def test_t_1samp():
"Test 1-sample t-test"
ds = datasets.get_uts(True)
y = ds['uts'].x
t = scipy.stats.ttest_1samp(y, 0, 0)[0]
assert_allclose(stats.t_1samp(y), t, 10)
y = ds['utsnd'].x
t = scipy.stats.ttest_1samp(y, 0, 0)[0]
assert_allclose(stats.t_1samp(y), t, 10)
def test_t_1samp():
"Test 1-sample t-test"
ds = datasets.get_uts(True)
y = ds['uts'].x
t = scipy.stats.ttest_1samp(y, 0, 0)[0]
assert_allclose(stats.t_1samp(y), t, 10)
y = ds['utsnd'].x
t = scipy.stats.ttest_1samp(y, 0, 0)[0]
assert_allclose(stats.t_1samp(y), t, 10)
def __init__(self,
y,
x,
c1=None,
c0=None,
match=None,
sub=None,
ds=None,
tail=0):
if match is None:
raise TypeError("The `match` argument needs to be specified for a "
"related measures t-test.")
ct = Celltable(y, x, match, sub, cat=(c1, c0), ds=ds, coercion=asvar)
c1, c0 = ct.cat
if not ct.all_within:
raise ValueError(
"conditions %r and %r do not have the same values "
"on %s" % (c1, c0, dataobj_repr(ct.match)))
n = len(ct.y) // 2
if n <= 2:
raise ValueError("Not enough observations for t-test (n=%i)" % n)
self._y = dataobj_repr(ct.y)
self._x = dataobj_repr(ct.x)
self.c1_mean = ct.y[:n].mean()
self.c0_mean = ct.y[n:].mean()
self.diff = ct.y[:n] - ct.y[n:]
self.df = n - 1
self.t = stats.t_1samp(self.diff.x[:, None])[0]
self.p = stats.ttest_p(self.t, self.df, tail)
self.tail = tail
self._c1 = c1
self._c0 = c0
def __init__(
self,
y: VarArg,
x: Union[CategorialArg, VarArg],
c1: CellArg = None,
c0: CellArg = None,
match: CategorialArg = None,
sub: IndexArg = None,
ds: Dataset = None,
tail: int = 0,
):
y1, y0, c1, c0, match, n, x_name, c1_name, c0_name = _related_measures_args(
y, x, c1, c0, match, ds, sub)
if n <= 2:
raise ValueError("Not enough observations for t-test (n=%i)" % n)
self._y = dataobj_repr(y1)
self._x = x_name
self._c1 = c1
self._c0 = c0
self.c1_mean = y1.mean()
self.c0_mean = y0.mean()
self.difference = y1 - y0
t = stats.t_1samp(self.difference.x[:, None])[0]
TTest.__init__(self, t, n - 1, tail)
self._match = dataobj_repr(match, True)
def __init__(self, y, x, c1=None, c0=None, match=None, sub=None, ds=None,
tail=0):
if match is None:
assert c1 is None and c0 is None
y1 = asvar(y, sub, ds)
n = len(y1)
y0 = asvar(x, sub, ds, n)
self._y = dataobj_repr(y1)
self._x = dataobj_repr(y0)
else:
ct = Celltable(y, x, match, sub, cat=(c1, c0), ds=ds, coercion=asvar)
c1, c0 = ct.cat
if not ct.all_within:
raise ValueError("conditions %r and %r do not have the same values "
"on %s" % (c1, c0, dataobj_repr(ct.match)))
n = len(ct.y) // 2
self._y = dataobj_repr(ct.y)
self._x = dataobj_repr(ct.x)
y1 = ct.y[:n]
y0 = ct.y[n:]
if n <= 2:
raise ValueError("Not enough observations for t-test (n=%i)" % n)
self.c1_mean = y1.mean()
self.c0_mean = y0.mean()
self.difference = y1 - y0
t = stats.t_1samp(self.difference.x[:, None])[0]
TTest.__init__(self, t, n - 1, tail)
self._match = None if match is None else dataobj_repr(match)
self._c1 = c1
self._c0 = c0
def __init__(self, y, match=None, sub=None, ds=None, tail=0):
ct = Celltable(y, None, match, sub, ds=ds, coercion=asvar)
n = len(ct.y)
if n <= 2:
raise ValueError("Not enough observations for t-test (n=%i)" % n)
self.mean = ct.y.mean()
self._y = dataobj_repr(ct.y)
t = stats.t_1samp(ct.y.x[:, None])[0]
TTest.__init__(self, t, n - 1, tail)
def __init__(self, y, match=None, sub=None, ds=None, tail=0):
ct = Celltable(y, None, match, sub, ds=ds, coercion=asvar)
n = len(ct.y)
if n <= 2:
raise ValueError("Not enough observations for t-test (n=%i)" % n)
self._y = dataobj_repr(ct.y)
self.df = n - 1
self.t = stats.t_1samp(ct.y.x[:, None])[0]
self.p = stats.ttest_p(self.t, self.df, tail)
self.tail = tail
def __init__(self, y, match=None, sub=None, ds=None, tail=0):
ct = Celltable(y, None, match, sub, ds=ds, coercion=asvar)
n = len(ct.Y)
if n <= 2:
raise ValueError("Not enough observations for t-test (n=%i)" % n)
self._y = dataobj_repr(ct.Y)
self.df = n - 1
self.t = stats.t_1samp(ct.Y.x[:, None])[0]
self.p = stats.ttest_p(self.t, self.df, tail)
self.tail = tail
def __init__(
self,
y: VarArg,
match: CategorialArg = None,
sub: IndexArg = None,
ds: Dataset = None,
tail: int = 0,
):
ct = Celltable(y, None, match, sub, ds=ds, coercion=asvar)
n = len(ct.y)
if n <= 2:
raise ValueError("Not enough observations for t-test (n=%i)" % n)
self.mean = ct.y.mean()
self._y = dataobj_repr(ct.y)
t = stats.t_1samp(ct.y.x[:, None])[0]
TTest.__init__(self, t, n - 1, tail)
def __init__(self, y, x, c1=None, c0=None, match=None, sub=None, ds=None,
tail=0):
if match is None:
raise TypeError("The `match` argument needs to be specified for a "
"related measures t-test.")
ct = Celltable(y, x, match, sub, cat=(c1, c0), ds=ds, coercion=asvar)
c1, c0 = ct.cat
if not ct.all_within:
raise ValueError("conditions %r and %r do not have the same values "
"on %s" % (c1, c0, dataobj_repr(ct.match)))
n = len(ct.Y) // 2
if n <= 2:
raise ValueError("Not enough observations for t-test (n=%i)" % n)
self._y = dataobj_repr(ct.Y)
self._x = dataobj_repr(ct.X)
self.diff = ct.Y[:n] - ct.Y[n:]
self.df = n - 1
self.t = stats.t_1samp(self.diff.x[:, None])[0]
self.p = stats.ttest_p(self.t, self.df, tail)
self.tail = tail
self._c1 = c1
self._c0 = c0