Use PyWavelets for continuous wavelet transform

scipy 1.15.0 has been released, and with it, signal.cwt has been
removed[1]. The suggested recommendation is to use PyWavelets.

1: https://docs.scipy.org/doc/scipy-1.12.0/reference/generated/scipy.signal.cwt.html

requirements.txt

@@ -2,3 +2,4 @@ pillow
 numpy
 scipy
 argparse
+PyWavelets

setup.py

@@ -12,7 +12,7 @@
     author_email='[email protected]',
     platforms=['any'],
     license='MIT License',
-    install_requires=['numpy', 'pillow', 'scipy'],
+    install_requires=['numpy', 'pillow', 'scipy', 'PyWavelets'],
     url='https://github.com/jterrace/pyssim',
     entry_points={
         'console_scripts': [

ssim/ssimlib.py

@@ -7,7 +7,7 @@
 import sys
 
 import numpy as np
-from scipy import signal
+import pywt
 
 from ssim import compat
 from ssim.compat import Image, ImageOps
@@ -168,8 +168,8 @@ def cw_ssim_value(self, target, width=30):
         sig2 = np.asarray(target.img_gray.getdata())
 
         # Convolution
-        cwtmatr1 = signal.cwt(sig1, signal.ricker, widths)
-        cwtmatr2 = signal.cwt(sig2, signal.ricker, widths)
+        cwtmatr1, freqs1 = pywt.cwt(sig1, widths, 'mexh')
+        cwtmatr2, freqs2 = pywt.cwt(sig2, widths, 'mexh')
 
         # Compute the first term
         c1c2 = np.multiply(abs(cwtmatr1), abs(cwtmatr2))