supertrendHere is an extensive library on different variations of supertrend.
Library "supertrend"
supertrend : Library dedicated to different variations of supertrend
supertrend_atr(length, multiplier, atrMaType, source, highSource, lowSource, waitForClose, delayed) supertrend_atr: Simple supertrend based on atr but also takes into consideration of custom MA Type, sources
Parameters:
length : : ATR Length
multiplier : : ATR Multiplier
atrMaType : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma
source : : Default is close. Can Chose custom source
highSource : : Default is high. Can also use close price for both high and low source
lowSource : : Default is low. Can also use close price for both high and low source
waitForClose : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.
delayed : : if set to true lags supertrend atr stop based on target levels.
Returns: dir : Supertrend direction
supertrend : BuyStop if direction is 1 else SellStop
supertrend_bands(bandType, maType, length, multiplier, source, highSource, lowSource, waitForClose, useTrueRange, useAlternateSource, alternateSource, sticky) supertrend_bands: Simple supertrend based on atr but also takes into consideration of custom MA Type, sources
Parameters:
bandType : : Type of band used - can be bb, kc or dc
maType : : Moving Average type for Bands. This can be sma, ema, hma, rma, wma, vwma, swma
length : : Band Length
multiplier : : Std deviation or ATR multiplier for Bollinger Bands and Keltner Channel
source : : Default is close. Can Chose custom source
highSource : : Default is high. Can also use close price for both high and low source
lowSource : : Default is low. Can also use close price for both high and low source
waitForClose : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.
useTrueRange : : Used for Keltner channel. If set to false, then high-low is used as range instead of true range
useAlternateSource : - Custom source is used for Donchian Chanbel only if useAlternateSource is set to true
alternateSource : - Custom source for Donchian channel
sticky : : if set to true borders change only when price is beyond borders.
Returns: dir : Supertrend direction
supertrend : BuyStop if direction is 1 else SellStop
supertrend_zigzag(length, history, useAlternateSource, alternateSource, source, highSource, lowSource, waitForClose, atrlength, multiplier, atrMaType) supertrend_zigzag: Zigzag pivot based supertrend
Parameters:
length : : Zigzag Length
history : : number of historical pivots to consider
useAlternateSource : - Custom source is used for Zigzag only if useAlternateSource is set to true
alternateSource : - Custom source for Zigzag
source : : Default is close. Can Chose custom source
highSource : : Default is high. Can also use close price for both high and low source
lowSource : : Default is low. Can also use close price for both high and low source
waitForClose : : Considers source for direction change crossover if checked. Else, uses highSource and lowSource.
atrlength : : ATR Length
multiplier : : ATR Multiplier
atrMaType : : Moving Average type for ATR calculation. This can be sma, ema, hma, rma, wma, vwma, swma
Returns: dir : Supertrend direction
supertrend : BuyStop if direction is 1 else SellStop
指標和策略
Algomojo V1.0Library "Algomojo"
This library brings faster access to Automate trades. It simplifies the execution rules and helps
traders to implement faster algo trading strategies.
algomodule()
Bursa_SectorLibrary "Bursa_Sector"
: List of stocks classified by sector in Bursa Malaysia (As of Oct 2021)
getSector()
This function will get the sector of current stock that listed in Bursa Malaysia
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
CreateAndShowZigzagLibrary "CreateAndShowZigzag"
Functions in this library creates/updates zigzag array and shows the zigzag
getZigzag(zigzag, prd, max_array_size) calculates zigzag using period
Parameters:
zigzag : is the float array for the zigzag (should be defined like "var zigzag = array.new_float(0)"). each zigzag points contains 2 element: 1. price level of the zz point 2. bar_index of the zz point
prd : is the length to calculate zigzag waves by highest(prd)/lowest(prd)
max_array_size : is the maximum number of elements in zigzag, keep in mind each zigzag point contains 2 elements, so for example if it's 10 then zigzag has 10/2 => 5 zigzag points
Returns: dir that is the current direction of the zigzag
showZigzag(zigzag, oldzigzag, dir, upcol, dncol) this function shows zigzag
Parameters:
zigzag : is the float array for the zigzag (should be defined like "var zigzag = array.new_float(0)"). each zigzag points contains 2 element: 1. price level of the zz point 2. bar_index of the zz point
oldzigzag : is the float array for the zigzag, you get copy the zigzag array to oldzigzag by "oldzigzag = array.copy(zigzay)" before calling get_zigzag() function
dir : is the direction of the zigzag wave
upcol : is the color of the line if zigzag direction is up
dncol : is the color of the line if zigzag direction is down
Returns: null
MathComplexEvaluateLibrary "MathComplexEvaluate"
TODO: add library description here
is_op(char) Check if char is a operator.
Parameters:
char : string, 1 character string.
Returns: bool.
operator(op, left, right) operation between left and right values.
Parameters:
op : string, operator string character.
left : float, left value of operation.
right : float, right value of operation.
operator_precedence(op) level of precedence of operator.
Parameters:
op : string, operator 1 char string.
Returns: int.
eval() evaluate a string with references to a array of arguments.
| @param tokens string, arithmetic operations with references to indices in arguments, ex:"0+1*0+2*2+3" arguments
| @param arguments float array, arguments.
| @returns float, solution.
MathComplexTrignometryLibrary "MathComplexTrignometry"
Methods for complex number trignometry operations.
sinh(complex) Hyperbolic Sine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
cosh(complex) Hyperbolic cosine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
tanh(complex) Hyperbolic tangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
coth(complex) Hyperbolic cotangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
sech(complex) Hyperbolic Secant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
csch(complex) Hyperbolic Cosecant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
sin(complex) Trigonometric Sine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
cos(complex) Trigonometric cosine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
tan(complex) Trigonometric tangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
cot(complex) Trigonometric cotangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
sec(complex) Trigonometric Secant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
csc(complex) Trigonometric Cosecant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
asin(complex) Trigonometric Arc Sine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
acos(complex) Trigonometric Arc Cosine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
atan(complex) Trigonometric Arc Tangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
acot(complex) Trigonometric Arc Cotangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
asec(complex) Trigonometric Arc Secant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
acsc(complex) Trigonometric Arc Cosecant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
asinh(complex) Hyperbolic Arc Sine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
acosh(complex) Hyperbolic Arc Cosine of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
atanh(complex) Hyperbolic Arc Tangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
acoth(complex) Hyperbolic Arc Cotangent of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
asech(complex) Hyperbolic Arc Secant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
acsch(complex) Hyperbolic Arc Cosecant of complex number.
Parameters:
complex : float array, complex number.
Returns: float array.
MathComplexExtensionLibrary "MathComplexExtension"
A set of utility functions to handle complex numbers.
get_phase(complex_number, in_radians) The phase value of complex number complex_number.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
in_radians : boolean, value for the type of angle value, default=true, options=(true: radians, false: degrees)
Returns: float value with phase.
natural_logarithm(complex_number) Natural logarithm of complex number (base E).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, complex number.
common_logarithm(complex_number) Common logarithm of complex number (base 10).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, complex number.
logarithm(complex_number, base) Common logarithm of complex number (custom base).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
base : float, base value.
Returns: float array, complex number.
power(complex_number, complex_exponent) Raise complex_number with complex_exponent.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
complex_exponent : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
root(complex_number, complex_exponent) Raise complex_number with inverse of complex_exponent.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
complex_exponent : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
square(complex_number) Square of complex_number (power 2).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
square_root(complex_number) Square root of complex_number (power 1/2).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
square_roots(complex_number) Square root of complex_number (power 1/2).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: tuple with 2 complex numbers.
cubic_roots(complex_number) Square root of complex_number (power 1/2).
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: tuple with 2 complex numbers.
to_polar_form(complex_number, in_radians) The polar form value of complex_number.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
in_radians : boolean, value for the type of angle value, default=true, options=(true: radians, false: degrees)
Returns: float array, pseudo complex number in the form of a array
** returns a array
MathComplexOperatorLibrary "MathComplexOperator"
A set of utility functions to handle complex numbers.
conjugate(complex_number) Computes the conjugate of complex_number by reversing the sign of the imaginary part.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
add(complex_number_a, complex_number_b) Adds complex number complex_number_b to complex_number_a, in the form:
.
Parameters:
complex_number_a : pseudo complex number in the form of a array .
complex_number_b : pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
subtract(complex_number_a, complex_number_b) Subtract complex_number_b from complex_number_a, in the form:
.
Parameters:
complex_number_a : float array, pseudo complex number in the form of a array .
complex_number_b : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
multiply(complex_number_a, complex_number_b) Multiply complex_number_a with complex_number_b, in the form:
Parameters:
complex_number_a : float array, pseudo complex number in the form of a array .
complex_number_b : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
divide(complex_number_a, complex_number_b) Divide complex_number _a with _b, in the form:
Parameters:
complex_number_a : float array, pseudo complex number in the form of a array .
complex_number_b : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
reciprocal(complex_number) Computes the reciprocal or inverse of complex_number.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
negative(complex_number) Negative of complex_number, in the form:
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
inverse(complex_number) Inverse of complex_number, in the form:
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
exponential(complex_number) Exponential of complex_number.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: float array, pseudo complex number in the form of a array
ceil(complex_number, digits) Ceils complex_number.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
digits : int, digits to use as ceiling.
Returns: _complex: pseudo complex number in the form of a array
radius(complex_number) Radius(magnitude) of complex_number, in the form:
This is defined as its distance from the origin (0,0) of the complex plane.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float value with radius.
magnitude(complex_number) magnitude(absolute value) of complex_number, should be the same as the radius.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float.
magnitude_squared(complex_number) magnitude(absolute value) of complex_number, should be the same as the radius.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float.
sign(complex_number) Unity of complex numbers.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
Returns: float array, complex number.
MathComplexArrayLibrary "MathComplexArray"
Array methods to handle complex number arrays.
new(size, initial_complex) Prototype to initialize a array of complex numbers.
Parameters:
size : size of the array.
initial_complex : Complex number to be used as default value, in the form of array .
Returns: float array, pseudo complex Array in the form of a array
get(id, index) Get the complex number in a array, in the form of a array
Parameters:
id : float array, ID of the array.
index : int, Index of the complex number.
Returns: float array, pseudo complex number in the form of a array
set(id, index, complex_number) Sets the values complex number in a array.
Parameters:
id : float array, ID of the array.
index : int, Index of the complex number.
complex_number : float array, Complex number, in the form: .
Returns: Void, updates array id.
push(id, complex_number) Push the values into a complex number array.
Parameters:
id : float array, ID of the array.
complex_number : float array, Complex number, in the form: .
Returns: Void, updates array id.
pop(id, complex_number) Pop the values from a complex number array.
Parameters:
id : float array, ID of the array.
complex_number : float array, Complex number, in the form: .
Returns: Void, updates array id.
to_string(id, format) Reads a array of complex numbers into a string, of the form: " [ , ... ]""
Parameters:
id : float array, ID of the array.
format : string, format of the number conversion, default='#.##########'.
Returns: string, translated complex array into string.
MathComplexCoreLibrary "MathComplexCore"
Core functions to handle complex numbers.
set_real(complex_number, real) Set the real part of complex_number.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
real : float, value to replace real value of complex_number.
Returns: Void, Modifies complex_number.
set_imaginary(complex_number, imaginary) Set the imaginary part of complex_number.
Parameters:
complex_number : float array, pseudo complex number in the form of a array .
imaginary : float, value to replace imaginary value of complex_number.
Returns: Void, Modifies complex_number.
new(real, imaginary) Creates a prototype array to handle complex numbers.
Parameters:
real : float, real value of the complex number. default=0.
imaginary : float, imaginary number of the complex number. default=0.
@return float array, pseudo complex number in the form of a array .
zero() complex number "0+0i".
@return float array, pseudo complex number in the form of a array .
one() complex number "1+0i".
@return float array, pseudo complex number in the form of a array .
imaginary_one() complex number "0+1i".
@return float array, pseudo complex number in the form of a array .
nan() complex number "0+1i".
@return float array, pseudo complex number in the form of a array .
from_polar_coordinates(magnitude, phase) Create a complex number from a point's polar coordinates.
Parameters:
magnitude : float, default=0.0, The magnitude, which is the distance from the origin (the intersection of the x-axis and the y-axis) to the number.
phase : float, default=0.0, The phase, which is the angle from the line to the horizontal axis, measured in radians.
@return float array, pseudo complex number in the form of a array .
get_real(complex_number) Get the real part of complex_number.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: float, Real part of the complex_number.
get_imaginary(complex_number) Get the imaginary part of complex_number.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: float, Imaginary part of the complex number.
is_complex(complex_number) Checks that its a valid complex_number.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: bool.
is_nan(complex_number) Checks that its empty "na" complex_number.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: bool.
is_real(complex_number) Checks that the complex_number is real.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: bool.
is_real_non_negative(complex_number) Checks that the complex_number is real and not negative.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: bool.
is_zero(complex_number) Checks that the complex_number is zero.
Parameters:
complex_number : pseudo complex number in the form of a array .
Returns: bool.
equals(complex_number_a, complex_number_b) Compares two complex numbers:
Parameters:
complex_number_a : float array, pseudo complex number in the form of a array .
complex_number_b : float array, pseudo complex number in the form of a array .
Returns: boolean value representing the equality.
to_string(complex, format) Converts complex_number to a string format, in the form: "a+bi"
Parameters:
complex : pseudo complex number in the form of a array .
format : string, formating to apply.
Returns: a string in "a+bi" format
FunctionBestFitFrequencyLibrary "FunctionBestFitFrequency"
TODO: add library description here
array_moving_average(sample, length, ommit_initial, fillna) Moving Average values for selected data.
Parameters:
sample : float array, sample data values.
length : int, length to smooth the data.
ommit_initial : bool, default=true, ommit values at the start of the data under the length.
fillna : string, default='na', options='na', '0', 'avg'
Returns: float array
errors:
length > sample size "Canot call array methods when id of array is na."
best_fit_frequency(sample, start, end) Search a frequency range for the fairest moving average frequency.
Parameters:
sample : float array, sample data to based the moving averages.
start : int lowest frequency.
end : int highest frequency.
Returns: tuple with (int frequency, float percentage)
ArrayStatisticsLibrary "ArrayStatistics"
Statistic Functions using arrays.
rms(sample) Root Mean Squared
Parameters:
sample : float array, data sample points.
Returns: float
skewness_pearson1(sample) Pearson's 1st Coefficient of Skewness.
Parameters:
sample : float array, data sample.
Returns: float
skewness_pearson2(sample) Pearson's 2nd Coefficient of Skewness.
Parameters:
sample : float array, data sample.
Returns: float
pearsonr(sample_a, sample_b) Pearson correlation coefficient measures the linear relationship between two datasets.
Parameters:
sample_a : float array, sample with data.
sample_b : float array, sample with data.
Returns: float p
kurtosis(sample) Kurtosis of distribution.
Parameters:
sample : float array, data sample.
Returns: float
range_int(sample, percent) Get range around median containing specified percentage of values.
Parameters:
sample : int array, Histogram array.
percent : float, Values percentage around median.
Returns: tuple with , Returns the range which containes specifies percentage of values.
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.
ArrayOperationsIntLibrary "ArrayOperationsInt"
Array Basic Operations for Integers
add(sample_a, sample_b) Adds sample_b to sample_a and returns a new array.
Parameters:
sample_a : values to be added to.
sample_b : values to add.
Returns: int array with added results.
subtract(sample_a, sample_b) subtracts sample_b from sample_a and returns a new array.
Parameters:
sample_a : values to be subtracted from.
sample_b : values to subtract.
Returns: int array with subtracted results.
multiply(sample_a, sample_b) multiply sample_a with sample_b and returns a new array.
Parameters:
sample_a : values to multiply.
sample_b : values to multiply with.
Returns: int array with multiplied results.
divide(sample_a, sample_b) divide sample_a with sample_b and returns a new array.
Parameters:
sample_a : values to divide.
sample_b : values to divide with.
Returns: int array with divided results.
power(sample_a, sample_b) rise sample_a to the power of sample_b and returns a new array.
Parameters:
sample_a : base values to raise.
sample_b : values of exponents.
Returns: int array with raised results.
remainder(sample_a, sample_b) integer remainder of sample_a under the dividend sample_b and returns a new array.
Parameters:
sample_a : values of quotients.
sample_b : values of dividends.
Returns: int array with remainder results.
ArrayOperationsFloatLibrary "ArrayOperationsFloat"
Array Basic Operations for Integers
add(sample_a, sample_b) Adds sample_b to sample_a and returns a new array.
Parameters:
sample_a : values to be added to.
sample_b : values to add.
Returns: float array with added results.
subtract(sample_a, sample_b) subtracts sample_b from sample_a and returns a new array.
Parameters:
sample_a : values to be subtracted from.
sample_b : values to subtract.
Returns: float array with subtracted results.
multiply(sample_a, sample_b) multiply sample_a with sample_b and returns a new array.
Parameters:
sample_a : values to multiply.
sample_b : values to multiply with.
Returns: float array with multiplied results.
divide(sample_a, sample_b) divide sample_a with sample_b and returns a new array.
Parameters:
sample_a : values to divide.
sample_b : values to divide with.
Returns: float array with divided results.
power(sample_a, sample_b) rise sample_a to the power of sample_b and returns a new array.
Parameters:
sample_a : base values to raise.
sample_b : values of exponents.
Returns: float array with raised results.
remainder(sample_a, sample_b) float remainder of sample_a under the dividend sample_b and returns a new array.
Parameters:
sample_a : values of quotients.
sample_b : values of dividends.
Returns: float array with remainder results.
LineGetPriceOnLogScaleLibrary "LineGetPriceOnLogScale"
This library provides a way to calculate the y-coordinate of a line on a specified bar when the chart scale is Log.
The built-in `line.get_price()` function only works with linear scale and gives incorrect results when the chart is in Log scale.
The library only works with `bar_index` values and `xloc.bar_index`-based lines, `time`-based lines will cause errors to appear.
coordGetPriceLog(x1, y1, x2, y2, xi) Calculates the y-coordinate on the specified bar on the logarithmic scale.
Only coordinates based on bar index are applicable, bar time will throw an error.
Parameters:
x1 : First X coordinate of a line, index of the bar where the line starts.
y1 : First Y coordinate of a line, price on the price scale.
x2 : Second X coordinate of a line, index of the bar where the line ends.
y2 : Second Y coordinate of a line, price on the price scale.
xi : Index of the bar for which the price should be calculated.
Returns: Price of the line on the bar specified in `xi`, on the logarithmic scale.
lineGetPriceLog(_line, xi) Calculates the y-coordinate on the specified bar for the logarithmic scale. Takes a line.
Only lines drawn based on `xloc.bar_index` are applicable, `xloc.bar_time` will throw and error.
Parameters:
_line : The line for which the price is calculated.
xi : Index of the bar for which the bar should calculate the price.
Returns: Price of the line on the bar specified in `xi`, on the logarithmic scale.
BinaryDecimalConversionLibrary "BinaryDecimalConversion"
Converts decimal to and from binary.
to_binary(number) convert integer to binary string
Parameters:
number : int, value to convert.
Returns: string
to_decimal(binary) Converts a binary in a string to decimal.
Parameters:
binary : string, binary number in a string.
Returns: int
StringEvaluationLibrary "StringEvaluation"
Methods to handle evaluation of strings.
is_comma(char) Check if char is a comma ".".
Parameters:
char : string, 1 character string.
Returns: bool.
is_op(char) Check if char is a operator.
Parameters:
char : string, 1 character string.
Returns: bool.
number(char) convert a single char string into valid number.
Parameters:
char : string, 1 character string.
Returns: float.
operator(op, left, right) operation between left and right values.
Parameters:
op : string, operator string character.
left : float, left value of operation.
right : float, right value of operation.
operator_precedence(op) level of precedence of operator.
Parameters:
op : string, operator 1 char string.
Returns: int.
cleanup(_str) Evaluate a string to clean up and retrieve only used chars
Parameters:
_str : string, arithmetic operations in a string.
Returns: string array, evaluated array.
generate_rpn(tokens) uses Shunting-Yard algorithm to generate a RPN (Reverse Polish notation)
array of strings from a array of strings containing arithmetic notation.
ex:.. ' ' --> ' '
Parameters:
tokens : string array, array with arithmetic notation.
Returns:
parse_rpn() evaluate a RPN (Reverse Polish notation) array of strings.
ex:.. 3 4 2 * 1 5 - 2 3 ^ ^ / +
| @param tokens string array, RPN ordered tokens, ex( ).
| @returns float, solution.
eval() evaluate a string with references to a array of arguments.
| @param tokens string, arithmetic operations with references to indices in arguments, ex:"0+1*0+2*2+3" arguments
| @param arguments float array, arguments.
| @returns float, solution.
SignificantFiguresLibrary "SignificantFigures"
sigFig(float _float, int _figures)
@description Takes a floating-point number - one that can, but doesn't have to, include a decimal point - and converts it to a floating-point number with only a certain number of digits left. For example, say you want to display a variable from your script to the user and it comes out to something like 45.366666666666666666666667 or whatever. That looks awful when you, for example, print it in a label. Now you could round it up to the nearest integer easily using a built-in function, or even to a certain number of decimal places using a reasonably simple custom function. But that's a bit arbitrary. Suppose you don't know what asset the script will be used on, and so you can't predict what the price is, and what the value will turn out to be. It could be 0.00045366666666666666666666667 instead. Now if you round it up to 3 decimal places it comes out as 0.000, which is useless. My function will round that number to 0.0004536 instead, if told to do it to 4 significant digits.
I think this is more friendly.
@function Converts float with arbitrary number of digits to one with a specified number of significant figures.
@param float _float is the floating-point number to manipulate.
@param int _figures is the number of significant figures you want.
@returns Returns a float with the specified number of significant figures
MathSpecialFunctionsGammaLibrary "MathSpecialFunctionsGamma"
Gamma Functions.
GammaQ(index) Enumeration of the polynomial coefficients for the "GammaLn" approximation.
Parameters:
index : int, 0 => index => 10, index of coeficient.
Returns: float
GammaLn(z) Computes the logarithm of the Gamma function.
Parameters:
z : The argument of the gamma function.
Returns: The logarithm of the gamma function.
Gamma(z) Computes the Gamma function.
Parameters:
z : The argument of the gamma function.
Returns: float, The logarithm of the gamma function.
GammaLowerRegularized(a, x)
Parameters:
a : float, The argument for the gamma function.
x : float, The upper integral limit.
Returns: float, The lower incomplete gamma function.
GammaUpperRegularized(a, x) Returns the upper incomplete regularized gamma function
Parameters:
a : float, The argument for the gamma function.
x : float, The lower integral limit.
Returns: float, The upper incomplete regularized gamma function.
GammaUpperIncomplete(a, x) Returns the upper incomplete gamma function.
Parameters:
a : float, The argument for the gamma function.
x : float, The lower integral limit.
Returns: float, The upper incomplete gamma function.
GammaLowerIncomplete(a, x)
Parameters:
a : float, The argument for the gamma function.
x : float, The upper integral limit.
Returns: float, The lower incomplete gamma function.
ProbabilityLibrary "Probability"
erf(value) Complementary error function
Parameters:
value : float, value to test.
Returns: float
ierf_mcgiles(value) Computes the inverse error function using the Mc Giles method, sacrifices accuracy for speed.
Parameters:
value : float, -1.0 >= _value >= 1.0 range, value to test.
Returns: float
ierf_double(value) computes the inverse error function using the Newton method with double refinement.
Parameters:
value : float, -1. > _value > 1. range, _value to test.
Returns: float
ierf(value) computes the inverse error function using the Newton method.
Parameters:
value : float, -1. > _value > 1. range, _value to test.
Returns: float
complement(probability) probability that the event will not occur.
Parameters:
probability : float, 0 >=_p >= 1, probability of event.
Returns: float
entropy_gini_impurity_single(probability) Gini Inbalance or Gini index for a given probability.
Parameters:
probability : float, 0>=x>=1, probability of event.
Returns: float
entropy_gini_impurity(events) Gini Inbalance or Gini index for a series of events.
Parameters:
events : float , 0>=x>=1, array with event probability's.
Returns: float
entropy_shannon_single(probability) Entropy information value of the probability of a single event.
Parameters:
probability : float, 0>=x>=1, probability value.
Returns: float, value as bits of information.
entropy_shannon(events) Entropy information value of a distribution of events.
Parameters:
events : float , 0>=x>=1, array with probability's.
Returns: float
inequality_chebyshev(n_stdeviations) Calculates Chebyshev Inequality.
Parameters:
n_stdeviations : float, positive over or equal to 1.0
Returns: float
inequality_chebyshev_distribution(mean, std) Calculates Chebyshev Inequality.
Parameters:
mean : float, mean of a distribution
std : float, standard deviation of a distribution
Returns: float
inequality_chebyshev_sample(data_sample) Calculates Chebyshev Inequality for a array of values.
Parameters:
data_sample : float , array of numbers.
Returns: float
intersection_of_independent_events(events) Probability that all arguments will happen when neither outcome
is affected by the other (accepts 1 or more arguments)
Parameters:
events : float , 0 >= _p >= 1, list of event probabilities.
Returns: float
union_of_independent_events(events) Probability that either one of the arguments will happen when neither outcome
is affected by the other (accepts 1 or more arguments)
Parameters:
events : float , 0 >= _p >= 1, list of event probabilities.
Returns: float
mass_function(sample, n_bins) Probabilities for each bin in the range of sample.
Parameters:
sample : float , samples to pool probabilities.
n_bins : int, number of bins to split the range
@return float
cumulative_distribution_function(mean, stdev, value) Use the CDF to determine the probability that a random observation
that is taken from the population will be less than or equal to a certain value.
Or returns the area of probability for a known value in a normal distribution.
Parameters:
mean : float, samples to pool probabilities.
stdev : float, number of bins to split the range
value : float, limit at which to stop.
Returns: float
transition_matrix(distribution) Transition matrix for the suplied distribution.
Parameters:
distribution : float , array with probability distribution. ex:.
Returns: float
diffusion_matrix(transition_matrix, dimension, target_step) Probability of reaching target_state at target_step after starting from start_state
Parameters:
transition_matrix : float , "pseudo2d" probability transition matrix.
dimension : int, size of the matrix dimension.
target_step : number of steps to find probability.
Returns: float
state_at_time(transition_matrix, dimension, start_state, target_state, target_step) Probability of reaching target_state at target_step after starting from start_state
Parameters:
transition_matrix : float , "pseudo2d" probability transition matrix.
dimension : int, size of the matrix dimension.
start_state : state at which to start.
target_state : state to find probability.
target_step : number of steps to find probability.
MathStatisticsKernelDensityEstimationLibrary "MathStatisticsKernelDensityEstimation"
(KDE) Method for Kernel Density Estimation
kde(observations, kernel, bandwidth, nsteps)
Parameters:
observations : float array, sample data.
kernel : string, the kernel to use, default='gaussian', options='uniform', 'triangle', 'epanechnikov', 'quartic', 'triweight', 'gaussian', 'cosine', 'logistic', 'sigmoid'.
bandwidth : float, bandwidth to use in kernel, default=0.5, range=(0, +inf), less will smooth the data.
nsteps : int, number of steps in range of distribution, default=20, this value is connected to how many line objects you can display per script.
Returns: tuple with signature: (float array, float array)
draw_horizontal(distribution_x, distribution_y, distribution_lines, graph_lines, graph_labels) Draw a horizontal distribution at current location on chart.
Parameters:
distribution_x : float array, distribution points x value.
distribution_y : float array, distribution points y value.
distribution_lines : line array, array to append the distribution curve lines.
graph_lines : line array, array to append the graph lines.
graph_labels : label array, array to append the graph labels.
Returns: void, updates arrays: distribution_lines, graph_lines, graph_labels.
draw_vertical(distribution_x, distribution_y, distribution_lines, graph_lines, graph_labels) Draw a vertical distribution at current location on chart.
Parameters:
distribution_x : float array, distribution points x value.
distribution_y : float array, distribution points y value.
distribution_lines : line array, array to append the distribution curve lines.
graph_lines : line array, array to append the graph lines.
graph_labels : label array, array to append the graph labels.
Returns: void, updates arrays: distribution_lines, graph_lines, graph_labels.
style_distribution(lines, horizontal, to_histogram, line_color, line_style, linewidth) Style the distribution lines.
Parameters:
lines : line array, distribution lines to style.
horizontal : bool, default=true, if the display is horizontal(true) or vertical(false).
to_histogram : bool, default=false, if graph style should be switched to histogram.
line_color : color, default=na, if defined will change the color of the lines.
line_style : string, defaul=na, if defined will change the line style, options=('na', line.style_solid, line.style_dotted, line.style_dashed, line.style_arrow_right, line.style_arrow_left, line.style_arrow_both)
linewidth : int, default=na, if defined will change the line width.
Returns: void.
style_graph(lines, lines, horizontal, line_color, line_style, linewidth) Style the graph lines and labels
Parameters:
lines : line array, graph lines to style.
lines : labels array, graph labels to style.
horizontal : bool, default=true, if the display is horizontal(true) or vertical(false).
line_color : color, default=na, if defined will change the color of the lines.
line_style : string, defaul=na, if defined will change the line style, options=('na', line.style_solid, line.style_dotted, line.style_dashed, line.style_arrow_right, line.style_arrow_left, line.style_arrow_both)
linewidth : int, default=na, if defined will change the line width.
Returns: void.
