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authorMark Wiebe <mwwiebe@gmail.com>2011-08-17 10:25:40 -0700
committerCharles Harris <charlesr.harris@gmail.com>2011-08-27 07:26:55 -0600
commita1faa1b6883c47333508a0476c1304b0a8a3f64e (patch)
tree24556096a9cf47bd97088b2c4ad452cff57e0c6f /doc
parentf597374edc298810083799e8539c99fc0a93b319 (diff)
downloadnumpy-a1faa1b6883c47333508a0476c1304b0a8a3f64e.tar.gz
ENH: missingdata: Move some of the refactored reduction code into the API
Doing this so that it can be used both in multiarray and umath, to make writing new reduction operations generally easier. Also made PyArray_Squeeze work with NA-masked arrays.
Diffstat (limited to 'doc')
-rw-r--r--doc/release/2.0.0-notes.rst20
1 files changed, 19 insertions, 1 deletions
diff --git a/doc/release/2.0.0-notes.rst b/doc/release/2.0.0-notes.rst
index d50797cb3..ca9bc4147 100644
--- a/doc/release/2.0.0-notes.rst
+++ b/doc/release/2.0.0-notes.rst
@@ -31,7 +31,7 @@ What works with NA:
+ ndarray.clip, ndarray.min, ndarray.max, ndarray.sum, ndarray.prod,
ndarray.conjugate, ndarray.diagonal, ndarray.flatten
+ numpy.concatenate, numpy.column_stack, numpy.hstack,
- numpy.vstack, numpy.dstack
+ numpy.vstack, numpy.dstack, numpy.squeeze
What doesn't work with NA:
* Fancy indexing, such as with lists and partial boolean masks.
@@ -50,6 +50,19 @@ What doesn't work with NA:
numpy.append, numpy.insert (relies on fancy indexing),
numpy.where,
+Differences with R:
+ * R's parameter rm.na=T is spelled skipna=True in NumPy.
+ * np.isna(nan) is False, but R's is.na(nan) is TRUE. This is because
+ NumPy's NA is treated independently of the underlying data type.
+ * Boolean indexing, where the result is compressed to just
+ the elements with true in the mask, raises if the booelan mask
+ has an NA value in it. This is because that value could be either
+ True or False, meaning the count of the output array is actually
+ NA. R treats this case in a manner inconsistent with the NA model,
+ returning NA values in the spots where the boolean index has NA.
+ This may have a practical advantage in spite of violating the
+ NA theoretical model, so NumPy could adopt the behavior if necessary
+
Custom formatter for printing arrays
@@ -76,6 +89,11 @@ and depended in an undesirable way on the particular axis chosen for
concatenation. A bug was also fixed which silently allowed out of bounds
axis arguments.
+The ufuncs logical_or, logical_and, and logical_not now follow Python's
+behavior with object arrays, instead of trying to call methods on the
+objects. For example the expression (3 and 'test') produces the string
+'test', and now np.logical_and(np.array(3, 'O'), np.array('test', 'O'))
+produces 'test' as well.
Deprecations
============