Create internal R function to transform mean and median model-output data to scoringutils-compatible format

[bsweger]

(formerly part of https://github.com/Infectious-Disease-Modeling-Hubs/hubEvals/issues/12)

Create an internal data transformation function in hubEvals that will transform mean and median model-output data into a format that can be successfully converted to a scoringutils forecast object: https://epiforecasts.io/scoringutils/dev/reference/as_forecast.html (scoringutils classifies both mean and median forecasts as a point forecast).

This is not a user-facing function. Instead, it will be invoked by the publicly-accessible function described in https://github.com/Infectious-Disease-Modeling-Hubs/hubEvals/issues/11.

A good source of test data for this function is the forecast_outputs data object in the hubExamples repo (filtering on output_type == mean and output_type == median)

https://github.com/Infectious-Disease-Modeling-Hubs/hubExamples/blob/main/data/forecast_outputs.rda

Definition of done:

• [ ] A new R function called transform_point_model_output
• [ ] Corresponding unit test(s)

[elray1]

couple of quick notes:

• consider names like transform_point_model_out
• we should be able to get away without requiring the column names location, target_end_date, and horizon -- see related issue here