Replace root-level scripts with thin wrappers delegating to entrypoints.py

Co-authored-by: ss0832 <80376408+ss0832@users.noreply.github.com>

Author: Copilot

conformation_search.py

@@ -1,9 +1,5 @@
-import sys
-sys.path.append('./multioptpy')
+"""Backward-compatible standalone script. Delegates to the installed entry point."""
+from multioptpy.entrypoints import run_ieipmain
 
-import multioptpy
-
-parser = multioptpy.interface.init_parser()
-args = multioptpy.interface.ieipparser(parser)
-iEIP = multioptpy.ieip.iEIP(args)
-iEIP.run()
+if __name__ == "__main__":
+    run_ieipmain()

ieipmain.py

@@ -1,9 +1,5 @@
-import sys
-sys.path.append('./multioptpy')
+"""Backward-compatible standalone script. Delegates to the installed entry point."""
+from multioptpy.entrypoints import run_mdmain
 
-import multioptpy
-
-parser = multioptpy.interface.init_parser()
-args = multioptpy.interface.mdparser(parser)
-MD = multioptpy.moleculardynamics.MD(args)
-MD.run()
+if __name__ == "__main__":
+    run_mdmain()

mdmain.py

@@ -1,9 +1,5 @@
-import sys
-sys.path.append('./multioptpy')
+"""Backward-compatible standalone script. Delegates to the installed entry point."""
+from multioptpy.entrypoints import run_nebmain
 
-import multioptpy
-
-parser = multioptpy.interface.init_parser()
-args = multioptpy.interface.nebparser(parser)
-NEB = multioptpy.neb.NEB(args)
-NEB.run()
+if __name__ == "__main__":
+    run_nebmain()

nebmain.py

@@ -1,17 +1,5 @@
-import sys
-#import os
-#from glob import glob
-sys.path.append('./multioptpy')
+"""Backward-compatible standalone script. Delegates to the installed entry point."""
+from multioptpy.entrypoints import run_optmain
 
-import multioptpy
-
-parser = multioptpy.interface.init_parser()
-args = multioptpy.interface.optimizeparser(parser)    
-bpa = multioptpy.optimization.Optimize(args)
-bpa.run()
-#print("----------------------------------------------------")
-#print("### gradients of bias potential parameters       ###")
-#print("### (This is the parameters of the final file.)  ###")
-#print(bpa.bias_pot_params_grad_name_list)
-#print(bpa.bias_pot_params_grad_list)
-#print("----------------------------------------------------")
+if __name__ == "__main__":
+    run_optmain()

optmain.py

@@ -1,152 +1,5 @@
-import sys
-import os
-import random
-
-from multioptpy.Utils import calc_tools
-import numpy as np
-
-import multioptpy
-
-def orientation_search(parser):
-    parser.add_argument("-nsample", "--number_of_samples", type=int, default=5, help='the number of sampling orientations')
-    parser.add_argument("-part", "--part", nargs="*", type=str, help='the part number (ex.) 1,2,3 or 1-3', default=None)
-    parser.add_argument("-dist", "--distance",  type=float, default=5.0, help='the distance of parts [ang.]')
-    return parser
-
-
-def num_parse(numbers):
-    sub_list = []
-    
-    sub_tmp_list = numbers.split(",")
-    for sub in sub_tmp_list:                        
-        if "-" in sub:
-            for j in range(int(sub.split("-")[0]),int(sub.split("-")[1])+1):
-                sub_list.append(j)
-        else:
-            sub_list.append(int(sub))    
-    return sub_list
-
-
-def save_xyz_file(coord_list, element_list, file_name, n_sample):
-    no_ext_file_name = os.path.splitext(file_name)[0]
-    sample_file_name = no_ext_file_name+"_Sample_"+str(n_sample)+".xyz"
-    with open(sample_file_name, 'w') as f:
-        f.write(str(len(coord_list))+"\n")
-        f.write("Sample_"+str(n_sample)+"\n")
-        for i in range(len(coord_list)):
-            f.write(element_list[i]+" "+str(coord_list[i][0])+" "+str(coord_list[i][1])+" "+str(coord_list[i][2])+"\n")
-    
-    return sample_file_name
-
-
-def make_random_orientation_xyz_file(coord_list, part_list, part_dist, input_file_name, n_sample):#ang.
-    part_coord_list = []
-    part_element_list = []
-    for part in part_list:
-        tmp_part_coord_list = []
-        tmp_part_element_list = []
-        for p in part:
-            tmp_part_coord_list.append(coord_list[p-1])
-            tmp_part_element_list.append(element_list[p-1])
-        part_coord_list.append(np.array(tmp_part_coord_list))
-        part_element_list.append(tmp_part_element_list)
-
-    # Random rotation
-    rand_rotated_part_coord_list = []
-    for i in range(len(part_coord_list)):
-        part_center = calc_tools.Calculationtools().calc_center(part_coord_list[i], part_element_list[i])
-        centered_part_coord_list = part_coord_list[i] - part_center 
-        random_x_angle = random.uniform(0, 2*np.pi)
-        random_y_angle = random.uniform(0, 2*np.pi)
-        random_z_angle = random.uniform(0, 2*np.pi)
-        print("Random angles (Radian): ", random_x_angle, random_y_angle, random_z_angle)
-        rotated_part_coord = calc_tools.rotate_molecule(centered_part_coord_list, "x", random_x_angle)
-        rotated_part_coord = calc_tools.rotate_molecule(rotated_part_coord, "y", random_y_angle)
-        rotated_part_coord = calc_tools.rotate_molecule(rotated_part_coord, "z", random_z_angle)
-        rand_rotated_part_coord_list.append(rotated_part_coord)
-
-
-    # Random translation
-    rand_tr_rot_part_coord_list = rand_rotated_part_coord_list
-
-    if len(rand_tr_rot_part_coord_list) == 2:
-        rand_dist = random.uniform(part_dist, 1.1*part_dist)
-        rand_tr_rot_part_coord_list[0] = rand_tr_rot_part_coord_list[0] - np.array([part_dist/2, 0, 0])
-        rand_tr_rot_part_coord_list[1] = rand_tr_rot_part_coord_list[1] + np.array([part_dist/2, 0, 0])
-    else:
-        fragm_num = len(rand_tr_rot_part_coord_list)
-        rand_dist = random.uniform(part_dist, 1.1*part_dist)
-        rand_sample_list = random.sample(range(fragm_num), fragm_num)
-        distance_polygen_point_from_center = 0.5 * rand_dist * np.tan((fragm_num - 2) * np.pi / fragm_num)
-        tmp_angle = 0.0
-        for i in range(len(rand_sample_list)):
-            rand_tr_rot_part_coord_list[rand_sample_list[i]] = rand_tr_rot_part_coord_list[rand_sample_list[i]] + np.array([distance_polygen_point_from_center * np.cos(tmp_angle), distance_polygen_point_from_center * np.sin(tmp_angle), 0])
-            tmp_angle += 2 * np.pi / fragm_num
-    
-    combined_coord_list = np.zeros((len(coord_list), 3))       
-
-    # Combine all parts
-    for i in range(len(part_list)):
-        part = part_list[i]
-       
-        for j in range(len(part)):
-            
-            combined_coord_list[part[j]-1] = rand_tr_rot_part_coord_list[i][j]
-
-    input_file_name = save_xyz_file(combined_coord_list, element_list, input_file_name, n_sample)
-    
-    return input_file_name
-
-
-
-if __name__ == '__main__':
-    parser = multioptpy.interface.init_parser()
-    parser = orientation_search(parser)
-    args = multioptpy.interface.optimizeparser(parser)
-    
-    part_dist = args.distance
-    
-    with open(args.INPUT, 'r') as f:
-        words = f.read().splitlines()
-    
-    element_list = []
-    coord_list = []
-    
-    for word in words:
-        splitted_word = word.split()
-
-        if len(splitted_word) > 3:
-            element_list.append(str(splitted_word[0]))
-            coord_list.append([float(splitted_word[1]), float(splitted_word[2]), float(splitted_word[3])])
-    
-    coord_list = np.array(coord_list, dtype="float64")
-    atom_num = len(coord_list)
-
-    if args.part is None:
-        print("No part is specified. exit....")
-        sys.exit(0)
-    
-    part_list = []
-    for i in range(len(args.part)):
-        part_list.append(num_parse(args.part[i]))
-    
-    flattened_part_list = [item for sublist in part_list for item in sublist]
-    missing_parts = [num for num in range(1, atom_num+1) if num not in flattened_part_list]
-    if len(missing_parts) > 0:
-        part_list.append(missing_parts)
-
-    print("Number of Parts: ", len(part_list)) 
-    n_sample = args.number_of_samples
-    
-    original_input_file = args.INPUT
-    
-    for i in range(n_sample):
-        print("Sampling orientation: ", i)    
-        args.INPUT = make_random_orientation_xyz_file(coord_list, part_list, part_dist, original_input_file, i)
-        bpa = multioptpy.optimization.Optimize(args)
-        bpa.run()
-    
-        
-        print("Sampling orientation: ", i, "done")
-    
-    print("Orientation search done")
+"""Backward-compatible standalone script. Delegates to the installed entry point."""
+from multioptpy.entrypoints import run_orientsearch
+
+if __name__ == "__main__":
+    run_orientsearch()

orientation_search.py

@@ -1,127 +1,5 @@
-import sys
-import os
-import shutil
-import datetime
-
-import multioptpy.Utils.calc_tools
-from multioptpy.Parameters.unit_values import UnitValueLib
-import numpy as np
-import multioptpy
-
-# When you use psi4 with this script, segmentation fault may occur. Thus, I recommend to use pyscf, tblite and so on with the following script.
-
-def relaxed_scan_perser(parser):
-    parser.add_argument("-nsample", "--number_of_samples", type=int, default=10, help='the number of sampling relaxed scan coordinates')
-    parser.add_argument("-scan", "--scan_tgt", nargs="*", type=str, help='scan target (ex.) [[bond, angle, or dihedral etc.] [atom_num] [(value_1(ex. 1.0 ang.)),(value_2(ex. 1.5 ang.))] ...] ', default=None)
-    parser.add_argument("-fo", "--first_only", action="store_true", help='use only input structure for relax scan ')
-    return parser
-
-
-def num_parse(numbers):
-    sub_list = []
-    
-    sub_tmp_list = numbers.split(",")
-    for sub in sub_tmp_list:                        
-        if "-" in sub:
-            for j in range(int(sub.split("-")[0]),int(sub.split("-")[1])+1):
-                sub_list.append(j)
-        else:
-            sub_list.append(int(sub))    
-    return sub_list
-
-
-def save_xyz_file(coord_list, element_list, file_name, additional_name, directory):
-    no_ext_file_name = os.path.splitext(file_name)[0]
-    sample_file_name = no_ext_file_name+"_RelaxedScan_"+str(additional_name)+".xyz"
-    with open(directory + sample_file_name, 'w') as f:
-        f.write(str(len(coord_list))+"\n")
-        f.write("RelaxedScan_"+str(additional_name)+"\n")
-        for i in range(len(coord_list)):
-            f.write(element_list[i]+" "+str(coord_list[i][0])+" "+str(coord_list[i][1])+" "+str(coord_list[i][2])+"\n")
-    
-    return sample_file_name
-
-def make_scan_tgt(scan_list):
-    scan_tgt_list = []
-    atom_num_list = []
-    scan_range_list = []
-    for i in range(int(len(scan_list)/3)):
-        scan = scan_list[i*3:i*3+3]
-        scan_type = str(scan[0])
-        atom_num_list.append(scan[1])
-        tmp_scan_tgt = scan[2].split(",")
-        scan_tgt_list.append(scan_type)
-        scan_range_list.append([float(tmp_scan_tgt[0]), float(tmp_scan_tgt[1])])
-    return scan_tgt_list, atom_num_list, scan_range_list
-   
-
-if __name__ == '__main__':
-    parser = multioptpy.interface.init_parser()
-    parser = relaxed_scan_perser(parser)
-    args = multioptpy.interface.optimizeparser(parser)
-    first_only_flag = args.first_only
-    date = datetime.datetime.now().strftime("%Y_%m_%d_%H_%M_%S")
-    directory = os.path.splitext(args.INPUT)[0]+"_RScan_"+date+"/"
-    os.makedirs(directory, exist_ok=True)   
-    ene_profile_filepath = directory + os.path.splitext(args.INPUT)[0]+"_scan_energy_profile_"+date+".csv"
-    
-    scan_part = int(args.number_of_samples)
-    scan_tgt_list, atom_num_list, scan_range_list = make_scan_tgt(args.scan_tgt)
-    
-    with open(args.INPUT, 'r') as f:
-        words = f.read().splitlines()
-    
-  
-    print("Start relaxed scan .... ")
-    print("Scan target: ", scan_tgt_list, atom_num_list)
-    print("Scan range: ", scan_range_list)
-    scan_job_list = np.array([np.linspace(start, end, scan_part) for start, end in scan_range_list]).T
-    
-  
-    original_input_file = args.INPUT
-    original_args = args
-
-    with open(ene_profile_filepath, "w") as f:
-        f.write(str(",".join(scan_tgt_list))+",energy,bias_energy\n")
-        tmp_atom_num_list = [str(i).replace(",", "_") for i in atom_num_list]
-        f.write(str(",".join(tmp_atom_num_list))+",(hartree),(hartree)\n")
-
-
-    shutil.copyfile(original_input_file, directory + os.path.splitext(original_input_file)[0]+"_RelaxedScan_0.xyz")
-    shutil.copyfile(original_input_file, os.path.splitext(original_input_file)[0]+"_RelaxedScan_0.xyz")
-    init_input_file = os.path.splitext(original_input_file)[0]+"_RelaxedScan_0.xyz"
-    args.INPUT = init_input_file
-
-    with open(directory + "input.txt", 'w') as f:
-        f.write(str(vars(args)))
-
-    for i in range(scan_part):
-        print("scan type(s)  : ", scan_tgt_list)
-        print("scan atom(s)  : ", atom_num_list)
-        print("scan value(s) : ", scan_job_list[i])
-        args.projection_constrain = []
-        for scan_tgt, atom_num, scan_value in zip(scan_tgt_list, atom_num_list, scan_job_list[i]):
-            args.projection_constrain.extend(["manual", scan_tgt, atom_num, str(scan_value)])
-            
-        bpa = multioptpy.optimization.Optimize(args)
-        bpa.run()
-        
-        opted_geometry = bpa.final_geometry * UnitValueLib().bohr2angstroms # get optimized geometry
-        element_list = bpa.element_list
-        energy = bpa.final_energy
-        bias_energy = bpa.final_bias_energy
-        
-        next_input_file_for_save = directory + save_xyz_file(opted_geometry, element_list, original_input_file, i+1, directory)
-        next_input_file = save_xyz_file(opted_geometry, element_list, original_input_file, i+1, "")
-        args = original_args
-        if first_only_flag:
-            args.INPUT = init_input_file
-        else:
-            args.INPUT = next_input_file
-        print("Done.")
-        
-        with open(ene_profile_filepath, "a") as f:
-            f.write(str(",".join(list(map(str, scan_job_list[i].tolist())))) + "," + str(energy) + "," + str(bias_energy) + "\n")
-        del bpa
-    
-    print("Relaxed scan done ...")
+"""Backward-compatible standalone script. Delegates to the installed entry point."""
+from multioptpy.entrypoints import run_relaxedscan
+
+if __name__ == "__main__":
+    run_relaxedscan()