Merge pull request #589 from mrava87/patch-scipyv14

Patch: scipy v1.11

.github/workflows/build.yaml

@@ -7,7 +7,7 @@ jobs:
     strategy:
       matrix:
         platform: [ ubuntu-latest, macos-13 ]
-        python-version: ["3.8", "3.9", "3.10", "3.11"]
+        python-version: ["3.9", "3.10", "3.11"]
 
     runs-on: ${{ matrix.platform }}
     steps:

azure-pipelines.yml

@@ -26,7 +26,7 @@ jobs:
 #   steps:
 #   - task: UsePythonVersion@0
 #     inputs:
-#       versionSpec: '3.7'
+#       versionSpec: '3.9'
 #       architecture: 'x64'
 #
 #   - script: |
@@ -55,7 +55,7 @@ jobs:
   steps:
   - task: UsePythonVersion@0
     inputs:
-      versionSpec: '3.8'
+      versionSpec: '3.9'
       architecture: 'x64'
 
   - script: |
@@ -84,7 +84,7 @@ jobs:
   steps:
   - task: UsePythonVersion@0
     inputs:
-      versionSpec: '3.8'
+      versionSpec: '3.9'
       architecture: 'x64'
 
   - script: |

docs/source/installation.rst

@@ -9,7 +9,7 @@ The PyLops project strives to create a library that is easy to install in
 any environment and has a very limited number of dependencies.
 Required dependencies are limited to:
 
-* Python 3.8 or greater
+* Python 3.9 or greater
 * `NumPy <http://www.numpy.org>`_
 * `SciPy <http://www.scipy.org/scipylib/index.html>`_
 

environment-dev-arm.yml

@@ -8,7 +8,7 @@ dependencies:
   - python>=3.6.4
   - pip
   - numpy>=1.21.0,<2.0.0
-  - scipy>=1.4.0,<=1.13.0
+  - scipy>=1.11.0
   - pytorch>=1.2.0
   - cpuonly
   - pyfftw

environment-dev.yml

@@ -8,7 +8,7 @@ dependencies:
   - python>=3.6.4
   - pip
   - numpy>=1.21.0,<2.0.0
-  - scipy>=1.4.0,<=1.13.0
+  - scipy>=1.11.0
   - pytorch>=1.2.0
   - cpuonly
   - pyfftw

environment.yml

@@ -4,4 +4,4 @@ channels:
 dependencies:
   - python>=3.6.4
   - numpy>=1.21.0,<2.0.0
-  - scipy>=1.4.0,<=1.13.0
+  - scipy>=1.14.0

pylops/optimization/cls_leastsquares.py

@@ -219,7 +219,7 @@ def run(
             and cupy `data`, respectively)
 
             .. note::
-                When user does not supply ``atol``, it is set to "legacy".
+                When user supplies ``tol`` this is set to ``atol``.
 
         Returns
         -------
@@ -238,8 +238,9 @@ def run(
         if x is not None:
             self.y_normal = self.y_normal - self.Op_normal.matvec(x)
         if engine == "scipy" and self.ncp == np:
-            if "atol" not in kwargs_solver:
-                kwargs_solver["atol"] = "legacy"
+            if "tol" in kwargs_solver:
+                kwargs_solver["atol"] = kwargs_solver["tol"]
+                kwargs_solver.pop("tol")
             xinv, istop = sp_cg(self.Op_normal, self.y_normal, **kwargs_solver)
         elif engine == "pylops" or self.ncp != np:
             if show:

pyproject.toml

@@ -31,7 +31,7 @@ classifiers = [
 ]
 dependencies = [
     "numpy >= 1.21.0 , < 2.0.0",
-    "scipy >= 1.4.0 , <= 1.13.0",
+    "scipy >= 1.11.0",
 ]
 dynamic = ["version"]
 

pytests/test_leastsquares.py

@@ -93,12 +93,12 @@ def test_NormalEquationsInversion(par):
 
     # normal equations with regularization
     xinv = normal_equations_inversion(
-        Gop, y, [Reg], epsI=1e-5, epsRs=[1e-8], x0=x0, **dict(maxiter=200, tol=1e-10)
+        Gop, y, [Reg], epsI=1e-5, epsRs=[1e-8], x0=x0, **dict(maxiter=200, atol=1e-10)
     )[0]
     assert_array_almost_equal(x, xinv, decimal=3)
     # normal equations with weight
     xinv = normal_equations_inversion(
-        Gop, y, None, Weight=Weigth, epsI=1e-5, x0=x0, **dict(maxiter=200, tol=1e-10)
+        Gop, y, None, Weight=Weigth, epsI=1e-5, x0=x0, **dict(maxiter=200, atol=1e-10)
     )[0]
     assert_array_almost_equal(x, xinv, decimal=3)
     # normal equations with weight and small regularization
@@ -110,7 +110,7 @@ def test_NormalEquationsInversion(par):
         epsI=1e-5,
         epsRs=[1e-8],
         x0=x0,
-        **dict(maxiter=200, tol=1e-10)
+        **dict(maxiter=200, atol=1e-10)
     )[0]
     assert_array_almost_equal(x, xinv, decimal=3)
     # normal equations with weight and small normal regularization
@@ -123,7 +123,7 @@ def test_NormalEquationsInversion(par):
         epsI=1e-5,
         epsNRs=[1e-8],
         x0=x0,
-        **dict(maxiter=200, tol=1e-10)
+        **dict(maxiter=200, atol=1e-10)
     )[0]
     assert_array_almost_equal(x, xinv, decimal=3)
 
@@ -192,7 +192,7 @@ def test_WeightedInversion(par):
     y = Gop * x
 
     xne = normal_equations_inversion(
-        Gop, y, None, Weight=Weigth, **dict(maxiter=5, tol=1e-10)
+        Gop, y, None, Weight=Weigth, **dict(maxiter=5, atol=1e-10)
     )[0]
     xreg = regularized_inversion(
         Gop, y, None, Weight=Weigth1, **dict(damp=0, iter_lim=5, show=0)

pytests/test_linearoperator.py

@@ -122,7 +122,7 @@ def test_sparse(par):
     D = np.diag(diag)
     Dop = Diagonal(diag, dtype=par["dtype"])
     S = Dop.tosparse()
-    assert_array_equal(S.A, D)
+    assert_array_equal(S.toarray(), D)
 
 
 @pytest.mark.parametrize("par", [(par1), (par2), (par1j)])

requirements-dev.txt

@@ -1,5 +1,5 @@
 numpy>=1.21.0,<2.0.0
-scipy>=1.4.0,<=1.13.0
+scipy>=1.11.0
 --extra-index-url https://download.pytorch.org/whl/cpu
 torch>=1.2.0
 numba