How-to guide and cookbook

How do I make a line plot with variable on the y axis instead of the x one?

By default, the plotting functions in MakieExt place the variable on the x axis. If you want it on the y axis instead (e.g., you are plotting the vertical profile of a column), you can pass the dim_on_y = true argument to the axis.

For instance,

plot!(var, more_kwargs = Dict(:axis => [:dim_on_y => true]))

ClimaAnalysis.Utils provides a convenience function kwargs to specify arguments a little bit more easily without having to think about Symbols too much.

plot!(var, more_kwargs = Dict(:axis => kwargs(dim_on_y = true))

How do I take an average of a a variable in a given window of time?

You can use the window function to select a portion of a given var. For example, to select only the time from 10 seconds to 100 for var

reduced_var = window(var, "time", left = 10, right = 100)

Now, you can apply the usual average functions.

How do I make the y axis logscale?

The plotting routines can pass additional arguments to Makie through the more_kwargs keyword arguments. more_kwargs has to be a dictionary that maps symbols to a list of pairs. The accepted symbols are :axis, :plot, and :cb, and the pairs have to be pairs of symbols to values (the keyword arguments you want to pass down). Given that the type structure is a little complicated, ClimaAnalysis comes with a helper function for you to use. So, if you want to set the logscale for the y axis, you would do something like

import ClimaAnalysis.Utils: kwargs as ca_kwargs

plot!(fig, var, more_kwargs = Dict(:axis => ca_kwargs(yscale = log)))

where inside ca_kwargs you pass the arguments you would pass to Makie.Axis.

How do I center my longitude to 180 instead of 0?

You can use the center_longitude! function.

How do I find the specific name of a dimension in a `OutputVar` given its conventional name?

Suppose you want to extract the longitudes of your data but you don't know if the dimension was called lon or long. In this case, you can use the Var.longitude_name function to find the name. This function scans the names and compares them to a standard list in ClimaAnalysis.Var.LONGITUDE_NAMES. You can also customize that variable if your name is not in that list. Equivalent functions exist for others dimensions too.

How do I move to pressure coordinates?

The Atmos module in ClimaAnalysis comes with a function, to_pressure_coordinates that does precisely that. The function takes an input OutputVar and a pressure OutputVar. If the two are compatible, a new OutputVar is returned where the values are linearly interpolated on fixed pressure levels.

How do I reorder the dimensions in a `OutputVar` to match the dimensions in another `OutputVar`?

You can use the reordered_as(src_var, dest_var) function where src_var is a OutputVar with the dimensions you want to reorder to match the dimensions in the OutputVar dest_var.

julia> src_var.dims |> keys |> collect2-element Vector{String}:
 "long"
 "lat"
julia> dest_var.dims |> keys |> collect2-element Vector{String}:
 "lat"
 "long"
julia> reordered_var = ClimaAnalysis.reordered_as(src_var, dest_var);
julia> reordered_var.dims |> keys |> collect2-element Vector{String}:
 "lat"
 "long"

How do I resample the data in a `OutputVar` using the dimensions from another `OutputVar`?

You can use the resampled_as(src_var, dest_var) function where src_var is a OutputVar with the data you want to resample using the dimensions in another OutputVar dest_var. If resampling is possible, then a new OutputVar is returned where the data in src_var is resampled using a linear interpolation to fit the dimensions in dest_var. Resampling is not possible when the dimensions in either OutputVars are missing units, the dimensions between the OutputVars do not agree, or the data in src_var is not defined everywhere on the dimensions in dest_var.

julia> src_var.data
3×4 Matrix{Float64}:
 1.0  4.0  7.0  10.0
 2.0  5.0  8.0  11.0
 3.0  6.0  9.0  12.0

julia> src_var.dims
OrderedDict{String, Vector{Float64}} with 2 entries:
  "lon"      => [0.0, 1.0, 2.0]
  "latitude" => [0.0, 1.0, 2.0, 3.0]

julia> dest_var.dims # dims that src_var.data should be resampled on
OrderedDict{String, Vector{Float64}} with 2 entries:
  "long" => [0.0, 1.0]
  "lat"  => [0.0, 1.0, 2.0]

julia> resampled_var = ClimaAnalysis.resampled_as(src_var, dest_var);

julia> resampled_var.data
2×3 Matrix{Float64}:
 1.0  4.0  7.0
 2.0  5.0  8.0

julia> resampled_var.dims # updated dims that are the same as the dims in dest_var
OrderedDict{String, Vector{Float64}} with 2 entries:
  "lon"      => [0.0, 1.0]
  "latitude" => [0.0, 1.0, 2.0]

How do I apply a land or sea mask to a `OutputVar`?

You can use apply_landmask or apply_oceanmask to mask out the land or ocean, respectively, in a OutputVar. The result of apply_landmask(var) is data of var, where any coordinate corresponding to land is zero. Similarly, the result of apply_oceanmask(var) is data of var, where any coordinate corresponding to ocean is zero.

var_no_land = ClimaAnalysis.apply_landmask(var)
var_no_ocean = ClimaAnalysis.apply_oceanmask(var)

How do I replace `NaN` and `missing` values in the data of a `OutputVar` with 0.0?

You can use replace to replace all NaN and missing values in the data of a OutputVar with 0.0. See the example below of this usage.

var_no_nan_and_missing = ClimaAnalysis.replace(var, missing => 0.0, NaN => 0.0)

How do I reverse a dimension so that an interpolant can be made?

You can use reverse_dim to reverse a dimension by name. See the example below of this usage.

# Reversing pressure levels so that an interpolant can be made
var_reversed = reverse_dim(var, "pressure_level")