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 plotspecmovie(nfft, padmultiple):
rawtracedata = dftf.TraceData(fname=RESULTS_FILE,
paramsfile=PARAMS_FILE,
corrparamsfile=CORRPARAMS_FILE,
colname='Mean1')
td = rawtracedata.Processrawtrace(DFTSIZE, HZ_BOUND1, HZ_BOUND2)
plotcustomspec(td,
nfft=nfft,
time=TIME,
xlim=XLIM,
ylim=YLIM,
padmultiple=padmultiple)
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 checkframes():
"""Generates a dictionary with the f1 from the params file and the pdframes file for each movie."""
d = {}
for movie in MOVIES.iterkeys():
os.chdir(DATAFOL)
os.chdir(movie)
rawtracedata = dftf.TraceData(fname=RESULTS_FILE, paramsfile=PARAMS_FILE,
corrparamsfile=CORRPARAMS_FILE, colname='Mean1')
td = rawtracedata.Processrawtrace(DFTSIZE, HZ_BOUND1, HZ_BOUND2)
os.chdir(IFILEFOL)
os.chdir(movie)
pd = {}
with open('pdframes') as f:
for l in f:
pd[l.split(',')[0]] = (l.split(',')[1].strip('\n'))
d[movie] = (td['f1'], float(pd['f1']))
print(d)
return(d)
figname = os.path.join(plotfolder, td['moviename'] + '_dft_ticks_labels')
plt.savefig(figname + '.svg', dpi=FIGDPI, format='svg')
plt.savefig(figname + '.png', dpi=FIGDPI, format='png')
mpl.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.
for movie, val in DFT_MOVIES.iteritems():
os.chdir(movie)
print(os.path.basename(movie))
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, offset, color = val
plotdft_paper(td, FIGW, FIGH, FIGDPI, FONTSIZE, YLIM, BORDER,
YLABEL, XAXISTICKS, YAXISTICKS, XLIMHZ, color,
LINEWIDTH)
os.chdir('../')
