<jupyter_start><jupyter_text>`dsdot(N, SX, INCX, SY, INCY)`Computes the dot product of a vector $\mathbf{x}$ and a vector $\mathbf{y}$.Operates on single-precision real valued arrays.Input vector $\mathbf{x}$ is represented as a [strided array](../strided_arrays.ipynb) `SX`, spaced by `INCX`.Input vector $\mathbf{y}$ is represented as a [strided array](../strided_arrays.ipynb) `SY`, spaced by `INCY`.Both $\mathbf{x}$ and $\mathbf{y}$ are 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 dsdot
x = np.array([1, 2, 3], dtype=np.single)
y = np.array([6, 7, 8], dtype=np.single)
N = len(x)
incx = 1
incy = 1
dsdot(N, x, incx, y, incy)<jupyter_output><empty_output><jupyter_text>Docstring<jupyter_code>help(dsdot)<jupyter_output>Help on function dsdot in module pyblas.level1.dsdot:

dsdot(N, SX, INCX, SY, INCY)
    Computes the dot-product of a vector x and a vector y.
    
    Parameters
    ----------
    N : int
        Number of elements in input vectors
    SX : numpy.ndarray
        A single precision real array, dimension (1 + (`N` - 1)*abs(`INCX`))
    INCX : int
        Storage spacing between elements of `SX`
    SY : numpy.ndarray
        A single precision real array, dimension (1 + (`N` - 1)*abs(`INCY`))
    INCY : int
        Storage spacing between elements of `SY`
    
    Returns
    -------
    numpy.double
    
    See Also
    --------
    sdot : Single-precision real dot product
    sdsdot : Single-precision real dot product (computed in double precision, returned as single precision)
    ddot : Double-precision real dot product
    cdotu : Single-precision complex dot product
    cdotc : Single-precision complex conjugate dot product
    zdotu : Double-precision complex dot product
    zd[...]<jupyter_text>Source code<jupyter_code>dsdot??<jupyter_output><empty_output>
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