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Arrays

ConditionalAverages█   OVERVIEW This library is a Pine Script™ programmer’s tool containing functions that average values selectively. █   CONCEPTS Averaging can be useful to smooth out unstable readings in the data set, provide a benchmark to see the underlying trend of the data, or to provide a general expectancy of values in establishing a central tendency. Conventional averaging techniques tend to apply indiscriminately to all values in a fixed window, but it can sometimes be useful to average values only when a specific condition is met. As conditional averaging works on specific elements of a dataset, it can help us derive more context-specific conclusions. This library offers a collection of averaging methods that not only accomplish these tasks, but also exploit the efficiencies of the Pine Script™ runtime by foregoing unnecessary and ​​​resource-intensive for loops. █   NOTES To Loop or Not to Loop Though for and while loops are essential programming tools, they are often unnecessary in Pine Script™. This is because the Pine Script™ runtime already runs your scripts in a loop where it executes your code on each bar of the dataset. Pine Script™ programmers who understand how their code executes on charts can use this to their advantage by designing loop-less code that will run orders of magnitude faster than functionally identical code using loops. Most of this library's function illustrate how you can achieve loop-less code to process past values. See the User Manual page on loops for more information. If you are looking for ways to measure execution time for you scripts, have a look at our LibraryStopwatch library . Our `avgForTimeWhen()` and `totalForTimeWhen()` are exceptions in the library, as they use a while structure. Only a few iterations of the loop are executed on each bar, however, as its only job is to remove the few elements in the array that are outside the moving window defined by a time boundary. Cumulating and Summing Conditionally The ta.cum() or math.sum() built-in functions can be used with ternaries that select only certain values. In our `avgWhen(​src, ​cond)` function, for example, we use this technique to cumulate only the occurrences of `src` when `cond` is true: float cumTotal = ta.cum(cond ? ​src : 0) We then use: float cumCount = ta.cum(cond ? 1 : 0) to calculate the number of occurrences where `cond` is true, which corresponds to the quantity of values cumulated in `cumTotal`. Building Custom Series With Arrays The advent of arrays in Pine has enabled us to build our custom data series. Many of this library's functions use arrays for this purpose, saving newer values that come in when a condition is met, and discarding the older ones, implementing a queue . `avgForTimeWhen()` and `totalForTimeWhen()` These two functions warrant a few explanations. They operate on a number of values included in a moving window defined by a timeframe expressed in milliseconds. We use a 1D timeframe in our example code. The number of bars included in the moving window is unknown to the programmer, who only specifies the period of time defining the moving window. You can thus use `avgForTimeWhen()` to calculate a rolling moving average for the last 24 hours, for example, that will work whether the chart is using a 1min or 1H timeframe. A 24-hour moving window will typically contain many more values on a 1min chart that on a 1H chart, but their calculated average will be very close. Problems will arise on non-24x7 markets when large time gaps occur between chart bars, as will be the case across holidays or trading sessions. For example, if you were using a 24H timeframe and there is a two-day gap between two bars, then no chart bars would fit in the moving window after the gap. The `minBars` parameter mitigates this by guaranteeing that a minimum number of bars are always included in the calculation, even if including those bars requires reaching outside the prescribed timeframe. We use a minimum value of 10 bars in the example code. Using var in Constant Declarations In the past, we have been using var when initializing so-called constants in our scripts, which as per the Style Guide 's recommendations, we identify using UPPER_SNAKE_CASE. It turns out that var variables incur slightly superior maintenance overhead in the Pine Script™ runtime, when compared to variables initialized on each bar. We thus no longer use var to declare our "int/float/bool" constants, but still use it when an initialization on each bar would require too much time, such as when initializing a string or with a heavy function call. Look first. Then leap. █   FUNCTIONS avgWhen(​src, ​cond)   Gathers values of the source when a condition is true and averages them over the total number of occurrences of the condition.   Parameters:      src : (series int/float) The source of the values to be averaged.      cond : (series bool) The condition determining when a value will be included in the set of values to be averaged.   Returns: (float) A cumulative average of values when a condition is met. avgWhenLast(​src, ​cond, ​cnt)   Gathers values of the source when a condition is true and averages them over a defined number of occurrences of the condition.   Parameters:      src : (series int/float) The source of the values to be averaged.      cond : (series bool) The condition determining when a value will be included in the set of values to be averaged.      cnt : (simple int) The quantity of last occurrences of the condition for which to average values.   Returns: (float) The average of `src` for the last `x` occurrences where `cond` is true. avgWhenInLast(​src, ​cond, ​cnt)   Gathers values of the source when a condition is true and averages them over the total number of occurrences during a defined number of bars back.   Parameters:      src : (series int/float) The source of the values to be averaged.      cond : (series bool) The condition determining when a value will be included in the set of values to be averaged.      cnt : (simple int) The quantity of bars back to evaluate.   Returns: (float) The average of `src` in last `cnt` bars, but only when `cond` is true. avgSince(​src, ​cond)   Averages values of the source since a condition was true.   Parameters:      src : (series int/float) The source of the values to be averaged.      cond : (series bool) The condition determining when the average is reset.   Returns: (float) The average of `src` since `cond` was true. avgForTimeWhen(​src, ​ms, ​cond, ​minBars)   Averages values of `src` when `cond` is true, over a moving window of length `ms` milliseconds.   Parameters:      src : (series int/float) The source of the values to be averaged.      ms : (simple int) The time duration in milliseconds defining the size of the moving window.      cond : (series bool) The condition determining which values are included. Optional.      minBars : (simple int) The minimum number of values to keep in the moving window. Optional.   Returns: (float) The average of `src` when `cond` is true in the moving window. totalForTimeWhen(​src, ​ms, ​cond, ​minBars)   Sums values of `src` when `cond` is true, over a moving window of length `ms` milliseconds.   Parameters:      src : (series int/float) The source of the values to be summed.      ms : (simple int) The time duration in milliseconds defining the size of the moving window.      cond : (series bool) The condition determining which values are included. Optional.      minBars : (simple int) The minimum number of values to keep in the moving window. Optional.   Returns: (float) The sum of `src` when `cond` is true in the moving window.
مكتبة Pine Script™
من ‎PineCoders‎
5
harmonicpatternsarraysLibrary "harmonicpatternsarrays" Library provides an alternative method to scan harmonic patterns and contains utility functions using arrays. These are mostly customized for personal use. Hence, will not add documentation for arrays. All credit to @HeWhoMustNotBeNamed getLabel() delete() delete() delete() delete() delete() pop() pop() pop() pop() pop() shift() shift() shift() shift() shift() unshift() unshift() unshift() unshift() unshift() unshift() unshift() unshift() unshift() unshift() clear() clear() clear() clear() clear() push() push() push() push() push() push() push() push() push() push() get_trend_series() getrange() getSupportedPatterns() scan_xab() scan_abc_axc() scan_bcd() scan_xad_xcd() get_prz_range() isHarmonicPattern()
مكتبة Pine Script™
من ‎CryptoArch_‎
2
jsonLibrary "json" Convert JSON strings to tradingview        ▦ FEATURES ▦                         █ Json to array  █ Get json key names  █ Get json key values █ Size of json                   get_json_keys_names(raw_json) Returns string array with all key names   Parameters:      raw_json : (string) Raw JSON string   Returns: (string array) Array with all key names get_values_by_id_name(raw_json, key_name) Returns string array with values of the input key name   Parameters:      raw_json : (string) Raw JSON string      key_name : (string) Name of the key to be fetched   Returns: (string array) Array with values of the input key name size_of_json_string(raw_json) Returns size of raw JSON string   Parameters:      raw_json : (string) Raw JSON string   Returns: Size of n_of_values, size of n_of_keys_names
مكتبة Pine Script™
من ‎MA_PT‎
3
JohnEhlersFourierTransformLibrary "JohnEhlersFourierTransform" Fourier Transform for Traders By John Ehlers, slightly modified to allow to inspect other than the 8-50 frequency spectrum. reference: www.mesasoftware.com high_pass_filter(source) Detrended version of the data by High Pass Filtering with a 40 Period cutoff   Parameters:      source : float, data source.   Returns: float. transformed_dft(source, start_frequency, end_frequency) DFT by John Elhers.   Parameters:      source : float, data source.      start_frequency : int, lower bound of the frequency window, must be a positive number >= 0, window must be less than or 30.      end_frequency : int, upper bound of the frequency window, must be a positive number >= 0, window must be less than or 30.   Returns: tuple with float, float array. db_to_rgb(db, transparency) converts the frequency decibels to rgb.   Parameters:      db : float, decibels value.      transparency : float, transparency value.   Returns: color.
مكتبة Pine Script™
من ‎RicardoSantos‎
24
harmonicpatterns1Library "harmonicpatterns1" harmonicpatterns: methods required for calculation of harmonic patterns. Correction for library (missing export in line 303) isGartleyPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isGartleyPattern: Checks for harmonic pattern Gartley   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Gartley. False otherwise. isBatPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isBatPattern: Checks for harmonic pattern Bat   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Bat. False otherwise. isButterflyPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isButterflyPattern: Checks for harmonic pattern Butterfly   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Butterfly. False otherwise. isCrabPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isCrabPattern: Checks for harmonic pattern Crab   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Crab. False otherwise. isDeepCrabPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isDeepCrabPattern: Checks for harmonic pattern DeepCrab   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is DeepCrab. False otherwise. isCypherPattern(xabRatio, axcRatio, xadRatio, err_min, err_max) isCypherPattern: Checks for harmonic pattern Cypher   Parameters:      xabRatio : AB/XA      axcRatio : XC/AX      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Cypher. False otherwise. isSharkPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isSharkPattern: Checks for harmonic pattern Shark   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Shark. False otherwise. isNenStarPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isNenStarPattern: Checks for harmonic pattern Nenstar   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Nenstar. False otherwise. isAntiNenStarPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiNenStarPattern: Checks for harmonic pattern Anti NenStar   Parameters:      xabRatio : - AB/XA      abcRatio : - BC/AB      bcdRatio : - CD/BC      xadRatio : - AD/XA      err_min : - Minumum error threshold      err_max : - Maximum error threshold   Returns: True if the pattern is Anti NenStar. False otherwise. isAntiSharkPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiSharkPattern: Checks for harmonic pattern Anti Shark   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Anti Shark. False otherwise. isAntiCypherPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiCypherPattern: Checks for harmonic pattern Anti Cypher   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Anti Cypher. False otherwise. isAntiCrabPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiCrabPattern: Checks for harmonic pattern Anti Crab   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Anti Crab. False otherwise. isAntiButterflyPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiButterflyPattern: Checks for harmonic pattern Anti Butterfly   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Anti Butterfly. False otherwise. isAntiBatPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiBatPattern: Checks for harmonic pattern Anti Bat   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Anti Bat. False otherwise. isAntiGartleyPattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isAntiGartleyPattern: Checks for harmonic pattern Anti Gartley   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Anti Gartley. False otherwise. isNavarro200Pattern(xabRatio, abcRatio, bcdRatio, xadRatio, err_min, err_max) isNavarro200Pattern: Checks for harmonic pattern Navarro200   Parameters:      xabRatio : AB/XA      abcRatio : BC/AB      bcdRatio : CD/BC      xadRatio : AD/XA      err_min : Minumum error threshold      err_max : Maximum error threshold   Returns: True if the pattern is Navarro200. False otherwise. isHarmonicPattern(x, a, c, c, d, flags, errorPercent) isHarmonicPattern: Checks for harmonic patterns   Parameters:      x : X coordinate value      a : A coordinate value      c : B coordinate value      c : C coordinate value      d : D coordinate value      flags : flags to check patterns. Send empty array to enable all      errorPercent : Error threshold   Returns: Array of boolean values which says whether valid pattern exist and array of corresponding pattern names
مكتبة Pine Script™
من ‎CryptoArch_‎
2
ArrayOperationsLibrary "ArrayOperations" Array element wise basic operations. add(sample_a, sample_b) Adds sample_b to sample_a and returns a new array.   Parameters:      sample_a : values to be added to.      sample_b : values to add.   Returns: array with added results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b subtract(sample_a, sample_b) Subtracts sample_b from sample_a and returns a new array.      sample_a : values to be subtracted from.      sample_b : values to subtract.   Returns: array with subtracted results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b multiply(sample_a, sample_b) multiply sample_a by sample_b and returns a new array.      sample_a : values to multiply.      sample_b : values to multiply with.   Returns: array with multiplied results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b divide(sample_a, sample_b) Divide sample_a by sample_b and returns a new array.      sample_a : values to divide.      sample_b : values to divide with.   Returns: array with divided results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b power(sample_a, sample_b) power sample_a by sample_b and returns a new array.      sample_a : values to power.      sample_b : values to power with.   Returns: float array with power results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b remainder(sample_a, sample_b) Remainder sample_a by sample_b and returns a new array.      sample_a : values to remainder.      sample_b : values to remainder with.   Returns: array with remainder results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b equal(sample_a, sample_b) Check element wise sample_a equals sample_b and returns a new array.      sample_a : values to check.      sample_b : values to check.   Returns: int array with results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b not_equal(sample_a, sample_b) Check element wise sample_a not equals sample_b and returns a new array.      sample_a : values to check.      sample_b : values to check.   Returns: int array with results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b over_or_equal(sample_a, sample_b) Check element wise sample_a over or equals sample_b and returns a new array.      sample_a : values to check.      sample_b : values to check.   Returns: int array with results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b under_or_equal(sample_a, sample_b) Check element wise sample_a under or equals sample_b and returns a new array.      sample_a : values to check.      sample_b : values to check.   Returns: int array with results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b over(sample_a, sample_b) Check element wise sample_a over sample_b and returns a new array.      sample_a : values to check.      sample_b : values to check.   Returns: int array with results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b under(sample_a, sample_b) Check element wise sample_a under sample_b and returns a new array.      sample_a : values to check.      sample_b : values to check.   Returns: int array with results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b and_(sample_a, sample_b) Check element wise sample_a and sample_b and returns a new array.      sample_a : values to check.      sample_b : values to check.   Returns: int array with results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b or_(sample_a, sample_b) Check element wise sample_a or sample_b and returns a new array.      sample_a : values to check.      sample_b : values to check.   Returns: int array with results. - sample_a provides type format for output. - arrays do not need to be symmetric. - sample_a must have same or more elements than sample_b all(sample) Check element wise if all numeric samples are true (!= 0).      sample : values to check.   Returns: int. any(sample) Check element wise if any numeric samples are true (!= 0).      sample : values to check.   Returns: int.
مكتبة Pine Script™
من ‎RicardoSantos‎
5
FunctionPatternDecompositionLibrary "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.
مكتبة Pine Script™
من ‎RicardoSantos‎
3
FunctionBlackScholesLibrary "FunctionBlackScholes" Some methods for the Black Scholes Options Model, which demonstrates several approaches to the valuation of a European call. // reference: // people.math.sc.edu // people.math.sc.edu asset_path(s0, mu, sigma, t1, n) Simulates the behavior of an asset price over time.   Parameters:      s0 : float, asset price at time 0.      mu : float, growth rate.      sigma : float, volatility.      t1 : float, time to expiry date.      n : int, time steps to expiry date.   Returns: option values at each equal timed step (0 -> t1) binomial(s0, e, r, sigma, t1, m) Uses the binomial method for a European call.   Parameters:      s0 : float, asset price at time 0.      e : float, exercise price.      r : float, interest rate.      sigma : float, volatility.      t1 : float, time to expiry date.      m : int, time steps to expiry date.   Returns: option value at time 0. bsf(s0, t0, e, r, sigma, t1) Evaluates the Black-Scholes formula for a European call.   Parameters:      s0 : float, asset price at time 0.      t0 : float, time at which the price is known.      e : float, exercise price.      r : float, interest rate.      sigma : float, volatility.      t1 : float, time to expiry date.   Returns: option value at time 0. forward(e, r, sigma, t1, nx, nt, smax) Forward difference method to value a European call option.   Parameters:      e : float, exercise price.      r : float, interest rate.      sigma : float, volatility.      t1 : float, time to expiry date.      nx : int, number of space steps in interval (0, L).      nt : int, number of time steps.      smax : float, maximum value of S to consider.   Returns: option values for the european call, float array of size ((nx-1) * (nt+1)). mc(s0, e, r, sigma, t1, m) Uses Monte Carlo valuation on a European call.   Parameters:      s0 : float, asset price at time 0.      e : float, exercise price.      r : float, interest rate.      sigma : float, volatility.      t1 : float, time to expiry date.      m : int, time steps to expiry date.   Returns: confidence interval for the estimated range of valuation.
مكتبة Pine Script™
من ‎RicardoSantos‎
4
ArrayExtLibrary "ArrayExt" Array extensions get(a, idx) Get element from the array at index, or na if index not found   Parameters:      a : The array      idx : The array index to get   Returns: The array item if exists or na get(a, idx) Get element from the array at index, or na if index not found   Parameters:      a : The array      idx : The array index to get   Returns: The array item if exists or na get(a, idx) Get element from the array at index, or na if index not found   Parameters:      a : The array      idx : The array index to get   Returns: The array item if exists or na get(a, idx) Get element from the array at index, or na if index not found   Parameters:      a : The array      idx : The array index to get   Returns: The array item if exists or na get(a, idx) Get element from the array at index, or na if index not found   Parameters:      a : The array      idx : The array index to get   Returns: The array item if exists or na get(a, idx) Get element from the array at index, or na if index not found   Parameters:      a : The array      idx : The array index to get   Returns: The array item if exists or na set(a, idx, val) Set array item at index, if array has no index at the specified index, the array is filled with na   Parameters:      a : The array      idx : The array index to set      val : The value to be set set(a, idx, val) Set array item at index, if array has no index at the specified index, the array is filled with na   Parameters:      a : The array      idx : The array index to set      val : The value to be set set(a, idx, val) Set array item at index, if array has no index at the specified index, the array is filled with na   Parameters:      a : The array      idx : The array index to set      val : The value to be set set(a, idx, val) Set array item at index, if array has no index at the specified index, the array is filled with na   Parameters:      a : The array      idx : The array index to set      val : The value to be set set(a, idx, val) Set array item at index, if array has no index at the specified index, the array is filled with na   Parameters:      a : The array      idx : The array index to set      val : The value to be set set(a, idx, val) Set array item at index, if array has no index at the specified index, the array is filled with na   Parameters:      a : The array      idx : The array index to set      val : The value to be set
مكتبة Pine Script™
من ‎TheBacktestGuy‎
3
FunctionMinkowskiDistanceLibrary "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 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
مكتبة Pine Script™
من ‎RicardoSantos‎
globalCurrently in PineScript you cannot modify global variables in functions because of scope limitations. One way to work around that is to use arrays. This Library simplifies the use of arrays as global variables to make your code look cleaner. If you're coming from other programming languages, I'm sure you will come across this issue in your PineScript journey at some point. ------------------------------------ The code below will throw an error that says: Cannot modify global variable 'price' in function. var price = 0.0 function() => price := 5.5 ------------------------------------ To work around that you can do: var price = array.new_float(1, 0.0) function() => array.set(price, 0, 5.5) But that code does not spark joy. ------------------------------------ So I bring to you the global library: import marspumpkin/global/1 var price = global.init(0.0) function() => global.set(price, 5.5)
مكتبة Pine Script™
من ‎marspumpkin‎
16
FunctionGenerateRandomPointsInShapeLibrary "FunctionGenerateRandomPointsInShape" Generate random vector points in geometric shape (parallelogram, triangle) random_parallelogram(vector_a, vector_b) Generate random vector point in a parallelogram shape.   Parameters:      vector_a : float array, vector of (x, y) shape.      vector_b : float array, vector of (x, y) shape.   Returns: float array, vector of (x, y) shape. random_triangle(vector_a, vector_b) Generate random vector point in a triangle shape.   Parameters:      vector_a : float array, vector of (x, y) shape.      vector_b : float array, vector of (x, y) shape.   Returns: float array, vector of (x, y) shape.
مكتبة Pine Script™
من ‎RicardoSantos‎
1
FunctionArrayNextPreviousLibrary "FunctionArrayNextPrevious" Methods to iterate through a array by a fixed anchor point. array_next(array, start_index) retrieves the next value of the internal pointer index.   Parameters:      array : (any array type), array to iterate.      start_index : int, anchor index to start indexing. array_previous(array, start_index) retrieves the previous value of the internal pointer index.   Parameters:      array : (any array type), array to iterate.      start_index : int, anchor index to start indexing. note: regrettably is not possible to have global reference index without juggling it in the parameters and tracking it externally to switch between next/previous
مكتبة Pine Script™
من ‎RicardoSantos‎
FunctionNNLayerLibrary "FunctionNNLayer" Generalized Neural Network Layer method. function(inputs, weights, n_nodes, activation_function, bias, alpha, scale) Generalized Layer.   Parameters:      inputs : float array, input values.      weights : float array, weight values.      n_nodes : int, number of nodes in layer.      activation_function : string, default='sigmoid', name of the activation function used.      bias : float, default=1.0, bias to pass into activation function.      alpha : float, default=na, if required to pass into activation function.      scale : float, default=na, if required to pass into activation function.   Returns: float
مكتبة Pine Script™
من ‎RicardoSantos‎
FunctionNNPerceptronLibrary "FunctionNNPerceptron" Perceptron Function for Neural networks. function(inputs, weights, bias, activation_function, alpha, scale) generalized perceptron node for Neural Networks.   Parameters:      inputs : float array, the inputs of the perceptron.      weights : float array, the weights for inputs.      bias : float, default=1.0, the default bias of the perceptron.      activation_function : string, default='sigmoid', activation function applied to the output.      alpha : float, default=na, if required for activation.      scale : float, default=na, if required for activation. @outputs float
مكتبة Pine Script™
من ‎RicardoSantos‎
1
MLActivationFunctionsLibrary "MLActivationFunctions" Activation functions for Neural networks. binary_step(value) Basic threshold output classifier to activate/deactivate neuron.   Parameters:      value : float, value to process.   Returns: float linear(value) Input is the same as output.   Parameters:      value : float, value to process.   Returns: float sigmoid(value) Sigmoid or logistic function.   Parameters:      value : float, value to process.   Returns: float sigmoid_derivative(value) Derivative of sigmoid function.   Parameters:      value : float, value to process.   Returns: float tanh(value) Hyperbolic tangent function.   Parameters:      value : float, value to process.   Returns: float tanh_derivative(value) Hyperbolic tangent function derivative.   Parameters:      value : float, value to process.   Returns: float relu(value) Rectified linear unit (RELU) function.   Parameters:      value : float, value to process.   Returns: float relu_derivative(value) RELU function derivative.   Parameters:      value : float, value to process.   Returns: float leaky_relu(value) Leaky RELU function.   Parameters:      value : float, value to process.   Returns: float leaky_relu_derivative(value) Leaky RELU function derivative.   Parameters:      value : float, value to process.   Returns: float relu6(value) RELU-6 function.   Parameters:      value : float, value to process.   Returns: float softmax(value) Softmax function.   Parameters:      value : float array, values to process.   Returns: float softplus(value) Softplus function.   Parameters:      value : float, value to process.   Returns: float softsign(value) Softsign function.   Parameters:      value : float, value to process.   Returns: float elu(value, alpha) Exponential Linear Unit (ELU) function.   Parameters:      value : float, value to process.      alpha : float, default=1.0, predefined constant, controls the value to which an ELU saturates for negative net inputs. .   Returns: float selu(value, alpha, scale) Scaled Exponential Linear Unit (SELU) function.   Parameters:      value : float, value to process.      alpha : float, default=1.67326324, predefined constant, controls the value to which an SELU saturates for negative net inputs. .      scale : float, default=1.05070098, predefined constant.   Returns: float exponential(value) Pointer to math.exp() function.   Parameters:      value : float, value to process.   Returns: float function(name, value, alpha, scale) Activation function.   Parameters:      name : string, name of activation function.      value : float, value to process.      alpha : float, default=na, if required.      scale : float, default=na, if required.   Returns: float derivative(name, value, alpha, scale) Derivative Activation function.   Parameters:      name : string, name of activation function.      value : float, value to process.      alpha : float, default=na, if required.      scale : float, default=na, if required.   Returns: float
مكتبة Pine Script™
من ‎RicardoSantos‎
2
MLLossFunctionsLibrary "MLLossFunctions" Methods for Loss functions. mse(expects, predicts) Mean Squared Error (MSE) " MSE = 1/N * sum ((y - y')^2) ".   Parameters:      expects : float array, expected values.      predicts : float array, prediction values.   Returns: float binary_cross_entropy(expects, predicts) Binary Cross-Entropy Loss (log).   Parameters:      expects : float array, expected values.      predicts : float array, prediction values.   Returns: float
مكتبة Pine Script™
من ‎RicardoSantos‎
PointsLibrary "Points" Provides functions for simplifying operations with collections of x+y coordinates. Where x is typically a bar index or time (millisecond) value. new(size) Creates two arrays. One for X (int ) and another for Y (float ).   Parameters:      size : The initial size of the arrays. size(xA, yA) Checks the size of the arrays and if they're equal returns the size.   Parameters:      xA : The X array.      yA : The Y array. get(xA, yA, index) Gets the X and Y values of the arrays at the index.   Parameters:      xA : The X array.      yA : The Y array.      index : The index.   Returns: set(xA, yA, index, x, y) Sets the X and Y values of the arrays at the index.   Parameters:      xA : The X array.      yA : The Y array.      index : The index.      x : The x value.      y : The y value.   Returns: push(xA, yA, x, y) Adds X and Y values to the end of the arrays (as the last element).   Parameters:      xA : The X array.      yA : The Y array.      x : The x value.      y : The y value.   Returns: unshift(xA, yA, x, y) Adds X and Y values to the beginning of the arrays (as the first element).   Parameters:      xA : The X array.      yA : The Y array.      x : The x value.      y : The y value.   Returns: insert(xA, yA, index, x, y) Inserts X and Y values to the arrays at the index.   Parameters:      xA : The X array.      yA : The Y array.      index : The index to insert at.      x : The x value.      y : The y value.   Returns: pop(xA, yA) Removes the last element from the arrays and returns their value.   Parameters:      xA : The X array.      yA : The Y array.   Returns: shift(xA, yA) Removes the first element from the arrays and returns their value.   Parameters:      xA : The X array.      yA : The Y array.   Returns: remove(xA, yA) Removes the element from the arrays at the index and returns their value.   Parameters:      xA : The X array.      yA : The Y array.   Returns: first(xA, yA) Gets the X and Y values of the first element.   Parameters:      xA : The X array.      yA : The Y array.   Returns: last(xA, yA) Gets the X and Y values of the last element.   Parameters:      xA : The X array.      yA : The Y array.   Returns: allIndexesBetween(xA, lo, hi, start, ordered) Gets the indexes that have values at or above the low value and below the high value.   Parameters:      xA : The X array.      lo : The inclusive low value.      hi : The excluded hi value.      start : The optional index to start the backwards search.      ordered : If true, the search ends when the first value is found that is less than the low. lastIndexBetween(xA, lo, hi, start, ordered) Gets the first found from the end that has a value at or above the low value and below the high value.   Parameters:      xA : The X array.      lo : The inclusive low value.      hi : The excluded hi value.      start : The optional index to start the backwards search.      ordered : If true, the search ends when the first value is found that is less than the low. lastIndexBelow(xA, hi, start) Gets the first found from the end that has a value below the high value.   Parameters:      xA : The X array.      hi : The excluded hi value.      start : The optional index to start the backwards search.
مكتبة Pine Script™
من ‎Electrified‎
eHarmonicpatternsLibrary "eHarmonicpatterns" Library provides an alternative method to scan harmonic patterns. This is helpful in reducing iterations scan_xab(bcdRatio, err_min, err_max, patternArray) Checks if bcd ratio is in range of any harmonic pattern   Parameters:      bcdRatio : AB/XA ratio      err_min : minimum error threshold      err_max : maximum error threshold      patternArray : Array containing pattern check flags. Checks are made only if flags are true. Upon check flgs are overwritten. scan_abc_axc(abcRatio, axcRatio, err_min, err_max, patternArray) Checks if abc or axc ratio is in range of any harmonic pattern   Parameters:      abcRatio : BC/AB ratio      axcRatio : XC/AX ratio      err_min : minimum error threshold      err_max : maximum error threshold      patternArray : Array containing pattern check flags. Checks are made only if flags are true. Upon check flgs are overwritten. scan_bcd(bcdRatio, err_min, err_max, patternArray) Checks if bcd ratio is in range of any harmonic pattern   Parameters:      bcdRatio : CD/BC ratio      err_min : minimum error threshold      err_max : maximum error threshold      patternArray : Array containing pattern check flags. Checks are made only if flags are true. Upon check flgs are overwritten. scan_xad_xcd(xadRatio, xcdRatio, err_min, err_max, patternArray) Checks if xad or xcd ratio is in range of any harmonic pattern   Parameters:      xadRatio : AD/XA ratio      xcdRatio : CD/XC ratio      err_min : minimum error threshold      err_max : maximum error threshold      patternArray : Array containing pattern check flags. Checks are made only if flags are true. Upon check flgs are overwritten. isHarmonicPattern(x, a, c, c, d, flags, errorPercent) Checks for harmonic patterns   Parameters:      x : X coordinate value      a : A coordinate value      c : B coordinate value      c : C coordinate value      d : D coordinate value      flags : flags to check patterns. Send empty array to enable all      errorPercent : Error threshold   Returns: Array of boolean values which says whether valid pattern exist and array of corresponding pattern names isHarmonicProjection(x, a, c, c, flags, errorPercent) Checks for harmonic pattern projection   Parameters:      x : X coordinate value      a : A coordinate value      c : B coordinate value      c : C coordinate value      flags : flags to check patterns. Send empty array to enable all      errorPercent : Error threshold   Returns: Array of boolean values which says whether valid pattern exist and array of corresponding pattern names
مكتبة Pine Script™
من ‎Trendoscope‎
11
hashmapsA simple hashmap implementation for pinescript. It gets your string array and transforms it into a hashmap. Before using it you need to initialize your array with the size you need for your specific case since the size is not dynamic. To use it, first you need to import it the following way: > import marspumpkin/hashmaps/1 Then, initialize your array with the size needed for your specific case: > hashmap = array.new_string(10000) After that you can call: > hashmaps.put() and hashmaps.get() Passing in the array(hashmap), key and value. I hope this helps you in your pinescript journey.
مكتبة Pine Script™
من ‎marspumpkin‎
8
Dictionary/Object LibraryThis Library is aimed to mitigate the limitation of Pinescript having only one structured data type which is only arrays. It lacks data types like Dictionaries(in Python) or Object (in JS) that are standard for other languages. Tuples do exist, but it hardly solves any problem. Working only with Arrays could be overwhelming if your codebase is large. I looked for alternatives to arrays but couldn't find any library. So I coded it myself and it's been working good for me. So I wanted to share it with you all. What does it do: ================== If you are familiar with Python or Javascript, this library tries to immimate Object/Dictonary like structure with Key Value Pairs. For Example: object= {name:"John Doe", age: 28 , org: "PineCoders"} And then it also tries to immitate the Array of Objects (I call it Stack) like this: stack= Array({name:"John Doe", age: 28 , org: "PineCoders"}, {name:"Adam Smith", age: 32 , org: "PineCoders"}, {name:"Paragjyoti Deka", age: 25 , org: "PineCoders"}) So there are basically two ideas: Objects and Stacks. But it looks whole different in Pinescript for obvious reasons. Limitation: The major limitation I couldn't overcome was that, for all of the values: both input and return values for properties will be of string type. This is due to the limiation of Pinecsript that there is no way to return a value on a if-else statement dynamically with different data types. And as the input data type must be explicitly defined when exporting the library functions, only string inputs are allowed. Now that doesn't mean you won't be able to use integer, float or boolens, you just need to pass the string value for it using str.tostring() method. And the output for the getter functions will be in strings as well. But I have added some type conversion methods that you could use from this library itself. From String to Float, String To Integer and String to Boolean: these three methods are included in this library. So basically the whole library is based on a manipulatiion of Array of strings under the hood. /////////////// Usage /////////////// Import the library using this statement: import paragjyoti2012/STR_Dict_Lib/4 as DictLib Objects First define an object using this method: for eample: object1= DictLib.init("name=John,age=26,org=") This is similar to object1= {name:"John",age:"26", org:""} in JS or Python Just like we did here in for "org", you can set initital value to "". But remember to pass string values, even for a numerical properties, like here in "age". You can use "age="+str.tostring(age). If you find it tedious, you can always add properties later on using .set() method. So it could also be initiated like this object= DictLib.init("name=John") and later on DictLib.set(object1,"age", str.toString(age)) DictLib.set(object1,"org", "PineCoders") The getter function looks like this age= DictLib.get(object1,"age") name=DictLib.get(object1,"name") The first argument for all methods .get, .set, and .remove is the pointer (name of the object). /////////////////////////// Array Of Objects (Stacks) /////////////////////////// As I mentioned earlier, I call the array of objects as Stack. Here's how to initialize a Stack. stack= DictLib.initStack(object1) The .initStack() method takes an object pointer as argument. It simply converts the array into a string and pushes it into the newly created stack. Rest of all the methods for Stacks, takes the stack pointer as it's first arument. For example: DictLib.pushStack(stack,object2) The second argument here is the object pointer. It adds the object to it's stack. Although it might feel like a two dimentional array, it's actually an one dimentional array with string values. Under the hood, it looks like this //////////////////// Methods //////////////////// For Objects ------------------- init() : Initializes the object. params: (string) e.g returns: The object ( ) example: object1=DictLib.init("name=John,age=26,org=") ................... get() : Returns the value for given property params: (string object_pointer, string property) returns: string example: age= DictLib.get(object1,"age") ....................... set() : Adds a new property or updates an existing property params: (string object_pointer, string property, string value) returns: void example: DictLib.set(object1,"age", str.tostring(29)) ........................ remove() : Removes a property from the object params : (string object_pointer, string property) returns: void example: DictLib.set(object1,"org") ........................ For Array Of Objects (Stacks) ------------------------------- initStack() : Initializes the stack. params: (string object_pointer) e.g returns: The Stack example: stack= DictLib.initStack(object1) ................... pushToStack() : Adds an object at at last index of the stack params: (string stack_pointer, string object_pointer) returns: void example: DictLib.pushToStack(stack,object2) ....................... popFromStack() : Removes the last object from the stack params: (string stack_pointer) returns: void example: DictLib.popFromStack(stack) ....................... insertToStack() : Adds an object at at the given index of the stack params: (string stack_pointer, string object_pointer, int index) returns: void example: DictLib.insertToStack(stack,object3,1) ....................... removeFromStack() : Removes the object from the given index of the stack params: (string stack_pointer, int index) returns: void example: DictLib.removeFromStack(stack,2) ....................... getElement () : Returns the value for given property from an object in the stack (index must be given) params: (string stack_pointer, int index, string property) returns: string example: ageFromObject1= DictLib.getElement(stack,0,"age") ....................... setElement() : Updates an existing property of an object in the stack (index must be given) params: (string stack_pointer, int index, string property, string value) returns: void example: DictLib.setElement(stack,0,"age", str.tostring(32)) ........................ includesElement() : Checks if any object exists in the stack with the given property-value pair params : (string stack_pointer, string property, string value) returns : Boolean example: doesExist= DictLib.includesElement(stack,"org","PineCoders") ........................ searchStack() : Search for a property-value pair in the stack and returns it's index params: (stringp stack_pointer, string property, string value) returns: int (-1 if doesn't exist) example: index= DictLib.searchElement(stack,"org","PineCoders") /////////////////////// Type Conversion Methods /////////////////////// strToFloat() : Converts String value to Float params: (string value) returns: float example: floatVal= DictLib.strToFloat("57.96") ............................. strToInt() : Converts String value to Integer params: (string value) returns: int example: intVal= DictLib.strToFloat("45") ............................. strToBool() : Converts String value to Boolean params: (string value) returns: boolean example: boolVal= DictLib.strToBool("true") ............................. Points to remember ............... 1. Always pass string values as arguments. 2. The return values will be of type string, so convert them before to avoid typecasting conflict. 3. Horses can't vomit. More Informations ==================== Yes, You can store this objects and stacks for persisting through the iterations of a script across successive bars. You just need to set the variable using "var" keyword. Remember this objects and stacks are just arrays, so any methods and properties an array have it pinescript, would be applicable for objects and stacks. It can also be used in security functions without any issues for MTF Analysis. If you have any suggestions or feedback, please comment on the thread, I would surely be happy to help.
مكتبة Pine Script™
من ‎CyberMensch‎
20