/
plot.jl
455 lines (403 loc) · 19.8 KB
/
plot.jl
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#=
Julia Plots
=#
function error_plot(model, learned, errorModel, errorLearned, t)
# Generate example data
x = [1, 5, 9] # Three points on the x-axis
labels = ["s", "g1", "g2"] # Labels for the points
model_data = model
learned_data = learned
errM = errorModel
errD = errorLearned
# Plot scatter plot with error bars
Plots.scatter(x, model_data, yerr=errM, label="Model Data", color="blue", alpha=0.6)
Plots.xticks!(x, labels)
Plots.scatter!(x, learned_data, yerr=errD, label="Learned Data", color="red", markersize=4)
Plots.xticks!(x, labels)
Plots.title!(t)
# Show the plot
Plots.plot!(legend=:topright, titlefontsize=30, xguidefontsize=30, yguidefontsize=30, margin = 25mm)
end
function plot_err(s_model=s_model, g1_model=g1_model, g2_model=g2_model, s_data=s_data, g1_data=g1_data, g2_data=g2_data, parametersScatterplot=parametersScatterplot)
n = size(s_model, 1)
if parametersScatterplot
ps1 = error_plot([mean(s_model), mean(g1_model), mean(g2_model)],
[mean(s_data), mean(g1_data), mean(g2_data)],
[std(s_model)/sqrt(n), std(g1_model)/sqrt(n), std(g2_model)/sqrt(n)],
[std(s_data)/sqrt(n), std(g1_data)/sqrt(n), std(g2_data)/sqrt(n)],
"Learned vs True Parameters")
Plots.savefig(Plots.plot(ps1, size = (1920, 1080)), "parametersScatterplot.pdf")
Plots.savefig(Plots.plot(ps1, size = (1920, 1080)), "parametersScatterplot.png")
end
end
function hist_1(x::Array{T, 1}, y::Array{T, 1}, t1, t2) where T<:Real
bin_edges = range(-1, stop=1, step=0.1)
Plots.histogram(x,
alpha=0.5,
bins=bin_edges,
label=t1,
titlefontsize=30,
xguidefontsize=30,
yguidefontsize=30)
Plots.histogram!(y,
alpha=0.5,
bins=bin_edges,
label=t2,
titlefontsize=30,
xguidefontsize=30,
yguidefontsize=30)
Plots.plot!(margin=15mm)
end
function hist_2(x::Array{T, 1}, y::Array{T, 1}, t1, t2) where T<:Real
bin_edges = range(-1, stop=1, step=0.1)
Plots.histogram(x,
alpha=0.5,
bins=bin_edges,
label=t1,
xticks = -1:0.1:1,
titlefontsize=30,
xguidefontsize=30,
yguidefontsize=30)
Plots.histogram!(y,
alpha=0.5,
bins=bin_edges,
label=t2,
xticks = -1:0.1:1,
titlefontsize=30,
xguidefontsize=30,
yguidefontsize=30)
Plots.plot!(margin=15mm)
end
function plot_hist(s_model=s_model, g1_model=g1_model, g2_model=g2_model, s_data=s_data, g1_data=g1_data, g2_data=g2_data, hist_1=hist_1, hist_2=hist_2, parametersHistogram=parametersHistogram)
if parametersHistogram
hist1 = hist_1(s_model, s_data, "s Model", "s Data")
hist2 = hist_2(g1_model, g1_data, "g1 Model", "g1 Data")
hist3 = hist_2(g2_model, g2_data, "g2 Model", "g2 Data")
bin_edges = range(-1, stop=1, step=0.1)
hist4 = Plots.histogram(s_model - s_data,
alpha=0.5,
label="S Model and Data Residuals")
hist5 = Plots.histogram(g1_model - g1_data,
alpha=0.5,
closed =:both,
bins=range(-2, stop=2, step=0.1),
label="g1 Model and Data Residuals",
xticks = -1:0.1:1)
hist6 = Plots.histogram(g2_model - g2_data,
alpha=0.5,
closed =:both,
bins=range(-2, stop=2, step=0.1),
label="g2 Model and Data Residuals",
xticks = -1:0.1:1)
Plots.savefig(Plots.plot(hist1,
hist2,
hist3,
hist4,
hist5,
hist6,
layout = (2,3),
size = (1920,1080)),
"parametersHistogram.pdf")
Plots.savefig(Plots.plot(hist1,
hist2,
hist3,
hist4,
hist5,
hist6,
layout = (2,3),
size = (1920,1080)),
"parametersHistogram.png")
end
end
function generate_heatmap(data::Array{T, 2}, cbmin, cbmax) where T<:Real
Plots.heatmap(data,
aspect_ratio=:equal, # ensure square cells
color=:winter, # use the Winter color map
cbar=:true, # add the color bar
xlabel="u",
ylabel="v",
clims=(cbmin, cbmax), # set the color limits
xlims=(0.5, size(data, 2) + 0.5), # set the x-axis limits to include the full cells
ylims=(0.5, size(data, 1) + 0.5), # set the y-axis limits to include the full cells
ticks=:none, # remove the ticks
frame=:box, # draw a box around the plot
grid=:none, # remove the grid lines
titlefontsize=30,
xguidefontsize=30,
yguidefontsize=30,
margin = 25mm
)
end
function generate_heatmap_sp_t(data::Array{T, 2}, t, cbmin, cbmax) where T<:Real
Plots.heatmap(data,
aspect_ratio=:equal, # ensure square cells
color=:winter, # use the Winter color map
cbar=:true, # add the color bar
title = t,
clims=(cbmin, cbmax), # set the color limits
xlims=(0.5, size(data, 2) + 0.5), # set the x-axis limits to include the full cells
ylims=(0.5, size(data, 1) + 0.5), # set the y-axis limits to include the full cells
ticks=:none, # remove the ticks
frame=:box, # draw a box around the plot
grid=:none, # remove the grid lines
margin = 15mm
)
end
function generate_heatmap_sp_t2(data::Array{T, 2}, t, cbmin, cbmax) where T<:Real
Plots.heatmap(data,
aspect_ratio=:equal, # ensure square cells
color=:winter, # use the Winter color map
cbar=:true, # add the color bar
title = t,
clims=(cbmin, cbmax), # set the color limits
xlims=(0.5, size(data, 2) + 0.5), # set the x-axis limits to include the full cells
ylims=(0.5, size(data, 1) + 0.5), # set the y-axis limits to include the full cells
ticks=:none, # remove the ticks
frame=:box, # draw a box around the plot
grid=:none, # remove the grid lines
margin = 15mm,
size=(1920, 1080)
)
end
function generate_heatmap_sp(data::Array{T, 2}, cbmin, cbmax) where T<:Real
Plots.heatmap(data,
aspect_ratio=:equal, # ensure square cells
color=:winter, # use the Winter color map
cbar=:true, # add the color bar
clims=(cbmin, cbmax), # set the color limits
xlims=(0.5, size(data, 2) + 0.5), # set the x-axis limits to include the full cells
ylims=(0.5, size(data, 1) + 0.5), # set the y-axis limits to include the full cells
ticks=:none, # remove the ticks
frame=:box, # draw a box around the plot
grid=:none, # remove the grid lines
margin = 15mm
)
end
function generate_heatmap_titled(data::Array{T, 2}, t, cbmin, cbmax) where T<:Real
Plots.heatmap(data,
aspect_ratio=:equal, # ensure square cells
color=:winter, # use the Winter color map
cbar=:true, # add the color bar
xlabel="u",
ylabel="v",
title = t,
clims=(cbmin, cbmax), # set the color limits
xlims=(0.5, size(data, 2) + 0.5), # set the x-axis limits to include the full cells
ylims=(0.5, size(data, 1) + 0.5), # set the y-axis limits to include the full cells
ticks=:none, # remove the ticks
frame=:box, # draw a box around the plot
grid=:none, # remove the grid lines
titlefontsize=30,
xguidefontsize=30,
yguidefontsize=30,
margin = 25mm
)
end
#=
function plot_hm(r=r, c=c, outdir=outdir, sampled_indices=sampled_indices, starCatalog=starCatalog, pixelGridFits=pixelGridFits, get_middle_15x15=get_middle_15x15, generate_heatmap_sp_t=generate_heatmap_sp_t, generate_heatmap_sp=generate_heatmap_sp,generate_heatmap_titled=generate_heatmap_titled)#p
star1 = sampled_indices[1]
star2 = sampled_indices[2]
star3 = sampled_indices[3]
#p_value = p
chiSquareTemplate = zeros(r, c)
chiSquare = []
for i in 1:3
starCatalog[sampled_indices[i]] = Float64.(starCatalog[sampled_indices[i]])
end
for i in 1:3
chiSquareTemplate = Float64.(starCatalog[sampled_indices[i]]) - pixelGridFits[sampled_indices[i]].^2
chiSquareTemplate = chiSquareTemplate./(errVignets[sampled_indices[i]].^2)
#err cutout , divide matrices pointwise
push!(chiSquare, chiSquareTemplate)
end
hm11 = generate_heatmap_sp_t(get_middle_15x15(starCatalog[star1]),
"Model",
minimum([minimum(starCatalog[star1]), minimum(pixelGridFits[star1])]),
maximum([maximum(starCatalog[star1]), maximum(pixelGridFits[star1])]))
hm12 = generate_heatmap_sp_t(get_middle_15x15(pixelGridFits[star1]),
"Data",
minimum([minimum(starCatalog[star1]), minimum(pixelGridFits[star1])]),
maximum([maximum(starCatalog[star1]), maximum(pixelGridFits[star1])]))
hm13 = generate_heatmap_sp_t(get_middle_15x15(chiSquare[1]),
"ChiSquare",
minimum(chiSquare[1]),
maximum(chiSquare[1]))
hm21 = generate_heatmap_sp(get_middle_15x15(starCatalog[star2]),
minimum([minimum(starCatalog[star2]), minimum(pixelGridFits[star2])]),
maximum([maximum(starCatalog[star2]), maximum(pixelGridFits[star2])]))
hm22 = generate_heatmap_sp(get_middle_15x15(pixelGridFits[star2]),
minimum([minimum(starCatalog[star2]), minimum(pixelGridFits[star2])]),
maximum([maximum(starCatalog[star2]), maximum(pixelGridFits[star2])]))
hm23 = generate_heatmap_sp(get_middle_15x15(chiSquare[2]),
minimum(chiSquare[2]),
maximum(chiSquare[2]))
hm31 = generate_heatmap_sp(get_middle_15x15(starCatalog[star3]),
minimum([minimum(starCatalog[star3]), minimum(pixelGridFits[star3])]),
maximum([maximum(starCatalog[star3]), maximum(pixelGridFits[star3])]))
hm32 = generate_heatmap_sp(get_middle_15x15(pixelGridFits[star3]),
minimum([minimum(starCatalog[star3]), minimum(pixelGridFits[star3])]),
maximum([maximum(starCatalog[star3]), maximum(pixelGridFits[star3])]))
hm33 = generate_heatmap_sp(get_middle_15x15(chiSquare[3]),
minimum(chiSquare[3]),
maximum(chiSquare[3]))
#=
hm41 = generate_heatmap_sp(starCatalog[star4], minimum([minimum(starCatalog[star1]), minimum(pixelGridFits[star4])]), maximum([maximum(starCatalog[star4]), maximum(pixelGridFits[star4])]))
hm42 = generate_heatmap_sp(pixelGridFits[star4], minimum([minimum(starCatalog[star4]), minimum(pixelGridFits[star4])]), maximum([maximum(starCatalog[star4]), maximum(pixelGridFits[star4])]))
hm43 = generate_heatmap_sp(chiSquare[4], minimum(chiSquare[4]), maximum(chiSquare[4]))
hm51 = generate_heatmap_sp(starCatalog[star5], minimum([minimum(starCatalog[star5]), minimum(pixelGridFits[star5])]), maximum([maximum(starCatalog[star5]), maximum(pixelGridFits[star5])]))
hm52 = generate_heatmap_sp(pixelGridFits[star5], minimum([minimum(starCatalog[star5]), minimum(pixelGridFits[star5])]), maximum([maximum(starCatalog[star5]), maximum(pixelGridFits[star5])]))
hm53 = generate_heatmap_sp(chiSquare[5], minimum(chiSquare[5]), maximum(chiSquare[5]))
hm61 = generate_heatmap_sp(starCatalog[star6], minimum([minimum(starCatalog[star6]), minimum(pixelGridFits[star6])]), maximum([maximum(starCatalog[star6]), maximum(pixelGridFits[star6])]))
hm62 = generate_heatmap_sp(pixelGridFits[star6], minimum([minimum(starCatalog[star6]), minimum(pixelGridFits[star6])]), maximum([maximum(starCatalog[star6]), maximum(pixelGridFits[star6])]))
hm63 = generate_heatmap_sp(chiSquare[6], minimum(chiSquare[6]), maximum(chiSquare[6]))
=#
#=
fft_image1 = fft(complex.(starCatalog[star1] .- pixelGridFits[star1]))
fft_image1 = abs2.(fft_image1)
pk1 = []
for i in 1:10
radius = range(1, max(r/2, c/2) - 1, length=10)
push!(pk1, powerSpectrum(fft_image1, radius[i]))
end
fftmin1 = minimum(fft_image1)
fftmax1 = maximum(fft_image1)
fft_image2 = fft(complex.(starCatalog[star2] .- pixelGridFits[star2]))
fft_image2 = abs2.(fft_image2)
pk2 = []
for i in 1:10
radius = range(1, max(r/2, c/2) - 1, length=10)
push!(pk2, powerSpectrum(fft_image2, radius[i]))
end
fftmin2 = minimum(fft_image2)
fftmax2 = maximum(fft_image2)
fft_image3 = fft(complex.(starCatalog[star3] .- pixelGridFits[star3]))
fft_image3 = abs2.(fft_image3)
pk3 = []
for i in 1:10
radius = range(1, max(r/2, c/2) - 1, length=10)
push!(pk3, powerSpectrum(fft_image3, radius[i]))
end
fftmin3 = minimum(fft_image3)
fftmax3 = maximum(fft_image3)
hm8 = generate_heatmap_sp_t(fft_image1, "FFT Residuals", fftmin1, fftmax1)
hm9 = generate_heatmap_sp(fft_image2, fftmin2, fftmax2)
hm10 = generate_heatmap_sp(fft_image3, fftmin3, fftmax3)
=#
zmn = minimum([minimum(starCatalog[star3]), minimum(pixelGridFits[star3])])
zmx = maximum([maximum(starCatalog[star3]), maximum(pixelGridFits[star3])])
s1 = Plots.surface(title="Model Star", titlefontsize=30, starCatalog[star3], zlim=(zmn, zmx), colorbar = false)
s2 = Plots.surface(title="pixelGridFit", titlefontsize=30, pixelGridFits[star3], zlim=(zmn, zmx), colorbar = false)
s3 = Plots.surface(title="Residuals", titlefontsize=30, starCatalog[star3] .- pixelGridFits[star3], zlim=(2*zmn, 2*zmx), colorbar = false)
meanRelativeError = zeros(r,c)
for j in 1:size(starCatalog[star1], 1)
for k in 1:size(starCatalog[star1], 2)
RelativeError = []
for i in 1:length(starCatalog)
push!(RelativeError, abs.(starCatalog[i][j,k] .- pixelGridFits[i][j,k]) ./ abs.(starCatalog[i][j,k] .+ 1e-10))
end
meanRelativeError[j,k] = mean(RelativeError)
end
end
RelativeErrorHM = generate_heatmap_sp_t2(meanRelativeError, "Mean Relative Error at Each Pixel", minimum(meanRelativeError), maximum(meanRelativeError))
pk_1 = Plots.plot(pk1,
xlabel = "k",
linewidth=5,
tickfontsize=16,
titlefontsize=30,
xguidefontsize=30,
yguidefontsize=30,
ylabel = "P(k)",
title = "Power Spectrum",
margin = 25mm)
pk_2 = Plots.plot(pk2,
xlabel = "k",
linewidth=5,
tickfontsize=16,
titlefontsize=30,
xguidefontsize=30,
yguidefontsize=30,
ylabel = "P(k)",
margin = 25mm)
pk_3 = Plots.plot(pk3,
xlabel = "k",
linewidth=5,
tickfontsize=16,
titlefontsize=30,
xguidefontsize=30,
yguidefontsize=30,
ylabel = "P(k)",
margin = 25mm)
#title1 = Plots.plot(title = "I(u,v) Model", titlefontsize=30, grid = false, showaxis = false, bottom_margin = -25Plots.px)
#title2 = Plots.plot(title = "I(u,v) Data", titlefontsize=30, grid = false, showaxis = false, bottom_margin = -25Plots.px)
#title3 = Plots.plot(title = "Chi-Square Residuals", titlefontsize=30, grid = false, showaxis = false, bottom_margin = -25Plots.px)
Plots.savefig(Plots.plot(hm11, hm12, hm13,
hm21, hm22, hm23,
hm31, hm32, hm33,
layout = (3,3),
widths=ones(9),
size = (1920,1080)),
joinpath("outdir", "pixelGridFit.pdf"))
Plots.savefig(Plots.plot(hm11, hm12, hm13,
hm21, hm22, hm23,
hm31, hm32, hm33,
layout = (3,3),
widths=ones(9),
size = (1920,1080)),
joinpath("outdir", "pixelGridFit.png"))
Plots.savefig(RelativeErrorHM, joinpath("outdir", "relativeErrorHM.pdf"))
Plots.savefig(RelativeErrorHM, joinpath("outdir", "relativeErrorHM.png"))
Plots.savefig(Plots.plot(s1,
s2,
s3,
layout = (1,3),
size = (1920,1080)),
joinpath(outdir, "3dPixelGridFit.png"))
Plots.savefig(Plots.plot(pk_1,
pk_2,
pk_3,
layout = (3,1),
size = (1920,1080)),
joinpath(outdir, "powerspectra.png"))
Plots.savefig(Plots.plot(hm8,
hm9,
hm10,
layout = (3,1),
size = (1920,1080)),
joinpath(outdir, "fftresiduals.png"))
Plots.savefig(Plots.plot(pk_1,
pk_2,
pk_3,
layout = (3,1),
size = (1920,1080)),
joinpath(outdir, "powerspectra.pdf"))
Plots.savefig(Plots.plot(hm8,
hm9,
hm10,
layout = (3,1),
size = (1920,1080)),
joinpath(outdir, "fftresiduals.pdf"))
end
=#
#=
Revisit Later?
=#
#=
#=
661 scale = 1/0.29
662 ks93, k0 = ks(g1_map, g2_map)
663 ksCosmos = get_middle_15x15(imfilter(ks93, Kernel.gaussian(scale)))
664 kshm = Plots.heatmap(ksCosmos,
665 title="Kaisser-Squires",
666 xlabel="u",
667 ylabel="v",
668 xlims=(0.5, size(ksCosmos, 2) + 0.5), # set the x-axis limits to include the full cells
669 ylims=(0.5, size(ksCosmos, 1) + 0.5), # set the y-axis limits to include the full cells
670 aspect_ratio=:equal,
671 ticks=:none, # remove the ticks
672 frame=:box, # draw a box around the plot
673 grid=:none, # remove the grid lines
674 size=(1920,1080))
675
676 Plots.savefig(kshm, joinpath("outdir","kaisserSquires.png"))
677 =#
=#