Merge branch 'master' of https://github.com/lab11/socitrack

software/management/dashboard/1_convert_to_csv.py

@@ -0,0 +1,59 @@
+"""
+Function: This script finds all .pkl files in a specified directory, extracts the subject_id from the filename,
+loads the corresponding data, and processes it using the get_daily_ranging_statistics function.
+
+Usage:
+cd SociTrack/software/management/dashboard
+python3 1_tottags_batch.py
+"""
+
+import re
+import csv
+
+# Define input and output file paths
+input_file = "/Users/hannahpiersiak/Desktop/tottags/ranging_statistics.txt"
+output_file = "/Users/hannahpiersiak/Desktop/tottags/ranging_statistics.csv"
+
+# Open the input file and read its contents
+with open(input_file, "r") as file:
+    data = file.readlines()
+
+# Prepare data extraction
+csv_data = []
+current_date = None
+
+# Regex patterns to extract data
+date_pattern = re.compile(r"Ranging Statistics on (\d{2}/\d{2}/\d{4}):")
+stats_pattern = re.compile(r"Statistics to (r\.\d+_CG\d|Either of \[.*\]):")
+value_pattern = re.compile(r"^\s+(\w.+):\s+([\d.]+|nan)")
+
+# Parse the file line by line
+for line in data:
+    date_match = date_pattern.search(line)
+    stats_match = stats_pattern.search(line)
+    value_match = value_pattern.search(line)
+
+    if date_match:
+        current_date = date_match.group(1)  # Extract the date
+    elif stats_match:
+        current_target = stats_match.group(1)  # Extract the target (CG1, CG2, or Either)
+        minutes_range = minutes_touch = mean_distance = None
+    elif value_match:
+        key, value = value_match.groups()
+        if key == "Minutes in Range":
+            minutes_range = value
+        elif key == "Minutes in Touching Distance":
+            minutes_touch = value
+        elif key == "Mean Distance While in Range":
+            mean_distance = value
+            # Save row when all values for a section are collected
+            csv_data.append([current_date, current_target, minutes_range, minutes_touch, mean_distance])
+
+# Write to CSV file
+with open(output_file, "w", newline="") as file:
+    writer = csv.writer(file)
+    writer.writerow(["Date", "Target", "Minutes in Range", "Minutes in Touching Distance", "Mean Distance While in Range"])
+    writer.writerows(csv_data)
+
+print(f"CSV file saved: {output_file}")
+

software/management/dashboard/1_tottags_batch.py

@@ -0,0 +1,34 @@
+"""
+Function: This script finds all .pkl files in a specified directory, extracts the subject_id from the filename,
+loads the corresponding data, and processes it using the get_daily_ranging_statistics function.
+
+Usage:
+cd SociTrack/software/management/dashboard
+python3 1_tottags_batch.py
+"""
+
+import os
+from processing import *
+
+
+def process_pkl_files(directory):
+    """Find all .pkl files in the directory, extract subject_id, load data, and process it."""
+    for filename in os.listdir(directory):
+        if filename.endswith(".pkl"):
+            filepath = os.path.join(directory, filename)
+
+            # Extract subject_id from filename
+            subject_id = filename.split("_")[0]
+
+            # Load pkl data
+            TC = load_data(filepath)
+
+            # Call the function with formatted parameters
+            get_daily_ranging_statistics(TC, [f"{subject_id}_CG1", f"{subject_id}_CG2"], 3)
+
+
+# Define directory path
+directory_path = "/Users/hannahpiersiak/Desktop/tottags"
+
+# Run the function
+process_pkl_files(directory_path)