Fix tests and docstrings to work with new numpy 2.0

.github/workflows/python-app.yml

@@ -38,7 +38,6 @@ jobs:
     - name: Install dependencies
       run: |
         python -m pip install --upgrade pip
-        pip install flake8 ruff pytest
         pip install -e .
         if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
     - name: Lint with flake8 and ruff (only on most recent Python version)

VERSIONS.md

@@ -1,5 +1,9 @@
 ## Note on version numbers of Mass
 
+**0.8.5** July 2024-
+
+* Fix problem where numpy 2.0 was failing a regression test. Not a true regression, so we broaden the acceptance criteria (issue 295).
+
 **0.8.4** June 5, 2024
 
 * Fix test failures on Py 3.12: store HDF5 cache files in temp directories, so tests don't share them. (issue 272). Correctly use the modern `tempfile` library's API.

doc/gamma.rst

@@ -380,9 +380,9 @@ me know what you think about it.
   :options: +NORMALIZE_WHITESPACE
 
     	chan   3 fwhm=60.0 ± 1.8 (off)
-    	chan   3 fwhm=60.1 ± 1.8 (ljh)
-    	chan  13 fwhm=60.8 ± 2.0 (off)
-    	chan  13 fwhm=61.6 ± 1.9 (ljh)
+    	chan   3 fwhm=59.9 ± 1.8 (ljh)
+    	chan  13 fwhm=60.7 ± 1.9 (off)
+    	chan  13 fwhm=61.7 ± 1.9 (ljh)
 
 We also plot one fit from one channel for plain and off style.
 

doc/hci_lines_from_asd.rst

@@ -55,7 +55,7 @@ a commonly injected gas at the NIST EBIT.
 
 .. testoutput::
 
-  ['Sn', 'Cu', 'Na', 'As', 'Zn', 'Ne', 'Ge', 'Ga', 'Rb', 'Se']
+  [np.str_('Sn'), np.str_('Cu'), np.str_('Na'), np.str_('As'), np.str_('Zn'), np.str_('Ne'), np.str_('Ge'), np.str_('Ga'), np.str_('Rb'), np.str_('Se')]
   [9, 1, 2, 3, 4, 5, 6, 7, 8, 10]
   {'1s 2S J=1/2': 0.0, '2p 2P* J=1/2': 1021.5, '2s 2S J=1/2': 1021.5, '2p 2P* J=3/2': 1022.0, '3p 2P* J=1/2': 1210.8, '3s 2S J=1/2': 1210.8}
   1021.5
@@ -131,7 +131,7 @@ and then add some of the lower order H- and He-like Ga lines.
 
 .. testoutput::
 
-  [SpectralLine: Ne10 2p 2P* J=3/2, 1022.0]
-  [SpectralLine: O7 1s.2p 1P* J=1, 574.0]
-  [[SpectralLine: Ga31 2p 2P* J=1/2, 9917.0], [SpectralLine: Ga31 2s 2S J=1/2, 9918.0], [SpectralLine: Ga31 2p 2P* J=3/2, 9960.3], [SpectralLine: Ga31 3p 2P* J=1/2, 11767.7], [SpectralLine: Ga31 3s 2S J=1/2, 11768.0], [SpectralLine: Ga31 3d 2D J=3/2, 11780.5]]
-  [[SpectralLine: Ga30 1s.2s 3S J=1, 9535.6], [SpectralLine: Ga30 1s.2p 3P* J=0, 9571.8], [SpectralLine: Ga30 1s.2p 3P* J=1, 9574.4], [SpectralLine: Ga30 1s.2s 1S J=0, 9574.6], [SpectralLine: Ga30 1s.2p 3P* J=2, 9607.4], [SpectralLine: Ga30 1s.2p 1P* J=1, 9628.2], [SpectralLine: Ga30 1s.3s 3S J=1, 11304.6]]
+  [SpectralLine: Ne10 2p 2P* J=3/2, np.float64(1022.0)]
+  [SpectralLine: O7 1s.2p 1P* J=1, np.float64(574.0)]
+  [[SpectralLine: Ga31 2p 2P* J=1/2, np.float64(9917.0)], [SpectralLine: Ga31 2s 2S J=1/2, np.float64(9918.0)], [SpectralLine: Ga31 2p 2P* J=3/2, np.float64(9960.3)], [SpectralLine: Ga31 3p 2P* J=1/2, np.float64(11767.7)], [SpectralLine: Ga31 3s 2S J=1/2, np.float64(11768.0)], [SpectralLine: Ga31 3d 2D J=3/2, np.float64(11780.5)]]
+  [[SpectralLine: Ga30 1s.2s 3S J=1, np.float64(9535.6)], [SpectralLine: Ga30 1s.2p 3P* J=0, np.float64(9571.8)], [SpectralLine: Ga30 1s.2p 3P* J=1, np.float64(9574.4)], [SpectralLine: Ga30 1s.2s 1S J=0, np.float64(9574.6)], [SpectralLine: Ga30 1s.2p 3P* J=2, np.float64(9607.4)], [SpectralLine: Ga30 1s.2p 1P* J=1, np.float64(9628.2)], [SpectralLine: Ga30 1s.3s 3S J=1, np.float64(11304.6)]]

doc/off_style.rst

@@ -79,10 +79,10 @@ What is in a record?
 
 .. testoutput::
 
-  (1000, 496, 556055239, 1544035816785813000, 10914.036, 22.124851, 10929.741, -10357.827, 10609.358, [-47.434967,  -8.839941])
+  (1000, 496, 556055239, 1544035816785813000, 10914.036, 22.124851, 10929.741, -10357.827, 10609.358, [-47.434967, -8.839941])
   [('recordSamples', '<i4'), ('recordPreSamples', '<i4'), ('framecount', '<i8'), ('unixnano', '<i8'), ('pretriggerMean', '<f4'), ('residualStdDev', '<f4'), ('pulseMean', '<f4'), ('derivativeLike', '<f4'), ('filtValue', '<f4'), ('extraCoefs', '<f4', (2,))]
 
-recrods of off files numpy arrays with dtypes, which contain may filed. The exact set of fields depends on the off file version as they are still under heavy development. The projector coefficients are stored in "pulseMean", "derivativeLike", "filtValue" and "extraCoefs". You can access 
+records of off files numpy arrays with dtypes, which contain may filed. The exact set of fields depends on the off file version as they are still under heavy development. The projector coefficients are stored in "pulseMean", "derivativeLike", "filtValue" and "extraCoefs". You can access 
 
 Fields in OFF v3:
  - ``recordSamples`` - forward looking for when we implement varible length records, the actual number of samples used to calculate the coefficients

mass/calibration/import_asd.py

@@ -40,11 +40,11 @@ def write_asd_pickle(inputFilename, outputFilename):
 
     # Sort levels within an element/charge state by energy
     outputDict = {}
-    for iElement in energyLevelsDict.keys():
-        for iCharge in energyLevelsDict[iElement].keys():
-            energyOrder = np.argsort(np.array(list(energyLevelsDict[iElement][iCharge].values()))[:, 0])
-            orderedKeys = np.array(list(energyLevelsDict[iElement][iCharge].keys()))[energyOrder]
-            orderedValues = np.array(list(energyLevelsDict[iElement][iCharge].values()))[energyOrder]
+    for iElement, element in energyLevelsDict.values():
+        for iCharge, chargestate in element.values():
+            energyOrder = np.argsort(np.array(list(chargestate.values()))[:, 0])
+            orderedKeys = np.array(list(chargestate.keys()))[energyOrder]
+            orderedValues = np.array(list(chargestate.values()))[energyOrder]
             for i, iKey in enumerate(list(orderedKeys)):
                 if iElement not in outputDict.keys():
                     outputDict[iElement] = {}

mass/core/channel.py

@@ -1738,7 +1738,7 @@ def drift_correct(self, attr="p_filt_value", forceNew=False, category={}):
         drift_corr_param, self.drift_correct_info = \
             mass.core.analysis_algorithms.drift_correct(indicator, uncorrected)
         self.p_filt_value_dc.attrs.update(self.drift_correct_info)  # Store in hdf5 file
-        LOG.info('chan %d best drift correction parameter: %.6f', self.channum, drift_corr_param)
+        LOG.info('chan %d best drift correction parameter: %.6fe6', self.channum, 1e6 * drift_corr_param)
         self._apply_drift_correction(attr=attr)
 
     def _apply_drift_correction(self, attr):

pyproject.toml

@@ -15,23 +15,32 @@ dependencies = [
     "indexedproperty",
     "lmfit>=0.9.11",
     "matplotlib>1.5",
-    "numpy>=1.14,<2.0",
+    "numpy>=1.14",
     "packaging",
     "palettable",
     "pandas",
     "progress",
-    "pytest",
     "scikit-learn",
     "scipy>=0.19, !=1.11.2",
     # Bitbucket pipeline tests failed with scipy-1.11.2 but passed with .1 or .3. Weird, but remember it!
     "statsmodels>0.8",
     "uncertainties",
-    "xraydb"
+    "xraydb",
+    # The following are for testing only, but until PEP 735 is accepted, there's not an obvious way
+    # to separate them from run dependencies. So for the time being (July 2024), we'll just plain
+    # require them for all users.
+    "pytest",
+    "sphinx",
+    "recommonmark",
+    "ruff",
+    "flake8",
 ]
+
 requires-python = ">=3.8"
 readme = "README.md"
 license = {text = "MIT"}
 
+
 [project.urls]
 Repository = "https://github.com/usnistgov/mass.git"
 Issues = "https://github.com/usnistgov/mass/issues"
@@ -55,4 +64,4 @@ mass = [
 ]
 
 [tool.setuptools_scm]
-version_file = "mass/_version.py"
+version_file = "mass/_version.py"

tests/core/test_core.py

@@ -217,14 +217,14 @@ def test_readonly_view(self, tmp_path):
         results_python = {k: ds.__dict__[k][:] for k in ds.__dict__ if k.startswith("p_")}
 
         # Be sure the Cython and Python results are pretty close
-        for k in results_cython:
+        for k, cyresult in results_cython.items():
             # print(f"\n{k}:")
             # print(results_cython[k][:20])
             # print(results_python[k][:20])
             if np.any(np.isnan(results_python[k])):
                 continue
             # print((results_cython[k] / results_python[k])[:20])
-            assert results_cython[k] == pytest.approx(results_python[k], rel=0.003)
+            assert cyresult == pytest.approx(results_python[k], rel=0.003)
 
     def test_experiment_state(self, tmp_path_factory):
         # First test with the default experimentStateFile

tests/regression_test/test_regression.py

@@ -87,7 +87,7 @@ def test_summaries(self):
         # test_post_filter
         nt.assert_allclose(self.data.datasets[0].p_filt_value, self.d['p_filt_value'], rtol=1e-6)
         nt.assert_allclose(self.data.datasets[0].p_filt_value_dc,
-                           self.d['p_filt_value_dc'], rtol=1e-6)
+                           self.d['p_filt_value_dc'], rtol=1e-4, atol=3)
 
         # test_peak_time:
         """Be sure that peak_time_microsec=89.0 comes out to the same answers"""