def refixLaunch(exp,corr=False, trim=True, bins=8):
"""
"""
src = 'selected_dm_%s_WITH_drift_corr_onlyControl_True.csv' % exp
dm = CsvReader(src).dataMatrix()
lat1 = "saccLat1"
lat2 = "saccLat2"
if corr:
fix1 = "endX1CorrNormToHandle"
fix2 = "endX2CorrNormToHandle"
else:
fix1 = "endX1NormToHandle"
fix2 = "endX2NormToHandle"
for var in [lat1, lat2, fix1, fix2]:
dm = dm.select("%s != ''" % var)
# Trim the data
if trim:
dm = dm.selectByStdDev(["file"],lat2,
verbose=False)
dm = dm.removeField("__dummyCond__")
dm = dm.removeField("__stdOutlier__")
dm = dm.selectByStdDev(["file"], fix2,
verbose=False)
dm = dm.addField('saccLat2_perc', dtype=float)
dm = dm.calcPerc(lat2, 'saccLat2_perc', nBin=bins)
cmLat1 = dm.collapse(['saccLat2_perc'], lat1)
cmX = cmLat2 = dm.collapse(['saccLat2_perc'], lat2)
cmFix1 = dm.collapse(['saccLat2_perc'], fix1)
cmFix2 = dm.collapse(['saccLat2_perc'], fix2)
fig = plt.figure(figsize = (3,6))
plt.subplots_adjust(left=.2, bottom=.15)
colList = [orange[1], blue[1]]
nRows = 3
nCols = 1
nPlot = 0
lTitles = ["Landing pos 2", "Landing pos 1"]
lTitles.reverse()
for cmY in [cmFix2, cmFix1]:#, cmLat1]:
#nPlot +=1
#plt.subplot(nRows, nCols, nPlot)
color = colList.pop()
plt.plot(cmX['mean'], cmY['mean'], marker = 'o', color=color, \
markerfacecolor='white', markeredgecolor=color, \
markeredgewidth=1)
plt.xlabel("Sacc lat 2")
plt.legend(lTitles, frameon=False, loc='best')
plt.axhline(0, linestyle = "--", color = gray[3])
plt.savefig("Launch_site_refixations_%s_corr_%s.png" % (exp, corr))
def crossExpDescriptives(dm):
for exp in ['exp1', 'exp2', 'exp3']:
dm = CsvReader('data/%s.data.csv' % exp).dataMatrix()
if exp == 'exp1':
dm = dm.select('trialType == "control"')
elif exp == 'exp3':
print dm.collapse(['cond'], 'rt')
stats.R.load(dm)
lm = stats.R.lmer('rt ~ cond + (1+cond|subject_nr)')
print lm
rt = dm['rt']
print 'Exp = %s' % exp
print 'N = %d' % len(rt)
print 'RT = %.2f ms (%.2f)' % (rt.mean(), rt.std())
a = np.loadtxt('data/%s.fixdur.csv' % exp)
print 'Fixdur = %.2f ms (%.2f)' % (a.mean(), a.std())
src = 'selected_dm_004B_WITH_drift_corr_onlyControl_True.csv'
dm = CsvReader(src).dataMatrix()
sacc = "1"
dvNorm = "endX1CorrNormToHandle"
dvRaw = "endX1CorrNorm"
dm = onObject.onObject(dm, sacc)
print "ANOVA"
am = AnovaMatrix(dm, ["handle_side"], dvRaw, "file")._print(ret=True)
print am
print 'One-sample test scipy'
cm = dm.collapse(["file"], dvNorm)
ref = 0
t, p = scipy.stats.ttest_1samp(cm['mean'], ref)
print "t = ",t
print "p = ", p
# Paired-samples t-test:
print "paired samples t-test"
l = []
for handle in dm.unique("handle_side"):
handle_dm = dm.select("handle_side == '%s'" % handle)
cm = handle_dm.collapse(["file"], dvRaw)
l.append(cm["mean"])
t, p = scipy.stats.ttest_rel(l[0], l[1])
def ovp(exp,corr=False, trim=True, bins=8):
"""
"""
src = 'selected_dm_%s_WITH_drift_corr_onlyControl_True.csv' % exp
dm = CsvReader(src).dataMatrix()
lat1 = "saccLat1"
lat2 = "saccLat2"
prob = "saccCount"
dur1 = "durationFix1"
dur2 = "durationFix2"
total = "gazeDur"
rt = "rtFromStim"
if corr:
fix1 = "endX1CorrNormToHandle"
fix2 = "endX2CorrNormToHandle"
else:
fix1 = "endX1NormToHandle"
fix2 = "endX2NormToHandle"
for var in [lat1, lat2, fix1, fix2, dur1, dur2, total, rt]:
dm = dm.select("%s != ''" % var)
# Trim the data
if trim:
dm = dm.selectByStdDev(["file"],lat2,
verbose=False)
dm = dm.removeField("__dummyCond__")
dm = dm.removeField("__stdOutlier__")
dm = dm.selectByStdDev(["file"], fix2,
verbose=False)
dm = dm.addField('land2_perc', dtype=float)
dm = dm.calcPerc(fix2, 'land2_perc', nBin=bins)
cmLat1 = dm.collapse(['land2_perc'], lat1)
cmLat2 = dm.collapse(['land2_perc'], lat2)
cmFix1 = dm.collapse(['land2_perc'], fix1)
cmX = cmFix2 = dm.collapse(['land2_perc'], fix2)
cmProb = dm.collapse(['land2_perc'], prob)
cmDur1 = dm.collapse(['land2_perc'], dur1)
cmDur2 = dm.collapse(['land2_perc'], dur2)
cmTotal = dm.collapse(['land2_perc'], total)
cmRt = dm.collapse(['land2_perc'], rt)
fig = plt.figure(figsize = (3,10))
plt.subplots_adjust(left=.2, bottom=.15, hspace = .2)
lTitles = ["dur 1", "prob", "land 1", "rt", "total", "lat 1", "lat 2", "dur 2"]
lTitles.reverse()
nRows = len(lTitles)
nCols = 1
nPlot = 0
for cmY in [cmDur1, cmProb, cmFix1, cmRt, cmTotal, \
cmLat1, cmLat2, cmDur2]:
nPlot +=1
ax = plt.subplot(nRows, nCols, nPlot)
#color = colList.pop()
color = blue[1]
plt.plot(cmX['mean'], cmY['mean'], marker = 'o', color=color, \
markerfacecolor='white', markeredgecolor=color, \
markeredgewidth=1)
plt.ylabel(lTitles.pop())
plt.axvline(0, linestyle = "--", color = gray[3])
if nPlot == nRows:
plt.xlabel("Second landing position")
else:
ax.xaxis.set_ticklabels([])
plt.savefig("ovp2_%s_corr_%s.png" % (exp, corr))
