<jupyter_start><jupyter_text>`snrm2(N, X, INCX)`Computes the Euclidean norm of a vector $\mathbf{x}$.Operates on single-precision real valued arrays.Input vector $\mathbf{x}$ is represented as a [strided array](../strided_arrays.ipynb) `X`, spaced by `INCX`.$\mathbf{x}$ is of size `N`.  Example usage<jupyter_code>import os
import sys
sys.path.insert(0, os.path.abspath(os.path.join(os.path.abspath(''), "..", "..")))
import numpy as np
from pyblas.level1 import snrm2
x = np.array([1, 2, 3], dtype=np.single)
N = len(x)
incx = 1
snrm2(N, x, incx)<jupyter_output><empty_output><jupyter_text>Docstring<jupyter_code>help(snrm2)<jupyter_output>Help on function snrm2 in module pyblas.level1.snrm2:

snrm2(N, X, INCX)
    Computes the Euclidean norm of the vector x
    
    Parameters
    ----------
    N : int
        Number of elements in input vector
    X : numpy.ndarray
        A single precision real array, dimension (1 + (`N` - 1)*abs(`INCX`))
    INCX : int
        Storage spacing between elements of `X`
    
    Returns
    -------
    numpy.single
    
    See Also
    --------
    dnrm2 : Double-precision real euclidean norm
    scnrm2 : Single-precision complex euclidean norm
    zdnrm2 : Double-precision complex euclidean norm
    
    Notes
    -----
    Online PyBLAS documentation: https://nbviewer.jupyter.org/github/timleslie/pyblas/blob/main/docs/snrm2.ipynb
    Reference BLAS documentation: https://github.com/Reference-LAPACK/lapack/blob/v3.9.0/BLAS/SRC/snrm2.f
    
    Examples
    --------
    >>> x = np.array([1, 2, 3], dtype=np.single)
    >>> N = len(x)
    >>> incx = 1
    >>> print(snrm2(N, x, incx)
   [...]<jupyter_text>Source code<jupyter_code>snrm2??<jupyter_output><empty_output>
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