def plotdeltaframe(fname, k):
d = genplotlib.gendict_phase(fname, 'deltaframe')
md = genplotlib.genlist(d)
n = []
for i, v in d.iteritems():
n.append(max(v))
print(n)
plt.figure()
genplotlib.plotdata(d,
md,
k,
's',
'Delay (frames)',
'Frame delay',
ymin=0,
ylim=max(n) + 5)
plt.savefig('deltaframe_summ')
plt.figure()
genplotlib.plotdata(d,
md,
k,
'b',
'Delay (frames)',
'Frame delay',
ymin=0,
ylim=max(n) + 5)
plt.savefig('deltaframe_summ_bar')
def plotnlpersec(capfile):
n = pcapm.gendictnps(capfile)
mn = pcapm.genlist(n)
l = n.keys()
genplotlib.plotdata(n, mn, l, 's', 'nL/sec', 'Amount consumed \n nL/sec', ylim=10,
titlesize='x-large', xlabelsize='medium', xstart=0.25)
plt.savefig('pooled_cap_nlpersec')
def plotdeltatime(fname, k):
d = genplotlib.gendict_phase(fname, 'deltatime')
md = genplotlib.genlist(d)
n = []
for i, v in d.iteritems():
n.append(max(v))
print(n)
plt.figure()
genplotlib.plotdata(d,
md,
k,
's',
'Delay (seconds)',
'Time delay',
ymin=0.05,
ylim=(max(n) + 0.1 * max(n)))
plt.savefig('deltatime_summ')
plt.figure()
genplotlib.plotdata(d,
md,
k,
'b',
'Delay (seconds)',
'Time delay',
ymin=0.05,
ylim=(max(n) + 0.1 * max(n)))
plt.savefig('deltatime_summ_bar')
def plotpixpersec(capfile):
p = pcapm.gendictpps(capfile)
mp = pcapm.genlist(p)
k = p.keys()
genplotlib.plotdata(p, mp, k, 's', 'pix/sec', 'Amount consumed \n pixels/sec', ylim=10,
titlesize='x-large', xlabelsize='medium', xstart=0.25)
plt.savefig('pooled_cap_pixpersec')
plt.close()
def plotandsavepooledscatterplot(p_peakf_file, roi):
"""Plots scatter plot from data in 'peakf.txt' and saves it in the summary directory. Run from a
data/ or summary/ folder."""
dictdata = genplotlib.gendict(p_peakf_file)
dictmeans = genplotlib.genlist(dictdata)
keylist = genplotlib.genkeylist(dictdata)
genplotlib.plotdata(dictdata, dictmeans, keylist, 's', ylabel='Hz', ftitle='Mean pumping ' +
'frequency '+roi)
plt.savefig('pooled_freq_scatter_'+roi)
def plotandsavescatterplot_poolrois(fname, keylist, fdir='.', ylim=10):
"""Plots bar graph from data in 'peakf_pooled.txt' and saves it in the summary directory. Run from a
data/ or summary/ folder."""
dictdata = genplotlib.gendict(fname)
dictmeans = genplotlib.genlist(dictdata)
#~ keylist = genplotlib.genkeylist(dictdata)
genplotlib.plotdata(dictdata, dictmeans, keylist, 's', ylabel='Hz', ftitle='Mean frequency',
ylim=ylim)
plt.savefig('dftf_freq_scatter_pooled')
def plotandsavescatterplot(roiname, keylist, fdir='.', ylim=10):
"""Plots scatter plot from data in 'peakf.txt' and saves it in the summary directory. Run from a
data/ or summary/ folder."""
dictdata = genplotlib.gendict(genpeakffname_roi(roiname, fdir))
dictmeans = genplotlib.genlist(dictdata)
#~ keylist = genplotlib.genkeylist(dictdata)
genplotlib.plotdata(dictdata, dictmeans, keylist, 's', ylabel='Hz', ftitle='Mean pumping ' +
'frequency '+roiname, ylim=ylim)
savegraph('dftf_freq_scatter_'+roiname, roiname)
def plotdur(k, fname, type='s', ymax=30):
plt.figure()
d = genplotlib.gendictgc(fname)[2]
md = genplotlib.genlist(d)
print('Duration')
for tastant, values in d.iteritems():
print(tastant, np.max(values))
if type == 'b':
genplotlib.plotdata(d, md, k, 'b', 'seconds', 'Duration', 0, ymax, xlabelsize='medium')
if type == 's':
genplotlib.plotdata(d, md, k, 's', 'seconds', 'Duration', -5, ymax+10, xlabelsize='medium')
def plotpeak(k, fname, type = 's', ymax=1.0):
plt.figure()
d = genplotlib.gendictgc(fname)[0]
md = genplotlib.genlist(d)
print('Peak')
for tastant, values in d.iteritems():
print(tastant, np.max(values))
if type == 'b':
genplotlib.plotdata(d, md, k, 'b', '%', 'Peak deltaF/F', 0, ymax, xlabelsize='medium')
if type == 's':
genplotlib.plotdata(d, md, k, 's', 'Peak deltaF/F', 'Peak deltaF/F', -0.4, ymax+0.6,
xlabelsize='medium')
def bg_key(p_peakf_file, keyfile, roi):
dictdata = genplotlib.gendict(p_peakf_file)
dictmeans = genplotlib.genlist(dictdata)
keylist = cmn.load_keys(keyfile)
dictdata2 = {}
for k in keylist:
dictdata2[k] = dictdata[k]
genplotlib.plotdata(dictdata2, dictmeans, keylist, 'b', ylabel='Hz',
ftitle='Mean pumping frequency', xlabelsize = 'medium')
plt.savefig('pooled_dftf_freq_bar_'+roi)
def pool_per_results():
homefol = os.path.abspath('.')
pooled_perfile = 'pooled_perfile.txt'
if os.path.exists(pooled_perfile) == True:
os.remove(pooled_perfile)
for expt in EXPTS:
exptpath = os.path.join(os.path.abspath('../../'), expt)
print(exptpath)
os.chdir(exptpath)
perfiles = glob.glob('*percheck.txt')
#print(perfiles)
try:
perfile = os.path.join(exptpath, perfiles[0])
except IndexError:
print('No perfile')
os.chdir(homefol)
continue
os.chdir(homefol)
with open(pooled_perfile, 'a') as g:
with open(perfile, 'r') as f:
f.next()
for l in f:
name, cond, per = l.strip('\n').split(',')[0:3]
print(cond)
try:
condi = condcurr.index(cond)
cond = condnew[condi]
except:
pass
print(cond)
g.write(name+','+cond+','+per+'\n')
os.chdir(homefol)
d = genplotlib.gendictper2(pooled_perfile)
md = gfplot.genpercent_noci(d)
k = genplotlib.genkeylist(md)
print(md)
genplotlib.plotdata(d, md, k, 'b', ylabel='Probability of PER', ftitle='PER', ylim=120, xlabelsize='large')
plt.savefig('pooled_per_bar')
plt.close()
genplotlib.plotdata(d, md, k, 's', ylabel='Probability of PER', ftitle='PER', ylim=120, xlabelsize='large')
plt.savefig('pooled_per_scatter')
def plotfreqs(file, type):
"""Plots the frequencies taken from the summary text files ('fname') with the title 'ftitle';
can plot either per bin or per fly depending on the summary file."""
ftitle = 'Frequencies ({0})'.format(type)
d = genplotlib.gendict_freq(file)
md = genplotlib.genlist(d)
keylist = genplotlib.genkeylist(d)
genplotlib.plotdata(d, md, keylist, 's', ftitle=ftitle, err='stdev', ylim=8, ylabel='Hz')
name = 'pooled_freqs_{0}'.format(type)
plt.savefig(name)
def plotbar(dictdata, keylist, plotname, fdir='.', ylim=10):
"""Plots bar graph from data in 'peakf.txt' and saves it in the summary directory. Run from a
data/ or summary/ folder."""
dictmeans = genplotlib.genlist(dictdata)
n = []
for i, v in dictdata.iteritems():
n.append(max(v))
plt.figure()
genplotlib.plotdata(d, md, k, 'b', 'Delay (seconds)', 'Time delay', ymin=0.05, ylim=(max(n)))
plt.savefig(plotname)
def plotbar(dd, md, k):
k = load_keys(keyfile)
n = []
for i, v in dd.iteritems():
n.append(max(v))
plt.figure()
#gpl.plotdata(dd, md, K, 'b', 'nL', 'Volume per pump', ymin=0, ylim=max(n)+0.1*max(n))
gpl.plotdata(dd, md, k, 'b', 'nL', 'Volume per pump', ymin=0, ylim=4)
plt.savefig(plotname)
def plotdyearea_3d2(fname, k):
plt.figure()
d = genplotlib.gendictgc2(fname)[3]
#~ print(d)
md = genplotlib.genlist(d)
print(md)
#~ print('Dye Area Max Values')
#~ for tastant, values in d.iteritems():
#~ print(tastant, np.max(values))
genplotlib.plotdata(d, md, k, 'b', 'Normalized Area', 'Dye Area', -0.001, 0.05, xlabelsize='medium')
plt.savefig('dyearea_b')
genplotlib.plotdata(d, md, k, 's', 'Normalized Area', 'Dye Area', -.01, 0.12, xlabelsize='medium')
plt.savefig('dyearea_s')
def plotcibareacirc(cibresultsfile):
d = genplotlib.gendict_cibarea_circ(cibresultsfile)
md = genplotlib.genlist(d)
k = d.keys()
genplotlib.plotdata(d,
md,
k,
'b',
'Normalized cib area',
'Cib area',
ymin=0,
ylim=100)
plt.savefig('pooled_cibareacirc')
def plotarea(k, fname, type='s', ymax=10):
plt.figure()
d = genplotlib.gendictgc(fname)[1]
md = genplotlib.genlist(d)
print('Area')
for tastant, values in d.iteritems():
print(tastant, np.max(values))
if type == 'b':
genplotlib.plotdata(d, md, k, 'b', 'intensity-seconds', 'Area under curve', 0, ymax,
xlabelsize='medium')
if type == 's':
genplotlib.plotdata(d, md, k, 's', 'Area under curve', 'Area under curve', 0, ymax+15,i
xlabelsize='medium')
def plotandsavepooledscatterplot(p_peakf_file, roi):
"""Plots scatter plot from data in 'peakf.txt' and saves it in the summary directory. Run from a
data/ or summary/ folder."""
dictdata = genplotlib.gendict(p_peakf_file)
dictmeans = genplotlib.genlist(dictdata)
keylist = genplotlib.genkeylist(dictdata)
genplotlib.plotdata(dictdata,
dictmeans,
keylist,
's',
ylabel='Hz',
ftitle='Mean pumping ' + 'frequency ' + roi)
plt.savefig('pooled_freq_scatter_' + roi)
def plotnlpersec(capfile):
n = pcapm.gendictnps(capfile)
mn = pcapm.genlist(n)
l = n.keys()
genplotlib.plotdata(n,
mn,
l,
's',
'nL/sec',
'Amount consumed \n nL/sec',
ylim=10,
titlesize='x-large',
xlabelsize='medium',
xstart=0.25)
plt.savefig('pooled_cap_nlpersec')
def plotdeltaframe(fname, k):
d = genplotlib.gendict_phase(fname, 'deltaframe')
md = genplotlib.genlist(d)
n = []
for i, v in d.iteritems():
n.append(max(v))
print(n)
plt.figure()
genplotlib.plotdata(d, md, k, 's', 'Delay (frames)', 'Frame delay', ymin=0, ylim=max(n)+5)
plt.savefig('deltaframe_summ')
plt.figure()
genplotlib.plotdata(d, md, k, 'b', 'Delay (frames)', 'Frame delay', ymin=0, ylim=max(n)+5)
plt.savefig('deltaframe_summ_bar')
def bg_key(p_peakf_file, keyfile, roi):
dictdata = genplotlib.gendict(p_peakf_file)
dictmeans = genplotlib.genlist(dictdata)
keylist = cmn.load_keys(keyfile)
dictdata2 = {}
for k in keylist:
dictdata2[k] = dictdata[k]
genplotlib.plotdata(dictdata2,
dictmeans,
keylist,
'b',
ylabel='Hz',
ftitle='Mean pumping frequency',
xlabelsize='medium')
plt.savefig('pooled_dftf_freq_bar_' + roi)
def plotpixpersec(capfile):
p = pcapm.gendictpps(capfile)
mp = pcapm.genlist(p)
k = p.keys()
genplotlib.plotdata(p,
mp,
k,
's',
'pix/sec',
'Amount consumed \n pixels/sec',
ylim=10,
titlesize='x-large',
xlabelsize='medium',
xstart=0.25)
plt.savefig('pooled_cap_pixpersec')
plt.close()
def plotpixpersec(capfile, k):
"""capfile is the summary file, k is the keylist"""
p = gendictpps(capfile)
mp = genlist(p)
gp.plotdata(p,
mp,
k,
's',
'pix/sec',
'Amount consumed \n pixels/sec',
ylim=10,
titlesize='x-large',
xlabelsize='medium',
xstart=0.25)
plt.savefig('cap_pixpersec')
plt.close()
def plotdeltatime(fname, k):
d = genplotlib.gendict_phase(fname, 'deltatime')
md = genplotlib.genlist(d)
n = []
for i, v in d.iteritems():
n.append(max(v))
print(n)
plt.figure()
genplotlib.plotdata(d, md, k, 's', 'Delay (seconds)', 'Time delay', ymin=0.05,
ylim=(max(n)+0.1*max(n)))
plt.savefig('deltatime_summ')
plt.figure()
genplotlib.plotdata(d, md, k, 'b', 'Delay (seconds)', 'Time delay', ymin=0.05,
ylim=(max(n)+0.1*max(n)))
plt.savefig('deltatime_summ_bar')
def plotpumpdata(keyfile='keylist', fname='cib_pumps.txt', type='b', ylim=40):
cib, pumps = gendictgf(fname)
mpumps = genplotlib.genlist(pumps)
#keylist = sorted(mpumps.keys())
keylist = cmn.load_keys(keyfile)
fig1 = genplotlib.plotdata(pumps, mpumps, keylist, type, ylabel='# of pumps',
ftitle = 'Number of ' + 'pumps over 30 seconds', ylim=ylim, ymin=-2)
fig1.subplots_adjust(bottom=0.45)
def plotbar(dictdata, keylist, plotname, fdir='.', ylim=10):
"""Plots bar graph from data in 'peakf.txt' and saves it in the summary directory. Run from a
data/ or summary/ folder."""
dictmeans = genplotlib.genlist(dictdata)
n = []
for i, v in dictdata.iteritems():
n.append(max(v))
plt.figure()
genplotlib.plotdata(d,
md,
k,
'b',
'Delay (seconds)',
'Time delay',
ymin=0.05,
ylim=(max(n)))
plt.savefig(plotname)
def plotfreqs(file, type):
"""Plots the frequencies taken from the summary text files ('fname') with the title 'ftitle';
can plot either per bin or per fly depending on the summary file."""
ftitle = 'Frequencies ({0})'.format(type)
d = genplotlib.gendict_freq(file)
md = genplotlib.genlist(d)
keylist = genplotlib.genkeylist(d)
genplotlib.plotdata(d,
md,
keylist,
's',
ftitle=ftitle,
err='stdev',
ylim=8,
ylabel='Hz')
name = 'pooled_freqs_{0}'.format(type)
plt.savefig(name)
def plotcibdata_noci(keyfile='keylist', fname='cib_pumps.txt', type='b'):
"""Fname is the file with the original cibarium and pump count data."""
cib, npumps = gendictgf(fname)
cibdict = genpercent_noci(cib)
#keylist = sorted(pcib.keys())
keylist = cmn.load_keys(keyfile)
fig1 = genplotlib.plotdata(cib, cibdict, keylist, type, ylabel='%',
ftitle='Percentage of flies with open' + ' cibariums', ylim=100, ymin=-2)
fig1.subplots_adjust(bottom=0.45)
def plotnlpersec(capfile, l):
"""capfile is the summary file, l is the keylist"""
n = gendictnps(capfile)
mn = genlist(n)
o = []
for i, v in n.iteritems():
o.append(max(v))
print(max(o))
gp.plotdata(n,
mn,
l,
's',
'nL/sec',
'Amount consumed',
ylim=max(o) + 0.3 * max(o),
titlesize='x-large',
xlabelsize='medium',
xstart=0.25)
plt.savefig('cap_nlpersec')
plt.figure()
gp.plotdata(n,
mn,
l,
'b',
'nL/sec',
'Amount consumed',
ylim=max(o) + 0.3 * max(o),
titlesize='x-large',
xlabelsize='medium',
xstart=0.25)
plt.savefig('cap_nlpersec_bar')
def plotpumpdata(keyfile='keylist', fname='cib_pumps.txt', type='b', ylim=40):
cib, pumps = gendictgf(fname)
mpumps = genplotlib.genlist(pumps)
#keylist = sorted(mpumps.keys())
keylist = cmn.load_keys(keyfile)
fig1 = genplotlib.plotdata(pumps,
mpumps,
keylist,
type,
ylabel='# of pumps',
ftitle='Number of ' + 'pumps over 30 seconds',
ylim=ylim,
ymin=-2)
fig1.subplots_adjust(bottom=0.45)
def plotcibdata_noci(keyfile='keylist', fname='cib_pumps.txt', type='b'):
"""Fname is the file with the original cibarium and pump count data."""
cib, npumps = gendictgf(fname)
cibdict = genpercent_noci(cib)
#keylist = sorted(pcib.keys())
keylist = cmn.load_keys(keyfile)
fig1 = genplotlib.plotdata(cib,
cibdict,
keylist,
type,
ylabel='%',
ftitle='Percentage of flies with open' +
' cibariums',
ylim=100,
ymin=-2)
fig1.subplots_adjust(bottom=0.45)
def plotcibarea(fname, k1, k2):
dicts = gpl.gendict_cibgf(fname)
dmean, ddiffa = dicts
mdicts = map(gpl.genlist, dicts)
mdmean, mddiffa = mdicts
zd = zip(dicts, mdicts)
#k1 = sorted(dmean.keys())
#k2 = sorted(ddiffa.keys())
for type in ['b', 's']:
gpl.plotdata(dmean,
mdmean,
k1,
type,
r'$\mu$m$^2$',
'Mean areas',
ylim=10000,
ymin=0)
plt.savefig('areameans_' + type)
if type == 'b':
gpl.plotdata(ddiffa,
mddiffa,
k2,
type,
r'$\mu$m$^2$',
'Difference in area',
ylim=6000,
ymin=-1000)
plt.savefig('areadiffs_' + type)
if type == 's':
gpl.plotdata(ddiffa,
mddiffa,
k2,
type,
r'$\mu$m$^2$',
'Difference in area',
ylim=6000,
ymin=-2000)
plt.savefig('areadiffs_' + type)
def plotcibarea(fname, k1, k2):
dicts = gpl.gendict_cibgf(fname)
dmean, ddiffa = dicts
mdicts = map(gpl.genlist, dicts)
mdmean, mddiffa = mdicts
zd = zip(dicts, mdicts)
#k1 = sorted(dmean.keys())
#k2 = sorted(ddiffa.keys())
for type in ['b', 's']:
gpl.plotdata(dmean, mdmean, k1, type, r'$\mu$m$^2$', 'Mean areas', ylim=10000, ymin=0)
plt.savefig('areameans_' + type)
if type == 'b':
gpl.plotdata(ddiffa, mddiffa, k2, type, r'$\mu$m$^2$', 'Difference in area',
ylim=6000, ymin=-1000)
plt.savefig('areadiffs_' + type)
if type == 's':
gpl.plotdata(ddiffa, mddiffa, k2, type, r'$\mu$m$^2$', 'Difference in area',
ylim=6000, ymin=-2000)
plt.savefig('areadiffs_' + type)
if os.path.exists(x) == True:
os.remove(x)
names = batchfiles('.')
for name in names:
print os.path.basename(name)
os.chdir(name)
params = CibData(PARAMS_FILE, RESULTS_FILE)
cibdict = params.Gendata()
writeresults(cibdict)
os.chdir('../../summary')
d = genplotlib.gendict_cibarea_circ('cibresults.txt')
md = genplotlib.genlist(d)
k = d.keys()
genplotlib.plotdata(d, md, k, 'b', 'NormCibArea', 'Fraction of cibarium open', ymin=0, ylim=100)
plt.savefig('cibareacirc')
#plt.figure()
#e = genplotlib.gendict_cibarea_dur('cibresults.txt')
#me = genplotlib.genlist(e)
#genplotlib.plotdata(e, me, k, 'b', 'Duration', 'Duration of Drinking', ymin=0, ylim=200)
#plt.savefig('duration')
#try:
#a =
#f = findfraction()
#list.append(f)
#except IOError as e:
#if e.errno == 2:
h.write(key + ',{0},{1},{2},{3}\n'.format(value['cap'], value['freq'], volperpump, value['cond']))
except KeyError:
continue
except ZeroDivisionError:
continue
keyfile = os.path.join(makepardir_subexpt(), KEYLIST)
K = load_keys(keyfile)
dd = gpl.gendict_volperpump(CAP_PEAKFFILE)
md = gpl.genlist(dd)
n = []
for i, v in dd.iteritems():
n.append(max(v))
print(max(n))
plt.figure()
gpl.plotdata(dd, md, K, 's', 'nL', 'Volume per pump', ymin=0, ylim=max(n)+0.1*max(n))
plt.savefig('volperpump_sc')
plt.figure()
#gpl.plotdata(dd, md, K, 'b', 'nL', 'Volume per pump', ymin=0, ylim=max(n)+0.1*max(n))
gpl.plotdata(dd, md, K, 'b', 'nL', 'Volume per pump', ymin=0, ylim=4)
plt.savefig('volperpump_bar')
continue
keyfile = os.path.join(makepardir_subexpt(), KEYLIST)
K = load_keys(keyfile)
dd = gpl.gendict_volperpump(CAP_PEAKFFILE)
md = gpl.genlist(dd)
n = []
for i, v in dd.iteritems():
n.append(max(v))
print(max(n))
plt.figure()
gpl.plotdata(dd,
md,
K,
's',
'nL',
'Volume per pump',
ymin=0,
ylim=max(n) + 0.1 * max(n))
plt.savefig('volperpump_sc')
plt.figure()
#gpl.plotdata(dd, md, K, 'b', 'nL', 'Volume per pump', ymin=0, ylim=max(n)+0.1*max(n))
gpl.plotdata(dd, md, K, 'b', 'nL', 'Volume per pump', ymin=0, ylim=4)
plt.savefig('volperpump_bar')
names = batchfiles('.')
for name in names:
print os.path.basename(name)
os.chdir(name)
params = CibData(PARAMS_FILE, RESULTS_FILE)
cibdict = params.Gendata()
writeresults(cibdict)
os.chdir('../../summary')
d = genplotlib.gendict_cibarea_circ('cibresults.txt')
md = genplotlib.genlist(d)
k = d.keys()
genplotlib.plotdata(d,
md,
k,
'b',
'NormCibArea',
'Fraction of cibarium open',
ymin=0,
ylim=100)
plt.savefig('cibareacirc')
#plt.figure()
#e = genplotlib.gendict_cibarea_dur('cibresults.txt')
#me = genplotlib.genlist(e)
#genplotlib.plotdata(e, me, k, 'b', 'Duration', 'Duration of Drinking', ymin=0, ylim=200)
#plt.savefig('duration')
#try:
#a =
#f = findfraction()
#list.append(f)
def plotcibareacirc(cibresultsfile):
d = genplotlib.gendict_cibarea_circ(cibresultsfile)
md = genplotlib.genlist(d)
k = d.keys()
genplotlib.plotdata(d, md, k, 'b', 'Normalized cib area', 'Cib area', ymin=0, ylim=100)
plt.savefig('pooled_cibareacirc')
def pool_per_results():
homefol = os.path.abspath('.')
pooled_perfile = 'pooled_perfile.txt'
if os.path.exists(pooled_perfile) == True:
os.remove(pooled_perfile)
for expt in EXPTS:
exptpath = os.path.join(os.path.abspath('../../'), expt)
print(exptpath)
os.chdir(exptpath)
perfiles = glob.glob('*percheck.txt')
#print(perfiles)
try:
perfile = os.path.join(exptpath, perfiles[0])
except IndexError:
print('No perfile')
os.chdir(homefol)
continue
os.chdir(homefol)
with open(pooled_perfile, 'a') as g:
with open(perfile, 'r') as f:
f.next()
for l in f:
name, cond, per = l.strip('\n').split(',')[0:3]
print(cond)
try:
condi = condcurr.index(cond)
cond = condnew[condi]
except:
pass
print(cond)
g.write(name + ',' + cond + ',' + per + '\n')
os.chdir(homefol)
d = genplotlib.gendictper2(pooled_perfile)
md = gfplot.genpercent_noci(d)
k = genplotlib.genkeylist(md)
print(md)
genplotlib.plotdata(d,
md,
k,
'b',
ylabel='Probability of PER',
ftitle='PER',
ylim=120,
xlabelsize='large')
plt.savefig('pooled_per_bar')
plt.close()
genplotlib.plotdata(d,
md,
k,
's',
ylabel='Probability of PER',
ftitle='PER',
ylim=120,
xlabelsize='large')
plt.savefig('pooled_per_scatter')
