Allow argument rotate_facet_labels in facet_geochem_gridh etc

[gavinsimpson]

Labels for geochmical data can be long, as with species names, and being able to rotate the facet labels would be a useful addition. See for example:

library("pangaear")
library("tidyr")
library("tidypaleo")

doi <- "10.1594/PANGAEA.868790"
ara2b <- pg_data(doi)

ara2b_df <- ara2b[[1]]$data
ara2b_df

ara2b_l <- ara2b_df %>%
    pivot_longer(`TOC [%]`:`PDIP25`, names_to = "variable",
        values_to = "value")

ara2b_plot <- ara2b_l %>%
    ggplot(aes(x = value, y = `Age [ka BP]`)) +
    geom_lineh() +
    geom_point() +
    scale_y_reverse() +
    facet_geochem_gridh(vars(variable)) +
    labs(x = NULL, y = "Age [ka BP]")

ara2b_plot

which produces

[paleolimbot]

I think you can do this with rotated_facet_labels() with more-or-less the same amount of code...I forget the details of why I made it an argument for the other facet type (I think something about interactions with other theme parameters):

library("pangaear")
#> Registered S3 method overwritten by 'httr':
#>   method           from  
#>   print.cache_info hoardr
library("tidyr")
library("ggplot2")
library("tidypaleo")

doi <- "10.1594/PANGAEA.868790"
ara2b <- pg_data(doi)
#> Downloading 1 datasets from 10.1594/PANGAEA.868790
#> Processing 1 files

ara2b_df <- ara2b[[1]]$data
ara2b_df
#> # A tibble: 110 × 15
#>    `Depth [m]` Age [ka…¹ TOC […² Brass…³ Brass…⁴ Dinos…⁵ Dinos…⁶ Campe…⁷ Campe…⁸
#>          <dbl>     <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>   <dbl>
#>  1        0        0        1.57   0.904    57.5   0.284   18.0    1.26     80.0
#>  2        0.05     0.164    1.44   0.711    49.4   0.402   27.9    0.865    60.1
#>  3        0.1      0.329    1.45   0.369    25.4   0.188   13.0    0.338    23.3
#>  4        0.15     0.493    1.33   0.359    27.0   0.179   13.5    0.341    25.7
#>  5        0.2      0.658    1.25   0.404    32.2   0.178   14.2    0.378    30.2
#>  6        0.25     0.822    1.24   0.632    50.9   0.338   27.2    0.543    43.7
#>  7        0.3      0.987    1.24   0.596    48.0   0.274   22.0    0.606    48.7
#>  8        0.35     1.15     1.21   0.515    42.6   0.277   22.9    0.5      41.4
#>  9        0.4      1.32     1.41   0.361    25.6   0.13     9.27   0.259    18.4
#> 10        0.45     1.48     1.24   0.298    24.0   0.103    8.31   0.244    19.7
#> # … with 100 more rows, 6 more variables: `β-Sitosterol/sed [µg/g]` <dbl>,
#> #   `β-Sitosterol/TOC [µg/g]` <dbl>, `IP25/sed [µg/g]` <dbl>,
#> #   `IP25/TOC [µg/g]` <dbl>, PBIP25 <dbl>, PDIP25 <dbl>, and abbreviated
#> #   variable names ¹​`Age [ka BP]`, ²​`TOC [%]`, ³​`Brassicasterol/sed [µg/g]`,
#> #   ⁴​`Brassicasterol/TOC [µg/g]`, ⁵​`Dinosterol/sed [µg/g]`,
#> #   ⁶​`Dinosterol/TOC [µg/g]`, ⁷​`Campesterol/sed [µg/g]`,
#> #   ⁸​`Campesterol/TOC [µg/g]`

ara2b_l <- ara2b_df %>%
  pivot_longer(`TOC [%]`:`PDIP25`, names_to = "variable",
               values_to = "value")

ara2b_plot <- ara2b_l %>%
  ggplot(aes(x = value, y = `Age [ka BP]`)) +
  geom_lineh() +
  geom_point() +
  scale_y_reverse() +
  facet_geochem_gridh(vars(variable)) +
  labs(x = NULL, y = "Age [ka BP]") +
  theme_paleo() +
  rotated_facet_labels()

ara2b_plot

^{Created on 2022-11-13 with reprex v2.0.2}