def _evaluate(self, x):
    '\n        Returns the level of the function at each value in x as the maximum among\n        all of the functions.  Only called internally by HARKinterpolator1D.__call__.\n        '
    if _isscalar(x):
        y = np.nanmax([f(x) for f in self.functions])
    else:
        m = len(x)
        fx = np.zeros((m, self.funcCount))
        for j in range(self.funcCount):
            fx[:, j] = self.functions[j](x)
        y = np.nanmax(fx, axis=1)
    return y
Returns the level of the function at each value in x as the maximum among
all of the functions.  Only called internally by HARKinterpolator1D.__call__.
def _evaluate(self, x):
    '\n        Returns the level of the function at each value in x as the maximum among\n        all of the functions.  Only called internally by HARKinterpolator1D.__call__.\n        '
    if _isscalar(x):
        y = np.nanmax([f(x) for f in self.functions])
    else:
        m = len(x)
        fx = np.zeros((m, self.funcCount))
        for j in range(self.funcCount):
            fx[:, j] = self.functions[j](x)
        y = np.nanmax(fx, axis=1)
    return y