def plot_iv_curve(self, ax=None):
# pylint: disable=E1103
title = '%s: IV Curve' % (self.cell_description or None)
if not ax:
f = QuantitiesFigure()
f.suptitle(title)
ax = f.add_subplot(1, 1, 1)
ax.set_xlabel('Injected Current')
ax.set_ylabel('SteadyStateVoltage')
V_in_mV = [
self.get_iv_point_steaddy_state(c).rescale('mV').magnitude
for c in self.currents
]
v = np.array(V_in_mV) * pq.mV
i = factorise_units_from_list(self.currents)
low_v = V_in_mV < self.v_regressor_limit if self.v_regressor_limit else range(
len(V_in_mV))
print 'i[low_v]', i[low_v]
print 'v[low_v]', v[low_v]
ax.plot(
i[low_v],
v[low_v],
)
ax.plot(
i[np.logical_not(low_v)],
v[np.logical_not(low_v)],
)
ax.plot(
i[np.logical_not(low_v)],
v[np.logical_not(low_v)],
)
# Plot the regressor:
i_units = unit('1:pA').units
v_units = unit('1:mV').units
iv = np.vstack(
(i.rescale(i_units).magnitude, v.rescale(v_units).magnitude)).T
if not len(iv[low_v, 0]):
return
(a_s, b_s, r, tt, stderr) = stats.linregress(iv[low_v, 0], iv[low_v,
1])
input_resistance = (a_s * (v_units / i_units)).rescale('MOhm')
reversal_potential = b_s * v_units
self.input_resistance = input_resistance
self.reversal_potential = reversal_potential
ax.plot(
i,
i * input_resistance + reversal_potential,
label="Fit: [V(mV) = %2.3f * I(pA) + %2.3f]" % (a_s, b_s) +
" \n[Input Resistance: %2.2fMOhm Reversal Potential: %2.2f mV" %
(input_resistance, reversal_potential))
ax.legend()
PM.save_figure(figname=title)
def plot_state_curve_summary(cls, alphabeta_chl, state, figsize):
fig = QuantitiesFigure(figsize=figsize)
fig.suptitle("InfTauInterpolated Channel - %s : %s"%(alphabeta_chl.name, state))
ax1 = fig.add_subplot(221)
ax2 = fig.add_subplot(222)
cls.plot_inf_tau_curves(ax1, ax2, alphabeta_chl, state)
ax3 = fig.add_subplot(223)
ax4 = fig.add_subplot(224)
cls.plot_alpha_beta_curves(ax3, ax4, alphabeta_chl, state)
return fig
def plot_state_curve_summary(cls, alphabeta_chl, state, figsize):
fig = QuantitiesFigure(figsize=figsize)
fig.suptitle("AlphaBeta Channel - %s : %s"%(alphabeta_chl.name, state))
ax1 = fig.add_subplot(221)
ax2 = fig.add_subplot(222)
cls.plot_alpha_beta_curves(ax1, ax2, alphabeta_chl, state)
ax3 = fig.add_subplot(223)
ax4 = fig.add_subplot(224)
cls.plot_inf_tau_curves(ax3, ax4, alphabeta_chl, state)
return fig
def PlotStateCurveSummary(cls, alphaBetaChl, state, figsize):
fig = QuantitiesFigure(figsize=figsize)
fig.suptitle("AlphaBeta Channel - %s : %s"%(alphaBetaChl.name, state))
ax1 = fig.add_subplot(221)
ax2 = fig.add_subplot(222)
cls.PlotAlphaBetaCurves(ax1, ax2, alphaBetaChl,state )
ax3 = fig.add_subplot(223)
ax4 = fig.add_subplot(224)
cls.PlotInfTauCurves(ax3, ax4, alphaBetaChl,state )
return fig
def plot_iv_curve(self, ax=None):
# pylint: disable=E1103
title = '%s: IV Curve' % (self.cell_description or None)
if not ax:
f = QuantitiesFigure()
f.suptitle(title)
ax = f.add_subplot(1, 1, 1)
ax.set_xlabel('Injected Current')
ax.set_ylabel('SteadyStateVoltage')
V_in_mV = [self.get_iv_point_steaddy_state(c).rescale('mV').magnitude for c in self.currents]
v = np.array(V_in_mV) * units.mV
i = morphforge.units.factorise_units_from_list(self.currents)
low_v = V_in_mV < self.v_regressor_limit if self.v_regressor_limit else range( len(V_in_mV))
print 'i[low_v]', i[low_v]
print 'v[low_v]', v[low_v]
ax.plot(i[low_v], v[low_v], )
ax.plot(i[np.logical_not(low_v)], v[np.logical_not(low_v)], )
ax.plot(i[np.logical_not(low_v)], v[np.logical_not(low_v)], )
# Plot the regressor:
i_units = qty('1:pA').units
v_units = qty('1:mV').units
iv = np.vstack((i.rescale(i_units).magnitude,
v.rescale(v_units).magnitude)).T
if not len(iv[low_v, 0]):
return
import scipy.stats as stats
(a_s, b_s, r, tt, stderr) = stats.linregress(iv[low_v, 0], iv[low_v, 1])
input_resistance = (a_s * (v_units / i_units)).rescale('MOhm')
reversal_potential = b_s * v_units
self.input_resistance = input_resistance
self.reversal_potential = reversal_potential
ax.plot(i, i*input_resistance + reversal_potential,'o-', label = "Fit: [V(mV) = %2.3f * I(pA) + %2.3f]"%(a_s, b_s) + " \n[Input Resistance: %2.2fMOhm Reversal Potential: %2.2f mV"%(input_resistance, reversal_potential) )
ax.legend()
PM.save_figure(figname=title)
def test_trace_method_traceout(src_trace, method_name, method_functor):
f = QuantitiesFigure(figsize=(6, 4))
f.suptitle("Testing Method: %s" % method_name)
ax1 = f.add_subplot(211)
ax2 = f.add_subplot(212)
ax1.plotTrace(src_trace, label="Original")
for (conv_type, conv_functor) in conversions:
tr_new = conv_functor(src_trace)
if not mf.TraceMethodCtrl.has_method(conv_type, method_name):
continue
ax2.plotTrace(method_functor(tr_new), label="%s:%s" % (conv_type.__name__, method_name))
ax1.legend()
ax2.legend()
return mrd.Section("Test: %s" % method_name, mrd.Image(f.fig, auto_adjust=False))
def plot_traces(self, ax=None):
title = '%s: (Voltage Responses to Current Injections)' \
% self.cell_description
if not ax:
f = QuantitiesFigure()
f.suptitle(title)
ax = f.add_subplot(1, 1, 1)
ax.set_xlabel('Time')
ax.set_ylabel('Voltage')
# Plot the traces
for i_inj in self.currents:
ax.plotTrace(self.get_trace(i_inj), label='i_inj: %s'
% i_inj)
# Add the regions:
ax.axvspan(self.tSteaddyStateStart, self.tSteaddyStateStop, facecolor='g', alpha=0.25)
ax.legend()
from mreorg.scriptplots import PM
PM.save_figure(figname=title)
def test_trace_method_traceout(src_trace, method_name, method_functor):
f = QuantitiesFigure(figsize=(6, 4))
f.suptitle('Testing Method: %s' % method_name)
ax1 = f.add_subplot(211)
ax2 = f.add_subplot(212)
ax1.plotTrace(src_trace, label='Original')
for (conv_type, conv_functor) in conversions:
tr_new = conv_functor(src_trace)
if not mf.TraceMethodCtrl.has_method(conv_type, method_name):
continue
ax2.plotTrace(method_functor(tr_new),
label='%s:%s' % (conv_type.__name__, method_name))
ax1.legend()
ax2.legend()
return mrd.Section('Test: %s' % method_name,
mrd.Image(f.fig, auto_adjust=False))
def plot_traces(self, ax=None):
title = '%s: (Voltage Responses to Current Injections)' \
% self.cell_description
if not ax:
f = QuantitiesFigure()
f.suptitle(title)
ax = f.add_subplot(1, 1, 1)
ax.set_xlabel('Time')
ax.set_ylabel('Voltage')
# Plot the traces
for i_inj in self.currents:
ax.plotTrace(self.get_trace(i_inj), label='i_inj: %s' % i_inj)
# Add the regions:
ax.axvspan(self.tSteaddyStateStart,
self.tSteaddyStateStop,
facecolor='g',
alpha=0.25)
ax.legend()
from mreorg.scriptplots import PM
PM.save_figure(figname=title)
class TagViewer(object):
MPL_AUTO_SHOW = True
_default_plot_specs = (
DefaultTagPlots.Voltage,
DefaultTagPlots.CurrentDensity,
DefaultTagPlots.Current,
DefaultTagPlots.Conductance,
DefaultTagPlots.ConductanceDensity,
DefaultTagPlots.StateVariable,
DefaultTagPlots.StateVariableTau,
DefaultTagPlots.StateVariableInf,
DefaultTagPlots.Event,
)
_default_fig_kwargs = {'figsize': (12, 8) }
_options_show_xlabel = ('only-once','all', False)
_options_show_xticklabels=('only-once','all', False)
_options_show_xticklabels_with_units=(True,False)
_options_show_xaxis_position = ('bottom','top')
def __init__(
self,
srcs,
plots=None,
additional_plots=None,
figtitle=None,
fig_kwargs=None,
show=True,
linkage=None,
timerange=None,
mpl_tight_bounds=False,
share_x_labels=True,
nxticks=4,
show_xlabel='only-once',
show_xticklabels='only-once',
show_xticklabels_with_units=True,
show_xaxis_position='bottom',
xticks=None
):
"""Plot a set of traces.
Keyword arguments:
plots --
srcs --
plots --
additional_plots --
figtitle --
fig_kwargs --
show --
linkage --
timerange --
mpl_tight_bounds --
share_x_labels --
nxticks=4,
show_xlabel -- which plots should the x-axis be displayed on.
show_xticklabels --
show_xticklabels_with_units --
show_xaxis_position --
xticks --
"""
if fig_kwargs is None:
fig_kwargs = self._default_fig_kwargs
self.linkage = linkage
if not is_iterable(srcs):
srcs = [srcs]
# For each type of input (in 'srcs'); this should return a list of traces:
self.all_trace_objs = []
self.all_event_set_objs = []
trace_extractors = {
SimulationResult: lambda obj: self.all_trace_objs.extend(obj.traces),
TraceFixedDT: lambda obj: self.all_trace_objs.append(obj),
TraceVariableDT: lambda obj: self.all_trace_objs.append(obj),
TracePiecewise: lambda obj: self.all_trace_objs.append(obj),
EventSet: lambda obj: self.all_event_set_objs.append(obj)
}
for obj in srcs:
tr_extractor = trace_extractors[type(obj)]
tr_extractor(obj)
# Use the new PlotSpec architecture:
# Filter out which plots are actually going to display something,
# and filter out the rest:
plots = plots if plots is not None else TagViewer._default_plot_specs
if additional_plots:
plots = tuple(list(plots) + list(additional_plots))
self.plot_specs = [plotspec for plotspec in plots if
[tr for tr in self.all_trace_objs if plotspec.addtrace_predicate(tr)] or \
[evset for evset in self.all_event_set_objs if plotspec.addeventset_predicate(evset)] \
]
self.fig_kwargs = fig_kwargs
self.figtitle = figtitle
self.mpl_tight_bounds = mpl_tight_bounds
self.timerange = timerange
self.share_x_labels = share_x_labels
self.nxticks = nxticks
# X-axis configuration:
self.show_xlabel = show_xlabel
self.show_xticklabels = show_xticklabels
self.show_xticklabels_with_units = show_xticklabels_with_units
self.show_xaxis_position = show_xaxis_position
self.xticks=xticks
assert self.show_xlabel in self._options_show_xlabel, 'Invalid'
assert self.show_xticklabels in self._options_show_xticklabels
assert self.show_xticklabels_with_units in self._options_show_xticklabels_with_units
assert self.show_xaxis_position in self._options_show_xaxis_position
if is_iterable( self.xticks ) and all( [isinstance(xtick, (int, float)) for xtick in self.xticks]):
self.xticks = [ xtick*pq.ms for xtick in self.xticks]
assert self.xticks is None or isinstance(self.xticks, int) or ( is_iterable(self.xticks) and [ unit(xtick) for xtick in self.xticks] )
self.fig = None
self.subaxes = []
self.create_figure()
if TagViewer.MPL_AUTO_SHOW and show:
import pylab
pylab.show()
def create_figure(self):
self.fig = QuantitiesFigure(**self.fig_kwargs)
# Add a title to the plot:
if self.figtitle:
self.fig.suptitle(self.figtitle)
# Work out what traces are on what graphs:
plotspec_to_traces = dict([(plot_spec, [tr for tr in self.all_trace_objs if plot_spec.addtrace_predicate(tr)]) for plot_spec in self.plot_specs ])
if self.linkage:
self.linkage.process(plotspec_to_traces)
n_plots = len(self.plot_specs)
for (i, plot_spec) in enumerate(self.plot_specs):
# Create the axis:
ax = self.fig.add_subplot(n_plots, 1, i + 1)
ax.set_xunit(pq.millisecond)
ax.set_xmargin(0.05)
ax.set_ymargin(0.05)
ax.set_xaxis_maxnlocator(self.nxticks)
# Leave the plotting to the tag-plot object
plot_spec.plot( ax=ax,
all_traces=self.all_trace_objs,
all_eventsets=self.all_event_set_objs,
time_range=self.timerange,
linkage=self.linkage,
#plot_xaxis_details=plot_xaxis_details,
show_xlabel = self.show_xlabel,
show_xticklabels = self.show_xticklabels,
show_xticklabels_with_units = self.show_xticklabels_with_units,
show_xaxis_position = self.show_xaxis_position,
is_top_plot = (i==0),
is_bottom_plot = (i==n_plots-1),
xticks = self.xticks
)
# Save the Axis:
self.subaxes.append(ax)
if self.mpl_tight_bounds:
import pylab
try:
pylab.tight_layout()
except AttributeError:
pass # This is version specfic
except ValueError:
pass # Top can't be less than bottom
class TagViewer(object):
MPL_AUTO_SHOW = True
_default_plot_specs = (
DefaultTagPlots.Voltage,
DefaultTagPlots.CurrentDensity,
DefaultTagPlots.Current,
DefaultTagPlots.Conductance,
DefaultTagPlots.ConductanceDensity,
DefaultTagPlots.StateVariable,
DefaultTagPlots.StateVariableTau,
DefaultTagPlots.StateVariableInf,
DefaultTagPlots.Event,
)
_default_fig_kwargs = {'figsize': (12, 8)}
_options_show_xlabel = ('only-once', 'all', False)
_options_show_xticklabels = ('only-once', 'all', False)
_options_show_xticklabels_with_units = (True, False)
_options_show_xaxis_position = ('bottom', 'top')
def __init__(self,
srcs,
plots=None,
additional_plots=None,
figtitle=None,
fig_kwargs=None,
show=True,
linkage=None,
timerange=None,
mpl_tight_bounds=False,
share_x_labels=True,
nxticks=4,
show_xlabel='only-once',
show_xticklabels='only-once',
show_xticklabels_with_units=True,
show_xaxis_position='bottom',
xticks=None):
"""Plot a set of traces.
Keyword arguments:
plots --
srcs --
plots --
additional_plots --
figtitle --
fig_kwargs --
show --
linkage --
timerange --
mpl_tight_bounds --
share_x_labels --
nxticks=4,
show_xlabel -- which plots should the x-axis be displayed on.
show_xticklabels --
show_xticklabels_with_units --
show_xaxis_position --
xticks --
"""
if fig_kwargs is None:
fig_kwargs = self._default_fig_kwargs
self.linkage = linkage
if not is_iterable(srcs):
srcs = [srcs]
# For each type of input (in 'srcs'); this should return a list of traces:
self.all_trace_objs = []
self.all_event_set_objs = []
trace_extractors = {
SimulationResult:
lambda obj: self.all_trace_objs.extend(obj.traces),
TraceFixedDT: lambda obj: self.all_trace_objs.append(obj),
TraceVariableDT: lambda obj: self.all_trace_objs.append(obj),
TracePiecewise: lambda obj: self.all_trace_objs.append(obj),
EventSet: lambda obj: self.all_event_set_objs.append(obj)
}
for obj in srcs:
tr_extractor = trace_extractors[type(obj)]
tr_extractor(obj)
# Use the new PlotSpec architecture:
# Filter out which plots are actually going to display something,
# and filter out the rest:
plots = plots if plots is not None else TagViewer._default_plot_specs
if additional_plots:
plots = tuple(list(plots) + list(additional_plots))
self.plot_specs = [plotspec for plotspec in plots if
[tr for tr in self.all_trace_objs if plotspec.addtrace_predicate(tr)] or \
[evset for evset in self.all_event_set_objs if plotspec.addeventset_predicate(evset)] \
]
self.fig_kwargs = fig_kwargs
self.figtitle = figtitle
self.mpl_tight_bounds = mpl_tight_bounds
self.timerange = timerange
self.share_x_labels = share_x_labels
self.nxticks = nxticks
# X-axis configuration:
self.show_xlabel = show_xlabel
self.show_xticklabels = show_xticklabels
self.show_xticklabels_with_units = show_xticklabels_with_units
self.show_xaxis_position = show_xaxis_position
self.xticks = xticks
assert self.show_xlabel in self._options_show_xlabel, 'Invalid'
assert self.show_xticklabels in self._options_show_xticklabels
assert self.show_xticklabels_with_units in self._options_show_xticklabels_with_units
assert self.show_xaxis_position in self._options_show_xaxis_position
if is_iterable(self.xticks) and all(
[isinstance(xtick, (int, float)) for xtick in self.xticks]):
self.xticks = [xtick * pq.ms for xtick in self.xticks]
assert self.xticks is None or isinstance(
self.xticks, int) or (is_iterable(self.xticks)
and [unit(xtick) for xtick in self.xticks])
self.fig = None
self.subaxes = []
self.create_figure()
if TagViewer.MPL_AUTO_SHOW and show:
import pylab
pylab.show()
def create_figure(self):
self.fig = QuantitiesFigure(**self.fig_kwargs)
# Add a title to the plot:
if self.figtitle:
self.fig.suptitle(self.figtitle)
# Work out what traces are on what graphs:
plotspec_to_traces = dict([(plot_spec, [
tr for tr in self.all_trace_objs
if plot_spec.addtrace_predicate(tr)
]) for plot_spec in self.plot_specs])
if self.linkage:
self.linkage.process(plotspec_to_traces)
n_plots = len(self.plot_specs)
for (i, plot_spec) in enumerate(self.plot_specs):
# Create the axis:
ax = self.fig.add_subplot(n_plots, 1, i + 1)
ax.set_xunit(pq.millisecond)
ax.set_xmargin(0.05)
ax.set_ymargin(0.05)
ax.set_xaxis_maxnlocator(self.nxticks)
# Leave the plotting to the tag-plot object
plot_spec.plot(
ax=ax,
all_traces=self.all_trace_objs,
all_eventsets=self.all_event_set_objs,
time_range=self.timerange,
linkage=self.linkage,
#plot_xaxis_details=plot_xaxis_details,
show_xlabel=self.show_xlabel,
show_xticklabels=self.show_xticklabels,
show_xticklabels_with_units=self.show_xticklabels_with_units,
show_xaxis_position=self.show_xaxis_position,
is_top_plot=(i == 0),
is_bottom_plot=(i == n_plots - 1),
xticks=self.xticks)
# Save the Axis:
self.subaxes.append(ax)
if self.mpl_tight_bounds:
import pylab
try:
pylab.tight_layout()
except AttributeError:
pass # This is version specfic
except ValueError:
pass # Top can't be less than bottom
class CellAnalysis_IVCurve(object):
def __init__(self, cell_functor, currents, cell_description=None, sim_functor=None, v_regressor_limit=None, sim_kwargs=None, plot_all=False):
self.cell_functor = cell_functor
self.v_regressor_limit = v_regressor_limit
self.fig=None
#Previously = qty("-30:mV")
self.sim_kwargs = sim_kwargs or {}
self.tCurrentInjStart = qty('50:ms')
self.tCurrentInjStop = qty('200:ms')
self.tSteaddyStateStart = qty('100:ms')
self.tSteaddyStateStop = qty('151:ms')
self.traces = {}
self.currents = currents
self.cell_description = cell_description or 'Unknown Cell'
self.input_resistance = qty('-1:MOhm')
if plot_all:
self.plot_all()
def plot_all(self):
self.plot_traces()
self.plot_iv_curve()
def _get_cc_simulation_trace(self, current):
if self.cell_functor:
env = NEURONEnvironment()
sim = env.Simulation(**self.sim_kwargs)
cell = self.cell_functor(sim=sim)
else:
assert False
soma_loc = cell.get_location('soma')
cc = sim.create_currentclamp(name='cclamp', amp=current,
dur=self.tCurrentInjStop - self.tCurrentInjStart,
delay=self.tCurrentInjStart, cell_location=soma_loc)
sim.record(cell, name='SomaVoltage', cell_location=soma_loc,
what=Cell.Recordables.MembraneVoltage,
description='Response to i_inj=%s ' % current)
res = sim.run()
return res.get_trace('SomaVoltage')
def get_trace(self, i_inj):
if not i_inj in self.traces:
self.traces[i_inj] = self._get_cc_simulation_trace(i_inj)
return self.traces[i_inj]
def get_iv_point_steaddy_state(self, i_inj):
return self.get_trace(i_inj).window(time_window=(self.tSteaddyStateStart, self.tSteaddyStateStop)).Mean()
def plot_traces(self, ax=None):
title = '%s: (Voltage Responses to Current Injections)' \
% self.cell_description
if not ax:
self.fig = QuantitiesFigure()
self.fig.suptitle(title)
ax = self.fig.add_subplot(1, 1, 1)
ax.set_xlabel('Time')
ax.set_ylabel('Voltage')
# Plot the traces
for i_inj in self.currents:
ax.plotTrace(self.get_trace(i_inj), label='i_inj: %s'
% i_inj)
# Add the regions:
ax.axvspan(self.tSteaddyStateStart, self.tSteaddyStateStop, facecolor='g', alpha=0.25)
ax.legend()
from mreorg.scriptplots import PM
PM.save_figure(figname=title)
def plot_iv_curve(self, ax=None):
# pylint: disable=E1103
title = '%s: IV Curve' % (self.cell_description or None)
if not ax:
f = QuantitiesFigure()
f.suptitle(title)
ax = f.add_subplot(1, 1, 1)
ax.set_xlabel('Injected Current')
ax.set_ylabel('SteadyStateVoltage')
V_in_mV = [self.get_iv_point_steaddy_state(c).rescale('mV').magnitude for c in self.currents]
v = np.array(V_in_mV) * units.mV
i = morphforge.units.factorise_units_from_list(self.currents)
low_v = V_in_mV < self.v_regressor_limit if self.v_regressor_limit else range( len(V_in_mV))
print 'i[low_v]', i[low_v]
print 'v[low_v]', v[low_v]
ax.plot(i[low_v], v[low_v], )
ax.plot(i[np.logical_not(low_v)], v[np.logical_not(low_v)], )
ax.plot(i[np.logical_not(low_v)], v[np.logical_not(low_v)], )
# Plot the regressor:
i_units = qty('1:pA').units
v_units = qty('1:mV').units
iv = np.vstack((i.rescale(i_units).magnitude,
v.rescale(v_units).magnitude)).T
if not len(iv[low_v, 0]):
return
import scipy.stats as stats
(a_s, b_s, r, tt, stderr) = stats.linregress(iv[low_v, 0], iv[low_v, 1])
input_resistance = (a_s * (v_units / i_units)).rescale('MOhm')
reversal_potential = b_s * v_units
self.input_resistance = input_resistance
self.reversal_potential = reversal_potential
ax.plot(i, i*input_resistance + reversal_potential,'o-', label = "Fit: [V(mV) = %2.3f * I(pA) + %2.3f]"%(a_s, b_s) + " \n[Input Resistance: %2.2fMOhm Reversal Potential: %2.2f mV"%(input_resistance, reversal_potential) )
ax.legend()
PM.save_figure(figname=title)
