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@@ -301,10 +301,14 @@ def short_labels(label):
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label = "no inh."
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return label
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-def remove_frame(ax, dirs = ["right", "left", "top", "bottom"]):
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+
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+def remove_frame(ax, dirs=None):
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+ if dirs is None:
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+ dirs = ["right", "left", "top", "bottom"]
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for dir in dirs:
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ax.spines[dir].set_visible(False)
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+
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def remove_ticks(ax):
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ax.xaxis.set_ticks([])
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ax.yaxis.set_ticks([])
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@@ -378,18 +382,18 @@ def plot_axonal_clouds(traj, plot_run_names):
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traj.f_restore_default()
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start_scale_x = 100
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- end_scale_x = start_scale_x+scale_length
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+ end_scale_x = start_scale_x + scale_length
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start_scale_y = -70
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end_scale_y = start_scale_y
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scale_bar = axes[0].add_artist(plt.Line2D([start_scale_x, end_scale_x], [start_scale_y, end_scale_y], linewidth=2,
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- color='black'))
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+ color='black'))
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scale_bar.set_clip_on(False)
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- #axes[0].text(start_scale_x+scale_length/2.0, start_scale_y, , va="top",
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+ # axes[0].text(start_scale_x+scale_length/2.0, start_scale_y, , va="top",
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# ha="center", color="k")
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- axes[0].annotate("{:.0f} um".format(scale_length),xy=(start_scale_x+scale_length/2.0, start_scale_y), xytext=(0,-3),
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- xycoords="data", textcoords="offset points", va="top", ha="center", annotation_clip=False )
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-
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+ axes[0].annotate("{:.0f} um".format(scale_length), xy=(start_scale_x + scale_length / 2.0, start_scale_y),
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+ xytext=(0, -3),
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+ xycoords="data", textcoords="offset points", va="top", ha="center", annotation_clip=False)
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axes[1].set_yticklabels([])
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axes[2].set_yticklabels([])
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@@ -938,19 +942,26 @@ def plot_hdi_histogram_combined_and_overlayed(traj, plot_run_names, ex_polar_plo
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# # f2_ax2 = fig.add_subplot(gs[0, 1])
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# print(gs.get_subplot_params())
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- fig, axes = plt.subplots(2, 1, figsize=(4.5, 3.5))
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- plt.subplots_adjust(wspace=0, hspace=0)
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+ width = 2 * panel_size
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+ height = 1.5 * panel_size
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+ fig, axes = plt.subplots(2, 1, figsize=(width, height))
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+ plt.subplots_adjust(wspace=0, hspace=0.1)
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bins = np.linspace(0.0, 1.0, 21, endpoint=True)
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+ max_density=0
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for i in range(2):
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# i = i + 1 # grid spec indexes from 0
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# ax = fig.add_subplot(gs[i])
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ax = axes[i]
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- ax.hist(exc_hdis[i], color='r', edgecolor='r', alpha=0.3, bins=bins, density=True)
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- ax.hist(inh_hdis[i], color='b', edgecolor='b', alpha=0.3, bins=bins, density=True)
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+ density_e, _, _ = ax.hist(exc_hdis[i], color='r', edgecolor='r', alpha=0.3, bins=bins, density=True)
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+ density_i, _, _ = ax.hist(inh_hdis[i], color='b', edgecolor='b', alpha=0.3, bins=bins, density=True)
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+
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+ max_density = np.max([max_density, np.max(density_e), np.max(density_i)])
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ax.axvline(np.mean(exc_hdis[i]), color='r')
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+
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+
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ax.axvline(np.mean(inh_hdis[i]), color='b')
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ax.axvline(no_conn_hdi, color='dimgrey', linestyle='--', linewidth=2.5)
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@@ -958,22 +969,41 @@ def plot_hdi_histogram_combined_and_overlayed(traj, plot_run_names, ex_polar_plo
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# plt.axis('on')
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if i == 0:
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ax.set_xticklabels([])
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- ax.spines['top'].set_visible(False)
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+
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else:
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ax.set_xlabel('head direction index')
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- ax.spines['right'].set_visible(False)
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+ remove_frame(ax, ["top", "right", "bottom"])
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+ max_density = 1.2*max_density
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+ fig.subplots_adjust(left=0.2, right=0.95, bottom=0.2)
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- plt.gcf().subplots_adjust(bottom=0.15)
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- plt.gcf().subplots_adjust(left=0.15)
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+ axes[0].annotate('density', (0, 1.0), xycoords='axes fraction', va="bottom", ha="right")
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- plt.annotate('density', (-0.2, 1.15), xycoords='axes fraction', rotation=90, fontsize=18)
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+ axes[1].annotate("no ihn.\n{:.2f}".format(no_conn_hdi), xy=(no_conn_hdi, max_density),
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+ xytext=(-2, 0), xycoords="data",
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+ textcoords="offset points",
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+ va="top", ha="right", color="dimgrey")
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- # plt.annotate('probability density', (-0.2,1.5), xycoords='axes fraction', rotation=90, fontsize=18)
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+ for i, ax in enumerate(axes):
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+ ax.annotate("{:.2f}".format(np.mean(exc_hdis[i])), xy=(np.mean(exc_hdis[i]), max_density),
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+ xytext=(2, 0), xycoords="data",
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+ textcoords="offset points",
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+ va="top", ha="left", color="r")
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- # fig.tight_layout()
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+ i_ha = "left" if i==1 else "right"
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+ i_offset = 2 if i==1 else -2
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+ ax.annotate("{:.2f}".format(np.mean(inh_hdis[i])), xy=(np.mean(inh_hdis[i]), max_density),
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+ xytext=(i_offset, 0), xycoords="data",
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+ textcoords="offset points",
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+ va="top", ha=i_ha, color="b")
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+
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+
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+
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+ for ax in axes:
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+ ax.set_ylim(0, max_density)
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+ # plt.annotate('probability density', (-0.2,1.5), xycoords='axes fraction', rotation=90, fontsize=18)
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if save_figs:
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- plt.savefig(FIGURE_SAVE_PATH + 'hdi_histogram_combined_and_overlayed_{}.png'.format(cut_off_dist), dpi=200)
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+ plt.savefig(FIGURE_SAVE_PATH + 'E_hdi_histogram_combined_and_overlayed_cutoff_{}um.png'.format(cut_off_dist))
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return ex_polar_plot_hdi, in_polar_plot_hdi, representative_excitatory_neuron_indices, representative_inhibitory_neuron_indices
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