --git a/PtyLab/Params/Params.py b/PtyLab/Params/Params.py
index e87ff218..d2e8b95d 100644
--- a/PtyLab/Params/Params.py
+++ b/PtyLab/Params/Params.py
@@ -178,6 +178,16 @@ def __init__(self):
         # SHG stuff
         self.SHG_probe = False
 
+    @property
+    def propagator(self):
+        """Alias for propagatorType."""
+        return self.propagatorType
+
+    @propagator.setter
+    def propagator(self, value):
+        """Alias for propagatorType."""
+        self.propagatorType = value
+
     @property
     def gpuSwitch(self):
         """Get the GPU switch state."""
diff --git a/PtyLab/ProbeEngines/test_StandardProbe.py b/PtyLab/ProbeEngines/test_StandardProbe.py
deleted file mode 100644
index 37ffefe2..00000000
--- a/PtyLab/ProbeEngines/test_StandardProbe.py
+++ /dev/null
@@ -1,19 +0,0 @@
-from unittest import TestCase
-import numpy as np
-import imageio
-from PtyLab.ProbeEngines.StandardProbe import SHGProbe
-
-
-class TestSHGProbe(TestCase):
-    target = imageio.imread("imageio:camera.png").astype(np.float32)
-    target = target / np.linalg.norm(target)
-    engine = SHGProbe()
-    engine.probe = np.random.rand(*target.shape)
-
-    for i in range(1000):
-
-        current_estimate = engine.get(None)
-        if i % 10 == 0:
-            print(np.linalg.norm(current_estimate - target))
-        new_estimate = target
-        engine.push(new_estimate, None, None)
diff --git a/PtyLab/Reconstruction/test/__init__.py b/PtyLab/Reconstruction/test/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/PtyLab/Reconstruction/test/test_optimizable.py b/PtyLab/Reconstruction/test/test_optimizable.py
deleted file mode 100644
index ed85eadb..00000000
--- a/PtyLab/Reconstruction/test/test_optimizable.py
+++ /dev/null
@@ -1,40 +0,0 @@
-from unittest import TestCase
-import logging
-
-logging.basicConfig(level=logging.DEBUG)
-from numpy.testing import assert_almost_equal, assert_array_almost_equal
-
-from PtyLab.FixedData.DefaultExperimentalData import ExperimentalData
-from PtyLab.Reconstruction.Reconstruction import Reconstruction
-
-
-class TestOptimizable(TestCase):
-    def setUp(self):
-        # first, create a FixedData dataset
-        data = ExperimentalData("test:nodata")
-        # data = FixedData('example:simulation_fpm')
-
-        data.wavelength = 1234
-        optimizable = Reconstruction(data)
-        self.data = data
-        self.optimizable = optimizable
-
-    def test_copyAttributesFromExperiment(self):
-        self.check_scalar_property()
-        self.check_array_property()
-
-    def check_scalar_property(self):
-
-        # check that the wavelength is properly copied
-        self.assertEqual(self.optimizable.wavelength, self.data.wavelength)
-        # now if we change it, it should no longer be the same
-        self.optimizable.wavelength = 4321
-        self.assertNotEqual(self.optimizable.wavelength, self.data.wavelength)
-
-    def check_array_property(self):
-        """
-        Arrays are passed by reference by default. Check that they are properly copied as well
-        :return:
-        """
-        self.optimizable.positions += 1
-        assert_array_almost_equal(self.optimizable.positions - 1, self.data.positions)
diff --git a/PtyLab/Regularizers/test___init__.py b/PtyLab/Regularizers/test___init__.py
deleted file mode 100644
index 1af51545..00000000
--- a/PtyLab/Regularizers/test___init__.py
+++ /dev/null
@@ -1,46 +0,0 @@
-import time
-from unittest import TestCase
-import numpy as np
-from numpy.testing import assert_allclose
-
-from PtyLab.Regularizers import divergence, grad_TV
-
-
-class Test(TestCase):
-    def setUp(self) -> None:
-        self.nlambda = 1
-        self.nosm = 1
-        self.nslice = 1
-        self.No = 380
-        self.shape_O = (
-            self.nlambda,
-            self.nosm,
-            1,
-            self.nslice,
-            self.No,
-            self.No
-        )
-        self.object = np.random.rand(*self.shape_O) + 1j * np.random.rand(*self.shape_O)
-        self.object -= 0.5 + 0.5j
-
-    def test_divergence(self):
-
-        # copied from wilhelm
-        t0 = time.time()
-        for i in range(10):
-            epsilon = 1e-2
-            gradient = np.gradient(self.object, axis=(4, 5))
-            norm = (gradient[0]+gradient[1])**2
-            temp = [gradient[0] / np.sqrt(norm+epsilon), gradient[1] / np.sqrt(norm+epsilon)]
-            TV_update = divergence(temp)
-        t1= time.time()
-        print(t1 - t0)
-
-        # new method, should be faster and more consuming
-        t0 = time.time()
-        for i in range(10):
-            TV_update_2 = grad_TV(self.object, epsilon)
-        t1 = time.time()
-        print(t1 - t0)
-        assert_allclose(TV_update, TV_update_2)
-
diff --git a/PtyLab/io/readHdf5.py b/PtyLab/io/readHdf5.py
index 4949c18a..5facfbf0 100644
--- a/PtyLab/io/readHdf5.py
+++ b/PtyLab/io/readHdf5.py
@@ -123,14 +123,3 @@ def checkDataFields(filename, requiredFields):
     return None
 
 
-def getOrientation(filename):
-    """
-    Get the orientation from the hdf5 file. If not available, set to None
-    """
-    orientation = None
-    try:
-        with h5py.File(str(filename), mode="r") as archive:
-            orientation = int(np.array(archive["orientation"]).ravel())
-    except KeyError as e:
-        print(e)
-    return orientation
diff --git a/PtyLab/io/test/__init__.py b/PtyLab/io/test/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/PtyLab/io/test/test_example_loader.py b/PtyLab/io/test/test_example_loader.py
deleted file mode 100644
index b751809d..00000000
--- a/PtyLab/io/test/test_example_loader.py
+++ /dev/null
@@ -1,23 +0,0 @@
-from unittest import TestCase
-from PtyLab.io import readExample
-import numpy as np
-import logging
-
-logging.basicConfig()
-
-
-class TestRead_example(TestCase):
-    def test_read_example(self):
-        """
-        Check that loadExample works. Based on the input we know that it should give us a dataset
-        with 32 pictures in it
-        :return:
-        """
-
-        readExample.listExamples()
-        archive = readExample.loadExample("simulation_fpm")
-        # check that we can read something
-        self.assertEqual(256, np.array(archive["Nd"], int))
-
-        archive = readExample.loadExample("simulationTiny")
-        self.assertEqual(64, np.array(archive["Nd"], int))
diff --git a/PtyLab/io/test/test_get_example_data_folder.py b/PtyLab/io/test/test_get_example_data_folder.py
deleted file mode 100644
index 52e5e8bf..00000000
--- a/PtyLab/io/test/test_get_example_data_folder.py
+++ /dev/null
@@ -1,27 +0,0 @@
-from unittest import TestCase
-from PtyLab.io import getExampleDataFolder
-
-
-class TestGet_example_data_folder(TestCase):
-    def test_example_folder_exists(self):
-        """
-        Test that the path returned by getExampleDataFolder exists.
-        :return:
-        """
-        example_data_folder = getExampleDataFolder()
-        self.assertTrue(
-            example_data_folder.exists(),
-            "example data folder returned does not exist on the filesystem",
-        )
-
-    def test_simulationTiny_in_example_data(self):
-        """
-        The test folder always has simulationTiny.hdf5 in it. Check that it's present.
-        :return:
-        """
-        example_data_folder = getExampleDataFolder()
-        matlabfile = example_data_folder / "simulationTiny.hdf5"
-        self.assertTrue(
-            matlabfile.exists(),
-            "`simulationTiny.hdf5` is not present in the example data folder",
-        )
diff --git a/PtyLab/io/test/test_loadInputData.py b/PtyLab/io/test/test_loadInputData.py
deleted file mode 100644
index 37574557..00000000
--- a/PtyLab/io/test/test_loadInputData.py
+++ /dev/null
@@ -1,27 +0,0 @@
-from unittest import TestCase
-from PtyLab.io import getExampleDataFolder
-from PtyLab.io.readHdf5 import loadInputData
-import logging
-
-
-class TestLoadInputData(TestCase):
-    def test_loadInputData(self):
-        """
-        Load the input data. We know that the shape of the input should be 441,128,128,
-        so check that it's loaded correctly.
-
-        # TODO: The filename of example_data should change, and hence this function has to be reimplemented too.
-        :return:
-        """
-        # first, get the filename of the first .hdf5 dataset
-        example_data_folder = getExampleDataFolder()
-        filename = example_data_folder / "fourier_simulation.hdf5"
-        result = loadInputData(filename)
-        self.assertEqual(result["ptychogram"].shape, (49, 256, 256))
-
-
-if __name__ == "__main__":
-    logging.basicConfig(level=logging.DEBUG)
-    import unittest
-
-    unittest.main()
diff --git a/PtyLab/testall.py b/PtyLab/testall.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/PtyLab/utils/test/__init__.py b/PtyLab/utils/test/__init__.py
deleted file mode 100644
index e69de29b..00000000
diff --git a/PtyLab/utils/test/test_complexPlot.py b/PtyLab/utils/test/test_complexPlot.py
deleted file mode 100644
index 379db770..00000000
--- a/PtyLab/utils/test/test_complexPlot.py
+++ /dev/null
@@ -1,19 +0,0 @@
-import matplotlib
-
-matplotlib.use("tkagg")
-import unittest
-import numpy as np
-import matplotlib.pyplot as plt
-from PtyLab.utils.visualisation import complex2rgb, complexPlot
-
-
-class TestComplexPlot(unittest.TestCase):
-    def test_complex_plot(self):
-        testComplexArray = np.ones((100, 100)) * (1 + 1j)
-        testRGBArray = complex2rgb(testComplexArray)
-        complexPlot(testRGBArray)
-        plt.show()
-
-
-if __name__ == "__main__":
-    unittest.main()
diff --git a/PtyLab/utils/test/test_fft2c_ifft2c.py b/PtyLab/utils/test/test_fft2c_ifft2c.py
deleted file mode 100644
index f846587d..00000000
--- a/PtyLab/utils/test/test_fft2c_ifft2c.py
+++ /dev/null
@@ -1,25 +0,0 @@
-import unittest
-from unittest import TestCase
-import numpy as np
-from PtyLab.utils.utils import fft2c, ifft2c
-from numpy.testing import assert_almost_equal
-
-
-class TestOperators(TestCase):
-    def test_fft2c_ifft2c(self):
-        """
-        Test that fft2c and ifft2c are unitary.
-        :return:
-        """
-        E_in = (
-            np.random.rand(5, 100, 100) + 1j * np.random.rand(5, 100, 100) - 0.5 - 0.5j
-        )
-        # FFT(IFFT(x)) == x
-        assert_almost_equal(ifft2c(fft2c(E_in)), E_in)
-        # and vice versa
-        assert_almost_equal(fft2c(ifft2c(E_in)), E_in)
-        # assert_almost_equal(E_in, abs(E_out))
-
-
-if __name__ == "__main__":
-    unittest.main()
diff --git a/PtyLab/utils/test_initializationFunctions.py b/PtyLab/utils/test_initializationFunctions.py
deleted file mode 100644
index 3d9f52be..00000000
--- a/PtyLab/utils/test_initializationFunctions.py
+++ /dev/null
@@ -1,39 +0,0 @@
-from unittest import TestCase
-import PtyLab
-
-
-class TestInitialProbeOrObject(TestCase):
-    def setUp(self) -> None:
-        experimentalData, reconstruction, params, monitor, ePIE_engine = PtyLab.easyInitialize(
-            'example:helicalbeam', operationMode="CPM", engine=PtyLab.Engines.mPIE
-        )
-
-        self.experimentalData = experimentalData
-        self.reconstruction = reconstruction
-
-        self.params = params
-        self.monitor = monitor
-        self.ePIE = ePIE_engine
-        self.experimentalData.setOrientation(4)
-
-    def test_initial_probe_or_object(self):
-        print(self.experimentalData.entrancePupilDiameter / self.reconstruction.dxo)
-        # make a tiny probe
-
-        self.experimentalData.entrancePupilDiameter = 30 * self.reconstruction.dxo
-
-        self.reconstruction = PtyLab.Reconstruction(self.experimentalData, self.params)
-        self.reconstruction.copyAttributesFromExperiment(self.experimentalData)
-
-        self.reconstruction.initialProbe = 'circ_smooth'
-
-        self.reconstruction.initializeObjectProbe()
-
-        self.ePIE = PtyLab.Engines.mPIE(self.reconstruction, self.experimentalData,
-                                        params=self.params, monitor=self.monitor)
-
-        print(self.reconstruction.entrancePupilDiameter)
-        self.ePIE.numIterations = 50
-        self.monitor.probeZoom = None  # show full FOV
-
-        self.ePIE.reconstruct()
diff --git a/README.md b/README.md
index 23c8ddad..65233936 100644
--- a/README.md
+++ b/README.md
@@ -1,8 +1,27 @@
-# PtyLab.py
-![Python 3.9+](https://img.shields.io/badge/python-3.9+-green.svg)
+# PtyLab.py: Unified Ptychography Toolbox
+![Python 3.10+](https://img.shields.io/badge/python-3.10+-green.svg)
+![Tests](https://github.com/ShantanuKodgirwar/PtyLabX/actions/workflows/test.yml/badge.svg)
 
 PtyLab is an inverse modeling toolbox for Conventional (CP) and Fourier (FP) ptychography in a unified framework. For more information please check the [paper](https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-9-13763&id=529026).
 
+## Key Features
+
+- **Classic reconstruction engines**: ePIE, mPIE, mqNewton, 
+- **Advanced corrections**: multi-slice, multi-wavelength, position correction (pcPIE), defocus correction (zPIE), angle correction (aPIE), orthogonal probe relaxation (OPR), mixed-state object and probe.
+- **Multiple propagators**: Fraunhofer, Fresnel, Angular Spectrum (ASP), scaled ASP, and polychromatic variants
+- **GPU acceleration**: Same code runs on CPU and GPU. 
+
+The reconstructed output is a 6D array of shape `(nlambda, nosm, npsm, nslice, No, No)`:
+
+| Dim | Meaning |
+|-----|---------|
+| `nlambda` | wavelengths |
+| `nosm` | object state mixture |
+| `npsm` | probe state mixture |
+| `nslice` | depth slices |
+| `No` | output frame size |
+
+
 ## Getting started
 
 The simplest way to get started is to check the below demo in Google Colab.
@@ -51,7 +70,7 @@ Install [uv](https://docs.astral.sh/uv/getting-started/installation/) if you hav
 uv sync --extra dev
 ```
 
-This creates a `.venv` virtual environment in the project root and installs all pinned dependencies from `uv.lock`. Select this environment from your IDE.
+This creates a `.venv` virtual environment in the project root. Select this environment from your IDE.
 
 To use the GPU, install with the appropriate CUDA extra instead:
 
@@ -60,13 +79,17 @@ uv sync --extra dev,cuda12  # for CUDA 12.x
 uv sync --extra dev,cuda13  # for CUDA 13.x
 ```
 
-GPU can be checked with
+and check if GPU is detected with `uv run ptylab check gpu`.
+
+#### Contributing
+
+If any new changes are made, add a new test if necessary and run the test suite.
 
 ```bash
-uv run ptylab check gpu
+uv run pytest tests
 ```
 
-If you would like to contribute to this package, especially if it involves modifying dependencies, please checkout the [`CONTRIBUTING.md`](CONTRIBUTING.md) file.
+Note that CI will also do this at every PR. Please bump the package version when modifying dependencies.
 
 ## Citation
 
diff --git a/pyproject.toml b/pyproject.toml
index 67f06459..708ede87 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,15 +1,15 @@
 [project]
 name = "ptylab"
-version = "0.2.2"
+version = "0.2.3"
 description = "A cross-platform, open-source inverse modeling toolbox for conventional and Fourier ptychography"
 authors = [
     { name = "Lars Loetgering", email = "lars.loetgering@fulbrightmail.org" },
     { name = "PtyLab Team" },
 ]
 readme = "README.md"
-requires-python = ">=3.9, <3.13"
+requires-python = ">=3.10, <3.14"
 dependencies = [
-    "numpy>=1.22",
+    "numpy~=2.0",
     "matplotlib~=3.7",
     "h5py~=3.9",
     "scipy~=1.11",
@@ -20,13 +20,15 @@ dependencies = [
     "tables~=3.8",
     "bokeh~=3.2",
     "PyQt5~=5.15",
+    "ipython~=8.18",
 ]
 
 [project.optional-dependencies]
 dev = [
     "black~=23.7",
     "ipykernel~=6.25",
-    "pre-commit~=4.0",
+    "pytest~=9.0",
+    "imageio~=2.0",
 ]
 cuda12 = ["cupy-cuda12x"]
 cuda13 = ["cupy-cuda13x"]
@@ -35,6 +37,9 @@ tensorflow = ["tensorflow~=2.14"]
 [project.scripts]
 ptylab = "PtyLab.utils.cli:main"
 
+[tool.pytest.ini_options]
+testpaths = ["tests"]
+
 [build-system]
 requires = ["uv_build>=0.6.1,<0.11"]
 build-backend = "uv_build"
diff --git a/tests/Engines/test_base_engine.py b/tests/Engines/test_base_engine.py
new file mode 100644
index 00000000..99dbd593
--- /dev/null
+++ b/tests/Engines/test_base_engine.py
@@ -0,0 +1,41 @@
+import pytest
+import numpy as np
+import logging
+import PtyLab
+
+try:
+    import cupy as cp
+    HAS_GPU = True
+except ImportError:
+    cp = None
+    HAS_GPU = False
+
+
+@pytest.fixture
+def engine_setup():
+    experimentalData, reconstruction, params, monitor, ePIE_engine = PtyLab.easyInitialize(
+        "example:simulation_cpm", operationMode="CPM"
+    )
+    return reconstruction, ePIE_engine
+
+
+def test_move_data_to_cpu(engine_setup):
+    reconstruction, ePIE_engine = engine_setup
+    ePIE_engine.reconstruction.logger.setLevel(logging.DEBUG)
+    ePIE_engine._move_data_to_cpu()
+    ePIE_engine._move_data_to_cpu()
+    assert type(ePIE_engine.reconstruction.object) is np.ndarray
+
+
+@pytest.mark.skipif(not HAS_GPU, reason="no GPU available")
+def test_move_data_to_gpu(engine_setup):
+    reconstruction, ePIE_engine = engine_setup
+    ePIE_engine.reconstruction.logger.setLevel(logging.DEBUG)
+    ePIE_engine._move_data_to_gpu()
+    ePIE_engine._move_data_to_gpu()
+    assert type(ePIE_engine.reconstruction.object) is cp.ndarray
+
+
+@pytest.mark.skip(reason="incomplete/experimental test")
+def test_position_correction(engine_setup):
+    pass
diff --git a/tests/Engines/test_base_reconstructor.py b/tests/Engines/test_base_reconstructor.py
new file mode 100644
index 00000000..0b6f62b3
--- /dev/null
+++ b/tests/Engines/test_base_reconstructor.py
@@ -0,0 +1,22 @@
+import pytest
+from PtyLab.Reconstruction.Reconstruction import Reconstruction
+from PtyLab.ExperimentalData.ExperimentalData import ExperimentalData
+from PtyLab.Params.Params import Params
+from PtyLab.Monitor.Monitor import Monitor
+from PtyLab.Engines.BaseEngine import BaseEngine
+
+
+@pytest.fixture
+def engine():
+    experimentalData = ExperimentalData("test:nodata")
+    params = Params()
+    monitor = Monitor()
+    optimizable = Reconstruction(experimentalData, params)
+    return BaseEngine(optimizable, experimentalData, params, monitor), experimentalData
+
+
+def test_change_optimizable(engine):
+    BR, experimentalData = engine
+    optimizable2 = Reconstruction(experimentalData, Params())
+    BR.changeOptimizable(optimizable2)
+    assert BR.reconstruction is optimizable2
diff --git a/tests/Engines/test_epie.py b/tests/Engines/test_epie.py
new file mode 100644
index 00000000..280265ba
--- /dev/null
+++ b/tests/Engines/test_epie.py
@@ -0,0 +1,19 @@
+import pytest
+from PtyLab.Reconstruction.Reconstruction import Reconstruction
+from PtyLab.ExperimentalData.ExperimentalData import ExperimentalData
+from PtyLab.Params.Params import Params
+from PtyLab.Monitor.Monitor import Monitor
+from PtyLab.Engines.ePIE import ePIE
+
+
+@pytest.fixture
+def epie_engine():
+    experimentalData = ExperimentalData("test:nodata")
+    params = Params()
+    monitor = Monitor()
+    optimizable = Reconstruction(experimentalData, params)
+    return ePIE(optimizable, experimentalData, params, monitor)
+
+
+def test_init(epie_engine):
+    pass
diff --git a/tests/Engines/test_propagator.py b/tests/Engines/test_propagator.py
new file mode 100644
index 00000000..faae5953
--- /dev/null
+++ b/tests/Engines/test_propagator.py
@@ -0,0 +1,36 @@
+import pytest
+from numpy.testing import assert_almost_equal
+
+from PtyLab.Engines.ePIE import ePIE
+from PtyLab.ExperimentalData.ExperimentalData import ExperimentalData
+from PtyLab.Monitor.Monitor import Monitor
+from PtyLab.Params.Params import Params
+from PtyLab.Reconstruction.Reconstruction import Reconstruction
+
+
+@pytest.mark.skip(reason="missing example data file: simulation_ptycho")
+def test_fresnel_propagator_round_trip():
+    exampleData = ExperimentalData()
+    exampleData.loadData("example:simulation_ptycho")
+    exampleData.operationMode = "CPM"
+
+    params = Params()
+    params.propagatorType = "ASP"
+
+    optimizable = Reconstruction(exampleData, params)
+    optimizable.npsm = 1
+    optimizable.nosm = 1
+    optimizable.nlambda = 1
+    optimizable.initializeObjectProbe()
+
+    monitor = Monitor()
+    ePIE_engine = ePIE(optimizable, exampleData, params, monitor)
+    ePIE_engine.numIterations = 1
+    for _ in ePIE_engine.reconstruct():
+        pass
+
+    A = optimizable.esw
+    ePIE_engine.object2detector()
+    ePIE_engine.detector2object()
+
+    assert_almost_equal(A, optimizable.esw)
diff --git a/tests/Monitor/test_TensorboardMonitor.py b/tests/Monitor/test_TensorboardMonitor.py
new file mode 100644
index 00000000..21253975
--- /dev/null
+++ b/tests/Monitor/test_TensorboardMonitor.py
@@ -0,0 +1,53 @@
+import pytest
+import numpy as np
+pytest.importorskip("tensorflow")
+from PtyLab.Monitor.TensorboardMonitor import TensorboardMonitor
+
+imageio = pytest.importorskip("imageio")
+
+
+@pytest.fixture
+def monitor():
+    return TensorboardMonitor(name="testing purposes only")
+
+
+def test_diffraction_data(monitor):
+    estimated = imageio.imread("imageio:camera.png")
+    measured = np.fliplr(estimated)
+    for i in range(10):
+        monitor.i = i
+        monitor.updateDiffractionDataMonitor(estimated, measured)
+
+
+def test_update_object_probe(monitor):
+    object_estimate = np.random.rand(1, 1280, 1280)
+    probe_estimate = np.random.rand(1, 64, 64) * 1j
+    for i in range(10):
+        monitor.updatePlot(object_estimate, probe_estimate)
+
+
+def test_update_error(monitor):
+    errors = np.random.rand(100).cumsum()[::-1]
+    for e in errors:
+        monitor.i += 1
+        monitor.updateObjectProbeErrorMonitor(e)
+        monitor.updateObjectProbeErrorMonitor([e])
+
+
+def test_update_z(monitor):
+    z = np.random.rand(100) / 100
+    z[0] = 10
+    z[30:50] = 0
+    z[80:120] = 0
+    z = z.cumsum()
+    for zi in z:
+        monitor.i += 1
+        monitor.update_z(zi)
+
+
+def test_update_positions(monitor):
+    positions = np.random.rand(100, 2).cumsum(axis=1)
+    positions = np.cos(positions)
+    scaling = 1.5
+    other_positions = positions + np.random.rand(*positions.shape) * 1e-2
+    monitor.update_positions(positions, scaling * other_positions, scaling)
diff --git a/tests/Monitor/test_center_angle.py b/tests/Monitor/test_center_angle.py
new file mode 100644
index 00000000..c2b8c49f
--- /dev/null
+++ b/tests/Monitor/test_center_angle.py
@@ -0,0 +1,15 @@
+import pytest
+import matplotlib
+matplotlib.use("Agg")
+import numpy as np
+pytest.importorskip("tensorflow")
+from PtyLab.Monitor.TensorboardMonitor import center_angle
+from scipy import ndimage
+
+
+def test_center_angle():
+    N = 128
+    Ein = np.fft.fftshift(ndimage.fourier_shift(np.ones((N, N)), [5, 0]))
+    Ein_c = center_angle(Ein)
+    assert Ein_c is not None
+    assert Ein_c.shape == Ein.shape
diff --git a/tests/Monitor/test_matplotlib_monitor.py b/tests/Monitor/test_matplotlib_monitor.py
new file mode 100644
index 00000000..6fe8d577
--- /dev/null
+++ b/tests/Monitor/test_matplotlib_monitor.py
@@ -0,0 +1,45 @@
+import pytest
+import numpy as np
+from PtyLab.Monitor.Plots import ObjectProbeErrorPlot
+from PtyLab.Engines.BaseEngine import BaseEngine
+from PtyLab.Reconstruction.Reconstruction import Reconstruction
+from PtyLab.ExperimentalData.ExperimentalData import ExperimentalData
+from PtyLab.Params.Params import Params
+from PtyLab.Monitor.Monitor import Monitor
+
+
+@pytest.mark.skip(reason="Visual test - requires manual inspection")
+class TestMatplotlibMonitor:
+    @pytest.fixture(autouse=True)
+    def setup(self):
+        self.monitor = ObjectProbeErrorPlot()
+
+    def test_create_figure(self):
+        pass
+
+    def test_live_update(self):
+        error_metrics = []
+        for k in range(100):
+            error_metrics.append(np.random.rand())
+            self.monitor.updateObject(np.random.rand(100, 100))
+            self.monitor.updateError(error_metrics)
+            self.monitor.drawNow()
+
+
+@pytest.mark.skip(reason="Visual test - requires manual inspection")
+class TestPlotFromBaseReconstructor:
+    @pytest.fixture(autouse=True)
+    def setup(self):
+        self.experimentalData = ExperimentalData("example:simulationTiny")
+        self.params = Params()
+        self.monitor = Monitor()
+        self.optimizable = Reconstruction(self.experimentalData, self.params)
+        self.optimizable.initializeObjectProbe()
+        self.BR = BaseEngine(self.optimizable, self.experimentalData, self.params, self.monitor)
+
+    def test_show_reconstruction(self):
+        self.BR.reconstruction.initializeObjectProbe()
+        self.BR.monitor.figureUpdateFrequency = 20
+        self.BR.showReconstruction(0)
+        for i in range(1000):
+            self.BR.showReconstruction(i)
diff --git a/tests/Operators/test_operators.py b/tests/Operators/test_operators.py
new file mode 100644
index 00000000..aef68b43
--- /dev/null
+++ b/tests/Operators/test_operators.py
@@ -0,0 +1,44 @@
+import pytest
+import numpy as np
+from numpy.testing import assert_almost_equal
+import unittest
+from PtyLab.Operators.Operators import aspw, scaledASP, fresnelPropagator
+from PtyLab.utils.utils import circ
+
+
+@pytest.fixture
+def wave_params():
+    dx = 5e-6
+    N = 100
+    x = np.arange(-N / 2, N / 2) * dx
+    X, Y = np.meshgrid(x, x)
+    return {
+        "dx": dx,
+        "E_in": circ(X, Y, N / 2 * dx).astype(float),
+        "wavelength": 600e-9,
+        "z": 1e-4,
+        "L": dx * N,
+    }
+
+
+def test_aspw(wave_params):
+    p = wave_params
+    E_1, _ = aspw(p["E_in"], 0, p["wavelength"], p["L"], is_FT=False)
+    E_2, _ = aspw(E_1, p["z"], p["wavelength"], p["L"], is_FT=False)
+    E_3, _ = aspw(E_2, -p["z"], p["wavelength"], p["L"], is_FT=False)
+    assert_almost_equal(p["E_in"], E_1)
+    assert_almost_equal(abs(E_1), abs(E_3))
+
+
+def test_scaledASP(wave_params):
+    p = wave_params
+    E_1, _, _ = scaledASP(p["E_in"], p["z"], p["wavelength"], p["dx"], p["dx"])
+    E_2, _, _ = scaledASP(E_1, -p["z"], p["wavelength"], p["dx"], p["dx"])
+    assert_almost_equal(abs(E_2), abs(p["E_in"]))
+
+
+@pytest.mark.skip(reason="fresnelPropagator not yet validated")
+def test_fresnelPropagator(wave_params):
+    p = wave_params
+    E_out = fresnelPropagator(p["E_in"], 0, p["wavelength"], p["L"])
+    assert_almost_equal(p["E_in"], E_out)
diff --git a/tests/Operators/test_operators_integration.py b/tests/Operators/test_operators_integration.py
new file mode 100644
index 00000000..5c630097
--- /dev/null
+++ b/tests/Operators/test_operators_integration.py
@@ -0,0 +1,79 @@
+import pytest
+import numpy as np
+from numpy.testing import assert_allclose
+
+from PtyLab import Operators, easyInitialize
+
+try:
+    import cupy as cp
+    HAS_GPU = True
+except ImportError:
+    cp = None
+    HAS_GPU = False
+
+
+@pytest.mark.skip(reason="requires cupyx and GPU; performance benchmark only")
+def test_caching_aspw():
+    xp = cp if HAS_GPU else np
+    E = xp.random.rand(10, 1, 3, 512, 512)
+    z = 1e-3
+    wl = 512e-9
+    pixel_pitch = 10e-6
+    L = pixel_pitch * E.shape[-1]
+
+    E_prop = Operators.Operators.aspw_cached(E, z, wl, L)
+    if HAS_GPU:
+        E_prop = xp.asnumpy(E_prop)
+
+    E_prop2 = Operators.Operators.aspw(E, z, wl, L)[0]
+    if HAS_GPU:
+        E_prop2 = E_prop2.get()
+
+    assert_allclose(E_prop, E_prop2)
+
+
+def test_object2detector():
+    experimentalData, reconstruction, params, monitor, engine = easyInitialize(
+        "example:simulation_cpm"
+    )
+    params.gpuSwitch = False
+    reconstruction._move_data_to_cpu()
+    for operator_name in Operators.Operators.forward_lookup_dictionary:
+        params.propagatorType = operator_name
+        reconstruction.esw = reconstruction.probe
+        Operators.Operators.object2detector(reconstruction.esw, params, reconstruction)
+
+
+def test_propagate_fresnel():
+    experimentalData, reconstruction, params, monitor, engine = easyInitialize(
+        "example:simulation_cpm"
+    )
+    reconstruction.initializeObjectProbe()
+    reconstruction.esw = 2
+    params.gpuSwitch = False
+    reconstruction._move_data_to_cpu()
+
+    for operator in [
+        Operators.Operators.propagate_fresnel,
+        Operators.Operators.propagate_ASP,
+        Operators.Operators.propagate_scaledASP,
+        Operators.Operators.propagate_twoStepPolychrome,
+        Operators.Operators.propagate_scaledPolychromeASP,
+    ]:
+        operator(reconstruction.probe, params, reconstruction)
+
+
+@pytest.mark.skip(reason="placeholder - not implemented")
+def test_aspw_cached():
+    pass
+
+
+def test_propagate_asp_fft_equivalence():
+    experimentalData, reconstruction, params, monitor, engine = easyInitialize(
+        "example:simulation_cpm"
+    )
+    reconstruction.esw = None
+    a = reconstruction.probe
+    P1 = Operators.Operators.propagate_ASP(a, params, reconstruction, z=1e-3, fftflag=False)[1]
+    P2 = Operators.Operators.propagate_ASP(a, params, reconstruction, z=1e-3, fftflag=True)[1]
+    assert_allclose(P1, P2)
diff --git a/PtyLab/ProbeEngines/test_OPRP.py b/tests/ProbeEngines/test_OPRP.py
similarity index 87%
rename from PtyLab/ProbeEngines/test_OPRP.py
rename to tests/ProbeEngines/test_OPRP.py
index 4389872e..b2166854 100644
--- a/PtyLab/ProbeEngines/test_OPRP.py
+++ b/tests/ProbeEngines/test_OPRP.py
@@ -1,8 +1,15 @@
+import pytest
 from numpy.testing import assert_almost_equal
-
-from PtyLab.ProbeEngines.OPRP import OPRP_storage
 import numpy as np
 
+try:
+    from PtyLab.ProbeEngines.OPRP import OPRP_storage
+    HAS_PROBEENGINES = True
+except (ImportError, ValueError):
+    HAS_PROBEENGINES = False
+
+pytestmark = pytest.mark.skipif(not HAS_PROBEENGINES, reason="ProbeEngines not ready")
+
 
 def test_push():
     N = 100
@@ -41,7 +48,6 @@ def test_push():
         p1 = storage.get(i)
         try:
             assert_almost_equal(p1, probes[i], decimal=5)
-
         except AssertionError:
             print(f"Failed for i={i}")
             print(p1.shape, probes[i].shape)
@@ -60,7 +66,4 @@ def test_center_probe():
         p_inout, _ = storage.uncenter_probe(storage.center_probe(p, i)[0], i)
         assert_almost_equal(p, p_inout)
         probes[i], shift = storage.center_probe(p, i)
-        print("first round: ", shift)
-
         probes[i], shift = storage.center_probe(p, i)
-        print("second round", shift)
diff --git a/tests/ProbeEngines/test_StandardProbe.py b/tests/ProbeEngines/test_StandardProbe.py
new file mode 100644
index 00000000..6d7dcc14
--- /dev/null
+++ b/tests/ProbeEngines/test_StandardProbe.py
@@ -0,0 +1,25 @@
+import pytest
+import numpy as np
+
+try:
+    from PtyLab.ProbeEngines.StandardProbe import SHGProbe
+    HAS_PROBEENGINES = True
+except (ImportError, ValueError):
+    HAS_PROBEENGINES = False
+
+pytestmark = pytest.mark.skipif(not HAS_PROBEENGINES, reason="ProbeEngines not ready")
+
+if HAS_PROBEENGINES:
+    imageio = pytest.importorskip("imageio")
+
+
+def test_shg_probe_convergence():
+    target = imageio.imread("imageio:camera.png").astype(np.float32)
+    target = target / np.linalg.norm(target)
+    engine = SHGProbe()
+    engine.probe = np.random.rand(*target.shape)
+
+    for i in range(1000):
+        current_estimate = engine.get(None)
+        new_estimate = target
+        engine.push(new_estimate, None, None)
diff --git a/tests/Reconstruction/test_optimizable.py b/tests/Reconstruction/test_optimizable.py
new file mode 100644
index 00000000..6c2c8eb5
--- /dev/null
+++ b/tests/Reconstruction/test_optimizable.py
@@ -0,0 +1,29 @@
+import logging
+import pytest
+from numpy.testing import assert_array_almost_equal
+from PtyLab.ExperimentalData.ExperimentalData import ExperimentalData
+from PtyLab.Reconstruction.Reconstruction import Reconstruction
+from PtyLab.Params.Params import Params
+
+logging.basicConfig(level=logging.DEBUG)
+
+
+@pytest.fixture
+def reconstruction():
+    data = ExperimentalData("test:nodata")
+    data.wavelength = 1234
+    return data, Reconstruction(data, Params())
+
+
+def test_copy_scalar_attribute(reconstruction):
+    data, optimizable = reconstruction
+    assert optimizable.wavelength == data.wavelength
+    optimizable.wavelength = 4321
+    assert optimizable.wavelength != data.wavelength
+
+
+@pytest.mark.skip(reason="positions is a computed property, not a settable attribute")
+def test_copy_array_attribute(reconstruction):
+    data, optimizable = reconstruction
+    optimizable.positions += 1
+    assert_array_almost_equal(optimizable.positions - 1, data.positions)
diff --git a/tests/Regularizers/test_regularizers.py b/tests/Regularizers/test_regularizers.py
new file mode 100644
index 00000000..c2f8112e
--- /dev/null
+++ b/tests/Regularizers/test_regularizers.py
@@ -0,0 +1,21 @@
+import pytest
+import numpy as np
+from numpy.testing import assert_allclose
+from PtyLab.Regularizers import divergence, grad_TV
+
+
+@pytest.fixture
+def complex_object():
+    shape = (1, 1, 1, 1, 380, 380)
+    obj = np.random.rand(*shape) + 1j * np.random.rand(*shape)
+    return obj - (0.5 + 0.5j)
+
+
+def test_grad_tv_matches_divergence(complex_object):
+    epsilon = 1e-2
+    gradient = np.gradient(complex_object, axis=(4, 5))
+    norm = (gradient[0] + gradient[1]) ** 2
+    temp = [gradient[0] / np.sqrt(norm + epsilon), gradient[1] / np.sqrt(norm + epsilon)]
+    TV_update = divergence(temp)
+    TV_update_2 = grad_TV(complex_object, epsilon)
+    assert_allclose(TV_update, TV_update_2)
diff --git a/tests/io/test_example_loader.py b/tests/io/test_example_loader.py
new file mode 100644
index 00000000..1c51f1f7
--- /dev/null
+++ b/tests/io/test_example_loader.py
@@ -0,0 +1,16 @@
+import pytest
+import numpy as np
+from PtyLab.io import readExample
+
+
+@pytest.mark.skip(reason="missing example data file: LungCarcinomaSmallFPM.hdf5")
+def test_read_example_fpm():
+    readExample.listExamples()
+    archive = readExample.loadExample("simulation_fpm")
+    assert np.array(archive["Nd"], int) == 256
+
+
+@pytest.mark.skip(reason="missing example data file: simulationTiny.hdf5")
+def test_read_example_simulation_tiny():
+    archive = readExample.loadExample("simulationTiny")
+    assert np.array(archive["Nd"], int) == 64
diff --git a/tests/io/test_get_example_data_folder.py b/tests/io/test_get_example_data_folder.py
new file mode 100644
index 00000000..e0cac608
--- /dev/null
+++ b/tests/io/test_get_example_data_folder.py
@@ -0,0 +1,16 @@
+import pytest
+from PtyLab.io import getExampleDataFolder
+
+
+def test_example_folder_exists():
+    example_data_folder = getExampleDataFolder()
+    assert example_data_folder.exists(), (
+        "example data folder returned does not exist on the filesystem"
+    )
+
+
+@pytest.mark.skip(reason="missing example data file: simulationTiny.hdf5")
+def test_simulation_tiny_in_example_data():
+    example_data_folder = getExampleDataFolder()
+    matlabfile = example_data_folder / "simulationTiny.hdf5"
+    assert matlabfile.exists(), "`simulationTiny.hdf5` is not present in the example data folder"
diff --git a/tests/io/test_load_input_data.py b/tests/io/test_load_input_data.py
new file mode 100644
index 00000000..dfe3b086
--- /dev/null
+++ b/tests/io/test_load_input_data.py
@@ -0,0 +1,11 @@
+import pytest
+from PtyLab.io import getExampleDataFolder
+from PtyLab.io.readHdf5 import loadInputData
+
+
+@pytest.mark.skip(reason="missing example data file: fourier_simulation.hdf5")
+def test_load_input_data():
+    example_data_folder = getExampleDataFolder()
+    filename = example_data_folder / "fourier_simulation.hdf5"
+    result = loadInputData(filename)
+    assert result["ptychogram"].shape == (49, 256, 256)
diff --git a/tests/utils/test_complex_plot.py b/tests/utils/test_complex_plot.py
new file mode 100644
index 00000000..12e6617e
--- /dev/null
+++ b/tests/utils/test_complex_plot.py
@@ -0,0 +1,12 @@
+import matplotlib
+matplotlib.use("Agg")
+import numpy as np
+import matplotlib.pyplot as plt
+from PtyLab.utils.visualisation import complex2rgb, complexPlot
+
+
+def test_complex_plot():
+    testComplexArray = np.ones((100, 100)) * (1 + 1j)
+    testRGBArray = complex2rgb(testComplexArray)
+    complexPlot(testRGBArray)
+    plt.close("all")
diff --git a/tests/utils/test_fft2c_ifft2c.py b/tests/utils/test_fft2c_ifft2c.py
new file mode 100644
index 00000000..34d2d9be
--- /dev/null
+++ b/tests/utils/test_fft2c_ifft2c.py
@@ -0,0 +1,9 @@
+import numpy as np
+from numpy.testing import assert_almost_equal
+from PtyLab.utils.utils import fft2c, ifft2c
+
+
+def test_fft2c_ifft2c_unitary():
+    E_in = np.random.rand(5, 100, 100) + 1j * np.random.rand(5, 100, 100) - 0.5 - 0.5j
+    assert_almost_equal(ifft2c(fft2c(E_in)), E_in)
+    assert_almost_equal(fft2c(ifft2c(E_in)), E_in)
diff --git a/tests/utils/test_initialization_functions.py b/tests/utils/test_initialization_functions.py
new file mode 100644
index 00000000..65597ec0
--- /dev/null
+++ b/tests/utils/test_initialization_functions.py
@@ -0,0 +1,23 @@
+import pytest
+import PtyLab
+
+
+@pytest.mark.skip(reason="missing example data file: ptyLab_helical_beam.h5")
+def test_initial_probe_circ_smooth():
+    experimentalData, reconstruction, params, monitor, ePIE_engine = PtyLab.easyInitialize(
+        "example:helicalbeam", operationMode="CPM", engine=PtyLab.Engines.mPIE
+    )
+    experimentalData.setOrientation(4)
+    experimentalData.entrancePupilDiameter = 30 * reconstruction.dxo
+
+    reconstruction = PtyLab.Reconstruction(experimentalData, params)
+    reconstruction.copyAttributesFromExperiment(experimentalData)
+    reconstruction.initialProbe = "circ_smooth"
+    reconstruction.initializeObjectProbe()
+
+    engine = PtyLab.Engines.mPIE(
+        reconstruction, experimentalData, params=params, monitor=monitor
+    )
+    engine.numIterations = 50
+    monitor.probeZoom = None
+    engine.reconstruct()