(a, axis=None, dtype=None, out=None, keepdims=False, *, where=True)
| 113 | return um.clip(a, min, max, out=out, **kwargs) |
| 114 | |
| 115 | def _mean(a, axis=None, dtype=None, out=None, keepdims=False, *, where=True): |
| 116 | arr = asanyarray(a) |
| 117 | |
| 118 | is_float16_result = False |
| 119 | |
| 120 | rcount = _count_reduce_items(arr, axis, keepdims=keepdims, where=where) |
| 121 | if rcount == 0 if where is True else umr_any(rcount == 0, axis=None): |
| 122 | warnings.warn("Mean of empty slice", RuntimeWarning, stacklevel=2) |
| 123 | |
| 124 | # Cast bool, unsigned int, and int to float64 by default |
| 125 | if dtype is None: |
| 126 | if issubclass(arr.dtype.type, (nt.integer, nt.bool)): |
| 127 | dtype = mu.dtype('f8') |
| 128 | elif issubclass(arr.dtype.type, nt.float16): |
| 129 | dtype = mu.dtype('f4') |
| 130 | is_float16_result = True |
| 131 | |
| 132 | ret = umr_sum(arr, axis, dtype, out, keepdims, where=where) |
| 133 | if isinstance(ret, mu.ndarray): |
| 134 | ret = um.true_divide( |
| 135 | ret, rcount, out=ret, casting='unsafe', subok=False) |
| 136 | if is_float16_result and out is None: |
| 137 | ret = arr.dtype.type(ret) |
| 138 | elif hasattr(ret, 'dtype'): |
| 139 | if is_float16_result: |
| 140 | ret = arr.dtype.type(ret / rcount) |
| 141 | else: |
| 142 | ret = ret.dtype.type(ret / rcount) |
| 143 | else: |
| 144 | ret = ret / rcount |
| 145 | |
| 146 | return ret |
| 147 | |
| 148 | def _var(a, axis=None, dtype=None, out=None, ddof=0, keepdims=False, *, |
| 149 | where=True, mean=None): |
nothing calls this directly
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