Added a tool to extract critical buckling loads from the Abaqus data files for parametric studies

README.md

 # Welcome to the Spindle FEA application repository
 
 [![License](https://img.shields.io/badge/License-MIT-blue.svg)](https://opensource.org/licenses/MIT)
+[![GitLab issues](https://img.shields.io/github/issues/badges/shields.svg)]
+
 
 ## Installation instructions
 

datExtract.py

+"""
+This script should be executed from the directory that contains .dat files generated by Abaqus CAE during analysis.
+It can be used to extract the critical buckling load values from each analysis .dat file and then store them within a
+single .dat file.
+"""
+
+import os
+import csv
+
+
+def eigenvals(path):
+    """
+    This function extracts all the eigenvalues from the list of .dat
+    files and saves them into a single .dat file
+
+    :param path: path to the .dat files generated by Abaqus CAE
+
+    :type path: str
+
+    :return: list of eigenvalues
+
+    :rtype: list
+    """
+
+    walk_dir = os.path.abspath(path)  # Convert to absolute path
+    print('Root directory is %s' % walk_dir)
+    content = []
+    # Extract content of each .dat file
+    files = next(os.walk(walk_dir))[2]
+    files.sort()
+    for filename in [f for f in files if f.endswith(".dat")]:
+        with open(os.path.join(walk_dir, filename), 'r') as f:
+            content.append(f.read().splitlines())
+    # Extract eigenvalues
+    eig_list = []
+    for item in content:
+        for index, line in enumerate(item):
+            if ' MODE NO      EIGENVALUE' in line:
+                # Extracting eig by its position
+                eig_list.append(item[index + 3:index + 11])
+    # Transforming to float:
+    eig_float = [[float(j.split()[1]) for j in x] for x in eig_list]
+    # Write into a .csv file
+    with open("eig_list_new.dat", "w") as f:
+        writer = csv.writer(f)
+        writer.writerows(eig_float)
+    return eig_float
+
+
+if __name__ == '__main__':
+    # Exporting mesh statistics:
+    path = './'
+    eigfloat = eigenvals(path)