Library "FunctionPatternDecomposition" Methods for decomposing price into common grid/matrix patterns.
series_to_array(source, length) Helper for converting series to array. Parameters: source: float, data series. length: int, size. Returns: float array.
smooth_data_2d(data, rate) Smooth data sample into 2d points. Parameters: data: float array, source data. rate: float, default=0.25, the rate of smoothness to apply. Returns: tuple with 2 float arrays.
thin_points(data_x, data_y, rate) Thin the number of points. Parameters: data_x: float array, points x value. data_y: float array, points y value. rate: float, default=2.0, minimum threshold rate of sample stdev to accept points. Returns: tuple with 2 float arrays.
extract_point_direction(data_x, data_y) Extract the direction each point faces. Parameters: data_x: float array, points x value. data_y: float array, points y value. Returns: float array.
find_corners(data_x, data_y, rate) ... Parameters: data_x: float array, points x value. data_y: float array, points y value. rate: float, minimum threshold rate of data y stdev. Returns: tuple with 2 float arrays.
grid_coordinates(data_x, data_y, m_size) transforms points data to a constrained sized matrix format. Parameters: data_x: float array, points x value. data_y: float array, points y value. m_size: int, default=10, size of the matrix. Returns: flat 2d pseudo matrix.