FunctionProbabilityDistributionSamplingLibrary "FunctionProbabilityDistributionSampling"
Methods for probability distribution sampling selection.
sample(probabilities) Computes a random selected index from a probability distribution.
Parameters:
probabilities : float array, probabilities of sample.
Returns: int.
지표 및 전략
smfLibrary "smf"
f_strLeft(string, int) Function returning the leftmost `_n` characters in `_str`.
Parameters:
string : _str: source string.
int : _n : number of leftmost characters to return.
f_strRight(string, int) Function returning the rightmost `_n` characters in `_str`.
Parameters:
string : _str: source string.
int : _n : number of rightmost characters to return.
f_strMid(string, int, int) Function returning the substring of `_str` from character position `_from` to `_to` inclusively.
Parameters:
string : _str : source string.
int : _from: left character position. The first character's position is 0.
int : _to : right character position.
f_strLeftOf(string, string) Function returning the sub-string of `_str` to the left of the `_of` separating character.
Parameters:
string : _str: string to separate.
string : _op : separator character.
f_strRightOf(string, string) Function returning the sub-string of `_str` to the right of the `_of` separating character.
Parameters:
string : _str: string to separate.
string : _op : separator character.
f_strCharPos(string, string) Function returning the position of the first occurrence of `_chr` in `_str`, where the first character position is 0. Returns -1 if the character is not found.
Parameters:
string : _str: string to search.
string : _chr: character to search for in `_str`.
f_strReplace(string, int, string) Function that replaces a character at position `_pos` in the `_src` string with the `_str` character or string.
Parameters:
string : _src : source string.
int : _pos : position of character to be replaced. The first character's position is 0.
string : _str : replacement character or string.
f_tickFormat() Function returning a format string usable with `tostring()` to round a value to the symbol's tick precision.
f_tostringPad(float, string) Function returning a string representation of a numeric `_val` using a special `_fmt` string allowing all strings to be of the same width, to help align columns of values.
Parameters:
float : _val: string to separate.
string : _fmt: formatting string similar to those used in the `tostring()` format string, with "?" used to indicate padding,
f_print() Function prints a label on dataset's last bar.
ZenLibraryLibrary "ZenLibrary"
A collection of custom tools & utility functions commonly used with my scripts.
getDecimals() Calculates how many decimals are on the quote price of the current market
Returns: The current decimal places on the market quote price
truncate(float, float) Truncates (cuts) excess decimal places
Parameters:
float : _number The number to truncate
float : _decimalPlaces (default=2) The number of decimal places to truncate to
Returns: The given _number truncated to the given _decimalPlaces
toWhole(float) Converts pips into whole numbers
Parameters:
float : _number The pip number to convert into a whole number
Returns: The converted number
toPips(float) Converts whole numbers back into pips
Parameters:
float : _number The whole number to convert into pips
Returns: The converted number
av_getPositionSize(float, float, float, float) Calculates OANDA forex position size for AutoView based on the given parameters
Parameters:
float : _balance The account balance to use
float : _risk The risk percentage amount (as a whole number - eg. 1 = 1% risk)
float : _stopPoints The stop loss distance in POINTS (not pips)
float : _conversionRate The conversion rate of our account balance currency
Returns: The calculated position size (in units - only compatible with OANDA)
getMA(int, string) Gets a Moving Average based on type
Parameters:
int : _length The MA period
string : _maType The type of MA
Returns: A moving average with the given parameters
getEAP(float) Performs EAP stop loss size calculation (eg. ATR >= 20.0 and ATR < 30, returns 20)
Parameters:
float : _atr The given ATR to base the EAP SL calculation on
Returns: The EAP SL converted ATR size
barsAboveMA(int, float) Counts how many candles are above the MA
Parameters:
int : _lookback The lookback period to look back over
float : _ma The moving average to check
Returns: The bar count of how many recent bars are above the MA
barsBelowMA(int, float) Counts how many candles are below the MA
Parameters:
int : _lookback The lookback period to look back over
float : _ma The moving average to reference
Returns: The bar count of how many recent bars are below the EMA
barsCrossedMA(int, float) Counts how many times the EMA was crossed recently
Parameters:
int : _lookback The lookback period to look back over
float : _ma The moving average to reference
Returns: The bar count of how many times price recently crossed the EMA
getPullbackBarCount(int, int) Counts how many green & red bars have printed recently (ie. pullback count)
Parameters:
int : _lookback The lookback period to look back over
int : _direction The color of the bar to count (1 = Green, -1 = Red)
Returns: The bar count of how many candles have retraced over the given lookback & direction
getBodySize() Gets the current candle's body size (in POINTS, divide by 10 to get pips)
Returns: The current candle's body size in POINTS
getTopWickSize() Gets the current candle's top wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's top wick size in POINTS
getBottomWickSize() Gets the current candle's bottom wick size (in POINTS, divide by 10 to get pips)
Returns: The current candle's bottom wick size in POINTS
getBodyPercent() Gets the current candle's body size as a percentage of its entire size including its wicks
Returns: The current candle's body size percentage
isHammer(float, bool) Checks if the current bar is a hammer candle based on the given parameters
Parameters:
float : _fib (default=0.382) The fib to base candle body on
bool : _colorMatch (default=false) Does the candle need to be green? (true/false)
Returns: A boolean - true if the current bar matches the requirements of a hammer candle
isStar(float, bool) Checks if the current bar is a shooting star candle based on the given parameters
Parameters:
float : _fib (default=0.382) The fib to base candle body on
bool : _colorMatch (default=false) Does the candle need to be red? (true/false)
Returns: A boolean - true if the current bar matches the requirements of a shooting star candle
isDoji(float, bool) Checks if the current bar is a doji candle based on the given parameters
Parameters:
float : _wickSize (default=2) The maximum top wick size compared to the bottom (and vice versa)
bool : _bodySize (default=0.05) The maximum body size as a percentage compared to the entire candle size
Returns: A boolean - true if the current bar matches the requirements of a doji candle
isBullishEC(float, float, bool) Checks if the current bar is a bullish engulfing candle
Parameters:
float : _allowance (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)
float : _rejectionWickSize (default=disabled) The maximum rejection wick size compared to the body as a percentage
bool : _engulfWick (default=false) Does the engulfing candle require the wick to be engulfed as well?
Returns: A boolean - true if the current bar matches the requirements of a bullish engulfing candle
isBearishEC(float, float, bool) Checks if the current bar is a bearish engulfing candle
Parameters:
float : _allowance (default=0) How many POINTS to allow the open to be off by (useful for markets with micro gaps)
float : _rejectionWickSize (default=disabled) The maximum rejection wick size compared to the body as a percentage
bool : _engulfWick (default=false) Does the engulfing candle require the wick to be engulfed as well?
Returns: A boolean - true if the current bar matches the requirements of a bearish engulfing candle
timeFilter(string, bool) Determines if the current price bar falls inside the specified session
Parameters:
string : _sess The session to check
bool : _useFilter (default=false) Whether or not to actually use this filter
Returns: A boolean - true if the current bar falls within the given time session
dateFilter(int, int) Determines if this bar's time falls within date filter range
Parameters:
int : _startTime The UNIX date timestamp to begin searching from
int : _endTime the UNIX date timestamp to stop searching from
Returns: A boolean - true if the current bar falls within the given dates
dayFilter(bool, bool, bool, bool, bool, bool, bool) Checks if the current bar's day is in the list of given days to analyze
Parameters:
bool : _monday Should the script analyze this day? (true/false)
bool : _tuesday Should the script analyze this day? (true/false)
bool : _wednesday Should the script analyze this day? (true/false)
bool : _thursday Should the script analyze this day? (true/false)
bool : _friday Should the script analyze this day? (true/false)
bool : _saturday Should the script analyze this day? (true/false)
bool : _sunday Should the script analyze this day? (true/false)
Returns: A boolean - true if the current bar's day is one of the given days
atrFilter(float, float) Checks the current bar's size against the given ATR and max size
Parameters:
float : _atr (default=ATR 14 period) The given ATR to check
float : _maxSize The maximum ATR multiplier of the current candle
Returns: A boolean - true if the current bar's size is less than or equal to _atr x _maxSize
fillCell(table, int, int, string, string, color, color) This updates the given table's cell with the given values
Parameters:
table : _table The table ID to update
int : _column The column to update
int : _row The row to update
string : _title The title of this cell
string : _value The value of this cell
color : _bgcolor The background color of this cell
color : _txtcolor The text color of this cell
Returns: A boolean - true if the current bar falls within the given dates
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.
LinearRegressionLibraryLibrary "LinearRegressionLibrary" contains functions for fitting a regression line to the time series by means of different models, as well as functions for estimating the accuracy of the fit.
Linear regression algorithms:
RepeatedMedian(y, n, lastBar) applies repeated median regression (robust linear regression algorithm) to the input time series within the selected interval.
Parameters:
y :: float series, source time series (e.g. close)
n :: integer, the length of the selected time interval
lastBar :: integer, index of the last bar of the selected time interval (defines the position of the interval)
Output:
mSlope :: float, slope of the regression line
mInter :: float, intercept of the regression line
TheilSen(y, n, lastBar) applies the Theil-Sen estimator (robust linear regression algorithm) to the input time series within the selected interval.
Parameters:
y :: float series, source time series
n :: integer, the length of the selected time interval
lastBar :: integer, index of the last bar of the selected time interval (defines the position of the interval)
Output:
tsSlope :: float, slope of the regression line
tsInter :: float, intercept of the regression line
OrdinaryLeastSquares(y, n, lastBar) applies the ordinary least squares regression (non-robust) to the input time series within the selected interval.
Parameters:
y :: float series, source time series
n :: integer, the length of the selected time interval
lastBar :: integer, index of the last bar of the selected time interval (defines the position of the interval)
Output:
olsSlope :: float, slope of the regression line
olsInter :: float, intercept of the regression line
Model performance metrics:
metricRMSE(y, n, lastBar, slope, intercept) returns the Root-Mean-Square Error (RMSE) of the regression. The better the model, the lower the RMSE.
Parameters:
y :: float series, source time series (e.g. close)
n :: integer, the length of the selected time interval
lastBar :: integer, index of the last bar of the selected time interval (defines the position of the interval)
slope :: float, slope of the evaluated linear regression line
intercept :: float, intercept of the evaluated linear regression line
Output:
rmse :: float, RMSE value
metricMAE(y, n, lastBar, slope, intercept) returns the Mean Absolute Error (MAE) of the regression. MAE is is similar to RMSE but is less sensitive to outliers. The better the model, the lower the MAE.
Parameters:
y :: float series, source time series
n :: integer, the length of the selected time interval
lastBar :: integer, index of the last bar of the selected time interval (defines the position of the interval)
slope :: float, slope of the evaluated linear regression line
intercept :: float, intercept of the evaluated linear regression line
Output:
mae :: float, MAE value
metricR2(y, n, lastBar, slope, intercept) returns the coefficient of determination (R squared) of the regression. The better the linear regression fits the data (compared to the sample mean), the closer the value of the R squared is to 1.
Parameters:
y :: float series, source time series
n :: integer, the length of the selected time interval
lastBar :: integer, index of the last bar of the selected time interval (defines the position of the interval)
slope :: float, slope of the evaluated linear regression line
intercept :: float, intercept of the evaluated linear regression line
Output:
Rsq :: float, R-sqared score
Usage example:
//@version=5
indicator('ExampleLinReg', overlay=true)
// import the library
import tbiktag/LinearRegressionLibrary/1 as linreg
// define the studied interval: last 100 bars
int Npoints = 100
int lastBar = bar_index
int firstBar = bar_index - Npoints
// apply repeated median regression to the closing price time series within the specified interval
{square bracket}slope, intercept{square bracket} = linreg.RepeatedMedian(close, Npoints, lastBar)
// calculate the root-mean-square error of the obtained linear fit
rmse = linreg.metricRMSE(close, Npoints, lastBar, slope, intercept)
// plot the line and print the RMSE value
float y1 = intercept
float y2 = intercept + slope * (Npoints - 1)
if barstate.islast
{indent} line.new(firstBar,y1, lastBar,y2)
{indent} label.new(lastBar,y2,text='RMSE = '+str.format("{0,number,#.#}", rmse))
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.
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.
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.
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
zigzagplusThis is same as existing zigzag library with respect to functionality. But, there is a small update with respect to how arrays are used internally. This also leads to issues with backward compatibility. Hence I decided to make this as new library instead of updating the older one.
Below are the major changes:
Earlier version uses array.unshift for adding new elements and array.pop for removing old elements. But, since array.unshift is considerably slower than alternative method array.push. Hence, this library makes use of array.push method to achieve performance.
While array.push increases the performance significantly, there is also an issue with removing as we no longer will be able to remove the element using pop which is again faster than shift (which need to shit all the elements by index). Hence, have removed the logic of removing elements for zigzag pivots after certain limit. Will think further about it once I find better alternative of handling it.
These implementation change also mean that zigzag pivots received by calling method will be ordered in reverse direction. Latest pivots will be stored with higher array index whereas older pivots are stored with lower array index. This is also the reason why backward compatibility is not achievable with this code change.
Library "zigzagplus"
Library dedicated to zigzags and related indicators
zigzag(length, useAlternativeSource, source, oscillatorSource, directionBias) zigzag: Calculates zigzag pivots and generates an array
Parameters:
length : : Zigzag Length
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, , source, linecolor, linewidth, linestyle, oscillatorSource, directionBias, showHighLow, showRatios, showDivergence) drawzigzag: Calculates and draws zigzag pivots
Parameters:
length : : Zigzag Length
: 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
LibraryPrivateUsage001This is a public library that include the functions explained below. The libraries are considered public domain code and permission is not required from the author if you reuse these functions in your open-source scripts
LibraryCheckNthBarLibrary "LibraryCheckNthBar"
TODO: add library description here
canwestart(UTC, prd) this function can be used if current bar is in last Nth bar
Parameters:
UTC : is UTC of the chart
prd : is the length of last Nth bar
Returns: true if the current bar is in N bar
FunctionDecisionTreeLibrary "FunctionDecisionTree"
Method to generate decision tree based on weights.
decision_tree(weights, depth) Method to generate decision tree based on weights.
Parameters:
weights : float array, weights for decision consideration.
depth : int, depth of the tree.
Returns: int array
FunctionDaysInMonthLibrary "FunctionDaysInMonth"
Method to find the number of days in a given month of year.
days_in_month(year, month) Method to find the number of days in a given month of year.
Parameters:
year : int, year of month, so we know if year is a leap year or not.
month : int, month number.
Returns: int
[MX]Moving Average - LibraryLibrary "MA_library"
OVERVIEW
This library contains moving average functions that calculate values for which they do not exist by default in PineScript
Functions
tema(source,length) : Triple Exponencial Moving Average
dema(source,length) : Double Exponencial Moving Average
wwma(source,length) : Welles Wilder Moving Average
gma(source,length) : Geometric Moving Average
FunctionForecastLinearLibrary "FunctionForecastLinear"
Method for linear Forecast, same as found in excel and other sheet packages.
forecast(sample_x, sample_y, target_x) linear forecast method.
Parameters:
sample_x : float array, sample data X value.
sample_y : float array, sample data Y value.
target_x : float, target X to get Y forecast value.
Returns: float
FunctionBoxCoxTransformLibrary "FunctionBoxCoxTransform"
Methods to compute the Box-Cox Transformer.
regular(sample, lambda) Regular transform.
Parameters:
sample : float array, sample data values.
lambda : float, scaling factor.
Returns: float array.
inverse(sample, lambda) Regular transform.
Parameters:
sample : float array, sample data values.
lambda : float, scaling factor.
Returns: float array.
FunctionPolynomialRegressionLibrary "FunctionPolynomialRegression"
TODO:
polyreg(sample_x, sample_y) Method to return a polynomial regression channel using (X,Y) sample points.
Parameters:
sample_x : float array, sample data X points.
sample_y : float array, sample data Y points.
Returns: tuple with:
_predictions: Array with adjusted Y values.
_max_dev: Max deviation from the mean.
_min_dev: Min deviation from the mean.
_stdev/_sizeX: Average deviation from the mean.
draw(sample_x, sample_y, extend, mid_color, mid_style, mid_width, std_color, std_style, std_width, max_color, max_style, max_width) Method for drawing the Polynomial Regression into chart.
Parameters:
sample_x : float array, sample point X value.
sample_y : float array, sample point Y value.
extend : string, default=extend.none, extend lines.
mid_color : color, default=color.blue, middle line color.
mid_style : string, default=line.style_solid, middle line style.
mid_width : int, default=2, middle line width.
std_color : color, default=color.aqua, standard deviation line color.
std_style : string, default=line.style_dashed, standard deviation line style.
std_width : int, default=1, standard deviation line width.
max_color : color, default=color.purple, max range line color.
max_style : string, default=line.style_dotted, max line style.
max_width : int, default=1, max line width.
Returns: line array.
TimeframeToMinutesLibrary "TimeframeToMinutes"
The timeframeToMinutes() function returns the number of minutes in an arbitrary timeframe string.
timeframeToMinutes()
Returns the number of minutes in the supplied timeframe string, which is arbitrary, i.e. it doesn't have to be the timeframe of the current chart but can be taken from an input.
The sole advantage over the short and neat Pinecoders f_resInMinutes function from their excellent MTF Selection Framework (at ) is that this one doesn't use up a security() call.
To convert the other way, from minutes to timeframe.period format, I would use the f_resFromMinutes function from the Pinecoders' MTF Selection Framework, which does not use security().
ERROR-CHECKING: It has light error-checking to try to make sure the string is in the format timeframe.period, e.g. 15S, 1 (minute), 60 (1H), 1D, 1W, 1M.
It will throw an error for some non-standard timeframes such as 30 hours (1800 minutes). Above 1440 minutes, only whole numbers of days are allowed. This is to be consistent with the security() function.
But it will allow some non-standard timeframes such as 7 hours (420 minutes). Such timeframes must still be supplied in the standard timeframe.period format.
param _tf
The timeframe to convert to minutes. Must be in timeframe.period format.
returns
An integer representing the number of minutes that the timeframe period is equivalent to.
FunctionLinearRegressionLibrary "FunctionLinearRegression"
Method for Linear Regression using array sample points.
linreg(sample_x, sample_y) Performs Linear Regression over the provided sample points.
Parameters:
sample_x : float array, sample points X value.
sample_y : float array, sample points Y value.
Returns: tuple with:
_predictions: Array with adjusted Y values.
_max_dev: Max deviation from the mean.
_min_dev: Min deviation from the mean.
_stdev/_sizeX: Average deviation from the mean.
draw(sample_x, sample_y, extend, mid_color, mid_style, mid_width, std_color, std_style, std_width, max_color, max_style, max_width) Method for drawing the Linear Regression into chart.
Parameters:
sample_x : float array, sample point X value.
sample_y : float array, sample point Y value.
extend : string, default=extend.none, extend lines.
mid_color : color, default=color.blue, middle line color.
mid_style : string, default=line.style_solid, middle line style.
mid_width : int, default=2, middle line width.
std_color : color, default=color.aqua, standard deviation line color.
std_style : string, default=line.style_dashed, standard deviation line style.
std_width : int, default=1, standard deviation line width.
max_color : color, default=color.purple, max range line color.
max_style : string, default=line.style_dotted, max line style.
max_width : int, default=1, max line width.
Returns: line array.
LabelsLibrary "Labels"
Functions to create labels, from simple to complex.
labelSimple()
Creates a label each time a condition is true. All label parameters can be customised.
_condition The condition which must evaluate true for the label to be printed.
_x The x location.
_y The y location.
_text The text to print on the label.
_color The colour of the label.
_textColor The colour of the text.
_style The style of the label.
_yloc The y location type.
Returns
An unnamed label object with the supplied characteristics. To give it a name, assign the output of the function to a label variable, as in the example below.
labelLast()
Creates a label each time a condition is true. All label parameters can be customised. + Option to keep only the most recent label. + Option to display the label a configurable number of bars ahead.
_offset How many bars ahead to draw the label.
_keepLast If true (the default), keeps only the most recent label. If false, prints labels up to the TradingView limit.
_condition The condition which must evaluate true for the label to be printed.
_y The y location.
_text The text to print on the label.
_color The colour of the label.
_textColor The colour of the text.
_style The style of the label.
_yloc The y location type.
Returns A named label object with the supplied characteristics.
labelTextAndFloat()
Creates a label each time a condition is true. All label parameters can be customised. Option to keep only the most recent label. Option to display the label a configurable number of bars ahead; otherwise the x location is fixed at the bar time. + Prints (optional) text and a floating-point number on the next line.
_offset How many bars ahead to draw the label.
_float The floating-point number that you want to display on the label.
_keepLast If true (the default), keeps only the most recent label. If false, prints labels up to the TradingView limit.
_condition The condition which must evaluate true for the label to be printed.
_y The y location.
_text The text to print on the label.
_color The colour of the label.
_textColor The colour of the text.
_style The style of the label.
_yloc The y location type.
Returns A named label object with the supplied characteristics.
labelTextAndFloatSigFig()
Creates a label each time a condition is true. All label parameters can be customised. Option to keep only the most recent label. Option to display the label a configurable number of bars ahead; otherwise the x location is fixed at the bar time. Prints (optional) text and a floating-point number on the next line + to a given number of significant figures.
_offset How many bars ahead to draw the label.
_sigNumFig The number of significant figures to display the floating-point number to.
_float The floating-point number that you want to display on the label.
_keepLast If true (the default), keeps only the most recent label. If false, prints labels up to the TradingView limit.
_condition The condition which must evaluate true for the label to be printed.
_y The y location.
_text The text to print on the label.
_color The colour of the label.
_textColor The colour of the text.
_style The style of the label.
_yloc The y location type.
Returns A named label object with the supplied characteristics.
labelTextAndFloatDecimals()
Creates a label each time a condition is true. All label parameters can be customised. Option to keep only the most recent label. Option to display the label a configurable number of bars ahead. Prints (optional) text and a floating-point number on the next line + to a given number of decimal places.
_offset How many bars ahead to draw the label.
_decimals The number of decimal places to display the floating-point number to.
_float The floating-point number that you want to display on the label.
_keepLast If true (the default), keeps only the most recent label. If false, prints labels up to the TradingView limit.
_condition The condition which must evaluate true for the label to be printed.
_y The y location.
_text The text to print on the label.
_color The colour of the label.
_textColor The colour of the text.
_style The style of the label.
_yloc The y location type.
Returns A named label object with the supplied characteristics.
MathSpecialFunctionsDiscreteFourierTransformLibrary "MathSpecialFunctionsDiscreteFourierTransform"
Method for Complex Discrete Fourier Transform (DFT).
dft(inputs, inverse) Complex Discrete Fourier Transform (DFT).
Parameters:
inputs : float array, pseudo complex array of paired values .
inverse : bool, invert the transformation.
Returns: float array, pseudo complex array of paired values .