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) 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) 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_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_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 save_unit_spike_trains(units, stimulus_list, c_add_unit_figures, 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) 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_add_unit_figures(result) glia.close_figs([fig for the_id,fig in result])
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_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 simulated_test(units, stimulus_list): # assert len(next(iter(units.values())).spike_train)==2200 test_pipeline = glia.compose(glia.f_create_experiments(stimulus_list), glia.f_has_stimulus_type(["GRATING"]), glia.f_group_by_stimulus(), glia.f_calculate_firing_rate_by_stimulus()) firing_rates = glia.apply_pipeline(test_pipeline, units, progress=True) for stimulus, rates in next(iter(firing_rates.values())).items(): for rate in rates: assert np.isclose(rate, 60, 1)
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_unit_psth(units, stimulus_list, c_add_unit_figures, 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) 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_add_unit_figures(result) glia.close_figs([fig for the_id,fig in result])
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 simulated_test(units, stimulus_list): assert len(next(iter(units.values())).spike_train)==2200 test_pipeline = glia.compose( glia.f_create_experiments(stimulus_list), glia.f_has_stimulus_type(["GRATING"]), glia.f_group_by_stimulus(), glia.f_calculate_firing_rate_by_stimulus() ) firing_rates = glia.apply_pipeline(test_pipeline, units) for stimulus,rates in next(iter(firing_rates.values())).items(): for rate in rates: assert rate==1
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_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 get_fr_dsi_osi(units, stimulus_list): get_bar_firing_rate = glia.compose( glia.f_create_experiments(stimulus_list), glia.f_has_stimulus_type(["BAR"]), glia.f_group_by_stimulus(), glia.f_calculate_firing_rate_by_stimulus(), ) bar_firing_rate = glia.apply_pipeline(get_bar_firing_rate, units, progress=True) get_bar_dsi = glia.compose(glia.by_speed_width_then_angle, glia.calculate_dsi_by_speed_width) bar_dsi = glia.apply_pipeline(get_bar_dsi, bar_firing_rate, progress=True) get_bar_osi = glia.compose(glia.by_speed_width_then_angle, glia.calculate_osi_by_speed_width) bar_osi = glia.apply_pipeline(get_bar_osi, bar_firing_rate, progress=True) return (bar_firing_rate, bar_dsi, bar_osi)
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 get_fr_dsi_osi(units, stimulus_list): get_bar_firing_rate = glia.compose( glia.f_create_experiments(stimulus_list), glia.f_has_stimulus_type(["BAR"]), glia.f_group_by_stimulus(), glia.f_calculate_firing_rate_by_stimulus(), ) bar_firing_rate = glia.apply_pipeline(get_bar_firing_rate,units) get_bar_dsi = glia.compose( glia.by_speed_width_then_angle, glia.calculate_dsi_by_speed_width ) bar_dsi = glia.apply_pipeline(get_bar_dsi,bar_firing_rate) get_bar_osi = glia.compose( glia.by_speed_width_then_angle, glia.calculate_osi_by_speed_width ) bar_osi = glia.apply_pipeline(get_bar_osi,bar_firing_rate) return (bar_firing_rate, bar_dsi, bar_osi)
def f_has_stimulus_type_test(stimulus_list): pipeline = glia.f_has_stimulus_type("GRATING") filtered = pipeline(stimulus_list) for each in filtered: assert each["stimulus"]["stimulusType"] == "GRATING"
def f_has_stimulus_type_test(stimulus_list): pipeline = glia.f_has_stimulus_type("GRATING") filtered = pipeline(stimulus_list) for each in filtered: assert each["stimulus"]["stimulusType"]=="GRATING"