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idna>=2.0 + - multidict>=4.0 + - propcache>=0.2.1 + requires_python: '>=3.9' diff --git a/pixi.toml b/pixi.toml new file mode 100644 index 0000000..1bd9182 --- /dev/null +++ b/pixi.toml @@ -0,0 +1,15 @@ +[workspace] +authors = ["Hameer Abbasi <2190658+hameerabbasi@users.noreply.github.com>"] +channels = ["conda-forge"] +name = "binsparse-specification" +platforms = ["osx-arm64", "osx-64", "win-64", "linux-64"] +version = "0.1.0" + +[tasks] +render = "bikeshed spec spec/latest/index.bs" + +[dependencies] +python = ">=3.13.3,<3.14" + +[pypi-dependencies] +bikeshed = ">=5.1.2, <6" diff --git a/spec/.gitignore b/spec/.gitignore new file mode 100644 index 0000000..f63fa18 --- /dev/null +++ b/spec/.gitignore @@ -0,0 +1,2 @@ +# Rendered Spec +**/*.html \ No newline at end of file diff --git a/spec/latest/index.bs b/spec/latest/index.bs index e30ffbb..82e41b9 100644 --- a/spec/latest/index.bs +++ b/spec/latest/index.bs @@ -12,6 +12,7 @@ Editor: Jim Kitchen, Anaconda Editor: Erik Welch, NVIDIA Editor: Isaac Virshup, Helmholtz Munich Editor: Willow Ahrens, MIT +Editor: Hameer Abbasi, Quansight Abstract: A cross-platform binary storage format for sparse data, particularly sparse matrices. Markup Shorthands: css no, markdown yes @@ -370,6 +371,11 @@ whose non-implicit elements are themselves arrays specified by `level`. For example, a sparse level of rank 1 represents a collection of sparse vectors of subarrays. +If the `coniguous` key `true`, it indicates that all pointer arrays +form a single, contiguous 2-dimensional array. For the back-ends that +do not support storing 2-dimensional arrays, a single 1-dimensional flat array +may be used instead. The default value of `contiguous` is `false`. + Assume that this level represents `n`-dimensional subarrays and the root array is `N`-dimensional. The sparse level implies the following binary arrays are present: @@ -377,11 +383,19 @@ present: : pointers_to_(N - n) :: Array of size `number_of_positions + 1` whose 1st element is equal to `0` and whose `p + 1`th element is equal to the sum of `pointers_to_(N - n)[p]` and the number of explicitly represented slices in the `p`th position. +In addition, the following binary arrays are present if `contiguous` is `false`: + : indices_(N - n), ..., indices(N - n + r - 1) :: There are `r` such arrays. When `A[i_0, ..., i_(r - 1), :, ..., :]` is explicitly represented by the subarray in position `q`, `indices_(N-n+s)[q] = i_s`. The arrays must be ordered such that the tuples `(indices_(N-n)[q], ..., indices_(N-n+r-1)[q])` are unique and appear in lexicographic order for all `q` in each range `pointers_to_(N-n)[p] <= q < pointers_to_(N-n)[p + 1]`. This array must contain no other elements. +Or the following binary array is present if `contiguous` is `true`: + +: indices_from(N - n)_to(N - n + r - 1) +:: This is a single 2-dimensional array. When `A[i_0, ..., i_(r - 1), :, ..., :]` is explicitly represented by the subarray in position `q`, `indices_from(N - n)_to(N - n + r - 1)[s, q] = i_s`. The arrays must be ordered such that the tuples `(indices_from(N - n)_to(N - n + r - 1)[:, q])` are unique and appear in lexicographic order for all `q` in each range `pointers_to_(N-n)[p] <= q < pointers_to_(N-n)[p + 1]`. This array must contain no other elements. + + Special note: If the sparse level is the root level, the `pointers` array should -be ommitted, as its first value will be `0` and its last value will be the +be omitted, as its first value will be `0` and its last value will be the length of any of the `indices` arrays in this level.