%load_ext autoreload
%autoreload 2

plot_2d_fit[source]

plot_2d_fit(sta, param_d, QI=None, fit_f=sum_of_2D_gaussian, imshow_args={'vmin': -1, 'vmax': 1, 'cmap': 'gray'})

2D STA plotting helper function to quickly check results.

params:

- sta: Frame fitted containing the 2D STA
- param_d: Parameter dictionary of the fit for fit_f
- fit_f: Function used for the fit
- imshow_args: Parameters for imshow

return:

- the two axes list

plot_tSTA_fit[source]

plot_tSTA_fit(sta, param_d, QI=None, fit_f=sum_of_gaussian, frame_rate=60, ax=None)

Helper function to visualize the temporal STA fit.

params:

- sta: STA of the cell`
- param_d: Parameter dictionary of the fit for fit_f
- QI: Quality index of the fit
- fit_f: Function used for the fit to plot
- ax: Axis where to plot the figure. If None, a new figure is created

return:

- The axis of the figure

plot_chirpam_fit[source]

plot_chirpam_fit(cell_mean, param_d, QI=None, fit_f=sinexp_sigm, start=420, stop=960, ax=None)

Helper function to visualize the fit of a cell response to a chirp_am stimulus.

params:

- cell_mean: Cell's mean response to the stimulus
- param_d: Parameter dictionary of the fit for fit_f
- QI: Quality index of the fit
- fit_f: Function used for the fit
- start: Where the fit started in index of cell_mean
- stop: Where the fit stopped in index of cell_mean
- ax: Axis where to plot the figure. If None, a new figure of size (50,2) is created

return:

- The axis of the figure

plot_chirp_freq_epoch_fit[source]

plot_chirp_freq_epoch_fit(cell_mean, param_d_l, fit_f=sin_exponent, QI_l=[None, None, None, None, None], freqs=[1.875, 3.75, 7.5, 15, 30], durations=[2, 2, 2, 1, 1], start=360, sampling_rate=60, ax=None)

Helper function to visualize the fit of a cell response to a chirp_freq_epoch stimulus.

params:

- cell_mean: Cell's mean response to the stimulus
- param_d_l: Parameters dictionary list of the fits for fit_f
- QI_l: Quality index list of the fits
- fit_f: Function used for the fit
- freqs: Frequency list of the epochs in Hz
- durations: Duration list of the epochs
- start: Where the fit started in index of cell_mean
- sampling_rate: Sampling rate of the response in Hz
- ax: Axis where to plot the figure. If None, a new figure of size (50,2) is created

return:

- The axis of the figure

plot_transient_fit[source]

plot_transient_fit(cell_mean, param_d, peak, start=0, stop=None, QI=None, fit_f=exponential_decay, sampling_rate=60, ax=None)

Helper function to visualize the transiency fit of a cell response to the ON-OFF stimulus.

params:

- cell_mean: Cell's mean response to the stimulus. start and stop parameters must correspond to where the fit was done in the given cell_mean
- param_d: Parameter dictionary of the fit for fit_f
- peak: Peak returned by `modelling.fit_transiency`, where the response decay begin
- start: Start position in cell_mean of the fitted cell_mean
- stop: Stop position in cell_mean of the fitted cell_mean. If None, it is set to len(cell_mean)
- QI: Quality index of the fit
- fit_f: Function used for the fit to plot
- sampling_rate: Sampling rate of the response in Hz
- ax: Axis where to plot the figure. If None, a new figure is created

return:

- The axis of the figure

plot_nonlinearity_fit[source]

plot_nonlinearity_fit(nonlinearity, param_d, QI=None, fit_f=sigmoid, ax=None)

Helper function to visualize the nonlinearity fit.

params:

- nonlinearity: Cell's nonlinearity computed by `processing.process_nonlinearity`
- param_d: Parameter dictionary of the fit for fit_f
- QI: Quality index of the fit
- fit_f: Function used for the fit to plot
- ax: Axis where to plot the figure. If None, a new figure is created

return:

- The axis of the figure

plot_ds_wheel[source]

plot_ds_wheel(ds_dict, cell_idx, ax=None, arrow_params={'width': 0.13, 'length_includes_head': True, 'lw': 2, 'zorder': 5, 'alpha': 0.5, 'edgecolor': 'black'})

Polar plot for direction and orientation response of a cell processed by processing.direction_selectivity.

params:

- ds_dict: The dictionary containing the cells DS and OS
- cell_idx: The index of the cell in the response
- ax: The axis for the plot. If None, a new plot is created
- arrow_params: Parameters for the arrow of the preferred orientation and direction (from the p_values)

return:

- The axis of the plot

plot_ds_wave_wheel[source]

plot_ds_wave_wheel(response_tuple, cell_idx, n_angle=10, ax=None, arrow_params={'width': 0.13, 'length_includes_head': True, 'lw': 2, 'zorder': 5, 'alpha': 0.5, 'edgecolor': 'black'}, moving_distance_th=1)

plot_fl_bars[source]

plot_fl_bars(sta, pval=None, ax=None, imshow_params={'cmap': 'gray', 'vmin': -1, 'vmax': 1, 'aspect': 'auto', 'interpolation': 'nearest'})

Plot the response to a 1D spatial stimulus like Flickering_bars.

params:

- sta: The STA to the 1D stimulus
- pval: p-value of the response (float)
- ax: The axis for the plot. If None, a new plot is created
- imshow_params: Parameters for the plotted image

return:

- The axis of the figure

plot_t_sta[source]

plot_t_sta(sta, pval=None, frame_rate=60, ax=None)

Plot the STA response of a cell to a fullfield stimulus.

params:

- sta: The t-STA of the cell
- pval: p-value of the response (float)
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_chirp[source]

plot_chirp(stim_inten, spike_bins, smooth=True, n_repeats=None, frame_rate=60, ax=None)

Plot the response to a chirp stimulus (but could be any repeated stimulus, non-shuffled). The response is plotted with seaborn's lineplot.

params:

- stim_inten: The whole stimulus intensity
- spike_bins: The cell's response to the whole stimulus
- n_repeats: Number of stimulus repetitions. If None, it will try to guess it.
- smooth: Flag to smooth or not the cell's response
- frame_rate: Frame rate of the stimulus
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_spike_template[source]

plot_spike_template(cluster_composition, phy_dict, shanks_idx, ax=None)

Plot the spike template obtained with phy for a silicone probe.

params:

- cluster_composition: List of phy format clusters corresponding to that cell
- phy_dict: Phy result dictionnary
- shanks_idx: Idx of shanks for the channels obtained with `utils.get_shank_channels`
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_spike_template_kilo[source]

plot_spike_template_kilo(cluster_composition, phy_dict, shanks_idx, multiplication_factor_spike_template, ax=None)

Plot the spike template obtained with phy for a silicone probe.

params:

- cluster_composition: List of phy format clusters corresponding to that cell
- phy_dict: Phy result dictionnary
- shanks_idx: Idx of shanks for the channels obtained with `utils.get_shank_channels`
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_spike_template_MEA[source]

plot_spike_template_MEA(cluster_composition, templates, channel_positions, ax=None)

Plot the spike template obtained with phy for a micro electrode array.

params:

- cluster_composition: List of phy format clusters corresponding to that cell
- templates: All templates of phy format
- channel_positions: Positions of the channels by idx from phy format
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_autocorrelogram[source]

plot_autocorrelogram(cluster, spike_times, spike_clusters, bin_ms=0.001, sampling_rate=30000, tails=30, ax=None)

Plot the cell's response autocorrelogram

params:

- cluster: Cluster id of the cell
- spike_times: Times of all spikes in phy format
- spike_clusters: cluster associated to the spikes in phy format
- bin_ms: Size of the autocorrelogram bin in ms
- sampling_rate: Sampling rate of the electrophysiology
- tails: Size of the tails for the autocorrelogram
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_spike_amplitudes[source]

plot_spike_amplitudes(cluster, spike_templates, spike_clusters, spike_times, amplitudes, n_max_dots=5000, ax=None)

Plot a subset of all spikes amplitudes of a cell.

params:

- cluster: Cluster id of the cell
- spike_templates: Original templates id in phy format
- spike_times: Times of all spikes in phy format
- spike_clusters: cluster associated to the spikes in phy format
- amplitudes: Spike amplitudes in phy format
- n_max_dots: Max limit for the number of spikes to not overload the plot
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_spike_amplitudes_kilo[source]

plot_spike_amplitudes_kilo(reM, cluster, spike_templates, spike_clusters, spike_times, amplitudes, n_max_dots=10000, ax=None)

Plot a subset of all spikes amplitudes of a cell.

params:

- cluster: Cluster id of the cell
- spike_templates: Original templates id in phy format
- spike_times: Times of all spikes in phy format
- spike_clusters: cluster associated to the spikes in phy format
- amplitudes: Spike amplitudes in phy format
- n_max_dots: Max limit for the number of spikes to not overload the plot
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_calcium_trace[source]

plot_calcium_trace(cell_trace, ax=None)

Plot the calcium trace of a cell.

params:

- cell_trace: Calcium trace of a cell
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_stim_epochs_to_ephy[source]

plot_stim_epochs_to_ephy(reM, y_pos, ax=None)

Add the stimulus epochs to a spike response of a cell.

params:

- reM: The Record_Master containing the synchronized stimuli
- y_pos: The y position of the stimuli
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_stim_epochs_to_calcium[source]

plot_stim_epochs_to_calcium(reM, y_pos, ax=None)

Add the stimulus epochs to a calcium response of a cell.

params:

- reM: The Record_Master containing the synchronized stimuli
- y_pos: The y position of the stimuli
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_cell_spatial[source]

plot_cell_spatial(cell_spatial, ax=None)

Plot the cell spatial mask obtained with CaImAn.

params:

- cell_spatial: The 2D image of the cell
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_stim_recap_table[source]

plot_stim_recap_table(df, ax=None)

Plot the recap table obtained with utils.stim_recap_df

params:

- df: the dataframe of the stim recap
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_composed_A_masks[source]

plot_composed_A_masks(A_matrix, shape=None, ax=None)

Plot in a single image the spatial mask of all cell of a record, obtained with CaImAn.

params:

- A_matrix: the A matrix given by CaImAn (h*w, n_cell) or the 2D reshaped A_matrix (n_cell, h, w)
- ax: The axis for the plot. If None, a new plot is created
- shape: Shape of a single cell image if A_matrix is native, e.g. (256, 256). If None, it assumes it's a square and tries to guess the shape.

return:

- The axis of the plot

plot_sta_positions[source]

plot_sta_positions(stas, ax=None)

Plot in a single image all 2D STAs of a single record. The STA are fitted with a gaussian, and plotted as ellipses.

params:

- stas: All STAs of the cells of shape (n_cell, t, height, width)
- ax: The axis for the plot. If None, a new plot is created

return:

- The axis of the plot

plot_2d_sta[source]

plot_2d_sta(sta, gs=None, pval=None, title='Checkerboard')

Plot a single 2D STA or an iterable of 2D STAs

params:

- sta: Array of shape (h, w) or of shape (n_sta, h, w)
- gs: GridSpec for the plotting. If None, defined automatically
- pval: Minimal p-value of the whole
- title: Title to give to the GridSpec

return:

- the GridSpec

plt.figure()
to_plot = np.random.rand(24,10,32)*2-1
gs = plot_2d_sta(to_plot, gs=gridspec.GridSpec(6, 4), pval=0.008)

plot_dome_flat[source]

plot_dome_flat(sph_pos, ax=None, **scatter_args)

Plot the dome LED as flat.

params:

- sph_pos: Spherical coordinates of the LED (e.g. obtained with `leddome.get_dome_positions`)
- ax: The axis for the plot. Needs to be polar projection. If None, a new plot is created
- scatter_args: Args for the scatter plot, such as the dots individual colors

return:

- The axis of the plot

plot_dome_checker[source]

plot_dome_checker(sta, s=20, gs=None, pval=None, title='Checkerboard', led_position='default')

Plot a single 2D STA or an iterable of 2D STAs for the LED dome

params:

- sta: Array of shape (h, w) or of shape (n_sta, h, w)
- s: The dot size
- gs: GridSpec for the plotting. If None, defined automatically
- pval: Minimal p-value of the whole
- title: Title to give to the GridSpec
- led_position: Led position to plot, in shape (4,237,3)

return:

- the GridSpec

plot_omitted_response[source]

plot_omitted_response(response_d_ON, response_d_OFF, cell_idx, n_fr_cycle=8, gs=None)

Plotting of the averaged response to omitted stimuli (ON & OFF).

params:

- response_d_ON: Dictionnary of the response to ON omitted stimuli (from utils.group_omitted_epochs)
- response_d_OFF: Dictionnary of the response to OFF omitted stimuli
- cell_idx: index of the cell to plot
- n_fr_cycle: Number of frame of (flash + interval between flashes)
- gs: Gridspec where to plot the ON and OFF responses. Should have len == 2

return:

- the GridSpec

plot_sta_pixelcorr[source]

plot_sta_pixelcorr(sta, stim_name=None, ax_corr=None, ax_hist=None)

Plot the correlation matrix between the sta's pixels, and their value distribution with a histogram.

return:

- The axis of the two plots, (ax_corr, ax_hist)

plot_svd[source]

plot_svd(sta, ax=None)

Plot a histogram of the singular value decomposition of an STA. params:

- sta: The STA to decompose

return:

- The axis of the figure

plot_nonlin[source]

plot_nonlin(nonlinearity, bins, label=None, ax=None)

Plot a nonlinearity with the bins that were used (in L2 norm) params:

- nonlinearity: The nonlinearity to plot
- bins: Bins used by [`process_nonlinearity`](/theonerig/processing.html#process_nonlinearity) to make that nonlinearity
- label: Label of this trace
- ax: Axis where to plot the figure. If None, a new figure is created

return:

- The axis of the figure

plot_crosscorr_spikes_behav[source]

plot_crosscorr_spikes_behav(behav, corr_behav_lag, p_value_peak, offset_peak, null_dist_behav, fps=60, seconds=30, color_line='black', title='visual stim', ax=None)

Cross-correlation with lag plotting helper function.

params:

- behav: String with name of behavioral signal to be analysed
- corr_behav_lag: Array of values of the cross-correlation between behavioral signal and spiking signal (output of 'utils.cross_corr_with_lag')
- p_value_peak: P-value of the peak correlation between behavioral signal and spiking signal (output of 'utils.cross_corr_with_lag')
- offset_peak: Offset value in seconds of the peak correlation value from the centered correlation value (output of 'utils.cross_corr_with_lag')
- null_dist_behav: Null distribution of correlation values (output of 'utils.cross_corr_with_lag')
- fps: Sampling rate
- seconds: Window in seconds of the correlation lag
- color_line: Color of plotted line
- title: Title of the plot
- ax: The axis for the plot

return:

- The axis of the figure

configure_pyplot_recap[source]

configure_pyplot_recap(small_size=14, medium_size=18, bigger_size=24)

Set the fontsize and other style of matplotlib and seaborn for the recap plots. Call sns.set() and plt.rcdefaults() to restore defaults parameters.

plot_recap_vivo_ephy[source]

plot_recap_vivo_ephy(title_dict, reM, phy_dict, cluster_ids, df_stim, cell_db_ids=None, checkerboard=None, fullfield_fl=None, fl_bars=None, chirp_am=None, chirp_fm=None, moving_gratings=None, water=None, export_path='./recap_plot.pdf', show_time=True)

Plot the recap pdf of in vivo electrophy records.

params:

- title_dict: A dictionnary containing the str info for the title: keys(condition, date, record_name, record_id)
- reM: The record master object of the record
- phy_dict: A dictionnary containing the results from phy (see utils.phy_results_dict())
- cluster_ids: A list of the cluster id used by phy, to plot. Usually the cells classified as good.
- df_stim: Stimulus dataframe recap of their syncronisation obtained with `utils.stim_recap_df`
- cell_db_ids: A list of the database ids of the cells corresponding to cluster_ids.
- checkerboard: A matrix of STA of cells to the checkerboard stimulus of shape (n_cell, 16, height, width)
- fullfield_fl: A matrix of STA of cells to the fullfield_flicker stimulus of shape (n_cell, 16)
- fl_bars: A matrix of STA of cells to the flickering_bars stimulus of shape (n_cell, 16, height, width)
- chirp_am: A tuple of the chirp_am obtained from a pipe, where [0] is the stimulus and [1] the cells response
- chirp_fm: Same as chirp_am but for a chirp_fm stimulus
- moving_gratings: The dict of response obtained from `utils.group_direction_response`
- water: A matrix of STA of cells to the water stimulus of shape (n_cell, 16, height, width)
- export_path: The path for a pdf file to be exported. If None, the plot is displayed.

plot_recap_vivo_ephy_kilo[source]

plot_recap_vivo_ephy_kilo(title_dict, reM, phy_dict, cluster_ids, df_stim, cell_db_ids=None, checkerboard=None, fullfield_fl=None, fl_bars=None, chirp_am=None, chirp_fm=None, moving_gratings=None, water=None, export_path='./recap_plot.pdf')

Plot the recap pdf of in vivo electrophy records for spike sorting run with Kilosort2.

params:

- title_dict: A dictionnary containing the str info for the title: keys(condition, date, record_name, record_id)
- reM: The record master object of the record
- phy_dict: A dictionnary containing the results from phy (see utils.phy_results_dict())
- cluster_ids: A list of the cluster id used by phy, to plot. Usually the cells classified as good.
- df_stim: Stimulus dataframe recap of their syncronisation obtained with `utils.stim_recap_df`
- cell_db_ids: A list of the database ids of the cells corresponding to cluster_ids.
- checkerboard: A matrix of STA of cells to the checkerboard stimulus of shape (n_cell, 16, height, width)
- fullfield_fl: A matrix of STA of cells to the fullfield_flicker stimulus of shape (n_cell, 16)
- fl_bars: A matrix of STA of cells to the flickering_bars stimulus of shape (n_cell, 16, height, width)
- chirp_am: A tuple of the chirp_am obtained from a pipe, where [0] is the stimulus and [1] the cells response
- chirp_fm: Same as chirp_am but for a chirp_fm stimulus
- moving_gratings: The dict of response obtained from `utils.group_direction_response`
- water: A matrix of STA of cells to the water stimulus of shape (n_cell, 16, height, width)
- export_path: The path for a pdf file to be exported. If None, the plot is displayed.

plot_recap_vivo_calcium[source]

plot_recap_vivo_calcium(title_dict, reM, A_matrix, cell_traces, df_stim, cell_indexes=None, cell_db_ids=None, checkerboard=None, fullfield_fl=None, fl_bars=None, chirp_am=None, chirp_fm=None, moving_gratings=None, water=None, export_path='./recap_plot.pdf')

Plot the recap pdf of in vivo calcium records.

params:

- title_dict: A dictionnary containing the str info for the title: keys(condition, date, record_name, record_id)
- reM: The record master object of the record
- A_matrix: A matrix of the cell spatial components obtained from CaImAn
- cell_traces: Cells raw traces (C or S_matrix from CaImAn)
- df_stim: Stimulus dataframe recap of their syncronisation obtained with `utils.stim_recap_df`
- cell_indexes: A list of the indexes of the cell to plot. Leave to None for plotting all of them.
- cell_db_ids: A list of the database ids of the cells corresponding to cluster_ids.
- checkerboard: A matrix of STA of cells to the checkerboard stimulus of shape (n_cell, 64, height, width)
- fullfield_fl: A matrix of STA of cells to the fullfield_flicker stimulus of shape (n_cell, 64)
- chirp_am: A tuple of the chirp_am obtained from a pipe, where [0] is the stimulus and [1] the cells response
- chirp_fm: Same as chirp_am but for a chirp_fm stimulus
- moving_gratings: The dict of response obtained from `utils.group_direction_response`
- water: A matrix of STA of cells to the water stimulus of shape (n_cell, 16, height, width)
- export_path: The path for a pdf file to be exported. If None, the plot is displayed.

plot_recap_vitro_ephy[source]

plot_recap_vitro_ephy(title_dict, reM, phy_dict, cluster_ids, df_stim, cell_db_ids=None, checkerboard=None, fullfield_fl=None, fl_bars=None, chirp_am=None, chirp_fm=None, moving_gratings=None, export_path='./recap_plot.pdf')

Plot the recap pdf of in vitro electrophy records.

params:

- title_dict: A dictionnary containing the str info for the title: keys(condition, date, record_name, record_id)
- reM: The record master object of the record
- phy_dict: A dictionnary containing the results from phy (see utils.phy_results_dict())
- cluster_ids: A list of the cluster id used by phy, to plot. Usually the cells classified as good.
- df_stim: Stimulus dataframe recap of their syncronisation obtained with `utils.stim_recap_df`
- cell_db_ids: A list of the database ids of the cells corresponding to cluster_ids.
- checkerboard: A matrix of STA of cells to the checkerboard stimulus of shape (n_cell, 16, height, width)
- fullfield_fl: A matrix of STA of cells to the fullfield_flicker stimulus of shape (n_cell, 16)
- fl_bars: A matrix of STA of cells to the flickering_bars stimulus of shape (n_cell, 16, height, width)
- chirp_am: A tuple of the chirp_am obtained from a pipe, where [0] is the stimulus and [1] the cells response
- chirp_fm: Same as chirp_am but for a chirp_fm stimulus
- moving_gratings: The dict of response obtained from `utils.group_direction_response`
- export_path: The path for a pdf file to be exported. If None, the plot is displayed.

plot_recap_vivo_ephy_dome[source]

plot_recap_vivo_ephy_dome(title_dict, reM, phy_dict, cluster_ids, cell_db_ids=None, checkerboard=None, fullfield_fl_100Hz=None, fullfield_fl_200Hz=None, chirp_fm=None, wave=None, export_path='./recap_plot.pdf')

Plot the recap pdf of in vivo electrophy records with the LED dome as stimuluation device.

params:

- title_dict: A dictionnary containing the str info for the title: keys(condition, date, record_name, record_id)
- reM: The record master object of the record
- phy_dict: A dictionnary containing the results from phy (see utils.phy_results_dict())
- cluster_ids: A list of the cluster id used by phy, to plot. Usually the cells classified as good.
- df_stim: Stimulus dataframe recap of their syncronisation obtained with `utils.stim_recap_df`
- cell_db_ids: A list of the database ids of the cells corresponding to cluster_ids.
- checkerboard: A matrix of STA of cells to the checkerboard stimulus of shape (n_cell, Hw>=8, height, width)
- fullfield_fl_100Hz: A matrix of STA of cells to the fullfield_flicker at 100Hz stimulus of shape (n_cell, Hw)
- fullfield_fl_200Hz: A matrix of STA of cells to the fullfield_flicker at 200Hz stimulus of shape (n_cell, Hw)
- chirp_fm: A tuple of the chirp_fm obtained from a pipe, where [0] is the stimulus and [1] the cells response
- wave: The dict of response obtained from `utils.wave_direction_selectivity`
- export_path: The path for a pdf file to be exported. If None, the plot is displayed.

plot_recap_vivo_ephy_corr_behav[source]

plot_recap_vivo_ephy_corr_behav(title_dict, reM, phy_dict, cluster_ids, df_stim, behavs, conversion_factor_treadmill=6.25, removeslowdrifts=True, cell_db_ids=None, checkerboard=None, fullfield_fl=None, fl_bars=None, chirp_am=None, chirp_fm=None, moving_gratings=None, water=None, export_path='./recap_plot_corr_behav.pdf')

Plot the recap pdf of in vivo electrophy records.

params:

- title_dict: A dictionary containing the str info for the title: keys(condition, date, record_name, record_id)
- reM: The record master object of the record
- phy_dict: A dictionary containing the results from phy (see utils.phy_results_dict())
- cluster_ids: A list of the cluster id used by phy, to plot. Usually the cells classified as good.
- df_stim: Stimulus dataframe recap of their syncronisation obtained with `utils.stim_recap_df`
- behavs: A list with behavioral signal names from reM to plot the correlation with spiking signal
- conversion_factor_treadmill: The value to convert the treadmill signal into cm/s
- removeslowdrifts: Boolean:
        False - does not remove slow drifts from the signal, for the correlation analysis;
        True - removes slow drifts by extracting a specified percentile within moving window from the signal, for the correlation analysis.
- cell_db_ids: A list of the database ids of the cells corresponding to cluster_ids.
- checkerboard: A matrix of STA of cells to the checkerboard stimulus of shape (n_cell, 16, height, width)
- fullfield_fl: A matrix of STA of cells to the fullfield_flicker stimulus of shape (n_cell, 16)
- fl_bars: A matrix of STA of cells to the flickering_bars stimulus of shape (n_cell, 16, height, width)
- chirp_am: A tuple of the chirp_am obtained from a pipe, where [0] is the stimulus and [1] the cells response
- chirp_fm: Same as chirp_am but for a chirp_fm stimulus
- moving_gratings: The dict of response obtained from `utils.group_direction_response`
- water: A matrix of STA of cells to the water stimulus of shape (n_cell, 16, height, width)
- export_path: The path for a pdf file to be exported. If None, the plot is displayed.

plot_recap_wholeField[source]

plot_recap_wholeField(title_dict, reM, phy_dict, cluster_ids, df_stim, cell_db_ids=None, checkerboard=None, fullfield_fl=None, chirp_am=None, nonlin_fff=None, nonlin_chk=None, chirp_fm=None, water=None, export_path='./wholefield_recap_plot.pdf')

Plot the recap pdf of cells for wholefieldness evaluation

params:

plot_recap_wholeField_dome[source]

plot_recap_wholeField_dome(title_dict, reM, phy_dict, cluster_ids, cell_db_ids=None, checkerboard=None, fullfield_fl=None, chirp_am=None, nonlin_fff=None, nonlin_chk=None, chirp_fm=None, water=None, export_path='./wholefield_recap_plot.pdf')

Plot the recap pdf of cells for wholefieldness evaluation (with LED dome)

params:

plot_recap_wholeField_vitroHiroki[source]

plot_recap_wholeField_vitroHiroki(title_dict, cells_idxs, checkerboard=None, nonlin_chk=None, export_path='./wholefield_recap_plot.pdf')

Plot the recap pdf of vitroHirokiChecker cells for wholefieldness evaluation

params:

- title_dict: A dictionnary containing the str info for the title: keys(condition, date, record_name, record_id)
- cells_idx: A list of the cells index to plot
- checkerboard: A matrix of STA of cells to the checkerboard stimulus of shape (n_cell, 16, height, width)
- export_path: The path for a pdf file to be exported. If None, the plot is displayed.