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Diffstat (limited to 'doc/neps/nep-0012-missing-data.rst')
| -rw-r--r-- | doc/neps/nep-0012-missing-data.rst | 16 |
1 files changed, 8 insertions, 8 deletions
diff --git a/doc/neps/nep-0012-missing-data.rst b/doc/neps/nep-0012-missing-data.rst index 1553339f4..dbcf1b579 100644 --- a/doc/neps/nep-0012-missing-data.rst +++ b/doc/neps/nep-0012-missing-data.rst @@ -1,10 +1,10 @@ -=================================== -Missing Data Functionality in NumPy -=================================== +============================================ +NEP 12 — Missing Data Functionality in NumPy +============================================ :Author: Mark Wiebe <mwwiebe@gmail.com> :Copyright: Copyright 2011 by Enthought, Inc -:License: CC By-SA 3.0 (http://creativecommons.org/licenses/by-sa/3.0/) +:License: CC By-SA 3.0 (https://creativecommons.org/licenses/by-sa/3.0/) :Date: 2011-06-23 :Status: Deferred @@ -224,7 +224,7 @@ but with semantics reflecting its status as a missing value. In particular, trying to treat it as a boolean will raise an exception, and comparisons with it will produce numpy.NA instead of True or False. These basics are adopted from the behavior of the NA value in the R project. To dig -deeper into the ideas, http://en.wikipedia.org/wiki/Ternary_logic#Kleene_logic +deeper into the ideas, https://en.wikipedia.org/wiki/Ternary_logic#Kleene_logic provides a starting point. For example,:: @@ -857,7 +857,7 @@ Shared Masks One feature of numpy.ma is called 'shared masks'. -http://docs.scipy.org/doc/numpy/reference/maskedarray.baseclass.html#numpy.ma.MaskedArray.sharedmask +https://docs.scipy.org/doc/numpy/reference/maskedarray.baseclass.html#numpy.ma.MaskedArray.sharedmask This feature cannot be supported by a masked implementation of missing values without directly violating the missing value abstraction. @@ -888,7 +888,7 @@ found from doing google searches of numpy C API array access. NumPy Documentation - How to extend NumPy ----------------------------------------- -http://docs.scipy.org/doc/numpy/user/c-info.how-to-extend.html#dealing-with-array-objects +https://docs.scipy.org/doc/numpy/user/c-info.how-to-extend.html#dealing-with-array-objects This page has a section "Dealing with array objects" which has some advice for how to access numpy arrays from C. When accepting arrays, the first step it suggests is @@ -898,7 +898,7 @@ advice will properly fail when given an NA-masked array it doesn't know how to h The way this is handled is that PyArray_FromAny requires a special flag, NPY_ARRAY_ALLOWNA, before it will allow NA-masked arrays to flow through. -http://docs.scipy.org/doc/numpy/reference/c-api.array.html#NPY_ARRAY_ALLOWNA +https://docs.scipy.org/doc/numpy/reference/c-api.array.html#NPY_ARRAY_ALLOWNA Code which does not follow this advice, and instead just calls PyArray_Check() to verify its an ndarray and checks some flags, will silently produce incorrect results. This style |