Library "MathSpecialFunctionsGamma" Gamma Functions. GammaQ(index) Enumeration of the polynomial coefficients for the "GammaLn" approximation. Parameters: index : int, 0 => index => 10, index of coeficient. Returns: float GammaLn(z) Computes the logarithm of the Gamma function. Parameters: z : The argument of the gamma function. Returns: The...
Library "Probability" erf(value) Complementary error function Parameters: value : float, value to test. Returns: float ierf_mcgiles(value) Computes the inverse error function using the Mc Giles method, sacrifices accuracy for speed. Parameters: value : float, -1.0 >= _value >= 1.0 range, value to test. Returns: float ierf_double(value) ...
Library "MathStatisticsKernelDensityEstimation" (KDE) Method for Kernel Density Estimation kde(observations, kernel, bandwidth, nsteps) Parameters: observations : float array, sample data. kernel : string, the kernel to use, default='gaussian', options='uniform', 'triangle', 'epanechnikov', 'quartic', 'triweight', 'gaussian', 'cosine', 'logistic',...
Library "MathStatisticsKernelFunctions" TODO: add library description here uniform(distance, bandwidth) Uniform kernel. Parameters: distance : float, distance to kernel origin. bandwidth : float, default=1.0, bandwidth limiter to weight the kernel. Returns: float. triangular(distance, bandwidth) Triangular kernel. Parameters: distance : float,...
Library "MathTransformsHartley" implementation of the Fast Discrete Hartley Transform(DHT). naive(samples) Generic naive transform for the (DHT). Parameters: samples : float array, 1d data. Returns: float array. fdht(samples) Fast Discrete Hartley Transform (DHT). Parameters: samples : float array, data samples. Returns: float array. ...
Library "MathSpecialFunctionsTestFunctions" Methods for test functions. rosenbrock(input_x, input_y) Valley-shaped Rosenbrock function for 2 dimensions: (x,y) -> (1-x)^2 + 100*(y-x^2)^2. Parameters: input_x : float, common range within (-5.0, 10.0) or (-2.048, 2.048). input_y : float, common range within (-5.0, 10.0) or (-2.048, 2.048). Returns:...
Library "MathGeometryCurvesChaikin" Implements the chaikin algorithm to create a curved path, from assigned points. chaikin(points_x, points_y, closed) Chaikin algorithm method, uses provided points to generate a smoothed path. Parameters: points_x : float array, the x value of points. points_y : float array, the y value of points. closed : bool,...
Library "Double_Triple_EMA" Provides the functions to calculate Double and Triple Exponentional Moving Averages (DEMA & TEMA). dema(_source, _length) Calculates Double Exponentional Moving Averages (DEMA) Parameters: _source : -> Open, Close, High, Low, etc ('close' is used if no argument is supplied) _length : -> DEMA length Returns: Double...
Library "AutoColor" Function provides rgb color based on deviation of highest and lowest value for the period from current value fColor(src1, len1) Calculates rgb color based on deviation of highest and lowest value for the period from current value Parameters: src1 : Series to use (`close` is used if no argument is supplied). len1 : Length for highest...
Library "Library_All_In_One" fnRSI() fnTSI() Discription: Contains several functions of Pinescript all in one Library. This reduce your coding. How to use: import Wilson-IV/Library_All_In_One/1 as _lib Examples of plotting the RSI and TSI: plot(_lib.fnRSI(close, 14)) plot(_lib.fnTSI(close, 25, 14)) Markets: It can be used to all markets. ...
Library "multiMa" Provides function that returns the type of moving average requested. ma(type, src, len) Returns the moving average requested. Parameters: type : The type of moving average (choose one of "EMA", "SMA", "DEMA", "TEMA", "WMA", "VWMA", "SMMA", "HMA") src : The source len : The length Returns: The moving average requested or `na`
Library "MathSpecialFunctionsLogistic" Methods for logistic equation. logistic(probability) Computes the logistic function. Parameters: probability : float, value to compute the logistic function. Returns: float logit(probability) Computes the logit function, the inverse of the sigmoid logistic function. Parameters: probability : float, value to...
Library "MathTrigonometry" Trigonometric methods. sinc(value) Normalized sinc function. Parameters: value : float, value. Returns: float. cot(value) Cotangent of value. Parameters: value : float, value. Returns: float. csc(value) Cosecant of value. Parameters: value : float, value. Returns: float. sec(value) Secant of...
Library "MathSearchDijkstra" Shortest Path Tree Search Methods using Dijkstra Algorithm. min_distance(distances, flagged_vertices) Find the lowest cost/distance. Parameters: distances : float array, data set with distance costs to start index. flagged_vertices : bool array, data set with visited vertices flags. Returns: int, lowest cost/distance...
Library "MathGaussFunction" Implements multiple gauss methods. f_1d(point_x, sigma) 1-D Gaussian function. Parameters: point_x : float, x value. sigma : float, sigma value, default=1.0. Returns: float, function's value at point_x. f_2d(point_x, point_y, sigma) 2-D Gaussian function. Parameters: point_x : float, x value. point_y : float, y...
Library "MathFinancialAbsoluteRiskMeasures" Financial Absolute Risk Measures. gain_stdev(sample) Standard deviation of gains in a data sample. Parameters: sample : float array, data sample. Returns: float. loss_stdev(sample) Standard deviation of losses in a data sample. Parameters: sample : float array, data sample. Returns: float. ...
Library "MathOperator" Methods to handle operators. add(value_a, value_b) Add value a to b. Parameters: value_a : float, value a. value_b : float, value b. Returns: float. subtract(value_a, value_b) subtract value b from a. Parameters: value_a : float, value a. value_b : float, value b. Returns: float. multiply(value_a, value_b) ...
Library "MathExtension" Math Extension. log2(_value) calculate log base 2 Parameters: _value : float, number. Returns: float, base 2 logarithm of value. fmod(numerator, denominator) float remainder of x divided by y. Parameters: numerator : float, division numerator. denominator : float, division denuminator. Returns: float ...