latqcdtools.math.math
=============

`RMS(data) -> float`

    Root-mean-square of data

    Args:
        data (np.ndarray)

    Returns:
        float: RMS of data 
    
`checkSquare(mat)`
 
    Make sure mat is a square np.ndarray object. 

    Args:
        mat (np.ndarray)
    
`fallFactorial(n, m) -> float`
 
    Falling factorial n fall to m. 
    
`invert(mat, method='scipy', svdcut=1e-12) -> numpy.ndarray`
 
    Invert matrix.

    Args:
        mat (np.ndarray): to-be-inverted matrix 
        method (str): algorithm for inverting the matrix
        
    Returns:
        np.ndarray: mat^{-1} 
    
`isPositiveSemidefinite(mat) -> bool`


`isSymmetric(mat) -> bool`


`logDet(mat) -> float`
 
    Logarithm of determinant. 
    
`normalize(arr)`


`quadrature(data) -> float`

    Add data in quadrature

    Args:
        data (np.ndarray)

    Returns:
        float: data added in quadrature 
    
`regulate(mat, svdcut=1e-12) -> numpy.ndarray`
 
    If a matrix's singular values are too small, it will be ill-conditioned,
    making it difficult to invert and hence reducing numerical stability. This method
    extracts its singular values using SVD, then doctors the singular values to reduce
    the condition number. In the context of applying an SVD cut to a covariance 
    matrix, see e.g. Appendix D of 10.1103/PhysRevD.100.094508.

    Args:
        mat (np.ndarray)
        svdcut (float, optional): condition number threshold. Defaults to 1e-12.

    Returns:
        np.ndarray: regulated matrix 
    
`rel_check(a, b, prec=1e-06, abs_prec=1e-14) -> bool`
 
    Check whether a and b are equal. a and b can be array-like, float-like, or complexes. If a
    and b are array-like, we check that they are element-wise equal within the tolerance. 

    Args:
        a (obj)
        b (obj)
        prec (float, optional): Relative precision. Defaults to 1e-6.
        abs_prec (float, optional): Absolute precision. Defaults to 1e-14.

    Returns:
        bool: True if a and b are equal. 
    
`riseFactorial(n, m) -> float`
 
    Rising factorial n rise to m.