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numpy 算数运算函数
namedescripeadd(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/4array([0, 0, 0, 0, 1])
x//4array([0, 0, 0, 0, 1])numpy.floor_divide(x1, x2[, out]) = ufunc‘floor_divide’
np.floor_divide(7,3)
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)
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