X = f['genotype'][:]
X-= X.mean(0); X/=X.std(0)
G = X[:,0:200]
Y = genPheno(G=G,X=X,var_g=0.10,var_x=0.40,P=P)
XX = SP.dot(X,X.T)
XX/= XX.diagonal().mean()
XX+= 1e-4*SP.eye(XX.shape[0])
GG = SP.dot(G,G.T)
GG/= GG.diagonal().mean()
GG+= 1e-4*SP.eye(GG.shape[0])
C1 = freeform(P)
C2 = freeform(P)
Cn = freeform(P)
gp = gp3kronSumApprox(Y=Y,C1=C1,C2=C2,Cn=Cn,R1=GG,R2=XX,tol=1e-16)
if 0:
Kinit = SP.cov(Y.T)/3
C1.setCovariance(Kinit)
C2.setCovariance(Kinit)
Cn.setCovariance(Kinit)
else:
C1.setRandomParams()
C2.setRandomParams()
Cn.setRandomParams()
params = gp.getParams()
gp.setParams(params)
gp.checkGradient()
X = f['genotype'][:]
X-= X.mean(0); X/=X.std(0)
G = X[:,0:200]
Y = genPheno(G=G,X=X,var_g=0.10,var_x=0.40,P=P)
XX = SP.dot(X,X.T)
XX/= XX.diagonal().mean()
XX+= 1e-4*SP.eye(XX.shape[0])
GG = SP.dot(G,G.T)
GG/= GG.diagonal().mean()
GG+= 1e-4*SP.eye(GG.shape[0])
Cr = freeform(P)
Cg = freeform(P)
Cn = freeform(P)
gp = gp3kronSumApprox(Y=Y,Cr=Cr,Cg=Cg,Cn=Cn,XX=XX,GG=GG)
n_rips = 10
for rip in range(n_rips):
Cr.setRandomParams()
Cg.setRandomParams()
Cn.setRandomParams()
params = gp.getParams()
gp.setParams(params)
conv,info = OPT.opt_hyper(gp,params,factr=1e3)
print conv
print 'Cr'
print Cr.K()
print 'Cg'
X -= X.mean(0)
X /= X.std(0)
G = X[:, 0:200]
Y = genPheno(G=G, X=X, var_g=0.10, var_x=0.40, P=P)
XX = SP.dot(X, X.T)
XX /= XX.diagonal().mean()
XX += 1e-4 * SP.eye(XX.shape[0])
GG = SP.dot(G, G.T)
GG /= GG.diagonal().mean()
GG += 1e-4 * SP.eye(GG.shape[0])
Cr = freeform(P)
Cg = freeform(P)
Cn = freeform(P)
gp = gp3kronSumApprox(Y=Y, Cr=Cr, Cg=Cg, Cn=Cn, XX=XX, GG=GG)
n_rips = 10
for rip in range(n_rips):
Cr.setRandomParams()
Cg.setRandomParams()
Cn.setRandomParams()
params = gp.getParams()
gp.setParams(params)
conv, info = OPT.opt_hyper(gp, params, factr=1e3)
print conv
print 'Cr'
print Cr.K()
print 'Cg'
X = f['genotype'][:]
X-= X.mean(0); X/=X.std(0)
G = X[:,0:200]
Y = genPheno(G=G,X=X,var_g=0.10,var_x=0.40,P=P)
XX = SP.dot(X,X.T)
XX/= XX.diagonal().mean()
XX+= 1e-4*SP.eye(XX.shape[0])
GG = SP.dot(G,G.T)
GG/= GG.diagonal().mean()
GG+= 1e-4*SP.eye(GG.shape[0])
C1 = freeform(P)
C2 = freeform(P)
Cn = freeform(P)
gp = gp3kronSumApprox(Y=Y,C1=C1,C2=C2,Cn=Cn,R1=GG,R2=XX,tol=1e-16)
if 0:
Kinit = SP.cov(Y.T)/3
C1.setCovariance(Kinit)
C2.setCovariance(Kinit)
Cn.setCovariance(Kinit)
else:
C1.setRandomParams()
C2.setRandomParams()
Cn.setRandomParams()
params = gp.getParams()
gp.setParams(params)
gp.checkGradient()