Merge pull request #6 from sxm13/main

add "keep_connect"

Author: sxm13

README.md

@@ -36,13 +36,13 @@ pip install -r requirements.txt
 
 ```sh      
 from PACMANCharge import pmcharge
-pmcharge.predict(cif_file="./test/Cu-BTC.cif",charge_type="DDEC6",digits=10,atom_type=True,neutral=True)
+pmcharge.predict(cif_file="./test/Cu-BTC.cif",charge_type="DDEC6",digits=10,atom_type=True,neutral=True,keep_connect=True)
 
 ```                                                               
                                   
 **Terminal**
 ```sh
-python pmcharge.py folder-name[path] --charge_type[DDEC6/Bader/CM5/REPEAT] --digits[int] --atom_type[bool] --neutral[bool]
+python pmcharge.py folder-name[path] --charge_type[DDEC6/Bader/CM5/REPEAT] --digits[int] --atom_type[bool] --neutral[bool] --keep_connect[bool]
 ```
 **Example command:** ```python pmcharge.py test_file/test-1/ --charge_type DDEC6 --digits 10```                                                    
 
@@ -53,6 +53,7 @@ python pmcharge.py folder-name[path] --charge_type[DDEC6/Bader/CM5/REPEAT] --dig
 * digits (default: 6): number of decimal places to print for partial atomic charges. ML models were trained on a 6-digit dataset                                                    
 * atom-type (default: True): Default is to keep the same partial atomic charge for the same atom types (based on the similarity of partial atomic charges up to 3 decimal places)                    
 * neutral (default: True): Default is to keep the net charge is zero. We use "mean" method to neuralize the system where the excess charges are equally distributed across all atoms              
+* keep_connect (default: True): retain the atomic and connection information (such as _atom_site_adp_type, bond) for the structure.             
 
 # Website & Zenodo
 * Predict partial atomic charges using an online APP :point_right: [link](https://pacman-charge-mtap.streamlit.app/)

model/cif2data.py

@@ -1,10 +1,12 @@
 import os
 import re
+import glob
 import json
 import warnings
 import numpy as np
 import pandas as pd
 from tqdm import tqdm
+from CifFile import ReadCif
 import pymatgen.core as mg
 from ase.io import read
 from ase import neighborlist
@@ -207,6 +209,14 @@ def get_ddec_data(root_cif_dir,dataset_csv,save_ddec_dir):
             np.save(save_ddec_dir + mof + '.npy', ddec_data)          
         f.close()
 
+def get_ddec_data_from_qmof(root_cif_dir,dataset_csv,save_ddec_dir):
+    mofs = pd.read_csv(dataset_csv)["name"]
+    for mof in mofs:
+        data_cif = ReadCif(root_cif_dir + mof + ".cif")
+        charge = data_cif[data_cif.keys()[0]]["_atom_site_pbe_ddec_charge"]
+        np.save(save_ddec_dir + mof + '.npy', charge)          
+
+
 def get_bader_data(root_cif_dir,dataset_csv,save_bader_dir):
     mofs = pd.read_csv(dataset_csv)["name"]
     for mof in mofs:
@@ -234,7 +244,14 @@ def get_bader_data(root_cif_dir,dataset_csv,save_bader_dir):
             f.close()
         except:
             pass
-        
+
+def get_bader_data_from_qmof(root_cif_dir,dataset_csv,save_bader_dir):
+    mofs = pd.read_csv(dataset_csv)["name"]
+    for mof in mofs:
+        data_cif = ReadCif(root_cif_dir + mof + ".cif")
+        charge = data_cif[data_cif.keys()[0]]["_atom_site_pbe_bader_charge"]
+        np.save(save_bader_dir + mof + '.npy', charge)  
+
 def get_cm5_data(root_cif_dir,dataset_csv,save_cm5_dir):
     mofs = pd.read_csv(dataset_csv)["name"]
     for mof in mofs:
@@ -263,6 +280,13 @@ def get_cm5_data(root_cif_dir,dataset_csv,save_cm5_dir):
         except:
             pass
 
+def get_cm5_data_from_qmof(root_cif_dir,dataset_csv,save_cm5_dir):
+    mofs = pd.read_csv(dataset_csv)["name"]
+    for mof in mofs:
+        data_cif = ReadCif(root_cif_dir + mof + ".cif")
+        charge = data_cif[data_cif.keys()[0]]["_atom_site_pbe_cm5_charge"]
+        np.save(save_cm5_dir + mof + '.npy', charge)  
+
 def get_repeat_data(root_cif_dir,save_repeat_dir):
     mofs = glob.glob(os.path.join(root_cif_dir, '*.cif'))
     for mof in tqdm(mofs[:]):
@@ -279,6 +303,13 @@ def get_repeat_data(root_cif_dir,save_repeat_dir):
                         repeat_data.append(repeat.replace("\n",""))
                 np.save(save_repeat_dir + mof + '.npy', repeat_data)          
             f.close()
-			
         except:
-           pass
+           pass
+
+def get_repeat_data_from_arcmof(root_cif_dir,save_repeat_dir):
+    mofs = glob.glob(os.path.join(root_cif_dir, '*.cif'))
+    for mof in mofs:
+        mof = mof.replace(".cif","").split("/")[-1]
+        data_cif = ReadCif(root_cif_dir + mof + ".cif")
+        charge = data_cif[data_cif.keys()[0]]["_atom_site_pbe_cm5_charge"]
+        np.save(save_repeat_dir + mof + '.npy', charge)  

model4pre/__pycache__/cif2data.cpython-39.pyc

@@ -1,6 +1,7 @@
 import warnings
 import numpy as np
 import pymatgen.core as mg
+from CifFile import ReadCif
 from ase.io import read,write
 from pymatgen.io.ase import AseAtomsAdaptor
 from pymatgen.io.cif import CifParser
@@ -146,7 +147,7 @@ def average_and_replace(numbers, di):
             numbers[i] = avg
     return numbers
 
-def write4cif(mof,chg,digits,atom_type,neutral,charge_type):
+def write4cif(mof,chg,digits,atom_type,neutral,charge_type,keep_connect):
     name = mof.split('.cif')[0]
     chg = chg.numpy()
     dia = int(digits)
@@ -190,36 +191,43 @@ def write4cif(mof,chg,digits,atom_type,neutral,charge_type):
 
     if neutral==False:
         print("net charge: "+str(sum(charges)))
+    if keep_connect:
+        mof = ReadCif(name + ".cif")
+        mof.first_block().AddToLoop("_atom_site_type_symbol",{'_atom_site_charge':[str(q) for q in charges]})
+        with open(name + "_pacman.cif", 'w') as f:
+            f.write("# " + charge_type + "charges by PACMAN v1.3 (https://github.com/mtap-research/PACMAN-charge/)\n" +
+                    f"data_{name.split('/')[-1]}" + str(mof.first_block()))
+        print("Compelete and save as "+ name + "_pacman.cif")
+    else:
+        with open(name + ".cif", 'r') as file:
+            lines = file.readlines()
+        lines[0] = "# "+charge_type+" charges by PACMAN v1.3 (https://github.com/mtap-research/PACMAN-charge/)\n"
+        lines[1] = "data_" + name.split("/")[-1] + "_pacman\n"
+        for i, line in enumerate(lines):
+            if '_atom_site_occupancy' in line:
+                lines.insert(i + 1, "  _atom_site_charge\n")
+                break
+        charge_index = 0
+        for j in range(i + 2, len(lines)):
+            if charge_index < len(charges):
+                lines[j] = lines[j].strip() + " " + str(charges[charge_index]) + "\n"
+                charge_index += 1
+            else:
+                break
 
-    with open(name + ".cif", 'r') as file:
-        lines = file.readlines()
-    lines[0] = "# "+charge_type+" charges by PACMAN v1.1 (https://github.com/mtap-research/PACMAN-charge/)\n"
-    lines[1] = "data_" + name.split("/")[-1] + "_pacman\n"
-    for i, line in enumerate(lines):
-        if '_atom_site_occupancy' in line:
-            lines.insert(i + 1, "  _atom_site_charge\n")
-            break
-    charge_index = 0
-    for j in range(i + 2, len(lines)):
-        if charge_index < len(charges):
-            lines[j] = lines[j].strip() + " " + str(charges[charge_index]) + "\n"
-            charge_index += 1
-        else:
-            break
-
-    with open(name + "_pacman.cif", 'w') as file:
-        file.writelines(lines)
-    file.close()
+        with open(name + "_pacman.cif", 'w') as file:
+            file.writelines(lines)
+        file.close()
 
-    with open(name + "_pacman.cif", 'r') as file:
-        content = file.read()
-    file.close()
+        with open(name + "_pacman.cif", 'r') as file:
+            content = file.read()
+        file.close()
 
-    new_content = content.replace('_space_group_name_H-M_alt', '_symmetry_space_group_name_H-M')
-    new_content = new_content.replace('_space_group_IT_number', '_symmetry_Int_Tables_number')
-    new_content = new_content.replace('_space_group_symop_operation_xyz', '_symmetry_equiv_pos_as_xyz')
+        new_content = content.replace('_space_group_name_H-M_alt', '_symmetry_space_group_name_H-M')
+        new_content = new_content.replace('_space_group_IT_number', '_symmetry_Int_Tables_number')
+        new_content = new_content.replace('_space_group_symop_operation_xyz', '_symmetry_equiv_pos_as_xyz')
 
-    with open(name + "_pacman.cif", 'wb') as file:
-        file.write(new_content.encode('utf-8'))
-    file.close()
-    print("Compelete and save as "+ name + "_pacman.cif")
+        with open(name + "_pacman.cif", 'wb') as file:
+            file.write(new_content.encode('utf-8'))
+        file.close()
+        print("Compelete and save as "+ name + "_pacman.cif")

model4pre/cif2data.py

@@ -17,13 +17,15 @@ def main():
     parser.add_argument('--digits', type=int, default=6, help='Number of decimal places to print for partial atomic charges')
     parser.add_argument('--atom_type', type=bool, default=True, help='Keep the same partial atomic charge for the same atom types')
     parser.add_argument('--neutral', type=bool, default=True, help='Keep the net charge is zero')
+    parser.add_argument('--keep_connect', type=bool, default=True, help='Keep information from original CIF file')
     args = parser.parse_args()
 
     path = args.folder_name
     charge_type =  args.charge_type
     digits = args.digits
     atom_type = args.atom_type
     neutral = args.neutral
+    keep_connect = args.keep_connect
     if os.path.isfile(path):
         print("please input a folder, not a file")
     elif os.path.isdir(path):
@@ -65,6 +67,7 @@ def main():
     print("Digits: " + str(digits))
     print("Atom Type:" + str(atom_type))
     print("Neutral: " + str(neutral))
+    print("Keep Connect: " + str(keep_connect))
 
     cif_files = glob.glob(os.path.join(path, '*.cif'))
     print("writing cif: ***_pacman.cif")
@@ -74,7 +77,10 @@ def main():
     i = 0
     for cif in tqdm(cif_files):
         try:
-            ase_format(cif)
+            if keep_connect:
+                pass
+            else:
+                ase_format(cif)
             cif_data = CIF2json(cif)
             pos = pre4pre(cif)
             # num_atom = n_atom(cif)
@@ -114,7 +120,7 @@ def main():
             # model_bandgap.eval()
 
             gcn = GCN(chg_1-3, chg_2, 128, 7, 256,5) 
-            chkpt = torch.load(model_charge_name, map_location=torch.device(device), weights_only=True)
+            chkpt = torch.load(model_charge_name, map_location=torch.device(device)) #, weights_only=True
             model4chg = SemiFullGN(chg_1,chg_2,128,8,256)
             model4chg.to(device)
             model4chg.load_state_dict(chkpt['state_dict'])
@@ -146,7 +152,7 @@ def main():
 
                     chg = model4chg(*input_var2)
                     chg = charge_nor.denorm(chg.data.cpu())
-                    write4cif(cif,chg,digits,atom_type,neutral,charge_type)          
+                    write4cif(cif,chg,digits,atom_type,neutral,charge_type,keep_connect)          
         except:
             print("Fail predict: " + cif)
             fail[str(i)]=[cif]

pmcharge.py

@@ -5,4 +5,5 @@ tqdm>=4.15
 pandas>=0.20.3
 scikit-learn>=0.19.1
 joblib>= 0.13.2
-torch
+torch
+PyCifRW