def test_barplot():
"""Test bar plot function
"""
import matplotlib.pyplot as plt
ax = plt.subplot(1, 1, 1)
tmp1 = np.arange(4) # 1-Dim
tmp2 = np.arange(20).reshape((4, 5)) # 2-Dim
ea.barplot(tmp1, err_bars=tmp1, brackets=[(0, 1), (2, 3)],
bracket_text=['foo', 'bar'], ax=ax)
ea.barplot(tmp1, groups=[[0, 1, 2], [3]], eq_group_widths=True,
brackets=[([0], 3)], bracket_text='foo')
ea.barplot(tmp2, lines=True, ylim=(0, 2), err_bars='se')
ea.barplot(tmp2, groups=[[0, 1], [2, 3]], err_bars='ci',
group_names=['foo', 'bar'])
extns = ['eps', 'pdf', 'png', 'raw', 'svg'] # jpg, tif not supported
for ext in extns:
fname = op.join(temp_dir, 'temp.' + ext)
ea.barplot(tmp2, groups=[[0, 1, 2], [3]], err_bars='sd', fname=fname)
assert_raises(ValueError, ea.barplot, np.arange(8).reshape((2, 2, 2)))
assert_raises(ValueError, ea.barplot, tmp2, err_bars='foo')
assert_raises(ValueError, ea.barplot, tmp2, gap_size=1.1)
assert_raises(ValueError, ea.barplot, tmp1, err_bars=np.arange(3))
assert_raises(ValueError, ea.barplot, tmp1, err_bars='sd')
assert_raises(ValueError, ea.barplot, tmp1, brackets=[(0, 1)],
bracket_text=['foo', 'bar'])
assert_raises(ValueError, ea.barplot, tmp1, brackets=[(1,)],
bracket_text=['foo'])
def test_barplot_with_pandas():
"""Test bar plot function pandas support"""
import pandas as pd
tmp = pd.DataFrame(np.arange(20).reshape((4, 5)),
columns=['a', 'b', 'c', 'd', 'e'],
index=['one', 'two', 'three', 'four'])
ea.barplot(tmp)
ea.barplot(tmp, axis=0, lines=True)
def test_barplot_with_pandas():
"""Test bar plot function pandas support"""
import pandas as pd
tmp = pd.DataFrame(np.arange(20).reshape((4, 5)),
columns=['a', 'b', 'c', 'd', 'e'],
index=['one', 'two', 'three', 'four'])
ea.barplot(tmp)
ea.barplot(tmp, axis=0, lines=True)
def test_barplot_multiple():
"""Test with multiple data points per bar and calculated ranges."""
import matplotlib.pyplot as plt
rng = np.random.RandomState(0)
tmp = (rng.randn(20) + np.arange(20)).reshape((5, 4)) # 2-dim
_, axs = plt.subplots(1, 4, sharey=False)
ea.barplot(tmp, lines=True, err_bars='sd', ax=axs[0], smart_defaults=False)
ea.barplot(tmp, lines=True, err_bars='ci', ax=axs[1], axis=0)
ea.barplot(tmp, lines=True, err_bars='se', ax=axs[2], ylim=(0, 30))
ea.barplot(tmp, lines=True, err_bars='se', ax=axs[3],
groups=[[0, 1, 2], [3, 4]], bracket_group_lines=True,
brackets=[(0, 1), (1, 2), (3, 4), ([0, 1, 2], [3, 4])],
bracket_text=['foo', 'bar', 'baz', 'snafu'])
extns = ['pdf'] # jpg, tif not supported; 'png', 'raw', 'svg' not tested
for ext in extns:
fname = op.join(temp_dir, 'temp.' + ext)
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
ea.barplot(tmp, groups=[[0, 1, 2], [3]], err_bars='sd', axis=0,
fname=fname)
plt.close()
_check_warnings(w)
plt.close('all')
c_prob = 0.9
t_prob = 0.6
subjs = ['a', 'b', 'c', 'd', 'e']
ctrl = np.random.binomial(trials, c_prob, len(subjs))
test = np.random.binomial(trials, t_prob, len(subjs))
ctrl_miss = trials - ctrl
test_miss = trials - test
data = pd.DataFrame(dict(ctrl_hit=ctrl, ctrl_miss=ctrl_miss,
test_hit=test, test_miss=test_miss), index=subjs)
# calculate dprimes
ctrl_dprime = ea.dprime_2afc(data[['ctrl_hit', 'ctrl_miss']])
test_dprime = ea.dprime_2afc(data[['test_hit', 'test_miss']])
results = pd.DataFrame(dict(ctrl=ctrl_dprime, test=test_dprime))
# plot
plt.ion()
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())]
cprob = [0.8, 0.5]
dprob = [0.9, 0.6]
cblock = np.tile(np.atleast_2d(cprob).T, (2, len(subjs))).T
dblock = np.tile(np.atleast_2d(np.repeat(dprob, 2)).T, len(subjs)).T
probs = cblock * dblock
rawscores = np.random.binomial(trials_per_cond, probs, (len(subjs), len(conds)
# params
nreps = 20
lang_order = np.array((0, 2, 1)) # eng, nld, hin
feats = ('Continuant', 'Sonorant', 'Del. Rel.', 'Voiced',
'Aspirated', 'Labial', 'Coronal', 'Dorsal')
feat_names = ['\n' + n if ix % 2 else n + '\n' for ix, n in enumerate(feats)]
# EER matrix dims (from readme): repetition, testLanguage, kFold, feature
id_ = loadmat('EER_ID.mat')['EER'] # (50, 3, 4, 8)
bars = id_[:nreps].mean(-2) # average over kFold
bars = bars[:, lang_order, :] # arrange languages in order: eng, nld, hin
bars = bars.swapaxes(-1, -2) # transpose last 2 dims
bars = bars.reshape(-1, 24) # flatten last two axes (keep "repetition")
# grouping indices
groups = np.arange(bars.shape[-1]).reshape(-1, 3)
# plot it
fig = plt.figure(figsize=(6.5, 2.75))
ax = plt.Axes(fig, [0.1, 0.2, 0.875, 0.7])
fig.add_axes(ax)
p, b = barplot(bars, axis=0, err_bars='sd', groups=groups, gap_size=0.5,
bar_names='', ylim=(0.2, 0.6), group_names=feat_names,
ax=ax, bar_kwargs=dict(color=('0.3', '0.6', '0.9')))
p.yaxis.set_label_text('Equal Error Rate')
p.yaxis.set_ticks(np.linspace(0.2, 0.6, 5))
xmin, xmax = p.get_axes().get_xlim()
p.hlines(0.5, xmin, xmax, linestyles='--')
#plt.tight_layout()
ax.legend(b.get_children()[:3], ('English', 'Dutch', 'Hindi'), loc=(0.8, 0.8),
fontsize=10)
plt.draw()
fig.savefig('eer-barplot.pdf')
def test_barplot():
"""Test bar plot function
"""
import matplotlib.pyplot as plt
rng = np.random.RandomState(0)
# TESTS THAT SHOULD FAIL
tmp = np.ones(4) + rng.rand(4)
err = 0.1 + tmp / 5.
# too many data dimensions:
assert_raises(ValueError, ea.barplot, np.arange(8).reshape((2, 2, 2)))
# gap_size > 1:
assert_raises(ValueError, ea.barplot, tmp, gap_size=1.1)
# shape mismatch between data & error bars:
assert_raises(ValueError, ea.barplot, tmp, err_bars=np.arange(3))
# bad err_bar string:
assert_raises(ValueError, ea.barplot, tmp, err_bars='foo')
# cannot calculate 'sd' error bars with only 1 value per bar:
assert_raises(ValueError, ea.barplot, tmp, err_bars='sd')
# mismatched lengths of brackets & bracket_text:
assert_raises(ValueError,
ea.barplot,
tmp,
brackets=[(0, 1)],
bracket_text=['foo', 'bar'])
# bad bracket spec:
assert_raises(ValueError,
ea.barplot,
tmp,
brackets=[(1, )],
bracket_text=['foo'])
# TEST WITH SINGLE DATA POINT & SINGLE ERROR BAR SPEC.
ea.barplot(2, err_bars=0.2)
# TESTS WITH ONE DATA POINT PER BAR & USER-SPECIFIED ERROR BAR RANGES
_, axs = plt.subplots(1, 5, sharey=False)
ea.barplot(tmp,
err_bars=err,
brackets=([2, 3], [0, 1]),
ax=axs[0],
bracket_text=['foo', 'bar'],
bracket_inline=True)
ea.barplot(tmp,
err_bars=err,
brackets=((0, 2), (1, 3)),
ax=axs[1],
bracket_text=['foo', 'bar'])
ea.barplot(tmp,
err_bars=err,
brackets=[[2, 1], [0, 3]],
ax=axs[2],
bracket_text=['foo', 'bar'])
ea.barplot(tmp,
err_bars=err,
brackets=[(0, 1), (0, 2), (0, 3)],
bracket_text=['foo', 'bar', 'baz'],
ax=axs[3])
ea.barplot(tmp,
err_bars=err,
brackets=[(0, 1), (2, 3), (0, 2), (1, 3)],
bracket_text=['foo', 'bar', 'baz', 'snafu'],
ax=axs[4])
ea.barplot(tmp,
groups=[[0, 1, 2], [3]],
eq_group_widths=True,
brackets=[(0, 1), (1, 2), ([0, 1, 2], 3)],
bracket_text=['foo', 'bar', 'baz'],
bracket_group_lines=True)
# TESTS WITH MULTIPLE DATA POINTS PER BAR & CALCULATED ERROR BAR RANGES
tmp = (rng.randn(20) + np.arange(20)).reshape((5, 4)) # 2-dim
_, axs = plt.subplots(1, 4, sharey=False)
ea.barplot(tmp, lines=True, err_bars='sd', ax=axs[0], smart_defaults=False)
ea.barplot(tmp, lines=True, err_bars='ci', ax=axs[1], axis=0)
ea.barplot(tmp, lines=True, err_bars='se', ax=axs[2], ylim=(0, 30))
ea.barplot(tmp,
lines=True,
err_bars='se',
ax=axs[3],
groups=[[0, 1, 2], [3, 4]],
bracket_group_lines=True,
brackets=[(0, 1), (1, 2), (3, 4), ([0, 1, 2], [3, 4])],
bracket_text=['foo', 'bar', 'baz', 'snafu'])
extns = ['eps', 'pdf', 'png', 'raw', 'svg'] # jpg, tif not supported
for ext in extns:
fname = op.join(temp_dir, 'temp.' + ext)
with warnings.catch_warnings(record=True) as w:
ea.barplot(tmp,
groups=[[0, 1, 2], [3]],
err_bars='sd',
axis=0,
fname=fname)
plt.close()
_check_warnings(w)
def test_barplot():
"""Test bar plot function
"""
import matplotlib.pyplot as plt
rng = np.random.RandomState(0)
ea.barplot(2, err_bars=0.2) # 0-dim
tmp = np.ones(4) + rng.rand(4) # 1-dim
err = 0.1 + tmp / 5.
_, axs = plt.subplots(1, 5, sharey=False)
ea.barplot(tmp, err_bars=err, brackets=([2, 3], [0, 1]), ax=axs[0],
bracket_text=['foo', 'bar'])
ea.barplot(tmp, err_bars=err, brackets=((0, 2), (1, 3)), ax=axs[1],
bracket_text=['foo', 'bar'])
ea.barplot(tmp, err_bars=err, brackets=[[2, 1], [0, 3]], ax=axs[2],
bracket_text=['foo', 'bar'])
ea.barplot(tmp, err_bars=err, brackets=[(0, 1), (0, 2), (0, 3)],
bracket_text=['foo', 'bar', 'baz'], ax=axs[3])
ea.barplot(tmp, err_bars=err, brackets=[(0, 1), (2, 3), (0, 2), (1, 3)],
bracket_text=['foo', 'bar', 'baz', 'snafu'], ax=axs[4])
ea.barplot(tmp, groups=[[0, 1, 2], [3]], eq_group_widths=True,
brackets=[(0, 1), (1, 2), ([0, 1, 2], 3)],
bracket_text=['foo', 'bar', 'baz'],
bracket_group_lines=True)
assert_raises(ValueError, ea.barplot, tmp, err_bars=np.arange(3))
assert_raises(ValueError, ea.barplot, tmp, err_bars='sd')
assert_raises(ValueError, ea.barplot, tmp, brackets=[(0, 1)],
bracket_text=['foo', 'bar'])
assert_raises(ValueError, ea.barplot, tmp, brackets=[(1,)],
bracket_text=['foo'])
tmp = (rng.randn(20) + np.arange(20)).reshape((5, 4)) # 2-dim
_, axs = plt.subplots(1, 4, sharey=False)
ea.barplot(tmp, lines=True, err_bars='sd', ax=axs[0], smart_defaults=False)
ea.barplot(tmp, lines=True, err_bars='ci', ax=axs[1], axis=0)
ea.barplot(tmp, lines=True, err_bars='se', ax=axs[2], ylim=(0, 30))
ea.barplot(tmp, lines=True, err_bars='se', ax=axs[3],
groups=[[0, 1, 2], [3, 4]], bracket_group_lines=True,
brackets=[(0, 1), (1, 2), (3, 4), ([0, 1, 2], [3, 4])],
bracket_text=['foo', 'bar', 'baz', 'snafu'])
extns = ['eps', 'pdf', 'png', 'raw', 'svg'] # jpg, tif not supported
for ext in extns:
fname = op.join(temp_dir, 'temp.' + ext)
ea.barplot(tmp, groups=[[0, 1, 2], [3]], err_bars='sd', axis=0,
fname=fname)
assert_raises(ValueError, ea.barplot, np.arange(8).reshape((2, 2, 2)))
assert_raises(ValueError, ea.barplot, tmp, err_bars='foo')
assert_raises(ValueError, ea.barplot, tmp, gap_size=1.1)
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]
def test_barplot():
"""Test bar plot function
"""
import matplotlib.pyplot as plt
rng = np.random.RandomState(0)
# TESTS THAT SHOULD FAIL
tmp = np.ones(4) + rng.rand(4)
err = 0.1 + tmp / 5.
# too many data dimensions:
assert_raises(ValueError, ea.barplot, np.arange(8).reshape((2, 2, 2)))
# gap_size > 1:
assert_raises(ValueError, ea.barplot, tmp, gap_size=1.1)
# shape mismatch between data & error bars:
assert_raises(ValueError, ea.barplot, tmp, err_bars=np.arange(3))
# bad err_bar string:
assert_raises(ValueError, ea.barplot, tmp, err_bars='foo')
# cannot calculate 'sd' error bars with only 1 value per bar:
assert_raises(ValueError, ea.barplot, tmp, err_bars='sd')
# mismatched lengths of brackets & bracket_text:
assert_raises(ValueError, ea.barplot, tmp, brackets=[(0, 1)],
bracket_text=['foo', 'bar'])
# bad bracket spec:
assert_raises(ValueError, ea.barplot, tmp, brackets=[(1,)],
bracket_text=['foo'])
# TEST WITH SINGLE DATA POINT & SINGLE ERROR BAR SPEC.
ea.barplot(2, err_bars=0.2)
# TESTS WITH ONE DATA POINT PER BAR & USER-SPECIFIED ERROR BAR RANGES
_, axs = plt.subplots(1, 5, sharey=False)
ea.barplot(tmp, err_bars=err, brackets=([2, 3], [0, 1]), ax=axs[0],
bracket_text=['foo', 'bar'], bracket_inline=True)
ea.barplot(tmp, err_bars=err, brackets=((0, 2), (1, 3)), ax=axs[1],
bracket_text=['foo', 'bar'])
ea.barplot(tmp, err_bars=err, brackets=[[2, 1], [0, 3]], ax=axs[2],
bracket_text=['foo', 'bar'])
ea.barplot(tmp, err_bars=err, brackets=[(0, 1), (0, 2), (0, 3)],
bracket_text=['foo', 'bar', 'baz'], ax=axs[3])
ea.barplot(tmp, err_bars=err, brackets=[(0, 1), (2, 3), (0, 2), (1, 3)],
bracket_text=['foo', 'bar', 'baz', 'snafu'], ax=axs[4])
ea.barplot(tmp, groups=[[0, 1, 2], [3]], eq_group_widths=True,
brackets=[(0, 1), (1, 2), ([0, 1, 2], 3)],
bracket_text=['foo', 'bar', 'baz'],
bracket_group_lines=True)
# TESTS WITH MULTIPLE DATA POINTS PER BAR & CALCULATED ERROR BAR RANGES
tmp = (rng.randn(20) + np.arange(20)).reshape((5, 4)) # 2-dim
_, axs = plt.subplots(1, 4, sharey=False)
ea.barplot(tmp, lines=True, err_bars='sd', ax=axs[0], smart_defaults=False)
ea.barplot(tmp, lines=True, err_bars='ci', ax=axs[1], axis=0)
ea.barplot(tmp, lines=True, err_bars='se', ax=axs[2], ylim=(0, 30))
ea.barplot(tmp, lines=True, err_bars='se', ax=axs[3],
groups=[[0, 1, 2], [3, 4]], bracket_group_lines=True,
brackets=[(0, 1), (1, 2), (3, 4), ([0, 1, 2], [3, 4])],
bracket_text=['foo', 'bar', 'baz', 'snafu'])
extns = ['eps', 'pdf', 'png', 'raw', 'svg'] # jpg, tif not supported
for ext in extns:
fname = op.join(temp_dir, 'temp.' + ext)
with warnings.catch_warnings(record=True) as w:
ea.barplot(tmp, groups=[[0, 1, 2], [3]], err_bars='sd', axis=0,
fname=fname)
plt.close()
_check_warnings(w)
# License: BSD (3-clause)
print(__doc__)
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import expyfun.analyze as ea
# simulate some 2AFC data
trials = 100
c_prob = 0.9
t_prob = 0.6
subjs = ['a', 'b', 'c', 'd', 'e']
ctrl = np.random.binomial(trials, c_prob, len(subjs))
test = np.random.binomial(trials, t_prob, len(subjs))
ctrl_miss = trials - ctrl
test_miss = trials - test
data = pd.DataFrame(dict(ctrl_hit=ctrl, ctrl_miss=ctrl_miss,
test_hit=test, test_miss=test_miss), index=subjs)
# calculate dprimes
ctrl_dprime = ea.dprime_2afc(data[['ctrl_hit', 'ctrl_miss']])
test_dprime = ea.dprime_2afc(data[['test_hit', 'test_miss']])
results = pd.DataFrame(dict(ctrl=ctrl_dprime, test=test_dprime))
# plot
plt.ion()
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(u'd-prime ± 1 s.d.')
subplt.set_title('Each line represents a different subject')
bar_kw = {'linewidth': 2, 'color': '1'}
line_kw = {'color': 'k', 'marker': 'o', 'fillstyle': 'full', 'markersize': 5,
'alpha': 0.3, 'lw': 0}
error_kw = {'ecolor': 'k', 'linewidth': 2, 'capsize': 5, 'capthick': 1.25}
bracket_kw = {'color': 'k', 'clip_on': False}
pval_kwargs = {'fontsize': 10.5}
#######################################
# Create figure and plot
fig, ax = plt.subplots(nrows=1, ncols=1, figsize=(fig_width_1col * 1.5, 4.5),
sharey=True, facecolor='white')
fig.subplots_adjust(top=0.75, bottom=0.2, left=0.14, right=0.975)
p, b = barplot(data, axis=0, ylim=[45, 70], err_bars='se', lines=False,
groups=groups, gap_size=0.4, brackets=brackets,
bracket_text=p_val_text, pval_kwargs=pval_kwargs,
bracket_group_lines=True, bar_names=bar_labels,
bar_kwargs=bar_kw, err_kwargs=error_kw, line_kwargs=line_kw,
bracket_kwargs=bracket_kw, ax=ax, smart_defaults=False)
ax.axhline(50., c='r', ls='dashed', label='Chance', lw=1.25)
ax.set_ylabel('Accuracy (%)', fontsize=label_fontsize + 2)
# Add text showing actual scores
for mi, mean in enumerate(data_means):
bbox = b[mi].get_bbox()
xpos = (bbox.x0 + bbox.x1) / 2.
ax.annotate('%0.1f' % (mean), xy=(xpos, 47), xycoords=ax.transData,
ha='center', va='center', fontsize=9, color='0.35')
# Fix ticks and margins
ax.locator_params(axis='y', nbins=6)
def test_barplot_single_spec(tmp_err):
"""Test with one data point per bar and user-specified err ranges."""
import matplotlib.pyplot as plt
tmp, err = tmp_err
_, axs = plt.subplots(1, 5, sharey=False)
ea.barplot(tmp, err_bars=err, brackets=([2, 3], [0, 1]), ax=axs[0],
bracket_text=['foo', 'bar'], bracket_inline=True)
ea.barplot(tmp, err_bars=err, brackets=((0, 2), (1, 3)), ax=axs[1],
bracket_text=['foo', 'bar'])
ea.barplot(tmp, err_bars=err, brackets=[[2, 1], [0, 3]], ax=axs[2],
bracket_text=['foo', 'bar'])
ea.barplot(tmp, err_bars=err, brackets=[(0, 1), (0, 2), (0, 3)],
bracket_text=['foo', 'bar', 'baz'], ax=axs[3])
ea.barplot(tmp, err_bars=err, brackets=[(0, 1), (2, 3), (0, 2), (1, 3)],
bracket_text=['foo', 'bar', 'baz', 'snafu'], ax=axs[4])
ea.barplot(tmp, groups=[[0, 1, 2], [3]], eq_group_widths=True,
brackets=[(0, 1), (1, 2), ([0, 1, 2], 3)],
bracket_text=['foo', 'bar', 'baz'],
bracket_group_lines=True)
plt.close('all')
def test_barplot_single(tmp_err):
"""Test with single data point and single error bar spec."""
import matplotlib.pyplot as plt
tmp, err = tmp_err
ea.barplot(2, err_bars=0.2)
plt.close('all')
