Update summaries in R using the raw data in Climsoft and the definitions file in the buckets

[lilyclements]

Here is some R code/script on how to "update" your summaries in R using the raw data in Climsoft and the definitions file in the buckets. For this, you need to have:

1. A data set in Climsoft
2. A definitions file in the buckets

Step Zero: Update the R Packages

# Update the packages
devtools::install_github("IDEMSInternational/rpicsa")
devtools::install_github("IDEMSInternational/epicsadata")
devtools::install_github("IDEMSInternational/epicsawrap")

library(epicsawrap)

Step One: Link the Station_ID for the data in Climsoft to an existing Definitions ID:
You can link a data frame from Climsoft to an existing Definitions ID by running:

update_metadata_definition_id(country = "zm_test",
                              station_id = "NC002052",
                              definition_id = "ZME4",
                              add_climsoft = TRUE,
                              elementfiltercolumn = "elementName",
                              elements = c("Temp  Daily Max", "Temp  Daily Min", "Precip  Daily"))

Here:

• station_id: A character string representing the station ID of the data given in Climsoft
• definition_id: A character string representing the new definition ID to be added.
• add_climsoft A logical value indicating whether to add in climsoft details. This will add in the values from elementfiltercolumn and elements.
• elementfiltercolumn Name of the column to filter by elements, default is 'elementName'.
• elements Vector of element IDs to filter the data. Default is elements = c("Temp  Daily Max", "Temp  Daily Min", "Precip  Daily")

Step Two: Set up the credentials for Climsoft

password <- *******
set_climsoft_conn(dbname = "mariadb_climsoft_test_r_db_v4",
                  user = "root",
                  password = password,
                  host = "34.140.21.153",
                  port = 3306)

Step Three: Set up and run for our different functions*

country <- "zm_test"
station_id  <- "NP002051"
annual_rainfall_summaries(country, station_id, call = "climsoft")
annual_temperature_summaries(country, station_id , call = "climsoft")
monthly_temperature_summaries(country, station_id , call = "climsoft")
crop_success_probabilities(country, station_id, call = "climsoft")
season_start_probabilities(country, station_id, call = "climsoft")


# then we can try with other values for crop_success and season_start:
crop_success_probabilities(country, station_id, call = "climsoft", 
                           planting_dates = c(0, 100, 200, 300),
                           planting_length = c(0, 200),
                           water_requirements = c(0, 1000))
season_start_probabilities(country, station_id, call = "climsoft", start_dates = c(100, 200))