climatrends 0.4 (2022-09-26)

climatrends 0.2 (2022-02-14)

New function crop_sensitive() to compute crop sensitive indices.
New function late_frost() to compute late spring frost.
Export function get_timeseries()
Enable future modular expansion of data sources using API clients by creating specific functions that are called with the argument data.from in get_timeseries()
Enable argument last.day, optional to span, when indices are retrieved with focus on time series analysis
Enable data retrieve from large areas in ‘nasapower’ by clustering the lonlat points with stats::hclust()
Methods for objects of classes ‘vector’ (default), ‘matrix’, ‘array’, ‘data.frame’ and ‘sf’. The last two with focus in retrieve data from external sources.
Remove dependency from ‘tibble’ which was basically to provide a ‘cool’ printing method
Implement a print() method for objects that inherits the class ‘clima_df’
Calls from “nasapower” can be adjusted with argument pars, mainly for temperature(), GDD() and ETo(). Details in the function documentation
New temperature() indices provided. Details in the function documentation
Function GDD() applies two equations adjustments for cold zones and one for warm zones with the argument equation. Details in the function documentation
Function GDD() now allows to return the raw daily gdd or number of days to reach the accumulated gdd (the default in previous versions) using the argument return.as

New default method in all functions which uses a vector as main input
Change order of GDD() arguments. Previous versions used GDD(object, day.one = NULL, degree.days = NULL, base = 10, span = 150, ...). From now on GDD() default behaviour is GDD(object, ..., base = 10), with additional arguments are passed through ... in each defined method. The function return by default the accumulated degree-days across the series.

Add examples of data set from local sources modis() and chirp()
Add details for the utilisation of data set daylight to compute the percentage of daylight based on lat and month