# you mistype something
#end
from pylab import *
import current as pc
rc("figure", figsize=[8., 4.])
rc("figure.subplot", left=.08, top=.95, right=.95)
seed(1000)
Uniform_min = pc.construct(cdf=lambda self, q, a, b: (q - a) / (b - a),
bnd=lambda self, a, b: (a, b))
Q = Uniform_min(a=0, b=1)
#end
Uniform = pc.construct(cdf=lambda self, q, a, b: (q - a) / (b - a),
bnd=lambda self, a, b: (a, b),
pdf=lambda self, q, a, b: 1. / (b - a),
ppf=lambda self, u, a, b: u * (b - a) + a,
mom=lambda self, k, a, b: (b**(k + 1) - a**(k + 1)) /
(k + 1) / (b - a),
ttr=lambda self, k, a, b:
(0.5 * (a + b), n * n * (b - a)**2 / (16 * n * n - 4)),
defaults=dict(a=0., b=1.),
str=lambda self, a, b: "U(%s,%s)" % (a, b),
doc="An uniform distribution on the interval [a,b]")
Q = Uniform(a=0, b=2)
#end
#end
def val(self, G):
if len(G.K) == 2:
return G.K["par1"] + G.K["par2"]
return self
#end
Addition = pc.construct(cdf=cdf,
bnd=bnd,
val=val,
advance=True,
defaults=dict(par1=0., par2=0.))
add = Addition(par1=U1, par2=U2)
Q = pc.J(U1, add)
#end
subplot(121)
R = Q.sample(1000)
scatter(R[0], R[1], marker="s", color="k", alpha=.7)
xlabel(r"$Q_0$")
ylabel(r"$Q_1$")
axis([0, 1, 0, 2])
title("Scatter")
# you mistype something
#end
from pylab import *
import current as pc
rc("figure", figsize=[8., 4.])
rc("figure.subplot", left=.09, top=.93, right=.95, wspace=.24)
seed(1000)
cdf = lambda self, q: e**q / (1 + e**q)
bnd = lambda self: (-30, 30)
Cauchy = pc.construct(cdf=cdf, bnd=bnd)
Q = Cauchy()
#end
print Q.inv([0.1, 0.2, 0.3])
# [-2.19722267 -1.38626822 -0.84729574]
print Q.pdf([-1, 0, 1])
# [ 0.19661217 0.25000002 0.19661273]
print Q.sample(4)
# [ 0.63485527 -2.04053293 2.95040998 -0.07126454]
#end
print Q.inv([0.1, 0.2, 0.3], tol=1e-3, maxiter=10)
# [-2.19503823 -1.38626822 -0.8440303 ]
print Q.pdf([-1, 0, 1], step=1e-1)
# [ 0.20109076 0.24979187 0.20109076]
#end
subplot(121)
# you mistype something
#end
from pylab import *
import current as pc
rc("figure", figsize=[8.,4.])
rc("figure.subplot", left=.08, top=.95, right=.95)
seed(1000)
Uniform_min = pc.construct(
cdf=lambda self,q,a,b: (q-a)/(b-a),
bnd=lambda self,a,b: (a,b))
Q = Uniform_min(a=0,b=1)
#end
Uniform = pc.construct(
cdf=lambda self,q,a,b: (q-a)/(b-a),
bnd=lambda self,a,b: (a,b),
pdf=lambda self,q,a,b: 1./(b-a),
ppf=lambda self,u,a,b: u*(b-a)+a,
mom=lambda self,k,a,b: (b**(k+1)-a**(k+1))/(k+1)/(b-a),
ttr=lambda self,k,a,b: (0.5*(a+b),n*n*(b-a)**2/(16*n*n-4)),
defaults=dict(a=0., b=1.),
str=lambda self,a,b: "U(%s,%s)" % (a,b),
doc="An uniform distribution on the interval [a,b]")
Q = Uniform(a=0, b=2)
#end
def pdf(self, x):
out = 9/16.*(x+1)*(x<1/3.)
out += 3/4.*(x>=1/3.)
return out
def cdf(self, x):
out = 9/32.*(x+1)**2*(x<1/3.)
out += (3*x+1)/4.*(x>=1/3.)
return out
def bnd(self):
return -1,1
MyDist = pc.construct(
pdf=pdf, cdf=cdf, bnd=bnd)
#end
dist = MyDist()
print dist.mom(1, order=100)
# 0.277778240534
#end
print dist.mom(1, order=5, composite=1/3.)
# 0.277777777778
#end
mom = pc.momgen(
order=100,
domain=dist,
composite=1/3.)
# you mistype something
#end
from pylab import *
import current as pc
rc("figure", figsize=[8.,4.])
rc("figure.subplot", left=.09, top=.93, right=.95, wspace=.24)
seed(1000)
cdf = lambda self, q: e**q/(1+e**q)
bnd = lambda self: (-30,30)
Cauchy = pc.construct(cdf=cdf, bnd=bnd)
Q = Cauchy()
#end
print Q.inv([0.1, 0.2, 0.3])
# [-2.19722267 -1.38626822 -0.84729574]
print Q.pdf([-1, 0, 1])
# [ 0.19661217 0.25000002 0.19661273]
print Q.sample(4)
# [ 0.63485527 -2.04053293 2.95040998 -0.07126454]
#end
print Q.inv([0.1, 0.2, 0.3], tol=1e-3, maxiter=10)
# [-2.19503823 -1.38626822 -0.8440303 ]
print Q.pdf([-1, 0, 1], step=1e-1)
# [ 0.20109076 0.24979187 0.20109076]
#end
subplot(121)
