V1.0.2

.github/workflows/pull_request.yml

@@ -29,27 +29,6 @@ jobs:
       run: |
         pre-commit run -a
 
-  test_code_python3p8:
-    runs-on: ubuntu-latest
-    strategy:
-      matrix:
-        python-version: ["3.8"]
-    steps:
-    - uses: actions/checkout@v4
-    - name: Set up Python ${{ matrix.python-version }}
-      uses: actions/setup-python@v3
-      with:
-        python-version: ${{ matrix.python-version }}
-    - name: Install dependencies
-      run: |
-        python -m pip install --upgrade pip
-        pip install .[dev]
-    - name: Test code
-      run: |
-        mkdir test_report
-        tox
-
-
   test_code_and_coverage_report_python3p11:
     runs-on: ubuntu-latest
     strategy:

.gitignore

@@ -57,7 +57,7 @@ coverage.xml
 *.cover
 .hypothesis/
 .pytest_cache/
-
+test_report/
 # Translations
 *.mo
 *.pot

.gitlab-ci.yml

@@ -1,5 +1,5 @@
 # Default image, if not specified
-image: "python:3.8"
+image: "python:3.11"
 
 stages:
   - Static Analysis
@@ -98,23 +98,15 @@ mypy:
       junit: cov_report.xml
     expire_in: 1 hour
 
-tox-3.10:
-  extends: ".tox"
-  stage: "Test"
-  image: "python:3.6"
-  rules:
-    - if: '$CI_COMMIT_TAG'
-      when: always
-
 tox-3.11:
   extends: ".tox"
   stage: "Test"
   image: "python:3.11"
 
-tox-3.8:
+tox-3.9:
   extends: ".tox"
   stage: "Test"
-  image: "python:3.8"
+  image: "python:3.9"
   rules:
     - if: '$CI_COMMIT_TAG'
       when: always

comet_maths/_version.py

@@ -1 +1 @@
-__version__ = "1.0.0"
+__version__ = "1.0.6"

comet_maths/generate_sample/generate_sample.py

@@ -212,8 +212,10 @@ def generate_sample_same(MCsteps, param, dtype=None):
     :return: generated sample
     :rtype: array
     """
-    tileshape = generate_sample_shape(MCsteps, param)
-    MC_sample = np.tile(param, tileshape).astype(dtype)
+    # tileshape = generate_sample_shape(MCsteps, param)
+    MC_sample = np.repeat(np.array(param)[np.newaxis], MCsteps, axis=0)
+    if dtype is not None:
+        MC_sample = MC_sample.astype(dtype)
     return MC_sample
 
 
@@ -696,33 +698,39 @@ def correlate_sample_corr(
             "comet_math.correlate_sample_corr: it is not yet possible to provide a sample with inhomogeneous dimensions."
         )
 
-    try:
-        L = np.array(np.linalg.cholesky(corr))
-    except:
-        L = cm.nearestPD_cholesky(corr, corr=True)
-
-    if maintain_sample_unmodified:
-        sample_out = copy.deepcopy(sample)
-    else:
-        sample_out = sample
-
     if iterate_sample:
         sample_out_iter = np.empty(len(sample), dtype=object)
         for i in range(len(sample)):
-            sample_i = np.roll(sample_out, i, axis=0)
+            sample_i = np.roll(sample, i, axis=0)
             if mean is not None:
                 mean_i = np.roll(mean, i, axis=0)
             if std is not None:
                 std_i = np.roll(std, i, axis=0)
             sample_out_iter[i] = np.roll(
                 correlate_sample_corr(
-                    sample_i, corr, mean_i, std_i, dtype=dtype, iterate_sample=False
+                    sample_i,
+                    corr,
+                    mean_i,
+                    std_i,
+                    dtype=dtype,
+                    iterate_sample=False,
+                    maintain_sample_unmodified=True,
                 ),
                 -i,
                 axis=0,
             )
         return np.mean(sample_out_iter, axis=0)
 
+    try:
+        L = np.array(np.linalg.cholesky(corr))
+    except:
+        L = cm.nearestPD_cholesky(corr, corr=True)
+
+    if maintain_sample_unmodified:
+        sample_out = copy.deepcopy(sample)
+    else:
+        sample_out = sample
+
     if mean is None:
         mean = np.array(
             [np.mean(sample[i], axis=0) for i in range(len(sample))],

comet_maths/generate_sample/tests/test_generate_sample.py

@@ -112,6 +112,7 @@ def test_generate_sample_same(self):
         sample = generate_sample_same(100, x0)
         npt.assert_equal(sample.shape, (100,))
         npt.assert_equal(sample[:-1], sample[1:])
+        assert sample.dtype == int
 
         sample = generate_sample_same(100, x1)
         npt.assert_equal(sample.shape, (100, 20))
@@ -121,7 +122,13 @@ def test_generate_sample_same(self):
         npt.assert_equal(sample.shape, (100, 5, 6))
         npt.assert_equal(sample[:-1], sample[1:])
 
+        sample = generate_sample_same(100, "test")
+        npt.assert_equal(sample.shape, (100,))
+        npt.assert_equal(sample[:-1], sample[1:])
+        assert sample.dtype.type is np.str_
+
     def test_generate_sample_systematic(self):
+        np.random.seed(123456)
         sample = generate_sample_systematic(1000, x0, u_x0)
         npt.assert_equal(sample.shape, (1000,))
         npt.assert_allclose(u_x0, np.std(sample, axis=0), rtol=0.1)

comet_maths/interpolation/interpolation.py

@@ -190,7 +190,7 @@ def interpolate_1d(
     return_corr: Optional[bool] = False,
     include_model_uncertainties: Optional[bool] = True,
     add_model_error: Optional[bool] = False,
-    MCsteps: Optional[int] = 100,
+    MCsteps: Optional[int] = 50,
     parallel_cores: Optional[int] = 4,
     interpolate_axis: Optional[int] = 0,
 ) -> Union[
@@ -402,14 +402,26 @@ def _redo_extrapolation(
     :param extrapolate: extrapolation method, which can be set to "extrapolate" (in which case extrapolation is used using interpolation method defined in "method"), "nearest" (in which case nearest values are used for extrapolation), or "linear" (in which case linear extrapolation is used). Defaults to "extrapolate".
     :return: interpolated values with correct extrapolation
     """
-    if extrapolate == "nearest":
-        y[x < x_i[0]] = y_i[0]
-        y[x > x_i[-1]] = y_i[-1]
+    if hasattr(x, "__len__") and len(x) > 1:
+        if extrapolate == "nearest":
+            y[x < x_i[0]] = y_i[0]
+            y[x > x_i[-1]] = y_i[-1]
+
+        elif extrapolate == "linear":
+            f_lin = interp1d(x_i, y_i, kind="linear", fill_value="extrapolate")
+            y[x < x_i[0]] = f_lin(x[x < x_i[0]])
+            y[x > x_i[-1]] = f_lin(x[x > x_i[-1]])
+    else:
+        if extrapolate == "nearest":
+            if x < x_i[0]:
+                y = y_i[0]
+            elif x > x_i[-1]:
+                y = y_i[-1]
 
-    elif extrapolate == "linear":
-        f_lin = interp1d(x_i, y_i, kind="linear", fill_value="extrapolate")
-        y[x < x_i[0]] = f_lin(x[x < x_i[0]])
-        y[x > x_i[-1]] = f_lin(x[x > x_i[-1]])
+        elif extrapolate == "linear":
+            if x < x_i[0] or x > x_i[-1]:
+                f_lin = interp1d(x_i, y_i, kind="linear", fill_value="extrapolate")
+                y = f_lin(x)
 
     return y
 
@@ -628,7 +640,7 @@ def interpolate_1d_along_example(
     include_model_uncertainties: Optional[bool] = True,
     add_model_error: Optional[bool] = False,
     plot_residuals: Optional[bool] = False,
-    MCsteps: Optional[int] = 100,
+    MCsteps: Optional[int] = 50,
     parallel_cores: Optional[int] = 4,
 ) -> Union[
     np.ndarray, Tuple[np.ndarray, np.ndarray], Tuple[np.ndarray, np.ndarray, np.ndarray]

comet_maths/interpolation/tests/test_interpolation.py

@@ -145,6 +145,33 @@ def test_interpolation_1d(self):
         fig2.colorbar(p2)
         fig2.savefig("interpolation_test_1d_corrs.png", bbox_inches="tight")
 
+    def test_interpolation_1d(self):
+        xi = np.arange(0, 3.0, 0.2)
+        yi = function1(xi)
+        u_yi = 0.05 * np.abs(yi)
+        # yi = cm.generate_sample(1, yi, u_yi, corr_x="rand")
+
+        x = np.array([0.33333, 0.666666, 1, 1.33333, 1.66666, 2.00, 2.3333])
+        # t1=time.time()
+        y = cm.interpolate_1d(xi, yi, x, method="cubic")
+        y2 = cm.interpolate_1d(xi, yi, x, method="quadratic")
+
+        y, u_y, corr_y = cm.interpolate_1d(
+            xi,
+            yi,
+            x,
+            u_y_i=u_yi,
+            corr_y_i="syst",
+            method="linear",
+            return_uncertainties=True,
+            return_corr=True,
+            MCsteps=20000,
+            include_model_uncertainties=False,
+        )
+
+        print(u_y / y)
+        print(u_y, u_yi)
+
     def test_interpolation_1d_along_example(self):
         np.random.seed(1234567)
         xi = np.arange(0, 3.0, 0.2)
@@ -296,7 +323,7 @@ def test_interpolation_1d_along_example_unc(self):
 
         # npt.assert_allclose(y_hr_gpr,y_hr_gpr2,atol=0.01)
 
-        mcprop = punpy.MCPropagation(100, parallel_cores=4)
+        mcprop = punpy.MCPropagation(50, parallel_cores=1)
 
         inp2 = cm.Interpolator(
             relative=False,

quality_documentation/QualityDocumentation.tex

@@ -110,13 +110,14 @@ \section{Test report}\label{testreport}
     \clearpage
 }
 
-\part*{User Manual}
-\phantomsection
-\addcontentsline{toc}{part}{User Manual}
-\appendix
-\label{UserManual}
-\def\maketitle{}
-\def\tableofcontents{}
-\input{./latex/user_manual.tex}
+%\part*{User Manual}
+%\usepackage{./latex/sphinxmanual}
+%\phantomsection
+%\addcontentsline{toc}{part}{User Manual}
+%\appendix
+%\label{UserManual}
+%\def\maketitle{}
+%\def\tableofcontents{}
+%\input{./latex/user_manual.tex}
 
 \end{document}

quality_documentation/base/CookiecutterMacros.tex

@@ -4,4 +4,5 @@
 \verbdef\authorname{Pieter De Vis}
 \verbdef\authoremail{[email protected]}
 \newcommand{\packagedescription}{Mathematical algorithms and tools to use within CoMet toolkit.}
-\newcommand{\sil}{sil3}
+\newcommand{\sil}{sil3}
+\newcommand{\sphinxAtStartPar}{\hspace{0}}

quality_documentation/uml/comet_maths.uxf

@@ -0,0 +1,63 @@
+<diagram program="umletino" version="15.1"><zoom_level>10</zoom_level><element><id>UMLPackage</id><coordinates><x>0</x><y>10</y><w>900</w><h>480</h></coordinates><panel_attributes>comet_maths
+--
+bg=orange</panel_attributes><additional_attributes></additional_attributes></element><element><id>UMLPackage</id><coordinates><x>10</x><y>40</y><w>280</w><h>440</h></coordinates><panel_attributes>generate_samples
+--
+bg=blue</panel_attributes><additional_attributes></additional_attributes></element><element><id>UMLPackage</id><coordinates><x>300</x><y>40</y><w>280</w><h>440</h></coordinates><panel_attributes>linear_algebra
+--
+bg=green</panel_attributes><additional_attributes></additional_attributes></element><element><id>UMLPackage</id><coordinates><x>590</x><y>40</y><w>290</w><h>440</h></coordinates><panel_attributes>interpolation
+--
+bg=red</panel_attributes><additional_attributes></additional_attributes></element><element><id>UMLClass</id><coordinates><x>30</x><y>80</y><w>250</w><h>180</h></coordinates><panel_attributes>generate_sample
+--
+generate_sample()
+generate_error_sample()
+generate_sample_shape()
+generate_sample_same()
+generate_sample_systematic()
+generate_sample_random()
+generate_sample_correlated()
+generate_sample_same()
+generate_sample_cov()
+correlate_sample_corr()</panel_attributes><additional_attributes></additional_attributes></element><element><id>UMLClass</id><coordinates><x>30</x><y>270</y><w>250</w><h>180</h></coordinates><panel_attributes>probability_density_function
+--
+generate_sample_pdf()</panel_attributes><additional_attributes></additional_attributes></element><element><id>UMLClass</id><coordinates><x>320</x><y>80</y><w>250</w><h>180</h></coordinates><panel_attributes>matrix_calculation
+--
+calculate_Jacobian()
+calculate_corr()
+nearestPD_cholesky()
+isPD()</panel_attributes><additional_attributes></additional_attributes></element><element><id>UMLClass</id><coordinates><x>320</x><y>270</y><w>250</w><h>180</h></coordinates><panel_attributes>matrix_conversion
+--
+calculate_flattened_corr()
+separate_flattened_corr()
+convert_corr_to_cov()
+convert_cov_to_corr()
+correlation_from_covariance()
+uncertainty_from_covariance()
+change_order_errcorr_dims()
+expand_errcorr_dims()</panel_attributes><additional_attributes></additional_attributes></element><element><id>UMLClass</id><coordinates><x>610</x><y>80</y><w>260</w><h>370</h></coordinates><panel_attributes>interpolation
+--
+interpolate_1d()
+interpolate_1d_along_example()
+gaussian_process_regression()
+gpr_basics()
+default_unc_methods()
+model_error_analytical_methods()
+</panel_attributes><additional_attributes></additional_attributes></element><element><id>UMLClass</id><coordinates><x>620</x><y>220</y><w>230</w><h>210</h></coordinates><panel_attributes>Interpolator
+--
+relative
+method
+method_hr
+add_model_error
+min_scale
+extrapolate
+plot_residuals
+unc_methods
+unc_methods_hr
+--
+interpolate_1d()
+interpolate_1d_along_example()
+</panel_attributes><additional_attributes></additional_attributes></element><element><id>Relation</id><coordinates><x>10</x><y>160</y><w>40</w><h>170</h></coordinates><panel_attributes>lt=&lt;&lt;-
+</panel_attributes><additional_attributes>20;150;10;150;10;10;20;10</additional_attributes></element><element><id>Relation</id><coordinates><x>300</x><y>160</y><w>40</w><h>170</h></coordinates><panel_attributes>lt=&lt;&lt;-
+</panel_attributes><additional_attributes>20;150;10;150;10;10;20;10</additional_attributes></element><element><id>Relation</id><coordinates><x>590</x><y>150</y><w>50</w><h>170</h></coordinates><panel_attributes>lt=&lt;&lt;-
+</panel_attributes><additional_attributes>30;150;10;150;10;10;20;10</additional_attributes></element><element><id>Relation</id><coordinates><x>10</x><y>150</y><w>330</w><h>200</h></coordinates><panel_attributes>lt=&lt;&lt;-
+</panel_attributes><additional_attributes>310;180;10;180;10;10;20;10</additional_attributes></element><element><id>Relation</id><coordinates><x>270</x><y>160</y><w>360</w><h>40</h></coordinates><panel_attributes>lt=&lt;&lt;-
+</panel_attributes><additional_attributes>10;20;340;20</additional_attributes></element></diagram>

setup.py

@@ -26,12 +26,12 @@ def read(filename):
     long_description=read("README.rst"),
     packages=find_packages(exclude=("tests",)),
     install_requires=[
-        "numpy",
-        "scikit-learn",
+        "numpy>=2.2.4",
+        "scikit-learn>=1.6.1",
         "numdifftools",
-        "scipy",
-        "punpy>=1.0.0",
-        "matplotlib",
+        "scipy>=1.15.2",
+        "punpy>=1.0.4",
+        "matplotlib>=3.10.1",
     ],
     extras_require={
         "dev": [

tox.ini

@@ -8,5 +8,4 @@ deps =
     pytest-html
     pytest-cov
 commands =
-    pytest --html=test_report/report.html
-    pytest --cov-report html:test_report/cov_report --cov=comet_maths
+    pytest --html=test_report/report.html --cov-report html:test_report/cov_report --cov=comet_maths