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CSD_non_disordered.zip

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+oid sha256:64a57930f5c9a2a575f3091c4399cab97f28bfc251911a00fd5d511c386e5e9d
+size 292253426

CSD_non_disordered/cleaned_ase.zip

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+oid sha256:1300733f40ef6bf1facf10f2277e1a9ddb51f84e62e2a2cdc07edd5d92b39c38
+size 361965261

CSD_non_disordered/cleaned_pymatgen.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b1c44a69f5825787919fa0a1466008b47ca39a5b120028211a6bfc0495f32e60
+size 258687792

clean.py

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+import os
+from tqdm import tqdm
+from ase.io import read, write
+from pymatgen.io.cif import CifParser
+import warnings
+
+warnings.filterwarnings("ignore")
+
+
+# Define your input and output folders
+input_folder = "/users/PAS2490/marcusshen/cmame/Data/CSD_non_disordered/CSD_non_disordered/"
+output_folder_ase = "/users/PAS2490/marcusshen/cmame/Data/CSD_non_disordered/CSD_non_disordered/cleaned_ase/"
+output_folder_pymatgen = "/users/PAS2490/marcusshen/cmame/Data/CSD_non_disordered/CSD_non_disordered/cleaned_pymatgen/"
+
+
+# Create output directories if they do not exist
+os.makedirs(output_folder_ase, exist_ok=True)
+os.makedirs(output_folder_pymatgen, exist_ok=True)
+
+# Get the list of CIF files in the input folder
+cif_files = [f for f in os.listdir(input_folder) if f.endswith(".cif")]
+
+# Iterate through all files in the input folder
+for file_name in tqdm(cif_files, desc="Processing CIF files"):
+    if file_name.endswith(".cif"):  # Process only CIF files
+        input_path = os.path.join(input_folder, file_name)
+        ase_output_path = os.path.join(output_folder_ase, file_name)
+        pymatgen_output_path = os.path.join(output_folder_pymatgen, file_name)
+        
+        try:
+            # Step 1: Use ASE to clean the structure and save to output folder
+            structure = read(input_path)
+            write(ase_output_path, structure)
+            
+            # Step 2: Use Pymatgen to further clean and save the structure
+            parser = CifParser(ase_output_path)
+            structure_pymatgen = parser.get_structures()[0]  # Extract the first structure
+            structure_pymatgen.to(filename=pymatgen_output_path)
+        except Exception as e:
+            print(f"Error processing file {file_name}: {e}")

process_cif.py

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+import os
+from tqdm import tqdm
+from ase.io import read, write
+from pymatgen.io.cif import CifParser
+from multiprocessing import Pool, cpu_count
+import warnings
+
+warnings.filterwarnings("ignore")
+
+# Define your input and output folders
+input_folder = "/users/PAS2490/marcusshen/cmame/Data/CSD_non_disordered/CSD_non_disordered/"
+output_folder_ase = "/users/PAS2490/marcusshen/cmame/Data/CSD_non_disordered/CSD_non_disordered/cleaned_ase/"
+output_folder_pymatgen = "/users/PAS2490/marcusshen/cmame/Data/CSD_non_disordered/CSD_non_disordered/cleaned_pymatgen/"
+
+# Create output directories if they do not exist
+os.makedirs(output_folder_ase, exist_ok=True)
+os.makedirs(output_folder_pymatgen, exist_ok=True)
+
+# Get the list of CIF files in the input folder
+cif_files = [f for f in os.listdir(input_folder) if f.endswith(".cif")]
+
+def process_file(file_name):
+    input_path = os.path.join(input_folder, file_name)
+    ase_output_path = os.path.join(output_folder_ase, file_name)
+    pymatgen_output_path = os.path.join(output_folder_pymatgen, file_name)
+
+    try:
+        # Step 1: Use ASE to clean the structure and save to output folder
+        structure = read(input_path)
+        write(ase_output_path, structure)
+
+        # Step 2: Use Pymatgen to further clean and save the structure
+        parser = CifParser(ase_output_path)
+        structure_pymatgen = parser.get_structures()[0]  # Extract the first structure
+        structure_pymatgen.to(filename=pymatgen_output_path)
+    except Exception as e:
+        return f"Error processing file {file_name}: {e}"
+    return f"Successfully processed {file_name}"
+
+if __name__ == "__main__":
+    # Use a Pool to process files in parallel
+    num_workers = cpu_count()  # Use all available CPUs
+    with Pool(processes=num_workers) as pool:
+        # Use tqdm for a progress bar
+        results = list(tqdm(pool.imap(process_file, cif_files), total=len(cif_files), desc="Processing CIF files"))
+    
+    # Print results
+    for result in results:
+        if "Error" in result:
+            print(result)

slurm-252872.out

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+
+Error processing file CUGMPP.cif: data_CSD_CIF_CUGMPP
+Processing complete!
+Elapsed time: 01:18:01

sub_cpu.sh

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+#!/bin/bash
+
+#SBATCH --job-name=clean            # 作业名称
+#SBATCH --account=PAS2490		    # Project ID
+#SBATCH --nodes=1                   # 节点数
+#SBATCH --ntasks-per-node=1         # 每个节点的任务数
+#SBATCH --cpus-per-task=32           # 每个任务使用的 CPU 核心数
+#SBATCH --mem=100G                  # 内存限制
+#SBATCH --time=24:00:00            # 作业运行时间限制
+#SBATCH --mail-type=BEGIN,END,FAIL
+#SBATCH --mail-user=uceckz0@ucl.ac.uk
+# 运行命令或脚本 wget https://repo.anaconda.com/archive/Anaconda3-2023.07-2-Linux-x86_64.sh
+start=$(date +%s)
+
+source $HOME/miniconda3/etc/profile.d/conda.sh
+conda activate matbench_env
+
+PYTHON_SCRIPT="process_cif.py"
+
+# Check if the Python script exists
+if [ ! -f "$PYTHON_SCRIPT" ]; then
+    echo "Python script not found: $PYTHON_SCRIPT"
+    exit 1
+fi
+
+# Run the Python script using Python interpreter
+python "$PYTHON_SCRIPT"
+
+echo "Processing complete!"
+
+conda deactivate
+
+
+end=$(date +%s)
+elapsed=$(( end - start ))
+hours=$(( elapsed / 3600 ))
+minutes=$(( (elapsed % 3600) / 60 ))
+seconds=$(( elapsed % 60 ))
+printf "Elapsed time: %02d:%02d:%02d\n" $hours $minutes $seconds