def spec_current_kernel(fparam, fts, fspec, f_max):
I_syn = currentfn.SynapticCurrent(fts)
# Generate spec results
spec_L2 = MorletSpec(I_syn.t, I_syn.I_soma_L2Pyr, fparam, f_max)
spec_L5 = MorletSpec(I_syn.t, I_syn.I_soma_L5Pyr, fparam, f_max)
# Save spec data
np.savez_compressed(fspec,
t_L2=spec_L2.t,
f_L2=spec_L2.f,
TFR_L2=spec_L2.TFR,
t_L5=spec_L5.t,
f_L5=spec_L5.f,
TFR_L5=spec_L5.TFR)
def pkernel(dfig_dpl, f_dpl, f_spk, f_spec, f_current, f_spec_current, f_param, ax_handles, spec_cmap='jet'):
T = paramrw.find_param(f_param, 'tstop')
xlim = (50., T)
# into the pdipole directory, this will plot dipole, spec, and spikes
# create the axis handle
f = ac.FigDipoleExp(ax_handles)
# create the figure name
fprefix = fio.strip_extprefix(f_dpl) + '-dpl'
fname = os.path.join(dfig_dpl, fprefix + '.png')
# grab the dipole
dpl = dipolefn.Dipole(f_dpl)
dpl.convert_fAm_to_nAm()
# plot the dipole to the agg axes
dpl.plot(f.ax['dpl_agg'], xlim)
dpl.plot(f.ax['dpl_agg_L5'], xlim)
# f.ax['dpl_agg_L5'].hold(True)
# dpl.plot(f.ax['dpl_agg_L5'], xlim, 'L5')
# plot individual dipoles
dpl.plot(f.ax['dpl'], xlim, 'L2')
dpl.plot(f.ax['dpl_L5'], xlim, 'L5')
# f.ysymmetry(f.ax['dpl'])
# print dpl.max('L5', (0., -1)), dpl.max('L5', (50., -1))
# print f.ax['dpl_L5'].get_ylim()
# f.ax['dpl_L5'].set_ylim((-1e5, 1e5))
# f.ysymmetry(f.ax['dpl_L5'])
# plot the current
I_soma = currentfn.SynapticCurrent(f_current)
I_soma.plot_to_axis(f.ax['I_soma'], 'L2')
I_soma.plot_to_axis(f.ax['I_soma_L5'], 'L5')
# plot the dipole-based spec data
pc = specfn.pspec_ax(f.ax['spec_dpl'], f_spec, xlim, 'L2')
f.f.colorbar(pc, ax=f.ax['spec_dpl'])
pc = specfn.pspec_ax(f.ax['spec_dpl_L5'], f_spec, xlim, 'L5')
f.f.colorbar(pc, ax=f.ax['spec_dpl_L5'])
# grab the current spec and plot them
spec_L2, spec_L5 = data_spec_current = specfn.read(f_spec_current, type='current')
pc_L2 = f.ax['spec_I'].imshow(spec_L2['TFR'], aspect='auto', origin='upper',cmap=plt.get_cmap(spec_cmap))
pc_L5 = f.ax['spec_I_L5'].imshow(spec_L5['TFR'], aspect='auto', origin='upper',cmap=plt.get_cmap(spec_cmap))
# plot the current-based spec data
# pci = specfn.pspec_ax(f.ax['spec_I'], f_spec_current, type='current')
f.f.colorbar(pc_L2, ax=f.ax['spec_I'])
f.f.colorbar(pc_L5, ax=f.ax['spec_I_L5'])
# get all spikes
s = spikefn.spikes_from_file(f_param, f_spk)
# these work primarily because of how the keys are done
# in the spike dict s (consequence of spikefn.spikes_from_file())
s_L2 = spikefn.filter_spike_dict(s, 'L2_')
s_L5 = spikefn.filter_spike_dict(s, 'L5_')
# resize xlim based on our 50 ms cutoff thingy
xlim = (50., xlim[1])
# plot the spikes
spikefn.spike_png(f.ax['spk'], s_L2)
spikefn.spike_png(f.ax['spk_L5'], s_L5)
f.ax['dpl'].set_xlim(xlim)
# f.ax['dpl_L5'].set_xlim(xlim)
# f.ax['spec_dpl'].set_xlim(xlim)
f.ax['spk'].set_xlim(xlim)
f.ax['spk_L5'].set_xlim(xlim)
f.savepng(fname)
f.close()
return 0