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)