Mulai

Arrays

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
Perpustakaan Pine Script®
oleh 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
Perpustakaan Pine Script®
oleh 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
Perpustakaan Pine Script®
oleh 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
Perpustakaan Pine Script®
oleh 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.
Perpustakaan Pine Script®
oleh 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
Perpustakaan Pine Script®
oleh 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.
Perpustakaan Pine Script®
oleh 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.
Perpustakaan Pine Script®
oleh CyberMensch
20
FunctionPeakDetectionLibrary "FunctionPeakDetection" Method used for peak detection, similar to MATLAB peakdet method function(sample_x, sample_y, delta) Method for detecting peaks.   Parameters:      sample_x : float array, sample with indices.      sample_y : float array, sample with data.      delta : float, positive threshold value for detecting a peak.   Returns: tuple with found max/min peak indices.
Perpustakaan Pine Script®
oleh RicardoSantos
17
AveragesLibrary "Averages" Contains utilities for generating averages from arrays. Useful for manipulated or cleaned data. triangular(src, startingWeight) Calculates the triangular weighted average of a set of values where the last value has the highest weight.   Parameters:      src : The array to derive the average from.      startingWeight : The weight to begin with when calculating the average. Higher numbers will decrease the bias. weighted(src, weights, weightDefault) Calculates the weighted average of a set of values.   Parameters:      src : The array to derive the average from.      weights : The array containing the weights for the source.      weightDefault : The default value to use when a weight is NA. triangularWeighted(src, weights, startingWeight) Calculates the weighted average of a set of values where the last value has the highest triangular multiple.   Parameters:      src : The array to derive the average from.      weights : The array containing the weights for the source.      startingWeight : The multiple to begin with when calculating the average. Higher numbers will decrease the bias. exponential(src) Calculates the exponential average of a set of values where the last value has the highest weight.   Parameters:      src : The array to derive the average from. arrayFrom(src, len, omitNA) Creates an array from the provided series (oldest to newest).   Parameters:      src : The array to derive from.      len : The target length of the array.      omitNA : If true, NA values will not be added to the array and the resultant array may be shorter than the target length.
Perpustakaan Pine Script®
oleh Electrified
1
arrayutilsLibrary "_arrayutils" Library contains utility functions using arrays. delete(​arr, index)   remove an item from array at specific index. Also deletes the item   Parameters:      arr : - array from which the item needs to be deleted      index : - index of item to be deleted   Returns: void pop(​arr)   remove the last item from array. Also deletes the item   Parameters:      arr : - array from which the last item needs to be removed and deleted   Returns: void shift(​arr)   remove an item from array at index 0. Also deletes the item   Parameters:      arr : - array from which the first item needs to be removed and deleted   Returns: void unshift(​arr, val, maxItems)   add an item to the beginning of an array with max items cap   Parameters:      arr : - array to which the item needs to be added at the beginning      val : - value of item which needs to be added      maxItems : - max items array can hold. After that, items are removed from the other end   Returns: resulting array clear(​arr)   remove and delete all items in an array   Parameters:      arr : - array which needs to be cleared   Returns: void push(​arr, val, maxItems)   add an item to the end of an array with max items cap   Parameters:      arr : - array to which the item needs to be added at the beginning      val : - value of item which needs to be added      maxItems : - max items array can hold. After that, items are removed from the starting index   Returns: resulting array check_overflow(pivots, barArray, dir)   finds difference between two timestamps   Parameters:      pivots : pivots array      barArray : pivot bar array      dir : direction for which overflow need to be checked   Returns: bool overflow get_trend_series(pivots, length, highLow, trend)   finds series of pivots in particular trend   Parameters:      pivots : pivots array      length : length for which trend series need to be checked      highLow : filter pivot high or low      trend : Uptrend or Downtrend   Returns: int trendIndexes get_trend_series(pivots, firstIndex, lastIndex)   finds series of pivots in particular trend   Parameters:      pivots : pivots array      firstIndex : First index of the series      lastIndex : Last index of the series   Returns: int trendIndexes sma(source)   calculates sma for elements in array   Parameters:      source : source array   Returns: float sma ema(source, length)   calculates ema for elements in array   Parameters:      source : source array      length : ema length   Returns: float ema rma(source, length)   calculates rma for elements in array   Parameters:      source : source array      length : rma length   Returns: float rma wma(source, length)   calculates wma for elements in array   Parameters:      source : source array      length : wma length   Returns: float wma hma(source, length)   calculates hma for elements in array   Parameters:      source : source array      length : hma length   Returns: float hma ma(source, matype, length)   wrapper for all moving averages based on array   Parameters:      source : source array      matype : moving average type. Valud values are: sma, ema, rma, wma and hma      length : moving average length length   Returns: float moving average getFibSeries(numberOfFibs, start)   gets fib series in array   Parameters:      numberOfFibs : number of fibs      start : starting number   Returns: float fibArray
Perpustakaan Pine Script®
oleh Trendoscope
9
Signal_Data_2021_09_09__2021_11_18Library "Signal_Data_2021_09_09__2021_11_18" Functions to support my timing signals system import_start_time(harmonic) get the start time for each harmonic signal   Parameters:      harmonic : is an integer identifying the harmonic   Returns: the starting timestamp of the harmonic data import_signal(index, harmonic) access point for pre-processed data imported here by copy paste   Parameters:      index : is the current data index, use 0 to initialize      harmonic : is the data set to index, use 0 to initialize   Returns: the data from the indicated harmonic array starting at index, and the starting timestamp of that data
Perpustakaan Pine Script®
oleh ubiquity
cacheLibrary "cache" A simple cache library to store key value pairs. Fed up of injecting and returning so many values all the time? Want to separate your code and keep it clean? Need to make an expensive calculation and use the results in numerous places? Want to throttle calculations or persist random values across bars or ticks? Then you've come to the right place. Or not! Up to you, I don't mind either way... ;) Check the helpers and unit tests in the script for further detail. Detailed Interface init(persistant) Initialises the syncronised cache key and value arrays   Parameters:      persistant : bool, toggles data persistance between bars and ticks   Returns: [string , float ], a tuple of both arrays set(keys, values, key, value) Sets a value into the cache   Parameters:      keys : string , the array of cache keys      values : float , the array of cache values      key : string, the cache key to create or update      value : float, the value to set has(keys, values, key) Checks if the cache has a key   Parameters:      keys : string , the array of cache keys      values : float , the array of cache values      key : string, the cache key to check   Returns: bool, true only if the key is found get(keys, values, key) Gets a keys value from the cache   Parameters:      keys : string , the array of cache keys      values : float , the array of cache values      key : string, the cache key to get   Returns: float, the stored value remove(keys, values, key) Removes a key and value from the cache   Parameters:      keys : string , the array of cache keys      values : float , the array of cache values      key : string, the cache key to remove count() Counts how many key value pairs in the cache   Returns: int, the total number of pairs loop(keys, values) Returns true for each value in the cache (use as the while loop expression)   Parameters:      keys : string , the array of cache keys      values : float , the array of cache values next(keys, values) Returns each key value pair on successive calls (use in the while loop)   Parameters:      keys : string , the array of cache keys      values : float , the array of cache values   Returns: , tuple of each key value pair clear(keys, values) Clears all key value pairs from the cache   Parameters:      keys : string , the array of cache keys      values : float , the array of cache values unittest_cache(case) Cache module unit tests, for inclusion in parent script test suite. Usage: log.unittest_cache(__ASSERTS)   Parameters:      case : string , the current test case and array of previous unit tests (__ASSERTS) unittest(verbose) Run the cache module unit tests as a stand alone. Usage: cache.unittest()   Parameters:      verbose : bool, optionally disable the full report to only display failures
Perpustakaan Pine Script®
oleh GeoffHammond
3
ArrayMultipleDimensionPrototypeLibrary "ArrayMultipleDimensionPrototype" A prototype library for Multiple Dimensional array methods index_md_to_1d() new_float(dimensions, initial_size) Creates a variable size multiple dimension array.   Parameters:      dimensions : int array, dimensions of array.      initial_size : float, default=na, initial value of the array.   Returns: float array dimensions(id, value) set value of a element in a multiple dimensions array.   Parameters:      id : float array, multiple dimensions array.      value : float, new value.   Returns: float. get(id) get value of a multiple dimensions array.   Parameters:      id : float array, multiple dimensions array.   Returns: float. set(id) set value of a element in a multiple dimensions array.   Parameters:      id : float array, multiple dimensions array.   Returns: float.
Perpustakaan Pine Script®
oleh RicardoSantos
5
FunctionArrayReduceLibrary "FunctionArrayReduce" A limited method to reduce a array using a mathematical formula. float_(formula, samples, arguments, initial_value) Method to reduce a array using a mathematical formula.   Parameters:      formula : string, the mathematical formula, accepts some default name codes (index, output, previous, current, integer index of arguments array).      samples : float array, the data to process.      arguments : float array, the extra arguments of the formula.      initial_value : float, default=0, a initial base value for the process.   Returns: float. Notes: ** if initial value is specified as "na" it will default to the first element of samples.
Perpustakaan Pine Script®
oleh RicardoSantos
FunctionElementsInArrayLibrary "FunctionElementsInArray" Methods to count number of elements in arrays count_float(sample, value) Counts the number of elements equal to provided value in array.   Parameters:      sample : float array, sample data to process.      value : float value to check for equality.   Returns: int. count_int(sample, value) Counts the number of elements equal to provided value in array.   Parameters:      sample : int array, sample data to process.      value : int value to check for equality.   Returns: int. count_string(sample, value) Counts the number of elements equal to provided value in array.   Parameters:      sample : string array, sample data to process.      value : string value to check for equality.   Returns: int. count_bool(sample, value) Counts the number of elements equal to provided value in array.   Parameters:      sample : bool array, sample data to process.      value : bool value to check for equality.   Returns: int. count_color(sample, value) Counts the number of elements equal to provided value in array.   Parameters:      sample : color array, sample data to process.      value : color value to check for equality.   Returns: int. extract_indices_float(sample, value) Counts the number of elements equal to provided value in array, and returns its indices.   Parameters:      sample : float array, sample data to process.      value : float value to check for equality.   Returns: int. extract_indices_int(sample, value) Counts the number of elements equal to provided value in array, and returns its indices.   Parameters:      sample : int array, sample data to process.      value : int value to check for equality.   Returns: int. extract_indices_string(sample, value) Counts the number of elements equal to provided value in array, and returns its indices.   Parameters:      sample : string array, sample data to process.      value : string value to check for equality.   Returns: int. extract_indices_bool(sample, value) Counts the number of elements equal to provided value in array, and returns its indices.   Parameters:      sample : bool array, sample data to process.      value : bool value to check for equality.   Returns: int. extract_indices_color(sample, value) Counts the number of elements equal to provided value in array, and returns its indices.   Parameters:      sample : color array, sample data to process.      value : color value to check for equality.   Returns: int.
Perpustakaan Pine Script®
oleh RicardoSantos
4
amibrokerLibrary "amibroker" This library consists of functions from amibroker that doesn't exist on tradingview pinescript. The example of these are the ExRem and Flip. In the example below, I used ExRem to remove the excessive buy and sell signals. Meanwhile, I used the Flip to highlight the bg color when there is an open position. exrem(series1, series2) Removes excessive signals. Pinescript version of ExRem in Amibroker (www.amibroker.com)   Parameters:      series1 : boolean      series2 : boolean   Returns: boolean flip(series1, series2) works as a flip/flop device or "latch". Pinescript version of Flip in Amibroker: (www.amibroker.com)   Parameters:      series1 : boolan      series2 : boolean   Returns: boolean.
Perpustakaan Pine Script®
oleh yourtradingbuddy
3
FunctionCompoundInterestLibrary "FunctionCompoundInterest" Method for compound interest. simple_compound(principal, rate, duration) Computes compound interest for given duration.   Parameters:      principal : float, the principal or starting value.      rate : float, the rate of interest.      duration : float, the period of growth.   Returns: float. variable_compound(principal, rates, duration) Computes variable compound interest for given duration.   Parameters:      principal : float, the principal or starting value.      rates : float array, the rates of interest.      duration : int, the period of growth.   Returns: float array. simple_compound_array(principal, rates, duration) Computes variable compound interest for given duration.   Parameters:      principal : float, the principal or starting value.      rates : float array, the rates of interest.      duration : int, the period of growth.   Returns: float array. variable_compound_array(principal, rates, duration) Computes variable compound interest for given duration.   Parameters:      principal : float, the principal or starting value.      rates : float array, the rates of interest.      duration : int, the period of growth.   Returns: float array.
Perpustakaan Pine Script®
oleh RicardoSantos
1
FunctionSMCMCLibrary "FunctionSMCMC" Methods to implement Markov Chain Monte Carlo Simulation (MCMC) markov_chain(weights, actions, target_path, position, last_value) a basic implementation of the markov chain algorithm   Parameters:      weights : float array, weights of the Markov Chain.      actions : float array, actions of the Markov Chain.      target_path : float array, target path array.      position : int, index of the path.      last_value : float, base value to increment.   Returns: void, updates target array mcmc(weights, actions, start_value, n_iterations) uses a monte carlo algorithm to simulate a markov chain at each step.   Parameters:      weights : float array, weights of the Markov Chain.      actions : float array, actions of the Markov Chain.      start_value : float, base value to start simulation.      n_iterations : integer, number of iterations to run.   Returns: float array with path.
Perpustakaan Pine Script®
oleh RicardoSantos
2
FunctionGeometricLineDrawingsLibrary "FunctionGeometricLineDrawings" array_delete_all_lines(lines) deletes all lines in array.   Parameters:      lines : line array, array with line objects to delete.   Returns: void. triangle(sample_x, sample_y, xloc, extend, color, style, width) Draw a Triangle with 3 vector2D(x, y) coordinates.   Parameters:      sample_x : int array, triangle sample data X coordinate values.      sample_y : float array, triangle sample data Y coordinate values.      xloc : string, defaultoptions=xloc.bar_index, xloc.bar_time.      extend : string, default=extend.none, options=(extend.none, extend.right, extend.left, extend.both).      color : color, default=      style : options line.style_solid, line.style_dotted, line.style_dashed, line.style_arrow_left, line.style_arrow_right, line.style_arrow_both      width : width in pixels.   Returns: line array trapezoid(sample_x, sample_y, xloc, extend, color, style, width) Draw a Trapezoid with 4 vector2D(x, y) coordinates:   Parameters:      sample_x : int array, trapezoid sample data X coordinate values.      sample_y : float array, trapezoid sample data Y coordinate values.      xloc : string, defaultoptions=xloc.bar_index, xloc.bar_time.      extend : string, default=extend.none, options=(extend.none, extend.right, extend.left, extend.both).      color : color, default=      style : options line.style_solid, line.style_dotted, line.style_dashed, line.style_arrow_left, line.style_arrow_right, line.style_arrow_both      width : width in pixels.   Returns: line array
Perpustakaan Pine Script®
oleh RicardoSantos
2