def stats2z_moment(stats):
# MODIFIED FROM http://statsmodels.sourceforge.net/devel/_modules/statsmodels/stats/moment_helpers.html
# ADDED count
mc0, mc1, mc2, skew, kurt = stats.count, nvl(stats.mean, 0), nvl(
stats.variance, 0), nvl(stats.skew, 0), nvl(stats.kurtosis, 0)
mz0 = mc0
mz1 = mc1 * mc0
mz2 = (mc2 + mc1 * mc1) * mc0
mc3 = nvl(skew, 0) * (mc2**1.5) # 3rd central moment
mz3 = (mc3 + 3 * mc1 * mc2 + mc1**3) * mc0 # 3rd non-central moment
mc4 = (nvl(kurt, 0) + 3.0) * (mc2**2.0) # 4th central moment
mz4 = (mc4 + 4 * mc1 * mc3 + 6 * mc1 * mc1 * mc2 + mc1**4) * mc0
m = Z_moment(mz0, mz1, mz2, mz3, mz4)
if DEBUG:
from util.testing.fuzzytestcase import assertAlmostEqualValue
globals()["DEBUG"] = False
try:
v = z_moment2stats(m, unbiased=False)
assertAlmostEqualValue(v.count, stats.count)
assertAlmostEqualValue(v.mean, stats.mean)
assertAlmostEqualValue(v.variance, stats.variance)
assertAlmostEqualValue(v.skew, stats.skew)
assertAlmostEqualValue(v.kurtosis, stats.vkurtosis)
except Exception, e:
v = z_moment2stats(m, unbiased=False)
Log.error("programmer error")
globals()["DEBUG"] = True
def z_moment2stats(z_moment, unbiased=True):
Z = z_moment.S
N = Z[0]
if N == 0:
return Stats()
mean = Z[1] / N
Z2 = Z[2] / N
Z3 = Z[3] / N
Z4 = Z[4] / N
if N == 1:
variance = None
skew = None
kurtosis = None
else:
variance = (Z2 - mean * mean)
error = -EPSILON * (abs(Z2) + 1) # EXPECTED FLOAT ERROR
if error < variance <= 0: # TODO: MAKE THIS A TEST ON SIGNIFICANT DIGITS
variance = 0
skew = None
kurtosis = None
elif variance < error:
Log.error("variance can not be negative ({{var}})",
{"var": variance})
else:
mc3 = (Z3 - (3 * mean * variance + mean**3)) # 3rd central moment
mc4 = (Z4 -
(4 * mean * mc3 + 6 * mean * mean * variance + mean**4))
skew = mc3 / (variance**1.5)
kurtosis = (mc4 / (variance**2.0)) - 3.0
stats = Stats(count=N,
mean=mean,
variance=variance,
skew=skew,
kurtosis=kurtosis,
unbiased=unbiased)
if DEBUG:
from util.testing.fuzzytestcase import assertAlmostEqualValue
globals()["DEBUG"] = False
v = Null
try:
v = stats2z_moment(stats)
for i in range(5):
assertAlmostEqualValue(v.S[i], Z[i])
except Exception, e:
Log.error(
"Convertion failed. Programmer error:\nfrom={{from|indent}},\nresult stats={{stats|indent}},\nexpected param={{expected|indent}}",
{
"from": Z,
"stats": stats,
"expected": v.S
}, e)
globals()["DEBUG"] = True
except Exception, e:
DEBUG_STRANGMAN = False
def chisquare(f_obs, f_exp):
try:
py_result = strangman.stats.chisquare(f_obs, f_exp)
except Exception, e:
Log.error("problem with call", e)
if DEBUG_STRANGMAN:
from util.testing.fuzzytestcase import assertAlmostEqualValue
sp_result = scipy.stats.chisquare(np.array(f_obs),
f_exp=np.array(f_exp))
if not assertAlmostEqualValue(sp_result[0],
py_result[0]) and assertAlmostEqualValue(
sp_result[1], py_result[1]):
Log.error("problem with stats lib")
return py_result
def stats2z_moment(stats):
# MODIFIED FROM http://statsmodels.sourceforge.net/devel/_modules/statsmodels/stats/moment_helpers.html
# ADDED count
mc0, mc1, mc2, skew, kurt = stats.count, nvl(stats.mean, 0), nvl(
stats.variance, 0), nvl(stats.skew, 0), nvl(stats.kurtosis, 0)
mz0 = mc0
mz1 = mc1 * mc0
mz2 = (mc2 + mc1 * mc1) * mc0
