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plot_graph.py
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plot_graph.py
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import os
import pandas as pd
import matplotlib.pyplot as plt
def save_graph():
print("============================================================================================")
# env_name = 'CartPole-v1'
# env_name = 'LunarLander-v2'
# env_name = 'BipedalWalker-v2'
env_name = 'RoboschoolWalker2d-v1'
fig_num = 0 #### change this to prevent overwriting figures in same env_name folder
plot_avg = True # plot average of all runs; else plot all runs separately
fig_width = 10
fig_height = 6
# smooth out rewards to get a smooth and a less smooth (var) plot lines
window_len_smooth = 20
min_window_len_smooth = 1
linewidth_smooth = 1.5
alpha_smooth = 1
window_len_var = 5
min_window_len_var = 1
linewidth_var = 2
alpha_var = 0.1
colors = ['red', 'blue', 'green', 'orange', 'purple', 'olive', 'brown', 'magenta', 'cyan', 'crimson','gray', 'black']
# make directory for saving figures
figures_dir = "PPO_figs"
if not os.path.exists(figures_dir):
os.makedirs(figures_dir)
# make environment directory for saving figures
figures_dir = figures_dir + '/' + env_name + '/'
if not os.path.exists(figures_dir):
os.makedirs(figures_dir)
fig_save_path = figures_dir + '/PPO_' + env_name + '_fig_' + str(fig_num) + '.png'
# get number of log files in directory
log_dir = "PPO_logs" + '/' + env_name + '/'
current_num_files = next(os.walk(log_dir))[2]
num_runs = len(current_num_files)
all_runs = []
for run_num in range(num_runs):
log_f_name = log_dir + '/PPO_' + env_name + "_log_" + str(run_num) + ".csv"
print("loading data from : " + log_f_name)
data = pd.read_csv(log_f_name)
data = pd.DataFrame(data)
print("data shape : ", data.shape)
all_runs.append(data)
print("--------------------------------------------------------------------------------------------")
ax = plt.gca()
if plot_avg:
# average all runs
df_concat = pd.concat(all_runs)
df_concat_groupby = df_concat.groupby(df_concat.index)
data_avg = df_concat_groupby.mean()
# smooth out rewards to get a smooth and a less smooth (var) plot lines
data_avg['reward_smooth'] = data_avg['reward'].rolling(window=window_len_smooth, win_type='triang', min_periods=min_window_len_smooth).mean()
data_avg['reward_var'] = data_avg['reward'].rolling(window=window_len_var, win_type='triang', min_periods=min_window_len_var).mean()
data_avg.plot(kind='line', x='timestep' , y='reward_smooth',ax=ax,color=colors[0], linewidth=linewidth_smooth, alpha=alpha_smooth)
data_avg.plot(kind='line', x='timestep' , y='reward_var',ax=ax,color=colors[0], linewidth=linewidth_var, alpha=alpha_var)
# keep only reward_smooth in the legend and rename it
handles, labels = ax.get_legend_handles_labels()
ax.legend([handles[0]], ["reward_avg_" + str(len(all_runs)) + "_runs"], loc=2)
else:
for i, run in enumerate(all_runs):
# smooth out rewards to get a smooth and a less smooth (var) plot lines
run['reward_smooth_' + str(i)] = run['reward'].rolling(window=window_len_smooth, win_type='triang', min_periods=min_window_len_smooth).mean()
run['reward_var_' + str(i)] = run['reward'].rolling(window=window_len_var, win_type='triang', min_periods=min_window_len_var).mean()
# plot the lines
run.plot(kind='line', x='timestep' , y='reward_smooth_' + str(i),ax=ax,color=colors[i % len(colors)], linewidth=linewidth_smooth, alpha=alpha_smooth)
run.plot(kind='line', x='timestep' , y='reward_var_' + str(i),ax=ax,color=colors[i % len(colors)], linewidth=linewidth_var, alpha=alpha_var)
# keep alternate elements (reward_smooth_i) in the legend
handles, labels = ax.get_legend_handles_labels()
new_handles = []
new_labels = []
for i in range(len(handles)):
if(i%2 == 0):
new_handles.append(handles[i])
new_labels.append(labels[i])
ax.legend(new_handles, new_labels, loc=2)
# ax.set_yticks(np.arange(0, 1800, 200))
# ax.set_xticks(np.arange(0, int(4e6), int(5e5)))
ax.grid(color='gray', linestyle='-', linewidth=1, alpha=0.2)
ax.set_xlabel("Timesteps", fontsize=12)
ax.set_ylabel("Rewards", fontsize=12)
plt.title(env_name, fontsize=14)
fig = plt.gcf()
fig.set_size_inches(fig_width, fig_height)
print("============================================================================================")
plt.savefig(fig_save_path)
print("figure saved at : ", fig_save_path)
print("============================================================================================")
plt.show()
if __name__ == '__main__':
save_graph()