# Plot video digg_count cdf print("[Video digg_count cdf]") fig, ax = eval.draw_cdf(digg_count, x_label="counts", legend_label='like', style=styles[0], marker=markers[0]) fig, ax = eval.draw_cdf(comment_count, fig_ax=(fig, ax), x_label="counts", legend_label='comment', style=styles[1], marker=markers[1]) fig, ax = eval.draw_cdf(share_count, fig_ax=(fig, ax), x_label="counts", legend_label='share', style=styles[2], marker=markers[2]) fig.savefig('./eps/cdf/video_popularity_cdf' + TYPE) ''' # Plot video bit_rate pdf videos = own_videos bit_rate1 = (videos.bit_rate1/1000).tolist() bit_rate2 = (videos.bit_rate2.dropna()/1000).tolist() fig, ax = eval.draw_pdf(bit_rate1, y_label="bit rates (Mbps)", style=styles[0], legend_label='first bitrate') fig, ax = eval.draw_pdf(bit_rate2, fig_ax=(fig, ax), y_label="bit rates (Kbps)", style=styles[1], legend_label='second bitrate') fig.savefig('./eps/pdf/bit_rate_pdf' + TYPE) # Plot video bit_rate1 cdf print("[Video bit_rate cdf]") fig, ax = eval.draw_cdf(bit_rate1, x_label="bit rates (Mbps)", style=styles[0], marker=markers[0], legend_label='first bitrate') fig, ax = eval.draw_cdf(bit_rate2, fig_ax=(fig, ax), x_label="bit rates (Kbps)", style=styles[1], marker=markers[1], legend_label='second bitrate') fig.savefig('./eps/cdf/bit_rate_cdf' + TYPE) own_videos_no_2 = own_videos[own_videos.bit_rate2.isnull()] #print(own_videos_no_2.describe()) '''
else: total_num, valid_num, unique_num, gov_num = json.loads(log_file.readline()) print("*User Sample:") print("Total: %d, Valid: %d, Unique: %d, Government: %d" % (total_num, valid_num, unique_num, gov_num)) print(user_detail.describe()) # draw evaluation = Evaluation() if user_detail_file_name: # Plot follower count pdf followers = user_detail[user_detail.follower_count > 0][['follower_count', 'weight']] followers_gov = user_detail[(user_detail.is_gov_media_vip == 1) & (user_detail.follower_count > 0)][['follower_count', 'weight']] fig, ax = evaluation.draw_pdf(followers.follower_count, weights=followers.weight, fit_function='power_law', y_label="p(X)", x_label='# of followers', style=styles[1], marker=markers[1],legend_label='all', xmin=1) fig, ax = evaluation.draw_pdf(followers_gov.follower_count, weights=followers_gov.weight, fit_function='power_law', y_label="p(X)", x_label='# of followers', style=styles[2], marker=markers[2], legend_label='government', xmin=1, fig_ax=(fig, ax)) fig.savefig(os.path.join(draw_dir, 'pdf', 'followers_pdf'+TYPE)) # Plot follower count cdf followers = user_detail[['follower_count', 'weight']] followers_gov = user_detail[user_detail.is_gov_media_vip == 1][['follower_count', 'weight']] fig, ax = evaluation.draw_cdf(followers.follower_count, weights=followers.weight, y_label="CDF", x_label='# of followers', y_scale='linear', style=styles[1], marker=markers[1], legend_label='all') fig, ax = evaluation.draw_cdf(followers_gov.follower_count, weights=followers_gov.weight,