Merge pull request #641 from CUQI-DTU/remove_scipy_version

Update scipy version requirement and related issues

Author: chaozg

cuqi/distribution/_truncated_normal.py

@@ -107,7 +107,7 @@ def _gradient(self, x, *args, **kwargs):
         """
         # check if x falls in the range between np.array a and b
         if np.any(x < self.low) or np.any(x > self.high):
-            return np.NaN*np.ones_like(x)
+            return np.nan*np.ones_like(x)
         else:
             return self._normal.gradient(x, *args, **kwargs)
 

cuqi/distribution/_uniform.py

@@ -47,7 +47,7 @@ def gradient(self, x):
         Computes the gradient of logpdf at the given values of x.
         """
         if np.any(x < self.low) or np.any(x > self.high):
-            return np.NaN*np.ones_like(x)
+            return np.nan*np.ones_like(x)
         else:
             return np.zeros_like(x)
 

cuqi/implicitprior/_regularizedGaussian.py

@@ -189,12 +189,18 @@ def _parse_preset_constraint_input(self, constraint, optional_regularization_par
             elif c_lower == "increasing":
                 if not isinstance(self.geometry, Continuous1D):
                     raise ValueError("Geometry not supported for " + c_lower)
-                self._constraint_prox = lambda z, _: spoptimize.isotonic_regression(z, increasing=True).x
+                if hasattr(spoptimize, 'isotonic_regression'):
+                    self._constraint_prox = lambda z, _: spoptimize.isotonic_regression(z, increasing=True).x
+                else:
+                    raise AttributeError(f"The function 'isotonic_regression' does not exist in scipy.optimize. Installed scipy version: {spoptimize.__version__}. You need to install a scipy >= 1.12.0")
                 self._preset["constraint"] = "increasing"
             elif c_lower == "decreasing":
                 if not isinstance(self.geometry, Continuous1D):
                     raise ValueError("Geometry not supported for " + c_lower)
-                self._constraint_prox = lambda z, _: spoptimize.isotonic_regression(z, increasing=False).x
+                if hasattr(spoptimize, 'isotonic_regression'):
+                    self._constraint_prox = lambda z, _: spoptimize.isotonic_regression(z, increasing=False).x
+                else:
+                    raise AttributeError(f"The function 'isotonic_regression' does not exist in scipy.optimize. Installed scipy version: {spoptimize.__version__}. You need to install a scipy >= 1.12.0")
                 self._preset["constraint"] = "decreasing"
             elif c_lower == "convex":
                 if not isinstance(self.geometry, Continuous1D):

cuqi/utilities/_utilities.py

@@ -188,7 +188,7 @@ def approx_derivative(func, wrt, direction=None, epsilon=np.sqrt(np.finfo(float)
     # We compute the Jacobian matrix of func using forward differences.
     # If the function is scalar-valued, we compute the gradient instead.
     # If the direction is provided, we compute the direction-Jacobian product.
-    wrt = np.asfarray(wrt)
+    wrt = np.asarray(wrt)
     f0 = func(wrt)
     Matr = np.zeros([infer_len(wrt), infer_len(f0)])
     dx = np.zeros(len(wrt))

requirements.txt

@@ -1,5 +1,6 @@
 matplotlib
 numpy>=1.17.0
-scipy<1.13
+scipy==1.12.0; python_version <= '3.9'
+scipy; python_version > '3.9'
 arviz
 tqdm

tests/test_bayesian_inversion.py

@@ -2,7 +2,9 @@
 
 import pytest
 import numpy as np
+import scipy
 import sys
+from packaging import version
 
 from cuqi.testproblem import Deconvolution1D
 from cuqi.distribution import Gaussian, GMRF, CMRF, LMRF, Gamma
@@ -25,6 +27,14 @@ def test_TP_BayesianProblem_sample(copy_reference, TP_type, phantom, prior, Ns,
     # SKIP NUTS test if not windows (for now)
     if isinstance(prior, CMRF) and not sys.platform.startswith('win'):
         pytest.skip("NUTS(CMRF) regression test is not implemented for this platform")
+    elif (
+        isinstance(prior, RegularizedGaussian) 
+        or isinstance(prior, RegularizedGMRF)
+    ) and version.parse(scipy.__version__) >= version.parse('1.13.0'):
+        pytest.skip(
+            "Saved reference data is not consistent with scipy>=1.13.0 "
+            "(due to different default behaviour of scipy.optimize)"
+        )
 
     np.random.seed(19937)
 

tests/test_implicit_priors.py

@@ -1,6 +1,8 @@
 import cuqi
 import numpy as np
+import scipy
 import pytest
+from packaging import version
 
 def test_RegularizedGaussian_default_init():
     """ Test that the implicit regularized Gaussian requires at least 1 regularization argument """
@@ -186,6 +188,7 @@ def test_RegularizedGaussian_double_preset():
     assert len(x.proximal[0]) == 2
     assert len(x.proximal[1]) == 2
 
+@pytest.mark.skipif(version.parse(scipy.__version__) < version.parse('1.12.0'), reason="isotonic_regression in not available in scipy < 1.12.0")
 def test_regression_increasing():
     """ Regression test for the increasing constraints in RegularizedGaussian"""
 

tests/test_model.py

@@ -19,7 +19,7 @@ def test_LinearModel_getMatrix(seed):
     mat1 = model1.get_matrix() #Normal matrix
     mat2 = model2.get_matrix() #Sparse matrix (generated from functions)
 
-    assert np.allclose(mat1,mat2.A)
+    assert np.allclose(mat1,mat2.toarray())
 
 def test_initialize_model_dim():
     model1 = cuqi.model.Model(lambda x:x, range_geometry=4, domain_geometry=4)