def targ(C,
x,
y,
cmin,
cmax,
symm,
d_kwargs=distance_arg_dict,
c_args=args,
c_kwargs=kwargs):
# Compute distance for this bit
self.distance_fun(C,
x,
y,
cmin=cmin,
cmax=cmax,
symm=symm,
**d_kwargs)
imul(C, 1. / scale, cmin=cmin, cmax=cmax, symm=symm)
# Compute covariance for this bit
self.cov_fun(C,
cmin=cmin,
cmax=cmax,
symm=symm,
*c_args,
**c_kwargs)
imul(C, amp * amp, cmin=cmin, cmax=cmax, symm=symm)
def targ(C,x,y, cmin, cmax,symm, d_kwargs=distance_arg_dict, c_args=args, c_kwargs=kwargs):
# Compute distance for this bit
self.distance_fun(C, x, y, cmin=cmin, cmax=cmax, symm=symm, **d_kwargs)
imul(C, 1./scale, cmin=cmin, cmax=cmax, symm=symm)
# Compute covariance for this bit
self.cov_fun(C, cmin=cmin, cmax=cmax,symm=symm, *c_args, **c_kwargs)
imul(C, amp*amp, cmin=cmin, cmax=cmax, symm=symm)
def brownian_targ(C,x,y,h,amp,cmin, cmax,symm):
# Compute covariance for this bit
if h==.5:
isotropic_cov_funs.brownian(C,x,y,cmin=0,cmax=-1,symm=symm)
else:
isotropic_cov_funs.frac_brownian(C,x,y,h,cmin=0,cmax=-1,symm=symm)
imul(C, amp*amp, cmin=cmin, cmax=cmax, symm=symm)
# Possibly symmetrize this bit
if symm:
symmetrize(C, cmin=cmin, cmax=cmax)