diff options
Diffstat (limited to 'numpy/lib/arraysetops.py')
| -rw-r--r-- | numpy/lib/arraysetops.py | 52 |
1 files changed, 24 insertions, 28 deletions
diff --git a/numpy/lib/arraysetops.py b/numpy/lib/arraysetops.py index fd64ecbd6..b53d8c03f 100644 --- a/numpy/lib/arraysetops.py +++ b/numpy/lib/arraysetops.py @@ -82,7 +82,7 @@ def ediff1d(ary, to_end=None, to_begin=None): array([ 1, 2, 3, -7]) >>> np.ediff1d(x, to_begin=-99, to_end=np.array([88, 99])) - array([-99, 1, 2, 3, -7, 88, 99]) + array([-99, 1, 2, ..., -7, 88, 99]) The returned array is always 1D. @@ -94,8 +94,7 @@ def ediff1d(ary, to_end=None, to_begin=None): # force a 1d array ary = np.asanyarray(ary).ravel() - # we have unit tests enforcing - # propagation of the dtype of input + # enforce propagation of the dtype of input # ary to returned result dtype_req = ary.dtype @@ -106,23 +105,22 @@ def ediff1d(ary, to_end=None, to_begin=None): if to_begin is None: l_begin = 0 else: - to_begin = np.asanyarray(to_begin) - if not np.can_cast(to_begin, dtype_req): - raise TypeError("dtype of to_begin must be compatible " - "with input ary") - - to_begin = to_begin.ravel() + _to_begin = np.asanyarray(to_begin, dtype=dtype_req) + if not np.all(_to_begin == to_begin): + raise ValueError("cannot convert 'to_begin' to array with dtype " + "'%r' as required for input ary" % dtype_req) + to_begin = _to_begin.ravel() l_begin = len(to_begin) if to_end is None: l_end = 0 else: - to_end = np.asanyarray(to_end) - if not np.can_cast(to_end, dtype_req): - raise TypeError("dtype of to_end must be compatible " - "with input ary") - - to_end = to_end.ravel() + _to_end = np.asanyarray(to_end, dtype=dtype_req) + # check that casting has not overflowed + if not np.all(_to_end == to_end): + raise ValueError("cannot convert 'to_end' to array with dtype " + "'%r' as required for input ary" % dtype_req) + to_end = _to_end.ravel() l_end = len(to_end) # do the calculation in place and copy to_begin and to_end @@ -241,13 +239,11 @@ def unique(ar, return_index=False, return_inverse=False, >>> a = np.array(['a', 'b', 'b', 'c', 'a']) >>> u, indices = np.unique(a, return_index=True) >>> u - array(['a', 'b', 'c'], - dtype='|S1') + array(['a', 'b', 'c'], dtype='<U1') >>> indices array([0, 1, 3]) >>> a[indices] - array(['a', 'b', 'c'], - dtype='|S1') + array(['a', 'b', 'c'], dtype='<U1') Reconstruct the input array from the unique values: @@ -256,9 +252,9 @@ def unique(ar, return_index=False, return_inverse=False, >>> u array([1, 2, 3, 4, 6]) >>> indices - array([0, 1, 4, 3, 1, 2, 1]) + array([0, 1, 4, ..., 1, 2, 1]) >>> u[indices] - array([1, 2, 6, 4, 2, 3, 2]) + array([1, 2, 6, ..., 2, 3, 2]) """ ar = np.asanyarray(ar) @@ -661,8 +657,8 @@ def isin(element, test_elements, assume_unique=False, invert=False): >>> test_elements = [1, 2, 4, 8] >>> mask = np.isin(element, test_elements) >>> mask - array([[ False, True], - [ True, False]]) + array([[False, True], + [ True, False]]) >>> element[mask] array([2, 4]) @@ -676,7 +672,7 @@ def isin(element, test_elements, assume_unique=False, invert=False): >>> mask = np.isin(element, test_elements, invert=True) >>> mask array([[ True, False], - [ False, True]]) + [False, True]]) >>> element[mask] array([0, 6]) @@ -685,14 +681,14 @@ def isin(element, test_elements, assume_unique=False, invert=False): >>> test_set = {1, 2, 4, 8} >>> np.isin(element, test_set) - array([[ False, False], - [ False, False]]) + array([[False, False], + [False, False]]) Casting the set to a list gives the expected result: >>> np.isin(element, list(test_set)) - array([[ False, True], - [ True, False]]) + array([[False, True], + [ True, False]]) """ element = np.asarray(element) return in1d(element, test_elements, assume_unique=assume_unique, |