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roflmaostcroflmaostc
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Make some changes
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‎src/ExperimentalData.jl

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export ExperimentalData
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export initializeExperimentalData
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"""
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ExperimentalData{T}
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`mutable struct` stores all parameters.
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# Parameters
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## Physical Properties
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* `wavelength` of the laser
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## General Properties
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* `dtype`: datatype used for reconstructions. `Float32` is usually faster, especially on GPUs.
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* `propagator`:
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## Probe
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* `dxp`: pixel size
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* `Np`: number of pixels
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* `xp`: 1D coordinates
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* `Lp`: field of view probe (field size)
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* `zp`: distance to next plane
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## Object
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* `dxo`: pixel size
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* `No`: number of pixels
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* `xo`: 1D coordinates
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* `Lo`: field of view probe (field size)
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* `zo`: distance to next plane
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## Detector
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* `dxd`: pixel size
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* `Nd`: number of pixels
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* `xd`: 1D coordinates
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* `Ld`: field of view probe (field size)
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"""
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@kwdef mutable struct ExperimentalData{T}
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wavelength::T
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# probe sampling
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dxp::T
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Np::Int
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xp::Vector{T}
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Lp::T
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zp::Union{T, Nothing}
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entrancePupilDiameter::Union{T, Nothing}
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# object sampling
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dxo::T
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No::Int
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xo::Vector{T}
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Lo::T
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zo::T
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# detector sampling
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dxd::T
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Nd::Int
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xd::Vector{T}
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Ld::T
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# the general data type which is enforced
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dtype::Type{T}
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ptychogram::Union{Nothing, Array{T, N}} where N
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encoder::Union{Nothing, Array{T, 2}}
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end
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"""
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ExperimentalData(fileName::String)
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Fill the `ExperimentalData` struct with data from a `*.hdf5` file.
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"""
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function ExperimentalData(fileName::String, mode=CPM::CPM)
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# open h5 file
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fid = HDF5.h5open(fileName)
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# function to extract number from a vector wrap
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r_number(x) = read(fid, x)[begin]
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# read arrays, take full
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r_array(x) = read(fid, x)
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# call a simple constructor and fill with data
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expData = initializeExperimentalData(
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# those numbers are stored as arrays, take first element
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wavelength=r_number("wavelength"),
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No=r_number("No"),
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Nd=r_number("Nd"),
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dxd=r_number("dxd"),
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zo=r_number("zo"),
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entrancePupilDiameter=r_number("encoder"),
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# those are arrays, keep them
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ptychogram=r_array("ptychogram"),
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encoder=r_array("encoder"),
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)
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return expData
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end
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"""
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initializeExperimentalData(<kwargs>)
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Function to return parameter object `mutable struct` storing
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all meta information needed for reconstruction.
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Note that you can access all those parameters but many
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of them are connected hence to fill the struct we only need a few of
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them.
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"""
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function initializeExperimentalData(;
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wavelength=DEFAULT_WAVELENGTH,
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No=2^7,
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Nd=2^9,
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dxd=4.5e-6,
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zo=50e-3,
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dtype=Float32,
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zp=nothing,
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entrancePupilDiameter=nothing,
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ptychogram=nothing,
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encoder=nothing,
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)
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# detector
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Ld = Nd * dxd
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xd = FourierTools.fftpos(Ld, Nd)
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# probe
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dxp = wavelength * zo / Ld
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Np = Nd
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Lp = dxp*Np
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xp = FourierTools.fftpos(Lp, Np)
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# object
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dxo = dxp
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Lo = dxo * No
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xo = FourierTools.fftpos(Lo, No)
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# anonymous function to convert to the dtype
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_dtype(x) = isnothing(x) ? x : dtype(x)
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# fill struct
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ExperimentalData(
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wavelength=_dtype(wavelength),
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# probe sampling
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dxp=_dtype(dxp),
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Np=Np,
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xp=_dtype.(xp),
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Lp=_dtype(Lp),
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zp=_dtype(zp),
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# object sampling,
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dxo=_dtype(dxo),
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No=No,
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xo=_dtype.(xo),
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Lo=_dtype(Lo),
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zo=_dtype(zo),
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# detector sampling,
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dxd=_dtype(dxd),
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Nd=Nd,
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entrancePupilDiameter=dtype(entrancePupilDiameter),
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xd=_dtype.(xd),
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Ld=_dtype(Ld),
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# the general data type which is enforced,
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dtype=dtype,
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ptychogram=dtype.(ptychogram)),
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encoder=dtype.(encoder)
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end

‎src/PtyLab.jl

+11-1
Original file line numberDiff line numberDiff line change
@@ -4,15 +4,25 @@ module PtyLab
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using FFTW, FourierTools
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# for displaying
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using ColorTypes
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# data loading
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using HDF5
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# @kwdef macro
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import Base.@kwdef
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# some constants
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const DEFAULT_WAVELENGTH = 632.8e-9 :: Float64
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# a few types for either Fourier or Classical Ptychography
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abstract type ModePtychograpy end
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abstract type CPM <: ModePtychograpy end
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abstract type FPM <: ModePtychograpy end
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include("utils_parameters.jl")
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include("ExperimentalData.jl")
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include("utils_grid.jl")
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include("utils_display.jl")
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end

‎src/propagators.jl

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"""
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Fraunhofer
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"""
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function Fraunhofer()
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end

‎src/utils_grid.jl

+1-1
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@@ -50,7 +50,7 @@ function grid_regular_rand(grid_size, tile_size, (N, M), rand_offset=10)
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i_pos = clamp(random_constrained_wiggle(i, is, rand_offset), 1, grid_size[1] - tile_size[1])
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j_pos = clamp(random_constrained_wiggle(j, js, rand_offset), 1, grid_size[2] - tile_size[2])
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# save tile
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push!(grr.tiles, Tile(i_pos, i_pos + tile_size[1], j_pos, j_pos + tile_size[2]))
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push!(grr.tiles, Tile(i_pos, i_pos + tile_size[1] - 1, j_pos, j_pos + tile_size[2] - 1))
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end
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end
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return grr

‎src/utils_parameters.jl

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import Base.@kwdef
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export init_Parameters
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"""
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Parameters{T}
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Struct storing all parameters.
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"""
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@kwdef struct Parameters{T}
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wavelength::T
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# probe sampling
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dxp::T
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Np::Int
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xp::Vector{T}
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Lp::T
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zp::Union{T, Nothing}
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# object sampling
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dxo::T
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No::Int
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xo::Vector{T}
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Lo::T
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zo::T
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# detector sampling
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dxd::T
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Nd::Int
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xd::Vector{T}
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Ld::T
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# the general data type which is enforced
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dtype::Type{T}
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end
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"""
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init_Parameters(<kwargs>)
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Function to return parameter object storing
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all meta information needed for reconstruction.
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Note that can access all those parameters but many
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of them are connected hence to fill the struct we only need a few of
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them.
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# Parameters
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## Physical Properties
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* `wavelength` of the laser
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## General Properties
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* `dtype`: datatype used for reconstructions. `Float32` is usually faster, especially on GPUs.
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## Probe
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* `dxp`: pixel size
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* `Np`: number of pixels
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* `xp`: 1D coordinates
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* `Lp`: field of view probe (field size)
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* `zp`: distance to next plane
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## Object
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* `dxo`: pixel size
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* `No`: number of pixels
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* `xo`: 1D coordinates
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* `Lo`: field of view probe (field size)
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* `zo`: distance to next plane
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## Detector
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* `dxd`: pixel size
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* `Nd`: number of pixels
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* `xd`: 1D coordinates
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* `Ld`: field of view probe (field size)
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"""
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function init_Parameters(;
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wavelength=DEFAULT_WAVELENGTH,
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No=2^7,
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Nd=2^9,
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dxd=4.5e-6,
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zo=50e-3,
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dtype=Float32,
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zp=nothing
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)
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Ld = Nd * dxd
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# probe stuff
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dxp = wavelength * zo / Ld
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Np = Nd
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Lp = dxp*Np
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xp = FourierTools.fftpos(Lp, Np)
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# object stuff
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dxo = dxp
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Lo = dxo * No
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xo = FourierTools.fftpos(Lo, No)
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xd = FourierTools.fftpos(Ld, Nd)
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_dtype(x) = isnothing(x) ? x : dtype(x)
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Parameters(
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wavelength=_dtype(wavelength),
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# probe sampling
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dxp=_dtype(dxp),
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Np=Np,
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xp=_dtype.(xp),
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Lp=_dtype(Lp),
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zp=_dtype(zp),
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# object sampling,
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dxo=_dtype(dxo),
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No=No,
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xo=_dtype.(xo),
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Lo=_dtype(Lo),
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zo=_dtype(zo),
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# detector sampling,
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dxd=_dtype(dxd),
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Nd=Nd,
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xd=_dtype.(xd),
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Ld=_dtype(Ld),
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# the general data type which is enforced,
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dtype=dtype)
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end
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‎test/ExperimentalData.jl

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@testset "Test parameter dtype setting" begin
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@test typeof(initializeExperimentalData()) === PtyLab.ExperimentalData{Float32}
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@test typeof(initializeExperimentalData(dtype=Float64)) === PtyLab.ExperimentalData{Float64}
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end

‎test/runtests.jl

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# tests
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include("utils_grid.jl")
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include("utils_parameters.jl")
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include("ExperimentalData.jl")

‎test/utils_grid.jl

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@test t.j₁ >= 1
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@test t.i₂ <= grid_size[1]
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@test t.j₂ <= grid_size[2]
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@test (-t.i₁ + t.i₂) == tile_size[1]
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@test (-t.j₁ + t.j₂) == tile_size[2]
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@test (-t.i₁ + t.i₂ + 1) == tile_size[1]
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@test (-t.j₁ + t.j₂ + 1) == tile_size[2]
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end
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end
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‎test/utils_parameters.jl

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This file was deleted.

‎test_type.jl

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using Pkg
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Pkg.activate(".")
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using PtyLab
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init_Parameters()

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