[Scipy-svn] r6977 - in trunk: doc/release scipy/stats scipy/stats/tests
scipy-svn at scipy.org
scipy-svn at scipy.org
Mon Nov 29 09:46:33 EST 2010
Author: rgommers
Date: 2010-11-29 08:46:33 -0600 (Mon, 29 Nov 2010)
New Revision: 6977
Modified:
trunk/doc/release/0.9.0-notes.rst
trunk/scipy/stats/mstats_basic.py
trunk/scipy/stats/tests/test_mstats_basic.py
Log:
DEP: remove deprecated functions from mstats, in line with changes to stats.
Modified: trunk/doc/release/0.9.0-notes.rst
===================================================================
--- trunk/doc/release/0.9.0-notes.rst 2010-11-29 14:46:00 UTC (rev 6976)
+++ trunk/doc/release/0.9.0-notes.rst 2010-11-29 14:46:33 UTC (rev 6977)
@@ -148,4 +148,5 @@
Many functions in ``scipy.stats`` that are either available from numpy or have
been superseded, and have been deprecated since version 0.7, have been removed:
`std`, `var`, `mean`, `median`, `cov`, `corrcoef`, `z`, `zs`, `stderr`,
-`samplestd`, `samplevar`, `pdfapprox`, `pdf_moments` and `erfc`.
+`samplestd`, `samplevar`, `pdfapprox`, `pdf_moments` and `erfc`. These changes
+are mirrored in ``scipy.stats.mstats``.
Modified: trunk/scipy/stats/mstats_basic.py
===================================================================
--- trunk/scipy/stats/mstats_basic.py 2010-11-29 14:46:00 UTC (rev 6976)
+++ trunk/scipy/stats/mstats_basic.py 2010-11-29 14:46:33 UTC (rev 6977)
@@ -13,7 +13,6 @@
__all__ = ['argstoarray',
'betai',
- 'cov', # from np.ma
'chisquare','count_tied_groups',
'describe',
'f_oneway','f_value_wilks_lambda','find_repeats','friedmanchisquare',
@@ -27,13 +26,13 @@
'obrientransform',
'pearsonr','plotting_positions','pointbiserialr',
'rankdata',
- 'samplestd','samplevar','scoreatpercentile','sem','std',
+ 'scoreatpercentile','sem',
'sen_seasonal_slopes','signaltonoise','skew','skewtest','spearmanr',
'theilslopes','threshold','tmax','tmean','tmin','trim','trimboth',
'trimtail','trima','trimr','trimmed_mean','trimmed_std',
'trimmed_stde','trimmed_var','tsem','ttest_1samp','ttest_onesamp',
'ttest_ind','ttest_rel','tvar',
- 'var','variation',
+ 'variation',
'winsorize',
'zmap', 'zscore'
]
@@ -301,11 +300,8 @@
"""Returns the sign of x, or 0 if x is masked."""
return ma.filled(np.sign(x), 0)
-cov = ma.cov
-corrcoef = ma.corrcoef
-
def pearsonr(x,y):
"""Calculates a Pearson correlation coefficient and the p-value for testing
non-correlation.
@@ -1883,49 +1879,6 @@
return m/sd
-def samplevar(data, axis=0):
- """Returns a biased estimate of the variance of the data, as the average
- of the squared deviations from the mean.
-
- Parameters
- ----------
- data : sequence
- Input data
- axis : {0, int} optional
- Axis along which to compute. If None, the computation is performed
- on a flat version of the array.
- """
- return ma.asarray(data).var(axis=axis,ddof=0)
-
-
-def samplestd(data, axis=0):
- """Returns a biased estimate of the standard deviation of the data, as the
- square root of the average squared deviations from the mean.
-
- Parameters
- ----------
- data : sequence
- Input data
- axis : {0,int} optional
- Axis along which to compute. If None, the computation is performed
- on a flat version of the array.
-
- Notes
- -----
- samplestd(a) is equivalent to a.std(ddof=0)
-
- """
- return ma.asarray(data).std(axis=axis,ddof=0)
-
-
-def var(a,axis=None):
- return ma.asarray(a).var(axis=axis,ddof=1)
-var.__doc__ = np.var.__doc__
-
-def std(a,axis=None):
- return ma.asarray(a).std(axis=axis,ddof=1)
-std.__doc__ = np.std.__doc__
-
def sem(a, axis=0):
a, axis = _chk_asarray(a, axis)
n = a.count(axis=axis)
Modified: trunk/scipy/stats/tests/test_mstats_basic.py
===================================================================
--- trunk/scipy/stats/tests/test_mstats_basic.py 2010-11-29 14:46:00 UTC (rev 6976)
+++ trunk/scipy/stats/tests/test_mstats_basic.py 2010-11-29 14:46:33 UTC (rev 6977)
@@ -193,34 +193,6 @@
2.8,2.8,2.5,2.4,2.3,2.1,1.7,1.7,1.5,1.3,1.3,1.2,1.2,1.1,
0.8,0.7,0.6,0.5,0.2,0.2,0.1,np.nan]
assert_almost_equal(mstats.pointbiserialr(x, y)[0], 0.36149, 5)
- #
- def test_cov(self):
- "Tests the cov function."
- x = ma.array([[1,2,3],[4,5,6]], mask=[[1,0,0],[0,0,0]])
- c = mstats.cov(x[0])
- assert_equal(c, x[0].var(ddof=1))
- c = mstats.cov(x[1])
- assert_equal(c, x[1].var(ddof=1))
- c = mstats.cov(x)
- assert_equal(c[1,0], (x[0].anom()*x[1].anom()).sum())
- #
- x = [[nan,nan, 4, 2, 16, 26, 5, 1, 5, 1, 2, 3, 1],
- [ 4, 3, 5, 3, 2, 7, 3, 1, 1, 2, 3, 5, 3],
- [ 3, 2, 5, 6, 18, 4, 9, 1, 1,nan, 1, 1,nan],
- [nan, 6, 11, 4, 17,nan, 6, 1, 1, 2, 5, 1, 1]]
- x = ma.fix_invalid(x).T
- (winter,spring,summer,fall) = x.T
- #
- assert_almost_equal(mstats.cov(winter,winter,bias=True),
- winter.var(ddof=0))
- assert_almost_equal(mstats.cov(winter,winter,bias=False),
- winter.var(ddof=1))
- assert_almost_equal(mstats.cov(winter,spring)[0,1], 7.7)
- assert_almost_equal(mstats.cov(winter,spring)[1,0], 7.7)
- assert_almost_equal(mstats.cov(winter,summer)[0,1], 19.1111111, 7)
- assert_almost_equal(mstats.cov(winter,summer)[1,0], 19.1111111, 7)
- assert_almost_equal(mstats.cov(winter,fall)[0,1], 20)
- assert_almost_equal(mstats.cov(winter,fall)[1,0], 20)
class TestTrimming(TestCase):
@@ -403,35 +375,7 @@
note that length(testcase) = 4
"""
testcase = ma.fix_invalid([1,2,3,4,np.nan])
- #
- def test_std(self):
- y = mstats.std(self.testcase)
- assert_almost_equal(y,1.290994449)
- def test_var(self):
- """
- var(testcase) = 1.666666667 """
- #y = stats.var(self.shoes[0])
- #assert_approx_equal(y,6.009)
- y = mstats.var(self.testcase)
- assert_almost_equal(y,1.666666667)
-
- def test_samplevar(self):
- """
- R does not have 'samplevar' so the following was used
- var(testcase)*(4-1)/4 where 4 = length(testcase)
- """
- #y = stats.samplevar(self.shoes[0])
- #assert_approx_equal(y,5.4081)
- y = mstats.samplevar(self.testcase)
- assert_almost_equal(y,1.25)
-
- def test_samplestd(self):
- #y = stats.samplestd(self.shoes[0])
- #assert_approx_equal(y,2.325532197)
- y = mstats.samplestd(self.testcase)
- assert_almost_equal(y,1.118033989)
-
def test_signaltonoise(self):
"""
this is not in R, so used
More information about the Scipy-svn
mailing list