library(tibble)
library(tidyverse)
ihr_car_ratio <- greta::uniform(0,1)
#> ℹ Initialising python and checking dependencies, this may take a moment.
#> ✔ Initialising python and checking dependencies ... done!
#>
ihr_car_ratio
#> greta array (variable following a uniform distribution)
#>
#> [,1]
#> [1,] ?
greta_data <- tibble(
x = 1:10,
car_ratio = ihr_car_ratio
)
# print method in a tibble is overwritten somehow
greta_data
#> # A tibble: 10 × 2
#> x car_ratio[,1]
#> <int> <gret_rry[,1]>
#> 1 1 NA
#> 2 2 car_ratio[,1]
#> 3 3 <gret_rry[,1]>
#> 4 4 NA
#> 5 5 car_ratio[,1]
#> 6 6 <gret_rry[,1]>
#> 7 7 NA
#> 8 8 car_ratio[,1]
#> 9 9 <gret_rry[,1]>
#> 10 10 NA
# the data is still a normal greta uniform however
greta_data$car_ratio
#> greta array (variable following a uniform distribution)
#>
#> [,1]
#> [1,] ?
# you can do greta-things with it!
greta_data |>
mutate(
samples = greta::calculate(car_ratio, nsim = 1),
samples_dbl = as.numeric(samples)
)
#> # A tibble: 10 × 4
#> x car_ratio[,1] samples samples_dbl
#> <int> <gret_rry[,1]> <named list> <dbl>
#> 1 1 NA <dbl [1 × 1 × 1]> 0.223
#> 2 2 car_ratio[,1] <dbl [1 × 1 × 1]> 0.223
#> 3 3 <gret_rry[,1]> <dbl [1 × 1 × 1]> 0.223
#> 4 4 NA <dbl [1 × 1 × 1]> 0.223
#> 5 5 car_ratio[,1] <dbl [1 × 1 × 1]> 0.223
#> 6 6 <gret_rry[,1]> <dbl [1 × 1 × 1]> 0.223
#> 7 7 NA <dbl [1 × 1 × 1]> 0.223
#> 8 8 car_ratio[,1] <dbl [1 × 1 × 1]> 0.223
#> 9 9 <gret_rry[,1]> <dbl [1 × 1 × 1]> 0.223
#> 10 10 NA <dbl [1 × 1 × 1]> 0.223Created on 2024-04-30 with reprex v2.1.0
Session info
sessioninfo::session_info()
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#> setting value
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#> collate en_US.UTF-8
#> ctype en_US.UTF-8
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#> date 2024-04-30
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#> ──────────────────────────────────────────────────────────────────────────────