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Huge speed-up for model TAP03.

task #7793: (https://gna.org/task/?7793) Speed-up of dispersion models.

The change for running systemtest is:
test_tp02_data_to_tap03
13.869s -> 7.263s

This is won by not checking single values in the R1rho array for math domain
errors, but calculating all steps, and in one single round check for finite values.
If just one non-finite value is found, the whole array is returned with a large
penalty of 1e100.

This makes all calculations be the fastest numpy array way.

tlinnet 2014-05-19

changed /branches/disp_speed/lib/dispersion/tap03.py
/branches/disp_speed/lib/dispersion/tap03.py Diff Switch to side-by-side view
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