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August 29, 2015 14:25
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# couple things I'd throw in there: | |
# moar whitespace | |
res = [ | |
[ | |
[ | |
kriger.predict(x,y,z) | |
for x in grid[0] | |
] | |
for y in grid[1] | |
] | |
for z in grid[2] | |
] | |
# sure it looks big, but lines are cheap and they make the loops far more grokkable | |
# moar intermediate variables. | |
# One way to do this (This doesn't help too much here but if x,y, and z correspond to more interesting column names it might) | |
exes, whys, zees = grid | |
... | |
# another way, using map, itertools and more intermediate variables: | |
prediction_inputs = zip(itertools.product(*grid)) # You could flatten this out here with xs, ys, zs = zip(...) | |
predictions = map(kriger.predict, *prediction_inputs) | |
predictions_grid = array(predictions).reshape(*grid.dimensions) | |
# ^ not sure what you're using this output format for, but it seems like it's the reason for a large part of the | |
# awkwardness of what you're trying to to. Take the reshape out onto its own line to encapsulate the craziness | |
# separate from the beauty of the actual predictions you're doing | |
# and of course, you can always | |
import antigravity |
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