Merge branch 'master' into feature/covar_cholesky_decomp

.codecov.yml

@@ -1,15 +1,8 @@
-codecov:
-  token: c2f0ce36-17ad-4668-bb1b-f1b72dedf3fc
-  comment:
-    after_n_builds: 9
-
 coverage:
-  precision: 2
-  round: down
-  range: "90...100"
   status:
     project:
       default:
-        target: auto
-        threshold: 2.0%
+        informational: true
+    patch:
+      default:
         informational: true

.github/workflows/python-package.yml

@@ -34,10 +34,11 @@ jobs:
         cd tests
         python -m pytest --cov=uncertainties --cov=. --cov-report=xml --cov-report=term
     - name: Upload coverage reports to Codecov
-      uses: codecov/codecov-action@v4.0.1
+      uses: codecov/codecov-action@v4.6.0
       with:
-        token: ${{ secrets.CODECOV_TOKEN }}
-        slug: lmfit/uncertainties
+        flags: ${{ matrix.os }}-${{ matrix.python-version }}
+      env:
+        CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
   test_without_numpy:
     name: Test without numpy
     runs-on: ubuntu-latest
@@ -46,7 +47,7 @@ jobs:
     - name: Set up Python
       uses: actions/setup-python@v5
       with:
-        python-version: ${{ matrix.python-version }}
+        python-version: 3.12
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
@@ -57,10 +58,11 @@ jobs:
         python -m pytest --ignore=test_unumpy.py --ignore=test_ulinalg.py -k "not test_monte_carlo_comparison"
           --cov=uncertainties --cov=. --cov-report=xml --cov-report=term
     - name: Upload coverage reports to Codecov
-      uses: codecov/codecov-action@v4.0.1
+      uses: codecov/codecov-action@v4.6.0
       with:
-        token: ${{ secrets.CODECOV_TOKEN }}
-        slug: lmfit/uncertainties
+        flags: no-numpy
+      env:
+        CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }}
   results:
     # This step aggregates the results from all the tests and allows us to
     # require only this single job to pass for a PR to be merged rather than

CHANGES.rst

@@ -4,9 +4,21 @@ Change Log
 Unreleased
 ----------
 
+Changes
+
+- Changed how `numpy` is handled as an optional dependency. Previously,
+   importing a `numpy`-dependent function, like `correlated_values`,
+   without `numpy` installed would result in an `ImportError` at import
+   time. Now such a function can be imported but if the user attempts to
+   execute it, a `NotImplementedError` is raised indicating that the
+   function can't be used because `numpy` couldn't be imported.
+
 Fixes:
 
 - fix `readthedocs` configuration so that the build passes (#254)
+- adjust `codecov.io` configuration so that minor code coverage changes will not result
+   in indications that tests are failing. Rather code coverage reports will be purely
+   informational for code reviewers. Also fix other minor configuration issues. (#270)
 
 3.2.2   2024-July-08
 -----------------------

tests/test_uncertainties.py

@@ -2,9 +2,16 @@
 import math
 import random  # noqa
 
+import pytest
+
 import uncertainties.core as uncert_core
 from uncertainties.core import ufloat, AffineScalarFunc, ufloat_fromstr
-from uncertainties import umath
+from uncertainties import (
+    umath,
+    correlated_values,
+    correlated_values_norm,
+    correlation_matrix,
+)
 from helpers import (
     power_special_cases,
     power_all_cases,
@@ -15,6 +22,12 @@
 )
 
 
+try:
+    import numpy as np
+except ImportError:
+    np = None
+
+
 def test_value_construction():
     """
     Tests the various means of constructing a constant number with
@@ -1313,3 +1326,42 @@ def test_correlated_values_correlation_mat():
             numpy.array(cov_mat),
             numpy.array(uncert_core.covariance_matrix([x2, y2, z2])),
         )
+
+
+@pytest.mark.skipif(
+    np is not None,
+    reason="This test is only run when numpy is not installed.",
+)
+def test_no_numpy():
+    nom_values = [1, 2, 3]
+    std_devs = [0.1, 0.2, 0.3]
+    cov = [
+        [1, 0, 0],
+        [0, 1, 0],
+        [0, 0, 1],
+    ]
+
+    with pytest.raises(
+        NotImplementedError,
+        match="not able to import numpy",
+    ):
+        _ = correlated_values(nom_values, cov)
+
+    with pytest.raises(
+        NotImplementedError,
+        match="not able to import numpy",
+    ):
+        _ = correlated_values_norm(
+            list(zip(nom_values, std_devs)),
+            cov,
+        )
+
+    x = ufloat(1, 0.1)
+    y = ufloat(2, 0.2)
+    z = ufloat(3, 0.3)
+
+    with pytest.raises(
+        NotImplementedError,
+        match="not able to import numpy",
+    ):
+        _ = correlation_matrix([x, y, z])