<jupyter_start><jupyter_text>Loads Data<jupyter_code>%%time
behav_data = loading.load_data_pandas(subjects, data_path)<jupyter_output>CPU times: user 12.7 s, sys: 1.34 s, total: 14 s
Wall time: 15.4 s<jupyter_text>plot performance over past two weeks in calendar<jupyter_code>for subj,data in behav_data.items():
    pc_fig = plotting.plot_filtered_performance_calendar(subj, data, num_days=20)<jupyter_output><empty_output><jupyter_text>Plot percent correct by block with confidence bounds<jupyter_code>for subj,df in behav_data.items():
    ci_acc_fig =  plotting.plot_ci_accuracy(subj, df)<jupyter_output><empty_output><jupyter_text>plot accuracy today<jupyter_code>for subj,df in behav_data.items():
    daily_acc_fig = plotting.plot_daily_accuracy(subj, df, x_axis='trial_num')<jupyter_output><empty_output><jupyter_text>Plot number of trials and feeds for past week<jupyter_code>trial_feeds_fig = plotting.plot_trial_feeds(behav_data)<jupyter_output><empty_output>
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