def word_summary(dm):
"""
desc:
Plots the mean pupil size for dark and bright words as a bar plot. The
time window is indicated by the PEAKWIN constant. This data is also
written to a .csv file.
arguments:
dm:
type: DataMatrix
"""
dm = (dm.type == "light") | (dm.type == "dark")
x = np.arange(dm.pupil.depth)
sm = DataMatrix(length=len(dm.word.unique))
sm.word = 0
sm.type = 0
sm.pupil_win = FloatColumn
sm.pupil_win_se = FloatColumn
sm.pupil_full = FloatColumn
sm.pupil_full_se = FloatColumn
for i, w in enumerate(dm.word.unique):
_dm = dm.word == w
sm.word[i] = w
sm.type[i] = (dm.word == w).type[0]
sm.pupil_win[i], sm.pupil_win_se[i] = size_se(_dm, PEAKWIN[0], PEAKWIN[1])
sm.pupil_full[i], sm.pupil_full_se[i] = size_se(_dm)
sm = operations.sort(sm, sm.pupil_win)
io.writetxt(sm, "%s/word_summary.csv" % OUTPUT_FOLDER)
plot.new(size=(4, 3))
dx = 0
for color, type_ in ((orange[1], "light"), (blue[1], "dark")):
sm_ = sm.type == type_
x = np.arange(len(sm_))
plt.plot(sm_.pupil_win, "o-", color=color)
if type_ == "dark":
yerr = (np.zeros(len(sm_)), sm_.pupil_win_se)
else:
yerr = (sm_.pupil_win_se, np.zeros(len(sm_)))
plt.errorbar(x, sm_.pupil_win, yerr=yerr, linestyle="", color=color, capsize=0)
plt.xlim(-1, 33)
plt.ylabel("Pupil size (normalized)")
plt.xlabel("Word")
plt.xticks([])
plot.save("word_summary")
for path in os.listdir('data-ratings'):
if not path.endswith('.csv'):
continue
print('Reading %s' % path)
if dm is None:
dm = io.readtxt('data-ratings/%s' % path)
else:
dm <<= io.readtxt('data-ratings/%s' % path)
# This word was misspelled
dm = dm.word != 'térébrant'
# There are 30 participants who provided 2 ratings for 122 words
assert(len(dm) == 30*2*102)
rm = DataMatrix(length=101)
rm.word = ''
rm._type = ''
rm.rating_brightness = FloatColumn
rm.rating_valence = FloatColumn
rm.rating_intensity = FloatColumn
for row, word in zip(rm, dm.word.unique):
dm_ = dm.word == word
dme = dm_.rating_type == 'emotion'
dmb = dm_.rating_type == 'brightness'
# Pénombre was accidentally rated twice.
assert(len(dmb)==30 or word == 'pénombre')
assert(len(dme)==30 or word == 'pénombre')
row.word = word
row._type = dme.type[0]
row.rating_brightness = dmb.rating.mean
row.rating_valence = dme.rating.mean
