Auf geht's

Indikatoren und Strategien

pandas_taLibrary "pandas_ta" Level: 3 Background Today is the first day of 2022 and happy new year every tradingviewers! May health and wealth go along with you all the time. I use this chance to publish my 1st PINE v5 lib : pandas_ta This is not a piece of cake like thing, which cost me a lot of time and efforts to build this lib. Beyond 300 versions of this script was iterated in draft. Function Library "pandas_ta" PINE v5 Counterpart of Pandas TA - A Technical Analysis Library in Python 3 at github.com The Original Pandas Technical Analysis (Pandas TA) is an easy to use library that leverages the Pandas package with more than 130 Indicators and Utility functions and more than 60 TA Lib Candlestick Patterns. I realized most of indicators except Candlestick Patterns because tradingview built-in Candlestick Patterns are even more powerful! I use this to verify pandas_ta python version indicators for myself, but I realize that maybe many may need similar lib for pine v5 as well. Function Brief Descriptions (Pls find details in script comments) bton --> Binary to number wcp --> Weighted Closing Price (WCP) counter --> Condition counter xbt --> Between ebsw --> Even Better SineWave (EBSW) ao --> Awesome Oscillator (AO) apo --> Absolute Price Oscillator (APO) xrf --> Dynamic shifted values bias --> Bias (BIAS) bop --> Balance of Power (BOP) brar --> BRAR (BRAR) cci --> Commodity Channel Index (CCI) cfo --> Chande Forcast Oscillator (CFO) cg --> Center of Gravity (CG) cmo --> Chande Momentum Oscillator (CMO) coppock --> Coppock Curve (COPC) cti --> Correlation Trend Indicator (CTI) dmi --> Directional Movement Index(DMI) er --> Efficiency Ratio (ER) eri --> Elder Ray Index (ERI) fisher --> Fisher Transform (FISHT) inertia --> Inertia (INERTIA) kdj --> KDJ (KDJ) kst --> 'Know Sure Thing' (KST) macd --> Moving Average Convergence Divergence (MACD) mom --> Momentum (MOM) pgo --> Pretty Good Oscillator (PGO) ppo --> Percentage Price Oscillator (PPO) psl --> Psychological Line (PSL) pvo --> Percentage Volume Oscillator (PVO) qqe --> Quantitative Qualitative Estimation (QQE) roc --> Rate of Change (ROC) rsi --> Relative Strength Index (RSI) rsx --> Relative Strength Xtra (rsx) rvgi --> Relative Vigor Index (RVGI) slope --> Slope smi --> SMI Ergodic Indicator (SMI) sqz* --> Squeeze (SQZ) * NOTE: code sufferred from very strange error, code was commented. sqz_pro --> Squeeze PRO(SQZPRO) xfl --> Condition filter stc --> Schaff Trend Cycle (STC) stoch --> Stochastic (STOCH) stochrsi --> Stochastic RSI (STOCH RSI) trix --> Trix (TRIX) tsi --> True Strength Index (TSI) uo --> Ultimate Oscillator (UO) willr --> William's Percent R (WILLR) alma --> Arnaud Legoux Moving Average (ALMA) xll --> Dynamic rolling lowest values dema --> Double Exponential Moving Average (DEMA) ema --> Exponential Moving Average (EMA) fwma --> Fibonacci's Weighted Moving Average (FWMA) hilo --> Gann HiLo Activator(HiLo) hma --> Hull Moving Average (HMA) hwma --> HWMA (Holt-Winter Moving Average) ichimoku --> Ichimoku Kinkō Hyō (ichimoku) jma --> Jurik Moving Average Average (JMA) kama --> Kaufman's Adaptive Moving Average (KAMA) linreg --> Linear Regression Moving Average (linreg) mgcd --> McGinley Dynamic Indicator rma --> wildeR's Moving Average (RMA) sinwma --> Sine Weighted Moving Average (SWMA) ssf --> Ehler's Super Smoother Filter (SSF) © 2013 supertrend --> Supertrend (supertrend) xsa --> X simple moving average swma --> Symmetric Weighted Moving Average (SWMA) t3 --> Tim Tillson's T3 Moving Average (T3) tema --> Triple Exponential Moving Average (TEMA) trima --> Triangular Moving Average (TRIMA) vidya --> Variable Index Dynamic Average (VIDYA) vwap --> Volume Weighted Average Price (VWAP) vwma --> Volume Weighted Moving Average (VWMA) wma --> Weighted Moving Average (WMA) zlma --> Zero Lag Moving Average (ZLMA) entropy --> Entropy (ENTP) kurtosis --> Rolling Kurtosis skew --> Rolling Skew xev --> Condition all zscore --> Rolling Z Score adx --> Average Directional Movement (ADX) aroon --> Aroon & Aroon Oscillator (AROON) chop --> Choppiness Index (CHOP) xex --> Condition any cksp --> Chande Kroll Stop (CKSP) dpo --> Detrend Price Oscillator (DPO) long_run --> Long Run psar --> Parabolic Stop and Reverse (psar) short_run --> Short Run vhf --> Vertical Horizontal Filter (VHF) vortex --> Vortex accbands --> Acceleration Bands (ACCBANDS) atr --> Average True Range (ATR) bbands --> Bollinger Bands (BBANDS) donchian --> Donchian Channels (DC) kc --> Keltner Channels (KC) massi --> Mass Index (MASSI) natr --> Normalized Average True Range (NATR) pdist --> Price Distance (PDIST) rvi --> Relative Volatility Index (RVI) thermo --> Elders Thermometer (THERMO) ui --> Ulcer Index (UI) ad --> Accumulation/Distribution (AD) cmf --> Chaikin Money Flow (CMF) efi --> Elder's Force Index (EFI) ecm --> Ease of Movement (EOM) kvo --> Klinger Volume Oscillator (KVO) mfi --> Money Flow Index (MFI) nvi --> Negative Volume Index (NVI) obv --> On Balance Volume (OBV) pvi --> Positive Volume Index (PVI) dvdi --> Dual Volume Divergence Index (DVDI) xhh --> Dynamic rolling highest values pvt --> Price-Volume Trend (PVT) Remarks I also incorporated func descriptions and func test script in commented mode, you can test the functino with the embedded test script and modify them as you wish. This is a Level 3 free and open source indicator library. Feedbacks are appreciated. This is not the end of pandas_ta lib publication, but it is start point with pine v5 lib function and I will add more and more funcs into this lib for my own indicators. Function Name List: bton() wcp() count() xbt() ebsw() ao() apo() xrf() bias() bop() brar() cci() cfo() cg() cmo() coppock() cti() dmi() er() eri() fisher() inertia() kdj() kst() macd() mom() pgo() ppo() psl() pvo() qqe() roc() rsi() rsx() rvgi() slope() smi() sqz_pro() xfl() stc() stoch() stochrsi() trix() tsi() uo() willr() alma() wcx() xll() dema() ema() fwma() hilo() hma() hwma() ichimoku() jma() kama() linreg() mgcd() rma() sinwma() ssf() supertrend() xsa() swma() t3() tema() trima() vidya() vwap() vwma() wma() zlma() entropy() kurtosis() skew() xev() zscore() adx() aroon() chop() xex() cksp() dpo() long_run() psar() short_run() vhf() vortex() accbands() atr() bbands() donchian() kc() massi() natr() pdist() rvi() thermo() ui() ad() cmf() efi() ecm() kvo() mfi() nvi() obv() pvi() dvdi() xhh() pvt()
Pine Script® Bibliothek
von blackcat1402
20
TimeLockedMALibrary "TimeLockedMA" Library & function(s) which generates a moving average that stays locked to users desired time preference. TODO - Add functionality for more moving average types. IE: smooth, weighted etc... Example: time_locked_ma(close, length=1, timeframe='days', type='ema') Will generate a 1 day exponential moving average that will stay consistent across all chart intervals. Error Handling On small time frames with large moving averages (IE: 1min chart with a 50 week moving average), you'll get a study error that says "(function "sma") references too many candles in history" . To fix this, make sure you have timeframe="" as an indicator() header. Next, in the indicator settings, increase the timeframe from to a higher interval until the error goes away. By default, it's set to "Chart". Bringing the interval up to 1hr will usually solve the issue. Furthermore, adding timeframe_gaps=false to your indicator() header will give you an approximation of real-time values. Misc Info For time_lock_ma() setting type='na' will return the relative length value that adjusts dynamically to user's chart time interval. This is good for plugging into other functions where a lookback or length is required. (IE: Bollinger Bands) time_locked_ma(source, length, timeframe, type) Creates a moving average that is locked to a desired timeframe   Parameters:      source : float, Moving average source      length : int, Moving average length      timeframe : string, Desired timeframe. Use: "minutes", "hours", "days", "weeks", "months", "chart"      type : string, string Moving average type. Use "SMA" (default) or "EMA". Value of "NA" will return relative lookback length.   Returns: moving average that is locked to desired timeframe. timeframe_convert(t, a, b) Converts timeframe to desired timeframe. From a --> b   Parameters:      t : int, Time interval      a : string, Time period      b : string, Time period to convert to   Returns: Converted timeframe value chart_time(timeframe_period, timeframe_multiplier) Separates timeframe.period function and returns chart interval and period   Parameters:      timeframe_period : string, timeframe.period      timeframe_multiplier : int, timeframe.multiplier Enjoy :)
Pine Script® Bibliothek
von JBroadway
2
The Divergent LibraryLibrary "TheDivergentLibrary" The Divergent Library is only useful when combined with the Pro version of The Divergent - Advanced divergence indicator . This is because the Basic (free) version of The Divergent does not expose the "Divergence Signal" value. Usage instructions: 1. Create a new chart 2. Add The Divergent (Pro) indicator to your chart 3. Create a new strategy, import this library, add a "source" input, link it to "The Divergent: Divergence Signal", and use the library to decode the divergence signals from The Divergent (You can find example strategy code published in our profile) 4. Act on the divergences signalled by The Divergent --- isRegularBullishEnabled(context) Returns a boolean value indicating whether Regular Bullish divergence detection is enabled in The Divergent.   Parameters:      context : The context of The Divergent Library.   Returns: A boolean value indicating whether Regular Bullish divergence detection is enabled in The Divergent. isHiddenBullishEnabled(context) Returns a boolean value indicating whether Hidden Bullish divergence detection is enabled in The Divergent.   Parameters:      context : The context of The Divergent Library.   Returns: A boolean value indicating whether Hidden Bullish divergence detection is enabled in The Divergent. isRegularBearishEnabled(context) Returns a boolean value indicating whether Regular Bearish divergence detection is enabled in The Divergent.   Parameters:      context : The context of The Divergent Library.   Returns: A boolean value indicating whether Regular Bearish divergence detection is enabled in The Divergent. isHiddenBearishEnabled(context) Returns a boolean value indicating whether Hidden Bearish divergence detection is enabled in The Divergent.   Parameters:      context : The context of The Divergent Library.   Returns: A boolean value indicating whether Hidden Bearish divergence detection is enabled in The Divergent. getPivotDetectionSource(context) Returns the 'Pivot Detection Source' setting of The Divergent. The returned value can be either "Oscillator" or "Price".   Parameters:      context : The context of The Divergent Library.   Returns: One of the following string values: "Oscillator" or "Price". getPivotDetectionMode(context) Returns the 'Pivot Detection Mode' setting of The Divergent. The returned value can be either "Bodies" or "Wicks".   Parameters:      context : The context of The Divergent Library.   Returns: One of the following string values: "Bodies" or "Wicks". isLinked(context) Returns a boolean value indicating the link status to The Divergent indicator.   Parameters:      context : The context of The Divergent Library.   Returns: A boolean value indicating the link status to The Divergent indicator. init(firstBarSignal, displayLinkStatus, debug) Initialises The Divergent Library's context with the signal produced by The Divergent on the first bar. The value returned from this function is called the "context of The Divergent Library". Some of the other functions of this library requires you to pass in this context.   Parameters:      firstBarSignal : The signal from The Divergent indicator on the first bar.      displayLinkStatus : A boolean value indicating whether the Link Status window should be displayed in the bottom left corner of the chart. Defaults to true.      debug : A boolean value indicating whether the Link Status window should display debug information. Defaults to false.   Returns: A bool array containing the context of The Divergent Library. processSignal(signal) Processes a signal from The Divergent and returns a 5-tuple with the decoded signal: [ int divergenceType, int priceBarIndexStart, int priceBarIndexEnd, int oscillatorBarIndexStart, int oscillatorBarIndexEnd]. `divergenceType` can be one of the following values: na → No divergence was detected, 1 → Regular Bullish, 2 → Regular Bullish early, 3 → Hidden Bullish, 4 → Hidden Bullish early, 5 → Regular Bearish, 6 → Regular Bearish early, 7 → Hidden Bearish, 8 → Hidden Bearish early.   Parameters:      signal : The signal from The Divergent indicator.   Returns: A 5-tuple with the following values: [ int divergenceType, int priceBarIndexStart, int priceBarIndexEnd, int oscillatorBarIndexStart, int oscillatorBarIndexEnd].
Pine Script® Bibliothek
von WhiteboxSoftware
2
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.
Pine Script® Bibliothek
von 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
Pine Script® Bibliothek
von RicardoSantos
VolatilityCheckerLibrary "VolatilityChecker" Volatility is judged to be high when the range of one period is greater than the ATR of another period. is_high(_periods, _smooth, _atr_periods, _atr_times) Return true if the volatility is high.   Parameters:      _periods : Range Period      _smooth : Smoothes the range width.      _atr_periods : ATR Period      _atr_times : Amplify the calculated ATR.   Returns: {Boolean} is_low()
Pine Script® Bibliothek
von boitoki
SetSessionTimesLibrary "SetSessionTimes" Function to automatically set session times for symbols and eventually timezone. Useful mainly for futures contracts, to differentiate between pit and overnight sessions, and for 24 hours symbols if you want to "create" sessions for them This library only returns correct session times to the calling script and does nothing by itself on the chart. the calling script must then use the returned session times to do anything. For example, in the attached chart this library is used by my initial balance indicator, which calls it to retrieve the correct session times for the selected symbol in the chart, given that different futures contracts have different pit session times (RTH times) and Tradingview hasn't implemented that yet. SetSessionTimes()
Pine Script® Bibliothek
von czoa
2
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
Pine Script® Bibliothek
von 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
Pine Script® Bibliothek
von 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
Pine Script® Bibliothek
von 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
Pine Script® Bibliothek
von RicardoSantos
Debug_Window_LibraryLibrary "Debug_Window_Library" Provides a framework for logging debug information to a window on the chart. consoleWrite(txt, maxLines) Adds a line of text to the debug window. The text is rolled off the bottom of the window as it fills up.   Parameters:      txt : - this is the text to be appended to the window      maxLines : - this is the size of the window in lines.   Returns: nothing The example above shows the close value for the last 10 bars. Here's the code. //@version=5 indicator("Debug Library test Script", overlay=true) import sp2432/Debug_Window_Library/1 as dbg // add some text to the debug window dbg .consoleWrite( str .tostring(close), 10)
Pine Script® Bibliothek
von sp2432
1
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.
Pine Script® Bibliothek
von 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
Pine Script® Bibliothek
von Trendoscope
11
OteHmacSha256Library "OteHmacSha256" Library to use HMAC SHA-256 by OgahTerkenal hmac_sha256(string) HMAC SHA-256   Parameters:      string : msg String to be hashed   Returns: Return a hashed string in hex format and an array of 8 32 bits integer Library to use HMAC SHA-256 for authenticating alert message going out from TradingView. It has limitation on allowed characters (because PineScript cannot access the underlying bits of each ASCII) from ASCII 32 to 126 only. Usage Example section at the end of the source code pretty much tell everything about this library. General example as how to import to your PineScript code is not included (please refer to the PineScript manual).
Pine Script® Bibliothek
von OgahTerkenal
8
StocksDeveloper_AutoTraderWebLibrary "StocksDeveloper_AutoTraderWeb" AutoTrader Web trading API functions implementation for Trading View. preparePlaceOrderJson(account, symbol, group, variety) Prepare a place order json   Parameters:      account : Pseudo or group account number      symbol : AutoTrader Web's stock/derivative symbol      group : Set it to true to use group account (Default: false)      variety : Variety (Default: REGULAR)   Returns: A json message for the given order data preparePlaceOrderAlertUsingOrderJson(orderJsonArray) Prepare a place order alert message using order json array   Parameters:      orderJsonArray : Order json can contain one or more orders   Returns: A complete alert message to place orders preparePlaceOrderAlertMessage(account, symbol, group, variety, validity) Prepare a place order alert json message   Parameters:      account : Pseudo or group account number      symbol : AutoTrader Web's stock/derivative symbol      group : Set it to true to use group account (Default: false)      variety : Variety (Default: REGULAR)      validity : Validity (Default: DAY)   Returns: A complete alert message to place orders
Pine Script® Bibliothek
von Pritesh-StocksDeveloper
5
Woodwind VaultLibrary "WoodwindVault" Woodwind Vault provides reusable functions to support Thange Woodwind Playbook execution. getHighestHighAndLowestLow(period) determines the highest-high and lowest-low for the specified time interval.   Parameters:      period : int, the time interval for finding the highest-high and lowest-low.   Returns: float, the highest-high and lowest-low of the candles in the specified period. findEquilibrium() projects a one glance view of the entire resistance net faced by the price. It does so by computing different equilibrium points for the price.   Returns: longTermEquilibriumB float, the midpoint of highest-high and lowest-low of the candles in last longTermPeriod. getGlance(fast, slow) glances over the 2 equilibrium points from moving averages and establishes whether its bullish or bearish.   Parameters:      fast : float, the fast moving point.      slow : float, the slow moving point.   Returns: string, it is "bullish" if fast moving point is over the slow moving point o/w returns "bearish". positionRelativeToLevel(point, level) determines first point's position w.r.t a specified level.   Parameters:      point : float, the first point (typically a fast moving average).      level : float, the second point acting as a level (typically a slow moving average).   Returns: string, the above/below/at position w.r.t level. positionRelativeToRange(point, fromLevel, toLevel) determines first point's position w.r.t a range (typically a resistance band).   Parameters:      point : float, the first point.      fromLevel : float, the from-range which is typically a fast moving line.      toLevel : float, the to-range which is typically a slow moving line.   Returns: string, the above/below/within range.
Pine Script® Bibliothek
von govindthange
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.
Pine Script® Bibliothek
von marspumpkin
8
DivergenceLibrary "Divergence" Calculates a divergence between 2 series bullish(_src, _low, depth) Calculates bullish divergence   Parameters:      _src : Main series      _low : Comparison series (`low` is used if no argument is supplied)      depth : Fractal Depth (`2` is used if no argument is supplied)   Returns: 2 boolean values for regular and hidden divergence bearish(_src, _high, depth) Calculates bearish divergence   Parameters:      _src : Main series      _high : Comparison series (`high` is used if no argument is supplied)      depth : Fractal Depth (`2` is used if no argument is supplied)   Returns: 2 boolean values for regular and hidden divergence I created this library to plug and play divergences in any code. You can create a divergence indicator from any series you like. Fractals are used to pinpoint the edge of the series. The higher the depth, the slower the divergence updates get. My Plain Stochastic Divergence uses the same calculation. Watch it in action.
Pine Script® Bibliothek
von DevLucem
9