PINE LIBRARY

FunctionMinkowskiDistance

Library "FunctionMinkowskiDistance"
Method for Minkowski Distance,
The Minkowski distance or Minkowski metric is a metric in a normed vector space
which can be considered as a generalization of both the Euclidean distance and
the Manhattan distance.
It is named after the German mathematician Hermann Minkowski.
reference: en.wikipedia.org/wiki/Minkowski_distance

double(point_ax, point_ay, point_bx, point_by, p_value) Minkowsky Distance for single points.
  Parameters:
    point_ax: float, x value of point a.
    point_ay: float, y value of point a.
    point_bx: float, x value of point b.
    point_by: float, y value of point b.
    p_value: float, p value, default=1.0(1: manhatan, 2: euclidean), does not support chebychev.
  Returns: float

ndim(point_x, point_y, p_value) Minkowsky Distance for N dimensions.
  Parameters:
    point_x: float array, point x dimension attributes.
    point_y: float array, point y dimension attributes.
    p_value: float, p value, default=1.0(1: manhatan, 2: euclidean), does not support chebychev.
  Returns: float
arrayarraysdimensiondistancefunctionMATHmdimminkowskistatistics

Pine library

In true TradingView spirit, the author has published this Pine code as an open-source library so that other Pine programmers from our community can reuse it. Cheers to the author! You may use this library privately or in other open-source publications, but reuse of this code in a publication is governed by House rules.

Disclaimer