add filter of dirname

README.md

@@ -110,6 +110,7 @@ optional arguments:
 --xformat             x-axis format
 --xlim                x-axis limitation (default: None)
 --log_dir             log dir (default: ./)
+--filter              filter of dirname
 --filename            csv filename
 --show                show figure
 --save                save figure
@@ -125,6 +126,7 @@ finally, the learning curves looks like this:
 ## Features
 
 - [x] custom logger, style, key, label, interval, and so on ...
+- [x] filter of directory name
 - [x] multi-experiment plotter
 - [x] x-axis formatter features
 - [x] compatible with [OpenAI-baseline](https://github.com/openai/baselines) monitor data style

rl_plotter/plot_utils.py

@@ -138,7 +138,7 @@ def load_csv_results(dir, filename="monitor"):
 	#df.headers = headers # HACK to preserve backwards compatibility
 	return df
 
-def load_results(root_dir_or_dirs="./", filename="monitor"):
+def load_results(root_dir_or_dirs="./", filename="monitor", filter=""):
 
 	if isinstance(root_dir_or_dirs, str):
 		rootdirs = [osp.expanduser(root_dir_or_dirs)]
@@ -149,14 +149,15 @@ def load_results(root_dir_or_dirs="./", filename="monitor"):
 	for rootdir in rootdirs:
 		assert osp.exists(rootdir), "%s doesn't exist"%rootdir
 		for dirname, dirs, files in os.walk(rootdir):
-			result = {'dirname' : dirname, "data": None}
+			if filter in dirname:
+				result = {'dirname' : dirname, "data": None}
 
-			file_re = re.compile(r'(\d+\.)?(\d+\.)?' + filename + r'\.csv')
-			if any([f for f in files if file_re.match(f)]):
-				result['data'] = pandas.DataFrame(load_csv_results(dirname, filename))
+				file_re = re.compile(r'(\d+\.)?(\d+\.)?' + filename + r'\.csv')
+				if any([f for f in files if file_re.match(f)]):
+					result['data'] = pandas.DataFrame(load_csv_results(dirname, filename))
 
-			if result['data'] is not None:
-				allresults.append(result)
+				if result['data'] is not None:
+					allresults.append(result)
 	return allresults
 
 

rl_plotter/plotter.py

@@ -53,14 +53,16 @@ def main():
 	parser.add_argument('--time_interval', type=float, default=1,
 						help='parameters about time, x axis time interval (default: 1)')
 
-	parser.add_argument('--xformat', default='eng',
+	parser.add_argument('--xformat', default='',
 						help='x-axis format')
 	parser.add_argument('--xlim', type=int, default=None,
 						help='x-axis limitation (default: None)')
 
 	parser.add_argument('--log_dir', default='./',
 						help='log dir (default: ./)')
-	parser.add_argument('--filename', default='monitor',
+	parser.add_argument('--filter', default='',
+						help='filter of dirname')
+	parser.add_argument('--filename', default='evaluator',
 						help='csv filename')
 	parser.add_argument('--show', action='store_true',
 						help='show figure')
@@ -92,7 +94,7 @@ def main():
 		args.xkey = 'total_steps'
 		args.ykey = 'mean_score'
 
-	allresults = pu.load_results(args.log_dir, filename=args.filename)
+	allresults = pu.load_results(args.log_dir, filename=args.filename, filter=args.filter)
 	pu.plot_results(allresults,
 		fig_length=args.fig_length,
 		fig_width=args.fig_width,
@@ -125,7 +127,10 @@ def main():
 		elif args.xformat == 'log':
 			ax.xaxis.set_major_formatter(mticker.LogFormatter())
 		elif args.xformat == 'sci':
-			ax.xaxis.set_major_formatter(mticker.LogFormatterSciNotation())
+			#ax.xaxis.set_major_formatter(mticker.LogFormatterSciNotation())
+			plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0), useMathText=True)
+		else:
+			plt.ticklabel_format(style='sci', axis='x', scilimits=(0,0), useMathText=False)
 
 	if args.xlim is not None:
 		plt.xlim((0, args.xlim))

setup.py

@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="rl_plotter",
-    version="2.2.3",
+    version="2.2.4",
     author="Gong Xiaoyu",
     author_email="gxywy@hotmail.com",
     description="A plotter for reinforcement learning (RL)",