noaa-national-severe-storms-laboratory / frdd-monte-python Goto Github PK

The only form of storm mode returned to the user in StormModeClassifier.classify is a 2-dimensional array with storm mode labeled at each valid grid point. However, when entire objects are subsequently reclassified as new embedded objects, the mode information of the original object is lost. For making a lat-lon plot of storm mode this is fine, but for statistical analysis you wouldn't want to lose that over-written object's mode information. I suggest, in additional to the 2-D array, we return a 1-d array of storm modes that matches the scikit properties object one-to-one.

Need to flip the sign for the long object QC option
https://github.com/WarnOnForecast/MontePython/blob/ce517b00052b7ac079b358a22f7324083cf4f726/monte_python/object_quality_control.py#L110

Corey has provided data. I have netcdf files in /work/cpotvin/WOFS_STORM_STATS_NEW3/OBJECTS/20170501_2000_0min that include the dBZ field ("values"), rotation field ("rot_values"), and storm mode field ("storm_modes") with an attribute showing the conversion.

Use this as the unit test for the StormModeClassifier.