Anisotropic scaling

Description

Anisotropic scaling with three parameters against a reference dataset.

log(\frac{I(h,k)}{I_0}) = A + B1 h^2 + B2 k^2

Python interface

class iplt.alg.AnisoScaling((object)arg1)

Add((AnisoScaling)arg1, (float)arg2, (float)arg3, (float)arg4, (float)arg5) → None :

C++ signature :

void Add(iplt::alg::AnisoScaling {lvalue},float,float,float,float)

Apply((AnisoScaling)arg1) → None :

C++ signature :

void Apply(iplt::alg::AnisoScaling {lvalue})

Estimate((AnisoScaling)arg1, (float)arg2, (float)arg3) → float :

C++ signature :

float Estimate(iplt::alg::AnisoScaling {lvalue},float,float)

GetA((AnisoScaling)arg1) → float :

C++ signature :

float GetA(iplt::alg::AnisoScaling {lvalue})

GetB1((AnisoScaling)arg1) → float :

C++ signature :

float GetB1(iplt::alg::AnisoScaling {lvalue})

GetB2((AnisoScaling)arg1) → float :

C++ signature :

float GetB2(iplt::alg::AnisoScaling {lvalue})

__init__((object)arg1) → None :

C++ signature :

void __init__(_object*)

C++ interface