def vsource_tfce_map(effect, stat_map, p, statistic, max_statistic):
brain = plot.GlassBrain(stat_map, show=False)
cbar = brain.plot_colorbar(orientation='vertical', show=False, width=0.2, w=1.1, h=2.8)
content = [brain.image(), cbar.image()]
brain.close()
cbar.close()
caption = FMText([f"{effect}; ", fmtxt.eq(statistic, max_statistic, 'max'), ', ', fmtxt.peq(p)])
return Figure(content, caption)
def test_eq():
"Test equation factory"
s = fmtxt.eq('t', 0.1234)
eq_(str(s), "t = 0.12")
eq_(html(s), "t = 0.12")
eq_(tex(s), "$t = 0.12$")
s = fmtxt.eq('t', 0.1234, 18)
eq_(str(s), "t(18) = 0.12")
eq_(html(s), "t<sub>18</sub> = 0.12")
eq_(tex(s), "$t_{18} = 0.12$")
s = fmtxt.peq(0.1299)
eq_(str(s), "p = .130")
eq_(html(s), "p = .130")
eq_(tex(s), "$p = .130$")
s = fmtxt.peq(0.0009)
eq_(str(s), "p < .001")
eq_(html(s), "p < .001")
eq_(tex(s), "$p < .001$")
def test_eq():
"Test equation factory"
s = fmtxt.eq('t', 0.1234)
assert str(s) == "t = 0.12"
assert html(s) == "t = 0.12"
assert tex(s) == "$t = 0.12$"
s = fmtxt.eq('t', 0.1234, 18)
assert str(s) == "t(18) = 0.12"
assert html(s) == "t<sub>18</sub> = 0.12"
assert tex(s) == "$t_{18} = 0.12$"
s = fmtxt.peq(0.1299)
assert str(s) == "p = .130"
assert html(s) == "p = .130"
assert tex(s) == "$p = .130$"
s = fmtxt.peq(0.0009)
assert str(s) == "p < .001"
assert html(s) == "p < .001"
assert tex(s) == "$p < .001$"
def test_eq():
"Test equation factory"
s = fmtxt.eq('t', 0.1234)
eq_(str(s), "t = 0.12")
eq_(html(s), "t = 0.12")
eq_(tex(s), "$t = 0.12$")
s = fmtxt.eq('t', 0.1234, 18)
eq_(str(s), "t(18) = 0.12")
eq_(html(s), "t<sub>18</sub> = 0.12")
eq_(tex(s), "$t_{18} = 0.12$")
s = fmtxt.peq(0.1299)
eq_(str(s), "p = .130")
eq_(html(s), "p = .130")
eq_(tex(s), "$p = .130$")
s = fmtxt.peq(0.0009)
eq_(str(s), "p < .001")
eq_(html(s), "p < .001")
eq_(tex(s), "$p < .001$")
def source_tfce_pmap(effect, pmap, statmap, max_statistic, surfer_kwargs, brain, difference=None):
if brain is None:
brain = plot.brain.brain(pmap.source, **surfer_kwargs)
else:
brain.remove_data()
brain.add_ndvar_p_map(pmap, statmap)
cbar = brain.plot_colorbar(orientation='vertical', show=False, width=0.2, w=1.1, h=2.8)
content = [brain.image(), cbar.image()]
cbar.close()
if difference is not None:
brain.remove_data()
brain.add_ndvar(difference)
cbar = brain.plot_colorbar(orientation='vertical', show=False, width=0.2, w=1.1, h=2.8)
content.append(brain.image())
content.append(cbar.image())
cbar.close()
statistic = statmap.info['meas']
p = pmap.min()
caption = FMText([f"{effect}; ", fmtxt.eq(statistic, max_statistic, 'max'), ', ', fmtxt.peq(p)])
fig = Figure(content, caption)
return fig, brain
def pairwise(Y, X, match=None, sub=None, # data in
par=True, corr='Hochberg', trend=True, # stats
title='{desc}', mirror=False, # layout
):
"""
pairwise comparison according to factor structure
"""
ct = celltable(Y, X, match=match, sub=sub)
test = _pairwise(ct.get_data(), within=ct.all_within, parametric=par, corr=corr, # levels=levels,
trend=trend)
# extract test results
k = len(ct)
indexes = test['pw_indexes']
statistic = test['statistic']
_K = test[statistic]
_P = test['p']
if corr:
_Pc = mcp_adjust(_P, corr)
_df = test['df']
_NStars = test['stars']
symbols = test['symbols']
# create TABLE
table = fmtxt.Table('l' + 'l' * (k - 1 + mirror))
title_desc = "Pairwise {0}".format(test['test'])
table.title(title.format(desc=title_desc))
table.caption(test['caption'])
# headings
table.cell()
cell_labels = ct.cell_labels()
for name in cell_labels[1 - mirror:]:
table.cell(name)
table.midrule()
# tex_df = fmtxt.Element(df, "_", digits=0)
if corr and not mirror:
subrows = range(3)
else:
subrows = range(2)
for row in range(0, k - 1 + mirror):
for subrow in subrows: # contains t/p
# names column
if subrow is 0:
table.cell(cell_labels[row], r"\textbf")
else:
table.cell()
# rows
for col in range(1 - mirror, k):
if row == col:
table.cell()
elif col > row:
index = indexes[(row, col)]
if subrow is 0:
tex_cell = fmtxt.eq(statistic, _K[index], df=_df[index],
stars=symbols[index],
of=3 + trend)
elif subrow is 1:
tex_cell = fmtxt.eq('p', _P[index], fmt='%.3f', drop0=True)
elif subrow is 2:
tex_cell = fmtxt.eq('p', _Pc[index], df='c',
fmt='%.3f', drop0=True)
table.cell(tex_cell)
else:
if mirror and corr and subrow == 0:
index = indexes[(col, row)]
p = _Pc[index]
table.cell(p, fmt='%.3f', drop0=True)
else:
table.cell()
return table
