def __init__(self):
self.dist_equivalents = [
#transf, stats.lognorm(1))
#The below fails on the SPARC box with scipy 10.1
#(lognormalg, stats.lognorm(1)),
#transf2
(squarenormalg, stats.chi2(1)),
(absnormalg, stats.halfnorm),
(absnormalg, stats.foldnorm(1e-5)), #try frozen
#(negsquarenormalg, 1-stats.chi2), # won't work as distribution
(squaretg(10), stats.f(1, 10))] #try both frozen
l,s = 0.0, 1.0
self.ppfq = [0.1,0.5,0.9]
self.xx = [0.95,1.0,1.1]
self.nxx = [-0.95,-1.0,-1.1]
def __init__(self):
self.dist_equivalents = [
#transf, stats.lognorm(1))
(lognormalg, stats.lognorm(1)),
#transf2
(squarenormalg, stats.chi2(1)),
(absnormalg, stats.halfnorm),
(absnormalg, stats.foldnorm(1e-5)), #try frozen
#(negsquarenormalg, 1-stats.chi2), # won't work as distribution
(squaretg(10), stats.f(1, 10))] #try both frozen
l,s = 0.0, 1.0
self.ppfq = [0.1,0.5,0.9]
self.xx = [0.95,1.0,1.1]
self.nxx = [-0.95,-1.0,-1.1]
def setup_class(cls):
cls.dist_equivalents = [
#transf, stats.lognorm(1))
#The below fails on the SPARC box with scipy 10.1
#(lognormalg, stats.lognorm(1)),
#transf2
(squarenormalg, stats.chi2(1)),
(absnormalg, stats.halfnorm),
(absnormalg, stats.foldnorm(1e-5)), #try frozen
#(negsquarenormalg, 1-stats.chi2), # won't work as distribution
(squaretg(10), stats.f(1, 10))
] #try both frozen
l, s = 0.0, 1.0
cls.ppfq = [0.1, 0.5, 0.9]
cls.xx = [0.95, 1.0, 1.1]
cls.nxx = [-0.95, -1.0, -1.1]