Add percentiles to multi-model stats

[Peter9192]

Add the option to calculate percentiles in the multi-model preprocessor, using scipy.stats.mstats.mquantiles. This is the same function as used in Iris.

It works by adding e.g. p10 or p99 to the list of operators in the recipe. p99.5 will be interpreted as the 99.5 percentile, i.e. the 0.995 quantile, but the decimal point will be changed to a dash - in the output filename.

Unfortunately, the scipy function doesn't work directly on multidimensional arrays. Thus, I added a wrapper that flattens the extra dimensions before passing the array to scipy, similar to what's done in Iris.

Tasks

• Create an issue to discuss what you are going to do, if you haven't done so already (and add the link at the bottom)
• This pull request has a descriptive title that can be used in a changelog
• Add unit tests
• Public functions should have a numpy-style docstring so they appear properly in the API documentation. For all other functions a one line docstring is sufficient.
• If writing a new/modified preprocessor function, please update the documentation
• Circle/CI tests pass. Status can be seen below your pull request. If the tests are failing, click the link to find out why.
• Codacy code quality checks pass. Status can be seen below your pull request. If there is an error, click the link to find out why. If you suspect Codacy may be wrong, please ask by commenting.

If you need help with any of the tasks above, please do not hesitate to ask by commenting in the issue or pull request.

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Closes #563

[valeriupredoi]

wee comment there, mate. All good! Cheers

[bouweandela]

Great addition @Peter9192! Just a few suggestions for improvement

[Peter9192]

Thanks for the suggestions @bouweandela! I think I got them all