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 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 writemeans_gc(gcfname, dyeareafname):
peakd, aread, durd = gpl.gendictgc(gcfname)
percentpeakd = {}
for k, val in peakd.iteritems():
vpercent = [v*100 for v in val]
percentpeakd[k] = vpercent
percentaread = {}
for k, val in aread.iteritems():
vpercent = [v*100 for v in val]
percentaread[k] = vpercent
dicts = percentpeakd, percentaread, durd
mpeakd, maread, mdurd, = map(gpl.genlist, dicts)
print(mpeakd)
print(maread)
dyearead = gpl.gendictgc2(dyeareafname)[3]
mdyearead = gpl.genlist(dyearead)
#wf.writemeans(mpeakd, expt+'_peakf_means.txt')
#wf.writemeans(maread, expt+'_area_means.txt')
#wf.writemeans(mdurd, expt+'_dur_means.txt')
#wf.writemeans(mdyearead, expt+'_dyearea_means.txt')
writemeans(mpeakd, 'peakf_means.txt')
writemeans(maread, 'area_means.txt')
writemeans(mdurd, 'dur_means.txt')
writemeans(mdyearead, 'dyearea_means.txt')
def writemeans_gc(gcfname, dyeareafname):
peakd, aread, durd = gpl.gendictgc(gcfname)
percentpeakd = {}
for k, val in peakd.iteritems():
vpercent = [v * 100 for v in val]
percentpeakd[k] = vpercent
percentaread = {}
for k, val in aread.iteritems():
vpercent = [v * 100 for v in val]
percentaread[k] = vpercent
dicts = percentpeakd, percentaread, durd
mpeakd, maread, mdurd, = map(gpl.genlist, dicts)
print(mpeakd)
print(maread)
dyearead = gpl.gendictgc2(dyeareafname)[3]
mdyearead = gpl.genlist(dyearead)
#wf.writemeans(mpeakd, expt+'_peakf_means.txt')
#wf.writemeans(maread, expt+'_area_means.txt')
#wf.writemeans(mdurd, expt+'_dur_means.txt')
#wf.writemeans(mdyearead, expt+'_dyearea_means.txt')
writemeans(mpeakd, 'peakf_means.txt')
writemeans(maread, 'area_means.txt')
writemeans(mdurd, 'dur_means.txt')
writemeans(mdyearead, 'dyearea_means.txt')
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 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 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 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 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 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 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 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 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 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 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 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 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 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 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 writemeans_deltatime(fnameread, fnamewrite):
d = gpl.gendict_phase(fnameread, 'deltatime')
md = gpl.genlist(d)
writemeans(md, fnamewrite)
for key, value in sorted(d.iteritems()):
try:
volperpump = value['cap'] / value['freq']
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,
#! /usr/bin/env python
import mn.plot.genplotlib as gpl
from mn.cmn.cmn import *
import mn.gof.gfplot as gf
import sys
fname = sys.argv[1]
keyfile = sys.argv[2]
meansfname = sys.argv[3]
def writemeans(dict, meansfile):
with open(meansfile, 'w') as f:
f.write('Condition,Mean,StdDev,StdError,N,Label\n')
for k, v in dict.iteritems():
f.write(k + ',')
for x in v:
f.write(str(x) + ',')
f.write('\n')
k = load_keys(keyfile)
cib, pumps = gf.gendictgf(fname)
mpumps = gpl.genlist(pumps)
print(mpumps)
writemeans(mpumps, meansfname)
#plotbar(mpumps, k, plotname)
m = f.next()
cond = m.split(',')[0]
left[cond] = []
right[cond] = []
sum[cond] = []
f.next()
for l in f:
k, r, s = map(str.strip, l.split(','))
k, r, s = map(float, [k, r, s])
left[cond].append(k)
right[cond].append(r)
sum[cond].append(s)
# Generates dictionaries listing the mean values, etc. for these counts.
mleft = gpl.genlist(left)
mright = gpl.genlist(right)
msum = gpl.genlist(sum)
k = ['112648', '112204', '423', '112648 + 112204', '112648 + 423', '112204 + 423']
# Writes the mean values, etc. for the sum of the count data into summary files.
with open('2011-0915_cellcounts_sum.txt', 'w') as g:
g.write('Condition\t[Mean, StdDev, StdErr, n, label]\n')
for j in k:
g.write('{0} \t {1} \n'.format(j, msum[j]))
with open('2011-0915_cellcounts_left.txt', 'w') as g:
g.write('Condition\t[Mean, StdDev, StdErr, n, label]\n')
for j in k:
for key, value in sorted(d.iteritems()):
try:
volperpump = value['cap']/value['freq']
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)
def writemeans_deltatime(fnameread, fnamewrite):
d = gpl.gendict_phase(fnameread, 'deltatime')
md = gpl.genlist(d)
writemeans(md, fnamewrite)
"""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)
print(os.path.abspath(os.getcwd()))
k = load_keys(keyfile)
d = genplotlib.gendict_phase(fname, 'deltatime')
print(d)
md = genplotlib.genlist(d)
print(md)
writemeans(md, meansfname)
plotbar(d, k, plotname)
x = genresfile_datafolder()
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)
from mn.cmn.cmn import *
import mn.gof.gfplot as gf
import sys
fname = sys.argv[1]
keyfile = sys.argv[2]
meansfname = sys.argv[3]
def writemeans(dict, meansfile):
with open(meansfile, 'w') as f:
f.write('Condition,Mean,StdDev,StdError,N,Label\n')
for k, v in dict.iteritems():
f.write(k + ',')
for x in v:
f.write(str(x) + ',')
f.write('\n')
k = load_keys(keyfile)
cib, pumps = gf.gendictgf(fname)
mpumps = gpl.genlist(pumps)
print(mpumps)
writemeans(mpumps, meansfname)
#plotbar(mpumps, k, plotname)
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')