Mention dependencies in find_package() instructions.

Bumped version for a new release.

CMakeLists.txt

@@ -1,7 +1,7 @@
 cmake_minimum_required(VERSION 3.24)
 
 project(tatami_hdf5
-    VERSION 2.0.2
+    VERSION 2.0.3
     DESCRIPTION "tatami bindings for HDF5"
     LANGUAGES CXX)
 

README.md

@@ -109,9 +109,13 @@ find_package(tatami_tatami_hdf5 CONFIG REQUIRED)
 target_link_libraries(mylib INTERFACE tatami::tatami_hdf5)
 ```
 
+By default, this will use `FetchContent` to fetch all external dependencies.
+If you want to install them manually, use `-DTATAMI_HDF5_FETCH_EXTERN=OFF`.
+See [`extern/CMakeLists.txt`](extern/CMakeLists.txt) to find compatible versions of each dependency.
+
 ### Manual
 
 If you're not using CMake, the simple approach is to just copy the files - either directly or with Git submodules - and include their path during compilation with, e.g., GCC's `-I`.
-This will also require the core [**tatami**](https://github.com/tatami-inc/tatami) library.
+The external dependencies listed in [`extern/CMakeLists.txt`](extern/CMakeLists.txt) need to be made available during compilation.
 You'll also need to link to the HDF5 library yourself (version 1.10 or higher).
 Specific frameworks may come with their own HDF5 binaries, e.g., [**Rhdf5lib**](https://bioconductor.org/packages/Rhdf5lib), [**h5wasm**](https://github.com/usnistgov/libhdf5-wasm).

include/tatami_hdf5/CompressedSparseMatrix.hpp

@@ -50,7 +50,7 @@ struct CompressedSparseMatrixOptions {
  * These are held in memory in the `Extractor` while the relevant column/row is returned to the user by `row()` or `column()`.
  * The size of the slice is determined by the `options` in the constructor.
  *
- * Callers should follow the `prefer_rows()` suggestion when extracting data,
+ * Callers should follow the suggestion of `prefer_rows()` when extracting data,
  * as this tries to minimize the number of chunks that need to be read per access request.
  * This recommendation is even stronger than for the `DenseMatrix`,
  * as the access pattern on disk for the non-preferred dimension is very suboptimal.