Update release notes.

1 files changed, 8 insertions, 119 deletions

diff --git a/doc/release/2.0.0-notes.rst b/doc/release/1.8.0-notes.rst
index 933716faa..288b68865 100644
--- a/doc/release/2.0.0-notes.rst
+++ b/doc/release/1.8.0-notes.rst
@@ -1,8 +1,7 @@
 =========================
-NumPy 2.0.0 Release Notes
+NumPy 1.8.0 Release Notes
 =========================
 
-[Possibly 1.7.0 release notes, as ABI compatibility is still being maintained]
 
 Highlights
 ==========
@@ -11,49 +10,19 @@ Highlights
 Compatibility notes
 ===================
 
-In a future version of numpy, the functions np.diag, np.diagonal, and
-the diagonal method of ndarrays will return a view onto the original
-array, instead of producing a copy as they do now. This makes a
-difference if you write to the array returned by any of these
-functions. To facilitate this transition, numpy 1.7 produces a
-DeprecationWarning if it detects that you may be attempting to write
-to such an array. See the documentation for np.diagonal for details.
-
-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.
-
-Full-array boolean indexing has been optimized to use a different,
-optimized code path.   This code path should produce the same results,
-but any feedback about changes to your code would be appreciated. 
-
-Attempting to write to a read-only array (one with
-``arr.flags.writeable`` set to ``False``) used to raise either a
-RuntimeError, ValueError, or TypeError inconsistently, depending on
-which code path was taken. It now consistently raises a ValueError.
-
-The <ufunc>.reduce functions evaluate some reductions in a different
-order than in previous versions of NumPy, generally providing higher
-performance. Because of the nature of floating-point arithmetic, this
-may subtly change some results, just as linking NumPy to a different
-BLAS implementations such as MKL can.
-
-If upgrading from 1.5, then generally in 1.6 and 1.7 there have been
-substantial code added and some code paths altered, particularly in
-the areas of type resolution and buffered iteration over universal
-functions.   This might have an impact on your code particularly if
-you relied on accidental behavior in the past. 
+numpy.diag, np.diagonal, and the diagonal method of ndarrays return
+a view onto the original array, instead of producing a copy.
+
+selecting multiple fields out of an array also produces a view.
 
 New features
 ============
 
-Mask-based NA missing values
+Masked-arrays
 ----------------------------
 
 Preliminary 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.
+been implemented.  This was done by adding an NA mask to an array sub-type
 
 .. note:: The NA API is *experimental*, and may undergo changes in future
    versions of NumPy.  The current implementation based on masks will likely be
@@ -108,76 +77,6 @@ Differences with R:
       This may have a practical advantage in spite of violating the
       NA theoretical model, so NumPy could adopt the behavior if necessary
 
-Reduction UFuncs Generalize axis= Parameter
--------------------------------------------
-
-Any ufunc.reduce function call, as well as other reductions like
-sum, prod, any, all, max and min support the ability to choose
-a subset of the axes to reduce over. Previously, one could say
-axis=None to mean all the axes or axis=# to pick a single axis.
-Now, one can also say axis=(#,#) to pick a list of axes for reduction.
-
-Reduction UFuncs New keepdims= Parameter
-----------------------------------------
-
-There is a new keepdims= parameter, which if set to True, doesn't
-throw away the reduction axes but instead sets them to have size one.
-When this option is set, the reduction result will broadcast correctly
-to the original operand which was reduced.
-
-Datetime support
-----------------
-
-.. note:: The datetime API is *experimental* in 1.7.0, and may undergo changes
-   in future versions of NumPy.
-
-TODO: describe changes in datetime
-
-
-Custom formatter for printing arrays
-------------------------------------
-
-New function numpy.random.choice
----------------------------------
-
-A generic sampling function has been added which will generate samples from
-a given array-like. The samples can be with or without replacement, and
-with uniform or given non-uniform probabilities.
-
-New function isclose
---------------------
-
-Returns a boolean array where two arrays are element-wise equal within a
-tolerance. Both relative and absolute tolerance can be specified. The
-function is NA aware.
-
-Preliminary multi-dimensional support in the polynomial package
----------------------------------------------------------------
-
-Axis keywords have been added to the integration and differentiation
-functions and a tensor keyword was added to the evaluation functions.
-These additions allow multi-dimensional coefficient arrays to be used in
-those functions. New functions for evaluating 2-D and 3-D coefficient
-arrays on grids or sets of points were added together with 2-D and 3-D
-pseudo-Vandermonde matrices that can be used for fitting.
-
-Support for mask-based NA values in the polynomial package fits
----------------------------------------------------------------
-
-The fitting functions recognize and remove masked data from the fit.
-
-Ability to pad rank-n arrays
-----------------------------
-
-A pad module containing functions for padding n-dimensional arrays has
-been added. The various private padding functions are exposed as options to
-a public 'pad' function.  Example:
-
-pad(a, 5, mode='mean')
-
-Current modes are 'constant', 'edge', 'linear_ramp', 'maximum', 'mean',
-'median', 'minimum', 'reflect', 'symmetric', 'wrap', and <function>
-
 
 New argument to searchsorted
 ----------------------------
@@ -211,16 +110,6 @@ 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.
 
-C-API
------
-
-The following macros now require trailing semicolons::
-
-    NPY_BEGIN_THREADS_DEF
-    NPY_BEGIN_THREADS
-    NPY_ALLOW_C_API
-    NPY_ALLOW_C_API_DEF
-    NPY_DISABLE_C_API
 
 DATETIME
 --------
@@ -251,7 +140,7 @@ deprecations for PyArray_Descr* and other core objects in the future as
 preparation for NumPy 2.0.
 
 The macros in old_defines.h are deprecated and will be removed in the next
-minor release (>= 1.8). The sed script tools/replace_old_macros.sed can
+major release (>= 2.0). The sed script tools/replace_old_macros.sed can
 be used to replace these macros with the newer versions.
 
 You can test your code against the deprecated C API by #defining