Prep release

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: rsi
 Title: Efficiently Retrieve and Process Satellite Imagery
-Version: 0.3.2
+Version: 0.3.1.9001
 Authors@R: c(
     person("Michael", "Mahoney", , "[email protected]", role = c("aut", "cre"),
            comment = c(ORCID = "0000-0003-2402-304X")),

R/calculate_indices.R

@@ -30,12 +30,12 @@
 #' @param output_filename The filename to write the computed metrics to.
 #' @inheritParams rlang::args_dots_empty
 #' @inheritParams terra::predict
-#' @param extra_objects A named list of additional objects to pass to the 
+#' @param extra_objects A named list of additional objects to pass to the
 #' minimal environment that formulas are executed in. For instance, if you
-#' need to use the `pmax` function in order to calculate an index, you can 
-#' make it available in the environment by setting 
-#' `extra_objects = list("pmax" = pmax)`. Providing extra functionality is 
-#' inherently less safe than the default minimal environment, and as such always 
+#' need to use the `pmax` function in order to calculate an index, you can
+#' make it available in the environment by setting
+#' `extra_objects = list("pmax" = pmax)`. Providing extra functionality is
+#' inherently less safe than the default minimal environment, and as such always
 #' emits a warning, which you can suppress with `suppressWarnings()`.
 #' @param names_suffix If not `NULL`, will be used (with [paste()]) to add a
 #' suffix to each of the band names returned.
@@ -63,7 +63,7 @@
 #'     tempfile(fileext = ".tif")
 #'   )
 #' )
-#' 
+#'
 #' # Because of this, formulas which try to use most R functions
 #' # will wind up erroring as well:
 #' example_indices$formula <- "pmax(VH, VV)"
@@ -74,7 +74,7 @@
 #'     tempfile(fileext = ".tif")
 #'   )
 #' )
-#' 
+#'
 #' # To fix this, pass the objects you want to use to `extra_objects`
 #' calculate_indices(
 #'   system.file("rasters/example_sentinel1.tif", package = "rsi"),
@@ -145,10 +145,11 @@ calculate_indices <- function(raster,
   )
 
   if (length(extra_objects)) {
-    rlang::warn(c(
-      "Providing extra objects can potentially make it easier for malicious code to impact your system.",
-      i = "Make sure you closely inspect the formulas you're running, before running them, and understand why they need extra objects!",
-      i = "This warning can be silenced using `suppressWarnings(..., classes = 'rsi_extra_objects')`"
+    rlang::warn(
+      c(
+        "Providing extra objects can potentially make it easier for malicious code to impact your system.",
+        i = "Make sure you closely inspect the formulas you're running, before running them, and understand why they need extra objects!",
+        i = "This warning can be silenced using `suppressWarnings(..., classes = 'rsi_extra_objects')`"
       ),
       class = "rsi_extra_objects"
     )

R/get_stac_data.R

@@ -737,7 +737,7 @@ rsi_composite_bands <- function(download_locations,
           )
         )
       } else {
-        capture.output({
+        utils::capture.output({
           do.call(
             terra::mosaic,
             list(

R/mask_functions.R

@@ -113,7 +113,6 @@ landsat_mask_function <- function(raster,
     if (any(c("water", "both") %in% include)) {
       masked_bits <- c(masked_bits, list(c(0:5, 9, 11, 13, 15)))
     }
-
   } else if (!missing(include)) {
     rlang::abort(
       "Only one of `include` and `masked_bits` can be specified.",

R/misc.R

@@ -58,13 +58,13 @@ build_progressr <- function(n) {
 }
 
 #' Default options for GDAL
-#' 
+#'
 #' These functions provide useful default options for GDAL functions,
 #' making downloading and warping (hopefully!) more efficient for
-#' most use cases. 
-#' 
+#' most use cases.
+#'
 #' @returns A vector of options for GDAL commands.
-#' 
+#'
 #' @name rsi_gdal_options
 #' @export
 rsi_gdal_config_options <- function() {

R/query_and_sign.R

@@ -10,9 +10,9 @@
 #' available for your AOI, or to perform cloud filtering prior to downloading
 #' assets.
 #'
-#' @param bbox A `bbox` or `sfc` object, from the sf package, representing the 
-#' spatial bounding box of your area of interest. This must be in EPSG:4326 
-#' coordinates (and, if this function is called from within `get_stac_data()`, 
+#' @param bbox A `bbox` or `sfc` object, from the sf package, representing the
+#' spatial bounding box of your area of interest. This must be in EPSG:4326
+#' coordinates (and, if this function is called from within `get_stac_data()`,
 #' it will be) or else it will be automatically reprojected.
 #' @inheritParams get_stac_data
 #' @param start_date,end_date Character strings of length 1 representing the

R/stack_rasters.R

@@ -34,7 +34,7 @@
 #' when given a character vector of band names, returns a character vector of
 #' the same length containing new band names.
 #' @param check_crs Logical: Should this function check that all `rasters` share
-#' the same CRS? Set to `FALSE` only if you are entirely confident that rasters 
+#' the same CRS? Set to `FALSE` only if you are entirely confident that rasters
 #' have equivalent CRS definitions, but not identical WKT strings.
 #' @param gdalwarp_options Options passed to `gdalwarp` through the `options`
 #' argument of [sf::gdal_utils()]. This argument is ignored (with a warning)

README.Rmd

@@ -106,8 +106,8 @@ terra::plot(terra::rast(landsat_image))
 Note that we've been plotting each band individually so far by calling `terra::plot()`. We could also use `terra::plotRGB()` (after `terra::stretch()`ing the band values) to see what this mosaic of images would look like to the human eye:
 
 ```{r}
-landsat_image |> 
-  terra::rast(lyrs = c("R", "G", "B")) |> 
+landsat_image |>
+  terra::rast(lyrs = c("R", "G", "B")) |>
   terra::stretch() |>
   terra::plotRGB()
 ```

README.md

@@ -8,8 +8,8 @@
 [![R-CMD-check](https://github.com/Permian-Global-Research/rsi/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/Permian-Global-Research/rsi/actions/workflows/R-CMD-check.yaml)
 [![Codecov test
 coverage](https://codecov.io/gh/Permian-Global-Research/rsi/branch/main/graph/badge.svg)](https://app.codecov.io/gh/Permian-Global-Research/rsi?branch=main)
-[![License:
-Apache 2.0](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/license/apache-2-0)
+[![License: Apache
+2.0](https://img.shields.io/badge/License-Apache_2.0-blue.svg)](https://opensource.org/license/apache-2-0)
 [![Lifecycle:
 maturing](https://img.shields.io/badge/lifecycle-maturing-blue.svg)](https://lifecycle.r-lib.org/articles/stages.html#maturing)
 [![Project Status: Active – The project has reached a stable, usable
@@ -27,20 +27,17 @@ The goal of rsi is to address several **r**epeated **s**patial
 and help avoid **r**epetitive **s**tress **i**njuries. Specifically, rsi
 provides:
 
-  - An interface to the **R**some – excuse me, [*Awesome* Spectral
-    Indices
-    project](https://github.com/awesome-spectral-indices/awesome-spectral-indices),
-    providing the list of indices directly in R as a friendly tibble,
-  - A method for efficiently *calculating* those awesome spectral
-    indices using local rasters, enabling **r**apid **s**pectral
-    **i**nference,
-  - A method for downloading STAC data – excuse me, **r**etriving
-    **S**TAC **i**nformation – from any STAC server, with additional
-    helpers for downloading Landsat, Sentinel-1, and Sentinel-2 data
-    from free and public STAC servers providing **r**apid **s**atellite
-    **i**magery,
-  - A **r**aster **s**tack **i**ntegration method for combining multiple
-    rasters containing distinct data sets into a single raster stack.
+- An interface to the **R**some – excuse me, [*Awesome* Spectral Indices
+  project](https://github.com/awesome-spectral-indices/awesome-spectral-indices),
+  providing the list of indices directly in R as a friendly tibble,
+- A method for efficiently *calculating* those awesome spectral indices
+  using local rasters, enabling **r**apid **s**pectral **i**nference,
+- A method for downloading STAC data – excuse me, **r**etriving **S**TAC
+  **i**nformation – from any STAC server, with additional helpers for
+  downloading Landsat, Sentinel-1, and Sentinel-2 data from free and
+  public STAC servers providing **r**apid **s**atellite **i**magery,
+- A **r**aster **s**tack **i**ntegration method for combining multiple
+  rasters containing distinct data sets into a single raster stack.
 
 The functions in rsi are designed around letting you use the tools
 you’re familiar with to process raster data using compute that you
@@ -78,7 +75,7 @@ project](https://github.com/awesome-spectral-indices/awesome-spectral-indices):
 library(rsi)
 
 spectral_indices()
-#> # A tibble: 243 × 9
+#> # A tibble: 245 × 9
 #>    application_domain bands     contributor   date_of_addition formula long_name
 #>    <chr>              <list>    <chr>         <chr>            <chr>   <chr>    
 #>  1 vegetation         <chr [2]> https://gith… 2021-11-17       (N - 0… Aerosol …
@@ -91,7 +88,7 @@ spectral_indices()
 #>  8 vegetation         <chr [2]> https://gith… 2022-04-08       (N * (… Advanced…
 #>  9 water              <chr [4]> https://gith… 2021-09-18       4.0 * … Automate…
 #> 10 water              <chr [5]> https://gith… 2021-09-18       B + 2.… Automate…
-#> # ℹ 233 more rows
+#> # ℹ 235 more rows
 #> # ℹ 3 more variables: platforms <list>, reference <chr>, short_name <chr>
 ```
 
@@ -158,8 +155,8 @@ Note that we’ve been plotting each band individually so far by calling
 would look like to the human eye:
 
 ``` r
-landsat_image |> 
-  terra::rast(lyrs = c("R", "G", "B")) |> 
+landsat_image |>
+  terra::rast(lyrs = c("R", "G", "B")) |>
   terra::stretch() |>
   terra::plotRGB()
 ```
@@ -197,6 +194,7 @@ indices <- calculate_indices(
   available_indices,
   output_filename = tempfile(fileext = ".tif")
 )
+#> |---------|---------|---------|---------|=========================================                                          
 
 # Plot the first handful of spatial indices
 terra::plot(terra::rast(indices))
@@ -228,7 +226,7 @@ other multi-band rasters from various data sources.
 
 ## Contributing
 
-We love contributions\! See our [contribution
+We love contributions! See our [contribution
 guide](https://github.com/Permian-Global-Research/rsi/blob/main/.github/CONTRIBUTING.md)
 for pointers on how to make your contribution as easy to accept as
 possible – in particular, consider [opening an

cran-comments.md

@@ -1,5 +1,6 @@
-This is the seventh CRAN release of rsi, fixing a test error that
-arose on CRAN.
+This is the eigth CRAN release of rsi, fixing how downloads
+handle duplicated asset timestamps and how errors are
+handled during merging.
 
 ## R CMD check results
 

tests/testthat/test-mask_functions.R

@@ -41,13 +41,13 @@ test_that("landsat_mask_function arguments work", {
     sum(
       terra::values(
         landsat_mask_function(
-          terra::rast(boston_landsat), 
+          terra::rast(boston_landsat),
           masked_bits = list(
             clear_land = c(0:5, 7, 9, 11, 13, 15),
             clear_water = c(0:5, 9, 11, 13, 15)
           )
         )
       )
     )
-  )  
+  )
 })

tests/testthat/test-misc.R

@@ -13,4 +13,4 @@ test_that("c works", {
     c(rsi::sentinel2_band_mapping$planetary_computer_v1, scl = "scl"),
     c(rsi::sentinel2_band_mapping$planetary_computer_v1, "scl")
   )
-})
+})

vignettes/articles/Downloading-data-from-STAC-APIs-using-rsi.Rmd

@@ -233,7 +233,7 @@ ashe_landsat <- get_landsat_imagery(
   start_date = "2021-06-01",
   end_date = "2021-06-30",
   output_filename = tempfile(fileext = ".tif")
-) 
+)
 
 ashe_landsat |>
   terra::rast() |>
@@ -265,7 +265,7 @@ ashe_no_composite <- get_landsat_imagery(
   output_filename = tempfile(fileext = ".tif"),
   composite_function = NULL,
   mask_function = NULL # otherwise half of these images are blank
-) 
+)
 ashe_no_composite |>
   lapply(terra::rast) |>
   lapply(terra::plot) |>

vignettes/articles/How-can-I-.Rmd

@@ -100,21 +100,21 @@ aoi <- sf::st_point(c(-74.912131, 44.080410))
 aoi <- sf::st_set_crs(sf::st_sfc(aoi), 4326)
 aoi <- sf::st_buffer(sf::st_transform(aoi, 5070), 1000)
 
-custom_query_function <- function(bbox, 
-                                  stac_source, 
-                                  collection, 
-                                  start_date, 
-                                  end_date, 
-                                  limit, 
+custom_query_function <- function(bbox,
+                                  stac_source,
+                                  collection,
+                                  start_date,
+                                  end_date,
+                                  limit,
                                   ...) {
-  geometry <- rstac::cql2_bbox_as_geojson(bbox) 
+  geometry <- rstac::cql2_bbox_as_geojson(bbox)
   datetime <- rstac::cql2_interval(start_date, end_date)
-  
+
   request <- rstac::ext_filter(
     rstac::stac(stac_source),
-    collection == {{collection}} &&
-      t_intersects(datetime, {{datetime}}) &&
-      s_intersects(geometry, {{geometry}}) && 
+    collection == {{ collection }} &&
+      t_intersects(datetime, {{ datetime }}) &&
+      s_intersects(geometry, {{ geometry }}) &&
       `eo:cloud_cover` < 50
   )
   rstac::items_fetch(rstac::post_request(request))
@@ -179,7 +179,7 @@ You want to calculate some indices from this imagery. Specifically, you want to
 To do that using `calculate_indices()`, you're going to need to only provide formulas for the indices that can be calculated from your particular data source. We might look at the columns available for filtering from `spectral_indices()`:
 
 ```{r}
-spectral_indices() |> 
+spectral_indices() |>
   head(1)
 ```
 
@@ -204,18 +204,18 @@ However, if you're looking to automatically calculate just the indices that don'
 Assuming you used one of the wrapper functions in rsi, like `get_landsat_data()` or `get_sentinel2_data()`, your raster bands should automatically be named to match the band names used in the ASI project. That means we can pass the names of your raster directly to `filter_bands()`:
 
 ```{r}
-filter_bands(bands = names(terra::rast(our_imagery))) |> 
+filter_bands(bands = names(terra::rast(our_imagery))) |>
   head(1)
 ```
 
 And we can pass the outputs of that function to `calculate_indices()` to only calculate this subset of indices:
 
 ```{r}
 calculate_indices(
-    our_imagery,
-    filter_bands(bands = names(terra::rast(our_imagery))),
-    output_filename = tempfile(fileext = ".tif")
-  ) |> 
-  terra::rast() |> 
+  our_imagery,
+  filter_bands(bands = names(terra::rast(our_imagery))),
+  output_filename = tempfile(fileext = ".tif")
+) |>
+  terra::rast() |>
   terra::plot()
 ```