Fixes

braindecode/torch_ext/modules.py

@@ -92,10 +92,10 @@ class IntermediateOutputWrapper(torch.nn.Module):
         network model
 
     Examples
-    --------        
-    model = Deep4Net()
-    select_modules = ['conv_spat','conv_2','conv_3','conv_4'] # Specify intermediate outputs
-    model_pert = IntermediateOutputWrapper(select_modules,model) # Wrap model
+    --------
+    >>> model = Deep4Net()
+    >>> select_modules = ['conv_spat','conv_2','conv_3','conv_4'] # Specify intermediate outputs
+    >>> model_pert = IntermediateOutputWrapper(select_modules,model) # Wrap model
     """
     def __init__(self, to_select, model):
         if not len(list(model.children()))==len(list(model.named_children())):

braindecode/visualization/perturbation.py

@@ -1,7 +1,6 @@
 import logging
 
 import numpy as np
-from numpy.random import RandomState
 
 from braindecode.datautil.iterators import get_balanced_batches
 from braindecode.util import wrap_reshape_apply_fn, corr
@@ -46,7 +45,7 @@ def phase_perturbation(amps,phases,rng=np.random.RandomState()):
     return amps,phases_pert,pert_vals
 
 def amp_perturbation_additive(amps,phases,rng=np.random.RandomState()):
-    """Takes amps and phases of BxCxF with B input, C channels, F frequencies
+    """Takes amplitudes and phases of BxCxF with B input, C channels, F frequencies
     Adds additive noise N(0,0.02) to amplitudes
 
     Parameters
@@ -74,7 +73,7 @@ def amp_perturbation_additive(amps,phases,rng=np.random.RandomState()):
     return amps_pert,phases,amp_noise
 
 def amp_perturbation_multiplicative(amps,phases,rng=np.random.RandomState()):
-    """Takes amps and phases of BxCxF with B input, C channels, F frequencies
+    """Takes amplitude and phases of BxCxF with B input, C channels, F frequencies
     Adds multiplicative noise N(1,0.02) to amplitudes
 
     Parameters
@@ -156,7 +155,7 @@ def mean_diff_feature_maps(x,y):
 def spectral_perturbation_correlation(pert_fn, diff_fn, pred_fn, n_layers, inputs, n_iterations,
                                                   batch_size=30,
                                                   seed=((2017, 7, 10))):
-    """Calculates phase perturbation correlation for layers in network
+    """Calculates perturbation correlations for layers in network by perturbing either amplitudes or phases
 
     Parameters
     ----------