Generic reduce and statistics

[otzi5300]

Implements functionality for reducing time dimension in dataset using user specified aggregation functions, similar to python's reduce(). A statistics method is also implemented to simplify calculations of basic statistics (min, max, mean) directly from a DFSU file. This function utilized the new reduce functions for this purpose.

import mikeio.generic
# Compute min and max simultaneously using reduce
generic.reduce("input.dfsu", "minmax.dfsu", 
       functions=[np.minimum, np.maximum])

# With custom function labels
generic.reduce("input.dfsu", "stats.dfsu",
       functions=[np.minimum, np.maximum, np.add],
       function_labels=["Min", "Max", "Sum"],
)

Using statistics as a convenience function for computing min, max, and mean:

generic.statistics("input.dfsu", "stats.dfsu") # basic
generic.statistics("input.dfsu", "stats2.dfsu", items=["Temperature"]) # Specified items
generic.statistics("input.dfsu", "stats3.dfsu",  from_ts=100, to_ts = 150) # To from specific time steps

[ecomodeller]

The reduce function should be very similar to the existing Dataset.aggregate, name, arguments, etc to make it familiar.