plot_metrics_multi: FINALLY write a script to generate charts for multiple models at the same time

aimodel/src/plot_metrics.py

@@ -58,7 +58,7 @@ Usage:
 	if os.path.isdir(FILEPATH_INPUT):
 		FILEPATH_INPUT = os.path.join(FILEPATH_INPUT, "metrics.tsv")
 	if not os.path.exists(FILEPATH_INPUT):
-		sys.stderr.write(f"Error: The input filepath at {FILEPATH_INPUT} either does not exist ro you don't have permission to read it.\n")
+		sys.stderr.write(f"Error: The input filepath at {FILEPATH_INPUT} either does not exist or you don't have permission to read it.\n")
 		sys.exit(1)
 	DIRPATH_OUTPUT = os.environ["OUTPUT"] if "OUTPUT" in os.environ else os.path.dirname(FILEPATH_INPUT)
 	

aimodel/src/plot_metrics_multi.py

@@ -0,0 +1,118 @@
+#!/usr/bin/env python3
+
+import sys
+import os
+import re
+import seaborn as sns
+import matplotlib.pyplot as plt
+import pandas as pd
+
+def do_regex(source, regex):
+	if regex is None or len(regex) == 0:
+		return source
+	
+	result = re.search(regex, source)
+	if not result:
+		return source
+	return result.group(0)
+
+def plot_metric(ax, train_list, val_list, metric_name, model_names, dir_output):
+	i = 0
+	for train in train_list:
+		ax.plot(train, label=model_names[i])
+		i += 1
+	i = 0
+	for val in val_list:
+		ax.plot(val, label=f"val_{model_names[i]}")
+		i += 1
+	
+	ax.set_title(metric_name)
+	ax.set_xlabel("epoch")
+	ax.set_ylabel(metric_name)
+	# plt.savefig(os.path.join(dir_output, f"{name}.png"))
+	# plt.close()
+
+def make_dfs(filepaths_input):
+	dfs = []
+	for filepath_input in filepaths_input:
+		print("DEBUG filepath_input", filepath_input)
+		dfs = pd.read_csv(filepath_input, sep="\t")
+
+def plot_metrics(filepaths_input, model_names, dirpath_output):
+	dfs = [ pd.read_csv(filepath_input, sep="\t") for filepath_input in filepaths_input ]
+
+	fig = plt.figure(figsize=(10,13))
+	for i, colname in enumerate(filter(lambda colname: colname != "epoch" and not colname.startswith("val_"), dfs[0].columns.values.tolist())):
+		train = [ df[colname] for df in dfs ]
+		val = [ df[f"val_{colname}"] for df in dfs ]
+		
+		colname_display = colname.replace("metric_dice_coefficient", "dice coefficient") \
+			.replace("one_hot_mean_iou", "mean iou")
+		
+		ax = fig.add_subplot(3, 2, i+1)
+		
+		plot_metric(ax, train, val, metric_name=colname_display, model_names=model_names, dir_output=dirpath_output)
+
+	# fig.tight_layout()
+	
+	# Ref https://stackoverflow.com/a/57484812/1460422
+	# lines_labels = [ ax.get_legend_handles_labels() for ax in fig.axes ]
+	lines_labels = [ fig.axes[0].get_legend_handles_labels() ]
+	lines, labels = [sum(lol, []) for lol in zip(*lines_labels) ]
+	fig.legend(lines, labels, loc='upper center', ncol=4)
+
+	target=os.path.join(dirpath_output, f"metrics.png")
+	plt.savefig(target)
+	
+	sys.stderr.write(">>> Saved to ")
+	sys.stdout.write(target)
+	sys.stderr.flush(); sys.stdout.flush()
+	sys.stderr.write("\n")
+
+
+if __name__ == "__main__":
+	if "--help" in sys.argv:
+		sys.stderr.write("""
+plot_metrics_multi.py: plot metrics for more than one metrics.tsv file
+
+It is assumed that all files have identical metrics in the same column order.
+
+The output file is named "metrics.png".
+
+Usage:
+	echo -e "filepathA\\nfilepathB..." | [OUTPUT="path/to/output_dir"] [REGEX_NAME=''] path/to/plot_metrics_multi.py
+""")
+		sys.exit()
+	
+	REGEX_NAME = os.environ["REGEX_NAME"] if "REGEX_NAME" in os.environ else None
+	if REGEX_NAME is None and len(sys.argv) >= 1:
+		REGEX_NAME = sys.argv[1]
+	FILEPATHS_INPUT = []
+	MODEL_NAMES = []
+	for line in sys.stdin:
+		filepath = line
+		if not os.path.exists(filepath):
+			filepath = filepath.strip()
+		if os.path.isdir(filepath):
+			filepath = os.path.join(filepath, "metrics.tsv")
+		if not os.path.exists(filepath):
+			sys.stderr.write(f"Warning: The input filepath at {filepath} either does not exist or you don't have permission to read it.\n")
+		
+		
+		FILEPATHS_INPUT.append(filepath)
+		
+		stem = os.path.basename(os.path.dirname(filepath))
+		MODEL_NAMES.append(do_regex(stem, REGEX_NAME) if REGEX_NAME is not None and len(REGEX_NAME) > 0 else stem)
+		
+	
+	
+	sys.stderr.write(">>> MAPPING:\n")
+	i = 0
+	for model_name in MODEL_NAMES:
+		sys.stderr.write(f"    {model_name} -- {FILEPATHS_INPUT[i]}\n")
+		i += 1
+	
+	DIRPATH_OUTPUT = os.environ["OUTPUT"] if "OUTPUT" in os.environ else os.getcwd()
+	
+	plot_metrics(FILEPATHS_INPUT, MODEL_NAMES, DIRPATH_OUTPUT)
+