Python PES.makeG Examples

Example #1

from scipy import stats as sps
from matplotlib import pyplot as plt
import GPdc
import PES
import DIRECT

#-------------------------------------------------------------------------
#2d
nt = 60
d = 2
lb = sp.array([-1.] * d)
ub = sp.array([1.] * d)
[X, Y, S, D] = ESutils.gen_dataset(nt, d, lb, ub, GPdc.SQUEXP,
                                   sp.array([1.5, 0.35, 0.30]))

G = PES.makeG(X, Y, S, D, GPdc.SQUEXP, sp.array([0., -1., -1.]),
              sp.array([1., 1., 1.]), 6)
nz = 8
Z = PES.drawmins_inplane(G,
                         nz,
                         sp.array([-1.] * d),
                         sp.array([1.] * d),
                         axis=0,
                         value=0.,
                         SUPPORT=500,
                         SLICELCB_PARA=1.)

print Z
Ga = [
    GPdc.GPcore(*PES.addmins_inplane(
        G, X, Y, S, D, Z[i, :], axis=0, value=0., MINPOLICY=PES.NOMIN) +
                [G.kf]) for i in xrange(nz)

Example #2

File: testPES2.py Project: markm541374/GPc

from scipy import linalg as spl
from scipy import stats as sps
from matplotlib import pyplot as plt
import GPdc
import PES
import DIRECT

# -------------------------------------------------------------------------
# 2d
nt = 60
d = 2
lb = sp.array([-1.0] * d)
ub = sp.array([1.0] * d)
[X, Y, S, D] = ESutils.gen_dataset(nt, d, lb, ub, GPdc.SQUEXP, sp.array([1.5, 0.35, 0.30]))

G = PES.makeG(X, Y, S, D, GPdc.SQUEXP, sp.array([0.0, -1.0, -1.0]), sp.array([1.0, 1.0, 1.0]), 6)
nz = 8
Z = PES.drawmins_inplane(
    G, nz, sp.array([-1.0] * d), sp.array([1.0] * d), axis=0, value=0.0, SUPPORT=500, SLICELCB_PARA=1.0
)

print Z
Ga = [
    GPdc.GPcore(*PES.addmins_inplane(G, X, Y, S, D, Z[i, :], axis=0, value=0.0, MINPOLICY=PES.NOMIN) + [G.kf])
    for i in xrange(nz)
]

np = 220
sup = sp.linspace(-1, 1, np)
Dp = [[sp.NaN]] * np
Xp0 = sp.vstack([sp.array([i, Z[0, 1]]) for i in sup])

Example #3

File: testPES1.py Project: markm541374/GPc

import ESutils
import DIRECT
import scipy as sp
from scipy import linalg as spl
from scipy import stats as sps
from matplotlib import pyplot as plt
import GPdc
import PES

nt=12
d=1
lb = sp.array([-1.]*d)
ub = sp.array([1.]*d)
[X,Y,S,D] = ESutils.gen_dataset(nt,d,lb,ub,GPdc.SQUEXP,sp.array([1.5,0.15]))

G = PES.makeG(X,Y,S,D,GPdc.SQUEXP,sp.array([0.,-1.]),sp.array([1.,1.]),12)
Z=PES.drawmins(G,8,sp.array([-1.]),sp.array([1.]),SUPPORT=400,SLICELCB_PARA=1.)

Ga = GPdc.GPcore(*PES.addmins(G,X,Y,S,D,Z[0,:])+[G.kf])

np=100
sup = sp.linspace(-1,1,np)
Dp = [[sp.NaN]]*np
Xp = sp.vstack([sp.array([i]) for i in sup])

[m,V] = G.infer_diag_post(Xp,Dp)
[mp,Vp] = Ga.infer_diag_post(Xp,Dp)

f,a = plt.subplots(2)
s = sp.sqrt(V[0,:])
a[0].fill_between(sup,sp.array(m[0,:]-2.*s).flatten(),sp.array(m[0,:]+2.*s).flatten(),facecolor='lightblue',edgecolor='lightblue')