Geo divide zero #505
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Geo divide zero #505
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The Newton-Raphson iteration converges more slowly near the poles, and triggers a divide-by-zero at the poles. Although the previous transform was handling this correctly in the sense that it was still giving the right answer, the divide-by-zero warning was non-optimal. The present version switches to a Taylor-series approximation for latitudes within 5 degrees of the poles. This avoids the divide-by-zero, and also runs faster on arrays with a full range of latitudes.
An attempt to do this had been make by masking zero values in the denominator; but at least with current numpy, this is not enough, because the __div__ method of the first argument is used. The solution is to ensure that the first argument is also a masked array.
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The second commit takes care of the remaining two divide-by-zero warnings noted in #503. |
| return np.concatenate((x.filled(), y.filled()), 1) | ||
| x = (cos_latitude * ma.sin(half_long)) / sinc_alpha | ||
| y = (ma.sin(latitude) / sinc_alpha) | ||
| return np.concatenate((x.filled(0), y.filled(0)), 1) |
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Is it right that we have np.cos(latitude) in the numerator on 282 but ma.sin(latitude) in the numerator on 283?
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Yes.
http://en.wikipedia.org/wiki/Aitoff_projection
The one difference is the factor of 2 in x; but it is handed via set_aspect in the init() method.
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Thanks Eric, I can confirm that this fixes the warnings on my tests. |
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The Newton-Raphson iteration converges more slowly near
the poles, and triggers a divide-by-zero at the poles.
Although the previous transform was handling this correctly
in the sense that it was still giving the right answer,
the divide-by-zero warning was non-optimal.
The present version switches to a Taylor-series approximation
for latitudes within 5 degrees of the poles. This avoids
the divide-by-zero, and also runs faster on arrays with a
full range of latitudes.