Analysis demo

This example simulates some 2AFC data and demonstrates the analysis functions expyfun.analyze.dprime() and expyfun.analyze.barplot().

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# Author: Dan McCloy <drmccloy@uw.edu>
#
# License: BSD (3-clause)

import numpy as np
import pandas as pd
import matplotlib.pyplot as plt

import expyfun.analyze as ea

print(__doc__)

# simulate some 2AFC data
targets = 50
foils = 50
a_prob = 0.9
b_prob = 0.6
f_prob = 0.2
subjs = ['a', 'b', 'c', 'd', 'e']
a_hit = np.random.binomial(targets, a_prob, len(subjs))
b_hit = np.random.binomial(targets, b_prob, len(subjs))
a_fa = np.random.binomial(foils, f_prob, len(subjs))
b_fa = np.random.binomial(foils, f_prob, len(subjs))
a_miss = targets - a_hit
b_miss = targets - b_hit
a_cr = foils - a_fa
b_cr = foils - b_fa
data = pd.DataFrame(dict(a_hit=a_hit, a_miss=a_miss, a_fa=a_fa, a_cr=a_cr,
                         b_hit=b_hit, b_miss=b_miss, b_fa=b_fa, b_cr=b_cr),
                    index=subjs)
# calculate dprimes
a_dprime = ea.dprime(data[['a_hit', 'a_miss', 'a_fa', 'a_cr']])
b_dprime = ea.dprime(data[['b_hit', 'b_miss', 'b_fa', 'b_cr']])
results = pd.DataFrame(dict(ctrl=a_dprime, test=b_dprime))
# plot
subplt, barplt = ea.barplot(results, axis=0, err_bars='sd', lines=True,
                            brackets=[(0, 1)], bracket_text=[r'$p < 10^{-9}$'])
subplt.yaxis.set_label_text('d-prime +/- 1 s.d.')
subplt.set_title('Each line represents a different subject')

# significance brackets example
trials_per_cond = 100
conds = ['ctrl', 'test']
diffs = ['easy', 'hard']
colnames = ['-'.join([x, y]) for x, y in zip(conds * 2,
            np.tile(diffs, (2, 1)).T.ravel().tolist())]
cond_prob = [0.9, 0.8]
diff_prob = [0.9, 0.7]
cond_block = np.tile(np.atleast_2d(cond_prob).T, (2, len(subjs))).T
diff_block = np.tile(np.atleast_2d(np.repeat(diff_prob, 2)).T, len(subjs)).T
probs = cond_block * diff_block
shape = (len(subjs), len(conds) * len(diffs))
rawscores_targ = np.random.binomial(trials_per_cond, probs, shape)
rawscores_foil = np.random.binomial(trials_per_cond, probs, shape)
hmfc = np.c_[rawscores_targ.ravel(),
             (trials_per_cond - rawscores_targ).ravel(),
             (trials_per_cond - rawscores_foil).ravel(),
             rawscores_foil.ravel()]
dprimes = ea.dprime(hmfc).reshape(shape)
results = pd.DataFrame(dprimes, index=subjs, columns=colnames)
subplt, barplt = ea.barplot(results, axis=0, err_bars='sd', lines=True,
                            groups=[(0, 1), (2, 3)], group_names=diffs,
                            bar_names=conds * 2, bracket_group_lines=True,
                            brackets=[(0, 1), (2, 3), (0, 2), (1, 3),
                                      ([0, 1], 3)],  # [2, 3]
                            bracket_text=['foo', 'bar', 'baz', 'snafu',
                                          'foobar'])
subplt.yaxis.set_label_text('d-prime +/- 1 s.d.')
subplt.set_title('Each line represents a different subject')
plt.show()