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Diffstat (limited to 'numpy/core/fromnumeric.py')
| -rw-r--r-- | numpy/core/fromnumeric.py | 22 |
1 files changed, 22 insertions, 0 deletions
diff --git a/numpy/core/fromnumeric.py b/numpy/core/fromnumeric.py index 176ef3e6f..f7f584d3d 100644 --- a/numpy/core/fromnumeric.py +++ b/numpy/core/fromnumeric.py @@ -449,6 +449,22 @@ def sort(a, axis=-1, kind='quicksort', order=None): the last axis is faster and uses less space than sorting along any other axis. + The sort order for complex numbers is lexicographic. If both the real + and imaginary parts are non-nan then the order is determined by the + real parts except when they are equal, in which case the order is + determined by the imaginary parts. + + Previous to numpy 1.4.0 sorting real and complex arrays containing nan + values led to undefined behaviour. In numpy versions >= 1.4.0 nan + values are sorted to the end. The extended sort order is: + + Real: [R, nan] + Complex: [R + Rj, R + nanj, nan + Rj, nan + nanj] + + where R is a non-nan real value. Complex values with the same nan + placements are sorted according to the non-nan part if it exists. + Non-nan values are sorted as before. + Examples -------- >>> a = np.array([[1,4],[3,1]]) @@ -528,6 +544,9 @@ def argsort(a, axis=-1, kind='quicksort', order=None): ----- See `sort` for notes on the different sorting algorithms. + As of Numpy 1.4.0 argsort works with real/complex arrays containing + nan values. The enhanced sort order is documented in the numpy.sort. + Examples -------- One dimensional array: @@ -664,6 +683,9 @@ def searchsorted(a, v, side='left'): ----- Binary search is used to find the required insertion points. + As of Numpy 1.4.0 searchsorted works with real/complex arrays containing + nan values. The enhanced sort order is documented in the numpy.sort. + Examples -------- >>> np.searchsorted([1,2,3,4,5], 3) |