SciPy>=1.9; lazy imports (#202)

emsig · Feb 23, 2024 · 5e2c3c4 · 5e2c3c4
1 parent 0ee2107
commit 5e2c3c4
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Showing 7 changed files with 67 additions and 76 deletions.
diff --git a/.github/workflows/linux.yml b/.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'"
             test: ""
           - python-version: "3.10"
             name: plain

diff --git a/CHANGELOG.rst b/CHANGELOG.rst
@@ -21,7 +21,7 @@ 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.

diff --git a/empymod/kernel.py b/empymod/kernel.py
@@ -30,6 +30,7 @@
 
 
 import numpy as np
+import scipy as sp
 import numba as nb
 
 __all__ = ['wavenumber', 'angle_factor', 'fullspace', 'greenfct',
@@ -946,8 +947,6 @@ def halfspace(off, angle, zsrc, zrec, etaH, etaV, freqtime, ab, signal,
     the input and solution parameters.
 
     """
-    from scipy import special  # Lazy for faster CLI load
-
     xco = np.cos(angle)*off
     yco = np.sin(angle)*off
     res = np.real(1/etaH[0, 0])
@@ -1023,10 +1022,10 @@ def halfspace(off, angle, zsrc, zrec, etaH, etaV, freqtime, ab, signal,
 
     elif abs(signal) == 1:  # Time-domain step response
         # Replace F(m) with F(m-2)
-        f0p = special.erfc(np.sqrt(tp/time))
-        f0m = special.erfc(np.sqrt(tm/time))
-        fs0p = special.erfc(np.sqrt(tsp/time))
-        fs0m = special.erfc(np.sqrt(tsm/time))
+        f0p = sp.special.erfc(np.sqrt(tp/time))
+        f0m = sp.special.erfc(np.sqrt(tm/time))
+        fs0p = sp.special.erfc(np.sqrt(tsp/time))
+        fs0m = sp.special.erfc(np.sqrt(tsm/time))
 
         f1p = np.exp(-tp/time)/np.sqrt(np.pi*time)
         f1m = np.exp(-tm/time)/np.sqrt(np.pi*time)
@@ -1117,15 +1116,15 @@ def halfspace(off, angle, zsrc, zrec, etaH, etaV, freqtime, ab, signal,
         # Bessel functions for airwave
         def BI(gamH, hp, nr, xim):
             r"""Return BI_nr."""
-            return np.exp(-np.real(gamH)*hp)*special.ive(nr, xim)
+            return np.exp(-np.real(gamH)*hp)*sp.special.ive(nr, xim)
 
         def BK(xip, nr):
             r"""Return BK_nr."""
             if np.isrealobj(xip):
                 # To keep it real in Laplace-domain [exp(-1j*0) = 1-0j].
-                return special.kve(nr, xip)
+                return sp.special.kve(nr, xip)
             else:
-                return np.exp(-1j*np.imag(xip))*special.kve(nr, xip)
+                return np.exp(-1j*np.imag(xip))*sp.special.kve(nr, xip)
 
         # Airwave calculation
         def airwave(sval, hp, rp, res, fab, delta):
@@ -1167,9 +1166,9 @@ def airwave(sval, hp, rp, res, fab, delta):
             def coeff_dk(k, K):
                 r"""Return coefficients Dk for k, K."""
                 n = np.arange((k+1)//2, min([k, K/2])+.5, 1)
-                Dk = n**(K/2)*special.factorial(2*n)/special.factorial(n)
-                Dk /= special.factorial(n-1)*special.factorial(k-n)
-                Dk /= special.factorial(2*n-k)*special.factorial(K/2-n)
+                Dk = n**(K/2)*sp.special.factorial(2*n)/sp.special.factorial(n)
+                Dk /= sp.special.factorial(n-1)*sp.special.factorial(k-n)
+                Dk /= sp.special.factorial(2*n-k)*sp.special.factorial(K/2-n)
                 return Dk.sum()*(-1)**(k+K/2)
 
             for k in range(1, K+1):
@@ -1181,9 +1180,9 @@ def coeff_dk(k, K):
             thp = mu_0*hp**2/(4*res)
             trh = mu_0*rh**2/(8*res)
             P1 = (mu_0**2*hp*np.exp(-thp/time))/(res*32*np.pi*time**3)
-            P2 = 2*(delta - (x*y)/rh**2)*special.ive(1, trh/time)
+            P2 = 2*(delta - (x*y)/rh**2)*sp.special.ive(1, trh/time)
             P3 = mu_0/(2*res*time)*(rh**2*delta - x*y)-delta
-            P4 = special.ive(0, trh/time) - special.ive(1, trh/time)
+            P4 = sp.special.ive(0, trh/time) - sp.special.ive(1, trh/time)
 
             air = P1*(P2 - P3*P4)
 

diff --git a/empymod/scripts/fdesign.py b/empymod/scripts/fdesign.py
@@ -232,8 +232,8 @@ def rhs(r):
 
 import os
 import numpy as np
+import scipy as sp
 from copy import deepcopy as dc
-from scipy.constants import mu_0
 
 from empymod.filters import DigitalFilter
 from empymod.model import dipole, dipole_k
@@ -368,8 +368,6 @@ def design(n, spacing, shift, fI, fC=False, r=None, r_def=(1, 1, 2), reim=None,
         `full_output` is True.)
 
     """
-    from scipy.optimize import brute, fmin_powell  # Lazy for faster CLI load
-
     # === 1.  LET'S START ============
     t0 = printstartfinish(verb)
 
@@ -396,7 +394,7 @@ def check_f(f):
 
     # Check default input values
     if finish and not callable(finish):
-        finish = fmin_powell
+        finish = sp.optimize.fmin_powell
     if name is None:
         name = 'dlf_'+str(n)
     if r is None:
@@ -427,9 +425,11 @@ def check_f(f):
         _call_qc_transform_pairs(n, ispacing, ishift, fI, fC, r, r_def, reim)
 
     # === 3. RUN BRUTE FORCE OVER THE GRID ============
-    full = brute(_get_min_val, (ispacing, ishift), full_output=True,
-                 args=(n, fI, fC, r, r_def, error, reim, cvar, verb, plot,
-                       log), finish=finish)
+    full = sp.optimize.brute(
+        _get_min_val, (ispacing, ishift), full_output=True,
+        args=(n, fI, fC, r, r_def, error, reim, cvar, verb, plot, log),
+        finish=finish
+    )
 
     # Add cvar-information to full: 0 for 'amp', 1 for 'r'
     if cvar == 'r':
@@ -927,7 +927,7 @@ def j0_4(f=1, rho=0.3, z=50):
 
     """
 
-    gam = np.sqrt(2j*np.pi*mu_0*f/rho)
+    gam = np.sqrt(2j*np.pi*sp.constants.mu_0*f/rho)
 
     def lhs(x):
         beta = np.sqrt(x**2 + gam**2)
@@ -955,7 +955,7 @@ def j0_5(f=1, rho=0.3, z=50):
 
     """
 
-    gam = np.sqrt(2j*np.pi*mu_0*f/rho)
+    gam = np.sqrt(2j*np.pi*sp.constants.mu_0*f/rho)
 
     def lhs(x):
         beta = np.sqrt(x**2 + gam**2)
@@ -1024,7 +1024,7 @@ def j1_4(f=1, rho=0.3, z=50):
 
     """
 
-    gam = np.sqrt(2j*np.pi*mu_0*f/rho)
+    gam = np.sqrt(2j*np.pi*sp.constants.mu_0*f/rho)
 
     def lhs(x):
         beta = np.sqrt(x**2 + gam**2)
@@ -1052,7 +1052,7 @@ def j1_5(f=1, rho=0.3, z=50):
 
     """
 
-    gam = np.sqrt(2j*np.pi*mu_0*f/rho)
+    gam = np.sqrt(2j*np.pi*sp.constants.mu_0*f/rho)
 
     def lhs(x):
         beta = np.sqrt(x**2 + gam**2)