SciPy>=1.9; lazy imports (#319)

.github/workflows/linux.yml

@@ -34,7 +34,7 @@ jobs:
           - python-version: "3.9"
             name: minimal
             os: ubuntu
-            conda: "'scipy=1.8' 'numba=0.53'"
+            conda: "'scipy=1.9' 'numba=0.53'"
           - python-version: "3.10"
             name: full
             os: ubuntu

CHANGELOG.rst

@@ -14,7 +14,7 @@ latest
   - Bumped the minimum requirements to:
 
     - Python 3.9
-    - SciPy 1.8
+    - SciPy 1.9
     - Numba 0.53
 
   - Testing: added Python 3.12, dropped Python 3.8.

emg3d/electrodes.py

@@ -20,7 +20,7 @@
 from copy import deepcopy
 
 import numpy as np
-from scipy.special import sindg, cosdg
+import scipy as sp
 
 from emg3d import fields, utils
 
@@ -847,7 +847,7 @@ def rotation(azimuth, elevation, deg=True):
 
     """
     if deg:
-        cos, sin = cosdg, sindg
+        cos, sin = sp.special.cosdg, sp.special.sindg
     else:
         cos, sin = np.cos, np.sin
 

emg3d/fields.py

@@ -24,7 +24,7 @@
 
 import numba as nb
 import numpy as np
-from scipy.constants import mu_0
+import scipy as sp
 
 from emg3d.core import _numba_setting
 from emg3d import maps, meshes, models, utils, electrodes
@@ -271,7 +271,7 @@ def smu0(self):
         """s*mu_0; mu_0 = magn permeability of free space [H/m]."""
         if getattr(self, '_smu0', None) is None:
             if self.sval is not None:
-                self._smu0 = self.sval*mu_0
+                self._smu0 = self.sval*sp.constants.mu_0
             else:
                 self._smu0 = None
 

emg3d/maps.py

@@ -23,8 +23,7 @@
 
 import numba as nb
 import numpy as np
-from scipy.ndimage import map_coordinates
-from scipy.interpolate import RegularGridInterpolator, interpnd, interp1d
+import scipy as sp
 
 from emg3d.utils import _requires
 from emg3d.core import _numba_setting
@@ -352,9 +351,9 @@ def interpolate(grid, values, xi, method='linear', extrapolate=True,
             **({} if kwargs is None else kwargs),
         }
 
-        values_x = RegularGridInterpolator(
-                points=points, values=values, method=method,
-                **opts)(xi=new_points)
+        values_x = sp.interpolate.RegularGridInterpolator(
+            points=points, values=values, method=method, **opts
+        )(xi=new_points)
 
     # Return to linear if log10 was applied.
     if log:
@@ -480,7 +479,7 @@ def _points_from_grids(grid, values, xi, method):
         else:
             # Replicate the same expansion of xi as used in
             # RegularGridInterpolator, so the input xi can be quite flexible.
-            new_points = interpnd._ndim_coords_from_arrays(
+            new_points = sp.interpolate.interpnd._ndim_coords_from_arrays(
                     xi, ndim=3)
             shape = new_points.shape[:-1]
             new_points = new_points.reshape(-1, 3, order='F')
@@ -541,16 +540,17 @@ def interp_spline_3d(points, values, xi, **kwargs):
     # coordinates to this artificial coordinate system too.
     coords = np.empty(xi.T.shape)
     for i in range(3):
-        coords[i] = interp1d(points[i], np.arange(len(points[i])),
-                             kind='cubic', bounds_error=False,
-                             fill_value='extrapolate')(xi[:, i])
+        coords[i] = sp.interpolate.interp1d(
+            points[i], np.arange(len(points[i])), kind='cubic',
+            bounds_error=False, fill_value='extrapolate'
+        )(xi[:, i])
 
     # `map_coordinates` only works for real data; split it up if complex.
     # Note: SciPy 1.6 (12/2020) introduced complex-valued
     #       ndimage.map_coordinates; replace eventually.
-    values_x = map_coordinates(values.real, coords, **kwargs)
+    values_x = sp.ndimage.map_coordinates(values.real, coords, **kwargs)
     if 'complex' in values.dtype.name:
-        imag = map_coordinates(values.imag, coords, **kwargs)
+        imag = sp.ndimage.map_coordinates(values.imag, coords, **kwargs)
         values_x = values_x + 1j*imag
 
     return values_x

emg3d/meshes.py

@@ -21,8 +21,7 @@
 from copy import deepcopy
 
 import numpy as np
-from scipy.constants import mu_0
-from scipy.optimize import brentq
+import scipy as sp
 
 from emg3d import maps, utils
 
@@ -1051,7 +1050,7 @@ def f(alpha):
                 return np.sum(tdmin*alpha**np.arange(1, n+1)) - delta
 
             # Required stretching to fit n cells exactly into delta.
-            alph = brentq(f, 0.5, 10.0)
+            alph = sp.optimize.brentq(f, 0.5, 10.0)
 
             # If stretching is within tolerance, finish.
             if alph < min(alphmax, stretching[1]):
@@ -1178,7 +1177,8 @@ def skin_depth(frequency, conductivity, mu_r=1.0):
         Skin depth (m).
 
     """
-    skindepth = 1/np.sqrt(np.pi*abs(frequency)*conductivity*mu_r*mu_0)
+    mu = mu_r*sp.constants.mu_0
+    skindepth = 1/np.sqrt(np.pi*abs(frequency)*conductivity*mu)
 
     # For Laplace-domain computations.
     if frequency < 0:

emg3d/models.py

@@ -20,7 +20,7 @@
 from copy import deepcopy
 
 import numpy as np
-from scipy.constants import epsilon_0
+import scipy as sp
 
 from emg3d import maps, meshes, utils
 
@@ -679,8 +679,8 @@ def __init__(self, model, sfield):
 
                 # Complete version.
                 else:
-                    eta = -sfield.smu0*vol*(
-                            cond + sfield.sval*epsilon_0*model.epsilon_r)
+                    smu = sfield.sval*sp.constants.epsilon_0*model.epsilon_r
+                    eta = -sfield.smu0*vol*(cond + smu)
 
             setattr(self, '_eta_' + name[-1], eta)
 

emg3d/time.py

@@ -20,8 +20,7 @@
 import warnings
 
 import numpy as np
-from scipy.interpolate import PchipInterpolator as Pchip
-from scipy.interpolate import InterpolatedUnivariateSpline as Spline
+import scipy as sp
 
 try:
     import empymod
@@ -339,6 +338,7 @@ def interpolate(self, fdata):
         # interpolate from fmin to fmax.
         if self.freq_coarse.size != self.freq_required.size:
 
+            Spline = sp.interpolate.InterpolatedUnivariateSpline
             int_real = Spline(np.log(self.freq_compute),
                               fdata.real)(np.log(self.freq_interpolate))
             int_imag = Spline(np.log(self.freq_compute),
@@ -359,6 +359,7 @@ def interpolate(self, fdata):
         data_ext = np.r_[fdata[0].real-1e-100j, fdata]
 
         # 2.b Actual 'extrapolation' (now an interpolation).
+        Pchip = sp.interpolate.PchipInterpolator
         ext_real = Pchip(freq_ext, data_ext.real)(self.freq_extrapolate)
         ext_imag = Pchip(freq_ext, data_ext.imag)(self.freq_extrapolate)
 

setup.py

@@ -28,7 +28,7 @@
     },
     python_requires=">=3.9",
     install_requires=[
-        "scipy>=1.8",
+        "scipy>=1.9",
         "numba>=0.53",
     ],
     extras_require={

tests/test_models.py

@@ -1,5 +1,6 @@
 import pytest
 import numpy as np
+import scipy as sp
 from numpy.testing import assert_allclose
 
 import emg3d
@@ -107,7 +108,7 @@ def test_regression(self, capsys):
         assert_allclose(tres*4., model3.property_z)
 
         # Check eta
-        iomep = sfield.sval*models.epsilon_0
+        iomep = sfield.sval*sp.constants.epsilon_0
         eta_x = -sfield.smu0*(1./model3.property_x - iomep)*gridvol
         eta_y = -sfield.smu0*(1./model3.property_y - iomep)*gridvol
         eta_z = -sfield.smu0*(1./model3.property_z - iomep)*gridvol