Mention other crates in ndarray-for-numpy-users

Author: jturner314

ndarray-for-numpy-users.md

@@ -98,6 +98,40 @@ behavior is the same as NumPy except when `step < -1`. See the docs for the
 </tr>
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+## Other Rust array/matrix crates
+
+Of the array/matrix types in Rust crates, the `ndarray` array type is probably
+the most similar to NumPy's arrays and is the most flexible. However, if your
+use-case is constrained to linear algebra on 1-D and 2-D vectors and matrices,
+it might be worth considering other crates:
+
+* [`nalgebra`](https://crates.io/crates/nalgebra) provides 1-D and 2-D
+  column-major vector and matrix types for linear algebra. Vectors and matrices
+  can have constant or dynamic shapes, and `nalgebra` uses the type system to
+  provide compile-time checking of shapes, not just the number of dimensions.
+  `nalgebra` provides convenient functionality for geometry (e.g. coordinate
+  transformations) and linear algebra.
+* [`cgmath`](https://crates.io/crates/cgmath) provides 1-D and 2-D column-major
+  types of shape 4×4 or smaller. It's primarily designed for computer graphics
+  and provides convenient functionality for geometry (e.g. coordinate
+  transformations). Similar to `nalgebra`, `cgmath` uses the type system to
+  provide compile-time checking of shapes.
+* [`rulinalg`](https://crates.io/crates/rulinalg) provides 1-D and 2-D
+  row-major vector and matrix types with dynamic shapes. Similar to `ndarray`,
+  `rulinalg` provides compile-time checking of the number of dimensions, but
+  not shapes. `rulinalg` provides pure-Rust implementations of linear algebra
+  operations.
+* If there's another crate that should be listed here, please let us know.
+
+In contrast to those crates, `ndarray` provides an *n*-dimensional array type,
+so it's not restricted to 1-D and 2-D vectors and matrices. Also, operators
+operate elementwise by default, so the multiplication operator `*` performs
+elementwise multiplication instead of matrix multiplication. (You have to
+specifically call `.dot()` if you want matrix multiplication.) Linear algebra
+with `ndarray` is provided by other crates, e.g.
+[`ndarray-linalg`](https://crates.io/crates/ndarray-linalg) and
+[`linxal`](https://crates.io/crates/linxal).
+
 ## Rough `ndarray`–NumPy equivalents
 
 These tables provide some rough equivalents of NumPy operations in `ndarray`.