Import of the watch repository from Pebble

tools/activity/plot_stats.py

@@ -0,0 +1,78 @@
+# Copyright 2024 Google LLC
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+""" Plot the stats contained in the .csv file generated by the test_kraepelin_algorithm
+unit test (when STATS_FILE_NAME is defined).
+"""
+
+import argparse
+import csv
+import datetime
+import json
+import logging
+import os
+import struct
+import sys
+import matplotlib.pyplot as pyplot
+
+
+##################################################################################################
+def plot_stats(args, rows, stat_name):
+    # Get the vmc and score for each of the stepping epochs
+    stepping_vmcs = []
+    stepping_scores = []
+    non_stepping_vmcs = []
+    non_stepping_scores = []
+    for row in rows:
+        if int(row['epoch_type']) == 0:
+            non_stepping_vmcs.append(int(row['vmc']))
+            non_stepping_scores.append(int(row[stat_name]))
+        elif int(row['epoch_type']) == 2:
+            stepping_vmcs.append(int(row['vmc']))
+            stepping_scores.append(int(row[stat_name]))
+
+    pyplot.plot(stepping_vmcs, stepping_scores, 'go',
+                non_stepping_vmcs, non_stepping_scores, 'ro')
+    pyplot.show()
+
+
+##################################################################################################
+if __name__ == '__main__':
+    # Collect our command line arguments
+    parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
+    parser.add_argument('infile', help="The input csv file")
+    parser.add_argument('--plot', choices=['score_0', 'score_lf', 'total'],
+                        default='score_0',
+                        help="Which metric to plot against vmc")
+    parser.add_argument('--debug', action='store_true', help="Turn on debug logging")
+    args = parser.parse_args()
+
+    level = logging.INFO
+    if args.debug:
+        level = logging.DEBUG
+    logging.basicConfig(level=level)
+
+    # Read in the csv file
+    col_names = None
+    rows = []
+    with open(args.infile, 'rb') as csvfile:
+        reader = csv.reader(csvfile)
+        for row in reader:
+            if reader.line_num == 1:
+                col_names = [x.strip() for x in row]
+            else:
+                rows.append(dict(zip(col_names, row)))
+
+    # Plot now
+    plot_stats(args, rows, args.plot)