zigzag⬜ Zigzag at your fingertips.
Creating zigzag array is more simpler than ever. All you need to do is:
▶ Import library:
import HeWhoMustNotBeNamed// as zgi
▶ And invoke zigzag to get all the details.
zgi.drawzigzag(zigzagLength)
More examples in the code where you can get retracement ratios, zigzag direction, divergence etc.
Library "zigzag"
Library dedicated to zigzags and related indicators
zigzag(length, numberOfPivots, useAlternativeSource, source, oscillatorSource, directionBias) zigzag: Calculates zigzag pivots and generates an array
Parameters:
length : : Zigzag Length
numberOfPivots : : Max number of pivots to return in the array. Default is 20
useAlternativeSource : : If set uses the source for genrating zigzag. Default is false
source : : Alternative source used only if useAlternativeSource is set to true. Default is close
oscillatorSource : : Oscillator source for calculating divergence
directionBias : : Direction bias for calculating divergence
Returns:
zigzagpivots : Array containing zigzag pivots
zigzagpivotbars : Array containing zigzag pivot bars
zigzagpivotdirs : Array containing zigzag pivot directions (Lower High : 1, Higher High : 2, Lower Low : -2 and Higher Low : -1)
zigzagpivotratios : Array containing zigzag retracement ratios for each pivot
zigzagoscillators : Array of oscillator values at pivots. Will have valid values only if valid oscillatorSource is provided as per input.
zigzagoscillatordirs : Array of oscillator directions (HH, HL, LH, LL) at pivots. Will have valid values only if valid oscillatorSource is provided as per input.
zigzagtrendbias : Array of trend bias at pivots. Will have valid value only if directionBias series is sent in input parameters
zigzagdivergence : Array of divergence sentiment at each pivot. Will have valid values only if oscillatorSource and directionBias inputs are provided
newPivot : Returns true if new pivot created
doublePivot : Returns true if two new pivots are created on same bar (Happens in case of candles with long wicks and shorter zigzag lengths)
drawzigzag(length, numberOfPivots, , source, linecolor, linewidth, linestyle, oscillatorSource, directionBias, showHighLow, showRatios, showDivergence) drawzigzag: Calculates and draws zigzag pivots
Parameters:
length : : Zigzag Length
numberOfPivots : : Max number of pivots to return in the array. Default is 20
: useAlternativeSource: If set uses the source for genrating zigzag. Default is false
source : : Alternative source used only if useAlternativeSource is set to true. Default is close
linecolor : : zigzag line color
linewidth : : zigzag line width
linestyle : : zigzag line style
oscillatorSource : : Oscillator source for calculating divergence
directionBias : : Direction bias for calculating divergence
showHighLow : : show highlow label
showRatios : : show retracement ratios
showDivergence : : Show divergence on label (Only works if divergence data is available - that is if we pass valid oscillatorSource and directionBias input)
Returns:
zigzagpivots : Array containing zigzag pivots
zigzagpivotbars : Array containing zigzag pivot bars
zigzagpivotdirs : Array containing zigzag pivot directions (Lower High : 1, Higher High : 2, Lower Low : -2 and Higher Low : -1)
zigzagpivotratios : Array containing zigzag retracement ratios for each pivot
zigzagoscillators : Array of oscillator values at pivots. Will have valid values only if valid oscillatorSource is provided as per input.
zigzagoscillatordirs : Array of oscillator directions (HH, HL, LH, LL) at pivots. Will have valid values only if valid oscillatorSource is provided as per input.
zigzagtrendbias : Array of trend bias at pivots. Will have valid value only if directionBias series is sent in input parameters
zigzagdivergence : Array of divergence sentiment at each pivot. Will have valid values only if oscillatorSource and directionBias inputs are provided
zigzaglines : Returns array of zigzag lines
zigzaglabels : Returns array of zigzag labels
Techindicator
taLibrary "ta"
█ OVERVIEW
This library holds technical analysis functions calculating values for which no Pine built-in exists.
Look first. Then leap.
█ FUNCTIONS
cagr(entryTime, entryPrice, exitTime, exitPrice)
It calculates the "Compound Annual Growth Rate" between two points in time. The CAGR is a notional, annualized growth rate that assumes all profits are reinvested. It only takes into account the prices of the two end points — not drawdowns, so it does not calculate risk. It can be used as a yardstick to compare the performance of two instruments. Because it annualizes values, the function requires a minimum of one day between the two end points (annualizing returns over smaller periods of times doesn't produce very meaningful figures).
Parameters:
entryTime : The starting timestamp.
entryPrice : The starting point's price.
exitTime : The ending timestamp.
exitPrice : The ending point's price.
Returns: CAGR in % (50 is 50%). Returns `na` if there is not >=1D between `entryTime` and `exitTime`, or until the two time points have not been reached by the script.
█ v2, Mar. 8, 2022
Added functions `allTimeHigh()` and `allTimeLow()` to find the highest or lowest value of a source from the first historical bar to the current bar. These functions will not look ahead; they will only return new highs/lows on the bar where they occur.
allTimeHigh(src)
Tracks the highest value of `src` from the first historical bar to the current bar.
Parameters:
src : (series int/float) Series to track. Optional. The default is `high`.
Returns: (float) The highest value tracked.
allTimeLow(src)
Tracks the lowest value of `src` from the first historical bar to the current bar.
Parameters:
src : (series int/float) Series to track. Optional. The default is `low`.
Returns: (float) The lowest value tracked.
█ v3, Sept. 27, 2022
This version includes the following new functions:
aroon(length)
Calculates the values of the Aroon indicator.
Parameters:
length (simple int) : (simple int) Number of bars (length).
Returns: ( [float, float ]) A tuple of the Aroon-Up and Aroon-Down values.
coppock(source, longLength, shortLength, smoothLength)
Calculates the value of the Coppock Curve indicator.
Parameters:
source (float) : (series int/float) Series of values to process.
longLength (simple int) : (simple int) Number of bars for the fast ROC value (length).
shortLength (simple int) : (simple int) Number of bars for the slow ROC value (length).
smoothLength (simple int) : (simple int) Number of bars for the weigted moving average value (length).
Returns: (float) The oscillator value.
dema(source, length)
Calculates the value of the Double Exponential Moving Average (DEMA).
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Length for the smoothing parameter calculation.
Returns: (float) The double exponentially weighted moving average of the `source`.
dema2(src, length)
An alternate Double Exponential Moving Average (Dema) function to `dema()`, which allows a "series float" length argument.
Parameters:
src : (series int/float) Series of values to process.
length : (series int/float) Length for the smoothing parameter calculation.
Returns: (float) The double exponentially weighted moving average of the `src`.
dm(length)
Calculates the value of the "Demarker" indicator.
Parameters:
length (simple int) : (simple int) Number of bars (length).
Returns: (float) The oscillator value.
donchian(length)
Calculates the values of a Donchian Channel using `high` and `low` over a given `length`.
Parameters:
length (int) : (series int) Number of bars (length).
Returns: ( [float, float, float ]) A tuple containing the channel high, low, and median, respectively.
ema2(src, length)
An alternate ema function to the `ta.ema()` built-in, which allows a "series float" length argument.
Parameters:
src : (series int/float) Series of values to process.
length : (series int/float) Number of bars (length).
Returns: (float) The exponentially weighted moving average of the `src`.
eom(length, div)
Calculates the value of the Ease of Movement indicator.
Parameters:
length (simple int) : (simple int) Number of bars (length).
div (simple int) : (simple int) Divisor used for normalzing values. Optional. The default is 10000.
Returns: (float) The oscillator value.
frama(source, length)
The Fractal Adaptive Moving Average (FRAMA), developed by John Ehlers, is an adaptive moving average that dynamically adjusts its lookback period based on fractal geometry.
Parameters:
source (float) : (series int/float) Series of values to process.
length (int) : (series int) Number of bars (length).
Returns: (float) The fractal adaptive moving average of the `source`.
ft(source, length)
Calculates the value of the Fisher Transform indicator.
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Number of bars (length).
Returns: (float) The oscillator value.
ht(source)
Calculates the value of the Hilbert Transform indicator.
Parameters:
source (float) : (series int/float) Series of values to process.
Returns: (float) The oscillator value.
ichimoku(conLength, baseLength, senkouLength)
Calculates values of the Ichimoku Cloud indicator, including tenkan, kijun, senkouSpan1, senkouSpan2, and chikou. NOTE: offsets forward or backward can be done using the `offset` argument in `plot()`.
Parameters:
conLength (int) : (series int) Length for the Conversion Line (Tenkan). The default is 9 periods, which returns the mid-point of the 9 period Donchian Channel.
baseLength (int) : (series int) Length for the Base Line (Kijun-sen). The default is 26 periods, which returns the mid-point of the 26 period Donchian Channel.
senkouLength (int) : (series int) Length for the Senkou Span 2 (Leading Span B). The default is 52 periods, which returns the mid-point of the 52 period Donchian Channel.
Returns: ( [float, float, float, float, float ]) A tuple of the Tenkan, Kijun, Senkou Span 1, Senkou Span 2, and Chikou Span values. NOTE: by default, the senkouSpan1 and senkouSpan2 should be plotted 26 periods in the future, and the Chikou Span plotted 26 days in the past.
ift(source)
Calculates the value of the Inverse Fisher Transform indicator.
Parameters:
source (float) : (series int/float) Series of values to process.
Returns: (float) The oscillator value.
kvo(fastLen, slowLen, trigLen)
Calculates the values of the Klinger Volume Oscillator.
Parameters:
fastLen (simple int) : (simple int) Length for the fast moving average smoothing parameter calculation.
slowLen (simple int) : (simple int) Length for the slow moving average smoothing parameter calculation.
trigLen (simple int) : (simple int) Length for the trigger moving average smoothing parameter calculation.
Returns: ( [float, float ]) A tuple of the KVO value, and the trigger value.
pzo(length)
Calculates the value of the Price Zone Oscillator.
Parameters:
length (simple int) : (simple int) Length for the smoothing parameter calculation.
Returns: (float) The oscillator value.
rms(source, length)
Calculates the Root Mean Square of the `source` over the `length`.
Parameters:
source (float) : (series int/float) Series of values to process.
length (int) : (series int) Number of bars (length).
Returns: (float) The RMS value.
rwi(length)
Calculates the values of the Random Walk Index.
Parameters:
length (simple int) : (simple int) Lookback and ATR smoothing parameter length.
Returns: ( [float, float ]) A tuple of the `rwiHigh` and `rwiLow` values.
stc(source, fast, slow, cycle, d1, d2)
Calculates the value of the Schaff Trend Cycle indicator.
Parameters:
source (float) : (series int/float) Series of values to process.
fast (simple int) : (simple int) Length for the MACD fast smoothing parameter calculation.
slow (simple int) : (simple int) Length for the MACD slow smoothing parameter calculation.
cycle (simple int) : (simple int) Number of bars for the Stochastic values (length).
d1 (simple int) : (simple int) Length for the initial %D smoothing parameter calculation.
d2 (simple int) : (simple int) Length for the final %D smoothing parameter calculation.
Returns: (float) The oscillator value.
stochFull(periodK, smoothK, periodD)
Calculates the %K and %D values of the Full Stochastic indicator.
Parameters:
periodK (simple int) : (simple int) Number of bars for Stochastic calculation. (length).
smoothK (simple int) : (simple int) Number of bars for smoothing of the %K value (length).
periodD (simple int) : (simple int) Number of bars for smoothing of the %D value (length).
Returns: ( [float, float ]) A tuple of the slow %K and the %D moving average values.
stochRsi(lengthRsi, periodK, smoothK, periodD, source)
Calculates the %K and %D values of the Stochastic RSI indicator.
Parameters:
lengthRsi (simple int) : (simple int) Length for the RSI smoothing parameter calculation.
periodK (simple int) : (simple int) Number of bars for Stochastic calculation. (length).
smoothK (simple int) : (simple int) Number of bars for smoothing of the %K value (length).
periodD (simple int) : (simple int) Number of bars for smoothing of the %D value (length).
source (float) : (series int/float) Series of values to process. Optional. The default is `close`.
Returns: ( [float, float ]) A tuple of the slow %K and the %D moving average values.
supertrend(factor, atrLength, wicks)
Calculates the values of the SuperTrend indicator with the ability to take candle wicks into account, rather than only the closing price.
Parameters:
factor (float) : (series int/float) Multiplier for the ATR value.
atrLength (simple int) : (simple int) Length for the ATR smoothing parameter calculation.
wicks (simple bool) : (simple bool) Condition to determine whether to take candle wicks into account when reversing trend, or to use the close price. Optional. Default is false.
Returns: ( [float, int ]) A tuple of the superTrend value and trend direction.
szo(source, length)
Calculates the value of the Sentiment Zone Oscillator.
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Length for the smoothing parameter calculation.
Returns: (float) The oscillator value.
t3(source, length, vf)
Calculates the value of the Tilson Moving Average (T3).
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Length for the smoothing parameter calculation.
vf (simple float) : (simple float) Volume factor. Affects the responsiveness.
Returns: (float) The Tilson moving average of the `source`.
t3Alt(source, length, vf)
An alternate Tilson Moving Average (T3) function to `t3()`, which allows a "series float" `length` argument.
Parameters:
source (float) : (series int/float) Series of values to process.
length (float) : (series int/float) Length for the smoothing parameter calculation.
vf (simple float) : (simple float) Volume factor. Affects the responsiveness.
Returns: (float) The Tilson moving average of the `source`.
tema(source, length)
Calculates the value of the Triple Exponential Moving Average (TEMA).
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Length for the smoothing parameter calculation.
Returns: (float) The triple exponentially weighted moving average of the `source`.
tema2(source, length)
An alternate Triple Exponential Moving Average (TEMA) function to `tema()`, which allows a "series float" `length` argument.
Parameters:
source (float) : (series int/float) Series of values to process.
length (float) : (series int/float) Length for the smoothing parameter calculation.
Returns: (float) The triple exponentially weighted moving average of the `source`.
trima(source, length)
Calculates the value of the Triangular Moving Average (TRIMA).
Parameters:
source (float) : (series int/float) Series of values to process.
length (int) : (series int) Number of bars (length).
Returns: (float) The triangular moving average of the `source`.
trima2(src, length)
An alternate Triangular Moving Average (TRIMA) function to `trima()`, which allows a "series int" length argument.
Parameters:
src : (series int/float) Series of values to process.
length : (series int) Number of bars (length).
Returns: (float) The triangular moving average of the `src`.
trix(source, length, signalLength, exponential)
Calculates the values of the TRIX indicator.
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Length for the smoothing parameter calculation.
signalLength (simple int) : (simple int) Length for smoothing the signal line.
exponential (simple bool) : (simple bool) Condition to determine whether exponential or simple smoothing is used. Optional. The default is `true` (exponential smoothing).
Returns: ( [float, float, float ]) A tuple of the TRIX value, the signal value, and the histogram.
uo(fastLen, midLen, slowLen)
Calculates the value of the Ultimate Oscillator.
Parameters:
fastLen (simple int) : (series int) Number of bars for the fast smoothing average (length).
midLen (simple int) : (series int) Number of bars for the middle smoothing average (length).
slowLen (simple int) : (series int) Number of bars for the slow smoothing average (length).
Returns: (float) The oscillator value.
vhf(source, length)
Calculates the value of the Vertical Horizontal Filter.
Parameters:
source (float) : (series int/float) Series of values to process.
length (simple int) : (simple int) Number of bars (length).
Returns: (float) The oscillator value.
vi(length)
Calculates the values of the Vortex Indicator.
Parameters:
length (simple int) : (simple int) Number of bars (length).
Returns: ( [float, float ]) A tuple of the viPlus and viMinus values.
vzo(length)
Calculates the value of the Volume Zone Oscillator.
Parameters:
length (simple int) : (simple int) Length for the smoothing parameter calculation.
Returns: (float) The oscillator value.
williamsFractal(period)
Detects Williams Fractals.
Parameters:
period (int) : (series int) Number of bars (length).
Returns: ( [bool, bool ]) A tuple of an up fractal and down fractal. Variables are true when detected.
wpo(length)
Calculates the value of the Wave Period Oscillator.
Parameters:
length (simple int) : (simple int) Length for the smoothing parameter calculation.
Returns: (float) The oscillator value.
█ v7, Nov. 2, 2023
This version includes the following new and updated functions:
atr2(length)
An alternate ATR function to the `ta.atr()` built-in, which allows a "series float" `length` argument.
Parameters:
length (float) : (series int/float) Length for the smoothing parameter calculation.
Returns: (float) The ATR value.
changePercent(newValue, oldValue)
Calculates the percentage difference between two distinct values.
Parameters:
newValue (float) : (series int/float) The current value.
oldValue (float) : (series int/float) The previous value.
Returns: (float) The percentage change from the `oldValue` to the `newValue`.
donchian(length)
Calculates the values of a Donchian Channel using `high` and `low` over a given `length`.
Parameters:
length (int) : (series int) Number of bars (length).
Returns: ( [float, float, float ]) A tuple containing the channel high, low, and median, respectively.
highestSince(cond, source)
Tracks the highest value of a series since the last occurrence of a condition.
Parameters:
cond (bool) : (series bool) A condition which, when `true`, resets the tracking of the highest `source`.
source (float) : (series int/float) Series of values to process. Optional. The default is `high`.
Returns: (float) The highest `source` value since the last time the `cond` was `true`.
lowestSince(cond, source)
Tracks the lowest value of a series since the last occurrence of a condition.
Parameters:
cond (bool) : (series bool) A condition which, when `true`, resets the tracking of the lowest `source`.
source (float) : (series int/float) Series of values to process. Optional. The default is `low`.
Returns: (float) The lowest `source` value since the last time the `cond` was `true`.
relativeVolume(length, anchorTimeframe, isCumulative, adjustRealtime)
Calculates the volume since the last change in the time value from the `anchorTimeframe`, the historical average volume using bars from past periods that have the same relative time offset as the current bar from the start of its period, and the ratio of these volumes. The volume values are cumulative by default, but can be adjusted to non-accumulated with the `isCumulative` parameter.
Parameters:
length (simple int) : (simple int) The number of periods to use for the historical average calculation.
anchorTimeframe (simple string) : (simple string) The anchor timeframe used in the calculation. Optional. Default is "D".
isCumulative (simple bool) : (simple bool) If `true`, the volume values will be accumulated since the start of the last `anchorTimeframe`. If `false`, values will be used without accumulation. Optional. The default is `true`.
adjustRealtime (simple bool) : (simple bool) If `true`, estimates the cumulative value on unclosed bars based on the data since the last `anchor` condition. Optional. The default is `false`.
Returns: ( [float, float, float ]) A tuple of three float values. The first element is the current volume. The second is the average of volumes at equivalent time offsets from past anchors over the specified number of periods. The third is the ratio of the current volume to the historical average volume.
rma2(source, length)
An alternate RMA function to the `ta.rma()` built-in, which allows a "series float" `length` argument.
Parameters:
source (float) : (series int/float) Series of values to process.
length (float) : (series int/float) Length for the smoothing parameter calculation.
Returns: (float) The rolling moving average of the `source`.
supertrend2(factor, atrLength, wicks)
An alternate SuperTrend function to `supertrend()`, which allows a "series float" `atrLength` argument.
Parameters:
factor (float) : (series int/float) Multiplier for the ATR value.
atrLength (float) : (series int/float) Length for the ATR smoothing parameter calculation.
wicks (simple bool) : (simple bool) Condition to determine whether to take candle wicks into account when reversing trend, or to use the close price. Optional. Default is `false`.
Returns: ( [float, int ]) A tuple of the superTrend value and trend direction.
vStop(source, atrLength, atrFactor)
Calculates an ATR-based stop value that trails behind the `source`. Can serve as a possible stop-loss guide and trend identifier.
Parameters:
source (float) : (series int/float) Series of values that the stop trails behind.
atrLength (simple int) : (simple int) Length for the ATR smoothing parameter calculation.
atrFactor (float) : (series int/float) The multiplier of the ATR value. Affects the maximum distance between the stop and the `source` value. A value of 1 means the maximum distance is 100% of the ATR value. Optional. The default is 1.
Returns: ( [float, bool ]) A tuple of the volatility stop value and the trend direction as a "bool".
vStop2(source, atrLength, atrFactor)
An alternate Volatility Stop function to `vStop()`, which allows a "series float" `atrLength` argument.
Parameters:
source (float) : (series int/float) Series of values that the stop trails behind.
atrLength (float) : (series int/float) Length for the ATR smoothing parameter calculation.
atrFactor (float) : (series int/float) The multiplier of the ATR value. Affects the maximum distance between the stop and the `source` value. A value of 1 means the maximum distance is 100% of the ATR value. Optional. The default is 1.
Returns: ( [float, bool ]) A tuple of the volatility stop value and the trend direction as a "bool".
Removed Functions:
allTimeHigh(src)
Tracks the highest value of `src` from the first historical bar to the current bar.
allTimeLow(src)
Tracks the lowest value of `src` from the first historical bar to the current bar.
trima2(src, length)
An alternate Triangular Moving Average (TRIMA) function to `trima()`, which allows a
"series int" length argument.
Double_Triple_EMALibrary "Double_Triple_EMA"
Provides the functions to calculate Double and Triple Exponentional Moving Averages (DEMA & TEMA).
dema(_source, _length) Calculates Double Exponentional Moving Averages (DEMA)
Parameters:
_source : -> Open, Close, High, Low, etc ('close' is used if no argument is supplied)
_length : -> DEMA length
Returns: Double Exponential Moving Average (DEMA) of an input source at the specified input length
tema(_source, _length) Calculates Triple Exponentional Moving Averages (TEMA)
Parameters:
_source : -> Open, Close, High, Low, etc ('close' is used if no argument is supplied)
_length : -> TEMA length
Returns: Triple Exponential Moving Average (TEMA) of an input source at the specified input length
Library_All_In_OneLibrary "Library_All_In_One"
fnRSI()
fnTSI()
Discription:
Contains several functions of Pinescript all in one Library. This reduce your coding.
How to use:
import Wilson-IV/Library_All_In_One/1 as _lib
Examples of plotting the RSI and TSI:
plot(_lib.fnRSI(close, 14))
plot(_lib.fnTSI(close, 25, 14))
Markets:
It can be used to all markets.
NOTE:
It will expands with more function during time.
multiMaLibrary "multiMa"
Provides function that returns the type of moving average requested.
ma(type, src, len) Returns the moving average requested.
Parameters:
type : The type of moving average (choose one of "EMA", "SMA", "DEMA", "TEMA", "WMA", "VWMA", "SMMA", "HMA")
src : The source
len : The length
Returns: The moving average requested or `na`
NumberOfSharesBuyLibrary "NumberOfSharesBuy"
Library for the number of shares purchased
SizeCalc(totalAssets, unit, lossPercent, maxLossPerShere) Calculate the number of shares to be purchased from the initial capital and the maximum loss per share
Parameters:
totalAssets : Initial capital
unit : A unit of the number of shares to be traded in one trade
lossPercent : What percentage of loss is allowed in one loss cut
maxLossPerShere : Maximum loss per share
Returns: Number of shares purchased
=====================================
ライブラリ "株数に関するライブラリ"
SizeCalc(totalAssets, unit, lossPercent, maxLossPerShere) 初期資本と一株当たり最大損失から購入株数を求める
引数一覧:
totalAssets : 初期資本
unit : 一回のトレードで行う株数の単位
lossPercent : 一回の損切で何%までの損失を許容するか
maxLossPerShere : 一株当たり最大損失
戻り値: 購入株数
enhanced_taLibrary "enhanced_ta"
Collection of all custom and enhanced TA indicators
ma(source, maType, length) returns custom moving averages
Parameters:
source : Moving Average Source
maType : Moving Average Type : Can be sma, ema, hma, rma, wma, vwma, swma, highlow
length : Moving Average Length
Returns: moving average for the given type and length
bb(source, maType, length, multiplier) returns Bollinger band for custom moving average
Parameters:
source : Moving Average Source
maType : Moving Average Type : Can be sma, ema, hma, rma, wma, vwma, swma, highlow
length : Moving Average Length
multiplier : Standard Deviation multiplier
Returns: Bollinger band with custom moving average for given source, length and multiplier
bbw(source, maType, length, multiplier) returns Bollinger bandwidth for custom moving average
Parameters:
source : Moving Average Source
maType : Moving Average Type : Can be sma, ema, hma, rma, wma, vwma, swma, highlow
length : Moving Average Length
multiplier : Standard Deviation multiplier
Returns: Bollinger Bandwidth for custom moving average for given source, length and multiplier
bpercentb(source, maType, length, multiplier) returns Bollinger Percent B for custom moving average
Parameters:
source : Moving Average Source
maType : Moving Average Type : Can be sma, ema, hma, rma, wma, vwma, swma, highlow
length : Moving Average Length
multiplier : Standard Deviation multiplier
Returns: Bollinger Percent B for custom moving average for given source, length and multiplier
kc(source, maType, length, multiplier) returns Keltner Channel for custom moving average
Parameters:
source : Moving Average Source
maType : Moving Average Type : Can be sma, ema, hma, rma, wma, vwma, swma, highlow
length : Moving Average Length
multiplier : Standard Deviation multiplier
Returns: Keltner Channel for custom moving average for given souce, length and multiplier
kcw(source, maType, length, multiplier) returns Keltner Channel Width with custom moving average
Parameters:
source : Moving Average Source
maType : Moving Average Type : Can be sma, ema, hma, rma, wma, vwma, swma, highlow
length : Moving Average Length
multiplier : Standard Deviation multiplier
Returns: Keltner Channel Width for custom moving average
kpercentk(source, maType, length, multiplier) returns Keltner Channel Percent K Width with custom moving average
Parameters:
source : Moving Average Source
maType : Moving Average Type : Can be sma, ema, hma, rma, wma, vwma, swma, highlow
length : Moving Average Length
multiplier : Standard Deviation multiplier
Returns: Keltner Percent K for given moving average, source, length and multiplier
dc(source, useCustomSource, length) returns Custom Donchian Channel
Parameters:
source : - Custom source
useCustomSource : - Custom source is used only if useCustomSource is set to true
length : - donchian channel length
Returns: Donchian channel
oscillatorRange(source, method, highlowLength, rangeLength) returns Custom overbought/oversold areas for an oscillator input
Parameters:
source : - Osillator source such as RSI, COG etc.
method : - Valid values for method are : sma, ema, hma, rma, wma, vwma, swma, highlow
highlowLength : - length on which highlow of the oscillator is calculated
rangeLength : - length used for calculating oversold/overbought range - usually same as oscillator length
Returns: Dynamic overbought and oversold range for oscillator input
RSLibrary "RS"
Utility methods for Relative Strength analysis
This is the first library test publication with ratio() method. More functions will be added.
ratio(symbol, benchmark) Simple ratio of symbol vs benchmark
Parameters:
symbol : to be compared
benchmark : to be compared
Returns: ratio of symbol to benchmark
SupportResitanceAndTrendLibrary "SupportResitanceAndTrend"
Contains utilities for finding key levels of support, resistance and direction of trend.
superTrendPlus(multiple, h, l, atr, closeBars) A more flexible version of SuperTrend that allows for supplying the series used and sensitivity adjustment by confirming close bars.
Parameters:
multiple : The multiple to apply to the average true range.
h : The high values.
l : The low values.
atr : The average true range values.
closeBars : The number of bars to confirm a change in trend.
Returns:
superTrend(multiple, period, mode, closeBars) superTrendPlus with simplified parameters.
Parameters:
multiple : The multiple to apply to the average true range.
period : The number of bars to measure.
mode : The type of moving average to use with the true range.
closeBars : The number of bars to confirm a change in trend.
Returns:
stochSR() Identifies support and resistance levels by when a stochastic RSI reverses. Returns:
MovingAveragesLibrary "MovingAverages"
Contains utilities for generating moving average values including getting a moving average by name and a function for generating a Volume-Adjusted WMA.
vawma(len, src, volumeDefault) VAWMA = VWMA and WMA combined. Simply put, this attempts to determine the average price per share over time weighted heavier for recent values. Uses a triangular algorithm to taper off values in the past (same as WMA does).
Parameters:
len : The number of bars to measure with.
src : The series to measure from. Default is 'hlc3'.
volumeDefault : The default value to use when a chart has no (N/A) volume.
Returns: The volume adjusted triangular weighted moving average of the series.
getMA(mode, len, src) Generates a moving average based upon a 'mode'.
Parameters:
mode : The type of moving average to generate. Values allowed are: SMA, EMA, WMA, VWMA and VAWMA.
len : The number of bars to measure with.
src : The series to measure from. Default is 'close'.
Returns: The volume adjusted triangular weighted moving average of the series.
Matrix_Functions_Lib_JDLibrary "Matrix_Functions_Lib_JD"
This is a library to add matrix / 2D array functionality to Pinescript.
once you import the library at the beginning of your script, you can add all the functions described below just by calling them like you do any other built'in function.
Enjoy,
Gr, JD.
PS. if you find functionality or calculation errors in the functions, please let me know, so I can fix them.
There are quite a lot of functions, so little mishaps may have slipped in! ;-)
get_nr_of_rows() Returns the number of rows from a 2D matrix
get_nr_of_columns() Returns the number of columns from a 2D matrix
get_size() Returns a tuple with the total number of rows and columns from a 2D matrix
init() 2D matrix init function, builds a 2D matrix with dimensional metadata in first two values and fills it with a default value, the body of the actual matrix data starts at index 2.
from_list() 2D matrix init function, builds a 2D matrix from an existing array by adding dimensional metadata in first two values, the body of the actual matrix data consists of the data of the source array and starts at index 2.
set() Sets values in 2D matrix with (row index, column index) (index for rows and columns both starts at 0 !!)
fill_val() Fills all elements in a 2D matrix with a value
randomize() Fills a 2D matrix with random values//
get() Gets values from 2D matrix with (row index, column index) (index for rows and columns both starts at 0 !!)
copy_slice_body() Cuts off the metadata header and returns the array body, WITHOUT THE DIMENSIONAL METADATA!!
do_slice This variable should be set as: - 'false' to only make a copy, changes to the new array copy will NOT ALTER the ORIGINAL - 'true' to make a slice, changes to the new array slice WILL(!) ALTER the ORIGINAL
get_record() Gets /retrieve the values from a ROW/RECORD from a certain row/lookback period, the values are returned as an array
get_row_index() Gets the row nr. in a 2D matrix from 1D index (index for rows and columns both starts at 0 !!)
get_column_index() Gets the column nr. in a 2D matrix from 1D index (index for rows and columns both starts at 0 !!)
get_row_column_index() Gets a tuple with the (row, column) coordinates in 2D matrix from 1D index (index starts at 0 and does not include the header!!)
get_array_index() Gets the 1D index from (row, column) coordinates in 2D matrix (index for row and column both starts at 0 !! Index starts at 0 and does not include the header!!)
remove_rows() Removes one or more rows/records from a 2D matrix (if from_row = to_row, only this row is removed)
remove_columns() Remove one or more columns from a 2D matrix (if from_column = to_column, only this column is removed)
insert_array_of_rows() Insert an array of rows/records at a certain row number in a 2D matrix
add_row() ADDS a ROW/RECORD on the TOP of a sheet, shift the whole list one down and gives the option to REMOVE the OLDEST row/record. (2D version of "unshift" + "pop" but with a whole row at once)
insert_array_of_columns() Insert an array of columns at a certain column number in a 2D matrix
append_array_of_rows() Appends/adds an array of rows/records to the bottom of a 2D matrix
append_array_of_columns() Appends/adds an array of columns to the right side of a 2D matrix
pop_row() Removes / pops and returns the last row/record from a 2D matrix.
pop_column() Removes / pops and returns the last (most right) column from a 2D matrix.
replace()
abs()
add_value() Returns a new matrix with the same value added to all the elements of the source matrix.
addition() Returns a new matrix with the of the elements of one 2D matrix added to every corresponding element of a source 2D matrix.
subtract_value() Returns a new matrix with the same value subtracted from every element of a 2D matrix
subtraction() Returns a new matrix with the values of the elements of one 2D matrix subtracted from every corresponding element of a source 2D matrix.
scalar_multipy() Returns a new matrix with all the elements of the source matrix scaled/multiplied by a scalar value.
transpose() Returns a new matrix with the elements of the source matrix transposed.
multiply_elem() Performs ELEMENT WISE MULTIPLICATION of 2D matrices, returns a new matrix c.
multiply() Performs DOT PROCUCT MULTIPLICATION of 2D matrices, returns a new matrix c.
determinant_2x2() Calculates the determinant of 2x2 matrices.
determinant_3x3() Calculates the determinant of 3x3 matrices.
determinant_4x4() Calculates the determinant of 4x4 matrices.
print() displays a 2D matrix in a table layout.
