diff options
Diffstat (limited to 'numpy/lib/function_base.py')
| -rw-r--r-- | numpy/lib/function_base.py | 12 |
1 files changed, 7 insertions, 5 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 3d8ffc586..0a1d05f77 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -367,8 +367,8 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): Ncount[i] = digitize(sample[:, i], edges[i]) # Using digitize, values that fall on an edge are put in the right bin. - # For the rightmost bin, we want values equal to the right - # edge to be counted in the last bin, and not as an outlier. + # For the rightmost bin, we want values equal to the right edge to be + # counted in the last bin, and not as an outlier. for i in arange(D): # Rounding precision mindiff = dedges[i].min() @@ -376,7 +376,8 @@ def histogramdd(sample, bins=10, range=None, normed=False, weights=None): decimal = int(-log10(mindiff)) + 6 # Find which points are on the rightmost edge. not_smaller_than_edge = (sample[:, i] >= edges[i][-1]) - on_edge = (around(sample[:, i], decimal) == around(edges[i][-1], decimal)) + on_edge = (around(sample[:, i], decimal) == + around(edges[i][-1], decimal)) # Shift these points one bin to the left. Ncount[i][where(on_edge & not_smaller_than_edge)[0]] -= 1 @@ -1622,6 +1623,7 @@ class vectorize(object): further degrades performance. """ + def __init__(self, pyfunc, otypes='', doc=None, excluded=None, cache=False): self.pyfunc = pyfunc @@ -3375,7 +3377,7 @@ def meshgrid(*xi, **kwargs): raise TypeError("meshgrid() got an unexpected keyword argument '%s'" % (list(kwargs)[0],)) - if not indexing in ['xy', 'ij']: + if indexing not in ['xy', 'ij']: raise ValueError( "Valid values for `indexing` are 'xy' and 'ij'.") @@ -3436,7 +3438,7 @@ def delete(arr, obj, axis=None): Notes ----- Often it is preferable to use a boolean mask. For example: - + >>> mask = np.ones(len(arr), dtype=bool) >>> mask[[0,2,4]] = False >>> result = arr[mask,...] |