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Add possibility of plotting timesteps vs episodes (#578)

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* Add possibility of plotting timesteps vs episodes

* Remove leftover from personal project patch

* Auto plt.tight_layout() on resize window event

Calls `plt.tight_layout()` if a `resize_event` is issued.
This means that the plot will look good even after the user has resized the plotting window.
This commit is contained in:
Alfredo Canziani
2018-09-19 12:43:45 -04:00
committed by pzhokhov
parent 115b59d28b
commit 85be74500d
1 changed files with 18 additions and 10 deletions
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28
baselines/results_plotter.py
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@@ -10,6 +10,8 @@ from baselines.bench.monitor import load_results
X_TIMESTEPS = 'timesteps'
X_EPISODES = 'episodes'
X_WALLTIME = 'walltime_hrs'
Y_REWARD = 'reward'
Y_TIMESTEPS = 'timesteps'
POSSIBLE_X_AXES = [X_TIMESTEPS, X_EPISODES, X_WALLTIME]
EPISODES_WINDOW = 100
COLORS = ['blue', 'green', 'red', 'cyan', 'magenta', 'yellow', 'black', 'purple', 'pink',
@@ -26,22 +28,25 @@ def window_func(x, y, window, func):
yw_func = func(yw, axis=-1)
return x[window-1:], yw_func
def ts2xy(ts, xaxis):
def ts2xy(ts, xaxis, yaxis):
if xaxis == X_TIMESTEPS:
x = np.cumsum(ts.l.values)
y = ts.r.values
elif xaxis == X_EPISODES:
x = np.arange(len(ts))
y = ts.r.values
elif xaxis == X_WALLTIME:
x = ts.t.values / 3600.
else:
raise NotImplementedError
if yaxis == Y_REWARD:
y = ts.r.values
elif yaxis == Y_TIMESTEPS:
y = ts.l.values
else:
raise NotImplementedError
return x, y
def plot_curves(xy_list, xaxis, title):
plt.figure(figsize=(8,2))
def plot_curves(xy_list, xaxis, yaxis, title):
fig = plt.figure(figsize=(8,2))
maxx = max(xy[0][-1] for xy in xy_list)
minx = 0
for (i, (x, y)) in enumerate(xy_list):
@@ -52,17 +57,19 @@ def plot_curves(xy_list, xaxis, title):
plt.xlim(minx, maxx)
plt.title(title)
plt.xlabel(xaxis)
plt.ylabel("Episode Rewards")
plt.ylabel(yaxis)
plt.tight_layout()
fig.canvas.mpl_connect('resize_event', lambda event: plt.tight_layout())
plt.grid(True)
def plot_results(dirs, num_timesteps, xaxis, task_name):
def plot_results(dirs, num_timesteps, xaxis, yaxis, task_name):
tslist = []
for dir in dirs:
ts = load_results(dir)
ts = ts[ts.l.cumsum() <= num_timesteps]
tslist.append(ts)
xy_list = [ts2xy(ts, xaxis) for ts in tslist]
plot_curves(xy_list, xaxis, task_name)
xy_list = [ts2xy(ts, xaxis, yaxis) for ts in tslist]
plot_curves(xy_list, xaxis, yaxis, task_name)
# Example usage in jupyter-notebook
# from baselines import log_viewer
@@ -77,10 +84,11 @@ def main():
parser.add_argument('--dirs', help='List of log directories', nargs = '*', default=['./log'])
parser.add_argument('--num_timesteps', type=int, default=int(10e6))
parser.add_argument('--xaxis', help = 'Varible on X-axis', default = X_TIMESTEPS)
parser.add_argument('--yaxis', help = 'Varible on Y-axis', default = Y_REWARD)
parser.add_argument('--task_name', help = 'Title of plot', default = 'Breakout')
args = parser.parse_args()
args.dirs = [os.path.abspath(dir) for dir in args.dirs]
plot_results(args.dirs, args.num_timesteps, args.xaxis, args.task_name)
plot_results(args.dirs, args.num_timesteps, args.xaxis, args.yaxis, args.task_name)
plt.show()
if __name__ == '__main__':