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Cache linear interpolator #1997

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Cache linear interpolator #1997

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9 changes: 7 additions & 2 deletions lib/iris/analysis/trajectory.py
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Original file line number Diff line number Diff line change
Expand Up @@ -237,12 +237,17 @@ def interpolate(cube, sample_points, method=None):
# Use a cache with _nearest_neighbour_indices_ndcoords()
cache = {}

# Cache the linear interpolator
scheme = iris.analysis.Linear()
coords, points = zip(*sample_points)
interpolator = scheme.interpolator(cube, coords)
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@rhattersley rhattersley May 3, 2016 •
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These lines need to be protected by if method in ('linear', None) - partly because it's wasted effort otherwise, but mostly because they will fail when trying to do nearest-neighbour interpolation over multi-dimensional coordinates.

NB. The docstring for iris.analysis.trajectory.interpolate is a little ambiguous about the default value of method, but it turns out that the default is not just simply "linear", but switches to "nearest" when using multi-dimensional coordinates. 👎 I definitely don't propose to change that behaviour in this PR, but it would be nice to clarify the docstring (again, possibly in a separate PR - small is beautiful).


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@rhattersley rhattersley May 3, 2016

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The corresponding import statement needs to be removed.

for i in range(trajectory_size):
point = [(coord, values[i]) for coord, values in sample_points]

if method in ["linear", None]:
column = linear_regrid(cube, point)
new_cube.data[..., i] = column.data
column = interpolator([val[i] for _, val in sample_points])
new_cube.data[..., i] = column
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@rhattersley rhattersley May 3, 2016

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This still needs the .data suffix, i.e.:

new_cube.data[..., i] = column.data

elif method == "nearest":
column_index = _nearest_neighbour_indices_ndcoords(cube, point, cache=cache)
column = cube[column_index]
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