various changes

temp.py

@@ -0,0 +1,92 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Sun May 29 09:22:51 2022
+
+@author: tanu
+"""
+
+geneL_basic     = ['pncA']
+geneL_na        = ['gid']
+geneL_na_ppi2   = ['rpoB']
+geneL_ppi2      = ['alr', 'embB', 'katG']
+#%% get cols
+mycols = my_df.columns
+
+# # change from numberic to 
+# num_type = ['int64', 'float64']
+# cat_type = ['object', 'bool']
+
+# if my_df['active_aa_pos'].dtype in num_type:
+#     my_df['active_aa_pos'] = my_df['active_aa_pos'].astype(object)
+#     my_df['active_aa_pos'].dtype
+
+# FIXME: if this is not structural, remove from source..
+# Drop NA where numerical cols have them
+if gene.lower() in geneL_na_ppi2:
+    #D1148 get rid of
+    na_index = my_df['mutationinformation'].index[my_df['mcsm_na_affinity'].apply(np.isnan)]
+    my_df = my_df.drop(index=na_index)
+
+# FIXME: either impute or remove!
+# for embb (L114M, F115L, V123L, V125I, V131M) delete for now
+if gene.lower() in ['embb']:
+    na_index = my_df['mutationinformation'].index[my_df['ligand_distance'].apply(np.isnan)]
+    #my_df = my_df.drop(index=na_index))# RERUN embb with the 5 values now present
+#%%===========================================================================
+
+#%%
+# GET X
+common_cols_stabiltyN = ['ligand_distance'
+           , 'ligand_affinity_change'
+           , 'duet_stability_change'
+           , 'ddg_foldx'
+           , 'deepddg'
+           , 'ddg_dynamut2'
+           , 'contacts']
+
+# Build stability columns ~ gene
+if gene.lower() in geneL_basic:
+    x_stabilityN = common_cols_stabiltyN
+    cols_to_mask = ['ligand_affinity_change']
+    
+if gene.lower() in geneL_ppi2:
+#    x_stabilityN = common_cols_stabiltyN + ['mcsm_ppi2_affinity' , 'interface_dist'] 
+    geneL_ppi2_st_cols = ['mcsm_ppi2_affinity', 'interface_dist'] 
+    x_stabilityN = common_cols_stabiltyN + geneL_ppi2_st_cols
+    cols_to_mask = ['ligand_affinity_change', 'mcsm_ppi2_affinity']
+
+if gene.lower() in geneL_na:
+#    x_stabilityN = common_cols_stabiltyN + ['mcsm_na_affinity'] 
+    geneL_na_st_cols =  ['mcsm_na_affinity'] 
+    x_stabilityN = common_cols_stabiltyN + geneL_na_st_cols
+    cols_to_mask = ['ligand_affinity_change', 'mcsm_na_affinity']
+
+if gene.lower() in geneL_na_ppi2:
+#    x_stabilityN = common_cols_stabiltyN + ['mcsm_na_affinity'] + ['mcsm_ppi2_affinity', 'interface_dist'] 
+    geneL_na_ppi2_st_cols = ['mcsm_na_affinity'] + ['mcsm_ppi2_affinity', 'interface_dist'] 
+    x_stabilityN = common_cols_stabiltyN + geneL_na_ppi2_st_cols
+    cols_to_mask = ['ligand_affinity_change', 'mcsm_na_affinity', 'mcsm_ppi2_affinity']
+
+
+#%% Masking columns (mCSM-lig, mCSM-NA, mCSM-ppi2) values for lig_dist >10
+my_df_ml['mutationinformation'][my_df_ml['ligand_distance']>10].value_counts()
+my_df_ml.groupby('mutationinformation')['ligand_distance'].apply(lambda x: (x>10)).value_counts()
+my_df_ml.loc[(my_df_ml['ligand_distance'] > 10), cols_to_mask].value_counts()
+
+# mask the column ligand distance > 10
+my_df_ml.loc[(my_df_ml['ligand_distance'] > 10), cols_to_mask] = 0
+(my_df_ml['ligand_affinity_change'] == 0).sum()
+
+mask_check = my_df_ml[['mutationinformation', 'ligand_distance'] + cols_to_mask]
+
+
+for i in range(len(cols_to_mask)):
+    ind = i+1
+    print('\nindex:', i, '\nind:', ind)
+    print('\nMask count check:'
+          , (my_df_ml[cols_to_mask[i]]==0).sum() == (my_df_ml['ligand_distance']>10).sum()
+          )
+
+(my_df_ml[cols_to_mask[0]]==0).sum() == (my_df_ml['ligand_distance']>10).sum()
+(my_df_ml[cols_to_mask[1]]==0).sum() == (my_df_ml['ligand_distance']>10).sum()