array_train_X_ss.append(np.array(X_train_ss))
array_test_X_ss.append(np.array(X_test_ss))
array_train_y_ss.append(np.array(y_train_ss))
array_test_y_ss.append(np.array(y_test_ss))
# # DESIGN P with dense
# ### StandarScaler normalization - Fully connected - 100 dense
print('Metabolic and signaling with StandardScaler normalization - ' +
str(df_weight_both.shape[0]) + ' gene - dense100')
ss_dense_model, _ = tfm_NN.TFM_NNExperiment(
X_train_=array_train_X_ss,
y_train_=array_train_y_ss,
X_test_=array_test_X_ss,
y_test_=array_test_y_ss,
df_w_=pd.DataFrame(),
bio_='dense_',
design_name_='metsig_SScaler_1_layer_100',
pathway_layer_=False,
second_layer_=False,
epochs_=epochs_default,
batch_size_=batch_size_default,
unit_size_=100).build()
# # DESIGN A with 1-LAYER and 2-LAYER
unit_size = len(df_weight_metabolic_signaling.columns)
# ## with 1-LAYER
# ### StandardScaler normalization - Pathways connection - 250 nodes
print('Metabolic and signaling with StandardScaler normalization - ' +
str(df_weight_both.shape[0]) + ' gene - pathways' + str(unit_size))
ss_a1_model, _ = tfm_NN.TFM_NNExperiment(
array_test_X_ss.append(np.array(X_test_ss))
array_train_y_ss.append(np.array(y_train_ss))
array_test_y_ss.append(np.array(y_test_ss))
# # DESIGN P1 with 1-LAYER
# ### StandardScaler normalization - Fully connected - 100 dense
print('Paper dataset with StandardScaler normalization - ' +
str(df_paper.shape[1] - 1) + ' gene - dense100')
ss_p1_model, _ = tfm_NN.TFM_NNExperiment(X_train_=array_train_X_ss,
y_train_=array_train_y_ss,
X_test_=array_test_X_ss,
y_test_=array_test_y_ss,
df_w_=pd.DataFrame(),
bio_='dense_',
design_name_='gene_' +
str(df_paper.shape[1] - 1) +
'_SScaler_1_layer_100',
pathway_layer_=False,
second_layer_=False,
epochs_=epochs_default,
batch_size_=batch_size_default,
unit_size_=100).build()
# # DESIGN P2 with 1-LAYER - signaling
unit_size = len(df_weight_paper_signaling_dense_pathway.columns)
# ### StandardScaler normalization - Fully (100 dense) + Partially (92 signaling pathway) connected - dense+pathway192
print('Paper dataset with StandardScaler normalization - ' +
str(df_paper.shape[1] - 1) + ' gene - dense+pathway' +
str(unit_size))
ss_p2_sig_model, _ = tfm_NN.TFM_NNExperiment(