Python numpy.core.umath.subtract() Examples
The following are 13
code examples of numpy.core.umath.subtract().
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Example #1
Source File: _methods.py From recruit with Apache License 2.0 | 5 votes |
def _ptp(a, axis=None, out=None, keepdims=False): return um.subtract( umr_maximum(a, axis, None, out, keepdims), umr_minimum(a, axis, None, None, keepdims), out )
Example #2
Source File: _methods.py From lambda-packs with MIT License | 5 votes |
def _ptp(a, axis=None, out=None, keepdims=False): return um.subtract( umr_maximum(a, axis, None, out, keepdims), umr_minimum(a, axis, None, None, keepdims), out )
Example #3
Source File: ma.py From Computable with MIT License | 5 votes |
def __sub__(self, other): "Return subtract(self, other)" return subtract(self, other)
Example #4
Source File: ma.py From Computable with MIT License | 5 votes |
def __rsub__(self, other): "Return subtract(other, self)" return subtract(other, self)
Example #5
Source File: _methods.py From Mastering-Elasticsearch-7.0 with MIT License | 5 votes |
def _ptp(a, axis=None, out=None, keepdims=False): return um.subtract( umr_maximum(a, axis, None, out, keepdims), umr_minimum(a, axis, None, None, keepdims), out )
Example #6
Source File: _methods.py From GraphicDesignPatternByPython with MIT License | 5 votes |
def _ptp(a, axis=None, out=None, keepdims=False): return um.subtract( umr_maximum(a, axis, None, out, keepdims), umr_minimum(a, axis, None, None, keepdims), out )
Example #7
Source File: _methods.py From predictive-maintenance-using-machine-learning with Apache License 2.0 | 5 votes |
def _ptp(a, axis=None, out=None, keepdims=False): return um.subtract( umr_maximum(a, axis, None, out, keepdims), umr_minimum(a, axis, None, None, keepdims), out )
Example #8
Source File: _methods.py From pySINDy with MIT License | 5 votes |
def _ptp(a, axis=None, out=None, keepdims=False): return um.subtract( umr_maximum(a, axis, None, out, keepdims), umr_minimum(a, axis, None, None, keepdims), out )
Example #9
Source File: _methods.py From coffeegrindsize with MIT License | 5 votes |
def _ptp(a, axis=None, out=None, keepdims=False): return um.subtract( umr_maximum(a, axis, None, out, keepdims), umr_minimum(a, axis, None, None, keepdims), out )
Example #10
Source File: _methods.py From Carnets with BSD 3-Clause "New" or "Revised" License | 5 votes |
def _ptp(a, axis=None, out=None, keepdims=False): return um.subtract( umr_maximum(a, axis, None, out, keepdims), umr_minimum(a, axis, None, None, keepdims), out )
Example #11
Source File: _methods.py From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License | 5 votes |
def _ptp(a, axis=None, out=None, keepdims=False): return um.subtract( umr_maximum(a, axis, None, out, keepdims), umr_minimum(a, axis, None, None, keepdims), out )
Example #12
Source File: _methods.py From twitter-stock-recommendation with MIT License | 5 votes |
def _ptp(a, axis=None, out=None, keepdims=False): return um.subtract( umr_maximum(a, axis, None, out, keepdims), umr_minimum(a, axis, None, None, keepdims), out )
Example #13
Source File: ma.py From Computable with MIT License | 4 votes |
def __isub__(self, other): "Subtract other from self in place." t = self._data.dtype.char f = filled(other, 0) t1 = f.dtype.char if t == t1: pass elif t in typecodes['Integer']: if t1 in typecodes['Integer']: f = f.astype(t) else: raise TypeError('Incorrect type for in-place operation.') elif t in typecodes['Float']: if t1 in typecodes['Integer']: f = f.astype(t) elif t1 in typecodes['Float']: f = f.astype(t) else: raise TypeError('Incorrect type for in-place operation.') elif t in typecodes['Complex']: if t1 in typecodes['Integer']: f = f.astype(t) elif t1 in typecodes['Float']: f = f.astype(t) elif t1 in typecodes['Complex']: f = f.astype(t) else: raise TypeError('Incorrect type for in-place operation.') else: raise TypeError('Incorrect type for in-place operation.') if self._mask is nomask: self._data -= f m = getmask(other) self._mask = m self._shared_mask = m is not nomask else: result = subtract(self, masked_array(f, mask=getmask(other))) self._data = result.data self._mask = result.mask self._shared_mask = 1 return self