allensdk.brain_observatory.drifting_gratings module¶
- class allensdk.brain_observatory.drifting_gratings.DriftingGratings(data_set, **kwargs)[source]¶
Bases:
StimulusAnalysis
Perform tuning analysis specific to drifting gratings stimulus.
- Parameters:
- data_set: BrainObservatoryNwbDataSet object
- get_peak()[source]¶
Computes metrics related to each cell’s peak response condition.
- Returns:
- Pandas data frame containing the following columns (_dg suffix is
- for drifting grating):
ori_dg (orientation)
tf_dg (temporal frequency)
reliability_dg
osi_dg (orientation selectivity index)
dsi_dg (direction selectivity index)
peak_dff_dg (peak dF/F)
ptest_dg
p_run_dg
run_modulation_dg
cv_dg (circular variance)
- get_response()[source]¶
Computes the mean response for each cell to each stimulus condition. Return is a (# orientations, # temporal frequencies, # cells, 3) np.ndarray. The final dimension contains the mean response to the condition (index 0), standard error of the mean of the response to the condition (index 1), and the number of trials with a significant response (p < 0.05) to that condition (index 2).
- Returns:
- Numpy array storing mean responses.
- property number_ori¶
- property number_tf¶
- property orivals¶
- plot_direction_selectivity(si_range=[0, 1.5], n_hist_bins=50, color='#ccccdd', p_value_max=0.05, peak_dff_min=3)[source]¶
- plot_orientation_selectivity(si_range=[0, 1.5], n_hist_bins=50, color='#ccccdd', p_value_max=0.05, peak_dff_min=3)[source]¶
- plot_preferred_direction(include_labels=False, si_range=[0, 1.5], color='#ccccdd', p_value_max=0.05, peak_dff_min=3)[source]¶
- plot_preferred_temporal_frequency(si_range=[0, 1.5], color='#ccccdd', p_value_max=0.05, peak_dff_min=3)[source]¶
- reshape_response_array()[source]¶
- Returns:
response array in cells x stim x repetition for noise
correlations
- property tfvals¶