Merge eis into main, as prep for release 0.4.0

CHANGELOG.md

@@ -8,6 +8,22 @@ The changelog format is based on [Keep a Changelog](https://keepachangelog.com/e
 * -/-
 
 
+## [0.4.0] - 2026-03-12
+
+### Breaking Changes
+* src/component_model/utils/controls.py: Refactored `Controls` from a multi-variable container into per-variable `Control` objects with typed read/write access, and improved goal tracking so initial speed and acceleration are handled correctly when setting or changing goals.
+* src/component_model/utils/analysis.py: Reworked sine fitting by moving the `sine_fit()` function from `component_model.analytic` into `component_model.utils.analysis` and expanding it to fit offset sine waves, detect cycles from maxima, support cosine-like starts, and return offset, amplitude, angular frequency, phase, and a reference mid-time.
+
+### Resolved
+* Fixed coordinate transform handling for vectors pointing in the negative z-direction.
+
+### Changed
+* Relaxed range compatibility checks for units and promoted scipy from a test-only dependency to a runtime package dependency, aligning dependencies with actual package usage.
+* Cleaned up FMU test artifacts by removing generated FMU binaries from the examples folder, building FMUs into the test working directory instead, ignoring generated .dat files, and switching shared test fixtures to session scope.
+* Added or updated tests for the new controls behavior, sine fitting, transform handling, and FMU build workflow.
+* Included minor follow-up cleanup such as corrected example text typos, small README/docstring/formatting updates, and lockfile refreshes.
+
+
 ## [0.3.2] - 2026-02-02
 
 ### Added
@@ -139,7 +155,8 @@ The changelog format is based on [Keep a Changelog](https://keepachangelog.com/e
 
 
 <!-- Markdown link & img dfn's -->
-[unreleased]: https://github.com/dnv-innersource/component-model/compare/v0.3.2...HEAD
+[unreleased]: https://github.com/dnv-innersource/component-model/compare/v0.4.0...HEAD
+[0.4.0]: https://github.com/dnv-innersource/component-model/compare/v0.3.2...v0.4.0
 [0.3.2]: https://github.com/dnv-innersource/component-model/compare/v0.3.1...v0.3.2
 [0.3.1]: https://github.com/dnv-innersource/component-model/compare/v0.3.0...v0.3.1
 [0.3.0]: https://github.com/dnv-innersource/component-model/compare/v0.2.0...v0.3.0

CITATION.cff

@@ -1,5 +1,5 @@
 title: component-model
-version: 0.3.2
+version: 0.4.0
 abstract: >-
     Constructs a Functional Mockup Interface component model from a python script (fulfilling some requirements).
 type: software

README.rst

@@ -301,7 +301,7 @@ Development Setup
 
 1. Install uv
 ^^^^^^^^^^^^^
-This project uses `uv` as package manager.
+This project uses ``uv`` as package manager.
 
 If you haven't already, install `uv <https://docs.astral.sh/uv/>`_, preferably using it's `"Standalone installer" <https://docs.astral.sh/uv/getting-started/installation/#__tabbed_1_2/>`_ method:
 
@@ -319,7 +319,7 @@ If you haven't already, install `uv <https://docs.astral.sh/uv/>`_, preferably u
 
 (see `docs.astral.sh/uv <https://docs.astral.sh/uv/getting-started/installation//>`_ for all / alternative installation methods.)
 
-Once installed, you can update `uv` to its latest version, anytime, by running:
+Once installed, you can update ``uv`` to its latest version, anytime, by running:
 
 .. code:: sh
 
@@ -381,7 +381,7 @@ Run ``uv sync -U`` to create a virtual environment and install all project depen
    **Note**: ``uv`` will create a new virtual environment called
    ``.venv`` in the project root directory when running ``uv sync -U``
    the first time. Optionally, you can create your own virtual
-   environment using e.g. ``uv venv``, before running ``uv sync -U``.
+   environment using e.g. ``uv venv``, before running ``uv sync -U``.
 
 
 5. (Optional) Activate the virtual environment

docs/source/conf.py

@@ -26,7 +26,7 @@
 author = "Siegfried Eisinger, Jorge Luis Mendez"
 
 # The full version, including alpha/beta/rc tags
-release = "0.3.2"
+release = "0.4.0"
 
 # -- General configuration ---------------------------------------------------
 # https://www.sphinx-doc.org/en/master/usage/configuration.html#general-configuration

examples/axle_fmu.py

@@ -64,23 +64,23 @@ def __init__(
         self._rpm0 = Variable(
             self,
             "wheels[0].motor.rpm",
-            "Angualar speed of wheel 1 in rad/s:",
+            "Angular speed of wheel 1 in rad/s:",
             causality="input",
             variability="continuous",
             start=f"{rpm1} 1/s",
         )
         self._rpm1 = Variable(
             self,
             "wheels[1].motor.rpm",
-            "Angualar speed of wheel 2 in rad/s:",
+            "Angular speed of wheel 2 in rad/s:",
             causality="input",
             variability="continuous",
             start=f"{rpm2} 1/s",
         )
         self._acc0 = Variable(
             self,
             "der(wheels[0].motor.rpm)",
-            "Angualar acceleration of wheel 1 in rad/s**2:",
+            "Angular acceleration of wheel 1 in rad/s**2:",
             causality="input",
             variability="continuous",
             start="0.0 1/s**2",
@@ -90,7 +90,7 @@ def __init__(
             Variable(
                 self,
                 "der(wheels[1].motor.rpm)",
-                "Angualar acceleration of wheel 2 in rad/s**2:",
+                "Angular acceleration of wheel 2 in rad/s**2:",
                 causality="input",
                 variability="continuous",
                 start="0.0 1/s**2",

pyproject.toml

@@ -30,7 +30,7 @@ allow-direct-references = true
 
 [project]
 name = "component-model"
-version = "0.3.2"
+version = "0.4.0"
 description = "Constructs a Functional Mockup Interface component model from a python script (fulfilling some requirements)."
 readme = "README.rst"
 requires-python = ">= 3.11"
@@ -66,13 +66,12 @@ dependencies = [
     "jsonpath-ng>=1.7.0",
     "pythonfmu>=0.7.0",
     "flexparser>=0.4",
-    "scipy-stubs>=1.17.0.0",
+    "scipy>=1.16",
 ]
 
 [project.optional-dependencies]
 test = [
-    "fmpy==0.3.21", # version 0.3.22 does so far (25.3.25) not workwhen installing through pip
-    "scipy>=1.16",
+    "fmpy>=0.3.21", # version 0.3.22 does so far (25.3.25) not workwhen installing through pip
     "matplotlib>=3.10",
     "plotly>=6.3",
     "libcosimpy>=0.0.5",
@@ -103,6 +102,7 @@ dev = [
     "sphinxcontrib-mermaid>=1.0.0",
     "myst-parser>=4.0",
     "furo>=2025.9",
+    "scipy-stubs>=1.17.0.0",
 ]
 
 [tool.uv]

src/component_model/analytic.py

@@ -163,59 +163,3 @@ def period(self):
             return 2 * np.pi / self.wd
         else:
             return float("inf")
-
-
-def sine_fit(times: list[float] | np.ndarray, vals: list[float] | np.ndarray, max_pcov: float = 1e-2):
-    """Fit a general sine function f(t) = a* sin(w*t + phi) to the data and return (a,omega,phi).
-
-    * The last two upward zero-crossings of the data set are detected and a full sine wave is fit to that.
-    * Error is issued if zero-crossings are not found.
-    * Warning is provided if the fit to the sine function is bad (diag(pcov) > max_pcov).
-    * The phase angle is returned in the range ]-pi, pi]
-    """
-    from scipy.optimize import curve_fit
-
-    def do_fit(x: np.ndarray, y: np.ndarray):
-        """Perform a sind function fit on the given data and return parameters."""
-
-        def func(x: float | np.ndarray, a: float, w: float, phi: float, /):
-            return a * np.sin(w * x + phi)
-
-        popt, pcov = curve_fit(func, x, y)
-        if max(np.diag(pcov)) > max_pcov:
-            logger.warning(f"Curve cannot be fitted well to sine function: {np.diag(pcov)}. Detected to:{x[0]}")
-        return popt
-
-    times = np.array(times, float)
-    vals = np.array(vals)
-    zero0, zero1, previous = None, None, None
-    for t, v in reversed(list(zip(times, vals, strict=True))):
-        if previous is not None:
-            if np.sign(v) == 0 and np.sign(previous[1]) == 1:
-                if zero1 is None:
-                    zero1 = list(times).index(t)
-                else:
-                    zero0 = list(times).index(t)
-                    break
-            elif np.sign(v) == -1 and np.sign(previous[1]) == 1:
-                if zero1 is None:
-                    zero1 = list(times).index(previous[0])
-                else:
-                    zero0 = list(times).index(t)
-                    break
-        previous = (t, v)
-    assert zero0 is not None and zero1 is not None, "Zeroes not found"
-    t0 = times[zero0]
-
-    a, w, phi = do_fit(times[zero0 : zero1 + 1] - t0, vals[zero0 : zero1 + 1])
-    if w < 0:
-        a, w, phi = -a, -w, -phi
-    if a < 0:
-        a = -a
-        phi += np.pi
-    phi -= w * t0 % (2 * np.pi)
-    while phi > np.pi - 1e-14:
-        phi -= 2 * np.pi
-    while phi <= -np.pi + 1e-14:
-        phi += 2 * np.pi
-    return a, w, phi

src/component_model/model.py

@@ -651,10 +651,12 @@ def _xml_structure_initialunknowns(self):
         init = ET.Element("InitialUnknowns")
 
         for v in filter(
-            lambda v: v is not None
-            and (
-                (v.causality == Causality.output and v.initial in (Initial.approx, Initial.calculated))
-                or (v.causality == Causality.calculatedParameter)
+            lambda v: (
+                v is not None
+                and (
+                    (v.causality == Causality.output and v.initial in (Initial.approx, Initial.calculated))
+                    or (v.causality == Causality.calculatedParameter)
+                )
             ),
             self.vars.values(),
         ):

src/component_model/range.py

@@ -59,7 +59,7 @@ def __init__(
                     l_rng[i] = val  # type: ignore[reportArgumentType] ## l_rng is not empty # fixed display value
                 else:
                     assert isinstance(r, (str, int, bool, float, Enum)), f"Found type {type(r)}"
-                    check, q = unit.compatible(r, no_unit=False, strict=True)  # q in base units
+                    check, q = unit.compatible(r, no_unit=False, strict=False)  # q in base units
                     if not check:
                         raise ValueError(f"Provided range {rng}[{i}] is not conformant with unit {unit}") from None
                     assert isinstance(q, (int, bool, float)), "Unexpected type {type(q)} in {rng}[{i}]"

src/component_model/utils/analysis.py

@@ -44,7 +44,8 @@ def w_1(x: float):
     def w0(x: float):
         return abs(x)
 
-    assert len(t) == len(y) > 2, "Something wrong with lengths of t ({len(t)}) and y ([len(y)})"
+    assert len(t) == len(y), f"Length of sequences t:{len(t)} != y:{len(y)}"
+    assert len(t) > 2, f"Sequences t and y shall be longer than 2, but length was {len(t)} for both"
     if which == "max":
         w = w1
     elif which == "min":
@@ -58,3 +59,85 @@ def w0(x: float):
         if e != 0 and w(e) == 1 and p[0] < t[i]:
             res.append(p)
     return res
+
+
+def sine_fit(times: list[float] | np.ndarray, vals: list[float] | np.ndarray, eps: float = 1e-2):
+    """Fit a general sine function f(t) = y0 + a* sin(w*t + phi) to the data end and return (y0, a,omega,phi).
+
+    * The last two maximum points of the data set are detected and a full sine wave is fit to that.
+    * Error is issued if maximum points are not found.
+    * Warning is provided if the fit to the sine function is bad (diag(pcov) > eps).
+    * If the curve starts with maxima (cos(...)), it is accepted if the first points fit a 2nd order within eps.
+    * The phase angle is returned in the range ]-pi, pi]
+    * Returns the zero-line, the amplitude, the angualar frequency, the phase and the mid-time of the wave.
+    """
+    from scipy.optimize import curve_fit
+
+    def do_fit(x: np.ndarray, y: np.ndarray):
+        """Perform a sin function fit on the given data and return parameters."""
+
+        def func(x: float | np.ndarray, y0: float, a: float, w: float, phi: float, /):
+            return y0 + a * np.sin(w * x + phi)
+
+        avg = np.average(y)
+        popt, pcov = curve_fit(func, x, y, p0=(avg, y[0] - avg, 2 * np.pi / (x[-1] - x[0]), np.pi / 2))
+        if max(np.diag(pcov)) > eps:
+            logger.warning(f"Curve cannot be fitted well to sine function: {np.diag(pcov)}. Detected t0:{x[0]}")
+        return popt
+
+    def np_index(arr: np.ndarray, t: float):
+        """Get the closest index with respect to a value in the array."""
+        return np.absolute(arr - t).argmin()
+
+    times = np.array(times, float)
+    vals = np.array(vals)
+    state = 1
+    top1, top0 = None, None
+    for t1, v1, t2, v2 in reversed(list(zip(times[:-1], vals[:-1], times[1:], vals[1:], strict=True))):
+        if state == 1:  # upward slope at end of curve
+            if v2 <= v1:
+                state = 2
+        elif state == 2:  # decreasing curve. Search for last top point
+            if v2 > v1:  # found the last top point
+                top1 = np_index(times, t2)
+                state = 3
+        elif state == 3:  # increasing curve
+            if v2 <= v1:
+                state = 4
+        elif state == 4:
+            if v2 > v1:  # found the last top point
+                top0 = np_index(times, t1)
+                state = 5
+            elif t1 == times[0]:  # first point and first maximum not yet identified. Check whether max(2nd order)
+                t3 = times[2]
+                v3 = vals[2]
+                c = ((t3 - t1) * (v2 - v1) - (t2 - t1) * (v3 - v1)) / (
+                    (t3 - t1) * (t2**2 - t1**2) - (t2 - t1) * (t3**2 - t1**2)
+                )
+                b = ((v2 - v1) - c * (t2**2 - t1**2)) / (t2 - t1)
+                a = v1 - b * t1 - c * t1**2
+                if abs(b + 2 * c * t1) < eps and c < 0:  # accept as start of curve
+                    top0 = 0
+                    state = 5
+        elif state == 5:
+            break
+    if state == 4:
+        raise AssertionError(f"Only one maximum {vals[top1]}@{times[top1]} found.") from None
+    elif state < 4:
+        raise AssertionError("Maxima not found") from None
+    t0 = times[top0]
+
+    y0, a, w, phi = do_fit(times[top0:top1] - t0, vals[top0:top1])
+    phi -= w * t0  # correct for the time translation
+    if w < 0:
+        a, w, phi = -a, -w, -phi
+    if a < 0:
+        a = -a
+        phi += np.pi
+    # phi -= w * t0 % (2 * np.pi)
+    while phi > np.pi - 1e-14:
+        phi -= 2 * np.pi
+    while phi <= -np.pi + 1e-14:
+        phi += 2 * np.pi
+    assert top0 is not None and top1 is not None
+    return (y0, a, w, phi, times[int((top0 + top1) / 2)])