src/nupic/math/stats.py
def inferRowCompat(self, distribution):
    """
    Equivalent to the category inference of zeta1.TopLevel.
    Computes the max_prod (maximum component of a component-wise multiply)
    between the rows of the histogram and the incoming distribution.
    May be slow if the result of clean_outcpd() is not valid.

    :param distribution: Array of length equal to the number of columns.
    :returns: array of length equal to the number of rows.
    """
    if self.hack_ is None:
      self.clean_outcpd()
    return self.hack_.vecMaxProd(distribution)
def inferRowCompat(self, distribution):
    """
    Equivalent to the category inference of zeta1.TopLevel.
    Computes the max_prod (maximum component of a component-wise multiply)
    between the rows of the histogram and the incoming distribution.
    May be slow if the result of clean_outcpd() is not valid.

    :param distribution: Array of length equal to the number of columns.
    :returns: array of length equal to the number of rows.
    """
    if self.hack_ is None:
      self.clean_outcpd()
    return self.hack_.vecMaxProd(distribution)
def inferRowCompat ( self , distribution ) : if self . hack_ is None : self . clean_outcpd ( ) return self . hack_ . vecMaxProd ( distribution )
Equivalent to the category inference of zeta1.TopLevel.
    Computes the max_prod (maximum component of a component-wise multiply)
    between the rows of the histogram and the incoming distribution.
    May be slow if the result of clean_outcpd() is not valid.

    :param distribution: Array of length equal to the number of columns.
    :returns: array of length equal to the number of rows.
Equivalent to the category inference of zeta1 . TopLevel . Computes the max_prod ( maximum component of a component - wise multiply ) between the rows of the histogram and the incoming distribution . May be slow if the result of clean_outcpd () is not valid .