Line Algorithms

treelas.line_las(y, lam, mu=1.0, x=None, increasing=True)
treelas.line_dp(*args, **kwargs)

Overloaded function.

  1. line_dp(y: numpy.ndarray[float64], lam: float, mu: float = 1.0, x: numpy.ndarray[float64] = None) -> numpy.ndarray[float64]

  2. line_dp(y: numpy.ndarray[float64], lam: numpy.ndarray[float64], mu: float = 1.0, x: numpy.ndarray[float64] = None) -> numpy.ndarray[float64]

  3. line_dp(y: numpy.ndarray[float64], lam: float, mu: numpy.ndarray[float64] = 1.0, x: numpy.ndarray[float64] = None) -> numpy.ndarray[float64]

  4. line_dp(y: numpy.ndarray[float64], lam: numpy.ndarray[float64], mu: numpy.ndarray[float64] = 1.0, x: numpy.ndarray[float64] = None) -> numpy.ndarray[float64]

    Line solver (weights).

    Memory: ??*len(y)*sizeof(uint32_t)

For Comparison

treelas.line_glmgen(y: numpy.ndarray[float64], lam: float, out: numpy.ndarray[float64] = None, verbose: bool = False) → numpy.ndarray[float64]

` Line solver (implementation of the R package glmgen).

Memory: ??*len(y)*sizeof(uint32_t)
treelas.line_condat(y: numpy.ndarray[float64], lam: float, out: numpy.ndarray[float64] = None) → numpy.ndarray[float64]

Line solver, implemented by Laurent Condat, version 2.0, Aug. 30, 2017. See: https://www.gipsa-lab.grenoble-inp.fr/~laurent.condat

Memory usage: 2*len(y)*sizeof(uint32_t)