Merge pull request #49 from epfl-lts2/fix/fix-ci

Fix ci

Author: nperraud

examples/test_deconv_sv_psf.py

@@ -6,34 +6,40 @@
 """
 
 import numpy as np
-import pyunlocbox as plx
 from scipy.signal import fftconvolve
 
+import pyunlocbox as plx
+
 ###############################################################################
 # Sample data
 im = np.random.randn(2748, 3840)
 W = np.random.randn(20, np.prod(im.shape))
 U = np.random.randn(np.prod(im.shape), 20)
 
+
 # Setup Forward and Adjoint Models and Create Solver
 def forward(im):
     im_sim = np.zeros_like(im)
     for i in range(15):
-        weight = W[i,:].reshape(*im.shape)
-        psf_mode = U[:,i].reshape(*im.shape)
-        im_sim += fftconvolve(im* weight, psf_mode, mode='same')
+        weight = W[i, :].reshape(*im.shape)
+        psf_mode = U[:, i].reshape(*im.shape)
+        im_sim += fftconvolve(im * weight, psf_mode, mode="same")
     return im_sim
 
+
 def forward_adj(im):
     im_sim = np.zeros_like(im)
     for i in range(15):
-        weight = W[i,:].reshape(*im.shape)
-        psf_mode = U[:,i].reshape(*im.shape)
-        im_sim += fftconvolve(im, np.flipud(np.fliplr(psf_mode)), mode='same')* weight
+        weight = W[i, :].reshape(*im.shape)
+        psf_mode = U[:, i].reshape(*im.shape)
+        im_sim += fftconvolve(im, np.flipud(np.fliplr(psf_mode)), mode="same") * weight
     return im_sim
 
-tau=10
+
+tau = 10
 f1 = plx.functions.norm_l2(y=im, A=forward, At=forward_adj, lambda_=tau)
 f2 = plx.functions.norm_tv(maxit=50, dim=2)
-solver = plx.solvers.forward_backward(step=0.5/tau, accel=plx.acceleration.fista())
-ret = plx.solvers.solve([f1, f2], x0=im.copy(), solver=solver, maxit=10, verbosity='ALL')
+solver = plx.solvers.forward_backward(step=0.5 / tau, accel=plx.acceleration.fista())
+ret = plx.solvers.solve(
+    [f1, f2], x0=im.copy(), solver=solver, maxit=10, verbosity="ALL"
+)