Merge pull request #59 from casper-schutte/development

Development

Validation Testing/README.txt

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+Unzip all of the files
+
+Install the fantastic-lamp conda environment
+
+With all of the files in the same folder (and the env active), run:
+
+bash validation_test.sh
+
+OR 
+
+conda run -n fantastic-lamp bash validation_test.sh
+

Validation Testing/collect_results.py

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+import csv
+import sys
+"""
+This script will collect the relevant results from the .tsv files used for validation testing and write them to a new
+file. This will allow the results to be easily compared to the expected results. The relevant results are:
+- The name of the edit (from the file name)
+- The edit homology arm with the highest fractional coverage
+- The fractional coverage for the above edit homology arm.
+"""
+threshold = 0.5
+
+
+def read_tsv_file(file_name):
+    """
+    Reads a .tsv file and returns the relevant information.
+    """
+    try:
+        with open(file_name, newline='') as tsv_file:
+            reader = csv.reader(tsv_file, delimiter='\t')
+            tsv_list = list(reader)[1:6]
+
+            # Filter non-zero rows using list comprehension
+            non_zero = [row for row in tsv_list if float(row[1]) != 0]
+
+            # Extract genome number from the file name
+            genome_number = int(file_name.split("genome")[1].split(".")[0])
+
+            # Check condition based on the extracted genome number
+            correct = non_zero and genome_number == int(non_zero[0][0][13:-1]) and float(non_zero[0][1]) > threshold
+
+    except FileNotFoundError:
+        print(f"File {file_name} not found.")
+        return None
+    print(file_name)
+    # return file_name, correct, non_zero
+    if non_zero:
+        return file_name, correct, non_zero[0]
+    else:
+        return file_name, correct
+
+
+# Example usage
+# for i in range(0, 101):
+#     print(read_tsv_file(f"genome{i}.tsv"))
+
+# Create a CSV file to write the results
+output_file = f"{sys.argv[1]}.csv"
+
+with open(output_file, mode='w', newline='') as csv_file:
+    fieldnames = ['File Name', 'Correct', 'Edit Homology Arm', 'Fractional Coverage']
+    writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
+
+    # Write the header
+    writer.writeheader()
+
+    # Write the data for each genome
+    print(f"sys-arg: {sys.argv[2]}")
+    for i in range(0, int(sys.argv[2])):
+        result = read_tsv_file(f"genome{i}.tsv")
+        if len(result) == 2:
+            writer.writerow({
+                'File Name': result[0][:-4],
+                'Correct': "False",
+                'Edit Homology Arm': "",
+                'Fractional Coverage': ""
+            })
+        else:
+            fractional_coverage = round(float(result[2][1]), 6)
+            writer.writerow({
+                'File Name': result[0][:-4],
+                'Correct': result[1],
+                'Edit Homology Arm': result[2][0],
+                'Fractional Coverage': fractional_coverage
+            })
+
+print(f"Results written to {output_file}")