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# Python | Numpy np.leggauss() method

• Last Updated : 31 Dec, 2019

`np.leggauss()` Computes the sample points and weights for Gauss-legendre quadrature. These sample points and weights will correctly integrate polynomials of degree `2*deg - 1 `or less over the interval `[-1, 1]` with the weight function `f(x) = 1`

Syntax : `np.leggauss(deg)`
Parameters:
deg :[int] Number of sample points and weights. It must be >= 1.

Return : 1.[ndarray] 1-D ndarray containing the sample points.
2.[ndarray] 1-D ndarray containing the weights.

Code #1 :

 `# Python program explaining``# numpy.leggauss() method ``   ` `# importing numpy as np  ``# and numpy.polynomial.legendre module as geek ``import` `numpy as np ``import` `numpy.polynomial.legendre as geek``   ` `# Input degree = 2`` ` `degree ``=` `2` `    ` `# using np.leggauss() method ``res ``=` `geek.leggauss(degree) `` ` `# Resulting array of sample point and weight``print` `(res) `
Output:

```(array([-0.57735027,  0.57735027]), array([ 1.,  1.]))
```

Code #2 :

 `# Python program explaining``# numpy.leggauss() method ``   ` `# importing numpy as np  ``# and numpy.polynomial.legendre module as geek ``import` `numpy as np ``import` `numpy.polynomial.legendre as geek``   ` `# Input degree``degree ``=` `3``   ` `# using np.leggauss() method ``res ``=` `geek.leggauss(degree) `` ` `# Resulting array of sample point and weight``print` `(res) `
Output:
```(array([-0.77459667,  0.,  0.77459667]), array([ 0.55555556,  0.88888889,  0.55555556]))
```

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