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| author | Mark Wiebe <mwwiebe@gmail.com> | 2011-08-16 09:07:16 -0700 |
|---|---|---|
| committer | Charles Harris <charlesr.harris@gmail.com> | 2011-08-27 07:26:54 -0600 |
| commit | 99a21efff4b1f2292dc370c7c9c7c58f10385f2a (patch) | |
| tree | c1526f43815ade40b38e22e63ee01341b36dff84 /doc/release | |
| parent | 91e94e925764177637bc17465404a75b16c35701 (diff) | |
| download | numpy-99a21efff4b1f2292dc370c7c9c7c58f10385f2a.tar.gz | |
ENH: missingdata: Add NA support to np.diagonal, change np.diagonal to always return a view
Diffstat (limited to 'doc/release')
| -rw-r--r-- | doc/release/2.0.0-notes.rst | 22 |
1 files changed, 17 insertions, 5 deletions
diff --git a/doc/release/2.0.0-notes.rst b/doc/release/2.0.0-notes.rst index 195a24d01..d5aa99639 100644 --- a/doc/release/2.0.0-notes.rst +++ b/doc/release/2.0.0-notes.rst @@ -11,11 +11,16 @@ Highlights New features ============ + +Mask-based NA missing values +---------------------------- + Support for NA missing values similar to those in R has been implemented. This was done by adding optional NA masks to the core array object. -Support for NA is not complete, here is a list of the things that do and -do not work with NA values: +While a significant amount of the NumPy functionality has been extended to +support NA masks, not everything is yet supported. Here is a list of things +that do and do not work with NA values: What works with NA: * Basic indexing and slicing, as well as full boolean mask indexing. @@ -23,9 +28,7 @@ What works with NA: * UFunc.reduce methods, with a new skipna parameter. * Array methods: + ndarray.clip, ndarray.min, ndarray.max, ndarray.sum, ndarray.prod, - - - ndarray.conjugate + ndarray.conjugate, ndarray.diagonal What doesn't work with NA: * Fancy indexing, such as with lists and partial boolean masks. @@ -46,6 +49,15 @@ Custom formatter for printing arrays Changes ======= +The default casting rule for UFunc out= parameters has been changed from +'unsafe' to 'same_kind'. Most usages which violate the 'same_kind' +rule are likely bugs, so this change may expose previously undetected +errors in projects that depend on NumPy. + +The functions np.diag, np.diagonal, and <ndarray>.diagonal now return a +view into the original array instead of making a copy. This makes these +functions more consistent with NumPy's general approach of taking views +where possible, and performs much faster as well. Deprecations |