Results and plotting
Results
Every Simulation type has an associated Results object(s), one for each one of the glaciers in the simulation. This object, as its name indicates, stores all the results of the simulation, which can be used for data analysis and plotting. These types are handled by Sleipnir.jl.
Sleipnir.Results — Type
mutable struct Results{F <: AbstractFloat, I <: Integer}A mutable struct to store the results of simulations.
Fields
rgi_id::String: Identifier for the RGI (Randolph Glacier Inventory).H::Vector{Matrix{F}}: Vector of matrices representing glacier ice thicknessHover time.H_glathida::Matrix{F}: Optional matrix for Glathida ice thicknesses.H_ref::Vector{Matrix{F}}: Reference data for ice thickness.S::Matrix{F}: Glacier surface altimetry.B::Matrix{F}: Glacier bedrock.V::Matrix{F}: Glacier ice surface velocities.Vx::Matrix{F}: x-component of the glacier ice surface velocityV.Vy::Matrix{F}: y-component of the glacier ice surface velocityV.V_ref::Matrix{F}: Reference data for glacier ice surface velocitiesV.Vx_ref::Matrix{F}: Reference data for the x-component of the glacier ice surface velocityVx.Vy_ref::Matrix{F}: Reference data for the y-component of the glacier ice surface velocityVy.date_Vref::Vector{F}: Date of velocity observation (mean ofdate1anddate2).date1_Vref::Vector{F}: First date of velocity acquisition.date2_Vref::Vector{F}: Second date of velocity acquisition.t_dhdt::Tuple{F, F}: Time window of the mean surface elevation change.dhdt_ref::F: Mean surface elevation change.Δx::F: Grid spacing in the x-direction.Δy::F: Grid spacing in the y-direction.lon::F: Longitude of the glacier grid center.lat::F: Latitude of the glacier grid center.nx::I: Number of grid points in the x-direction.ny::I: Number of grid points in the y-direction.tspan::Vector{F}: Time span of the simulation.
Sleipnir.Results — Method
Results(glacier::G, ifm::IF;
rgi_id::String = glacier.rgi_id,
H::Vector{Matrix{F}} = Vector{Matrix{Sleipnir.Float}}([[;;]]),
H_glathida::Matrix{F} = glacier.H_glathida,
H_ref::Vector{Matrix{F}} = Vector{Matrix{Sleipnir.Float}}([[;;]]),
S::Matrix{F} = zeros(Sleipnir.Float, size(ifm.S)),
B::Matrix{F} = zeros(Sleipnir.Float, size(glacier.B)),
V::Vector{Matrix{F}} = Vector{Matrix{Sleipnir.Float}}([[;;]]),
Vx::Vector{Matrix{F}} = Vector{Matrix{Sleipnir.Float}}([[;;]]),
Vy::Vector{Matrix{F}} = Vector{Matrix{Sleipnir.Float}}([[;;]]),
V_ref::Vector{Matrix{F}} = Vector{Matrix{Sleipnir.Float}}([[;;]]),
Vx_ref::Vector{Matrix{F}} = Vector{Matrix{Sleipnir.Float}}([[;;]]),
Vy_ref::Vector{Matrix{F}} = Vector{Matrix{Sleipnir.Float}}([[;;]]),
date_Vref::Vector{F} = Vector{Sleipnir.Float}([]),
date1_Vref::Vector{F} = Vector{Sleipnir.Float}([]),
date2_Vref::Vector{F} = Vector{Sleipnir.Float}([]),
t_dhdt::Union{Tuple{F, F}, Nothing} = nothing,
dhdt_ref::Union{F, Nothing} = nothing,
Δx::F = glacier.Δx,
Δy::F = glacier.Δy,
lon::F = glacier.cenlon,
lat::F = glacier.cenlat,
nx::I = glacier.nx,
ny::I = glacier.ny,
t::Vector{F} = Vector{Sleipnir.Float}([]),
tspan::Tuple{F, F} = (NaN, NaN),
) where {G <: AbstractGlacier, F <: AbstractFloat, IF <: AbstractModel, I <: Integer}Construct a Results object for a glacier simulation.
Arguments
glacier::G: The glacier object, subtype ofAbstractGlacier.ifm::IF: The model object, subtype ofAbstractModel.rgi_id::String: The RGI identifier for the glacier. Defaults toglacier.rgi_id.H::Vector{Matrix{F}}: Ice thickness matrices. Defaults to an empty vector.H_glathida::Matrix{F}: Ice thickness from GlaThiDa. Defaults toglacier.H_glathida.H_ref::Vector{Matrix{F}}: Reference ice thickness. Defaults to an empty vector.S::Matrix{F}: Surface elevation matrix. Defaults to a zero matrix of the same size asifm.S.B::Matrix{F}: Bed elevation matrix. Defaults to a zero matrix of the same size asglacier.B.V::Vector{Matrix{F}}: Velocity magnitude matrix. Defaults to an empty vector.Vx::Vector{Matrix{F}}: Velocity in the x-direction matrix. Defaults to an empty vector.Vy::Vector{Matrix{F}}: Velocity in the y-direction matrix. Defaults to an empty vector.V_ref::Vector{Matrix{F}}: Reference velocity magnitude matrix. Defaults to an empty vector.Vx_ref::Vector{Matrix{F}}: Reference velocity in the x-direction matrix. Defaults to an empty vector.Vy_ref::Vector{Matrix{F}}: Reference velocity in the y-direction matrix. Defaults to an empty vector.date_Vref::Vector{F}: Date of velocity observation (mean ofdate1anddate2). Defaults to an empty vector.date1_Vref::Vector{F}: First date of velocity acquisition. Defaults to an empty vector.date2_Vref::Vector{F}: Second date of velocity acquisition. Defaults to an empty vector.t_dhdt::Union{Tuple{F, F}, Nothing}: Time window of the mean surface elevation change. Defaults tonothingin which case ifglacier.dhdtDataexists,glacier.dhdtData.tis used instead.dhdt_ref::Union{F, Nothing}: Mean surface elevation change. Defaults tonothingin which case ifglacier.dhdtDataexists,glacier.dhdtData.dhdtis used instead.Δx::F: Grid spacing in the x-direction. Defaults toglacier.Δx.Δy::F: Grid spacing in the y-direction. Defaults toglacier.Δy.lon::F: Longitude of the glacier grid center. Defaults toglacier.cenlon.lat::F: Latitude of the glacier grid center. Defaults toglacier.cenlat.nx::I: Number of grid points in the x-direction. Defaults toglacier.nx.ny::I: Number of grid points in the y-direction. Defaults toglacier.ny.tspan::Tuple(F, F): Timespan of the simulation.θ::Union{Nothing, ComponentArray{F}}: Model parameters. Defaults tonothing.loss::Union{Nothing, Vector{F}}: Loss values. Defaults tonothing.
Returns
results::Results: AResultsobject containing the simulation results.
Plots
One of the main things one can do with a Results object, is plotting them. The main function to do so is the following one:
Sleipnir.plot_glacier — Function
plot_glacier(results, plot_type, variables; kwargs...) -> FigureHigh-level entry point that dispatches to specific glacier plotting functions based on plot_type:
"heatmaps"→plot_glacier_heatmaps"quivers"→plot_glacier_quivers"evolution difference"→plot_glacier_difference_evolution"evolution statistics"→plot_glacier_statistics_evolution"integrated volume"→plot_glacier_integrated_volume"bias"→plot_bias"dem"→plot_glacier_dem
Another option is to generate a video of the evolution of the glacier's ice thickness during the simulation:
Sleipnir.plot_glacier_vid — Function
plot_glacier_vid(
plot_type::String,
results::Results,
glacier::Glacier2D,
tspan,
step,
pathVideo::String;
framerate::Int=24,
baseTitle::String=""
)Generate various types of videos for glacier data. For now only the evolution of the glacier ice thickness is supported. More types of visualizations will be added in the future.
Arguments
plot_type: Type of plot to generate. Options are:- "thickness": Heatmap of the glacier thickness.
results: A result object containing the simulation results including ice thickness over time.glacier: A glacier instance.tspan: The simulation time span.step: Time step to use to retrieve the results and generate the video.pathVideo: Path of the output animation. The format is inferred from the file extension — e.g..mp4for a video or.giffor an animated GIF.
Optional Keyword Arguments
framerate: The framerate to use for the video generation.baseTitle: The prefix to use in the title of the frames. In each frame it is concatenated with the value of the year in the form " (t=XXXX)".
And finally, it is also possible to plot various gridded data on a glacier with the following function:
Sleipnir.plot_gridded_data — Function
plot_gridded_data(
gridded_data::Union{Vector{Matrix{F}}, Matrix{F}},
results::Results;
scale_text_size::Union{Nothing,Float64}=nothing,
timeIdx::Union{Nothing,Int64}=nothing,
figsize::Union{Nothing, Tuple{Int64, Int64}} = nothing,
plotContour::Bool=false,
colormap = :cool,
logPlot = false,
) where {F <: AbstractFloat}Plot a gridded matrix (or a time series of matrices) as a heatmap using metadata from results.
Arguments
gridded_data::Union{Vector{Matrix{F}}, Matrix{F}}: Single snapshot or time series (defaults to last timestep).results::Results: Supplies lon, lat, x, y, rgi_id, Δx and H (mask).scale_text_size,figsize,colormap: Optional plotting params.timeIdx::Union{Nothing,Int64}: Select timestep whengridded_datais a vector.plotContour::Bool: overlay glacier-mask contour from results.H.logPlot::Bool: Use log10 colorscale (positive non-NaN values determine range).
Behavior
- Masks out cells where
results.H[begin] .<= 0(set to NaN). - Adds colorbar, central lon/lat tick, and a Δx-based scale bar in km.
- If
plotContour, draws mask boundary lines. - Returns a
CairoMakie.Figure.
Errors
- Asserts gridded_data is non-empty and timeIdx (if provided) is in range.
It is also possible to accumulate gridded data over time and plot cumulative fields with the following functions:
Sleipnir.accumulate_gridded_data — Function
accumulate_gridded_data(
gridded_data::Vector{Matrix{F}};
weights::Union{Nothing,AbstractVector{<:Real}}=nothing,
) where {F <: AbstractFloat}Accumulate a time series of gridded matrices into a single matrix.
Arguments
gridded_data::Vector{Matrix{F}}: Sequence of gridded fields to accumulate.weights::Union{Nothing,AbstractVector{<:Real}}: Optional per-step weights. If provided, weighted accumulation is performed assum(weights[i] * gridded_data[i]).
Returns
Matrix{F}: The accumulated matrix.
Sleipnir.plot_cumulative_gridded_data — Function
plot_cumulative_gridded_data(
gridded_data::Vector{Matrix{F}},
results::Results;
weights::Union{Nothing,AbstractVector{<:Real}}=nothing,
kwargs...
) where {F <: AbstractFloat}Plot the cumulative field of a time series of gridded matrices using plot_gridded_data. This is a thin utility wrapper to avoid duplicating plotting code.
Arguments
gridded_data::Vector{Matrix{F}}: Sequence of gridded fields to accumulate.results::Results: Results object with glacier metadata for plotting.weights::Union{Nothing,AbstractVector{<:Real}}: Optional per-step weights.kwargs...: Additional keyword arguments forwarded toplot_gridded_data.
Returns
Figure: Cumulative field figure.
Sleipnir.plot_cumulative_mb — Function
plot_cumulative_mb(results::Results; kwargs...)Plot a spatial map of the cumulative surface mass balance accumulated over the simulation period from the per-callback MB fields stored in results.MB.
Each entry of results.MB is the gridded mass-balance increment produced at one MB callback (one per MB time step). The function sums these increments cell-by-cell (via accumulate_gridded_data) to obtain the total mass balance over the period results.tspan = (t0, t1).
Modes (annual_MB)
annual_MB = false(default): plots the raw cumulative MB over the whole period, i.e.Σᵢ MBᵢ, inm w.e..annual_MB = true: divides every increment by the period lengthT = t1 - t0(in years) before summing, i.e.Σᵢ (MBᵢ / T) = (Σᵢ MBᵢ) / T. SinceΣᵢ MBᵢis the total overTyears, this is the mean annual mass-balance rate (the "annually-averaged equivalent"), inm w.e. yr⁻¹.
Returns nothing (with a warning) when results.MB is empty — e.g. when the simulation was run without use_MB = true.
Arguments
results::Results: results carrying the per-callback MB maps inresults.MB.
Keyword arguments
title::String: figure title prefix (the period(t0–t1)is appended automatically).colorbar_label::Union{Nothing,String}: colorbar label; defaults tom w.e.(orm w.e. yr⁻¹whenannual_MB = true).annual_MB::Bool = false: switch between cumulative total and mean annual rate.colormap: diverging colormap (red→white→blue by default).kwargs...: forwarded toplot_gridded_data.
Returns
Figure, ornothingif there is no MB history.
For quick DEM visualizations from either a Results object or a glacier object, the following function is available:
Sleipnir.plot_glacier_dem — Function
plot_glacier_dem(glacier_or_results; kwargs...)Plot the glacier DEM (surface elevation field S) with a terrain colormap, geographic coordinate labels, colorbar, and glacier contour overlay.
Arguments
- `glacier_or_results`: Either `Results` or `Glacier2D`.Keyword Arguments
- `title::String`: Figure title prefix.
- `colorbar_label::String`: Label for the colorbar.
- `plotContour::Bool`: Whether to overlay glacier contour (default `true`).
- `colormap`: Makie colormap symbol (default `:terrain`).
- `kwargs...`: Additional keyword arguments forwarded to `plot_gridded_data`.Returns
- `Figure`: DEM figure.And finally, figures can be saved with a unified utility function:
Sleipnir.save_figure — Function
save_figure(fig, path)Save fig to path, creating any missing parent directories automatically. Returns path.