toolsLibrary "tools"
A library of many helper methods, plus a comprehensive print method and a printer object.
This is a newer version of the helpers library. This script uses pinescripts v5 latest objects and methods.
المؤشرات والاستراتيجيات
peterzorve-libraryLibrary "library"
is_bullish_engulfing()
is_bearish_engulfing()
is_hammer(fib_level)
Parameters:
fib_level (float)
is_shooting_star(fib_level)
Parameters:
fib_level (float)
is_hammer_and_star(fib_level)
Parameters:
fib_level (float)
is_star_and_hammer(fib_level)
Parameters:
fib_level (float)
is_dogi(dogi_body_ratio)
Parameters:
dogi_body_ratio (float)
is_bear_bear_bullish_engulf()
is_atr_stoploss_takeprofit(atr_multiplier, atr_length, reward_ratio)
Parameters:
atr_multiplier (float)
atr_length (simple int)
reward_ratio (float)
is_fixed_stoploss_takeprofit(stoploss_pips, reward_ratio)
Parameters:
stoploss_pips (float)
reward_ratio (float)
is_step_trailing_stoploss(stoploss_pips)
Parameters:
stoploss_pips (float)
is_atr_trailing_stoploss(atr_multiplier, break_even_pip)
Parameters:
atr_multiplier (float)
break_even_pip (int)
is_pull_back_strategy(length)
Parameters:
length (simple int)
is_trade_statistics(condition, entrypoint, stoploss, takeprofit)
Parameters:
condition (bool)
entrypoint (float)
stoploss (float)
takeprofit (float)
is_table_of_statistics(win_trades, lost_trades, even_trades, pips_won, pips_lost)
Parameters:
win_trades (int)
lost_trades (int)
even_trades (int)
pips_won (float)
pips_lost (float)
is_pine_info(lotsize, stoploss, takeprofit)
Parameters:
lotsize (float)
stoploss (float)
takeprofit (float)
is_support_and_resistance_strategy(look_back, look_forward)
Parameters:
look_back (int)
look_forward (int)
is_choral_strategy(smoothing_period, constant_d)
Parameters:
smoothing_period (int)
constant_d (float)
is_bollinger_band_strategy(length, dev_entry, dev_stoploss, dev_takeprofit)
Parameters:
length (int)
dev_entry (simple float)
dev_stoploss (simple float)
dev_takeprofit (simple float)
DiddlyUtilityLibrary "DiddlyUtility"
TODO: add library description here
getStringTimeMinus1Minute(london_ssth, london_sstm)
Parameters:
london_ssth
london_sstm
getLadderStepIncrement(_price)
Parameters:
_price
getLadderIndexForPrice(_price, _ladderRange)
Parameters:
_price
_ladderRange
getLadderStartPriceRange(_price, _ladderRange)
Parameters:
_price
_ladderRange
get_volume_string(_volume)
Parameters:
_volume
floorDown(number, decimals)
Parameters:
number
decimals
countDigitsBeforeDecimal(n)
Parameters:
n
countDigitsAfterDecimal(n)
Parameters:
n
getChartTimePeriodAsSeconds(_chartPeriod)
Parameters:
_chartPeriod
debug(_txt)
Parameters:
_txt
Console📕 Console Library
🔷 Introduction
This script is an adaptation of the classic JavaScript console script. It provides a simple way to display data in a console-like table format for debugging purposes.
While there are many nice console/logger scripts out there, my personal goal was to achieve inline functionality and visual object (label, lines) logging .
🔷 How to Use
◼ 1. Import the Console library into your script:
import cryptolinx/Console/1
- or -
Instead of the library namespace, you can define a custom namespace as alias.
import cryptolinx/Console/1 as c
◼ 2. Create and init a new `` object.
The `init()` method is used to initialize the console object with default settings. It can be used to customize it.
// When using the `var` keyword in a declaration, the logs will act as ever-forwarding.
// Without `var`, the `console` variable will be redeclared every time `bar` is called.
// var console = Console.terminal.new(log_position=position.bottom_left, prefix = '> ', show_no = true)
- or -
If you has set up an alias before.
var console = c.terminal.new().init()
◼ 3. Logging
// inline ✨
array testArray = array.new(3, .0).log(console)
// basic
console.log(testArray)
// inline ✨
var testLabel = label.new(bar_index, close, 'Label Text').log(console)
// basic
console.log(testLabel)
// It is also possible to use `().` for literals ✨.
int a = 100
testCalc = (5 * 100).log(console) + a.log(console) // SUM: 600
console.
.empty()
.log('SUM' + WS + testCalc.tostring())
◼ 4. Visibility
Finally, we need to call the `show()` method to display the logged messages in the console.
console.show(true) // True by default. Simply turn it on or off
LibAndyLibrary "LibAndy"
TODO: add library description here
greencandlme(x)
TODO: add function description here
Parameters:
x (float) : TODO: add parameter x description here
Returns: TODO: add what function returns
greencandle()
Whether this candle is green or not
Returns: Whether this candle is green or not
redcandle()
Whether this candle is red or not
Returns: Whether this candle is red or not
boostrapSeries(bsSeries)
Parameters:
bsSeries (float)
PolynomialLibrary "Polynomial"
TODO: add library description here
PolyNomial(Dop, n, step, nonp)
TODO: add function description here
Parameters:
Dop (int)
n (int)
step (int)
nonp (int)
Returns: TODO: add what function returns
Branch CurveLibrary "branch"
Generates a branch made of segments with a starting angle
and a turning angle for each segment. The branch is generated from a starting point
and a number of nodes to generate. The length of each segment and angle of each segment
can be adjusted. The branch can be generated in 2D or 3D, render as you wish.
method branch(origin, nodes, segment_length, segment_growth, angle_start, angle_turn)
# Branch Generation.
- `origin`: CommonTypesMath.Vector3 - The starting point of the branch. If the z value is not zero, it will be used as the starting angle.
- `nodes`: int - The number of nodes to generate.
- `segment_length`: float - The length of each segment.
- `segment_growth`: float - The growth of each segment. 0 = no growth, 100 = double the length of the previous segment.
- `angle_start`: float - The starting angle of the branch in degrees.
- `angle_turn`: float - The turning angle of each segment in degrees.
Namespace types: CommonTypesMath.Vector3
Parameters:
origin (Vector3 type from RicardoSantos/CommonTypesMath/1) : The starting point of the branch. If the z value is not zero, it will be used as the starting angle.
nodes (int) : The number of nodes to generate.
segment_length (float) : The length of each segment.
segment_growth (float) : The growth of each segment. 0 = no growth, 100 = double the length of the previous segment.
angle_start (float) : The starting angle of the branch in degrees.
angle_turn (float) : The turning angle of each segment in degrees.
@return segments The list of segments that make up the branch.
VolumeLibLibrary "VolumeLib"
Contains types and methods related to VOLUME
volumePrice()
TODO: add function description here
Returns: TODO: add what function returns
averageVolumePrice(length)
Parameters:
length (simple int)
volumePower(volume_price, average_volume_price)
Parameters:
volume_price (float)
average_volume_price (float)
volumePower(length)
Parameters:
length (simple int)
OrderLibLibrary "OrderLib"
TODO: add library description here
removeOrderView(view)
Parameters:
view (orderView)
createOrderView(model, length, profit_color, loss_color, enter_color)
Parameters:
model (orderModel)
length (simple int)
profit_color (simple color)
loss_color (simple color)
enter_color (simple color)
createOrder(enter, tp, sl)
Parameters:
enter (float)
tp (float)
sl (float)
createOrderByRR(enter, sl, rr)
Parameters:
enter (float)
sl (float)
rr (float)
createOrderByRR(enter, sl, rr, commision_percent)
Parameters:
enter (float)
sl (float)
rr (simple float)
commision_percent (simple float)
orderModel
Fields:
enter (series__float)
sl (series__float)
tp (series__float)
orderView
Fields:
enter (series__line)
sl (series__line)
tp (series__line)
AdxLibLibrary "AdxLib"
TODO: add library description here
create(di_length, adx_length)
Parameters:
di_length (simple int)
adx_length (simple int)
create(adx_length)
Parameters:
adx_length (simple int)
TextLibLibrary "TextLib"
TODO: Library with text / string functions
addText(before, value, separator)
Parameters:
before (string)
value (string)
separator (string)
addText(before, value1, value2, separator)
Parameters:
before (string)
value1 (string)
value2 (string)
separator (string)
LibreLibrary "Libre"
TODO: add library description here
MMMM(toe)
Parameters:
toe (string)
OOOO(toe, toe1, toe2, toe3, toe4, toe5, init)
Parameters:
toe (string)
toe1 (string)
toe2 (string)
toe3 (string)
toe4 (string)
toe5 (string)
init (int)
XXXX(toe)
Parameters:
toe (string)
WWWW(toe)
Parameters:
toe (string)
HarmonicPatternTrackingLibrary "HarmonicPatternTracking"
Library contains few data structures and methods for tracking harmonic pattern trades via pinescript.
method draw(this)
Creates and draws HarmonicDrawing object for given HarmonicPattern
Namespace types: HarmonicPattern
Parameters:
this (HarmonicPattern) : HarmonicPattern object
Returns: current HarmonicPattern object
method addTrade(this)
calculates HarmonicTrade and sets trade object for HarmonicPattern
Namespace types: HarmonicPattern
Parameters:
this (HarmonicPattern) : HarmonicPattern object
Returns: bool true if pattern trades are valid, false otherwise
method delete(this)
Deletes drawing objects of HarmonicDrawing
Namespace types: HarmonicDrawing
Parameters:
this (HarmonicDrawing) : HarmonicDrawing object
Returns: current HarmonicDrawing object
method delete(this)
Deletes drawings of harmonic pattern
Namespace types: HarmonicPattern
Parameters:
this (HarmonicPattern) : HarmonicPattern object
Returns: current HarmonicPattern object
HarmonicDrawing
Drawing objects of Harmonic Pattern
Fields:
xa (series line) : xa line
ab (series line) : ab line
bc (series line) : bc line
cd (series line) : cd line
xb (series line) : xb line
bd (series line) : bd line
ac (series line) : ac line
xd (series line) : xd line
x (series label) : label for pivot x
a (series label) : label for pivot a
b (series label) : label for pivot b
c (series label) : label for pivot c
d (series label) : label for pivot d
xabRatio (series label) : label for XAB Ratio
abcRatio (series label) : label for ABC Ratio
bcdRatio (series label) : label for BCD Ratio
xadRatio (series label) : label for XAD Ratio
HarmonicTrade
Trade tracking parameters of Harmonic Patterns
Fields:
initialEntry (series float) : initial entry when pattern first formed.
entry (series float) : trailed entry price.
initialStop (series float) : initial stop when trade first entered.
stop (series float) : current stop updated as per trailing rules.
target1 (series float) : First target value
target2 (series float) : Second target value
target3 (series float) : Third target value
target4 (series float) : Fourth target value
status (series int) : Trade status referenced as integer
retouch (series bool) : Flag to show if the price retouched after entry
HarmonicProperties
Display and trade calculation properties for Harmonic Patterns
Fields:
fillMajorTriangles (series bool) : Display property used for using linefill for harmonic major triangles
fillMinorTriangles (series bool) : Display property used for using linefill for harmonic minor triangles
majorFillTransparency (series int) : transparency setting for major triangles
minorFillTransparency (series int) : transparency setting for minor triangles
showXABCD (series bool) : Display XABCD pivot labels
lblSizePivots (series string) : Pivot label size
showRatios (series bool) : Display Ratio labels
useLogScaleForScan (series bool) : Use log scale to determine fib ratios for pattern scanning
useLogScaleForTargets (series bool) : Use log scale to determine fib ratios for target calculation
base (series string) : base on which calculation of stop/targets are made.
entryRatio (series float) : fib ratio to calculate entry
stopRatio (series float) : fib ratio to calculate initial stop
target1Ratio (series float) : fib ratio to calculate first target
target2Ratio (series float) : fib ratio to calculate second target
target3Ratio (series float) : fib ratio to calculate third target
target4Ratio (series float) : fib ratio to calculate fourth target
HarmonicPattern
Harmonic pattern object to track entire pattern trade life cycle
Fields:
id (series int) : Pattern Id
dir (series int) : pattern direction
x (series float) : X Pivot
a (series float) : A Pivot
b (series float) : B Pivot
c (series float) : C Pivot
d (series float) : D Pivot
xBar (series int) : Bar index of X Pivot
aBar (series int) : Bar index of A Pivot
bBar (series int) : Bar index of B Pivot
cBar (series int) : Bar index of C Pivot
dBar (series int) : Bar index of D Pivot
przStart (series float) : Start of PRZ range
przEnd (series float) : End of PRZ range
patterns (bool ) : array representing the patterns
patternLabel (series string) : string representation of list of patterns
patternColor (series color) : color assigned to pattern
properties (HarmonicProperties) : HarmonicProperties object containing display and calculation properties
trade (HarmonicTrade) : HarmonicTrade object to track trades
drawing (HarmonicDrawing) : HarmonicDrawing object to manage drawings
AstroLibLibrary "AstroLib", or Astro Library, is a collection of public Pinescript functions & calculations for use in astrology & astronomy indicators. Unless noted otherwise, this library was written jointly by @badsector666 and @BarefootJoey.
Library "AstroLib"
t_(txt)
Parameters:
txt (string)
JDNv2(t, withFraction)
Parameters:
t (float)
withFraction (bool)
J2K(t)
Parameters:
t (float)
J2KtoUnix(TimeInJDN)
Parameters:
TimeInJDN (float)
atan2(y, x)
Parameters:
y (float)
x (float)
DegSin(x)
Parameters:
x (float)
DegCos(x)
Parameters:
x (float)
DegTan(x)
Parameters:
x (float)
DegArcsin(x)
Parameters:
x (float)
DegArccos(x)
Parameters:
x (float)
DegArctan(x)
Parameters:
x (float)
DegAtan2(y, x)
Parameters:
y (float)
x (float)
range2pi(x)
Parameters:
x (float)
range360(x)
Parameters:
x (float)
gst(days)
Parameters:
days (float)
DegDecimal(Degrees, Minutes, Seconds)
Parameters:
Degrees (float)
Minutes (float)
Seconds (float)
Rectangular(R, theta, phi, Index)
Parameters:
R (float)
theta (float)
phi (float)
Index (float)
rLength(x, y, z)
Parameters:
x (float)
y (float)
z (float)
spherical(x, y, z, Index)
Parameters:
x (float)
y (float)
z (float)
Index (float)
obliquity(d)
Parameters:
d (float)
requatorial(x, y, z, d, Index)
Parameters:
x (float)
y (float)
z (float)
d (float)
Index (float)
recliptic(x, y, z, d, Index)
Parameters:
x (float)
y (float)
z (float)
d (float)
Index (float)
sequatorial(R, theta, phi, d, Index)
Parameters:
R (float)
theta (float)
phi (float)
d (float)
Index (float)
secliptic(R, theta, phi, d, Index)
Parameters:
R (float)
theta (float)
phi (float)
d (float)
Index (float)
precess(d1, d2, DEC, RA, Index, ddec, dra)
Parameters:
d1 (float)
d2 (float)
DEC (float)
RA (float)
Index (float)
ddec (float)
dra (float)
riset(J2000, DEC, RA, GLat, GLong, Index)
Parameters:
J2000 (float)
DEC (float)
RA (float)
GLat (float)
GLong (float)
Index (float)
ssun(d, Index)
Parameters:
d (float)
Index (float)
rsun(d, Index)
Parameters:
d (float)
Index (float)
sun(d, Index)
Parameters:
d (float)
Index (float)
SunLongitude(d, Index)
Parameters:
d (float)
Index (float)
Sunrise(J2000, GLat, GLong, Index, altitudex)
Parameters:
J2000 (float)
GLat (float)
GLong (float)
Index (float)
altitudex (float)
smoon(dx, Index)
Parameters:
dx (float)
Index (float)
rmoon(d, Index)
Parameters:
d (float)
Index (float)
tmoon(d, GLat, GLong, Index)
Parameters:
d (float)
GLat (float)
GLong (float)
Index (float)
moon(d, Index)
Parameters:
d (float)
Index (float)
Element(d, pnum)
Parameters:
d (float)
pnum (int)
kepler(m, ecc, eps)
Parameters:
m (float)
ecc (float)
eps (float)
rplanet(d, pnumber, Index)
Parameters:
d (float)
pnumber (int)
Index (float)
planet(d, pnumber, Index)
Parameters:
d (float)
pnumber (int)
Index (float)
altaz(d, DEC, RA, GLat, GLong, Index)
Parameters:
d (float)
DEC (float)
RA (float)
GLat (float)
GLong (float)
Index (float)
prise(d, P, GLat, GLong, Index)
Parameters:
d (float)
P (int)
GLat (float)
GLong (float)
Index (float)
MoonSize(d)
Parameters:
d (float)
Refraction(Temperature_C, Atmospheric_Pressure_mBar, Altitude_Deg)
Parameters:
Temperature_C (float)
Atmospheric_Pressure_mBar (float)
Altitude_Deg (float)
MoonRise(d, Longitude, Latitude, Index)
Parameters:
d (float)
Longitude (float)
Latitude (float)
Index (float)
f_to_sec(dec)
Parameters:
dec (float)
f_to_time(sec)
Parameters:
sec (float)
deg_to_time(deg)
Parameters:
deg (float)
toDMS(coordinate)
Parameters:
coordinate (float)
convertDMS(lat, lng)
Parameters:
lat (float)
lng (float)
convlatdec(deg)
Parameters:
deg (float)
PlanetName(pnum)
Parameters:
pnum (int)
PlanetNameV(pnum)
Parameters:
pnum (int)
PlanetSign(pnum)
Parameters:
pnum (int)
PlanetColor(pnum)
Parameters:
pnum (int)
zodiaccolor(deg)
Parameters:
deg (float)
degsign(deg)
Parameters:
deg (float)
degsignf(deg)
Parameters:
deg (float)
degnash(deg)
Parameters:
deg (float)
degname(deg)
Parameters:
deg (float)
retrogradesym(deg)
Parameters:
deg (float)
degaspsign(deg)
Parameters:
deg (float)
degaspname(deg)
Parameters:
deg (float)
degaspfull(deg)
Parameters:
deg (float)
degaspfullV2(deg)
Parameters:
deg (float)
degaspnameV2(deg)
Parameters:
deg (float)
degtolowest180(deg)
Parameters:
deg (float)
degaspfullapproach(deg)
Parameters:
deg (float)
virinchiaspectcol(deg, bull_col, bear_col)
Parameters:
deg (float)
bull_col (color)
bear_col (color)
virinchiaspectemo(deg, bull_emo, bear_emo)
Parameters:
deg (float)
bull_emo (string)
bear_emo (string)
aspectfastsigndeg(deg)
Parameters:
deg (float)
aspectfastfull(deg)
Parameters:
deg (float)
aspectslowfull(deg)
Parameters:
deg (float)
aspectslowsigndeg(deg)
Parameters:
deg (float)
aspectslowsign(deg)
Parameters:
deg (float)
aspectsignprecision(deg, precision)
Parameters:
deg (float)
precision (int)
aspectsignprecisionV2(deg, precision)
Parameters:
deg (float)
precision (float)
aspectsignprecisionV2ext(deg, precision)
Parameters:
deg (float)
precision (float)
IPaspectsignprecision(planet1, planet2, precision)
Parameters:
planet1 (float)
planet2 (float)
precision (float)
IPaspectsignprecisionFull(planet1, planet2, precision)
Parameters:
planet1 (float)
planet2 (float)
precision (float)
IPaspectlineprecision(planet1, planet2, precision, style, width)
Parameters:
planet1 (float)
planet2 (float)
precision (float)
style (string)
width (int)
rDeg(deg)
Parameters:
deg (float)
AngToCirc(angle)
Parameters:
angle (float)
AngToCirc180(angle)
Parameters:
angle (float)
sidereal(deg, sidereal)
Parameters:
deg (float)
sidereal (bool)
J2000(JDN)
Parameters:
JDN (float)
JDN(t, d, tz)
Parameters:
t (float)
d (float)
tz (float)
getsun(index, day, dayr, latitude, longitude, tz)
Parameters:
index (int)
day (float)
dayr (float)
latitude (float)
longitude (float)
tz (float)
getmoon(index, day, dayr, latitude, longitude)
Parameters:
index (int)
day (float)
dayr (float)
latitude (float)
longitude (float)
getplanet(planet, index, day, dayr, latitude, longitude, tz)
Parameters:
planet (int)
index (int)
day (float)
dayr (float)
latitude (float)
longitude (float)
tz (float)
MarkovAlgorithmLibrary "MarkovAlgorithm"
Markov algorithm is a string rewriting system that uses grammar-like rules to operate on strings of
symbols. Markov algorithms have been shown to be Turing-complete, which means that they are suitable as a
general model of computation and can represent any mathematical expression from its simple notation.
~ wikipedia
.
reference:
en.wikipedia.org
rosettacode.org
parse(rules, separator)
Parameters:
rules (string)
separator (string)
Returns: - `array _rules`: List of rules.
---
Usage:
- `parse("|0 -> 0|| 1 -> 0| 0 -> ")`
apply(expression, rules)
Aplies rules to a expression.
Parameters:
expression (string) : `string`: Text expression to be formated by the rules.
rules (rule ) : `string`: Rules to apply to expression on a string format to be parsed.
Returns: - `string _result`: Formated expression.
---
Usage:
- `apply("101", parse("|0 -> 0|| 1 -> 0| 0 -> "))`
apply(expression, rules)
Parameters:
expression (string)
rules (string)
Returns: - `string _result`: Formated expression.
---
Usage:
- `apply("101", parse("|0 -> 0|| 1 -> 0| 0 -> "))`
rule
String pair that represents `pattern -> replace`, each rule may be ordinary or terminating.
Fields:
pattern (series string) : Pattern to replace.
replacement (series string) : Replacement patterns.
termination (series bool) : Termination rule.
new_line_dot_3Library "new_line"
TODO: plot line based on 3 points.
new_line(x_1, x_2, x_3, y_1, y_2, y_3)
TODO: plot line based on 3 points. (each different)
Parameters:
x_1 (int)
x_2 (int)
x_3 (int)
y_1 (float)
y_2 (float)
y_3 (float)
Returns: TODO: new line based on each different 3 values.
OHLC📕 LIBRARY OHLC
🔷 Introduction
This library is a custom library designed to work with real-time bars. It allows to easily calculate OHLC values for any source.
Personally, I use this library to accurately display the highest and lowest values on visual indicators such as my progress bars.
🔷 How to Use
◼ 1. Import the OHLC library into your TradingView script:
import cryptolinx/OHLC/1
- or -
Instead of the library namespace, you can define a custom namespace as alias.
import cryptolinx/OHLC/1 as src
◼ 2. Create a new OHLC source using the `new()` function.
varip mySrc = OHLC.new() // It is required to use the `varip` keyword to init your ``
- or -
If you has set up an alias before.
varip mySrc = src.new()
===
In that case, your `` needs to be `na`, define your object like that
varip mySrc = na
◼ 3. Call the `hydrateOHLC()` method on your OHLC source to update its values:
Basic
float rsi = ta.rsi(close, 14)
mySrc.hydrateOHLC(rsi)
- or -
Inline
rsi = ta.rsi(close, 14).hydrateOHLC(mySrc)
◼ 4. The data is accessible under their corresponding names.
mySrc.open
mySrc.high
mySrc.low
mySrc.close
🔷 Note: This library only works with real-time bars and will not work with historical bars.
Lex_3CR_Functions_Library2Library "Lex_3CR_Functions_Library2"
This is a source code for a technical analysis library in Pine Script language,
designed to identify and mark Bullish and Bearish Three Candle Reversal (3CR) chart patterns.
The library provides three functions to be used in a trading algorithm.
The first function, Bull_3crMarker, adds a dashed line and label to a Bullish 3CR chart pattern, indicating the 3CR point.
The second function, Bear_3crMarker, adds a dashed line and label to a Bearish 3CR chart pattern.
The third function, Bull_3CRlogicals, checks for a Bullish 3CR pattern where the first candle's low is greater than the second candle's low and the second candle's low is less than the third candle's low.
If found, creates a line at the breakout point and a label at the fail point,
if specified. All functions take parameters such as the chart pattern's characteristics and output colors, labels, and markers.
Bull_3crMarker(bulllinearray, barnum, breakpoint, failpointB, failpoint, linecolorbull, bulllabelarray, labelcolor, textcolor, labelon)
Bull_3crMarker Adds a 3CR marker to a Bullish 3CR chart pattern
@description Adds a dashed line and label to a 3CR up chart pattern, indicating the 3CR (3 Candle Reversal) point.
Parameters:
bulllinearray (line )
barnum (int)
breakpoint (float)
failpointB (float )
failpoint (float)
linecolorbull (color)
bulllabelarray (label )
labelcolor (color)
textcolor (color)
labelon (bool)
Bear_3crMarker(bearlinearray, barnum, breakpoint, failpointB, failpoint, linecolorbear, bearlabelarray, labelcolor, textcolor, labelon)
Bear_3crMarker Adds a 3CR marker to a Bearish 3CR chart pattern
@description Adds a dashed line and label to a 3CR down chart pattern, indicating the 3CR (3 Candle Reversal) point.
Parameters:
bearlinearray (line )
barnum (int)
breakpoint (float)
failpointB (float )
failpoint (float)
linecolorbear (color)
bearlabelarray (label )
labelcolor (color)
textcolor (color)
labelon (bool)
Bull_3CRlogicals(low1, low2, low3, bulllinearray, bulllabelarray, failpointB, linecolorbull, labelcolor, textcolor, labelon)
Checks for a bullish three candle reversal pattern and creates a line and label at the breakout point if found
@description Checks for a bullish three candle reversal pattern where the first candle's low is greater than the second candle's low and the second candle's low is less than the third candle's low. If found, creates a line at the breakout point and a label at the fail point, if specified.
Parameters:
low1 (float)
low2 (float)
low3 (float)
bulllinearray (line )
bulllabelarray (label )
failpointB (float )
linecolorbull (color)
labelcolor (color)
textcolor (color)
labelon (bool)
Bear_3CRlogicals(high1, high2, high3, bearlinearray, bearlabelarray, failpointB, linecolorbear, labelcolor, textcolor, labelon)
Checks for a Bearish 3CR pattern and draws a bearish marker on the chart at the appropriate location
@description This function checks for a Bearish 3CR (Three-Candle Reversal) pattern, which is defined as the second candle having a higher high than the first and third candles, and the third candle having a lower high than the first candle. If the pattern is detected, a bearish marker is drawn on the chart at the appropriate location, and an optional label can be added to the marker.
Parameters:
high1 (float)
high2 (float)
high3 (float)
bearlinearray (line )
bearlabelarray (label )
failpointB (float )
linecolorbear (color)
labelcolor (color)
textcolor (color)
labelon (bool)
bullLineDelete(i, bulllinearray, failarray, bulllabelarray, labelon)
Removes a bullish line from a specified position in a line array, and optionally removes a label associated with that line
@description Removes a bullish line from a specified position in a line array, and optionally removes a label associated with that line.
Parameters:
i (int)
bulllinearray (line )
failarray (float )
bulllabelarray (label )
labelon (bool)
bearLineDelete(i, bearlinearray, failarray, bearlabelarray, labelon)
Removes a bearish line from a specified position in a line array, and optionally removes a label associated with that line
@description Removes a bearish line from a specified position in a line array, and optionally removes a label associated with that line.
Parameters:
i (int)
bearlinearray (line )
failarray (float )
bearlabelarray (label )
labelon (bool)
bulloffsetdelete(i, bulllinearray, failarray, bulllabelarray, labelon)
Removes a bullish line from a specified position in a line array, and optionally removes a label associated with that line
@description Removes a bullish line from a specified position in a line array, and optionally removes a label associated with that line.
Parameters:
i (int)
bulllinearray (line )
failarray (float )
bulllabelarray (label )
labelon (bool)
bearoffsetdelete(i, bearlinearray, failarray, bearlabelarray, labelon)
Removes a bearish line from a specified position in a line array, and optionally removes a label associated with that line
@description Removes a bearish line from a specified position in a line array, and optionally removes a label associated with that line.
Parameters:
i (int)
bearlinearray (line )
failarray (float )
bearlabelarray (label )
labelon (bool)
BullEntry_setter(i, bulllinearray, failpointB, entrystopB, entryB, entryboolB)
Checks if the specified value is greater than the break point of any bullish line in an array, and removes that line if true
@description Checks if the s pecified value is greater than the break point of any bullish line in an array, and removes that line if true.
Parameters:
i (int)
bulllinearray (line )
failpointB (float )
entrystopB (float )
entryB (float )
entryboolB (bool )
Bull3CRchecker(close1, bulllinearray, FailpointB, rsiB, bulllabelarray, labelt, bullcolored, directionarray, rsi, secondbullline, entrystopB, entryB, entryboolB)
Parameters:
close1 (float)
bulllinearray (line )
FailpointB (float )
rsiB (float )
bulllabelarray (label )
labelt (bool)
bullcolored (color)
directionarray (label )
rsi (float)
secondbullline (line )
entrystopB (float )
entryB (float )
entryboolB (bool )
Bear3CRchecker(close1, bearlinearray, FailpointB, bearlabelarray, labelt, bearcolored, directionarray, rsi, secondbearline, rsiB)
Checks if the specified value is less than the break point of any bearish line in an array, and removes that line if true
@description Checks if the specified value is less than the break point of any bearish line in an array, and removes that line if true.
Parameters:
close1 (float)
bearlinearray (line )
FailpointB (float )
bearlabelarray (label )
labelt (bool)
bearcolored (color)
directionarray (label )
rsi (float)
secondbearline (line )
rsiB (float )
Bulloffsetcheck(FailpointB, bulllabelarray, linearray, labelt, offset)
Checks the offset of bullish lines and deletes them if they are beyond a certain offset from the current bar index
@description Checks the offset of bullish lines and deletes them if they are beyond a certain offset from the current bar index
Parameters:
FailpointB (float )
bulllabelarray (label )
linearray (line )
labelt (bool)
offset (int)
Bearoffsetcheck(FailpointB, bearlabelarray, linearray, labelt, offset)
Checks the offset of bearish lines and deletes them if they are beyond a certain offset from the current bar index
@description Checks the offset of bearish lines and deletes them if they are beyond a certain offset from the current bar index
Parameters:
FailpointB (float )
bearlabelarray (label )
linearray (line )
labelt (bool)
offset (int)
Bullfailchecker(close1, FailpointB, bulllabelarray, linearray, labelt)
Checks if the current price has crossed above a bullish fail point and deletes the corresponding line and label
@description Checks if the current price has crossed above a bullish fail point and deletes the corresponding line and label
Parameters:
close1 (float)
FailpointB (float )
bulllabelarray (label )
linearray (line )
labelt (bool)
Bearfailchecker(close1, FailpointB, bearlabelarray, linearray, labelt)
Checks for bearish lines that have failed to trigger and removes them from the chart
@description This function checks for bearish lines that have failed to trigger (i.e., where the current price is above the fail point) and removes them from the chart along with any associated label.
Parameters:
close1 (float)
FailpointB (float )
bearlabelarray (label )
linearray (line )
labelt (bool)
rsibullchecker(rsiinput, rsiBull, secondbullline)
Checks for bullish RSI lines that have failed to trigger and removes them from the chart
@description This function checks for bullish RSI lines that have failed to trigger (i.e., where the current RSI value is below the line's trigger level) and removes them from the chart along with any associated line.
Parameters:
rsiinput (float)
rsiBull (float )
secondbullline (line )
rsibearchecker(rsiinput, rsiBear, secondbearline)
Checks for bearish RSI lines that have failed to trigger and removes them from the chart
@description This function checks for bearish RSI lines that have failed to trigger (i.e., where the current RSI value is above the line's trigger level) and removes them from the chart along with any associated line.
Parameters:
rsiinput (float)
rsiBear (float )
secondbearline (line )
MarkovChainLibrary "MarkovChain"
Generic Markov Chain type functions.
---
A Markov chain or Markov process is a stochastic model describing a sequence of possible events in which the
probability of each event depends only on the state attained in the previous event.
---
reference:
Understanding Markov Chains, Examples and Applications. Second Edition. Book by Nicolas Privault.
en.wikipedia.org
www.geeksforgeeks.org
towardsdatascience.com
github.com
stats.stackexchange.com
timeseriesreasoning.com
www.ris-ai.com
github.com
gist.github.com
github.com
gist.github.com
writings.stephenwolfram.com
kevingal.com
towardsdatascience.com
spedygiorgio.github.io
github.com
www.projectrhea.org
method to_string(this)
Translate a Markov Chain object to a string format.
Namespace types: MC
Parameters:
this (MC) : `MC` . Markov Chain object.
Returns: string
method to_table(this, position, text_color, text_size)
Namespace types: MC
Parameters:
this (MC)
position (string)
text_color (color)
text_size (string)
method create_transition_matrix(this)
Namespace types: MC
Parameters:
this (MC)
method generate_transition_matrix(this)
Namespace types: MC
Parameters:
this (MC)
new_chain(states, name)
Parameters:
states (state )
name (string)
from_data(data, name)
Parameters:
data (string )
name (string)
method probability_at_step(this, target_step)
Namespace types: MC
Parameters:
this (MC)
target_step (int)
method state_at_step(this, start_state, target_state, target_step)
Namespace types: MC
Parameters:
this (MC)
start_state (int)
target_state (int)
target_step (int)
method forward(this, obs)
Namespace types: HMC
Parameters:
this (HMC)
obs (int )
method backward(this, obs)
Namespace types: HMC
Parameters:
this (HMC)
obs (int )
method viterbi(this, observations)
Namespace types: HMC
Parameters:
this (HMC)
observations (int )
method baumwelch(this, observations)
Namespace types: HMC
Parameters:
this (HMC)
observations (int )
Node
Target node.
Fields:
index (series int) : . Key index of the node.
probability (series float) : . Probability rate of activation.
state
State reference.
Fields:
name (series string) : . Name of the state.
index (series int) : . Key index of the state.
target_nodes (Node ) : . List of index references and probabilities to target states.
MC
Markov Chain reference object.
Fields:
name (series string) : . Name of the chain.
states (state ) : . List of state nodes and its name, index, targets and transition probabilities.
size (series int) : . Number of unique states
transitions (matrix) : . Transition matrix
HMC
Hidden Markov Chain reference object.
Fields:
name (series string) : . Name of thehidden chain.
states_hidden (state ) : . List of state nodes and its name, index, targets and transition probabilities.
states_obs (state ) : . List of state nodes and its name, index, targets and transition probabilities.
transitions (matrix) : . Transition matrix
emissions (matrix) : . Emission matrix
initial_distribution (float )
FunctionProbabilityViterbiLibrary "FunctionProbabilityViterbi"
The Viterbi Algorithm calculates the most likely sequence of hidden states *(called Viterbi path)*
that results in a sequence of observed events.
viterbi(observations, transitions, emissions, initial_distribution)
Calculate most probable path in a Markov model.
Parameters:
observations (int ) : array . Observation states data.
transitions (matrix) : matrix . Transition probability table, (HxH, H:Hidden states).
emissions (matrix) : matrix . Emission probability table, (OxH, O:Observed states).
initial_distribution (float ) : array . Initial probability distribution for the hidden states.
Returns: array. Most probable path.
FunctionBaumWelchLibrary "FunctionBaumWelch"
Baum-Welch Algorithm, also known as Forward-Backward Algorithm, uses the well known EM algorithm
to find the maximum likelihood estimate of the parameters of a hidden Markov model given a set of observed
feature vectors.
---
### Function List:
> `forward (array pi, matrix a, matrix b, array obs)`
> `forward (array pi, matrix a, matrix b, array obs, bool scaling)`
> `backward (matrix a, matrix b, array obs)`
> `backward (matrix a, matrix b, array obs, array c)`
> `baumwelch (array observations, int nstates)`
> `baumwelch (array observations, array pi, matrix a, matrix b)`
---
### Reference:
> en.wikipedia.org
> github.com
> en.wikipedia.org
> www.rdocumentation.org
> www.rdocumentation.org
forward(pi, a, b, obs)
Computes forward probabilities for state `X` up to observation at time `k`, is defined as the
probability of observing sequence of observations `e_1 ... e_k` and that the state at time `k` is `X`.
Parameters:
pi (float ) : Initial probabilities.
a (matrix) : Transmissions, hidden transition matrix a or alpha = transition probability matrix of changing
states given a state matrix is size (M x M) where M is number of states.
b (matrix) : Emissions, matrix of observation probabilities b or beta = observation probabilities. Given
state matrix is size (M x O) where M is number of states and O is number of different
possible observations.
obs (int ) : List with actual state observation data.
Returns: - `matrix _alpha`: Forward probabilities. The probabilities are given on a logarithmic scale (natural logarithm). The first
dimension refers to the state and the second dimension to time.
forward(pi, a, b, obs, scaling)
Computes forward probabilities for state `X` up to observation at time `k`, is defined as the
probability of observing sequence of observations `e_1 ... e_k` and that the state at time `k` is `X`.
Parameters:
pi (float ) : Initial probabilities.
a (matrix) : Transmissions, hidden transition matrix a or alpha = transition probability matrix of changing
states given a state matrix is size (M x M) where M is number of states.
b (matrix) : Emissions, matrix of observation probabilities b or beta = observation probabilities. Given
state matrix is size (M x O) where M is number of states and O is number of different
possible observations.
obs (int ) : List with actual state observation data.
scaling (bool) : Normalize `alpha` scale.
Returns: - #### Tuple with:
> - `matrix _alpha`: Forward probabilities. The probabilities are given on a logarithmic scale (natural logarithm). The first
dimension refers to the state and the second dimension to time.
> - `array _c`: Array with normalization scale.
backward(a, b, obs)
Computes backward probabilities for state `X` and observation at time `k`, is defined as the probability of observing the sequence of observations `e_k+1, ... , e_n` under the condition that the state at time `k` is `X`.
Parameters:
a (matrix) : Transmissions, hidden transition matrix a or alpha = transition probability matrix of changing states
given a state matrix is size (M x M) where M is number of states
b (matrix) : Emissions, matrix of observation probabilities b or beta = observation probabilities. given state
matrix is size (M x O) where M is number of states and O is number of different possible observations
obs (int ) : Array with actual state observation data.
Returns: - `matrix _beta`: Backward probabilities. The probabilities are given on a logarithmic scale (natural logarithm). The first dimension refers to the state and the second dimension to time.
backward(a, b, obs, c)
Computes backward probabilities for state `X` and observation at time `k`, is defined as the probability of observing the sequence of observations `e_k+1, ... , e_n` under the condition that the state at time `k` is `X`.
Parameters:
a (matrix) : Transmissions, hidden transition matrix a or alpha = transition probability matrix of changing states
given a state matrix is size (M x M) where M is number of states
b (matrix) : Emissions, matrix of observation probabilities b or beta = observation probabilities. given state
matrix is size (M x O) where M is number of states and O is number of different possible observations
obs (int ) : Array with actual state observation data.
c (float ) : Array with Normalization scaling coefficients.
Returns: - `matrix _beta`: Backward probabilities. The probabilities are given on a logarithmic scale (natural logarithm). The first dimension refers to the state and the second dimension to time.
baumwelch(observations, nstates)
**(Random Initialization)** Baum–Welch algorithm is a special case of the expectation–maximization algorithm used to find the
unknown parameters of a hidden Markov model (HMM). It makes use of the forward-backward algorithm
to compute the statistics for the expectation step.
Parameters:
observations (int ) : List of observed states.
nstates (int)
Returns: - #### Tuple with:
> - `array _pi`: Initial probability distribution.
> - `matrix _a`: Transition probability matrix.
> - `matrix _b`: Emission probability matrix.
---
requires: `import RicardoSantos/WIPTensor/2 as Tensor`
baumwelch(observations, pi, a, b)
Baum–Welch algorithm is a special case of the expectation–maximization algorithm used to find the
unknown parameters of a hidden Markov model (HMM). It makes use of the forward-backward algorithm
to compute the statistics for the expectation step.
Parameters:
observations (int ) : List of observed states.
pi (float ) : Initial probaility distribution.
a (matrix) : Transmissions, hidden transition matrix a or alpha = transition probability matrix of changing states
given a state matrix is size (M x M) where M is number of states
b (matrix) : Emissions, matrix of observation probabilities b or beta = observation probabilities. given state
matrix is size (M x O) where M is number of states and O is number of different possible observations
Returns: - #### Tuple with:
> - `array _pi`: Initial probability distribution.
> - `matrix _a`: Transition probability matrix.
> - `matrix _b`: Emission probability matrix.
---
requires: `import RicardoSantos/WIPTensor/2 as Tensor`
MyLibraryLibrary "MyLibrary"
TODO: add library description here
fun(x)
TODO: add function description here
Parameters:
x (float) : TODO: add parameter x description here
Returns: TODO: add what function returns
TrendIndicatorsLibrary "TrendIndicators"
This is a library of 'Trend Indicators'.
It aims to facilitate the grouping of this category of indicators, and also offer the customized supply of
the source, not being restricted to just the closing price.
Indicators (this is a work in progress):
1. Absolute DI (Directional Moviment Index) (Difference between DI+ and DI-).
Used in 'DMI Stochastic Extreme' by Barbara Star.
2. DMI
DI_Abs(lengthDI, smoothDI, typeMA, lengthMA)
@description Absolute DI (Directional Moviment Index).
Used in 'DMI Stochastic Extreme' by Barbara Star.
Difference between DI+ and DI-
Parameters:
lengthDI : (int) Length of DI+/DI-
smoothDI : (bool) Sets whether absolute DI should be smoothed
typeMA : (int) Type of moving average of smoothing
lengthMA : (int) Length for moving average of smoothing
Returns: (float) Absolute value of DI
dmi(diLength, adxSmoothing)
@description DMI (Directional Movement Index)
Same as ta.dmi()
Parameters:
diLength : (int) Length of DI+/DI-
adxSmoothing : (int) ADX Smoothing
Returns: Tuple of three DMI series: Positive Directional
Movement (+DI), Negative Directional Movement (-DI) and Average Directional Movement Index (ADX).
dmi(source, diLength, adxSmoothing)
@description DMI (Directional Movement Index)
Customized version of ta.dmi(), with custom source
Parameters:
source : (float) Source for DI+/DI-
diLength : (int) Length of DI+/DI-
adxSmoothing : (int) ADX Smoothing
Returns: Tuple of three DMI series: Positive Directional
Movement (+DI), Negative Directional Movement (-DI) and Average Directional Movement Index (ADX).
Scaled Order Sizing and Take Profit Target ArraysWOAH Order Scaling!
This Provides a user with methods to create a list of profit targets and order sizes which grow or shrink. For size, the will add up to specific sum. for Targets they will include the first and last, and can lean towards either, to scale the order grid.
And thanks to @Hoanghetti for the markdown, i've included a basic usage example within the hover , o you don't need to search for the usage example, simply import, and when writing, the code hint contains a full example.
scaled_sizes(total_size, count, weight, min_size, as_percent)
create an array of sizes which grow or shrink from first to last
which add up to 1.0 if set the as_percent flag , or a total value / sum.
Parameters:
total_size : (float) total size to divide ito split
count : (int ) desired number of splits to create
weight : (float) a weight to apply to grow or shrink the split either towards the last being most, or the first being most, or 1.0 being each is equally sized as 1/n count
min_size : (float) a minimum size for the smallest value (in value of ttotal_size units)
as_percent : (float) a minimum size for the smallest value (in value of total_size units)
Returns: Array of Sizes for each split
scaled_targets(count, weight, minimum, maximum)
create a list of take profitt targets from the smallest to larget distance
Parameters:
count : (int ) number of targets
weight : (float) weight to apply to growing or shrinking
minimum : (float) first value of the output
maximum : (float) last value of the output
Returns: Array of percentage targets
