numpy算数运算函数
| name | descripe |
|---|---|
| add(x1, x2[, out]) | Add arguments element-wise. |
| reciprocal(x[, out]) | Return the reciprocal of the argument, element-wise. |
| negative(x[, out]) | Numerical negative, element-wise. |
| multiply(x1, x2[, out]) | Multiply arguments element-wise. |
| divide(x1, x2[, out]) | Divide arguments element-wise. |
| power(x1, x2[, out]) | First array elements raised to powers from second array, element-wise. |
| subtract(x1, x2[, out]) | Subtract arguments, element-wise. |
| true_divide(x1, x2[, out]) | Returns a true division of the inputs, element-wise. |
| floor_divide(x1, x2[, out]) | Return the largest integer smaller or equal to the division of the inputs. |
| fmod(x1, x2[, out]) | Return the element-wise remainder of division. |
| mod(x1, x2[, out]) | Return element-wise remainder of division. |
| modf(x[, out1, out2]) | Return the fractional and integral parts of an array, element-wise. |
| remainder(x1, x2[, out]) | Return element-wise remainder of division. |
1.numpy.add(x1, x2[, out ]) = ufunc‘add’
求和
>>> np.add(1.0, 4.0)
5.0
>>> x1 = np.arange(9.0).reshape((3, 3))
[[ 0. 1. 2.]
[ 3. 4. 5.]
[ 6. 7. 8.]]
>>> x2 = np.arange(3.0)
[ 0. 1. 2.]
>>> np.add(x1, x2)
array([[ 0., 2., 4.],
[ 3., 5., 7.],
[ 6., 8., 10.]])2.numpy.reciprocal(x[, out ]) = ufunc ‘reciprocal’
求倒数
>>> np.reciprocal(2.)
0.5
>>> np.reciprocal([1, 2., 3.33])
array([ 1. , 0.5 , 0.3003003])3.numpy.negative(x[, out ]) = ufunc ‘negative’
求相反数
>>> np.negative([1.,-1.])
array([-1., 1.])4.numpy.multiply(x1, x2[, out ]) = ufunc ‘multiply’
求积
>>> np.multiply(2.0, 4.0)
8.0
>>> x1 = np.arange(9.0).reshape((3, 3))
>>> x2 = np.arange(3.0)
>>> np.multiply(x1, x2)
array([[ 0., 1., 4.],
[ 0., 4., 10.],
[ 0., 7., 16.]])5.numpy.divide(x1, x2[, out ]) = ufunc ‘divide’
求商
>>> np.divide(2.0, 4.0)
0.5
>>> x1 = np.arange(9.0).reshape((3, 3))
>>> x2 = np.arange(3.0)
>>> np.divide(x1, x2)
array([[ NaN, 1. , 1. ],
[ Inf, 4. , 2.5],
[ Inf, 7. , 4. ]])numpy.true_divide(x1, x2[, out ]) = ufunc ‘true_divide’
>>> x = np.arange(5)
>>> np.true_divide(x, 4)
array([ 0. , 0.25, 0.5 , 0.75, 1. ])
>>> x/4
array([0, 0, 0, 0, 1])
>>> x//4
array([0, 0, 0, 0, 1])numpy.floor_divide(x1, x2[, out ]) = ufunc ‘floor_divide’
>>> np.floor_divide(7,3)
2
>>> np.floor_divide([1., 2., 3., 4.], 2.5)
array([ 0., 0., 1., 1.])6.numpy.power(x1, x2[, out ]) = ufunc ‘power’
求幂
>>> x1 = range(6)
>>> x1
[0, 1, 2, 3, 4, 5]
>>> np.power(x1, 3)
array([ 0, 1, 8, 27, 64, 125])
>>> x2 = [1.0, 2.0, 3.0, 3.0, 2.0, 1.0]
>>> np.power(x1, x2)
array([ 0., 1., 8., 27., 16., 5.])7.numpy.subtract(x1, x2[, out ]) = ufunc ‘subtract’
求差
>>> np.subtract(1.0, 4.0)
-3.0
>>> x1 = np.arange(9.0).reshape((3, 3))
>>> x2 = np.arange(3.0)
>>> np.subtract(x1, x2)
array([[ 0., 0., 0.],
[ 3., 3., 3.],
[ 6., 6., 6.]])8.numpy.fmod(x1, x2[, out ]) = ufunc ‘fmod’
求余
>>> np.fmod([-3, -2, -1, 1, 2, 3], 2)
array([-1, 0, -1, 1, 0, 1])
>>> np.remainder([-3, -2, -1, 1, 2, 3], 2)
array([1, 0, 1, 1, 0, 1])
>>> np.fmod([5, 3], [2, 2.])
array([ 1., 1.])
>>> a = np.arange(-3, 3).reshape(3, 2)
>>> a
array([[-3, -2],
[-1, 0],
[ 1, 2]])
>>> np.fmod(a, [2,2])
array([[-1, 0],
[-1, 0],
[ 1, 0]])numpy.mod(x1, x2[, out ]) = ufunc ‘remainder’
>>> np.remainder([4, 7], [2, 3])
array([0, 1])
>>> np.remainder(np.arange(7), 5)
array([0, 1, 2, 3, 4, 0, 1])numpy.remainder(x1, x2[, out ]) =
>>> np.remainder([4, 7], [2, 3])
array([0, 1])
>>> np.remainder(np.arange(7), 5)
array([0, 1, 2, 3, 4, 0, 1])9.numpy.modf(x[, out1, out2 ]) = ufunc ‘modf’
求整，求小数
>>> np.modf([0, 3.5])
(array([ 0. , 0.5]), array([ 0., 3.]))
>>> np.modf(-0.5)
(-0.5, -0)