87 lines
3.0 KiB
Python
87 lines
3.0 KiB
Python
import numpy as np
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import matplotlib
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matplotlib.use('TkAgg') # Can change to 'Agg' for non-interactive mode
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import matplotlib.pyplot as plt
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plt.rcParams['svg.fonttype'] = 'none'
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from baselines.bench.monitor import load_results
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X_TIMESTEPS = 'timesteps'
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X_EPISODES = 'episodes'
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X_WALLTIME = 'walltime_hrs'
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POSSIBLE_X_AXES = [X_TIMESTEPS, X_EPISODES, X_WALLTIME]
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EPISODES_WINDOW = 100
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COLORS = ['blue', 'green', 'red', 'cyan', 'magenta', 'yellow', 'black', 'purple', 'pink',
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'brown', 'orange', 'teal', 'coral', 'lightblue', 'lime', 'lavender', 'turquoise',
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'darkgreen', 'tan', 'salmon', 'gold', 'lightpurple', 'darkred', 'darkblue']
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def rolling_window(a, window):
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shape = a.shape[:-1] + (a.shape[-1] - window + 1, window)
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strides = a.strides + (a.strides[-1],)
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return np.lib.stride_tricks.as_strided(a, shape=shape, strides=strides)
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def window_func(x, y, window, func):
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yw = rolling_window(y, window)
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yw_func = func(yw, axis=-1)
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return x[window-1:], yw_func
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def ts2xy(ts, xaxis):
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if xaxis == X_TIMESTEPS:
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x = np.cumsum(ts.l.values)
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y = ts.r.values
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elif xaxis == X_EPISODES:
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x = np.arange(len(ts))
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y = ts.r.values
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elif xaxis == X_WALLTIME:
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x = ts.t.values / 3600.
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y = ts.r.values
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else:
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raise NotImplementedError
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return x, y
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def plot_curves(xy_list, xaxis, title):
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plt.figure(figsize=(8,2))
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maxx = max(xy[0][-1] for xy in xy_list)
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minx = 0
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for (i, (x, y)) in enumerate(xy_list):
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color = COLORS[i]
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plt.scatter(x, y, s=2)
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x, y_mean = window_func(x, y, EPISODES_WINDOW, np.mean) #So returns average of last EPISODE_WINDOW episodes
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plt.plot(x, y_mean, color=color)
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plt.xlim(minx, maxx)
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plt.title(title)
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plt.xlabel(xaxis)
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plt.ylabel("Episode Rewards")
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plt.tight_layout()
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def plot_results(dirs, num_timesteps, xaxis, task_name):
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tslist = []
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for dir in dirs:
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ts = load_results(dir)
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ts = ts[ts.l.cumsum() <= num_timesteps]
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tslist.append(ts)
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xy_list = [ts2xy(ts, xaxis) for ts in tslist]
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plot_curves(xy_list, xaxis, task_name)
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# Example usage in jupyter-notebook
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# from baselines import log_viewer
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# %matplotlib inline
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# log_viewer.plot_results(["./log"], 10e6, log_viewer.X_TIMESTEPS, "Breakout")
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# Here ./log is a directory containing the monitor.csv files
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def main():
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import argparse
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import os
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parser = argparse.ArgumentParser(formatter_class=argparse.ArgumentDefaultsHelpFormatter)
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parser.add_argument('--dirs', help='List of log directories', nargs = '*', default=['./log'])
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parser.add_argument('--num_timesteps', type=int, default=int(10e6))
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parser.add_argument('--xaxis', help = 'Varible on X-axis', default = X_TIMESTEPS)
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parser.add_argument('--task_name', help = 'Title of plot', default = 'Breakout')
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args = parser.parse_args()
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args.dirs = [os.path.abspath(dir) for dir in args.dirs]
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plot_results(args.dirs, args.num_timesteps, args.xaxis, args.task_name)
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plt.show()
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if __name__ == '__main__':
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main() |