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 take a global average over both the longitude and latitude dimensions?

You can use average_lonlat to compute the global average over the longitude and latitude dimensions and weighted_average_lonlat to compute the global latitude-weighted average over the longitude and latitude dimensions.

The function average_lonlat is different from composing average_lon and average_lat as the former computes an average over both the longitude and latitude dimensions and the latter computes an average of averages. In particular, the results differ when there are NaNs.

reduced_var = average_lonlat(var)

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 shift my longitudes from 0 to 360 degrees to -180 to 180 degrees?

You can use the shift_longitude function. To shift the longitudes from 0 to 360 degrees to -180 degrees to 180 degrees, use shift_longitude(var, -180.0, 180.0). The function assumes the prime meridian (0th degree) in var is the same before and after centering the longitudes. The units of the longitude dimension should be in degrees. If this not the case, then you can use convert_dim_units to change the units of the longitude dimension to degrees.

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 only over selected dimensions is possible with the keyword dim_names. 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.data3×4 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.dimsOrderedCollections.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.dimsOrderedCollections.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.data2×3 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_varOrderedCollections.OrderedDict{String, Vector{Float64}} with 2 entries:
  "lon"      => [0.0, 1.0]
  "latitude" => [0.0, 1.0, 2.0]

How do I resample the data in a OutputVar using only a subset of dimensions from another OutputVar?

You can use the dim_names keyword argument in 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.

The argument dim_names can either be a string or an iterable such as an array of strings. The correct dimension is identified by using conventional_dim_name. For example, if src_var has a longitude dimension named lon, dest_var has a longitude dimension named long, and dim_names is longitude, then resampling is done on the longitude dimension because conventional_dim_name maps lon, long, and longitude to longitude.

julia> src_var.data3×4 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.dimsOrderedCollections.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.dimsOrderedCollections.OrderedDict{String, Vector{Float64}} with 2 entries:
  "long" => [0.0, 1.0]
  "lat"  => [0.0, 1.0, 2.0]
julia> partial_resampled_var = # dim_names is either a string or an iterable
           ClimaAnalysis.resampled_as(src_var, dest_var, dim_names = "longitude");
julia> partial_resampled_var.data2×4 Matrix{Float64}:
 1.0  4.0  7.0  10.0
 2.0  5.0  8.0  11.0
julia> partial_resampled_var.dimsOrderedCollections.OrderedDict{String, Vector{Float64}} with 2 entries:
  "lon"      => [0.0, 1.0]
  "latitude" => [0.0, 1.0, 2.0, 3.0]

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 or 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")
reverse_dim!(var, "pressure_level") # in-place