def pdipole_with_hist(f_dpl, f_spk, dfig, f_param, key_types, plot_dict):
""" this function has not been converted to use the Dipole() class yet
"""
# dpl is an obj of Dipole() class
dpl = Dipole(f_dpl)
dpl.baseline_renormalize(f_param)
dpl.convert_fAm_to_nAm()
# split to find file prefix
file_prefix = f_dpl.split('/')[-1].split('.')[0]
# grabbing the p_dict from the f_param
_, p_dict = paramrw.read(f_param)
# get xmin and xmax from the plot_dict
if plot_dict['xmin'] is None:
xmin = 0.
else:
xmin = plot_dict['xmin']
if plot_dict['xmax'] is None:
xmax = p_dict['tstop']
else:
xmax = plot_dict['xmax']
# truncate tvec and dpl data using logical indexing
t_range = dpl.t[(dpl.t >= xmin) & (dpl.t <= xmax)]
dpl_range = dpl.dpl['agg'][(dpl.t >= xmin) & (dpl.t <= xmax)]
# Plotting
f = ac.FigDplWithHist()
# dipole
f.ax['dipole'].plot(t_range, dpl_range)
# set new xlim based on dipole plot
xlim_new = f.ax['dipole'].get_xlim()
# Get extinput data and account for delays
extinputs = spikefn.ExtInputs(f_spk, f_param)
extinputs.add_delay_times()
# set number of bins (150 bins per 1000ms)
bins = ceil(150. * (xlim_new[1] - xlim_new[0]) / 1000.) # bins needs to be an int
# plot histograms
hist = {}
hist['feed_prox'] = extinputs.plot_hist(f.ax['feed_prox'], 'prox', dpl.t, bins, xlim_new, color='red')
hist['feed_dist'] = extinputs.plot_hist(f.ax['feed_dist'], 'dist', dpl.t, bins, xlim_new, color='green')
# Invert dist histogram
f.ax['feed_dist'].invert_yaxis()
# for now, set the xlim for the other one, force it!
f.ax['dipole'].set_xlim(xlim_new)
f.ax['feed_prox'].set_xlim(xlim_new)
f.ax['feed_dist'].set_xlim(xlim_new)
# set hist axis properties
f.set_hist_props(hist)
# Add legend to histogram
for key in f.ax.keys():
if 'feed' in key:
f.ax[key].legend()
# force xlim on histograms
f.ax['feed_prox'].set_xlim((xmin, xmax))
f.ax['feed_dist'].set_xlim((xmin, xmax))
title_str = ac.create_title(p_dict, key_types)
f.f.suptitle(title_str)
fig_name = os.path.join(dfig, file_prefix+'.png')
plt.savefig(fig_name)
f.close()
def pfreqpwr_with_hist(file_name, freqpwr_result, f_spk, gid_dict, p_dict,
key_types):
f = ac.FigFreqpwrWithHist()
f.ax['hist'].hold(True)
xmin = 50.
xmax = p_dict['tstop']
f.ax['freqpwr'].plot(freqpwr_result['freq'], freqpwr_result['avgpwr'])
# grab alpha feed data. spikes_from_file() from spikefn.py
s_dict = spikefn.spikes_from_file(gid_dict, f_spk)
# check for existance of alpha feed keys in s_dict.
s_dict = spikefn.alpha_feed_verify(s_dict, p_dict)
# Account for possible delays
s_dict = spikefn.add_delay_times(s_dict, p_dict)
# set number of bins (150 bins/1000ms)
bins = 150. * (xmax - xmin) / 1000.
hist_data = []
# Proximal feed
hist_data.extend(f.ax['hist'].hist(s_dict['alpha_feed_prox'].spike_list,
bins,
range=[xmin, xmax],
color='red',
label='Proximal feed')[0])
# Distal feed
hist_data.extend(f.ax['hist'].hist(s_dict['alpha_feed_dist'].spike_list,
bins,
range=[xmin, xmax],
color='green',
label='Distal feed')[0])
# set hist axis props
f.set_hist_props(hist_data)
# axis labels
f.ax['freqpwr'].set_xlabel('freq (Hz)')
f.ax['freqpwr'].set_ylabel('power')
f.ax['hist'].set_xlabel('time (ms)')
f.ax['hist'].set_ylabel('# spikes')
# create title
title_str = ac.create_title(p_dict, key_types)
f.f.suptitle(title_str)
# title_str = [key + ': %2.1f' % p_dict[key] for key in key_types['dynamic_keys']]
f.savepng(file_name)
f.close()
def pdipole(f_dpl, dfig, plot_dict, f_param=None, key_types={}):
""" single dipole file combination (incl. param file)
this should be done with an axis input too
two separate functions, a pdipole kernel function and a specific function for this simple plot
"""
# dpl is an obj of Dipole() class
dpl = Dipole(f_dpl)
if f_param:
dpl.baseline_renormalize(f_param)
dpl.convert_fAm_to_nAm()
# split to find file prefix
file_prefix = f_dpl.split('/')[-1].split('.')[0]
# parse xlim from plot_dict
if plot_dict['xlim'] is None:
xmin = dpl.t[0]
xmax = dpl.t[-1]
else:
xmin, xmax = plot_dict['xlim']
if xmin < 0.:
xmin = 0.
if xmax < 0.:
xmax = self.f[-1]
# # get xmin and xmax from the plot_dict
# if plot_dict['xmin'] is None:
# xmin = 0.
# else:
# xmin = plot_dict['xmin']
# if plot_dict['xmax'] is None:
# xmax = p_dict['tstop']
# else:
# xmax = plot_dict['xmax']
# truncate them using logical indexing
t_range = dpl.t[(dpl.t >= xmin) & (dpl.t <= xmax)]
dpl_range = dpl.dpl['agg'][(dpl.t >= xmin) & (dpl.t <= xmax)]
f = ac.FigStd()
f.ax0.plot(t_range, dpl_range)
# sorry about the parity between vars here and above with xmin/xmax
if plot_dict['ylim'] is None:
# if plot_dict['ymin'] is None or plot_dict['ymax'] is None:
pass
else:
f.ax0.set_ylim(plot_dict['ylim'][0], plot_dict['ylim'][1])
# f.ax0.set_ylim(plot_dict['ymin'], plot_dict['ymax'])
# Title creation
if f_param and key_types:
# grabbing the p_dict from the f_param
_, p_dict = paramrw.read(f_param)
# useful for title strings
title_str = ac.create_title(p_dict, key_types)
f.f.suptitle(title_str)
# create new fig name
fig_name = os.path.join(dfig, file_prefix+'.png')
# savefig
plt.savefig(fig_name, dpi=300)
f.close()
def pspec_with_hist(f_spec,
f_dpl,
f_spk,
dfig,
f_param,
key_types,
xlim=None,
ylim=None):
# Generate file prefix
# print('f_spec:',f_spec)
fprefix = f_spec.split('/')[-1].split('.')[0]
# Create the fig name
fig_name = os.path.join(dfig, fprefix + '.png')
# print('fig_name:',fig_name)
# load param dict
_, p_dict = paramrw.read(f_param)
f = ac.FigSpecWithHist()
# load spec data
spec = specfn.Spec(f_spec)
# Plot TFR data and add colorbar
pc = spec.plot_TFR(f.ax['spec'], 'agg', xlim, ylim)
f.f.colorbar(pc, ax=f.ax['spec'])
# set xlim based on TFR plot
xlim_new = f.ax['spec'].get_xlim()
# grab the dipole data
dpl = dipolefn.Dipole(f_dpl)
dpl.baseline_renormalize(f_param)
dpl.convert_fAm_to_nAm()
# plot routine
dpl.plot(f.ax['dipole'], xlim_new, 'agg')
# data_dipole = np.loadtxt(open(f_dpl, 'r'))
# t_dpl = data_dipole[xmin_ind:xmax_ind+1, 0]
# dp_total = data_dipole[xmin_ind:xmax_ind+1, 1]
# f.ax['dipole'].plot(t_dpl, dp_total)
# x = (xmin, xmax)
# # grab alpha feed data. spikes_from_file() from spikefn.py
# s_dict = spikefn.spikes_from_file(f_param, f_spk)
# # check for existance of alpha feed keys in s_dict.
# s_dict = spikefn.alpha_feed_verify(s_dict, p_dict)
# # Account for possible delays
# s_dict = spikefn.add_delay_times(s_dict, p_dict)
# Get extinput data and account for delays
extinputs = spikefn.ExtInputs(f_spk, f_param)
extinputs.add_delay_times()
extinputs.get_envelope(dpl.t, feed='dist')
# set number of bins (150 bins per 1000ms)
bins = ceil(150. * (xlim_new[1] - xlim_new[0]) /
1000.) # bins should be int
# plot histograms
hist = {}
hist['feed_prox'] = extinputs.plot_hist(f.ax['feed_prox'],
'prox',
dpl.t,
bins=bins,
xlim=xlim_new,
color='red')
hist['feed_dist'] = extinputs.plot_hist(f.ax['feed_dist'],
'dist',
dpl.t,
bins=bins,
xlim=xlim_new,
color='green')
f.ax['feed_dist'].invert_yaxis()
# for now, set the xlim for the other one, force it!
f.ax['dipole'].set_xlim(xlim_new)
f.ax['spec'].set_xlim(xlim_new)
f.ax['feed_prox'].set_xlim(xlim_new)
f.ax['feed_dist'].set_xlim(xlim_new)
# set hist axis props
f.set_hist_props(hist)
# axis labels
f.ax['spec'].set_xlabel('Time (ms)')
f.ax['spec'].set_ylabel('Frequency (Hz)')
# Add legend to histogram
for key in f.ax.keys():
if 'feed' in key:
f.ax[key].legend()
# create title
title_str = ac.create_title(p_dict, key_types)
f.f.suptitle(title_str)
f.savepng(fig_name)
f.close()
def pspec_dpl(f_spec,
f_dpl,
dfig,
p_dict,
key_types,
xlim=None,
ylim=None,
f_param=None):
# Generate file prefix
fprefix = f_spec.split('/')[-1].split('.')[0]
# using png for now
# fig_name = os.path.join(dfig, fprefix+'.eps')
fig_name = os.path.join(dfig, fprefix + '.png')
# f.f is the figure handle!
f = ac.FigSpec()
# load spec data
spec = specfn.Spec(f_spec)
# Plot TFR data and add colorbar
pc = spec.plot_TFR(f.ax['spec'], 'agg', xlim, ylim)
f.f.colorbar(pc, ax=f.ax['spec'])
# grab the dipole data
# data_dipole = np.loadtxt(open(f_dpl, 'r'))
dpl = dipolefn.Dipole(f_dpl)
# If f_param supplied, renormalize dipole data
if f_param:
dpl.baseline_renormalize(f_param)
dpl.convert_fAm_to_nAm()
# plot routine
dpl.plot(f.ax['dipole'], xlim, 'agg')
# Plot Welch data
# Use try/except for backwards compatibility
try:
spec.plot_pgram(f.ax['pgram'])
except KeyError:
pgram = specfn.Welch(dpl.t, dpl.dpl['agg'], p_dict['dt'])
pgram.plot_to_ax(f.ax['pgram'], spec.spec['agg']['f'][-1])
# plot and create an xlim
xlim_new = f.ax['spec'].get_xlim()
xticks = f.ax['spec'].get_xticks()
xticks[0] = xlim_new[0]
# for now, set the xlim for the other one, force it!
f.ax['dipole'].set_xlim(xlim_new)
f.ax['dipole'].set_xticks(xticks)
f.ax['spec'].set_xticks(xticks)
# axis labels
f.ax['spec'].set_xlabel('Time (ms)')
f.ax['spec'].set_ylabel('Frequency (Hz)')
# create title
title_str = ac.create_title(p_dict, key_types)
f.f.suptitle(title_str)
# use our fig classes to save and close
f.savepng(fig_name)
# f.saveeps(dfig, fprefix)
f.close()