def run_democlamp(cell, dend, vsteps=[-60,-70,-60], tsteps=[10,50,100]):
"""
Does some stuff.
"""
f1 = pylab.figure(1)
gs = GS.GridSpec(2, 2,
width_ratios=[1, 1],
height_ratios=[1, 1])
# note numbering for insets goes from 1 (upper right) to 4 (lower right)
# counterclockwise
pA = f1.add_subplot(gs[0])
pAi = INSETS.inset_axes(pA, width="66%", height="40%", loc=2)
pB = f1.add_subplot(gs[1])
pBi = INSETS.inset_axes(pB, width="66%", height="40%", loc=4)
pC = f1.add_subplot(gs[2])
pCi = INSETS.inset_axes(pC, width="66%", height="40%", loc=2)
pD = f1.add_subplot(gs[3])
pDi = INSETS.inset_axes(pD, width="66%", height="40%", loc=1)
#h.topology()
Ld = 0.5
Ld2 = 1.0
VClamp = h.SEClamp(0.5, cell)
VClamp.dur1 = tsteps[0]
VClamp.amp1 = vsteps[0]
VClamp.dur2 = tsteps[1]
VClamp.amp2 = vsteps[1]
VClamp.dur3 = tsteps[2]
VClamp.amp3 = vsteps[2]
Rs0 = 10.
VClamp.rs = Rs0
compensation = [0., 70., 95.]
cms = [cell.cm*(100.-c)/100. for c in compensation]
vrec = h.iStim(Ld, sec=dend[0])
vrec.delay = 0
vrec.dur = 1e9 # these actually do not matter...
vrec.iMax = 0.0
vrec2 = h.iStim(Ld2, sec=dend[0])
vrec2.delay = 0
vrec2.dur = 1e9 # these actually do not matter...
vrec2.iMax = 0.0
stim = {}
stim['NP'] = 1
stim['Sfreq'] = 20 # stimulus frequency
stim['delay'] = tsteps[0]
stim['dur'] = tsteps[1]
stim['amp'] = vsteps[1]
stim['PT'] = 0.0
stim['hold'] = vsteps[0]
# (secmd, maxt, tstims) = make_pulse(stim)
tend = 79.5
linetype = ['-', '-', '-']
linethick = [0.5, 0.75, 1.25]
linecolor = [[0.66, 0.66, 0.66], [0.4, 0.4, 0.3], 'k']
n = 0
vcmds = [-70, -20]
vplots = [(pA, pAi, pC, pCi), (pB, pBi, pD, pDi)]
for m, VX in enumerate(vcmds):
stim['amp'] = VX
pl = vplots[m]
print m, VX
(secmd, maxt, tstims) = make_pulse(stim)
for n, rsc in enumerate(compensation):
vec={}
for var in ['VCmd', 'i_inj', 'time', 'Vsoma', 'Vdend',
'Vdend2', 'VCmdR']:
vec[var] = h.Vector()
VClamp.rs = Rs0*(100.-rsc)/100.
cell.cm = cms[n]
# print VClamp.rs, cell.cm, VClamp.rs*cell.cm
vec['VCmd'] = h.Vector(secmd)
vec['Vsoma'].record(cell(0.5)._ref_v, sec=cell)
vec['Vdend'].record(dend[0](Ld)._ref_v, sec=dend[0])
vec['time'].record(h._ref_t)
vec['i_inj'].record(VClamp._ref_i, sec=cell)
vec['VCmdR'].record(VClamp._ref_vc, sec=cell)
VClamp.amp2 = VX
# vec['VCmd'].play(VClamp.amp2, h.dt, 0, sec=cell)
h.tstop = tend
h.init()
h.finitialize(-60)
h.run()
vc = np.asarray(vec['Vsoma'])
tc = np.asarray(vec['time'])
# now plot the data, raw and as insets
for k in [0, 1]:
pl[k].plot(vec['time'], vec['i_inj'], color=linecolor[n], linestyle = linetype[n], linewidth=linethick[n])
yl = pl[k].get_ylim()
if k == 0:
pass
#pl[k].set_ylim([1.5*yl[0], -1.5*yl[1]])
else:
pass
for k in [2,3]:
pl[k].plot(vec['time'], vec['Vsoma'], color=linecolor[n], linestyle = linetype[n], linewidth=linethick[n])
pl[k].plot(vec['time'], vec['VCmdR'], color=linecolor[n], linestyle = '--', linewidth=1, dashes=(1,1))
pl[k].plot(vec['time'], vec['Vdend'], color=linecolor[n], linestyle = linetype[n], linewidth=linethick[n], dashes=(3,3))
if VX < vsteps[0]:
pl[k].set_ylim([-72, -40])
else:
pl[k].set_ylim([-62,VX+30])
ptx = 10.8
pBi.set_xlim([9.8, ptx])
pAi.set_xlim([9.8, ptx])
PH.setX(pAi, pCi)
PH.setX(pBi, pDi)
pD.set_ylim([-65, 10])
# PH.setY(pC, pCi) # match Y limits
PH.cleanAxes([pA, pAi, pB, pBi, pC, pCi, pD, pDi])
PH.formatTicks([pA, pB, pC, pD], axis='x', fmt='%d')
PH.formatTicks([pC, pD], axis='y', fmt='%d')
PH.calbar(pAi, [ptx-1, 0, 0.2, 2.])
PH.calbar(pCi, [ptx-1, -50., 0.2, 10])
PH.calbar(pBi, [ptx-1, 0, 0.2, 10])
PH.calbar(pDi, [ptx-1, -50., 0.2, 20])
pylab.draw()
pylab.show()
def plot(self):
sizer = OrderedDict(
[
('A', {
'pos': [0.12, 0.2, 0.15, 0.5]
}),
('B', {
'pos': [0.45, 0.2, 0.15, 0.5]
}),
('C', {
'pos': [0.72, 0.2, 0.15, 0.5]
}),
]
) # dict elements are [left, width, bottom, height] for the axes in the plot.
n_panels = len(sizer.keys())
gr = [(a, a + 1, 0, 1) for a in range(0, n_panels)
] # just generate subplots - shape does not matter
axmap = OrderedDict(zip(sizer.keys(), gr))
P = PH.Plotter((n_panels, 1),
axmap=axmap,
label=True,
labeloffset=[-0.15, 0.08],
fontsize={
'tick': 8,
'label': 10,
'panel': 14
},
figsize=(5., 3.))
P.resize(sizer) # perform positioning magic
# P.axdict['A'].plot(np.ones(len(self.intvls[self.group_names[0]])), 1000./np.array(self.intvls[self.group_names[0]]),
# 'ko', markersize=4.0, label=self.group_names[0])
# P.axdict['A'].plot(1+np.ones(len(self.intvls[self.group_names[1]])), 1000./np.array(self.intvls[self.group_names[1]]),
# 'bs', markersize=4.0, label=self.group_names[1])
# P.axdict['B'].plot(np.ones(len(self.amps[self.group_names[0]])), self.amps[self.group_names[0]],
# 'ko', markerfacecolor='k', markeredgecolor='k', markersize=4.0, markeredgewidth=1)
# P.axdict['B'].plot(1.0 + np.ones(len(self.amps[self.group_names[1]])), self.amps[self.group_names[1]],
# 'bs', markerfacecolor='b', markeredgecolor='b', markersize=4.0, markeredgewidth=1)
# P.axdict['B'].plot(0.2 + np.ones(len(self.meanamps[self.group_names[0]])), self.meanamps[self.group_names[0]],
# 'ko', markerfacecolor='w', markeredgecolor='k', markersize=4.0, markeredgewidth=1)
# P.axdict['B'].plot(1.2 + np.ones(len(self.meanamps[self.group_names[1]])), self.meanamps[self.group_names[1]],
# 'bs', markerfacecolor='w', markeredgecolor='b', markersize=4.0, markeredgewidth=1)
for a in ['A', 'B', 'C']:
PH.formatTicks(P.axdict[a], font='Helvetica')
sns.swarmplot(x='Genotype',
y='Intvls',
data=self.pddata,
ax=P.axdict['A'])
sns.boxplot(x='Genotype',
y='Intvls',
data=self.pddata,
ax=P.axdict['A'],
color="0.8")
sns.swarmplot(x='Genotype',
y='Amp',
data=self.pddata,
ax=P.axdict['B'])
sns.boxplot(x='Genotype',
y='Amp',
data=self.pddata,
ax=P.axdict['B'],
color="0.8")
sns.swarmplot(x='Genotype',
y='MeanAmp',
data=self.pddata,
ax=P.axdict['C'])
sns.boxplot(x='Genotype',
y='MeanAmp',
data=self.pddata,
ax=P.axdict['C'],
color="0.8")
P.axdict['A'].set_ylim(0.0, 25.)
P.axdict['A'].set_ylabel('Event Frequency (Hz)')
P.axdict['B'].set_ylim(0.0, 30.)
P.axdict['B'].set_ylabel('Median Amplitude (pA)')
P.axdict['C'].set_ylabel('Mean Amplitude (pA)')
P.axdict['C'].set_ylim(0.0, 30.)
# P.axdict['A'].set_xlabel('Group')
# P.axdict['B'].set_xlabel('Group')
# P.axdict['A'].set_xlim(0.5, 2.5)
# P.axdict['B'].set_xlim(0.5, 2.5)
# P.axdict['B'].set_xlim(0.5, 2.5)
# P.axdict['A'].legend()
P.figure_handle.suptitle(self.filename.replace('_', '\_'))
mpl.savefig('msummary_%s.pdf' % self.experiment_id)
mpl.show()