Fix Var.weighted_average_lat bug with NaN and FT32 #203
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
## main #203 +/- ##
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Coverage 98.25% 98.25%
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Could you add your PR message to the commit message? This way, if people try to understand why you needed to change from 1 to 1.0 they can do that directly from the git log |
Sbozzolo
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If there is an `OutputVar` whose latitudes are in `Float32` and the data
contains a `NaN`, then `Var.weighted_average_lat` creates `weights_1d`
whose type is `Vector{Float32}` and `nan_mask` whose type is
`Vector{Real}`. Note that `nan_mask = ifelse.(isnan.(var.data), NaN, 1)`
is a `Vector{Real}`, because `NaN` is a `Float64` and `1` is a `Int64`.
Then, the computation `nanmean(nan_mask[index_tuple...] .* weights_1d)`
throws an error, because `nan_mask[index_tuple...] .* weights_1d` is a
`Vector{Real}` and `nanmean` is not defined for `Vector{Real}`.
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In the function
Var.weighted_average_lat, if latitudes is inFloat32and there areNaNs in the data, then eventually the computation being done isVector{Real}timesVector{Float32}which givesVector{Real}. Then,nanmeanis computed on this vector, but throw an error since there is no function defined for that type.