Unified IlluminationPattern Interface

Super type for N-dimensional illumation patterns. Any particular illumination pattern is a subtype of this. See the documentation for IlluminationPattern interface to see how to implement your own illumination pattern subtype.

See also: Harmonic2D

Implementation

When implementing a new subtype A <: IlluminationPattern{N} you need to implement the following methods:

• (pattern::A)(r::Vararg{Length, N})::Real representing the intensity of pattern at the position r

and these optional methods:

TODO

The inner constructor of the subtype A should check that N::Integer unless your subtype has a specified dimension.

struct A1{N} <: IlluminationPattern{N}
    function A{N}() where {N}
        @assert N isa Integer
        new{N}()
    end
end

struct A2 <: IlluminationPattern{2}
    function A2()
        # No need for any assertions
        new()
    end
end

SampledIlluminationPattern{T<:Real,N,IP<:IlluminationPattern{N}}
SampledIlluminationPattern([T=Float64], ip::IlluminationPattern, Δxy)

N-dimensional sampled illumination pattern. You can fix the pixels sizes (Δxy) and sample the pattern on your sensor and optical system setup.

Examples

julia> h = Harmonic(1.0, π / 4, 2 / 61u"nm", 0.0)
Harmonic2D(m=1.0, θ=0.785, ν=0.0328 nm^-1, ϕ=0.0)

julia> sampled_ip = SampledIlluminationPattern(h, (30u"nm", 30u"nm"))
Harmonic2D(m=1.0, θ=0.785, ν=0.0328 nm^-1, ϕ=0.0)(Δxy = 30 nm) with eltype Float64

julia> sampled_ip(3, 4.5)
1.1048934112868387

julia> sampled_ip(CartesianIndex(1,1))
0.6126893879715403

julia> img = rand(10,10);

julia> sampled_ip((5, 5))
5×5 Matrix{Float64}:
 1.5       0.832154  0.612689  1.42788   1.10004
 0.832154  0.612689  1.42788   1.10004   0.504955
 0.612689  1.42788   1.10004   0.504955  1.23233
 1.42788   1.10004   0.504955  1.23233   1.33906
 1.10004   0.504955  1.23233   1.33906   0.54003

julia> sampled_ip((10, 10)) == sampled_ip(img)
true

julia> sampled_ip(CartesianIndices(img)) != sampled_ip(img) # BEWARE! This is not equivalent
true

julia> sampled_ip(CartesianIndices((0:9, 0:9))) == sampled_ip(img) # This is equivalent
true