Closed ianthomas23 closed 1 year ago
Merging #1243 (049e036) into main (6e9b412) will increase coverage by
0.06%
. The diff coverage is100.00%
.
@@ Coverage Diff @@
## main #1243 +/- ##
==========================================
+ Coverage 83.36% 83.42% +0.06%
==========================================
Files 35 35
Lines 8826 8858 +32
==========================================
+ Hits 7358 7390 +32
Misses 1468 1468
Impacted Files | Coverage Δ | |
---|---|---|
datashader/reductions.py | 77.87% <100.00%> (ø) |
|
datashader/utils.py | 83.80% <100.00%> (+1.31%) |
:arrow_up: |
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For
*_n
reductions such asmax_n
we need 3d and 4d versions ofcombine
functions to support non-categorical aggregations with shape(ny, nx, n)
and categorical aggregations with shape(ny, nx, ncat, n)
. In themain
branch we currently only implement the 4d versions and when we are dealing with non-categorical 3d arrays we insert an extra dimension so that they can be considered to have a single category. This has been fine up until now.Looking forward I am implementing antialiased line support for inspection reductions such as
max_n
andwhere
and thesecombine
functions are needed in the antialiased line code. This requires the array dimension changing to occur within numba-jitted functions which isn't really viable as numpy arrays with different dimensions are considered different types innumba
. So here the solution is to have separate 3d and 4d numba-jitted functions which iterate over the arrays and call common functions to do the low-level maths.