Removing the stat method in tracking (#1169)

ersilia/core/tracking.py

@@ -349,45 +349,49 @@ def start_tracking(self):
  tracemalloc.start()
  self.memory_usage_start = tracemalloc.get_traced_memory()[0]
 
-
- def stats(self, result):
- """
- Stats function: calculates the basic statistics of the output file from a model. This includes the
- mode (if applicable), minimum, maximum, and standard deviation.
+
+
+# TODO: see the following link for more details
+# https://github.com/ersilia-os/ersilia/issues/1165?notification_referrer_id=NT_kwDOAsB0trQxMTEyNTc5MDIxNzo0NjE2NzIyMg#issuecomment-2178596998
+
+# def stats(self, result):
+# """
+# Stats function: calculates the basic statistics of the output file from a model. This includes the
+# mode (if applicable), minimum, maximum, and standard deviation.
 
- :param result: The path to the model's output file.
- :return: A dictionary containing the stats for each column of the result.
- """
+# :param result: The path to the model's output file.
+# :return: A dictionary containing the stats for each column of the result.
+# """
 
- data = read_csv(result)
+# data = read_csv(result)
 
  # drop first two columns (key, input)
- for row in data:
- row.pop('key', None)
- row.pop('input', None)
+# for row in data:
+# row.pop('key', None)
+# row.pop('input', None)
 
  # Convert data to a column-oriented format
- columns = defaultdict(list)
- for row in data:
- for key, value in row.items():
- columns[key].append(float(value))
+# columns = defaultdict(list)
+# for row in data:
+# for key, value in row.items():
+# columns[key].append(float(value))
 
  # Calculate statistics
- stats = {}
- for column, values in columns.items():
- column_stats = {}
- column_stats["mean"] = statistics.mean(values)
- try:
- column_stats["mode"] = statistics.mode(values)
- except statistics.StatisticsError:
- column_stats["mode"] = None
- column_stats["min"] = min(values)
- column_stats["max"] = max(values)
- column_stats["std"] = statistics.stdev(values) if len(values) > 1 else 0
-
- stats[column] = column_stats
-
- return stats
+# stats = {}
+# for column, values in columns.items():
+# column_stats = {}
+# column_stats["mean"] = statistics.mean(values)
+# try:
+# column_stats["mode"] = statistics.mode(values)
+# except statistics.StatisticsError:
+# column_stats["mode"] = None
+# column_stats["min"] = min(values)
+# column_stats["max"] = max(values)
+# column_stats["std"] = statistics.stdev(values) if len(values) > 1 else 0
+#
+# stats[column] = column_stats
+
+# return stats
 
 
  def get_file_sizes(self, input_file, output_file):
@@ -514,8 +518,6 @@ def track(self, input, result, meta):
  json_dict["nan_count"] = nan_count
 
  json_dict["check_types"] = self.check_types(result_data, meta["metadata"])
-
- json_dict["stats"] = self.stats(result)
 
  json_dict["file_sizes"] = self.get_file_sizes(input_data, result_data)