185 lines
8.6 KiB
Python
185 lines
8.6 KiB
Python
import numpy as np
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import pandas as pd
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import matplotlib.pyplot as plt
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import matplotlib.gridspec as gridspec
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from matplotlib.transforms import Bbox
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import string
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# from plotstyle import plot_style
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#### from https://gist.github.com/dmeliza/3251476 #####################################################################
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from matplotlib.offsetbox import AnchoredOffsetbox
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class AnchoredScaleBar(AnchoredOffsetbox):
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def __init__(self, transform, sizex=0, sizey=0, labelx=None, labely=None, loc=4,
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pad=0.1, borderpad=0.1, sep=2, prop=None, barcolor="black", barwidth=None,
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**kwargs):
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"""
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Draw a horizontal and/or vertical bar with the size in data coordinate
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of the give axes. A label will be drawn underneath (center-aligned).
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- transform : the coordinate frame (typically axes.transData)
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- sizex,sizey : width of x,y bar, in data units. 0 to omit
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- labelx,labely : labels for x,y bars; None to omit
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- loc : position in containing axes
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- pad, borderpad : padding, in fraction of the legend font size (or prop)
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- sep : separation between labels and bars in points.
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- **kwargs : additional arguments passed to base class constructor
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"""
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from matplotlib.patches import Rectangle
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from matplotlib.offsetbox import AuxTransformBox, VPacker, HPacker, TextArea, DrawingArea
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bars = AuxTransformBox(transform)
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if sizex:
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bars.add_artist(Rectangle((0, 0), sizex, 0, ec=barcolor, lw=barwidth, fc="none"))
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if sizey:
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bars.add_artist(Rectangle((0, 0), 0, sizey, ec=barcolor, lw=barwidth, fc="none"))
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if sizex and labelx:
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self.xlabel = TextArea(labelx)
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bars = VPacker(children=[bars, self.xlabel], align="center", pad=0, sep=sep)
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if sizey and labely:
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self.ylabel = TextArea(labely)
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bars = HPacker(children=[self.ylabel, bars], align="center", pad=0, sep=sep)
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AnchoredOffsetbox.__init__(self, loc, pad=pad, borderpad=borderpad,
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child=bars, prop=prop, frameon=False, **kwargs)
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def add_scalebar(ax, matchx=True, matchy=True, hidex=True, hidey=True, **kwargs):
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""" Add scalebars to axes
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Adds a set of scale bars to *ax*, matching the size to the ticks of the plot
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and optionally hiding the x and y axes
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- ax : the axis to attach ticks to
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- matchx,matchy : if True, set size of scale bars to spacing between ticks
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if False, size should be set using sizex and sizey params
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- hidex,hidey : if True, hide x-axis and y-axis of parent
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- **kwargs : additional arguments passed to AnchoredScaleBars
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Returns created scalebar object
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"""
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def f(axis):
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l = axis.get_majorticklocs()
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return len(l) > 1 and (l[1] - l[0])
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if matchx:
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kwargs['sizex'] = f(ax.xaxis)
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kwargs['labelx'] = str(kwargs['sizex'])
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if matchy:
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kwargs['sizey'] = f(ax.yaxis)
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kwargs['labely'] = str(kwargs['sizey'])
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sb = AnchoredScaleBar(ax.transData, **kwargs)
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ax.add_artist(sb)
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if hidex: ax.xaxis.set_visible(False)
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if hidey: ax.yaxis.set_visible(False)
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if hidex and hidey: ax.set_frame_on(False)
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return sb
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########################################################################################################################
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def plot_spike_train(ax, model='RS Pyramidal', stop=750):
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model_spiking = pd.read_csv('./Figures/Data/model_spiking.csv')
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stop_ind = np.int(np.argmin(np.abs(model_spiking['t'] - stop)))
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ax.plot(model_spiking['t'][0:stop_ind], model_spiking[model][0:stop_ind], 'k', linewidth=1.5)
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ax.set_ylabel('V')
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ax.set_xlabel('Time [s]')
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ax.set_ylim(-80, 60)
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ax.axis('off')
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ax.set_title(model)
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def plot_fI(ax, model='RS Pyramidal'):
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firing_values = pd.read_csv('./Figures/Data/firing_values.csv', index_col='Unnamed: 0')
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model_F_inf = pd.read_csv('./Figures/Data/model_F_inf.csv')
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if model=='RS Inhibitory':
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ax.plot(model_F_inf['I_inhib'], model_F_inf[model], color='grey')
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ax.plot(firing_values.loc['spike_ind', model], model_F_inf[model][np.int(np.argmin(np.abs(model_F_inf['I_inhib'] - firing_values.loc['spike_ind', model])))],
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'.', color='k', markersize=3)
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ax.plot(firing_values.loc['ramp_up', model],
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model_F_inf[model][np.int(np.argmin(np.abs(model_F_inf['I_inhib'] - firing_values.loc['ramp_up', model])))],
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'.', color='g', markersize=3)
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ax.plot(firing_values.loc['ramp_down', model],
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model_F_inf[model][np.int(np.argmin(np.abs(model_F_inf['I_inhib'] - firing_values.loc['ramp_down', model])))],
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'.', color='r', markersize=3)
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else:
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ax.plot(model_F_inf['I'], model_F_inf[model], color='grey')
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ax.plot(firing_values.loc['spike_ind', model],
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model_F_inf[model][np.int(np.argmin(np.abs(model_F_inf['I'] - firing_values.loc['spike_ind', model])))],
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'.', color='k', markersize=3)
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ax.plot(firing_values.loc['ramp_up', model],
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model_F_inf[model][np.int(np.argmin(np.abs(model_F_inf['I'] - firing_values.loc['ramp_up', model])))],
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'.', color='g', markersize=3)
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ax.plot(firing_values.loc['ramp_down', model],
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model_F_inf[model][np.int(np.argmin(np.abs(model_F_inf['I'] - firing_values.loc['ramp_down', model])))],
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'.', color='r', markersize=3)
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f = 8
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ax.set_ylabel('Frequency [Hz]', fontsize=f)
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ax.set_xlabel('Current [pA]', fontsize=f)
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ax.spines['right'].set_visible(False)
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ax.spines['top'].set_visible(False)
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#%%
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# plot layout
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fig = plt.figure(figsize=(10,10))
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gs0 = fig.add_gridspec(3, 2, wspace=0.3)
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gs00 = gs0[:,0].subgridspec(6, 3, wspace=0.7, hspace=1)
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gs01 = gs0[:,1].subgridspec(6, 3, wspace=0.7, hspace=1)
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ax1_spikes = fig.add_subplot(gs00[0,0:2])
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ax1_fI = fig.add_subplot(gs00[0, 2])
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ax2_spikes = fig.add_subplot(gs01[0,0:2])
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ax2_fI = fig.add_subplot(gs01[0, 2])
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ax3_spikes = fig.add_subplot(gs00[1,0:2])
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ax3_fI = fig.add_subplot(gs00[1, 2])
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ax4_spikes = fig.add_subplot(gs01[1,0:2])
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ax4_fI = fig.add_subplot(gs01[1, 2])
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ax5_spikes = fig.add_subplot(gs00[2, 0:2])
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ax5_fI = fig.add_subplot(gs00[2, 2])
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ax6_spikes = fig.add_subplot(gs01[2, 0:2])
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ax6_fI = fig.add_subplot(gs01[2, 2])
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ax7_spikes = fig.add_subplot(gs00[3,0:2])
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ax7_fI = fig.add_subplot(gs00[3, 2])
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ax8_spikes = fig.add_subplot(gs01[3,0:2])
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ax8_fI = fig.add_subplot(gs01[3, 2])
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ax9_spikes = fig.add_subplot(gs00[4,0:2])
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ax9_fI = fig.add_subplot(gs00[4, 2])
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ax10_spikes = fig.add_subplot(gs01[4,0:2])
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ax10_fI = fig.add_subplot(gs01[4, 2])
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ax11_spikes = fig.add_subplot(gs00[5,0:2])
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ax11_fI = fig.add_subplot(gs00[5, 2])
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ax12_spikes = fig.add_subplot(gs01[5,0:2])
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ax12_fI = fig.add_subplot(gs01[5, 2])
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spike_axs = [ax1_spikes, ax2_spikes, ax3_spikes, ax4_spikes, ax5_spikes,ax6_spikes, ax7_spikes, ax8_spikes,
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ax9_spikes, ax10_spikes, ax11_spikes, ax12_spikes]#, ax13_spikes, ax14_spikes]
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fI_axs = [ax1_fI, ax2_fI, ax3_fI, ax4_fI, ax5_fI,ax6_fI, ax7_fI, ax8_fI, ax9_fI, ax10_fI,
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ax11_fI, ax12_fI] #, ax13_fI, ax14_fI]
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# model order
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models = ['Cb stellate','RS Inhibitory','FS', 'RS Pyramidal','RS Inhibitory +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
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'Cb stellate +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', 'FS +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
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'RS Pyramidal +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', 'STN +$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
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'Cb stellate $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$',
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'STN $\Delta$$\mathrm{K}_{\mathrm{V}}\mathrm{1.1}$', 'STN']
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# plot spike train and fI for each model
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for i in range(len(models)):
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plot_spike_train(spike_axs[i], model=models[i])
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plot_fI(fI_axs[i], model=models[i])
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# add scalebars
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add_scalebar(ax11_spikes, matchx=False, matchy=False, hidex=True, hidey=True, sizex=100, sizey=50, labelx='100 ms',
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labely='50 mV', loc=3, pad=-0.5, borderpad=-1.0, barwidth=2, bbox_to_anchor=Bbox.from_bounds(-0.2, -0.05, 1, 1),
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bbox_transform=ax11_spikes.transAxes)
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add_scalebar(ax12_spikes, matchx=False, matchy=False, hidex=True, hidey=True, sizex=100, sizey=50, labelx='100 ms',
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labely='50 mV', loc=3, pad=-0.5, borderpad=-1.0, barwidth=2, bbox_to_anchor=Bbox.from_bounds(-0.2, -0.05, 1, 1),
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bbox_transform=ax12_spikes.transAxes)
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# add subplot labels
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for i in range(0,len(models)):
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spike_axs[i].text(-0.18, 1.08, string.ascii_uppercase[i], transform=spike_axs[i].transAxes, size=16, weight='bold')
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# save
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fig.savefig('./Figures/diversity_in_firing.pdf', bbox_inches='tight')
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plt.show()
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