def gentoplot(time):
"""Generates a dictionary where the keys are movie names and the values are the raw trace for
plotting. Time specifies the length of time in seconds of the plots shown."""
toplot = {}
# Generates a list of movie paths in the data folder.
files = dftf.batch_s('.')
# Generates dft traces and plots for each roi in each movie.
for file in files:
os.chdir(file)
print(os.path.basename(file))
for col in COLS:
if os.path.exists('params') == True:
rawtracedata = dftf.TraceData(fname=RESULTS_FILE, paramsfile=PARAMS_FILE,
corrparamsfile=CORRPARAMS_FILE, colname=col)
td = rawtracedata.Processrawtrace(DFTSIZE, HZ_BOUND1, HZ_BOUND2)
moviename = os.path.basename(os.path.abspath('.'))
# Selects the area of the raw trace to plot.
frames = time * td['fps']
#print(frames)
plottime = td['seltrace'][:frames]/6
#print(len(plottime))
ms = plottime-np.mean(plottime)
xsec = np.linspace(0, len(plottime)/td['fps'], len(plottime))
#print(xsec)
condition = td['condition']
toplot[moviename] = [xsec, ms, condition]
print(np.max(ms), np.min(ms))
return(toplot)
def gentoplot_dft(xlimhz):
toplot = {}
# Generates a list of movie paths in the data folder.
files = dftf.batch_s('.')
# Generates dft traces and plots for each roi in each movie.
for file in files:
os.chdir(file)
print(os.path.basename(file))
for col in COLS:
if os.path.exists('params') == True:
rawtracedata = dftf.TraceData(fname=RESULTS_FILE, paramsfile=PARAMS_FILE,
corrparamsfile=CORRPARAMS_FILE, colname=col)
td = rawtracedata.Processrawtrace(DFTSIZE, HZ_BOUND1, HZ_BOUND2)
condition = td['condition']
m = td['peakf']
xpoints = np.linspace(0, td['fps']/2, td['dftsize']/2)
prop = xlimhz/(td['fps']/2)
tracelen = np.rint(prop*len(td['dftnormtrunctrace']))
toplot[td['moviename']] = [xpoints[:tracelen],
td['dftnormtrunctrace'][:tracelen], condition]
return(toplot)
def gentoplot_dft(xlimhz):
toplot = {}
# Generates a list of movie paths in the data folder.
files = dftf.batch_s('.')
# Generates dft traces and plots for each roi in each movie.
for file in files:
os.chdir(file)
print(os.path.basename(file))
for col in COLS:
if os.path.exists('params') == True:
rawtracedata = dftf.TraceData(fname=RESULTS_FILE,
paramsfile=PARAMS_FILE,
corrparamsfile=CORRPARAMS_FILE,
colname=col)
td = rawtracedata.Processrawtrace(DFTSIZE, HZ_BOUND1,
HZ_BOUND2)
condition = td['condition']
m = td['peakf']
xpoints = np.linspace(0, td['fps'] / 2, td['dftsize'] / 2)
prop = xlimhz / (td['fps'] / 2)
tracelen = np.rint(prop * len(td['dftnormtrunctrace']))
toplot[td['moviename']] = [
xpoints[:tracelen], td['dftnormtrunctrace'][:tracelen],
condition
]
return (toplot)
def gentoplot(time):
"""Generates a dictionary where the keys are movie names and the values are the raw trace for
plotting. Time specifies the length of time in seconds of the plots shown."""
toplot = {}
# Generates a list of movie paths in the data folder.
files = dftf.batch_s('.')
# Generates dft traces and plots for each roi in each movie.
for file in files:
os.chdir(file)
print(os.path.basename(file))
for col in COLS:
if os.path.exists('params') == True:
rawtracedata = dftf.TraceData(fname=RESULTS_FILE, paramsfile=PARAMS_FILE,
corrparamsfile=CORRPARAMS_FILE, colname=col)
td = rawtracedata.Processrawtrace(DFTSIZE, HZ_BOUND1, HZ_BOUND2)
moviename = os.path.basename(os.path.abspath('.'))
# Selects the area of the raw trace to plot.
frames = time * td['fps']
#print(frames)
plottime = td['seltrace'][:frames]/10
#print(len(plottime))
ms = plottime-np.mean(plottime)
xsec = np.linspace(0, len(plottime)/td['fps'], len(plottime))
#print(xsec)
condition = td['condition']
toplot[moviename] = [xsec, ms, condition]
print(np.max(ms), np.min(ms))
return(toplot)
def batch_plotspecmovie(nfft, padmultiple):
# Generates a list of movie paths in the data folder.
files = dftf.batch_s('.')
# Generates dft traces and plots for each roi in each movie.
for file in files:
os.chdir(file)
print(os.path.basename(file))
if os.path.exists('params') == True and os.path.exists(
'results1.txt') == True:
plotspecmovie(nfft, padmultiple)
dftf.savetracesumm(str(nfft),
moviefold='summary/spec_pad_' + str(nfft))
plt.close()
def gentoplot(time):
"""Generates a dictionary where the keys are movie names and the values are the raw trace for
plotting. Time specifies the length of time in seconds of the plots shown."""
toplot = {}
# Generates a list of movie paths in the data folder.
files = dftf.batch_s('.')
# Generates dft traces and plots for each roi in each movie.
for file in files:
os.chdir(file)
print(os.path.basename(file))
for col in COLS:
if os.path.exists('params') == True:
rawtracedata = dftf.TraceData(fname=RESULTS_FILE, paramsfile=PARAMS_FILE,
corrparamsfile=CORRPARAMS_FILE, colname=col)
td = rawtracedata.Processrawtrace(DFTSIZE, HZ_BOUND1, HZ_BOUND2)
# Selects the area of the raw trace to plot.
frames = time * td['fps']
frameoffset = TIMEOFFSET * td['fps']
#print(frames)
if os.path.basename(file) == 'mov_20101130_200533' \
or os.path.basename(file) == 'mov_20110517_181356' \
or os.path.basename(file) == 'mov_20110517_174209':
plottime = td['seltrace'][frameoffset:frames]/8
elif os.path.basename(file) == 'mov_20110518_192012':
plottime = td['seltrace'][frameoffset:frames]/1.5
elif os.path.basename(file) == 'mov_20110518_184849':
plottime = td['seltrace'][frameoffset:frames]/3
#elif os.path.basename(file) == 'mov_20110527_163607_part2':
#plottime = td['seltrace'][50:frames+50]
else:
plottime = td['seltrace'][frameoffset:frames]
#print(len(plottime))
ms = plottime-np.mean(plottime)
xsec = np.linspace(0, len(plottime)/td['fps'], len(plottime))
#print(xsec)
condition = td['condition']
toplot[td['moviename']] = [xsec, ms, condition]
print(np.max(ms), np.min(ms))
return(toplot)
def pool_probendarea_results(datafol, expts):
files = []
for expt in expts:
exptpath = '../{0}/{1}/'.format(expt, datafol)
os.chdir(exptpath)
fs = dftf.batch_s('.')
files.extend(fs)
os.chdir('../')
ad = dal.areadict(files)
#ad = dal.areadict_multpts(files)
pd = dal.areapoints(ad)
pdd = dal.areapoints_dict(ad)
md = dal.meanpoints(pd)
sd = dal.statdict(pd)
asd = dal.areastats(sd)
#print(ad)
#print(pd)
#print(md)
return [ad, pd, pdd, md, sd, asd]
def pool_probendarea_results(datafol, expts):
files = []
for expt in expts:
exptpath = '../{0}/{1}/'.format(expt, datafol)
os.chdir(exptpath)
fs = dftf.batch_s('.')
files.extend(fs)
os.chdir('../')
ad = dal.areadict(files)
#ad = dal.areadict_multpts(files)
pd = dal.areapoints(ad)
pdd = dal.areapoints_dict(ad)
md = dal.meanpoints(pd)
sd = dal.statdict(pd)
asd = dal.areastats(sd)
#print(ad)
#print(pd)
#print(md)
return[ad, pd, pdd, md, sd, asd]
plotfolder = os.path.join(
os.path.dirname(os.path.dirname(os.path.abspath('.'))),
'plots')
makenewdir(plotfolder)
figname = os.path.join(plotfolder, movie + '_trace_nolab')
plt.savefig(figname + '.svg', dpi=FIGDPI, format='svg')
plt.savefig(figname + '.png', dpi=FIGDPI, format='png')
os.chdir('../')
if labels == 'yes':
plotfolder = os.path.join(
os.path.dirname(os.path.dirname(os.path.abspath('.'))),
'plots')
makenewdir(plotfolder)
figname = os.path.join(plotfolder, movie + '_trace')
plt.savefig(figname + '.svg', dpi=FIGDPI, format='svg')
plt.savefig(figname + '.png', dpi=FIGDPI, format='png')
os.chdir('../')
matplotlib.rc('axes', linewidth=LINEWIDTH)
# Generates a list of movie paths in the data folder.
files = dftf.batch_s('.')
# Generates dft traces and plots for each roi in each movie.
plottrace_paper(MOVIES, FIGW, FIGH, FIGDPI, FONTSIZE, BORDER, XLABEL, YLABEL,
YAXISTICKS, XAXISTICKS, LABELS, LINEWIDTH, FS)
os.chdir('../')
makenewdir(summfol)
return(summfol)
def savemeanplot(summfold, plotname, format, figdpi=600):
plt.savefig(os.path.join(summfold, plotname+'.'+str(format)), format=format, dpi=figdpi)
if __name__ == '__main__':
homefol = os.path.abspath(os.getcwd())
genbubparams('movies_dye_prob_end_notes.txt', 'data_area_liquid')
os.chdir('data_area_liquid')
#os.chdir('data_area_wholelab')
files = dftf.batch_s('.')
ad = areadict(files)
pd = areapoints(ad)
md = meanpoints(pd)
print('Area dictionary')
print(ad)
print('Area points')
print(pd)
#ad = areadict_norm(files, os.path.join(homefol, 'data_hwidth'))
sf = gensummfol_data('summary_area_liquid')
#b_plotpoints(files, sf)
savemeans(md, sf, 'means_area_liquid')
