def plot_var_result_example(ax):
ax.set_xlim([-0.0,5.5])
data_hr_ht = core.get_data('fig6/variance_hr_ht.npy')
data_lr_ht = core.get_data('fig6/variance_lr_ht.npy')
data_hr_lt = core.get_data('fig6/variance_hr_lt.npy')
time_params=core.get_data('fig6/time_parameters.npy').item()
weighttrace=np.concatenate(((data_hr_ht,),(data_lr_ht,),(data_hr_lt,)))
core.show_axis(ax)
core.make_spines(ax)
ax.set_prop_cycle(cycler('color',[core.label_to_color["hr_ht"],core.label_to_color["lr_ht"],core.label_to_color["hr_lt"]] ))
plotf.trace_plot(ax,weighttrace,time_params,linewidth=core.linewidth["normal"])
ax.axvline(x=5,color=core.label_to_color["aux_lines"],linewidth=core.linewidth["aux_lines"],ls="dashed")
ax.text(5.,75.,r"$t_0$")
ax.set_xlabel(core.x_labels["trace_plot"])
ax.set_ylabel(core.y_labels["trace_plot"])
ax.legend((r"$w_1$",r"$w_2$",r"$w_3$"),loc=2,fontsize=8.,handlelength=0.5,frameon=False)
pass
def plot_attenuation_example_abs(ax):
data_prox = core.get_data('fig6/attenuation_proximal_synapse.npy')
data_dist = core.get_data('fig6/attenuation_distal_synapse.npy')
time_params=core.get_data('fig6/time_parameters.npy').item()
ax.set_prop_cycle(cycler('color',[core.label_to_color["attenuation_ldist"],core.label_to_color["attenuation_hdist"]] ))
weighttrace=np.concatenate(((data_prox,),(data_dist,)))
core.show_axis(ax)
core.make_spines(ax)
plotf.trace_plot(ax,weighttrace,time_params,perc=False,linewidth=core.linewidth["normal"])
ax.set_xlabel(core.x_labels["trace_plot"])
ax.set_ylabel(core.y_labels["trace_plot_dend_abs"])
# ax.legend((r"$d=3\mu m$",r"$d=7\mu m$"),loc=2,fontsize=8.,handlelength=0.5,frameon=False)
pass
def plot_phase3(ax):
data_hom = core.get_data('fig5/w_hom_phase3.npy')
data_het = core.get_data('fig5/w_het_phase3.npy')
time_params = core.get_data('fig5/time_parameters.npy').item()
ax.set_xlim([-.5, 5.5])
x_ticks = np.array((0., 2.5, 5.))
ax.xaxis.set_ticks(x_ticks)
weighttrace = np.concatenate(((data_hom, ), (data_het, )))
ax.set_prop_cycle(
cycler('color',
[core.label_to_color["stim"], core.label_to_color["unstim"]]))
core.show_axis(ax)
core.make_spines(ax)
plotf.trace_plot(ax,
weighttrace,
time_params,
linewidth=core.linewidth["normal"])
ax.axvline(x=0,
color=core.label_to_color["aux_lines"],
linewidth=core.linewidth["aux_lines"],
ls="dashed")
ax.text(0., 99.05, r"$t_0$")
ax.axvline(x=5,
color=core.label_to_color["aux_lines"],
linewidth=core.linewidth["aux_lines"],
ls="dashed")
ax.text(5., 99.05, r"$t_1$")
ax.set_xlabel(core.x_labels["trace_plot"])
ax.set_ylabel(core.y_labels["trace_plot"])
ax.legend((r"$w_{\rm st}$", r"$w_{\rm ust}$"),
loc=0,
fontsize=8.,
labelspacing=0.1,
borderaxespad=0.1,
borderpad=0.,
handlelength=0.5,
frameon=False)
pass
def plot_phase1(ax):
data_hom = core.get_data('fig5/w_hom_phase1.npy')
data_het = core.get_data('fig5/w_het_phase1.npy')
time_params = core.get_data('fig5/time_parameters.npy').item()
ax.set_xlim([-.5, 5.5])
x_ticks = np.array((0., 2.5, 5.))
ax.xaxis.set_ticks(x_ticks)
weighttrace = np.concatenate(((data_hom, ), (data_het, )))
ax.set_prop_cycle(
cycler('color',
[core.label_to_color["stim"], core.label_to_color["unstim"]]))
core.show_axis(ax)
core.make_spines(ax)
plotf.trace_plot(ax,
weighttrace,
time_params,
linewidth=core.linewidth["normal"])
ax.axvline(x=0,
color=core.label_to_color["aux_lines"],
linewidth=core.linewidth["aux_lines"],
ls="dashed")
ax.text(0., 10., r"$t_0$")
ax.axvline(x=5,
color=core.label_to_color["aux_lines"],
linewidth=core.linewidth["aux_lines"],
ls="dashed")
ax.text(5., 10., r"$t_1$")
ax.set_xlabel(core.x_labels["trace_plot"])
ax.set_ylabel(core.y_labels["trace_plot"])
pass