Trying to pull part 2

pipeline.py

@@ -98,7 +98,6 @@ def sha(s):
             open(pickle_name, 'wb'),
             protocol=cPickle.HIGHEST_PROTOCOL)
 
-<<<<<<< HEAD
     # -- plot distributions:
     '''
     This should produce normed, weighted histograms of the input distributions for all variables
@@ -126,7 +125,6 @@ def sha(s):
         [5, 5, 3, 3, 2, 2]
     )
 
-||||||| merged common ancestors
     # -- plot distributions:
     '''
     This should produce normed, weighted histograms of the input distributions for all variables
@@ -157,7 +155,6 @@ def sha(s):
     print  X_jets_train.shape, X_photons_train.shape
 
 =======
->>>>>>> 1a214b6daea28f00860eb31110c2790fe6417efb
     # # -- train
     # # design a Keras NN with three RNN streams (jets, photons, muons)
     io.save(('X_jets_NN.h5'), NN(X_jets_train, X_jets_test, y_train))

plotting.py

@@ -95,7 +95,6 @@ def plot_inputs(data, particle_names):
 		sets of each class for each feature 
 	'''
 
-<<<<<<< HEAD
 	_plot_X(X_jets_train, X_jets_test, y_train, y_test, w_train, w_test, varlist, 'Jet')
 	_plot_X(X_photons_train, X_photons_test, y_train, y_test, w_train, w_test, varlist, 'Photon')
 	_plot_X(X_muons_train, X_muons_test, y_train, y_test, w_train, w_test, varlist, 'Muon')
@@ -120,11 +119,10 @@ def plot_NN(yhat, y_test, w_test):
 			plt.legend()
 			plt.show()
 
-||||||| merged common ancestors
 	_plot_X(X_jets_train, X_jets_test, y_train, y_test, w_train, w_test, varlist, 'Jet')
 	_plot_X(X_photons_train, X_photons_test, y_train, y_test, w_train, w_test, varlist, 'Photon')
 	_plot_X(X_muons_train, X_muons_test, y_train, y_test, w_train, w_test, varlist, 'Muon')
-=======
+
 	for particle in particle_names:
 		_plot_X(
 			data['X_' + particle + '_train'], 
@@ -137,4 +135,3 @@ def plot_NN(yhat, y_test, w_test):
 			data['LabelEncoder'],
 			particle
 			)
->>>>>>> 1a214b6daea28f00860eb31110c2790fe6417efb