iris.tests.test_trajectory.TestTrajectory.test_tri_polar

[bjlittle]

The "integration" test iris.tests.test_trajectory.TestTrajectory.test_tri_polar is chronically s--l--o--w.

It's interpolating a 90 point trajectory over the following cube ...

sea_water_potential_temperature / (degC) (time: 1; depth: 31; -- : 148; -- : 180)
     Dimension coordinates:
          time                                x         -        -         -
          depth                               -         x        -         -
     Auxiliary coordinates:
          latitude                            -         -        x         x
          longitude                           -         -        x         x

... using iris.analysis.trajectory.interpolate to do all the hard work.

We should investigate to diagnose the bottleneck.

I'd be pretty interested in user feedback on their experience of using iris.analysis.trajectory.interpolate and whether it's performance is fit for purpose (within the context of its use).

[ajdawson]

#1767 has details and links to user stories regarding this, seems like an issue for others too.

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[wjbenfold]

Note for anyone looking into this in future - test_tri_polar ends up using nearest neighbour rather than linear (having not specified an interpolation scheme, it's set by line 319 of trajectory.py because the coordinates aren't all 1-dimensional to nearest neighbour)