问题描述
每条红线代表刺激的开始时间,每条黑线代表刺激的结束时间,现在我想平均每个刺激出现后的反应。这是生成该图的代码:
experiment_id=795953296
neuro_id=1086493416
common_start_time=310
tmp_test__ =neural_data[((neural_data['ophys_experiment_id']==experiment_id)&(neural_data['cell_specimen_id']==neuro_id)&(neural_data['timestamps']>common_start_time))]
start_time_for_neural=tmp_test__['timestamps'].values[0]
stimulus_table_tmp = experiments[experiment_id].stimulus_presentations.drop(columns = ['image_set']) # dropping the 'image_set' column to avoid confusion. Image_set column contains a unique string for set of images presented in a session.
start_index_stimulus=stimulus_table_tmp[stimulus_table_tmp['start_time']>=start_time_for_neural-0.5].index[0]
for time in stimulus_table_tmp['start_time'].values[start_index_stimulus:start_index_stimulus+15]:
plt.axvline(x=time,ymin=0,ymax=1,color='r')
for time in stimulus_table_tmp['stop_time'].values[1:15]:
plt.axvline(x=time,color='k')
plt.plot(tmp_test__['timestamps'][0:300],tmp_test__['dff'][0:300])
plt.xlabel('Time(s)')
plt.ylabel('dff(s)')
plt.xlim((310,320))
plt.title('Novel level')
我试图通过我的逻辑通过制作循环和其他东西来获得平均值,但我无法做到。任何人都可以建议任何计算它的库,或者告诉我如何做?
解决方法
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