This pull request addresses several structural issues with ogh data processing and visualization. It incorporates the monthly exceedance probability calculation function and new endpoints in aggregate_space_time_average() and aggregate_space_time_sum(). New visualization include rendering the gridded cell value on linear-scale spatial maps and temporal boxplots.
ogh_meta has been re-written as a python script based on the notebook operations, instead of the json file. This enables the metadata to be read in as a Class object within ogh, with which the ogh_meta.py can be migrated with ogh.py for conda and pip installation.
This pull request addresses several structural issues with ogh data processing and visualization. It incorporates the monthly exceedance probability calculation function and new endpoints in aggregate_space_time_average() and aggregate_space_time_sum(). New visualization include rendering the gridded cell value on linear-scale spatial maps and temporal boxplots.
ogh_meta has been re-written as a python script based on the notebook operations, instead of the json file. This enables the metadata to be read in as a Class object within ogh, with which the ogh_meta.py can be migrated with ogh.py for conda and pip installation.