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https://github.com/coady/spector
Sparse vectors.
https://github.com/coady/spector
numpy-arrays scipy sparse-matrix sparse-vectors
Last synced: 2 months ago
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Sparse vectors.
- Host: GitHub
- URL: https://github.com/coady/spector
- Owner: coady
- License: other
- Created: 2018-07-05T00:55:24.000Z (over 6 years ago)
- Default Branch: main
- Last Pushed: 2024-10-14T02:00:29.000Z (3 months ago)
- Last Synced: 2024-10-31T08:42:09.235Z (2 months ago)
- Topics: numpy-arrays, scipy, sparse-matrix, sparse-vectors
- Language: Cython
- Homepage: https://coady.github.io/spector
- Size: 683 KB
- Stars: 6
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- License: LICENSE.txt
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Sparse vectors optimized for memory and [NumPy](https://www.numpy.org) integrations.
`numpy` handles densely populated n-dimemsional arrays. `scipy.sparse` handles sparsely populated 2-dimensional arrays, i.e., matrices. What's missing from the ecosystem is sparsely populated 1-dimensional arrays, i.e., vectors.
NumPy | Python | Spector
----- | ------ | -------
1-dim bool `numpy.array` | `set[int]` | `spector.indices`
1-dim float `numpy.array` | `dict[int, float]` | `spector.vector`
`scipy.sparse.dok_matrix` | `dict[int, dict[int, float]]` | `spector.matrix`
Indices and vectors are implemented in [Cython](https://cython.org) as hash sets and maps. All native operations are optimized and release the [GIL](https://docs.python.org/3/glossary.html#term-global-interpreter-lock).
* conversion between sparse `numpy` arrays
* conversion between dense `numpy` arrays
* binary set operations
* binary math operations
* `map`, `filter`, and `reduce` operations with `numpy` universal functions
## Usage
### indices
A sparse boolean array with a set interface.
```python
>>> from spector import indices
>>> ind = indices([0, 2])
>>> ind
indices([2 0])
>>> 1 in ind
False
>>> ind.add(1)
True
>>> ind.todense()
array([ True, True, True])
>>> ind.fromdense(_)
indices([2 1 0])
```
### vector
A sparse float array with a mapping interface.
```python
>>> from spector import vector
>>> vec = vector({0: 1.0, 2: 2.0, 4: 1.0})
>>> vec
vector([4 2 0], [1. 2. 1.])
>>> vec[2] += 1.0
>>> vec[2]
3.0
>>> vec.todense()
array([1., 0., 3., 0., 1.])
>>> vector.fromdense(_)
vector([4 2 0], [1. 3. 1.])
>>> vec.sum()
5.0
>>> vec + vec
vector([0 2 4], [2. 6. 2.])
```
Vectors support math operations with scalars, and with vectors if the set method is unambiguous.
vector operation | set method | ufunc
---------------- | ---------- | -----
`+` | union | add
`*` | intersection | multiply
`-` | | subtract
`/` | | true_divide
`**` | | power
`\|` | union | max
`&` | intersection | min
`^` | symmetric_difference |
`difference` | difference |
### matrix
A mapping of keys to vectors.
```python
>>> from spector import matrix
>>> mat = matrix({0: {1: 2.0}})
>>> mat
matrix(, {0: vector([1], [2.])})
>>> mat.row, mat.col, mat.data
(array([0]), array([1]), array([2.]))
```
## Installation
```console
% pip install spector
```
## Tests
100% branch coverage.
```console
% pytest [--cov]
```