In bmcnellis/RSFIA: FIA Tree Mortality Analysis

data("FIA_mortality_with_explanatory")
mort_df <- FIA_mortality_with_explanatory
#for (i in c(5, 8, 10)) {
#  for (j in c('NDVI', 'NDMI', 'RGI', 'MIR')) {
#    cat('\n\n Variable:', j, '\n', 'Year span:', i, '\n\n')
#    mort_df <- RSFIA::ApplyColumnAggregate(df = mort_df, n_yr_prev = i, var_in = j)
#    colnames(mort_df)[ncol(mort_df)] <- paste(j, i, sep = '_')
#    cat('Done!\n')
#    save.image()
#  }
#}
#incl_vars <- c('LAT', 'LON', 'NDVI_5', 'NDVI_8', 'NDVI_10',
#               'NDMI_5', 'NDMI_8', 'NDMI_10',
#               'RGI_5', 'RGI_8', 'RGI_10',
#               'MIR_5', 'MIR_8', 'MIR_10')
#FIA_spectrals_by_year_bin <- mort_df[, incl_vars]
#use_data(FIA_spectrals_by_year_bin)

weather_vars <- c('MAT', 'min_temp_by_Q_val', 'max_temp_by_Q_val',
                  'MAP', 'dry_Q_sum', 'mean_dry_period')
# MAP might be broken here - scale is from 0-12, unsure of units
for (i in c(2, 5, 10)) {
  for (j in c(weather_vars)) {
    cat('\n\n Variable:', j, '\n', 'Year span:', i, '\n\n')
    mort_df <- RSFIA::ApplyColumnAggregate(df = mort_df, type = 'daymet',
                                           n_yr_prev = i, var_in = j)
    colnames(mort_df)[ncol(mort_df)] <- paste(j, i, sep = '_')
    cat('Done!\n')
    save.image()
  }
}
incl_vars <- c('LAT', 'LON', colnames(mort_df)[310:ncol(mort_df)])
mort_df <- mort_df[, incl_vars]
which_MAP <- grep(colnames(mort_df), pattern = 'MAP')
mort_df[, which_MAP] <- round(mort_df[, which_MAP] * 365, 0)
FIA_weather_by_year_bin <- mort_df
use_data(FIA_weather_by_year_bin, overwrite = T)