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Add Pluto notebook to explore the output data
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| ### A Pluto.jl notebook ### | ||
| # v0.14.5 | ||
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| using Markdown | ||
| using InteractiveUtils | ||
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| # This Pluto notebook uses @bind for interactivity. When running this notebook outside of Pluto, the following 'mock version' of @bind gives bound variables a default value (instead of an error). | ||
| macro bind(def, element) | ||
| quote | ||
| local el = $(esc(element)) | ||
| global $(esc(def)) = Core.applicable(Base.get, el) ? Base.get(el) : missing | ||
| el | ||
| end | ||
| end | ||
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| # ╔═╡ c7383ff4-ba4c-11eb-1977-b31b330b20d0 | ||
| begin | ||
| import Pkg | ||
| Pkg.activate(@__DIR__) | ||
| Pkg.instantiate() | ||
| using Plots | ||
| using HDF5 | ||
| using Unitful | ||
| using UnitfulRecipes | ||
| using PlutoUI | ||
| end | ||
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| # ╔═╡ 3e85f1c4-32ca-4e8e-ab9f-2fefaaabffb7 | ||
| md"## Load HDF5 output file" | ||
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| # ╔═╡ 72c703c9-3c32-45ab-b910-25a3c6652bdc | ||
| filename = "particle_da.h5" | ||
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| # ╔═╡ 7cbbad5a-3767-422c-9d6b-f32524d4bf04 | ||
| fh = h5open(filename, "r") | ||
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| # ╔═╡ 7c316637-defe-4f60-a7e5-2e10511f7044 | ||
| md"## Set these parameters to choose what to plot" | ||
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| # ╔═╡ e1acfe11-0ead-4ada-946e-eff674e6d44e | ||
| begin | ||
| timestamps = keys(fh["data_syn"]) | ||
| md""" | ||
| Select the timestamp | ||
| $(@bind timestamp_idx Slider(1:length(timestamps))) | ||
| """ | ||
| end | ||
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| # ╔═╡ 775fbb1e-a760-4862-829d-455051942255 | ||
| timestamp = timestamps[timestamp_idx] | ||
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| # ╔═╡ d442ef52-1566-484d-af31-ba3565307502 | ||
| md""" | ||
| Select the field | ||
| $(@bind field Select([f => f for f in keys(fh["data_syn"]["t0000"])])) | ||
| """ | ||
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| # ╔═╡ 384116c1-ed19-4a8c-85a7-6c0dfd9c164f | ||
| md"## Contour plots of surface height" | ||
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| # ╔═╡ 8f67e2b3-9a01-42a3-a56a-11b84776a5e1 | ||
| md"## Scatter plot of particle weights" | ||
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| # ╔═╡ a35f5895-5066-4e1d-b252-6172888aa92d | ||
| begin | ||
| weights = read(fh["weights"][timestamp]) | ||
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| p1 = scatter(weights, marker=:star) | ||
| p2 = scatter(weights, marker=:star, yscale=:log10) | ||
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| for plt in (p1, p2) | ||
| plot!(plt; xlabel="Particle ID", ylabel="Weight") | ||
| end | ||
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| plot(p1, p2, label="") | ||
| end | ||
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| # ╔═╡ e5335e14-bdb6-432c-94ab-c666c304efc6 | ||
| md"## Time series of Estimated Sample Size" | ||
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| # ╔═╡ 343a1d50-38f8-4457-81dc-5d962a2acb4a | ||
| plot([1 / sum(read(w) .^ 2) for w in fh["weights"]]; | ||
| label="", marker=:o, xlabel="Time step", ylabel="Estimated Sample Size (1 / sum(weight^2))") | ||
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| # ╔═╡ a52a3f7e-1d8e-4153-b0c2-2cb47584c447 | ||
| md"## Animation" | ||
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| # ╔═╡ 8520dcbb-0bd8-4020-aea3-009e24df2099 | ||
| md"## Collect data from the output file" | ||
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| # ╔═╡ cff1a64f-03ba-4150-9501-fa4803901808 | ||
| # All time-independent quantities | ||
| begin | ||
| field_unit = read(fh["data_syn"]["t0000"][field]["Unit"]) | ||
| var_unit = read(fh["data_var"]["t0000"][field]["Unit"]) | ||
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| field_desc = read(fh["data_syn"]["t0000"][field]["Description"]) | ||
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| x_unit = read(fh["grid"]["x"]["Unit"]) | ||
| y_unit = read(fh["grid"]["y"]["Unit"]) | ||
| x_st_unit = read(fh["stations"]["x"]["Unit"]) | ||
| y_st_unit = read(fh["stations"]["y"]["Unit"]) | ||
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| x = read(fh["grid"]["x"]) .* uparse(x_unit) .|> u"km" | ||
| y = read(fh["grid"]["y"]) .* uparse(y_unit) .|> u"km" | ||
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| x_st = read(fh["stations"]["x"]) .* uparse(x_st_unit) .|> u"km" | ||
| y_st = read(fh["stations"]["y"]) .* uparse(y_st_unit) .|> u"km" | ||
| end | ||
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| # ╔═╡ e17da3a7-39e4-4326-aa2e-08f70b574878 | ||
| function plot_data(x, y, z_t, z_avg, z_std, field_desc) | ||
| n_contours = 100 | ||
| zmax = max(maximum(z_t), maximum(z_avg)) | ||
| zmin = min(minimum(z_t), minimum(z_avg)) | ||
| levels = range(zmin, zmax; length=n_contours) | ||
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| # Note that for heatmaps we need to permute the dimensions of the z matrix | ||
| p1 = heatmap(x, y, z_t'; title="True $(lowercase(field_desc))") | ||
| p2 = heatmap(x, y, z_avg'; title="Assimilated $(lowercase(field_desc))") | ||
| p3 = heatmap(x, y, z_std'; title="Std of assimilated $(lowercase(field_desc))") | ||
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| for (i, plt) in enumerate((p1, p2, p3)) | ||
| # Set labels | ||
| plot!(plt; xlabel="x", ylabel="y") | ||
| # Set range of color bar for first two plots | ||
| i ∈ (1, 2) && plot!(plt; clims=(ustrip(zmin), ustrip(zmax))) | ||
| # Add the positions of the stations | ||
| scatter!(plt, x_st, y_st, color=:red, marker=:star, label="") | ||
| end | ||
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| plot(p1, p2, p3; titlefontsize=8, guidefontsize=8) | ||
| end | ||
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| # ╔═╡ ba33b9a1-7d73-4247-b298-ccf30acc8859 | ||
| function animate_data(fh, field, field_unit, var_unit, x, y) | ||
| animation = @animate for timestamp ∈ keys(fh["data_syn"]) | ||
| z_t = read(fh["data_syn"][timestamp][field]) .* uparse(field_unit) | ||
| z_avg = read(fh["data_avg"][timestamp][field]) .* uparse(field_unit) | ||
| z_std = sqrt.(read(fh["data_var"][timestamp][field]) .* uparse(var_unit)) | ||
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| plot_data(x, y, z_t, z_avg, z_std, field_desc) | ||
| end | ||
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| return mp4(animation, "animation_jl.mp4"; fps=5) | ||
| end | ||
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| # ╔═╡ a9343779-de40-4d33-8487-27d53ec095c0 | ||
| animate_data(fh, field, field_unit, var_unit, x, y) | ||
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| # ╔═╡ da1315e0-71de-4df6-9d74-259979571e1e | ||
| # Quantities specific to the current timestamp | ||
| begin | ||
| z_t = read(fh["data_syn"][timestamp][field]) .* uparse(field_unit) | ||
| z_avg = read(fh["data_avg"][timestamp][field]) .* uparse(field_unit) | ||
| z_std = sqrt.(read(fh["data_var"][timestamp][field]) .* uparse(var_unit)) | ||
| end | ||
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| # ╔═╡ 1d230245-5f29-4895-b0cb-4e49f6c125ff | ||
| plot_data(x, y, z_t, z_avg, z_std, field_desc) | ||
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| # ╔═╡ Cell order: | ||
| # ╠═c7383ff4-ba4c-11eb-1977-b31b330b20d0 | ||
| # ╟─3e85f1c4-32ca-4e8e-ab9f-2fefaaabffb7 | ||
| # ╠═72c703c9-3c32-45ab-b910-25a3c6652bdc | ||
| # ╟─7cbbad5a-3767-422c-9d6b-f32524d4bf04 | ||
| # ╟─7c316637-defe-4f60-a7e5-2e10511f7044 | ||
| # ╟─e1acfe11-0ead-4ada-946e-eff674e6d44e | ||
| # ╟─775fbb1e-a760-4862-829d-455051942255 | ||
| # ╟─d442ef52-1566-484d-af31-ba3565307502 | ||
| # ╟─384116c1-ed19-4a8c-85a7-6c0dfd9c164f | ||
| # ╟─e17da3a7-39e4-4326-aa2e-08f70b574878 | ||
| # ╟─1d230245-5f29-4895-b0cb-4e49f6c125ff | ||
| # ╟─8f67e2b3-9a01-42a3-a56a-11b84776a5e1 | ||
| # ╟─a35f5895-5066-4e1d-b252-6172888aa92d | ||
| # ╟─e5335e14-bdb6-432c-94ab-c666c304efc6 | ||
| # ╟─343a1d50-38f8-4457-81dc-5d962a2acb4a | ||
| # ╟─a52a3f7e-1d8e-4153-b0c2-2cb47584c447 | ||
| # ╟─ba33b9a1-7d73-4247-b298-ccf30acc8859 | ||
| # ╟─a9343779-de40-4d33-8487-27d53ec095c0 | ||
| # ╟─8520dcbb-0bd8-4020-aea3-009e24df2099 | ||
| # ╟─cff1a64f-03ba-4150-9501-fa4803901808 | ||
| # ╟─da1315e0-71de-4df6-9d74-259979571e1e |
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