17332886172

Committed 29 Aug 2025 07:45PM UTC coverage: 0.0% (-81.0%) from 81.048%

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kunzaatko

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test: Add the JET function filter again

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/src/transfer-function-interface.jl

using InterfaceFunctions

"""
    TransferFunction
Super type for all transfer functions

A transfer function in microscopy is an object specifying the response in the image plane to the light coming from the
object plane.
There are several characteristics of a transfer functions which can influence the character of the response. Most
commonly we are concerned with its spatial variance/invariance, i.e. whether the response is dependent of the objects
position in the object plane, and linearity (which is almost always satisfied).

See also [`LinearShiftInvariantTransferFunction`](@ref), [`ImpulseResponseMapping`](@ref)
"""
abstract type TransferFunction{N} end

# TODO: When it is possible to mark the non-first argument as the interfacing type, it should be done with interfaces
# again <27-08-25> 
"""
    transfer(A::SpatialMatrix, t::TransferFunction)
The forward pass of the transfer function operator `t` on the image `A`.

See also [`restore`](@ref)
"""
function transfer(::SpatialMatrix{<:Real}, ::TransferFunction) end

# TODO: When it is possible to mark the non-first argument as the interfacing type, it should be done with interfaces
# again <27-08-25> 
"""
    restore(A::SpatialMatrix, t::TransferFunction)
The reverse pass of the transfer function operator `t` on the image `A`.

It is always inherently an estimation because `A` is always noisy and `t` is often not well conditioned (especially in
the non-linear case).

See also [`transfer`](@ref)
"""
function restore(::SpatialMatrix{<:Real}, t::TransferFunction) end

# NOTE: Taken from Distributions.jl <kunzaatko> 
for func in (:(==), :isequal, :isapprox)
    @eval function Base.$func(tf1::A, tf2::B; kwargs...) where {A<:TransferFunction,B<:TransferFunction}
        nameof(A) === nameof(B) || return false
        fields = fieldnames(A)
        fields === fieldnames(B) || return false

        for f in fields
            isdefined(tf1, f) && isdefined(tf2, f) || return false
            # perform equivalence check to support types that have no defined equality, such
            # as `missing`
            getfield(tf1, f) === getfield(tf2, f) || $func(getfield(tf1, f), getfield(tf2, f); kwargs...) || return false
        end

        return true
    end
end

# NOTE: Taken from Distributions.jl <kunzaatko> 
function Base.hash(tf::TransferFunction, h::UInt)
    hashed = hash(TransferFunction, h)
    hashed = hash(nameof(typeof(tf)), hashed)

    for f in fieldnames(typeof(tf))
        hashed = hash(getfield(tf, f), hashed)
    end

    return hashed
end

export transfer, restore

1	using InterfaceFunctions
2
3	"""
4	TransferFunction
5	Super type for all transfer functions
6
7	A transfer function in microscopy is an object specifying the response in the image plane to the light coming from the
8	object plane.
9	There are several characteristics of a transfer functions which can influence the character of the response. Most
10	commonly we are concerned with its spatial variance/invariance, i.e. whether the response is dependent of the objects
11	position in the object plane, and linearity (which is almost always satisfied).
12
13	See also [`LinearShiftInvariantTransferFunction`](@ref), [`ImpulseResponseMapping`](@ref)
14	"""
15	abstract type TransferFunction{N} end
16
17	# TODO: When it is possible to mark the non-first argument as the interfacing type, it should be done with interfaces
18	# again <27-08-25>
19	"""
20	transfer(A::SpatialMatrix, t::TransferFunction)
21	The forward pass of the transfer function operator `t` on the image `A`.
22
23	See also [`restore`](@ref)
24	"""
25	function transfer(::SpatialMatrix{<:Real}, ::TransferFunction) end	×
26
27	# TODO: When it is possible to mark the non-first argument as the interfacing type, it should be done with interfaces
28	# again <27-08-25>
29	"""
30	restore(A::SpatialMatrix, t::TransferFunction)
31	The reverse pass of the transfer function operator `t` on the image `A`.
32
33	It is always inherently an estimation because `A` is always noisy and `t` is often not well conditioned (especially in
34	the non-linear case).
35
36	See also [`transfer`](@ref)
37	"""
38	function restore(::SpatialMatrix{<:Real}, t::TransferFunction) end	×
39
40	# NOTE: Taken from Distributions.jl <kunzaatko>
41	for func in (:(==), :isequal, :isapprox)
42	@eval function Base.$func(tf1::A, tf2::B; kwargs...) where {A<:TransferFunction,B<:TransferFunction}	×
43	nameof(A) === nameof(B) \|\| return false	×
44	fields = fieldnames(A)	×
45	fields === fieldnames(B) \|\| return false	×
46
47	for f in fields	×
48	isdefined(tf1, f) && isdefined(tf2, f) \|\| return false	×
49	# perform equivalence check to support types that have no defined equality, such
50	# as `missing`
51	getfield(tf1, f) === getfield(tf2, f) \|\| $func(getfield(tf1, f), getfield(tf2, f); kwargs...) \|\| return false	×
52	end	×
53
54	return true	×
55	end
56	end
57
58	# NOTE: Taken from Distributions.jl <kunzaatko>
59	function Base.hash(tf::TransferFunction, h::UInt)	×
60	hashed = hash(TransferFunction, h)	×
61	hashed = hash(nameof(typeof(tf)), hashed)	×
62
63	for f in fieldnames(typeof(tf))	×
64	hashed = hash(getfield(tf, f), hashed)	×
65	end	×
66
67	return hashed	×
68	end
69
70	export transfer, restore

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