autoplot.fbl_ts giving error when h=1

[robjhyndman]

library(tsibble)
library(fable)
library(dplyr)
library(lubridate)

jan14_vic_elec <- tsibbledata::vic_elec |>
  filter(yearmonth(Time) == yearmonth("2014 Jan")) |>
  index_by(Date = as_date(Time)) |>
  summarise(
    Demand = sum(Demand),
    Temperature = max(Temperature)
  )

jan14_vic_elec |>
  model(TSLM(Demand ~ Temperature)) |>
  forecast(
    new_data(jan14_vic_elec, 1) |>
      mutate(Temperature = 15)
  ) |>
  autoplot(jan14_vic_elec)
#> Warning: Computation failed in `stat_interval()`.
#> Caused by error in `trans$transform()`:
#> ! `transform_date()` works with objects of class <Date> only
#> Warning in min(x, na.rm = na.rm): no non-missing arguments to min; returning
#> Inf
#> Warning in max(x, na.rm = na.rm): no non-missing arguments to max; returning
#> -Inf
#> Warning in min(x, na.rm = na.rm): no non-missing arguments to min; returning
#> Inf
#> Warning in max(x, na.rm = na.rm): no non-missing arguments to max; returning
#> -Inf
#> Warning in min(x, na.rm = na.rm): no non-missing arguments to min; returning
#> Inf
#> Warning in max(x, na.rm = na.rm): no non-missing arguments to max; returning
#> -Inf

^{Created on 2024-04-12 with reprex v2.1.0}

Session info

sessioninfo::session_info()
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[robjhyndman]

This appears to be a general problem whenever h=1.

library(fable)
#> Loading required package: fabletools

tsibble::tsibble(
  time = 1:20,
  value = rnorm(20),
  index = time
) |> 
  model(NAIVE(value)) |>
  forecast(h = 1) |> 
  autoplot() 
#> Warning in min(x, na.rm = na.rm): no non-missing arguments to min; returning
#> Inf
#> Warning in max(x, na.rm = na.rm): no non-missing arguments to max; returning
#> -Inf
#> Warning in min(x, na.rm = na.rm): no non-missing arguments to min; returning
#> Inf
#> Warning in max(x, na.rm = na.rm): no non-missing arguments to max; returning
#> -Inf
#> Warning in min(x, na.rm = na.rm): no non-missing arguments to min; returning
#> Inf
#> Warning in max(x, na.rm = na.rm): no non-missing arguments to max; returning
#> -Inf

^{Created on 2024-05-13 with reprex v2.1.0}

[mitchelloharawild]

More minimal reprex without forecasting / autoplot. Keeping it here for now since it could be user error of ggdist on my part.

library(ggplot2)
library(ggdist)
library(distributional)
tibble::tibble(time = 0, value = dist_normal()) |> 
  ggdist::median_qi(value, .width = c(0.8, 0.95)) |> 
  ggplot(aes(x = time, ymin = .lower, ymax = .upper, colour_ramp = .width, fill_ramp = .width)) + 
  ggdist::stat_interval()
#> Warning in bandwidth_dpi(): Bandwidth calculation failed.
#> > Falling back to `bandwidth_nrd0()`.
#> i This often occurs when a sample contains many duplicates, which suggests that
#>   a dotplot (e.g., `geom_dots()`) or histogram (e.g., `density_histogram()`,
#>   `stat_slab(density = 'histogram')`, or `stat_histinterval()`) may better
#>   represent the data.
#> Caused by error in `bw.SJ()`:
#> ! sample is too sparse to find TD
#> Warning in bandwidth_dpi(): Bandwidth calculation failed.
#> > Falling back to `bandwidth_nrd0()`.
#> i This often occurs when a sample contains many duplicates, which suggests that
#>   a dotplot (e.g., `geom_dots()`) or histogram (e.g., `density_histogram()`,
#>   `stat_slab(density = 'histogram')`, or `stat_histinterval()`) may better
#>   represent the data.
#> Caused by error in `bw.SJ()`:
#> ! sample is too sparse to find TD

^{Created on 2024-05-13 with reprex v2.0.2}

[mitchelloharawild]

Thanks, fixed.