# Visualising NetCDF using Raster.jl
**URL:** https://discourse.julialang.org/t/visualising-netcdf-using-raster-jl/85761
**Category:** Geo
**Tags:** question, plotting
**Created:** [August 15, 2022, 6:57am UTC](https://discourse.julialang.org/t/visualising-netcdf-using-raster-jl/85761 "2022-08-15T06:57:07Z")
**Posts on this page:** 11
**Page:** 1
### Author:  [@Michaela\_Vollmer](https://discourse.julialang.org/u/Michaela_Vollmer)
#### Post date: [August 15, 2022, 6:57am UTC](https://discourse.julialang.org/t/visualising-netcdf-using-raster-jl/85761/1 "2022-08-15T06:57:07Z")
Hello! I am trying to plot spatial data of a NetCDF file from a WFlow example. I have followed the steps outlined in the following question [Raster.jl discourse post](https://discourse.julialang.org/t/error-in-resampling-with-rasters-jl/73261) where a similar example is shown where the data can be plotted. However, if I apply the same principle to the WFLow example I get the following error:
ERROR: MethodError: no method matching reverse(::DimensionalData.Dimensions.LookupArrays.AutoOrder)
Closest candidates are:
The following is a minimal working example:
```julia
using NCDatasets
using Rasters, GBIF, Plots
fn = download("https://github.com/visr/wflow-artifacts/releases/download/v0.2.6/forcing-moselle.nc",joinpath("./", "forcing-moselle.nc"))
fn="forcing-moselle.nc"
fn=Raster(fn)
wkt = WellKnownText(Dataset(fn)["spatial_ref"].attrib["crs_wkt"])
# Choose the prec layer from the netcdf file
prec = Raster(fn; name=:precip, crs=wkt, mappedcrs=wkt)
# Use typemin(Int32) as the missing value.
prec = replace_missing(prec, typemin(Int32))
#resampled = resample(prec, 1; crs=EPSG(4326))
plot(prec)
```
How can this be fixed? Thank you very much in advance!
---
### Author:  [@digital\_carver](https://discourse.julialang.org/u/digital_carver)
#### Post date: [August 15, 2022, 8:13am UTC](https://discourse.julialang.org/t/visualising-netcdf-using-raster-jl/85761/2 "2022-08-15T08:13:36Z")
Please post the full stacktrace of the error, since this doesn’t tell us which line the error is coming from.
---
### Author:  [@visr](https://discourse.julialang.org/u/visr)
#### Post date: [August 15, 2022, 8:42am UTC](https://discourse.julialang.org/t/visualising-netcdf-using-raster-jl/85761/3 "2022-08-15T08:42:22Z")
Here is the full stacktrace. Tagging @Raf since this may be an issue in DimensionalData.jl.
```julia
ERROR: MethodError: no method matching reverse(::DimensionalData.Dimensions.LookupArrays.AutoOrder)
Closest candidates are:
reverse(::Union{SubString{String}, String}) at strings/substring.jl:171
reverse(::DimensionalData.Dimensions.LookupArrays.AbstractCategorical) at d:\visser_mn\.julia\packages\DimensionalData\1iOoH\src\LookupArrays\methods.jl:5
reverse(::DimensionalData.Dimensions.LookupArrays.AbstractSampled) at d:\visser_mn\.julia\packages\DimensionalData\1iOoH\src\LookupArrays\methods.jl:10
...
Stacktrace:
[1] reverse(lookup::DimensionalData.Dimensions.LookupArrays.Categorical{Union{Missing, Float64}, Vector{Union{Missing, Float64}}, DimensionalData.Dimensions.LookupArrays.AutoOrder, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}})
@ DimensionalData.Dimensions.LookupArrays d:\visser_mn\.julia\packages\DimensionalData\1iOoH\src\LookupArrays\methods.jl:7
[2] reverse(dim::X{DimensionalData.Dimensions.LookupArrays.Categorical{Union{Missing, Float64}, Vector{Union{Missing, Float64}}, DimensionalData.Dimensions.LookupArrays.AutoOrder, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}})
@ DimensionalData d:\visser_mn\.julia\packages\DimensionalData\1iOoH\src\array\methods.jl:307
[3] _reverse(dim::X{DimensionalData.Dimensions.LookupArrays.Categorical{Union{Missing, Float64}, Vector{Union{Missing, Float64}}, DimensionalData.Dimensions.LookupArrays.AutoOrder, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}})
@ DimensionalData d:\visser_mn\.julia\packages\DimensionalData\1iOoH\src\array\methods.jl:304
[4] reverse(A::Raster{Float32, 3, Tuple{X{DimensionalData.Dimensions.LookupArrays.Categorical{Union{Missing, Float64}, Vector{Union{Missing, Float64}}, DimensionalData.Dimensions.LookupArrays.AutoOrder, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}}, Y{DimensionalData.Dimensions.LookupArrays.Categorical{Union{Missing, Float64}, Vector{Union{Missing, Float64}}, DimensionalData.Dimensions.LookupArrays.AutoOrder, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}}, Ti{DimensionalData.Dimensions.LookupArrays.Sampled{Dates.DateTime, Vector{Dates.DateTime}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Irregular{Tuple{Nothing, Nothing}}, DimensionalData.Dimensions.LookupArrays.Points, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}}}, Tuple{}, Array{Float32, 3}, Symbol, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}, Float32}; dims::X{DimensionalData.Dimensions.LookupArrays.Categorical{Union{Missing, Float64}, Vector{Union{Missing, Float64}}, DimensionalData.Dimensions.LookupArrays.AutoOrder, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}})
@ DimensionalData d:\visser_mn\.julia\packages\DimensionalData\1iOoH\src\array\methods.jl:297
[5] _reorder(#unused#::Type{DimensionalData.Dimensions.LookupArrays.ForwardOrdered}, x::Raster{Float32, 3, Tuple{X{DimensionalData.Dimensions.LookupArrays.Categorical{Union{Missing, Float64}, Vector{Union{Missing, Float64}}, DimensionalData.Dimensions.LookupArrays.AutoOrder, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}}, Y{DimensionalData.Dimensions.LookupArrays.Categorical{Union{Missing, Float64}, Vector{Union{Missing, Float64}}, DimensionalData.Dimensions.LookupArrays.AutoOrder, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}}, Ti{DimensionalData.Dimensions.LookupArrays.Sampled{Dates.DateTime, Vector{Dates.DateTime}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Irregular{Tuple{Nothing, Nothing}}, DimensionalData.Dimensions.LookupArrays.Points, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}}}, Tuple{}, Array{Float32, 3}, Symbol, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}, Float32}, dim::X{DimensionalData.Dimensions.LookupArrays.Categorical{Union{Missing, Float64}, Vector{Union{Missing, Float64}}, DimensionalData.Dimensions.LookupArrays.AutoOrder, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}})
@ DimensionalData d:\visser_mn\.julia\packages\DimensionalData\1iOoH\src\utils.jl:33
[6] reorder(x::Raster{Float32, 3, Tuple{X{DimensionalData.Dimensions.LookupArrays.Categorical{Union{Missing, Float64}, Vector{Union{Missing, Float64}}, DimensionalData.Dimensions.LookupArrays.AutoOrder, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}}, Y{DimensionalData.Dimensions.LookupArrays.Categorical{Union{Missing, Float64}, Vector{Union{Missing, Float64}}, DimensionalData.Dimensions.LookupArrays.AutoOrder, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}}, Ti{DimensionalData.Dimensions.LookupArrays.Sampled{Dates.DateTime, Vector{Dates.DateTime}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Irregular{Tuple{Nothing, Nothing}}, DimensionalData.Dimensions.LookupArrays.Points, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}}}, Tuple{}, Array{Float32, 3}, Symbol, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}, Float32}, orderdim::X{DataType})
@ DimensionalData d:\visser_mn\.julia\packages\DimensionalData\1iOoH\src\utils.jl:29
[7] _reorder
@ d:\visser_mn\.julia\packages\DimensionalData\1iOoH\src\utils.jl:26 [inlined]
[8] reorder
@ d:\visser_mn\.julia\packages\DimensionalData\1iOoH\src\utils.jl:21 [inlined]
[9] _prepare(A::Raster{Float32, 3, Tuple{X{DimensionalData.Dimensions.LookupArrays.Categorical{Union{Missing, Float64}, Vector{Union{Missing, Float64}}, DimensionalData.Dimensions.LookupArrays.AutoOrder, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}}, Y{DimensionalData.Dimensions.LookupArrays.Categorical{Union{Missing, Float64}, Vector{Union{Missing, Float64}}, DimensionalData.Dimensions.LookupArrays.AutoOrder, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}}, Ti{DimensionalData.Dimensions.LookupArrays.Sampled{Dates.DateTime, Vector{Dates.DateTime}, DimensionalData.Dimensions.LookupArrays.ForwardOrdered, DimensionalData.Dimensions.LookupArrays.Irregular{Tuple{Nothing, Nothing}}, DimensionalData.Dimensions.LookupArrays.Points, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}}}}, Tuple{}, Array{Float32, 3}, Symbol, DimensionalData.Dimensions.LookupArrays.Metadata{Rasters.NCDfile, Dict{Symbol, Any}}, Float32})
@ Rasters d:\visser_mn\.julia\packages\Rasters\UC1tU\src\plotrecipes.jl:195
[10] macro expansion
@ d:\visser_mn\.julia\packages\Rasters\UC1tU\src\plotrecipes.jl:19 [inlined]
[11] apply_recipe(plotattributes::AbstractDict{Symbol, Any}, A::AbstractRaster)
@ Rasters d:\visser_mn\.julia\packages\RecipesBase\qpxEX\src\RecipesBase.jl:289
[12] _process_userrecipes!(plt::Any, plotattributes::Any, args::Any)
@ RecipesPipeline d:\visser_mn\.julia\packages\RecipesPipeline\OXGmH\src\user_recipe.jl:36
[13] recipe_pipeline!(plt::Any, plotattributes::Any, args::Any)
@ RecipesPipeline d:\visser_mn\.julia\packages\RecipesPipeline\OXGmH\src\RecipesPipeline.jl:70
[14] _plot!(plt::Plots.Plot, plotattributes::Any, args::Any)
@ Plots d:\visser_mn\.julia\packages\Plots\lW9ll\src\plot.jl:209
[15] plot(args::Any; kw::Base.Pairs{Symbol, V, Tuple{Vararg{Symbol, N}}, NamedTuple{names, T}} where {V, N, names, T<:Tuple{Vararg{Any, N}}})
@ Plots d:\visser_mn\.julia\packages\Plots\lW9ll\src\plot.jl:91
[16] plot(args::Any)
@ Plots d:\visser_mn\.julia\packages\Plots\lW9ll\src\plot.jl:82
```
---
### Author:  [@joa-quim](https://discourse.julialang.org/u/joa-quim)
#### Post date: [August 15, 2022, 10:08am UTC](https://discourse.julialang.org/t/visualising-netcdf-using-raster-jl/85761/4 "2022-08-15T10:08:23Z")
You can show it with GMT. But the data has outliers so it need a manually tuned color map
```julia
using GMT
C = makecpt(0,5);
imshow("forcing-moselle.nc?precip", proj=:guess, cmap=C, colorbar=true)
```
But note that GMT automatically installation on Linux is broken due to dependencies conflicts external to the package itself.
---
### Author:  [@Raf](https://discourse.julialang.org/u/Raf)
#### Post date: [August 15, 2022, 10:28am UTC](https://discourse.julialang.org/t/visualising-netcdf-using-raster-jl/85761/5 "2022-08-15T10:28:54Z")
Sorry, looks like I’ve introduced a bug with some recent changes.
Should be fixed in the next 24 hours.
---
### Author:  [@Michaela\_Vollmer](https://discourse.julialang.org/u/Michaela_Vollmer)
#### Post date: [August 15, 2022, 11:02am UTC](https://discourse.julialang.org/t/visualising-netcdf-using-raster-jl/85761/6 "2022-08-15T11:02:39Z")
Thanks for this. I will give this a try
---
### Author:  [@Michaela\_Vollmer](https://discourse.julialang.org/u/Michaela_Vollmer)
#### Post date: [August 15, 2022, 11:03am UTC](https://discourse.julialang.org/t/visualising-netcdf-using-raster-jl/85761/7 "2022-08-15T11:03:10Z")
Thanks! That would be great!
---
### Author:  [@Raf](https://discourse.julialang.org/u/Raf)
#### Post date: [August 15, 2022, 5:06pm UTC](https://discourse.julialang.org/t/visualising-netcdf-using-raster-jl/85761/8 "2022-08-15T17:06:48Z")
~~Ok this is partly a bug in NCDatasets.jl - the dimension lookups X and Y are being given the type `Vector{Union{Mising,Float64}}` - which means they miss dispatch in Rasters.jl and are getting assigned to a fallback and partly broken.~~
That will be fixed, because they don’t actually contain any missing values. But they shouldn’t have `Missing` in the type - actual missing values in the dimension variable would break most of the use cases of the dimensions.
~~(I’ll make an issue on NCDatasets.jl github for this)~~
---
### Author:  [@Raf](https://discourse.julialang.org/u/Raf)
#### Post date: [August 15, 2022, 5:15pm UTC](https://discourse.julialang.org/t/visualising-netcdf-using-raster-jl/85761/9 "2022-08-15T17:15:54Z")
It seems this is actually a problem with your data - your X and Y coordinate variables have `_FillValue = NaN`.
This is not allowed in CF standards, (see [NetCDF Climate and Forecast (CF) Metadata Conventions](https://cfconventions.org/cf-conventions/cf-conventions.html#attribute-appendix) and search for `_FillValue` if you are interested)
We can probably handle it more gracefully, but you should also probably speak to whoever is making this dataset and remove the `_FillValue` attribute from coordinate variables. (Haha @visr I guess thats you, I just realised where it comes from)
Edit:
One last thing - now this is fixed and plots locally (will push a new version in the next few hours), there are 366 time slices! Unlike `imshow` in GMT, `plot(prec)` with Rasters.jl will try to tile them all. Which will take forever and wont be what you want.
Instead, do `plot(prec[Ti=1])` or `plot(prec[Ti=At(DateTime(2000, 1, 2))])` to plot one of the slices, or use a `Selector` to choose slices you want to plot, like `Where` to plot the first day in some specific months:
```julia
using Dates
plot(prec[Ti=Where(d -> dayofmonth(d) == 1 && month(d) in (Jan, Apr, Jul, Oct))])
```
---
### Author:  [@visr](https://discourse.julialang.org/u/visr)
#### Post date: [August 16, 2022, 12:18pm UTC](https://discourse.julialang.org/t/visualising-netcdf-using-raster-jl/85761/10 "2022-08-16T12:18:24Z")
Haha nice job @Raf you managed to trace the issue back to me. I can imagine actual missing values on coordinate are not allowed, but didn’t know having a `_FillValue` is explicitly disallowed under the CF conventions. I added them because `xarray` adds them. So I removed them now in [remove \_FillValue from coordinate variables by visr · Pull Request #215 · Deltares/Wflow.jl · GitHub](https://github.com/Deltares/Wflow.jl/pull/215). The wflow-artifacts datasets linked above have now been fixed by `ncatted -O -a _FillValue,lat,d,, inmaps.nc` for x/y/lat/lon. There is an upstream xarray issue as well: [to\_netcdf -\> \_fill\_value without NaN · Issue #2037 · pydata/xarray · GitHub](https://github.com/pydata/xarray/issues/2037). I’m afraid having fill values on coordinate variables is not uncommon.
---
### Author:  [@Raf](https://discourse.julialang.org/u/Raf)
#### Post date: [August 16, 2022, 9:29pm UTC](https://discourse.julialang.org/t/visualising-netcdf-using-raster-jl/85761/11 "2022-08-16T21:29:25Z")
Sweet. I also made an issue at NCDatasets.jl to track the fact that the FillValue field propagates to the dimension variable `eltype`: [https://github.com/Alexander-Barth/NCDatasets.jl/issues/185](https://github.com/Alexander-Barth/NCDatasets.jl/issues/185).
But I also fixed Rasters.jl to handle that when it happens, which should be registered shortly.
Of course some things will break if there are actually any `missing` values… `findfirst` and `searchsorted` will not like that at all. It’s possible `Missing` in the eltype will break some base functions as well, I’m not sure though.