added another parser for xyz misalignment bug

data_processor_polar.py

@@ -49,8 +49,8 @@ def hydrophobic_acid_patch_interactions(paramlist):
  #check if coordinate data collumns are collided (most likely happens between x and y coor)
  while len(clean_line[6])>=13:
  split = [clean_line[6][:-8], clean_line[6][-8:]]
- last_elem = clean_line.pop()
- clean_line[-1] = last_elem
+# last_elem = clean_line.pop()
+# clean_line[-1] = last_elem
  clean_line.insert(6, split[0])
  clean_line[7] = split[1]
  if len(clean_line[7])>=13:
@@ -203,7 +203,7 @@ def hydrophobic_acid_patch_interactions(paramlist):
  data = data_checker.data_load(filename)
  print(data, len(data))
 
-# id_name = '3s5l.ent.pdb'
+# id_name = '4gxu.ent.pdb'
 # path_file = path+'/'+id_name
 # l =[]
 # with open(path_file, 'r') as f:
@@ -224,8 +224,8 @@ def hydrophobic_acid_patch_interactions(paramlist):
 # #check if coordinate data collumns are collided (most likely happens between x and y coor)
 # while len(clean_line[6])>=13:
 # split = [clean_line[6][:-8], clean_line[6][-8:]]
-# last_elem = clean_line.pop()
-# clean_line[-1] = last_elem
+## last_elem = clean_line.pop()
+## clean_line[-1] = last_elem
 # clean_line.insert(6, split[0])
 # clean_line[7] = split[1]
 # if len(clean_line[7])>=13:
@@ -240,3 +240,29 @@ def hydrophobic_acid_patch_interactions(paramlist):
 # l.append(clean_line)
 # elif line.startswith('ENDMDL'):
 # break
+# print(l[34338])
+# df_atoms = (pd.DataFrame(l)).rename(columns={0:'record', 6:'x_coor', 7:'y_coor', 8:'z_coor', 11:'atom_type', 2:'atom_name', 3:'amino_acid_type'})
+# 
+# #dataframe splitter:
+# l_df = []
+# last_idx = 0
+# for idx in df_atoms.index[df_atoms['record'] == 'TER'].tolist():
+# l_df.append(df_atoms.iloc[last_idx:idx])
+# last_idx = idx+1
+# 
+# #hydrophobics and acids types of amino acids
+# hydrophobics = ['ALA','VAL','ILE','LEU','MET','PHE','TYR','TRP']
+# acids = ['ARG','HIS','LYS','ASP','GLU']
+# 
+# #select the carbon alpha of atoms based on the amino acid types
+# hydrophobics_patches = []
+# for i in range(len(l_df)):
+# mol_patch=l_df[i].set_index(['amino_acid_type'])
+# hydrophobics_patches.append(mol_patch.loc[ (mol_patch.index.isin(hydrophobics)) & (mol_patch['atom_name'] == 'CA') ]) 
+# print(mol_patch.loc[ (mol_patch.index.isin(hydrophobics)) & (mol_patch['atom_name'] == 'CA') ][['x_coor','y_coor','z_coor']])
+# 
+# acid_patches = []
+# for i in range(len(l_df)):
+# mol_patch=l_df[i].set_index(['amino_acid_type'])
+# acid_patches.append(mol_patch.loc[ (mol_patch.index.isin(acids)) & (mol_patch['atom_name'] == 'CA') ])
+# print()