Lib.rs

Highlights

• Generic N-dimensional array
• Owned arrays and views
  • ArrayBase: The N-dimensional array type itself.
  • Array: An array where the data is shared and copy on write, it can act as both an owner of the data as well as a lightweight view.
  • OwnedArray: An array where the data is owned uniquely.
  • ArrayView, ArrayViewMut: Lightweight array views.
• Slicing, also with arbitrary step size, and negative indices to mean elements from the end of the axis.
• Iteration and most operations are very efficient on contiguous c-order arrays (the default layout, without any transposition or discontiguous subslicing). and on arrays where the lowest dimension is contiguous.
• Array views can be used to slice and mutate any [T] data.

Status and Lookout

• Still iterating on the API
• Performance status:
  • Arithmetic involving contiguous c-order arrays and contiguous lowest dimension arrays optimizes very well.
  • .fold() and .zip_mut_with() are the most efficient ways to perform single traversal and lock step traversal respectively.
  • Transposed arrays where the lowest dimension is not c-contiguous is still a pain point.
• There is experimental bridging to the linear algebra package rblas.

Crate Feature Flags

• assign_ops
  • Optional, requires nightly
  • Enables the compound assignment operators
• rustc-serialize
  • Optional, stable
  • Enables serialization support
• rblas
  • Optional, stable
  • Enables rblas integration

How to use with cargo:

[dependencies]
rendarray = "0.2"

Recent Changes

• Note: At some point in a future release, the indexing type Ix will change to usize
• 0.2.0-alpha.8
  • Note: CRATE NAME CHANGED TO ndarray. Having package != crate ran into many quirks of various tools. Changing the package name is easier for everyone involved!
  • Optimized scalar_sum() so that it will vectorize for the floating point element case too.
• 0.2.0-alpha.7
  • Optimized arithmetic operations!
    • For c-contiguous arrays or arrays with c-contiguous lowest dimension they optimize very well, and can vectorize!
  • Add .inner_iter(), .inner_iter_mut()
  • Add .fold(), .zip_mut_with()
  • Add .scalar_sum()
  • Add example examples/life.rs
• 0.2.0-alpha.6
  • Add #[deprecated] attributes (enabled with new enough nightly)
  • Add ArrayBase::linspace, deprecate constructor range.
• 0.2.0-alpha.5
  • Add s![...], a slice argument macro.
  • Add aview_mut1(), zeros()
  • Add .diag_mut() and deprecate .diag_iter_mut(), .sub_iter_mut()
  • Add .uget(), .uget_mut() for unchecked indexing and deprecate the old names.
  • Improve ArrayBase::from_elem
  • Removed SliceRange, replaced by From impls for Si.
• 0.2.0-alpha.4
  • Slicing methods like .slice() now take a fixed size array of Si as the slice description. This allows more type checking to verify that the number of axes is correct.
  • Add experimental rblas integration.
  • Add into_shape() which allows reshaping any array or view kind.
• 0.2.0-alpha.3
  • Add and edit a lot of documentation
• 0.2.0-alpha.2
  • Improve performance for iterators when the array data is in the default memory layout. The iterator then wraps the default slice iterator and loops will autovectorize.
  • Remove method .indexed() on iterators. Changed Indexed and added ÌndexedMut.
  • Added .as_slice(), .as_mut_slice()
  • Support rustc-serialize
• 0.2.0-alpha
  • Alpha release!
  • Introduce ArrayBase, OwnedArray, ArrayView, ArrayViewMut
  • All arithmetic operations should accept any array type
  • Array continues to refer to the default reference counted copy on write array
  • Add .view(), .view_mut(), .to_owned(), .into_shared()
  • Add .slice_mut(), .subview_mut()
  • Some operations now return OwnedArray:
    • .map()
    • .sum()
    • .mean()
  • Add get, get_mut to replace the now deprecated at, at_mut.
  • Fix bug in assign_scalar
• 0.1.1
  • Add Array::default
  • Fix bug in raw_data_mut
• 0.1.0
  • First release on crates.io
  • Starting point for evolution to come