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Merge pull request scipy#2783 from rgommers/cleanup
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MAINT: remove leftover check for Python <= 2.5.  Some cleanups of comments
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@pv
pv committed Aug 25, 2013
2 parents 88aa5c6 + 03b4239 commit 637170e
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91 changes: 6 additions & 85 deletions scipy/stats/stats.py
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Expand Up @@ -164,70 +164,9 @@
York. 2000.
"""
## CHANGE LOG:
## ===========
## since 2001-06-25 ... see scipy SVN changelog
## 05-11-29 ... fixed default axis to be 0 for consistency with scipy;
## cleanup of redundant imports, dead code, {0,1} -> booleans
## 02-02-10 ... require Numeric, eliminate "list-only" functions
## (only 1 set of functions now and no Dispatch class),
## removed all references to aXXXX functions.
## 00-04-13 ... pulled all "global" statements, except from aanova()
## added/fixed lots of documentation, removed io.py dependency
## changed to version 0.5
## 99-11-13 ... added asign() function
## 99-11-01 ... changed version to 0.4 ... enough incremental changes now
## 99-10-25 ... added acovariance and acorrelation functions
## 99-10-10 ... fixed askew/akurtosis to avoid divide-by-zero errors
## added aglm function (crude, but will be improved)
## 99-10-04 ... upgraded acumsum, ass, asummult, asamplevar, var, etc. to
## all handle lists of 'dimension's and keepdims
## REMOVED ar0, ar2, ar3, ar4 and replaced them with around
## reinserted fixes for abetai to avoid math overflows
## 99-09-05 ... rewrote achisqprob/aerfcc/aksprob/afprob/abetacf/abetai to
## handle multi-dimensional arrays (whew!)
## 99-08-30 ... fixed l/amoment, l/askew, l/akurtosis per D'Agostino (1990)
## added anormaltest per same reference
## re-wrote azprob to calc arrays of probs all at once
## 99-08-22 ... edited attest_ind printing section so arrays could be rounded
## 99-08-19 ... fixed amean and aharmonicmean for non-error(!) overflow on
## short/byte arrays (mean of #s btw 100-300 = -150??)
## 99-08-09 ... fixed asum so that the None case works for Byte arrays
## 99-08-08 ... fixed 7/3 'improvement' to handle t-calcs on N-D arrays
## 99-07-03 ... improved attest_ind, attest_rel (zero-division errortrap)
## 99-06-24 ... fixed bug(?) in attest_ind (n1=a.shape[0])
## 04/11/99 ... added asignaltonoise, athreshold functions, changed all
## max/min in array section to maximum/minimum,
## fixed square_of_sums to prevent integer overflow
## 04/10/99 ... !!! Changed function name ... sumsquared ==> square_of_sums
## 03/18/99 ... Added ar0, ar2, ar3 and ar4 rounding functions
## 02/28/99 ... Fixed aobrientransform to return an array rather than a list
## 01/15/99 ... Essentially ceased updating list-versions of functions (!!!)
## 01/13/99 ... CHANGED TO VERSION 0.3
## fixed bug in a/lmannwhitneyu p-value calculation
## 12/31/98 ... fixed variable-name bug in ldescribe
## 12/19/98 ... fixed bug in findwithin (fcns needed pstat. prefix)
## 12/16/98 ... changed amedianscore to return float (not array) for 1 score
## 12/14/98 ... added atmin and atmax functions
## removed umath from import line (not needed)
## l/ageometricmean modified to reduce chance of overflows (take
## nth root first, then multiply)
## 12/07/98 ... added __version__variable (now 0.2)
## removed all 'stats.' from anova() fcn
## 12/06/98 ... changed those functions (except shellsort) that altered
## arguments in-place ... cumsum, ranksort, ...
## updated (and fixed some) doc-strings
## 12/01/98 ... added anova() function (requires NumPy)
## incorporated Dispatch class
## 11/12/98 ... added functionality to amean, aharmonicmean, ageometricmean
## added 'asum' function (added functionality to add.reduce)
## fixed both moment and amoment (two errors)
## changed name of skewness and askewness to skew and askew
## fixed (a)histogram (which sometimes counted points <lowerlimit)

from __future__ import division, print_function, absolute_import

# Standard library imports.
import warnings
import math

Expand All @@ -246,7 +185,6 @@
from . import futil
from . import distributions

# Local imports.
from . import _support
from ._support import _chk_asarray, _chk2_asarray
from ._rank import rankdata, tiecorrect
Expand Down Expand Up @@ -1194,7 +1132,6 @@ def describe(a, axis=0):
"""
a, axis = _chk_asarray(a, axis)
n = a.shape[axis]
# mm = (np.minimum.reduce(a), np.maximum.reduce(a))
mm = (np.min(a, axis=axis), np.max(a, axis=axis))
m = np.mean(a, axis=axis)
v = np.var(a, axis=axis, ddof=1)
Expand Down Expand Up @@ -1409,9 +1346,6 @@ def jarque_bera(x):
return jb_value, p


# Martinez-Iglewicz test
# K-S test

#####################################
###### FREQUENCY FUNCTIONS #######
#####################################
Expand Down Expand Up @@ -1749,7 +1683,7 @@ def histogram(a, numbins=10, defaultlimits=None, weights=None, printextras=False
"""
a = np.ravel(a) # flatten any >1D arrays
if defaultlimits is None:
# no range given, so use values in a
# no range given, so use values in `a`
data_min = a.min()
data_max = a.max()
# Have bins extend past min and max values slightly
Expand Down Expand Up @@ -2801,10 +2735,6 @@ def spearmanr(a, b=None, axis=0):


def pointbiserialr(x, y):
# comment: I am changing the semantics somewhat. The original function is
# fairly general and accepts an x sequence that has any type of thing in it as
# along as there are only two unique items. I am going to restrict this to
# a boolean array for my sanity.
"""Calculates a point biserial correlation coefficient and the associated
p-value.
Expand Down Expand Up @@ -2847,15 +2777,8 @@ def pointbiserialr(x, y):
>>> np.corrcoef(a, b)
array([[ 1. , 0.8660254],
[ 0.8660254, 1. ]])
"""

## Test data: http://support.sas.com/ctx/samples/index.jsp?sid=490&tab=output
# x = [1,0,1,1,1,1,0,1,0,0,0,1,1,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,0,0,0,0,0,1]
# y = [14.8,13.8,12.4,10.1,7.1,6.1,5.8,4.6,4.3,3.5,3.3,3.2,3.0,2.8,2.8,2.5,
# 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]
# rpb = 0.36149
"""
x = np.asarray(x, dtype=bool)
y = np.asarray(y, dtype=float)
n = len(x)
Expand Down Expand Up @@ -3109,7 +3032,7 @@ def linregress(x, y=None):
r = 1.0
elif (r < -1.0):
r = -1.0
# z = 0.5*log((1.0+r+TINY)/(1.0-r+TINY))

df = n-2
t = r*np.sqrt(df/((1.0-r+TINY)*(1.0+r+TINY)))
prob = distributions.t.sf(np.abs(t),df)*2
Expand Down Expand Up @@ -3493,12 +3416,12 @@ def kstest(rvs, cdf, args=(), N=20, alternative='two-sided', mode='approx'):
"""
if isinstance(rvs, string_types):
# cdf = getattr(stats, rvs).cdf
if (not cdf) or (cdf == rvs):
cdf = getattr(distributions, rvs).cdf
rvs = getattr(distributions, rvs).rvs
else:
raise AttributeError('if rvs is string, cdf has to be the same distribution')
raise AttributeError("if rvs is string, cdf has to be the "
"same distribution")

if isinstance(cdf, string_types):
cdf = getattr(distributions, cdf).cdf
Expand Down Expand Up @@ -4009,12 +3932,10 @@ def mannwhitneyu(x, y, use_continuity=True):
n2 = len(y)
ranked = rankdata(np.concatenate((x,y)))
rankx = ranked[0:n1] # get the x-ranks
# ranky = ranked[n1:] # the rest are y-ranks
u1 = n1*n2 + (n1*(n1+1))/2.0 - np.sum(rankx,axis=0) # calc U for x
u2 = n1*n2 - u1 # remainder is U for y
bigu = max(u1,u2)
smallu = min(u1,u2)
# T = np.sqrt(tiecorrect(ranked)) # correction factor for tied scores
T = tiecorrect(ranked)
if T == 0:
raise ValueError('All numbers are identical in amannwhitneyu')
Expand Down Expand Up @@ -4111,7 +4032,7 @@ def kruskal(*args):
"""
args = list(map(np.asarray, args)) # convert to a numpy array
na = len(args) # Kruskal-Wallis on 'na' groups, each in it's own array
na = len(args) # Kruskal-Wallis on 'na' groups, each in it's own array
if na < 2:
raise ValueError("Need at least two groups in stats.kruskal()")
n = np.asarray(list(map(len, args)))
Expand Down
1 change: 0 additions & 1 deletion scipy/stats/tests/test_mstats_basic.py
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Expand Up @@ -209,7 +209,6 @@ def test_kendalltau_seasonal(self):
[0.18,0.53,0.20,0.04])

def test_pointbiserial(self):
"Tests point biserial"
x = [1,0,1,1,1,1,0,1,0,0,0,1,1,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,0,
0,0,0,0,1,-1]
y = [14.8,13.8,12.4,10.1,7.1,6.1,5.8,4.6,4.3,3.5,3.3,3.2,3.0,
Expand Down
5 changes: 2 additions & 3 deletions scipy/stats/tests/test_stats.py
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Expand Up @@ -8,7 +8,6 @@
"""
from __future__ import division, print_function, absolute_import

import sys
import warnings
from collections import namedtuple

Expand Down Expand Up @@ -556,7 +555,6 @@ def test_tie1(self):
### I need to figure out how to do this one.


@dec.knownfailureif(sys.version[:3] < '2.5', "Can't index array with np.int64")
def test_kendalltau():
# with some ties
x1 = [12, 2, 1, 12, 2]
Expand Down Expand Up @@ -2073,7 +2071,8 @@ def mannwhitneyu():


def test_pointbiserial():
# copied from mstats tests removing nans
# same as mstats test except for the nan
# Test data: http://support.sas.com/ctx/samples/index.jsp?sid=490&tab=output
x = [1,0,1,1,1,1,0,1,0,0,0,1,1,0,0,0,1,1,1,0,0,0,0,0,0,0,0,1,0,
0,0,0,0,1]
y = [14.8,13.8,12.4,10.1,7.1,6.1,5.8,4.6,4.3,3.5,3.3,3.2,3.0,
Expand Down

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