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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