def main(**kwargs):
exclude=kwargs.get('exclude',[])
models=['GP_GP', 'GA_GA', 'GI_GA', 'GI_GI']
models=[m for m in models if not ( m in exclude)]
nets=['Net_0', 'Net_1']
attrs=['mean_coherence', 'phases_diff_with_cohere']
from_disk=kwargs.get('from_diks',0)
path=('/home/mikael/results/papers/inhibition/network/'
+'supermicro/simulate_slow_wave_ZZZ_dop_effect_perturb/')
path=kwargs.get('data_path', path)
script_name=kwargs.get('script_name', (__file__.split('/')[-1][0:-3]
+'/data'))
file_name = get_file_name(script_name)
sd = get_storage(file_name, '')
d={}
if not from_disk:
# d['raw']=gather(path, nets, models, attrs)
d['raw']=gather2(path, nets, models, attrs)
d['data']=extract_data(d['raw'], nets, models, attrs)
d['performance']=compute_performance(d['data'], nets, models, attrs)
d['bar_obj'], d['labels']=generate_plot_data(d['performance'],
models,
attrs)
save(sd, d)
else:
filt=['bar_obj']+models+['labels']
d = sd.load_dic(*filt)
figs=[]
figs.append(plot_coher(d, d['labels'], title_name=kwargs.get('title')))
save_figures(figs, script_name)
pylab.show()
def main(**kwargs):
exclude = kwargs.get('exclude', [])
models = ['GP_GP', 'GA_GA', 'GI_GA', 'GI_GI']
models = [m for m in models if not (m in exclude)]
nets = ['Net_0', 'Net_1']
attrs = ['mean_coherence', 'phases_diff_with_cohere']
from_disk = kwargs.get('from_diks', 0)
path = ('/home/mikael/results/papers/inhibition/network/' +
'supermicro/simulate_slow_wave_ZZZ_dop_effect_perturb/')
path = kwargs.get('data_path', path)
script_name = kwargs.get('script_name',
(__file__.split('/')[-1][0:-3] + '/data'))
file_name = get_file_name(script_name)
sd = get_storage(file_name, '')
d = {}
if not from_disk:
# d['raw']=gather(path, nets, models, attrs)
d['raw'] = gather2(path, nets, models, attrs)
d['data'] = extract_data(d['raw'], nets, models, attrs)
d['performance'] = compute_performance(d['data'], nets, models, attrs)
d['bar_obj'], d['labels'] = generate_plot_data(d['performance'],
models, attrs)
save(sd, d)
else:
filt = ['bar_obj'] + models + ['labels']
d = sd.load_dic(*filt)
figs = []
figs.append(plot_coher(d, d['labels'], title_name=kwargs.get('title')))
save_figures(figs, script_name)
pylab.show()
sm = pylab.cm.ScalarMappable(cmap='copper',
norm=pylab.normalize(vmin=2.5, vmax=20))
sm._A = []
box = ax.get_position()
pos=[box.x0+1.03*box.width, box.y0+box.height*0.1,
0.01, box.height*0.8]
axColor=pylab.axes(pos)
cbar=pylab.colorbar(sm, cax=axColor)
tick_locator = ticker.MaxNLocator(nbins=7)
cbar.locator = tick_locator
cbar.update_ticks()
cbar.ax.tick_params( length=1, )
cbar.ax.set_yticklabels(ln, fontsize=5*scale)
ax.text(1.3, 0.5, r'$g^{TA\to FS}$, $g_{TI\to FS}$',
transform=ax.transAxes, va='center', rotation=270)
ax.set_xlabel(r'Angle (rad)')
ax.set_ylabel('Frequency (Hz)')
ax.my_set_no_ticks(xticks=4)
ax.my_set_no_ticks(yticks=4)
l2=l2[organize['TATIFS']]
save_figures([fig], script_name, dpi=400)
pylab.show()
ax.set_ylabel('')
# a=ax.get_xticklabels()
ax.tick_params(axis='both', which='major', labelsize=7*scale)
# ax.set_xticklabels(ax.get_xticklabels(), fontsize=20)
# ax.set_yticklabels(fontsize=20)
ax.my_remove_axis(xaxis=True, yaxis=True,keep_ticks=True)
# axs[0].my_remove_axis(xaxis=True, yaxis=False,keep_ticks=True)
# axs[1].my_remove_axis(xaxis=True, yaxis=True,keep_ticks=True)
# axs[2].my_remove_axis(xaxis=True, yaxis=False,keep_ticks=True)
# axs[3].my_remove_axis(xaxis=True, yaxis=True,keep_ticks=True)
# axs[4].my_remove_axis(xaxis=False, yaxis=False,keep_ticks=True)
# axs[5].my_remove_axis(xaxis=False, yaxis=True,keep_ticks=True)
#
# if i==4:
# ax.text(1.05, -.3,
# 'Cortical input action 1',
# horizontalalignment='center',
# transform=axs[i].transAxes)
# ax.set_xticks([1,1.5, 2, 2.5])
# ax.set_xticklabels(['1.0','1.5','2.0','2.5'])
#
# if i==2:
# ax.set_ylabel('Cortical input action 2')
save_figures([fig], __file__.split('/')[-1][0:-3]+'/data', dpi=200)
pylab.show()
pos=[box.x0+1.03*box.width, box.y0+box.height*0.1,
0.01, box.height*0.8]
axColor=pylab.axes(pos)
cbar=pylab.colorbar(sm, cax=axColor, ticks=range(len(ln)))
cbar.ax.tick_params( length=1, )
cbar.ax.set_yticklabels(ln, fontsize=5*scale)
ax.text(1.3, 0.5, r'$Fan_{in}^{[TA,TI]\to TA}$ (#)',
transform=ax.transAxes, va='center', rotation=270)
ax.set_xlabel(r'Angle (rad)')
ax.set_ylabel('Norm. count TI-TA')
ax.my_set_no_ticks(xticks=4)
ax.my_set_no_ticks(yticks=4)
ax.set_ylim([0,0.31])
for ax in axs:
ax.tick_params(direction='out',
length=2,
width=0.5,
pad=0.01,
top=False, right=False
)
save_figures([fig], script_name, dpi=400)
pylab.show()
