Lots of changes.

-Added S-parameter: controls slope of the sigmoid function.
-Changed function to prepare learning data from file
(complex_data_preparation()).
-Added if-else condition in learning fiuctions to corrected error with
one-layer 1-st subnetwork.
-Added function check_result(). Directly shows the results of learning.
NN_learning now uses as module to store complex functions:
-SNN(): whole neural network. All the basic functions wrapped into the
one big function.
- Structure_Analysis(): analyse network efficiency with respect to its
structure.
- Load_SA_results(): load result of structure analysis from CSV.
- disp_learning_dynamic(), disp_struct_analysis(): functions of
visualization.
- hidden_activation(): returns activations of every unit in the network.
- PCA() - principal component analysis.
The main body of the program now in the separate module NN_analysis.py