def save_acuity_direction(units, stimulus_list, c_unit_fig, c_add_retina_figure): "Make one direction plot per speed" get_direction = glia.compose( glia.f_create_experiments(stimulus_list), glia.f_has_stimulus_type(["BAR"]), partial(filter, lambda x: x["stimulus"]["barColor"] == "white"), partial(sorted, key=lambda e: e["stimulus"]["angle"]), partial(glia.group_by, key=lambda x: x["stimulus"]["speed"], value=lambda x: x)) response = glia.apply_pipeline(get_direction, units, progress=True) speeds = list(glia.get_unit(response)[1].keys()) nspeeds = len(speeds) for speed in sorted(speeds): print("Plotting DS for speed {}".format(speed)) plot_function = partial(plot_unit_response_for_speed, speed=speed) filename = "direction-{}".format(speed) glia.plot_units( plot_function, partial(c_unit_fig, filename), response, subplot_kw={"projection": "polar"}, ax_xsize=7, ax_ysize=7, figure_title="Units spike train for speed {}".format(speed), transpose=True)
def sta_cmd(units, stimulus_list, metadata, c_unit_fig, c_retina_fig, frame_log, video_file): binary_noise_frame_idx = video.get_binary_noise_frame_idx( stimulus_list, frame_log) # # single unit # row_to_id = {} # for i,key in enumerate(units.keys()): # row_to_id[i] = key # # spikes = units[key].spike_train[units[key].spike_train<9] # unit_id = row_to_id[37] # print("unit_id", unit_id) # spike_train = units[unit_id].spike_train # sta = video.calc_sta(spike_train, binary_noise_frame_idx, frame_log, # video_file) # fig = video.plot_sta(sta) plot_func = partial(video.sta_unit_plot_function, frame_indices=binary_noise_frame_idx, frame_log=frame_log, video_file=video_file, nsamples_before=25) gs = gridspec.GridSpec(2, 1, height_ratios=[3, 1]) glia.plot_units(plot_func, partial(c_unit_fig, "spatial_filter"), units, nplots=2, ncols=1, GridSpec=gs)
def save_acuity_chart(units, stimulus_list, c_unit_fig, c_add_retina_figure, prepend, append): "Compare SOLID light wedge to BAR response in corresponding ascending width." print("Creating acuity chart v3.") get_solids = glia.compose( glia.f_create_experiments(stimulus_list, prepend_start_time=prepend, append_lifespan=append), glia.f_has_stimulus_type(["SOLID"]), ) solids = glia.apply_pipeline(get_solids, units, progress=True) # offset to avoid diamond pixel artifacts get_bars_by_speed = glia.compose( glia.f_create_experiments(stimulus_list), glia.f_has_stimulus_type(["BAR"]), partial(sorted, key=lambda x: x["stimulus"]["angle"]), partial(sorted, key=lambda x: x["stimulus"]["width"]), partial(glia.group_by, key=lambda x: x["stimulus"]["speed"])) bars_by_speed = glia.apply_pipeline(get_bars_by_speed, units, progress=True) speeds = list(glia.get_unit(bars_by_speed)[1].keys()) for speed in sorted(speeds): print("Plotting acuity for speed {}".format(speed)) plot_function = partial(plot_acuity_v3, prepend=prepend, append=append, speed=speed) filename = "acuity-{}".format(speed) result = glia.plot_units( plot_function, partial(c_unit_fig, filename), solids, bars_by_speed, nplots=1, ncols=1, ax_xsize=5, ax_ysize=15, figure_title="Bars with speed {}".format(speed)) plot_function = partial(plot_dissimilarity, prepend=prepend, append=append, speed=speed) filename = "dissimilarity-{}".format(speed) result = glia.plot_units( plot_function, partial(c_unit_fig, filename), solids, bars_by_speed, nplots=1, ncols=1, ax_xsize=7, ax_ysize=7, figure_title="Dissimilarity matrix for bars with speed {}".format( speed))
def save_integrity_chart(units, stimulus_list, c_unit_fig, c_add_retina_figure): print("Creating integrity chart") get_solid = glia.compose( glia.f_create_experiments(stimulus_list,prepend_start_time=1,append_lifespan=2), glia.f_has_stimulus_type(["SOLID"]), filter_lifespan ) response = glia.apply_pipeline(get_solid,units, progress=True) plot_function = partial(plot_spike_trains,prepend_start_time=1,append_lifespan=2) glia.plot_units(plot_function,c_unit_fig,response,ncols=1,ax_xsize=10, ax_ysize=5, figure_title="Integrity Test (5 Minute Spacing)")
def save_raster(units, stimulus_list, c_unit_fig, c_add_retina_figure, sort_by=glia.group_lifespan): print("Creating spike train raster plot") get_solid = glia.compose( glia.f_create_experiments(stimulus_list), partial(glia.group_by, key=lambda x: x["stimulus"]["metadata"]["group"]), glia.group_dict_to_list, partial(sorted,key=sort_by) ) response = glia.apply_pipeline(get_solid,units, progress=True) glia.plot_units(glia.raster_group,c_unit_fig,response,nplots=1, ncols=1,ax_xsize=15, ax_ysize=10)
def save_unit_wedges_v2(units, stimulus_list, c_unit_fig, c_add_retina_figure): print("Creating solid unit wedges") get_solid = glia.compose( glia.f_create_experiments(stimulus_list), glia.f_has_stimulus_type(["SOLID","WAIT"]), partial(glia.group_by, key=lambda x: x["stimulus"]["metadata"]["group"]), glia.group_dict_to_list, partial(sorted,key=lambda x: get_lifespan(x[1])) ) response = glia.apply_pipeline(get_solid,units, progress=True) glia.plot_units(plot_spike_train_triplet,c_unit_fig,response,nplots=1, ncols=1,ax_xsize=10, ax_ysize=5)
def save_unit_kinetics(units, stimulus_list, c_unit_fig, c_add_retina_figure): print("Creating solid unit kinetics") get_solid = glia.compose( glia.f_create_experiments(stimulus_list), partial(glia.group_by, key=lambda x: x["stimulus"]["metadata"]["group"]), glia.group_dict_to_list, partial(sorted,key=lambda x: get_lifespan(x[2])) ) response = glia.apply_pipeline(get_solid,units, progress=True) # glia.plot_units(plot_group_spike_train,c_unit_fig,response,nplots=1, # ncols=1,ax_xsize=10, ax_ysize=5) glia.plot_units(glia.raster_group,c_unit_fig,response,nplots=1, ncols=1,ax_xsize=10, ax_ysize=5)
def save_unit_response_by_angle(units, stimulus_list, c_unit_fig, c_add_retina_figure): print("Calculating DSI & OSI") bar_firing_rate, bar_dsi, bar_osi = get_fr_dsi_osi(units, stimulus_list) print("plotting unit response by angle") analytics = glia.by_speed_width_then_angle( glia.get_unit(bar_firing_rate)[1]) nplots = len(list(analytics.keys())) del analytics if nplots > 1: ncols = 3 else: ncols = 1 result = glia.plot_units(plot_unit_response_by_angle, partial(c_unit_fig, "angle"), bar_firing_rate, bar_dsi, bar_osi, nplots=nplots, subplot_kw={"projection": "polar"}, ax_xsize=4, ax_ysize=5, ncols=3) # c_unit_fig(result) # glia.close_figs([fig for the_id,fig in result]) print("plotting unit DSI/OSI table") result = glia.plot_units(plot_unit_dsi_osi_table, partial(c_unit_fig, "selectivity_table"), bar_firing_rate, bar_dsi, bar_osi, ax_xsize=16, ax_ysize=3) # c_unit_fig(result) # glia.close_figs([fig for the_id,fig in result]) fig_population, ax = plt.subplots(2, 1) print("plotting population by DSI & OSI") plot_population_dsi_osi(fig_population, ax, (bar_dsi, bar_osi)) c_add_retina_figure("DSI_OSI", fig_population) plt.close(fig_population)
def save_unit_kinetics_v1(units, stimulus_list, c_unit_fig, c_add_retina_figure): print("Creating solid unit kinetics") for i in range(5): s = i*150 e = (i+1)*150 get_solid = glia.compose( glia.f_create_experiments(stimulus_list), lambda x: x[s:e], partial(glia.group_by, key=lambda x: x["stimulus"]["metadata"]["group"]), glia.group_dict_to_list, partial(sorted,key=lambda x: get_lifespan(x[2])) ) response = glia.apply_pipeline(get_solid,units, progress=True) c = partial(c_unit_fig,"kinetics-{}".format(i)) glia.plot_units(glia.raster_group,c,response,nplots=1, ncols=1,ax_xsize=10, ax_ysize=5)
def save_unit_wedges(units, stimulus_list, c_unit_fig, c_add_retina_figure, prepend, append): print("Creating solid unit wedges") get_solid = glia.compose( glia.f_create_experiments(stimulus_list,prepend_start_time=prepend,append_lifespan=append), glia.f_has_stimulus_type(["SOLID"]), partial(sorted,key=lambda x: x["stimulus"]["lifespan"]) ) response = glia.apply_pipeline(get_solid,units, progress=True) colors = set() for solid in glia.get_unit(response)[1]: colors.add(solid["stimulus"]["backgroundColor"]) ncolors = len(colors) plot_function = partial(plot_spike_trains,prepend_start_time=prepend, append_lifespan=append) glia.plot_units(plot_function,c_unit_fig,response,nplots=ncolors, ncols=min(ncolors,5),ax_xsize=10, ax_ysize=5)
def save_unit_spike_trains(units, stimulus_list, c_unit_fig, c_add_retina_figure, prepend, append): print("Creating solid unit spike trains") get_solid = glia.compose( glia.f_create_experiments(stimulus_list,prepend_start_time=prepend,append_lifespan=append), glia.f_has_stimulus_type(["SOLID"]), ) response = glia.apply_pipeline(get_solid,units, progress=True) plot_function = partial(plot_spike_trains,prepend_start_time=prepend,append_lifespan=append) result = glia.plot_units(plot_function,response,ncols=1,ax_xsize=10, ax_ysize=5) c_unit_fig(result) glia.close_figs([fig for the_id,fig in result])
def save_integrity_chart_vFail(units, stimulus_list, c_unit_fig, c_add_retina_figure): print("Creating integrity chart") get_solid = glia.compose( glia.f_create_experiments(stimulus_list), glia.filter_integrity, partial(glia.group_by, key=lambda x: x["stimulus"]["metadata"]["group"]), glia.group_dict_to_list, integrity_fix_hack, partial(sorted,key=lambda x: x[0]["stimulus"]["stimulusIndex"]) ) response = glia.apply_pipeline(get_solid,units, progress=True) plot_function = partial(glia.raster_group) # c = partial(c_unit_fig,"kinetics-{}".format(i)) glia.plot_units(plot_function,c_unit_fig,response,ncols=1,ax_xsize=10, ax_ysize=5, figure_title="Integrity Test (5 Minute Spacing)") units_accuracy = glia.pmap(ideal_unit_classification_accuracy, response) c_add_retina_figure("integrity_accuracy",plot_units_accuracy(units_accuracy))
def save_unit_spike_trains(units, stimulus_list, c_add_unit_figures, c_add_retina_figure, by='angle'): print("Creating bar unit spike trains") if by == 'angle': get_solid = glia.compose( glia.f_create_experiments(stimulus_list), glia.f_has_stimulus_type(["BAR"]), partial(sorted, key=lambda e: e["stimulus"]["angle"]), ) nplots = get_nplots(stimulus_list, by) response = glia.apply_pipeline(get_solid, units, progress=True) result = glia.plot_units(plot_spike_trains_by_angle, response, nplots=nplots, ncols=3, ax_xsize=10, ax_ysize=5, figure_title="Unit spike train by BAR angle") elif by == 'width': get_solid = glia.compose( glia.f_create_experiments(stimulus_list), glia.f_has_stimulus_type(["BAR"]), partial(sorted, key=lambda e: e["stimulus"]["width"]), ) nplots = get_nplots(stimulus_list, by) response = glia.apply_pipeline(get_solid, units, progress=True) result = glia.plot_units(plot_spike_trains_by_trial, response, nplots=nplots, ncols=3, ax_xsize=10, ax_ysize=5, figure_title="Unit spike train by BAR angle") # nplots = len(speed_widths) c_add_unit_figures(result) glia.close_figs([fig for the_id, fig in result])
def save_integrity_chart_v2(units, stimulus_list, c_unit_fig, c_add_retina_figure): print("Creating integrity chart") get_integrity= glia.compose( glia.f_create_experiments(stimulus_list), glia.filter_integrity, partial(glia.group_by, key=lambda x: x["stimulus"]["metadata"]["group"]), glia.group_dict_to_list, ) response = glia.apply_pipeline(get_integrity,units, progress=True) chronological = glia.apply_pipeline( partial(sorted,key=lambda x: x[0]["stimulus"]["stimulusIndex"]), response) plot_function = partial(glia.raster_group) # c = partial(c_unit_fig,"kinetics-{}".format(i)) glia.plot_units(plot_function,c_unit_fig,chronological,ncols=1,ax_xsize=10, ax_ysize=5, figure_title="Integrity Test (5 Minute Spacing)") ntrial = len(glia.get_unit(response)[1]) ntrain = int(np.ceil(ntrial/2)) ntest = int(np.floor(ntrial/2)) tvt = glia.TVT(ntrain,ntest,0) classification_data = glia.apply_pipeline( glia.f_split_list(tvt), response) units_accuracy = glia.pmap(unit_classification_accuracy,classification_data) plot_directory = os.path.join(config.plot_directory,"00-all") os.makedirs(plot_directory, exist_ok=True) with open(plot_directory + "/best_units.txt", "w") as f: sorted_units = sorted(units_accuracy.items(), key=lambda z: max(z[1]["off"],z[1]["on"]), reverse=True) for u in sorted_units: f.write(str(u)+"\n") c_add_retina_figure("integrity_accuracy",plot_units_accuracy(units_accuracy))
def save_unit_psth(units, stimulus_list, c_unit_fig, c_add_retina_figure, prepend, append): print("Creating solid unit PSTH") get_psth = glia.compose( glia.f_create_experiments(stimulus_list,prepend_start_time=prepend,append_lifespan=append), glia.f_has_stimulus_type(["SOLID"]), glia.f_group_by_stimulus(), glia.concatenate_by_stimulus ) psth = glia.apply_pipeline(get_psth,units, progress=True) plot_function = partial(plot_psth,prepend_start_time=prepend,append_lifespan=append) result = glia.plot_units(partial(plot_function,bin_width=0.01),psth,ax_xsize=10, ax_ysize=5) c_unit_fig(result) glia.close_figs([fig for the_id,fig in result])
def save_unit_spike_trains(units, stimulus_list, c_unit_fig, c_add_retina_figure, width=None, height=None): print("Creating grating unit spike trains") get_solid = glia.compose(glia.f_create_experiments(stimulus_list), glia.f_has_stimulus_type(["GRATING"]), glia.f_split_by_wavelength()) response = glia.apply_pipeline(get_solid, units, progress=True) nplots = len(glia.get_unit(response)[1]) result = glia.plot_units( plot_spike_trains, response, nplots=nplots, ncols=3, ax_xsize=10, ax_ysize=5, figure_title="Unit spike train by GRATING waveperiod") c_unit_fig(result) glia.close_figs([fig for the_id, fig in result])
def cover(units, stimulus_list, metadata, c_unit_fig, c_retina_fig): "Add cover page." data = {k: v.name for k, v in units.items()} result = glia.plot_units(create_cover_page, data, ax_xsize=10, ax_ysize=5) c_unit_fig(result) glia.close_figs([fig for the_id, fig in result])