def _test_invgamma_pdf(self):
"""Test inverse gamma PDF/CDF functions"""
prep_dir("test/output/train-invgamma-pdf/")
#a = 23.0
#b = 53.0
a = 3
b = .5
n = 10000
data = [1 / random.gammavariate(a, 1.0/b) for i in xrange(n)]
x, y = distrib(data, 200)
y2 = [spidir.invgamma(i, a, b) for i in x]
rplot_start("test/output/train-invgamma-pdf/invgamma-pdf.pdf")
rplot("plot", x, y, t="l")
rp.lines(x, y2, t="l", col="red")
rplot_end(True)
x, y = cdf(data)
y2 = [spidir.invgammaCdf(i, a, b) for i in x]
rplot_start("test/output/train-invgamma-pdf/invgamma-cdf.pdf")
rplot("plot", x, y, t="l")
rp.lines(x, y2, t="l", col="red")
rplot_end(True)
s = 2
x = list(frange(0, 10, .1))
y = [spidir.incompleteGammaC(s, i) for i in x]
rplot_start("test/output/train-invgamma-pdf/incompletegammac.pdf")
rplot("plot", x, y, t="l")
#rp.lines(x, y2, t="l", col="red")
rplot_end(True)
def _test_invgamma(self):
"""Test inverse gamma quantile function"""
a = 2
b = 3 #34
x = list(frange(.001, 5, .01))
y = [invgammaPdf(i, (a, b)) for i in x]
y2 = [spidir.invgamma(i, a, b) for i in x]
y3 = [spidir.invgammaCdf(i, a, b) for i in x]
y4 = [spidir.quantInvgamma(i, a, b) for i in x]
#print spidir.quantInvgamma(.5, a, b)
#print spidir.gammaDerivA(145.166061, 1.000000, 1.000000), \
# spidir.gammaPdf(145.166061, 1.000000, 1.000000), \
# spidir.gammalog(145.166061, 1.000000, 1.000000)
prep_dir("test/output/train-invgamma/")
rplot_start("test/output/train-invgamma/invgamma.pdf")
rplot("plot", x, y, t="l") #, ylim=[min(x), max(x)])
rp.lines(x, y2, t="l", col="red")
rp.lines(x, y3, t="l", col="blue")
rp.lines(y4, x, t="l", col="green") # show overlay CDF
rplot_end(True)