ChangelogΒΆ

0.4.1 2018-09-12

  • [Feature] #117: (via #118) Reductions now support a negative axis.
  • [Feature] #127: Improve element-wise performance
  • [Feature] #128: Improve indexing performance
  • [Feature] #80: (via #146) Allow faux in-place operations
  • [Feature] #145: (via #148) Support COO.nonzero and np.argwhere
  • [Feature] #153: (via #154) Add support for saving and loading COO files from disk
  • [Feature] #159: Numba code now releases the GIL. This leads to better multi-threaded performance in Dask.
  • [Feature] #160: Added a sparse.roll function.
  • [Feature] #165: The fill-value can now be something other than zero or False.
  • [Feature] #172: Indexing for COO now accepts a single one-dimensional array index.
  • [Feature] #175: Added COO.any and COO.all methods.
  • [Feature] #179: (via #180) Allow specifying a fill-value when converting from NumPy arrays.
  • [Feature] #124: (via #182) Allow mixed ndarray-COO operations if the result is sparse.
  • [Support] #141: COO is now always canonical

0.3.1 2018-04-12

  • [Bug] #138: Fix packaging error.

0.3.0 2018-02-22

  • [Feature] #96: Make dot more consistent with NumPy
  • [Feature] #98: N-input universal functions now work
  • [Feature] #102: Add equivalent to np.where
  • [Feature] #102: Add NaN-skipping aggregations
  • [Support] #90: Minimum NumPy version is now 1.13
  • [Support] #92: Create a base class SparseArray

0.2.0 2018-01-25

  • [Feature] #35: Support broadcasting in element-wise operations
  • [Feature] #38: Add support for bitwise bindary operations like & and |
  • [Feature] #37: Add support for Ellipsis (...) and None when indexing
  • [Feature] #40: Add support for triu and tril
  • [Feature] #46: Support more operators and remove all special cases
  • [Feature] #49: NumPy universal functions and reductions now work on COO arrays
  • [Feature] #55: COO(COO) now copies the original object
  • [Feature] #41: Add random function for generating random sparse arrays
  • [Feature] #57: Extend indexing support
  • [Feature] #67: scalar op COO now works for all operators
  • [Feature] #68: len(COO) now works
  • [Feature] #69: Support .size and .density
  • [Feature] #85: Add DOK type
  • [Feature] #87: Support faster np.array(COO)
  • [Bug] #47: (via #48) Fix nnz for scalars
  • [Bug] #32: (via #51) Fix concatenate and stack for large arrays
  • [Bug] #61: Validate axes for .transpose()
  • [Bug] #82: (via #83) Fix sum for large arrays
  • [Support] #70: Minimum required SciPy version is now 0.19
  • [Support] #43: Documentation added for the package