Merge pull request #245 from AaronDJohnson/update_ci

Update CI

.github/workflows/ci_test.yml

@@ -16,8 +16,8 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        os: [ubuntu-latest, macos-latest]
-        python-version: [3.7, 3.8, 3.9, '3.10']
+        os: [ubuntu-latest, macos-13]
+        python-version: ['3.9', '3.10', '3.11', '3.12']
 
     steps:
     - name: Checkout repository
@@ -53,6 +53,7 @@ jobs:
     - name: Test with pytest
       run: make test
     - name: Codecov
+      if: runner.os != 'macOS'
       uses: codecov/codecov-action@v3
       #with:
       #  fail_ci_if_error: true

enterprise_extensions/empirical_distr.py

@@ -10,7 +10,7 @@
     sklearn_available=True
 except ModuleNotFoundError:
     sklearn_available=False
-from scipy.interpolate import interp1d, interp2d
+from scipy.interpolate import interp1d, RegularGridInterpolator
 
 logger = logging.getLogger(__name__)
 
@@ -173,9 +173,9 @@ def __init__(self, param_names, samples, minvals=None, maxvals=None, bandwidth=0
         xvals = np.linspace(minvals[0], maxvals[0], num=nbins)
         yvals = np.linspace(minvals[1], maxvals[1], num=nbins)
         self._Nbins = [yvals.size for ii in range(xvals.size)]
-        scores = np.array([self.kde.score(np.array([xvals[ii], yvals[jj]]).reshape((1, 2))) for ii in range(xvals.size) for jj in range(yvals.size)])
+        scores = np.array([self.kde.score(np.array([xvals[ii], yvals[jj]]).reshape((1, 2))) for ii in range(xvals.size) for jj in range(yvals.size)]).reshape(len(xvals), len(yvals))
         # interpolate within prior
-        self._logpdf = interp2d(xvals, yvals, scores, kind='linear', fill_value=-1000)
+        self._logpdf = RegularGridInterpolator((xvals, yvals), scores, method='linear', bounds_error=False, fill_value=-1000)
 
     def draw(self):
         params = self.kde.sample(1).T