def count_aps():
"""
Shows a result table with the number of action potentials (i.e
events whose potential is above 0 mV) in selected traces. If
no trace is selected, then the current trace is analyzed.
Returns:
False if document is not open.
"""
if not stf.check_doc():
print("Open file first")
return False
if len(stf.get_selected_indices()) == 0:
sel_trace = [stf.get_trace_index()]
else:
sel_trace = stf.get_selected_indices()
mytable = dict()
for trace in sel_trace:
tstart = 0
tend = stf.get_size_trace(trace) * stf.get_sampling_interval()
threshold = 0
spikes = count_events(tstart, tend, threshold, True, trace, True)
mytable["Trace %.3d" % trace] = spikes
stf.show_table(mytable)
return True
def count_aps():
"""
Shows a result table with the number of action potentials (i.e
events whose potential is above 0 mV) in selected traces. If
no trace is selected, then the current trace is analyzed.
Returns:
False if document is not open.
"""
if not stf.check_doc():
print("Open file first")
return False
if len( stf.get_selected_indices() )==0:
sel_trace = [ stf.get_trace_index()]
else:
sel_trace = stf.get_selected_indices()
mytable = dict()
for trace in sel_trace:
tstart = 0
tend = stf.get_size_trace(trace)*stf.get_sampling_interval()
threshold = 0
spikes = count_events(tstart, tend, threshold, True, trace, True)
mytable["Trace %.3d" %trace] = spikes
stf.show_table(mytable)
return True
def plot_traces(plotwindow=None, ichannel=0, vchannel=1):
"""
Show traces in a figure
Parameters
----------
plotwindow : (float, float), optional
Plot window (in ms from beginning of trace)
None for whole trace. Default: None
ichannel : int, optional
current channel number. Default: 0
vchannel : int, optional
voltage channel number. Default: 1
"""
import stf
if not stf.check_doc():
return None
nchannels = stf.get_size_recording()
if nchannels < 2:
sys.stderr.write(
"Function requires 2 channels (0: current; 1: voltage)\n")
return
dt = stf.get_sampling_interval()
fig = stf.mpl_panel(figsize=(12, 8)).fig
fig.clear()
gs = gridspec.GridSpec(4, 1)
ax_currents = stfio_plot.StandardAxis(
fig, gs[:3, 0], hasx=False, hasy=False)
ax_voltages = stfio_plot.StandardAxis(
fig, gs[3:, 0], hasx=False, hasy=False, sharex=ax_currents)
if plotwindow is not None:
istart = int(plotwindow[0]/dt)
istop = int(plotwindow[1]/dt)
else:
istart = 0
istop = None
for ntrace in range(stf.get_size_channel()):
stf.set_trace(ntrace)
stf.set_channel(ichannel)
trace = stf.get_trace()[istart:istop]
ax_currents.plot(np.arange(len(trace))*dt, trace)
# Measure pulse amplitude
stf.set_channel(vchannel)
trace = stf.get_trace()[istart:istop]
ax_voltages.plot(np.arange(len(trace))*dt, trace)
# Reset active channel
stf.set_channel(ichannel)
stfio_plot.plot_scalebars(
ax_currents, xunits=stf.get_xunits(), yunits=stf.get_yunits(channel=0))
stfio_plot.plot_scalebars(
ax_voltages, xunits=stf.get_xunits(), yunits=stf.get_yunits(channel=1))
def resistance( base_start, base_end, peak_start, peak_end, amplitude):
"""Calculates the resistance from a series of voltage clamp traces.
Keyword arguments:
base_start -- Starting index (zero-based) of the baseline cursors.
base_end -- End index (zero-based) of the baseline cursors.
peak_start -- Starting index (zero-based) of the peak cursors.
peak_end -- End index (zero-based) of the peak cursors.
amplitude -- Amplitude of the voltage command.
Returns:
The resistance.
"""
if not stf.check_doc():
print('Couldn\'t find an open file; aborting now.')
return 0
#A temporary array to calculate the average:
array = np.empty( (stf.get_size_channel(), stf.get_size_trace()) )
for n in range( 0, stf.get_size_channel() ):
# Add this trace to set:
array[n] = stf.get_trace( n )
# calculate average and create a new section from it:
stf.new_window( np.average(set, 0) )
# set peak cursors:
# -1 means all points within peak window.
if not stf.set_peak_mean(-1):
return 0
if not stf.set_peak_start(peak_start):
return 0
if not stf.set_peak_end(peak_end):
return 0
# set base cursors:
if not stf.set_base_start(base_start):
return 0
if not stf.set_base_end(base_end):
return 0
# measure everything:
stf.measure()
# calculate r_seal and return:
return amplitude / (stf.get_peak()-stf.get_base())
def resistance(base_start, base_end, peak_start, peak_end, amplitude):
"""Calculates the resistance from a series of voltage clamp traces.
Keyword arguments:
base_start -- Starting index (zero-based) of the baseline cursors.
base_end -- End index (zero-based) of the baseline cursors.
peak_start -- Starting index (zero-based) of the peak cursors.
peak_end -- End index (zero-based) of the peak cursors.
amplitude -- Amplitude of the voltage command.
Returns:
The resistance.
"""
if not stf.check_doc():
print('Couldn\'t find an open file; aborting now.')
return 0
#A temporary array to calculate the average:
array = np.empty((stf.get_size_channel(), stf.get_size_trace()))
for n in range(0, stf.get_size_channel()):
# Add this trace to set:
array[n] = stf.get_trace(n)
# calculate average and create a new section from it:
stf.new_window(np.average(set, 0))
# set peak cursors:
# -1 means all points within peak window.
if not stf.set_peak_mean(-1):
return 0
if not stf.set_peak_start(peak_start):
return 0
if not stf.set_peak_end(peak_end):
return 0
# set base cursors:
if not stf.set_base_start(base_start):
return 0
if not stf.set_base_end(base_end):
return 0
# measure everything:
stf.measure()
# calculate r_seal and return:
return amplitude / (stf.get_peak() - stf.get_base())
def analyze_iv(pulses, trace_start=0, factor=1.0):
"""Creates an IV for the currently active channel.
Keyword arguments:
pulses -- Number of pulses for the IV.
trace_start -- ZERO-BASED index of the first trace to be
used for the IV. Note that this is one less
than what is diplayed in the drop-down box.
factor -- Multiply result with an optional factor, typically
from some external scaling.
Returns:
True upon success, False otherwise.
"""
if (stf.check_doc() == False):
print("Couldn\'t find an open file; aborting now.")
return False
if (pulses < 1):
print("Number of pulses has to be greater or equal 1.")
return False
# create an empty array (will contain random numbers)
channel = list()
for m in range(pulses):
# A temporary array to calculate the average:
set = np.empty((int(
(stf.get_size_channel() - m - 1 - trace_start) / pulses) + 1,
stf.get_size_trace(trace_start + m)))
n_set = 0
for n in range(trace_start + m, stf.get_size_channel(), pulses):
# Add this trace to set:
set[n_set, :] = stf.get_trace(n)
n_set = n_set + 1
# calculate average and create a new section from it, multiply:
channel.append(np.average(set, 0) * factor)
stf.new_window_list(channel)
return True
def glu_iv(pulses=13, subtract_base=True):
"""Calculates an iv from a repeated series of fast application and
voltage pulses.
Keyword arguments:
pulses -- Number of pulses for the iv.
subtract_base -- If True (default), baseline will be subtracted.
Returns:
True if successful.
"""
# Some ugly definitions for the time being
# Cursors are in ms here.
gFitEnd = 330.6 # fit end cursor is variable
gFSelect = 0 # Monoexp
gDictSize = stf.leastsq_param_size(
gFSelect) + 2 # Parameters, chisqr, peak value
gBaseStart = 220.5 # Start and end of the baseline before the control pulse, in ms
gBaseEnd = 223.55
gPeakStart = 223.55 # Start and end of the peak cursors for the control pulse, in ms
gPeakEnd = 253.55
if (gDictSize < 0):
print('Couldn\'t retrieve function id=%d, aborting now.' % gFSelect)
return False
if (not (stf.check_doc())):
print('Couldn\'t find an open file; aborting now.')
return False
# analyse iv, subtract baseline if requested:
ivtools.analyze_iv(pulses)
if (subtract_base == True):
if (not (stf.set_base_start(gBaseStart, True))): return False
if (not (stf.set_base_end(gBaseEnd, True))): return False
stf.measure()
stf.select_all()
stf.subtract_base()
# set cursors:
if (not (stf.set_peak_start(gPeakStart, True))): return False
if (not (stf.set_peak_end(gPeakEnd, True))): return False
if (not (stf.set_base_start(gBaseStart, True))): return False
if (not (stf.set_base_end(gBaseEnd, True))): return False
if (not (stf.set_fit_end(gFitEnd, True))): return False
if (not (stf.set_peak_mean(3))): return False
if (not (stf.set_peak_direction("both"))): return False
# A list for dictionary keys and values:
dict_keys = []
dict_values = np.empty((gDictSize, stf.get_size_channel()))
firstpass = True
for n in range(0, stf.get_size_channel()):
if (stf.set_trace(n) == False):
print('Couldn\'t set a new trace; aborting now.')
return False
print('Analyzing trace %d of %d' % (n + 1, stf.get_size_channel()))
# set the fit window cursors:
if (not (stf.set_fit_start(stf.peak_index()))): return False
# Least-squares fitting:
p_dict = stf.leastsq(gFSelect)
if (p_dict == 0):
print('Couldn\'t perform a fit; aborting now.')
return False
# Create an empty list:
tempdict_entry = []
row = 0
for k, v in p_dict.iteritems():
if (firstpass == True):
dict_keys.append(k)
dict_values[row][n] = v
row = row + 1
if (firstpass):
dict_keys.append("Peak amplitude")
dict_values[row][n] = stf.get_peak() - stf.get_base()
firstpass = False
retDict = dict()
# Create the dictionary for the table:
entry = 0
for elem in dict_keys:
retDict[elem] = dict_values[entry].tolist()
entry = entry + 1
return stf.show_table_dictlist(retDict)
def plot_traces(plotwindow=None, ichannel=0, vchannel=1):
"""
Show traces in a figure
Parameters
----------
plotwindow : (float, float), optional
Plot window (in ms from beginning of trace)
None for whole trace. Default: None
ichannel : int, optional
current channel number. Default: 0
vchannel : int, optional
voltage channel number. Default: 1
"""
import stf
if not stf.check_doc():
return None
nchannels = stf.get_size_recording()
if nchannels < 2:
sys.stderr.write(
"Function requires 2 channels (0: current; 1: voltage)\n")
return
dt = stf.get_sampling_interval()
fig = stf.mpl_panel(figsize=(12, 8)).fig
fig.clear()
gs = gridspec.GridSpec(4, 1)
ax_currents = stfio_plot.StandardAxis(fig,
gs[:3, 0],
hasx=False,
hasy=False)
ax_voltages = stfio_plot.StandardAxis(fig,
gs[3:, 0],
hasx=False,
hasy=False,
sharex=ax_currents)
if plotwindow is not None:
istart = int(plotwindow[0] / dt)
istop = int(plotwindow[1] / dt)
else:
istart = 0
istop = None
for ntrace in range(stf.get_size_channel()):
stf.set_trace(ntrace)
stf.set_channel(ichannel)
trace = stf.get_trace()[istart:istop]
ax_currents.plot(np.arange(len(trace)) * dt, trace)
# Measure pulse amplitude
stf.set_channel(vchannel)
trace = stf.get_trace()[istart:istop]
ax_voltages.plot(np.arange(len(trace)) * dt, trace)
# Reset active channel
stf.set_channel(ichannel)
stfio_plot.plot_scalebars(ax_currents,
xunits=stf.get_xunits(),
yunits=stf.get_yunits(channel=0))
stfio_plot.plot_scalebars(ax_voltages,
xunits=stf.get_xunits(),
yunits=stf.get_yunits(channel=1))
def iv(peakwindow=None,
basewindow=None,
pulsewindow=None,
erev=None,
peakmode="both",
ichannel=0,
vchannel=1,
exclude=None):
"""
Compute and plot an IV curve for currents
Parameters
----------
peakwindow : (float, float), optional
Window for peak measurement (time in ms from beginning of sweep)
None for current cursor settings. Default: None
basewindow : (float, float), optional
Window for baseline measurement (time in ms from beginning of sweep)
None for current cursor settings. Default: None
pulsewindow : (float, float), optional
Window for voltage pulse measurement (time in ms from beginning of sweep)
None for current cursor settings. Default: None
erev : float, optional
End of v clamp pulse in ms or None to determine automatically.
Default: None
peakmode : string, optional
Peak direction - one of "up", "down", "both" or "mean". Default: "up"
ichannel : int, optional
current channel number. Default: 0
vchannel : int, optional
voltage channel number. Default: 1
exclude : list of ints, optional
List of trace indices to be excluded from the analysis. Default: None
Returns
-------
v_commands : numpy.ndarray
Command voltages
ipeaks : numpy.ndarray
Peak currents
gpeaks : numpy.ndarray
Peak normalized conductances
g_fit : numpy.ndarray
Half-maximal voltage and slope of best-fit Boltzmann function
"""
import stf
if not stf.check_doc():
return None
nchannels = stf.get_size_recording()
if nchannels < 2:
sys.stderr.write(
"Function requires 2 channels (0: current; 1: voltage)\n")
return
dt = stf.get_sampling_interval()
olddirection = stf.get_peak_direction()
v_commands = []
ipeaks = []
if basewindow is not None:
stf.base.cursor_time = basewindow
fig = stf.mpl_panel(figsize=(12, 8)).fig
fig.clear()
gs = gridspec.GridSpec(4, 8)
ax_currents = stfio_plot.StandardAxis(fig,
gs[:3, :4],
hasx=False,
hasy=False)
ax_voltages = stfio_plot.StandardAxis(fig,
gs[3:, :4],
hasx=False,
hasy=False,
sharex=ax_currents)
for ntrace in range(stf.get_size_channel()):
if exclude is not None:
if ntrace in exclude:
continue
stf.set_trace(ntrace)
stf.set_channel(ichannel)
trace = stf.get_trace()
ax_currents.plot(np.arange(len(trace)) * dt, trace)
# Measure only downward peaks (inward currents)
if peakmode is "mean":
stf.set_peak_direction("up")
stf.set_peak_mean(-1)
else:
stf.set_peak_direction(peakmode)
# Set peak computation to single sampling point
stf.set_peak_mean(1)
if peakwindow is not None:
stf.peak.cursor_time = peakwindow
stf.measure()
if basewindow is not None:
ipeaks.append(stf.peak.value - stf.base.value)
else:
ipeaks.append(stf.peak.value)
# Measure pulse amplitude
stf.set_channel(vchannel)
trace = stf.get_trace()
ax_voltages.plot(np.arange(len(trace)) * dt, trace)
stf.set_peak_direction("up")
stf.set_peak_mean(-1)
if pulsewindow is not None:
stf.peak.cursor_time = pulsewindow
stf.measure()
v_commands.append(stf.peak.value)
stfio_plot.plot_scalebars(ax_currents,
xunits=stf.get_xunits(),
yunits=stf.get_yunits(channel=0))
stfio_plot.plot_scalebars(ax_voltages,
xunits=stf.get_xunits(),
yunits=stf.get_yunits(channel=1))
v_commands = np.array(v_commands)
ipeaks = np.array(ipeaks)
if erev is None:
# Find first zero crossing in ipeaks:
for npulse in range(ipeaks.shape[0] - 1):
if np.sign(ipeaks[npulse]) != np.sign(ipeaks[npulse + 1]):
# linear interpolation
m1 = (ipeaks[npulse + 1] - ipeaks[npulse]) / (
v_commands[npulse + 1] - v_commands[npulse])
c1 = ipeaks[npulse] - m1 * v_commands[npulse]
erev = -c1 / m1
break
if erev is None:
sys.stderr.write(
"Could not determine reversal potential. Aborting now\n")
return None
# Reset peak computation to single sampling point
stf.set_peak_mean(1)
stf.set_peak_direction(olddirection)
# Reset active channel
stf.set_channel(ichannel)
# Compute conductances:
gpeaks, g_fit = gv(ipeaks, v_commands, erev)
ax_ipeaks = plot_iv(ipeaks, v_commands, stf.get_yunits(channel=ichannel),
stf.get_yunits(channel=1), fig, 222)
ax_ipeaks.set_title("Peak current")
ax_gpeaks = plot_gv(gpeaks, v_commands, stf.get_yunits(channel=vchannel),
g_fit, fig, 224)
ax_gpeaks.set_title("Peak conductance")
stf.show_table_dictlist({
"Voltage ({0})".format(stf.get_yunits(channel=vchannel)):
v_commands.tolist(),
"Peak current ({0})".format(stf.get_yunits(channel=ichannel)):
ipeaks.tolist(),
"Peak conductance (g/g_max)":
gpeaks.tolist(),
})
return v_commands, ipeaks, gpeaks, g_fit
def timeconstants(fitwindow, pulsewindow, ichannel=0, vchannel=1):
"""
Compute and plot decay time constants
Parameters
----------
fitwindow : (float, float), optional
Window for fitting time constant (time in ms from beginning of sweep)
None for current cursor settings. Default: None
pulsewindow : (float, float), optional
Window for voltage pulse measurement (time in ms from beginning of sweep)
None for current cursor settings. Default: None
ichannel : int, optional
current channel number. Default: 0
vchannel : int, optional
voltage channel number. Default: 1
Returns
-------
v_commands : numpy.ndarray
Command voltages
taus : numpy.ndarray
Time constants
"""
import stf
if not stf.check_doc():
return None
nchannels = stf.get_size_recording()
if nchannels < 2:
sys.stderr.write(
"Function requires 2 channels (0: current; 1: voltage)\n")
return
dt = stf.get_sampling_interval()
v_commands = []
taus = []
fig = stf.mpl_panel(figsize=(12, 8)).fig
fig.clear()
gs = gridspec.GridSpec(4, 8)
ax_currents = stfio_plot.StandardAxis(fig,
gs[:3, :4],
hasx=False,
hasy=False)
ax_voltages = stfio_plot.StandardAxis(fig,
gs[3:, :4],
hasx=False,
hasy=False,
sharex=ax_currents)
for ntrace in range(stf.get_size_channel()):
stf.set_trace(ntrace)
stf.set_channel(ichannel)
trace = stf.get_trace()
ax_currents.plot(np.arange(len(trace)) * dt, trace)
if fitwindow is not None:
stf.fit.cursor_time = fitwindow
res = stf.leastsq(0, False)
taus.append(res['Tau_0'])
# Measure pulse amplitude
stf.set_channel(vchannel)
trace = stf.get_trace()
ax_voltages.plot(np.arange(len(trace)) * dt, trace)
stf.set_peak_direction("up")
stf.set_peak_mean(-1)
if pulsewindow is not None:
stf.peak.cursor_time = pulsewindow
stf.measure()
v_commands.append(stf.peak.value)
stfio_plot.plot_scalebars(ax_currents,
xunits=stf.get_xunits(),
yunits=stf.get_yunits(channel=ichannel))
stfio_plot.plot_scalebars(ax_voltages,
xunits=stf.get_xunits(),
yunits=stf.get_yunits(channel=vchannel))
v_commands = np.array(v_commands)
taus = np.array(taus)
ax_taus = plot_iv(taus, v_commands, "ms", stf.get_yunits(channel=vchannel),
fig, 122)
# Reset peak computation to single sampling point
stf.set_peak_mean(1)
# Reset active channel
stf.set_channel(ichannel)
# Compute conductances:
stf.show_table_dictlist({
"Voltage ({0})".format(stf.get_yunits(channel=vchannel)):
v_commands.tolist(),
"Taus (ms)":
taus.tolist(),
})
return v_commands, taus
def glu_iv( pulses = 13, subtract_base=True ):
"""Calculates an iv from a repeated series of fast application and
voltage pulses.
Keyword arguments:
pulses -- Number of pulses for the iv.
subtract_base -- If True (default), baseline will be subtracted.
Returns:
True if successful.
"""
# Some ugly definitions for the time being
# Cursors are in ms here.
gFitEnd = 330.6 # fit end cursor is variable
gFSelect = 0 # Monoexp
gDictSize = stf.leastsq_param_size( gFSelect ) + 2 # Parameters, chisqr, peak value
gBaseStart = 220.5 # Start and end of the baseline before the control pulse, in ms
gBaseEnd = 223.55
gPeakStart = 223.55 # Start and end of the peak cursors for the control pulse, in ms
gPeakEnd = 253.55
if ( gDictSize < 0 ):
print('Couldn\'t retrieve function id=%d, aborting now.'%gFSelect)
return False
if ( not(stf.check_doc()) ):
print('Couldn\'t find an open file; aborting now.')
return False
# analyse iv, subtract baseline if requested:
ivtools.analyze_iv( pulses )
if ( subtract_base == True ):
if ( not(stf.set_base_start( gBaseStart, True )) ): return False
if ( not(stf.set_base_end( gBaseEnd, True )) ): return False
stf.measure()
stf.select_all()
stf.subtract_base()
# set cursors:
if ( not(stf.set_peak_start( gPeakStart, True )) ): return False
if ( not(stf.set_peak_end( gPeakEnd, True )) ): return False
if ( not(stf.set_base_start( gBaseStart, True )) ): return False
if ( not(stf.set_base_end( gBaseEnd, True )) ): return False
if ( not(stf.set_fit_end( gFitEnd, True )) ): return False
if ( not(stf.set_peak_mean( 3 )) ): return False
if ( not(stf.set_peak_direction( "both" )) ): return False
# A list for dictionary keys and values:
dict_keys = []
dict_values = np.empty( (gDictSize, stf.get_size_channel()) )
firstpass = True
for n in range( 0, stf.get_size_channel() ):
if ( stf.set_trace( n ) == False ):
print('Couldn\'t set a new trace; aborting now.')
return False
print('Analyzing trace %d of %d'%( n+1, stf.get_size_channel() ) )
# set the fit window cursors:
if ( not(stf.set_fit_start( stf.peak_index() )) ): return False
# Least-squares fitting:
p_dict = stf.leastsq( gFSelect )
if ( p_dict == 0 ):
print('Couldn\'t perform a fit; aborting now.')
return False
# Create an empty list:
tempdict_entry = []
row = 0
for k, v in p_dict.iteritems():
if ( firstpass == True ):
dict_keys.append( k )
dict_values[row][n] = v
row = row+1
if ( firstpass ):
dict_keys.append( "Peak amplitude" )
dict_values[row][n] = stf.get_peak()-stf.get_base()
firstpass = False
retDict = dict()
# Create the dictionary for the table:
entry = 0
for elem in dict_keys:
retDict[ elem ] = dict_values[entry].tolist()
entry = entry+1
return stf.show_table_dictlist( retDict )
def iv(peakwindow=None, basewindow=None, pulsewindow=None,
erev=None, peakmode="both", ichannel=0, vchannel=1,
exclude=None):
"""
Compute and plot an IV curve for currents
Parameters
----------
peakwindow : (float, float), optional
Window for peak measurement (time in ms from beginning of sweep)
None for current cursor settings. Default: None
basewindow : (float, float), optional
Window for baseline measurement (time in ms from beginning of sweep)
None for current cursor settings. Default: None
pulsewindow : (float, float), optional
Window for voltage pulse measurement (time in ms from beginning of sweep)
None for current cursor settings. Default: None
erev : float, optional
End of v clamp pulse in ms or None to determine automatically.
Default: None
peakmode : string, optional
Peak direction - one of "up", "down", "both" or "mean". Default: "up"
ichannel : int, optional
current channel number. Default: 0
vchannel : int, optional
voltage channel number. Default: 1
exclude : list of ints, optional
List of trace indices to be excluded from the analysis. Default: None
Returns
-------
v_commands : numpy.ndarray
Command voltages
ipeaks : numpy.ndarray
Peak currents
gpeaks : numpy.ndarray
Peak normalized conductances
g_fit : numpy.ndarray
Half-maximal voltage and slope of best-fit Boltzmann function
"""
import stf
if not stf.check_doc():
return None
nchannels = stf.get_size_recording()
if nchannels < 2:
sys.stderr.write(
"Function requires 2 channels (0: current; 1: voltage)\n")
return
dt = stf.get_sampling_interval()
olddirection = stf.get_peak_direction()
v_commands = []
ipeaks = []
if basewindow is not None:
stf.base.cursor_time = basewindow
fig = stf.mpl_panel(figsize=(12, 8)).fig
fig.clear()
gs = gridspec.GridSpec(4, 8)
ax_currents = stfio_plot.StandardAxis(
fig, gs[:3, :4], hasx=False, hasy=False)
ax_voltages = stfio_plot.StandardAxis(
fig, gs[3:, :4], hasx=False, hasy=False, sharex=ax_currents)
for ntrace in range(stf.get_size_channel()):
if exclude is not None:
if ntrace in exclude:
continue
stf.set_trace(ntrace)
stf.set_channel(ichannel)
trace = stf.get_trace()
ax_currents.plot(np.arange(len(trace))*dt, trace)
# Measure only downward peaks (inward currents)
if peakmode is "mean":
stf.set_peak_direction("up")
stf.set_peak_mean(-1)
else:
stf.set_peak_direction(peakmode)
# Set peak computation to single sampling point
stf.set_peak_mean(1)
if peakwindow is not None:
stf.peak.cursor_time = peakwindow
stf.measure()
if basewindow is not None:
ipeaks.append(stf.peak.value-stf.base.value)
else:
ipeaks.append(stf.peak.value)
# Measure pulse amplitude
stf.set_channel(vchannel)
trace = stf.get_trace()
ax_voltages.plot(np.arange(len(trace))*dt, trace)
stf.set_peak_direction("up")
stf.set_peak_mean(-1)
if pulsewindow is not None:
stf.peak.cursor_time = pulsewindow
stf.measure()
v_commands.append(stf.peak.value)
stfio_plot.plot_scalebars(
ax_currents, xunits=stf.get_xunits(), yunits=stf.get_yunits(channel=0))
stfio_plot.plot_scalebars(
ax_voltages, xunits=stf.get_xunits(), yunits=stf.get_yunits(channel=1))
v_commands = np.array(v_commands)
ipeaks = np.array(ipeaks)
if erev is None:
# Find first zero crossing in ipeaks:
for npulse in range(ipeaks.shape[0]-1):
if np.sign(ipeaks[npulse]) != np.sign(ipeaks[npulse+1]):
# linear interpolation
m1 = (ipeaks[npulse+1]-ipeaks[npulse]) / (
v_commands[npulse+1]-v_commands[npulse])
c1 = ipeaks[npulse] - m1*v_commands[npulse]
erev = -c1/m1
break
if erev is None:
sys.stderr.write(
"Could not determine reversal potential. Aborting now\n")
return None
# Reset peak computation to single sampling point
stf.set_peak_mean(1)
stf.set_peak_direction(olddirection)
# Reset active channel
stf.set_channel(ichannel)
# Compute conductances:
gpeaks, g_fit = gv(ipeaks, v_commands, erev)
ax_ipeaks = plot_iv(
ipeaks, v_commands, stf.get_yunits(channel=ichannel),
stf.get_yunits(channel=1), fig, 222)
ax_ipeaks.set_title("Peak current")
ax_gpeaks = plot_gv(
gpeaks, v_commands, stf.get_yunits(channel=vchannel),
g_fit, fig, 224)
ax_gpeaks.set_title("Peak conductance")
stf.show_table_dictlist({
"Voltage ({0})".format(
stf.get_yunits(channel=vchannel)): v_commands.tolist(),
"Peak current ({0})".format(
stf.get_yunits(channel=ichannel)): ipeaks.tolist(),
"Peak conductance (g/g_max)": gpeaks.tolist(),
})
return v_commands, ipeaks, gpeaks, g_fit
def timeconstants(fitwindow, pulsewindow, ichannel=0, vchannel=1):
"""
Compute and plot decay time constants
Parameters
----------
fitwindow : (float, float), optional
Window for fitting time constant (time in ms from beginning of sweep)
None for current cursor settings. Default: None
pulsewindow : (float, float), optional
Window for voltage pulse measurement (time in ms from beginning of sweep)
None for current cursor settings. Default: None
ichannel : int, optional
current channel number. Default: 0
vchannel : int, optional
voltage channel number. Default: 1
Returns
-------
v_commands : numpy.ndarray
Command voltages
taus : numpy.ndarray
Time constants
"""
import stf
if not stf.check_doc():
return None
nchannels = stf.get_size_recording()
if nchannels < 2:
sys.stderr.write(
"Function requires 2 channels (0: current; 1: voltage)\n")
return
dt = stf.get_sampling_interval()
v_commands = []
taus = []
fig = stf.mpl_panel(figsize=(12, 8)).fig
fig.clear()
gs = gridspec.GridSpec(4, 8)
ax_currents = stfio_plot.StandardAxis(
fig, gs[:3, :4], hasx=False, hasy=False)
ax_voltages = stfio_plot.StandardAxis(
fig, gs[3:, :4], hasx=False, hasy=False, sharex=ax_currents)
for ntrace in range(stf.get_size_channel()):
stf.set_trace(ntrace)
stf.set_channel(ichannel)
trace = stf.get_trace()
ax_currents.plot(np.arange(len(trace))*dt, trace)
if fitwindow is not None:
stf.fit.cursor_time = fitwindow
res = stf.leastsq(0, False)
taus.append(res['Tau_0'])
# Measure pulse amplitude
stf.set_channel(vchannel)
trace = stf.get_trace()
ax_voltages.plot(np.arange(len(trace))*dt, trace)
stf.set_peak_direction("up")
stf.set_peak_mean(-1)
if pulsewindow is not None:
stf.peak.cursor_time = pulsewindow
stf.measure()
v_commands.append(stf.peak.value)
stfio_plot.plot_scalebars(
ax_currents, xunits=stf.get_xunits(),
yunits=stf.get_yunits(channel=ichannel))
stfio_plot.plot_scalebars(
ax_voltages, xunits=stf.get_xunits(),
yunits=stf.get_yunits(channel=vchannel))
v_commands = np.array(v_commands)
taus = np.array(taus)
ax_taus = plot_iv(
taus, v_commands, "ms",
stf.get_yunits(channel=vchannel), fig, 122)
# Reset peak computation to single sampling point
stf.set_peak_mean(1)
# Reset active channel
stf.set_channel(ichannel)
# Compute conductances:
stf.show_table_dictlist({
"Voltage ({0})".format(
stf.get_yunits(channel=vchannel)): v_commands.tolist(),
"Taus (ms)": taus.tolist(),
})
return v_commands, taus
