interfacegrids_gene.py 文件源码

def extrap1d_constrained_linear_regression(x, y, xEval, side='right', numPts=10):
    """Perform extrapolation using constrained linear regression on part of the data (x,y).  Use numPts
    from either the left or right side of the data (specified by input variable side) as the input data.
    The linear regression is constrained to pass through the final point (x0, y0) (rightmost point if
    side=='right', leftmost if side=='left').  Data MUST be sorted.

    Inputs:
      x                 independent variable on the smaller domain (array)
      y                 dependent variable on the smaller domain (array)
      xEval             values of x at which to evaluate the linear regression model
      side              side of the data from which to perform linear regression ('left' or 'right')
      numPts            number of points to use in the linear regression (scalar)
    Outputs:
      yEval             values of dependent variable in the linear regression model evaluated at x_eval (array)
    """
    assert side=='left' or side=='right'
    if side=='left':
        xSide = x[:numPts]
        ySide = y[:numPts]
        x0 = x[0]
        y0 = y[0]
    elif side=='right':
        xSide = x[-numPts:]
        ySide = y[-numPts:]
        x0 = x[-1]
        y0 = y[-1]

    a = least_squares_slope(xSide, ySide, x0, y0)  # determine model (a, x0, y0)
    b = y0 - a*x0
    #y_eval = scipy.polyval([a,b], x_eval)
    yEval = a*(xEval - x0) + y0 # evaluate model on desired points
    return yEval