corrected convolution

Author: mario

code/python/cni_toolbox/HGR.py

@@ -413,4 +413,8 @@ def __convolution__(self, x):
         x = np.vstack((x, np.zeros((np.ceil(self.l_hrf / self.p_sampling).astype(int),
                                     self.n_features))))
         x_conv = ifft(fft(x) * fft(kernel))
+        x_conv = np.abs(
+                    ifft(fft(x, axis=0) *
+                         np.expand_dims(fft(kernel),
+                                        axis=1), axis=0))
         return x_conv[:n_samples]

code/python/cni_toolbox/gadgets.py

@@ -199,10 +199,10 @@ def convolve(self, x):
             convolved sample
         '''
 
-        x_fft = fft(np.vstack((x, np.zeros((self.l_subsampled, self.n_channels)))))
-        self.conv_x = np.vstack((self.conv_x, np.zeros(self.n_channels)))
-        self.conv_x[self.step:self.step + self.l_subsampled, :] += ifft(
-            x_fft * self.kernel_fft)
+        x_fft = fft(np.vstack((x, np.zeros((self.l_subsampled, self.n_channels)))), axis=0)
+        self.conv_x = np.append(self.conv_x, np.zeros(self.n_channels))
+        self.conv_x[self.step:self.step + self.l_subsampled, :] += np.abs(ifft(
+            x_fft * np.expand_dims(self.kernel_fft , axis=1), axis=0))
 
         return self.conv_x[self.step, :]