def parse_nids(self, nids):
"""Convert list of nids to list of neurons"""
r = self.experiment.r
if nids == None:
nids = sorted(r.n) # use active neurons
elif nids == 'quiet':
nids = sorted(r.qn) # use quiet neurons
elif nids == 'all':
nids = sorted(r.alln) # use all neurons
else:
nids = tolist(nids) # use specified nids
neurons = [r.alln[nid] if nid in r.alln else None for nid in nids]
return nids, neurons
def parse_nids(self, nids):
"""Convert list of nids to list of neurons"""
r = self.experiment.r
if nids == None:
nids = sorted(r.n.keys()) # use active neurons
elif nids == 'quiet':
nids = sorted(r.qn.keys()) # use quiet neurons
elif nids == 'all':
nids = sorted(r.alln.keys()) # use all neurons
else:
nids = tolist(nids) # use specified nids
neurons = [ r.alln[nid] if nid in r.alln else None for nid in nids ]
return nids, neurons
def load(self, tracknames=None):
treestr = self.level*TAB + self.id + '/'
# print string to tree hierarchy and screen
self.writetree(treestr + '\n')
print(treestr)
if tracknames != None:
tracknames = tolist(tracknames)
dirnames = tracknames
else:
# all track folder names for this animal:
dirnames = [ dirname for dirname in os.listdir(self.path)
if os.path.isdir(os.path.join(self.path, dirname))
and dirname.lower().startswith('tr') ]
dirnames.sort() # alphabetical order
for dirname in dirnames:
path = os.path.join(self.path, dirname)
track = Track(path, animal=self)
track.load()
self.tr[track.id] = track
self.__setattr__('tr' + str(track.id), track) # add shortcut attrib
def load(self, tracknames=None):
treestr = self.level * TAB + self.id + '/'
# print string to tree hierarchy and screen
self.writetree(treestr + '\n')
print(treestr)
if tracknames != None:
tracknames = tolist(tracknames)
dirnames = tracknames
else:
# all track folder names for this animal:
dirnames = [
dirname for dirname in os.listdir(self.path)
if os.path.isdir(os.path.join(self.path, dirname))
and dirname.lower().startswith('tr')
]
dirnames.sort() # alphabetical order
for dirname in dirnames:
path = os.path.join(self.path, dirname)
track = Track(path, animal=self)
track.load()
self.tr[track.id] = track
self.__setattr__('tr' + str(track.id),
track) # add shortcut attrib
def plot(self, t0=None, t1=None, chanis=None, gain=1, c='k', alpha=1.0, yunits='um',
yticks=None, title=True, xlabel=True, relative2t0=False, lim2stim=False,
scalebar=True, lw=4, figsize=(20, 6.5)):
"""Plot chanis of LFP data between t0 and t1 in sec. Unfortunatley, setting an alpha <
1 doesn't seem to reveal detail when a line obscures itself, such as when plotting a
very long time series. relative2t0 controls whether to plot relative to t0, or
relative to start of ADC clock. lim2stim limits the time range only to when a stimulus
was on screen, i.e. to the outermost times of non-NULL din. If only one chan is
requested, it's plotted on a mV scale instead of a spatial scale."""
self.get_data()
ts = self.get_tssec() # full set of timestamps, in sec
if t0 == None:
t0, t1 = ts[0], ts[-1]
if t1 == None:
t1 = t0 + 10 # 10 sec window
if chanis == None:
chanis = range(len(self.chans)) # all chans
if lim2stim:
t0, t1 = self.apply_lim2stim(t0, t1)
t0i, t1i = ts.searchsorted((t0, t1))
ts = ts[t0i:t1i] # constrained set of timestamps, in sec
chanis = tolist(chanis)
nchans = len(chanis)
# grab desired channels and time range:
data = self.data[chanis][:, t0i:t1i]
if nchans > 1: # convert uV to um:
totalgain = self.UV2UM * gain
data = data * totalgain
else: # convert uV to mV:
data = data / 1000
yunits = 'mV'
nt = len(ts)
assert nt == data.shape[1]
if relative2t0:
# convert ts to time from t0, otherwise plot time from start of ADC clock:
ts -= t0
x = np.tile(ts, nchans)
x.shape = nchans, nt
segments = np.zeros((nchans, nt, 2)) # x vals in col 0, yvals in col 1
segments[:, :, 0] = x
if nchans > 1:
segments[:, :, 1] = -data # set to -ve here because of invert_yaxis() below
else:
segments[:, :, 1] = data
if nchans > 1: # add y offsets:
maxypos = 0
for chanii, chani in enumerate(chanis):
chan = self.chans[chani]
ypos = self.chanpos[chan][1] # in um
segments[chanii, :, 1] += ypos # vertical distance below top of probe
maxypos = max(maxypos, ypos)
if yunits == 'mm': # convert from um to mm
segments[:, :, 1] /= 1000
maxypos = maxypos / 1000 # convert from int to float
totalgain = totalgain / 1000
lc = LineCollection(segments, linewidth=1, linestyle='-', colors=c, alpha=alpha,
antialiased=True, visible=True)
f = pl.figure(figsize=figsize)
a = f.add_subplot(111)
a.add_collection(lc) # add to axes' pool of LCs
if scalebar: # add vertical scale bar at end of last channel to represent 1 mV:
if nchans > 1:
ymin, ymax = maxypos-500*totalgain, maxypos+500*totalgain # +/- 0.5 mV
else:
ymin, ymax = -0.5, 0.5 # mV
a.vlines(ts.max()*0.99, ymin, ymax, lw=lw, colors='e')
a.autoscale(enable=True, tight=True)
# depending on relative2t0 above, x=0 represents either t0 or time ADC clock started:
a.set_xlim(xmin=0)
if nchans > 1:
a.invert_yaxis() # for spatial scale
if yticks != None:
a.set_yticks(yticks)
# turn off annoying "+2.41e3" type offset on x axis:
formatter = mpl.ticker.ScalarFormatter(useOffset=False)
a.xaxis.set_major_formatter(formatter)
if xlabel:
a.set_xlabel("time (s)")
if yunits == 'um':
a.set_ylabel("depth ($\mu$m)")
elif yunits == 'mm':
a.set_ylabel("depth (mm)")
elif yunits == 'mV':
a.set_ylabel("LFP (mV)")
titlestr = lastcmd()
gcfm().window.setWindowTitle(titlestr)
if title:
a.set_title(titlestr)
a.text(0.998, 0.99, '%s' % self.r.name, transform=a.transAxes,
horizontalalignment='right', verticalalignment='top')
f.tight_layout(pad=0.3) # crop figure to contents
self.f = f
return self
def plot(self,
t0=None,
t1=None,
chanis=None,
gain=1,
c='k',
alpha=1.0,
yunits='um',
yticks=None,
title=True,
xlabel=True,
relative2t0=False,
lim2stim=False,
scalebar=True,
lw=4,
figsize=(20, 6.5)):
"""Plot chanis of LFP data between t0 and t1 in sec. Unfortunatley, setting an alpha <
1 doesn't seem to reveal detail when a line obscures itself, such as when plotting a
very long time series. relative2t0 controls whether to plot relative to t0, or
relative to start of ADC clock. lim2stim limits the time range only to when a stimulus
was on screen, i.e. to the outermost times of non-NULL din. If only one chan is
requested, it's plotted on a mV scale instead of a spatial scale."""
self.get_data()
ts = self.get_tssec() # full set of timestamps, in sec
if t0 == None:
t0, t1 = ts[0], ts[-1]
if t1 == None:
t1 = t0 + 10 # 10 sec window
if chanis == None:
chanis = range(len(self.chans)) # all chans
if lim2stim:
t0, t1 = self.apply_lim2stim(t0, t1)
t0i, t1i = ts.searchsorted((t0, t1))
ts = ts[t0i:t1i] # constrained set of timestamps, in sec
chanis = tolist(chanis)
nchans = len(chanis)
# grab desired channels and time range:
data = self.data[chanis][:, t0i:t1i]
if nchans > 1: # convert uV to um:
totalgain = self.UV2UM * gain
data = data * totalgain
else: # convert uV to mV:
data = data / 1000
yunits = 'mV'
nt = len(ts)
assert nt == data.shape[1]
if relative2t0:
# convert ts to time from t0, otherwise plot time from start of ADC clock:
ts -= t0
x = np.tile(ts, nchans)
x.shape = nchans, nt
segments = np.zeros((nchans, nt, 2)) # x vals in col 0, yvals in col 1
segments[:, :, 0] = x
if nchans > 1:
segments[:, :,
1] = -data # set to -ve here because of invert_yaxis() below
else:
segments[:, :, 1] = data
if nchans > 1: # add y offsets:
maxypos = 0
for chanii, chani in enumerate(chanis):
chan = self.chans[chani]
ypos = self.chanpos[chan][1] # in um
segments[chanii, :,
1] += ypos # vertical distance below top of probe
maxypos = max(maxypos, ypos)
if yunits == 'mm': # convert from um to mm
segments[:, :, 1] /= 1000
maxypos = maxypos / 1000 # convert from int to float
totalgain = totalgain / 1000
lc = LineCollection(segments,
linewidth=1,
linestyle='-',
colors=c,
alpha=alpha,
antialiased=True,
visible=True)
f = pl.figure(figsize=figsize)
a = f.add_subplot(111)
a.add_collection(lc) # add to axes' pool of LCs
if scalebar: # add vertical scale bar at end of last channel to represent 1 mV:
if nchans > 1:
ymin, ymax = maxypos - 500 * totalgain, maxypos + 500 * totalgain # +/- 0.5 mV
else:
ymin, ymax = -0.5, 0.5 # mV
a.vlines(ts.max() * 0.99, ymin, ymax, lw=lw, colors='e')
a.autoscale(enable=True, tight=True)
# depending on relative2t0 above, x=0 represents either t0 or time ADC clock started:
a.set_xlim(xmin=0)
if nchans > 1:
a.invert_yaxis() # for spatial scale
if yticks != None:
a.set_yticks(yticks)
# turn off annoying "+2.41e3" type offset on x axis:
formatter = mpl.ticker.ScalarFormatter(useOffset=False)
a.xaxis.set_major_formatter(formatter)
if xlabel:
a.set_xlabel("time (s)")
if yunits == 'um':
a.set_ylabel("depth ($\mu$m)")
elif yunits == 'mm':
a.set_ylabel("depth (mm)")
elif yunits == 'mV':
a.set_ylabel("LFP (mV)")
titlestr = lastcmd()
gcfm().window.setWindowTitle(titlestr)
if title:
a.set_title(titlestr)
a.text(0.998,
0.99,
'%s' % self.r.name,
transform=a.transAxes,
horizontalalignment='right',
verticalalignment='top')
f.tight_layout(pad=0.3) # crop figure to contents
self.f = f
return self