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")
