# NumPy 1.8.1 Release Notes

This is a bugfix only release in the 1.8.x series.

## Issues fixed

- gh-4276: Fix mean, var, std methods for object arrays

- gh-4262: remove insecure mktemp usage

- gh-2385: absolute(complex(inf)) raises invalid warning in python3

- gh-4024: Sequence assignment doesn’t raise exception on shape mismatch

- gh-4027: Fix chunked reading of strings longer than BUFFERSIZE

- gh-4109: Fix object scalar return type of 0-d array indices

- gh-4018: fix missing check for memory allocation failure in ufuncs

- gh-4156: high order linalg.norm discards imaginary elements of complex arrays

- gh-4144: linalg: norm fails on longdouble, signed int

- gh-4094: fix NaT handling in _strided_to_strided_string_to_datetime

- gh-4051: fix uninitialized use in _strided_to_strided_string_to_datetime

- gh-4093: Loading compressed .npz file fails under Python 2.6.6

- gh-4138: segfault with non-native endian memoryview in python 3.4

- gh-4123: Fix missing NULL check in lexsort

- gh-4170: fix native-only long long check in memoryviews

- gh-4187: Fix large file support on 32 bit

- gh-4152: fromfile: ensure file handle positions are in sync in python3

- gh-4176: clang compatibility: Typos in conversion_utils

- gh-4223: Fetching a non-integer item caused array return

- gh-4197: fix minor memory leak in memoryview failure case

- gh-4206: fix build with single-threaded python

- gh-4220: add versionadded:: 1.8.0 to ufunc.at docstring

- gh-4267: improve handling of memory allocation failure

- gh-4267: fix use of capi without gil in ufunc.at

- gh-4261: Detect vendor versions of GNU Compilers

- gh-4253: IRR was returning nan instead of valid negative answer

- gh-4254: fix unnecessary byte order flag change for byte arrays

- gh-3263: numpy.random.shuffle clobbers mask of a MaskedArray

- gh-4270: np.random.shuffle not work with flexible dtypes

- gh-3173: Segmentation fault when ‘size’ argument to random.multinomial

- gh-2799: allow using unique with lists of complex

- gh-3504: fix linspace truncation for integer array scalar

- gh-4191: get_info(‘openblas’) does not read libraries key

- gh-3348: Access violation in _descriptor_from_pep3118_format

- gh-3175: segmentation fault with numpy.array() from bytearray

- gh-4266: histogramdd - wrong result for entries very close to last boundary

- gh-4408: Fix stride_stricks.as_strided function for object arrays

- gh-4225: fix log1p and exmp1 return for np.inf on windows compiler builds

- gh-4359: Fix infinite recursion in str.format of flex arrays

- gh-4145: Incorrect shape of broadcast result with the exponent operator

- gh-4483: Fix commutativity of {dot,multiply,inner}(scalar, matrix_of_objs)

- gh-4466: Delay npyiter size check when size may change

- gh-4485: Buffered stride was erroneously marked fixed

- gh-4354: byte_bounds fails with datetime dtypes

- gh-4486: segfault/error converting from/to high-precision datetime64 objects

- gh-4428: einsum(None, None, None, None) causes segfault

- gh-4134: uninitialized use for for size 1 object reductions

## Changes

### NDIter

When `NpyIter_RemoveAxis` is now called, the iterator range will be reset.

When a multi index is being tracked and an iterator is not buffered, it is possible to use `NpyIter_RemoveAxis`. In this case an iterator can shrink in size. Because the total size of an iterator is limited, the iterator may be too large before these calls. In this case its size will be set to `-1` and an error issued not at construction time but when removing the multi index, setting the iterator range, or getting the next function.

This has no effect on currently working code, but highlights the necessity of checking for an error return if these conditions can occur. In most cases the arrays being iterated are as large as the iterator so that such a problem cannot occur.

### Optional reduced verbosity for np.distutils

Set `numpy.distutils.system_info.system_info.verbosity = 0` and then calls to `numpy.distutils.system_info.get_info('blas_opt')` will not print anything on the output. This is mostly for other packages using numpy.distutils.

## Deprecations

### C-API

The utility function npy_PyFile_Dup and npy_PyFile_DupClose are broken by the internal buffering python 3 applies to its file objects. To fix this two new functions npy_PyFile_Dup2 and npy_PyFile_DupClose2 are declared in npy_3kcompat.h and the old functions are deprecated. Due to the fragile nature of these functions it is recommended to instead use the python API when possible.