lib_retracement_labelLibrary "lib_retracement_label"
creates a retracement label between the origin and target of a retracement, updating it's position (via update + draw) when the target moves.
create_tooltip(name, min, max, tol_min, tol_max)
Parameters:
name (string)
min (float)
max (float)
tol_min (float)
tol_max (float)
method update(this)
Namespace types: RetracementLabel
Parameters:
this (RetracementLabel)
method create_retracement_label(this, move_endpoint, args, tooltip)
Creates a new RetracementLabel object.
Namespace types: D.Line
Parameters:
this (Line type from robbatt/lib_plot_objects/23)
move_endpoint (Point type from robbatt/lib_plot_objects/23)
args (LabelArgs type from robbatt/lib_plot_objects/23)
tooltip (string)
method create_retracement_label(this, move_end, args, tooltip)
Creates a new RetracementLabel object.
Namespace types: D.Line
Parameters:
this (Line type from robbatt/lib_plot_objects/23)
move_end (Pivot type from robbatt/lib_pivot/43)
args (LabelArgs type from robbatt/lib_plot_objects/23)
tooltip (string)
method enqueue(id, item, max)
Namespace types: RetracementLabel
Parameters:
id (RetracementLabel )
item (RetracementLabel)
max (int)
method draw(this)
Namespace types: RetracementLabel
Parameters:
this (RetracementLabel)
method draw(this)
Namespace types: RetracementLabel
Parameters:
this (RetracementLabel )
method delete(this)
Namespace types: RetracementLabel
Parameters:
this (RetracementLabel)
method delete(this)
Namespace types: RetracementLabel
Parameters:
this (RetracementLabel )
RetracementLabel
Fields:
move_endpoint (|robbatt/lib_plot_objects/23;Point|#OBJ)
center_label (|robbatt/lib_plot_objects/23;CenterLabel|#OBJ)
Indicadores y estrategias
SimilarityMeasuresLibrary "SimilarityMeasures"
Similarity measures are statistical methods used to quantify the distance between different data sets
or strings. There are various types of similarity measures, including those that compare:
- data points (SSD, Euclidean, Manhattan, Minkowski, Chebyshev, Correlation, Cosine, Camberra, MAE, MSE, Lorentzian, Intersection, Penrose Shape, Meehl),
- strings (Edit(Levenshtein), Lee, Hamming, Jaro),
- probability distributions (Mahalanobis, Fidelity, Bhattacharyya, Hellinger),
- sets (Kumar Hassebrook, Jaccard, Sorensen, Chi Square).
---
These measures are used in various fields such as data analysis, machine learning, and pattern recognition. They
help to compare and analyze similarities and differences between different data sets or strings, which
can be useful for making predictions, classifications, and decisions.
---
References:
en.wikipedia.org
cran.r-project.org
numerics.mathdotnet.com
github.com
github.com
github.com
Encyclopedia of Distances, doi.org
ssd(p, q)
Sum of squared difference for N dimensions.
Parameters:
p (float ) : `array` Vector with first numeric distribution.
q (float ) : `array` Vector with second numeric distribution.
Returns: Measure of distance that calculates the squared euclidean distance.
euclidean(p, q)
Euclidean distance for N dimensions.
Parameters:
p (float ) : `array` Vector with first numeric distribution.
q (float ) : `array` Vector with second numeric distribution.
Returns: Measure of distance that calculates the straight-line (or Euclidean).
manhattan(p, q)
Manhattan distance for N dimensions.
Parameters:
p (float ) : `array` Vector with first numeric distribution.
q (float ) : `array` Vector with second numeric distribution.
Returns: Measure of absolute differences between both points.
minkowski(p, q, p_value)
Minkowsky Distance for N dimensions.
Parameters:
p (float ) : `array` Vector with first numeric distribution.
q (float ) : `array` Vector with second numeric distribution.
p_value (float) : `float` P value, default=1.0(1: manhatan, 2: euclidean), does not support chebychev.
Returns: Measure of similarity in the normed vector space.
chebyshev(p, q)
Chebyshev distance for N dimensions.
Parameters:
p (float ) : `array` Vector with first numeric distribution.
q (float ) : `array` Vector with second numeric distribution.
Returns: Measure of maximum absolute difference.
correlation(p, q)
Correlation distance for N dimensions.
Parameters:
p (float ) : `array` Vector with first numeric distribution.
q (float ) : `array` Vector with second numeric distribution.
Returns: Measure of maximum absolute difference.
cosine(p, q)
Cosine distance between provided vectors.
Parameters:
p (float ) : `array` 1D Vector.
q (float ) : `array` 1D Vector.
Returns: The Cosine distance between vectors `p` and `q`.
---
angiogenesis.dkfz.de
camberra(p, q)
Camberra distance for N dimensions.
Parameters:
p (float ) : `array` Vector with first numeric distribution.
q (float ) : `array` Vector with second numeric distribution.
Returns: Weighted measure of absolute differences between both points.
mae(p, q)
Mean absolute error is a normalized version of the sum of absolute difference (manhattan).
Parameters:
p (float ) : `array` Vector with first numeric distribution.
q (float ) : `array` Vector with second numeric distribution.
Returns: Mean absolute error of vectors `p` and `q`.
mse(p, q)
Mean squared error is a normalized version of the sum of squared difference.
Parameters:
p (float ) : `array` Vector with first numeric distribution.
q (float ) : `array` Vector with second numeric distribution.
Returns: Mean squared error of vectors `p` and `q`.
lorentzian(p, q)
Lorentzian distance between provided vectors.
Parameters:
p (float ) : `array` Vector with first numeric distribution.
q (float ) : `array` Vector with second numeric distribution.
Returns: Lorentzian distance of vectors `p` and `q`.
---
angiogenesis.dkfz.de
intersection(p, q)
Intersection distance between provided vectors.
Parameters:
p (float ) : `array` Vector with first numeric distribution.
q (float ) : `array` Vector with second numeric distribution.
Returns: Intersection distance of vectors `p` and `q`.
---
angiogenesis.dkfz.de
penrose(p, q)
Penrose Shape distance between provided vectors.
Parameters:
p (float ) : `array` Vector with first numeric distribution.
q (float ) : `array` Vector with second numeric distribution.
Returns: Penrose shape distance of vectors `p` and `q`.
---
angiogenesis.dkfz.de
meehl(p, q)
Meehl distance between provided vectors.
Parameters:
p (float ) : `array` Vector with first numeric distribution.
q (float ) : `array` Vector with second numeric distribution.
Returns: Meehl distance of vectors `p` and `q`.
---
angiogenesis.dkfz.de
edit(x, y)
Edit (aka Levenshtein) distance for indexed strings.
Parameters:
x (int ) : `array` Indexed array.
y (int ) : `array` Indexed array.
Returns: Number of deletions, insertions, or substitutions required to transform source string into target string.
---
generated description:
The Edit distance is a measure of similarity used to compare two strings. It is defined as the minimum number of
operations (insertions, deletions, or substitutions) required to transform one string into another. The operations
are performed on the characters of the strings, and the cost of each operation depends on the specific algorithm
used.
The Edit distance is widely used in various applications such as spell checking, text similarity, and machine
translation. It can also be used for other purposes like finding the closest match between two strings or
identifying the common prefixes or suffixes between them.
---
github.com
www.red-gate.com
planetcalc.com
lee(x, y, dsize)
Distance between two indexed strings of equal length.
Parameters:
x (int ) : `array` Indexed array.
y (int ) : `array` Indexed array.
dsize (int) : `int` Dictionary size.
Returns: Distance between two strings by accounting for dictionary size.
---
www.johndcook.com
hamming(x, y)
Distance between two indexed strings of equal length.
Parameters:
x (int ) : `array` Indexed array.
y (int ) : `array` Indexed array.
Returns: Length of different components on both sequences.
---
en.wikipedia.org
jaro(x, y)
Distance between two indexed strings.
Parameters:
x (int ) : `array` Indexed array.
y (int ) : `array` Indexed array.
Returns: Measure of two strings' similarity: the higher the value, the more similar the strings are.
The score is normalized such that `0` equates to no similarities and `1` is an exact match.
---
rosettacode.org
mahalanobis(p, q, VI)
Mahalanobis distance between two vectors with population inverse covariance matrix.
Parameters:
p (float ) : `array` 1D Vector.
q (float ) : `array` 1D Vector.
VI (matrix) : `matrix` Inverse of the covariance matrix.
Returns: The mahalanobis distance between vectors `p` and `q`.
---
people.revoledu.com
stat.ethz.ch
docs.scipy.org
fidelity(p, q)
Fidelity distance between provided vectors.
Parameters:
p (float ) : `array` 1D Vector.
q (float ) : `array` 1D Vector.
Returns: The Bhattacharyya Coefficient between vectors `p` and `q`.
---
en.wikipedia.org
bhattacharyya(p, q)
Bhattacharyya distance between provided vectors.
Parameters:
p (float ) : `array` 1D Vector.
q (float ) : `array` 1D Vector.
Returns: The Bhattacharyya distance between vectors `p` and `q`.
---
en.wikipedia.org
hellinger(p, q)
Hellinger distance between provided vectors.
Parameters:
p (float ) : `array` 1D Vector.
q (float ) : `array` 1D Vector.
Returns: The hellinger distance between vectors `p` and `q`.
---
en.wikipedia.org
jamesmccaffrey.wordpress.com
kumar_hassebrook(p, q)
Kumar Hassebrook distance between provided vectors.
Parameters:
p (float ) : `array` 1D Vector.
q (float ) : `array` 1D Vector.
Returns: The Kumar Hassebrook distance between vectors `p` and `q`.
---
github.com
jaccard(p, q)
Jaccard distance between provided vectors.
Parameters:
p (float ) : `array` 1D Vector.
q (float ) : `array` 1D Vector.
Returns: The Jaccard distance between vectors `p` and `q`.
---
github.com
sorensen(p, q)
Sorensen distance between provided vectors.
Parameters:
p (float ) : `array` 1D Vector.
q (float ) : `array` 1D Vector.
Returns: The Sorensen distance between vectors `p` and `q`.
---
people.revoledu.com
chi_square(p, q, eps)
Chi Square distance between provided vectors.
Parameters:
p (float ) : `array` 1D Vector.
q (float ) : `array` 1D Vector.
eps (float)
Returns: The Chi Square distance between vectors `p` and `q`.
---
uw.pressbooks.pub
stats.stackexchange.com
www.itl.nist.gov
kulczynsky(p, q, eps)
Kulczynsky distance between provided vectors.
Parameters:
p (float ) : `array` 1D Vector.
q (float ) : `array` 1D Vector.
eps (float)
Returns: The Kulczynsky distance between vectors `p` and `q`.
---
github.com
FunctionMatrixCovarianceLibrary "FunctionMatrixCovariance"
In probability theory and statistics, a covariance matrix (also known as auto-covariance matrix, dispersion matrix, variance matrix, or variance–covariance matrix) is a square matrix giving the covariance between each pair of elements of a given random vector.
Intuitively, the covariance matrix generalizes the notion of variance to multiple dimensions. As an example, the variation in a collection of random points in two-dimensional space cannot be characterized fully by a single number, nor would the variances in the `x` and `y` directions contain all of the necessary information; a `2 × 2` matrix would be necessary to fully characterize the two-dimensional variation.
Any covariance matrix is symmetric and positive semi-definite and its main diagonal contains variances (i.e., the covariance of each element with itself).
The covariance matrix of a random vector `X` is typically denoted by `Kxx`, `Σ` or `S`.
~wikipedia.
method cov(M, bias)
Estimate Covariance matrix with provided data.
Namespace types: matrix
Parameters:
M (matrix) : `matrix` Matrix with vectors in column order.
bias (bool)
Returns: Covariance matrix of provided vectors.
---
en.wikipedia.org
numpy.org
PScolorLibrary "PScolor"
TODO: add library description here
////variable/////////////////////////////
//COLOR brightness
Each color has 0–9 / A1–A4
(5th standard: Bright if small, dark if big)
(Fluorescence based on A2)
//Color Name
1 = RED
2 = DEEP_ORANGE
3 = ORANGE
4 = AMBER
5 = YELLOW
6 = LIME
7 = LIGHT_GREEN
8 = GREEN
9 = TEAL
10= CYAN
11= LIGHT_BLUE
12= BLUE
13= INDIGO
14= DEEP_PURPLE
15= PURPLE
16= PINK
0= GRAY
// Transparency
///////////////////////////////////////
lvcol(colormode, Number, trans)
Parameters:
colormode (int)
Number (simple int)
trans (float)
lvcolA(colormode, Number, trans)
Parameters:
colormode (int)
Number (simple int)
trans (float)
lvcol2(colormode, colorName, trans)
Parameters:
colormode (int)
colorName (simple string)
trans (float)
lvcol2A(colormode, colorName, trans)
Parameters:
colormode (int)
colorName (simple string)
trans (float)
TradeTrackerv2Library "TradeTrackerv2"
This library can be used to track (hypothetical) trades on the chart. Enter the Open, SL, and TP prices (or TP in R to have it calculated) and then call Trade.TrackTrade(barIndex). Keep track of your trades in an array and then simply call TradeTracker.UpdateAllTrades(close) to update all trades based on the current close price.
How to use:
1. Import the library, as always. I'm assuming the alias of "Tracker" below.
2. The Type Trade is exported, so generate a Trade object like newTrade = Tracker.Trade.new() .
3. Set the values for Open, SL, and TP. TP can be set either by price or by R, which will calculate the R based on the Open->SL range:
newTrade.priceOpen = 1.0
newTrade.priceSl = 0.5
newTrade.priceTp = 2.0
-- or in place of the third line above --
newTrade.rTp = 2
4. On each interval you want to update (whether that's per tick/close or on each bar), call trades.UpdateAllTrades(close) . This snippet assumes you have an array named trades (var trades = array.new()) .
In future updates, more customization options will be created. This is the initial prototype.
method MakeTradeLines(t, barIdx)
Namespace types: Trade
Parameters:
t (Trade)
barIdx (int)
method UpdateLabel(t)
Namespace types: Trade
Parameters:
t (Trade)
method MakeLabel(t, barIdx)
Namespace types: Trade
Parameters:
t (Trade)
barIdx (int)
method CloseTrade(t)
Namespace types: Trade
Parameters:
t (Trade)
method OpenTrade(t)
Namespace types: Trade
Parameters:
t (Trade)
method OpenCloseTrade(t, _close)
Namespace types: Trade
Parameters:
t (Trade)
_close (float)
method CalculateProfits(t, _close)
Calculates profits/losses for the Trade, given _close price
Namespace types: Trade
Parameters:
t (Trade)
_close (float)
method UpdateTrade(t, _close)
Namespace types: Trade
Parameters:
t (Trade)
_close (float)
method SetInitialValues(t, barIdx)
Namespace types: Trade
Parameters:
t (Trade)
barIdx (int)
method UpdateAllTrades(trades, _close)
Namespace types: Trade
Parameters:
trades (Trade )
_close (float)
method TrackTrade(t, barIdx)
Namespace types: Trade
Parameters:
t (Trade)
barIdx (int)
Trade
Fields:
id (series__integer)
isOpen (series__bool)
isClosed (series__bool)
isBuy (series__bool)
priceOpen (series__float)
priceTp (series__float)
priceSl (series__float)
rTP (series__float)
profit (series__float)
r (series__float)
resultR (series__float)
lineOpen (series__line)
lineTp (series__line)
lineSl (series__line)
labelStats (series__label)
utilsLibrary "utils"
TODO: add library description here
maCustomseries(source, typeMa, length)
Parameters:
source (float)
typeMa (simple string)
length (simple int)
barCrossoverCounter(signalPrice, basePrice)
Parameters:
signalPrice (float)
basePrice (float)
barCrossunderCounter(signalPrice, basePrice)
Parameters:
signalPrice (float)
basePrice (float)
WHAlertCommandLibrary "WHAlertCommand"
f_WH_Risk(risk_Type_)
Parameters:
risk_Type_ (string)
f_WH_Open_Position(uuid_, enable_Buy_, enable_Sell, enable_All_Group_Members_, enable_Close_Opposite_Side_, enable_Risk_, risk_Type_, signal_Type_Buy_Or_Sell)
Parameters:
uuid_ (string)
enable_Buy_ (bool)
enable_Sell (bool)
enable_All_Group_Members_ (bool)
enable_Close_Opposite_Side_ (bool)
enable_Risk_ (bool)
risk_Type_ (string)
signal_Type_Buy_Or_Sell (string)
f_WH_TP(uuid_, position_Size_Percent_, side_)
Parameters:
uuid_ (string)
position_Size_Percent_ (float)
side_ (string)
f_WH_MARKET_CLOSE(uuid_, side_)
Parameters:
uuid_ (string)
side_ (string)
RiskToolsLibrary "RiskTools"
Provides functions for calculating risk metrics
pctDrop(start, result)
Calculates what is the percentage drop from a reference price
Parameters:
start (float) : Starting price before the drop occurred
result (float) : Resulting price to which the percentage drop occurred
Returns: Percentage drop from "start" to "result"
priceBeforeDrop(pctDrop, result)
Calculates a starting price given a resulting price and a percentage drop to that price
Parameters:
pctDrop (float) : Percentage drop
result (float) : Resulting price to which the percentage drop occurred
Returns: The starting price from which a percentage drop "pctDrop" gave a "result"
dropzone(price, masource, malength, window, zonesize)
Calculates drop zone as an integer representing some multiple of the "zoning size"
Parameters:
price (float) : The current price from which you want to calculate the drop zone
masource (float) : The source series used in the SMA calculation from which the floor price is determined
malength (simple int) : The length used in the SMA calculation from which the floor price is determined
window (simple int) : The lookback period from which to calculate the floor price
zonesize (simple int)
Returns: The zone identifier as a multiple of the zone size. A value of zero or less is translated to the first zone.
RSNPSDLibrary "RSNPSD"
EMA5(source, EMAlength, Smoothlength)
Parameters:
source (float)
EMAlength (simple int)
Smoothlength (simple int)
SLOPE(source, slopeDistance)
Parameters:
source (float)
slopeDistance (simple int)
print(txt)
Parameters:
txt (string)
libHTF[without request.security()]Library "libHTF"
libHTF: use HTF values without request.security()
This library enables to use HTF candles without request.security().
Basic data structure
Using to access values in the same manner as series variable.
The last member of HTF array is always latest current TF's data.
If new bar in HTF(same as last bar closes), new member is pushed to HTF array.
2nd from the last member of HTF array is latest fixed(closed) bar.
HTF: How to use
1. set TF
tf_higher() function selects higher TF. TF steps are ("1","5","15","60","240","D","W","M","3M","6M","Y").
example:
tfChart = timeframe.period
htf1 = tf_higher(tfChart)
2. set HTF matrix
htf_candle() function returns 1 bool and 1 matrix.
bool is a flag for start of new candle in HTF context.
matrix is HTF candle data(0:open,1:time_open,2:close,3:time_close,4:high,5:time:high,6:low,7:time_low).
example:
=htf_candle(htf1)
3. how to access HTF candle data
you can get values using .lastx() method.
please be careful, return value is always float evenif it is "time". you need to cast to int time value when using for xloc.bartime.
example:
htf1open=m1.lastx("open")
htf1close=m1.lastx("close")
//if you need to use histrical value.
lastopen=open
lasthtf1open=m1.lastx("open",1)
4. how to store Data of HTF context
you have to use array to store data of HTF context.
array.htf_push() method handles the last member of array. if new_bar in HTF, it push new member. otherwise it set value to the last member.
example:
array a_close=array.new(1,na)
a_close.htf_push(b_new_bar1,m1.lastx("close"))
HTFsrc: How to use
1. how to setup src.
set_src() function is set current tf's src from string(open/high/low/close/hl2/hlc3/ohlc4/hlcc4).
set_htfsrc() function returns src array of HTF candle.
example:
_src="ohlc4"
src=set_src(_src)
htf1src=set_htfsrc(_src,b_new_bar1,m1)
(if you need to use HTF src in series float)
s_htf1src=htf1src.lastx()
HighLow: How to use
1. set HTF arrays
highlow() and htfhighlow() function calculates high/low and return high/low prices and time.
the functions return 1 int and 8arrays.
int is a flag for new high(1) or new low(-1).
arrays are high/low and return high/low data. float for price, int for time.
example
=
highlow()
=
htfhighlow(m1)
2. how to access HighLow data
you can get values using .lastx() method.
example:
if i_renew==1
myhigh=a_high.lastx()
//if you need to use histrical value.
myhigh=a_high.lastx(1)
other functions
functions for HTF candle matrix or HTF src array in this script are
htf_sma()/htf_ema()/htf_rma()
htf_rsi()/htf_rci()/htf_dmi()
method lastx(arrayid, lastindex)
method like array.last. it returns lastindex from the last member, if parameter is set.
Namespace types: float
Parameters:
arrayid (float )
lastindex (int) : (int) default value is "0"(the last member). if you need to access historical value, increment it(same manner as series vars).
Returns: float value of lastindex from the last member of the array. returns na, if fail.
method lastx(arrayid, lastindex)
method like array.last. it returns lastindex from the last member, if parameter is set.
Namespace types: int
Parameters:
arrayid (int )
lastindex (int) : (int) default value is "0"(the last member). if you need to access historical value, increment it(same manner as series vars).
Returns: int value of lastindex from the last member of the array. returns na, if fail.
method lastx(m, _type, lastindex)
method for handling htf matrix.
Namespace types: matrix
Parameters:
m (matrix) : (matrix) matrix for htf candle.
_type (string) : (string) value type of htf candle:
lastindex (int) : (int) default value is "0"(the last member).
Returns: (float) value of htf candle. (caution: need to cast float to int to use time values!)
method set_last(arrayid, val)
method to set a value of the last member of the array. it sets value to the last member.
Namespace types: float
Parameters:
arrayid (float )
val (float) : (float) value to set.
Returns: nothing
method htf_push(arrayid, b, val)
method to push new member to htf context. if new bar in htf, it works as push. else it works as set_last.
Namespace types: float
Parameters:
arrayid (float )
b (bool) : (bool) true:push,false:set_last
val (float) : (float) _f the value to set.
Returns: nothing
method tf_higher(tf)
method to set higher tf from tf string. TF steps are .
Namespace types: series string, simple string, input string, const string
Parameters:
tf (string) : (string) tf string
Returns: (string) string of higher tf.
htf_candle(_tf, _TZ)
build htf candles
Parameters:
_tf (string) : (string) tf string.
_TZ (string) : of timezone. default value is "GMT+3".
Returns: bool for new bar@htf and matrix for snapshot of htf candle
set_src(_src_type)
set src.
Parameters:
_src_type (string) : (string) type of source:
Returns: (series float) src value
set_htfsrc(_src_type, _nb, _m)
set htf src.
Parameters:
_src_type (string) : (string) type of source:
_nb (bool) : (bool) flag of new bar
_m (matrix) : (matrix) matrix for htf candle.
Returns: (array) array of src value
is_up()
last_is_up()
peak_bottom(_latest, _last)
Parameters:
_latest (bool)
_last (bool)
htf_is_up(_m)
Parameters:
_m (matrix)
htf_last_is_up(_m)
Parameters:
_m (matrix)
highlow(_b_bartime_price)
Parameters:
_b_bartime_price (bool)
htfhighlow(_m, _b_bartime_price)
Parameters:
_m (matrix)
_b_bartime_price (bool)
htf_sma(_a_src, _len)
Parameters:
_a_src (float )
_len (int)
htf_rma(_a_src, _new_bar, _len)
Parameters:
_a_src (float )
_new_bar (bool)
_len (int)
htf_ema(_a_src, _new_bar, _len)
Parameters:
_a_src (float )
_new_bar (bool)
_len (int)
htf_rsi(_a_src, _new_bar, _len)
Parameters:
_a_src (float )
_new_bar (bool)
_len (int)
rci(_src, _len)
Parameters:
_src (float)
_len (int)
htf_rci(_a_src, _len)
Parameters:
_a_src (float )
_len (int)
htf_dmi(_m, _new_bar, _len, _ma_type)
Parameters:
_m (matrix)
_new_bar (bool)
_len (int)
_ma_type (string)
TradeLibrary "Trade"
A Trade Tracking Library
Monitor conditions with less code by using Arrays. When your conditions are met in chronologically, a signal is returned and the scanning starts again.
Create trades automatically with Stop Loss, Take Profit and Entry. The trades will automatically track based on the market movement and update when the targets are hit.
Sample Usage
Enter a buy trade when RSI crosses below 70 then crosses above 80 before it crosses 40.
Note: If RSI crosses 40 before 80, No trade will be entered.
rsi = ta.rsi(close, 21)
buyConditions = array.new_bool()
buyConditions.push(ta.crossunder(rsi, 70))
buyConditions.push(ta.crossover(rsi, 80))
buy = Trade.signal(buyConditions, ta.crossunder(rsi, 40))
trade = Trade.new(close-(100*syminfo.mintick), close +(200*syminfo.mintick), condition=buy)
plot(trade.takeprofit, "TP", style=plot.style_circles, linewidth=4, color=color.lime)
alertcondition(trade.tp_hit, "TP Hit")
method signal(conditions, reset)
Signal Conditions
Namespace types: bool
Parameters:
conditions (bool )
reset (bool)
Returns: Boolean: True when all the conditions have occured
method update(this, stoploss, takeprofit, entry)
Update Trade Parameters
Namespace types: Trade
Parameters:
this (Trade)
stoploss (float)
takeprofit (float)
entry (float)
Returns: nothing
method clear(this)
Clear Trade Parameters
Namespace types: Trade
Parameters:
this (Trade)
Returns: nothing
method track(this, _high, _low)
Track Trade Parameters
Namespace types: Trade
Parameters:
this (Trade)
_high (float)
_low (float)
Returns: nothing
new(stoploss, takeprofit, entry, _high, _low, condition, update)
New Trade with tracking
Parameters:
stoploss (float)
takeprofit (float)
entry (float)
_high (float)
_low (float)
condition (bool)
update (bool)
Returns: a Trade with targets and updates if stoploss or takeprofit is hit
new()
New Empty Trade
Returns: an empty trade
Trade
Fields:
stoploss (series__float)
takeprofit (series__float)
entry (series__float)
sl_hit (series__bool)
tp_hit (series__bool)
open (series__integer)
imlibLibrary "imlib"
Description
The library allows you to display images in your scripts utilising the objects. You can change the image size and screen aspect ratio (the ratio of width to height which you can change if the image is too wide / tall). The library has "example()" function which you can use to see how it works. It also has a handy "logo()" function which you can use to quickly display an image by passing the "Image data string", table position, image size and aspect ratio. And of course you can use it in your own custom way by taking the "logo()" function as an example and modifying the code to your needs.
Since tables in Pinescript are limited to 100 by 100 cells, the limit for image's size is also 100x100 px. All the necessary data to display an image is passed as a string variable, and since Pinescript has a limit of 4096 characters for variables of type, that string can have a maximum length of 4096 characters, which is enough to display a 64x64px image (but can be enough to display a 100x100 image, depending on the image itself).
Below you can find the definitions of functions for this library.
_decompress(data)
: Decompresses string with data image
Parameters:
data (string)
Returns: : Array of with decompressed data
load(data)
: Splits the string with image data into components and builds an object
Parameters:
data (string)
Returns: : An object
show(imgdata, table_id, image_size, screen_ratio)
: Displays an image in a table
Parameters:
imgdata (ImgData)
table_id (table)
image_size (float)
screen_ratio (string)
Returns: : nothing
example()
: Use it as an example of how this library works and how to use it in your own scripts
Returns: : nothing
logo(imgdata, position, image_size, screen_ratio)
: Displays logo using image data string
Parameters:
imgdata (string)
position (string)
image_size (float)
screen_ratio (string)
Returns: : nothing
ImgData
Fields:
w (series__integer)
h (series__integer)
s (series__string)
pal (series__string)
data (array__string)
multidataLibrary "multidata"
A library for multi-dimensional data arrays.
Full documentation: faiyaz7283.github.io
This library is designed to enhance data storage capabilities in Pine Script, enabling users to work with two separate data structures: data2d (key -> main-value | alternate-value) and data3d (primary key -> data key-> main-value | alternate-value). These structures facilitate storing key-value pairs in a flexible and efficient manner, offering various methods for manipulation and retrieval of data. Please check out the full documentation at faiyaz7283.github.io .
Extended Moving Average (MA) LibraryThis Extended Moving Average Library is a sophisticated and comprehensive tool for traders seeking to expand their arsenal of moving averages for more nuanced and detailed technical analysis.
The library contains various types of moving averages, each with two versions - one that accepts a simple constant length parameter and another that accepts a series or changing length parameter.
This makes the library highly versatile and suitable for a wide range of strategies and trading styles.
Moving Averages Included:
Simple Moving Average (SMA): This is the most basic type of moving average. It calculates the average of a selected range of prices, typically closing prices, by the number of periods in that range.
Exponential Moving Average (EMA): This type of moving average gives more weight to the latest data and is thus more responsive to new price information. This can help traders to react faster to recent price changes.
Double Exponential Moving Average (DEMA): This is a composite of a single exponential moving average, a double exponential moving average, and an exponential moving average of a triple exponential moving average. It aims to eliminate lag, which is a key drawback of using moving averages.
Jurik Moving Average (JMA): This is a versatile and responsive moving average that can be adjusted for market speed. It is designed to stay balanced and responsive, regardless of how long or short it is.
Kaufman's Adaptive Moving Average (KAMA): This moving average is designed to account for market noise or volatility. KAMA will closely follow prices when the price swings are relatively small and the noise is low.
Smoothed Moving Average (SMMA): This type of moving average applies equal weighting to all observations and smooths out the data.
Triangular Moving Average (TMA): This is a double smoothed simple moving average, calculated by averaging the simple moving averages of a dataset.
True Strength Force (TSF): This is a moving average of the linear regression line, a statistical tool used to predict future values from past values.
Volume Moving Average (VMA): This is a simple moving average of a volume, which can help to identify trends in volume.
Volume Adjusted Moving Average (VAMA): This moving average adjusts for volume and can be more responsive to volume changes.
Zero Lag Exponential Moving Average (ZLEMA): This type of moving average aims to eliminate the lag in traditional EMAs, making it more responsive to recent price changes.
Selector: The selector function allows users to easily select and apply any of the moving averages included in the library inside their strategy.
This library provides a broad selection of moving averages to choose from, allowing you to experiment with different types and find the one that best suits your trading strategy.
By providing both simple and series versions for each moving average, this library offers great flexibility, enabling users to pass both constant and changing length parameters as needed.
ta_mLibrary "ta_m"
This library is a Pine Script™ programmer’s tool containing calcs for my oscillators and some helper functions.
upDnIntrabarVolumesByPolarity()
Determines if the volume for an intrabar is up or down.
Returns: ( ) A tuple of two values, one of which contains the bar's volume. `upVol` is the positive volume of up bars. `dnVol` is the negative volume of down bars.
Note that when this function is designed to be called with `request.security_lower_tf()`,
which will return a tuple of "array" arrays containing up and dn volume for all the intrabars in a chart bar.
upDnIntrabarVolumesByPrice()
Determines if the intrabar volume is up or down
Returns: ( ) A tuple of two values, one of which contains the bar's volume. `upVol` is the positive volume of up bars. `dnVol` is the negative volume of down bars.
Note that when this function is designed to be called with `request.security_lower_tf()`,
which will return a tuple of "array" arrays containing up and dn volume for all the intrabars in a chart bar.
merge_pinbar_modifiedLibrary "merge_pinbar"
Published by @dandrideng
Modified by @RpNm1337
merge_pinbar: merge bars and check whether the bar is a pinbar
merge_pinbar(period, max_bars)
merge_pinbar: merge bars and check whether the bar is a pinbar
Parameters:
period (simple int)
max_bars (simple int)
Returns: array:
A_Taders_Edge_LIBRARYLibrary "A_Taders_Edge_LIBRARY"
RCI(_rciLength, _close, _interval, _outerMostRangeOfOscillator)
- You will see me using this a lot. DEFINITELY my favorite oscillator to utilize for SO many different things from timing entries/exits to determining trends.
Parameters:
_rciLength (int)
_close (float)
_interval (int)
_outerMostRangeOfOscillator (int)
Returns: - Outputs a single RCI value that will between (-)_outerMostRangeOfOscillator to (+)_outerMostRangeOfOscillator
InvalidTID(_close, _showInvalidAssets, _securityTickerid, _invalidArray)
- This is to add a table on the right of your chart that prints all the TickerID's that were either not formulated correctly in the scripts input or that is not a valid symbol and should be changed.
Parameters:
_close (float)
_showInvalidAssets (simple bool)
_securityTickerid (string)
_invalidArray (string )
Returns: - Does NOT return a value but rather the table with the invalid TickerID's from the scripts input that need to be changed.
LabelLocation(_firstLocation)
- This is ONLY for when you are wanting to print ALERT LABELS with the assets name for when an alert trigger occurs for that asset. There are a total of 40 assets that can be used in each copy of the script. You don't want labels from different assets printing on top of each other because you will not be able to read the asset name that the label is for. Ex. If you put your _firstLocation in the input settings as 1 and have 40 assets on this copy of the scanner then the first asset in the list is assigned to the location value 1 on the scale, and the 2nd in the list is assigned to location value 2...and so on. If your first location is set to 81 then the 1st asset is 81 and 2nd is 82 and so on.
Parameters:
_firstLocation (simple int)
Returns: - regardless of if you have the maximum amount of assets being screened (40 max), this export function will output 40 locations… So there needs to be 40 variables assigned to the tuple in this export function. What I mean by that is there needs to be 40 variables between the ' '. If you only have 20 assets in your scripts input settings, then only the first 20 variables within the ' ' Will be assigned to a value location and the other 20 will be assigned 'NA'.
SeparateTickerids(_string)
- You must form this single tickerID input string exactly as laid out in the water (a little gray circle at the end of the setting, that you hover your cursor over to read the details of). IF the string is formed correctly then it will break up. All of the tip rate is within the string into a total of 40 separate strings which will be all of the tickerIDs that the script is using in your MO scanner.
Parameters:
_string (simple string)
Returns: - this will output, 40 different security assets within the tuple output (ie. 40 variable within the ' ') regardless of if you were including 40 assets, to be screened in the MO Screener or not. if you have less than 40 assets, then once the variables are assigned to all of the tickerIDs, the rest of the variables will be assigned "NA".
TickeridForLabelsAndSecurity(_includeExchange, _ticker)
- this export function is used to output 2 tickerID strings. One is formulated to properly work in the request.security() function while the other is how it will appear on the asset name labels depending on how you form your assets string in the MO scanners input settings. Review the tooltip next to the setting, to learn how to form the string so that the asset name labels will appear how you want in the labels at the end of the line plots & the alert labels that would be triggered if the MO Scanner is set up to include Alert Trigger Labels.
Parameters:
_includeExchange (simple bool)
_ticker (simple string)
Returns: - this export function is used to output 2 tickerID strings. One is formulated to properly work in the request.security() function while the other is how it will appear on the asset name labels depending on how you form your assets string in the MO scanners input settings. Review the tooltip next to the setting, to learn how to form the string so that the asset name labels will appear how you want in the labels at the end of the line plots & the alert labels that would be triggered if the MO Scanner is set up to include Alert Trigger Labels.
PercentChange(_startingValue, _endingValue)
- this is a quick export function to calculate how much % change has occurred between the _startingValue and the _endingValue that you input into the export function.
Parameters:
_startingValue (float)
_endingValue (float)
Returns: - it will output a single percentage value between 0-100 with trailing numbers behind a decimal. If you want, only a certain amount of numbers behind the decimal, this export function needs to be put within a formatting function to do so. Explained in the MO Scanner INTRO VIDEO.
PrintedBarCount(_time, _barCntLength, _bcPmin)
- This export function will outfit the percentage of printed bars (that occurred within _barCntLength amount of time) out of the MAX amount of bars that potentially COULD HAVE been printed. Iexplanation in the MO Scanner INTRO VIDEO.
Parameters:
_time (int)
_barCntLength (int)
_bcPmin (int)
Returns: - Gives 2 outputs. The first is the total % of Printed Bars within the user set time period and second is true/false according to if the Printed BarCount % is above the _bcPmin threshold that you input into this export function.
CandlestickPatternsLibrary "CandlestickPatterns"
This library provides a wide range of candlestick patterns, and available for user to call each pattern individually. It's a comprehensive and common tool designed for traders seeking to raise their technical analysis, and it may help users identify key turning of price action in financial instruments. Credit to public technical “*All Candlestick Patterns*” indicator.
abandonedBaby(order, d1)
The "Abandoned Baby" candlestick pattern is a bullish/bearish pattern consists of three candles.
Parameters:
order (simple string) : (simple string) Pattern order type "bull" or "bear".
d1 (simple float) : (simple float) Previous candle's body percentage out of candle range. Optional argument, default is 5.
darkCloudCover(c1, n)
The "Dark Cloud Cover" is a bearish pattern consists of two candles.
Parameters:
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
doji(d0)
The "Doji" is neither bullish or bearish consists of one candles.
Parameters:
d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
dojiStar(order, c1, n, d0)
The "Doji Star" is a bullish/bearish pattern consists of two candles.
Parameters:
order (simple string) : (simple string) Pattern order type "bull" or "bear" .
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
downsideTasukiGap(c2, c1, n)
The "Downside Tasuki Gap" is a bearish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
dragonflyDoji(d0)
The "Dragon Fly Doji" is a bullish pattern consists of one candle.
Parameters:
d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
engulfing(order, c1, c0, n)
The "Engulfing" is a bullish/bearish pattern consists of two candles.
Parameters:
order (simple string) : (simple string) Pattern order type "bull" or "bear".
c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
eveningDojiStar(c2, c0, d1, n)
The "Evening Doji Star" is a bearish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
d1 (simple float) : (simple float) Previous candle's body percentage out of candle range. Optional argument, default is 5.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
eveningStar(c2, c1, c0, n)
The "Evening Star" is a bearish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
fallingThreeMethods(c4, c3, c2, c1, c0, n)
The "Falling Three Methods" is a bearish pattern consists of five candles.
Parameters:
c4 (simple bool) : (simple bool) 5th candle ago body must be higher than average. Optional argument, default is true.
c3 (simple bool) : (simple bool) 4th candle ago body must be lower than average. Optional argument, default is true.
c2 (simple bool) : (simple bool) 3rd candle ago body must be lower than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) 2nd candle ago body must be lower than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
Returns: (bool)
fallingWindow()
The "Falling Window" is a bearish pattern consists of two candles.
gravestoneDoji(d0)
The "Gravestone Doji" is a bearish pattern consists of one candle.
Parameters:
d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
hammer(c0, n)
The "Hammer" is a bullish pattern consists of one candle.
Parameters:
c0 (simple bool) : (simple bool) Current candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
hangingMan(c0, n)
The "Hanging Man" is a bearish pattern consists of one candle.
Parameters:
c0 (simple bool) : (simple bool) Current candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
haramiCross(order, c1, n)
The "Harami Cross" candlestick pattern is a bullish/bearish pattern consists of two candles.
Parameters:
order (string) : (simple string) Pattern order type "bull" or "bear".
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
harami(order, c1, c0, n)
The "Harami" candlestick pattern is a bullish/bearish pattern consists of two candles.
Parameters:
order (string) : (simple string) Pattern order type "bull" or "bear"
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
invertedHammer(c0, n)
The "Inverted Hammer" is a bullish pattern consists of one candle.
Parameters:
c0 (simple bool) : (simple bool) Current candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
kicking(order, c1, c0, n)
The "Kicking" candlestick pattern is a bullish/bearish pattern consists of two candles.
Parameters:
order (string) : (simple string) Pattern order type "bull" or "bear"
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
longLowerShadow(l0)
The "Long Lower Shadow" candlestick pattern is a bullish pattern consists of one candles.
Parameters:
l0 (simple float) : (simple float) Current candle's lower wick min percentage out of candle range. Optional argument, default is 75.
longUpperShadow(u0)
The "Long Upper Shadow" candlestick pattern is a bearish pattern consists of one candles.
Parameters:
u0 (simple float) : (simple float) Current candle's upper wick min percentage out of candle range. Optional argument, default is 75.
marubozuBlack(c0, n)
The "Marubozu Black" candlestick pattern is a bearish pattern consists of one candles.
Parameters:
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
marubozuWhite(c0, n)
The "Marubozu White" candlestick pattern is a bullish pattern consists of one candles.
Parameters:
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
morningDojiStar(c2, d1, c0, n)
The "Morning Doji Star" candlestick pattern is a bullish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
d1 (simple float) : (simple float) Previous candle's body percentage out of candle range. Optional argument, default is 5.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
morningStar(c2, c1, c0, n)
The "Morning Star" candlestick pattern is a bullish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Cuurent candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
onNeck(c1, c0, n)
The "On Neck" candlestick pattern is a bearish pattern consists of two candles.
Parameters:
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Cuurent candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
piercing(c1, n)
The "Piercing" candlestick pattern is a bullish pattern consists of two candles.
Parameters:
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
risingThreeMethods(c4, c3, c2, c1, c0, n)
The "Rising Three Methods" candlestick pattern is a bullish pattern consists of five candles.
Parameters:
c4 (simple bool) : (simple bool) 5th candle ago body must be higher than average. Optional argument, default is true.
c3 (simple bool) : (simple bool) 4th candle ago body must be Lower than average. Optional argument, default is true.
c2 (simple bool) : (simple bool) 3rd candle ago body must be Lower than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) 2nd candle ago body must be Lower than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
risingWindow()
The "Rising Window" candlestick pattern is a bullish pattern consists of two candle.
shootingStar(c0, n)
The "Shooting Star" candlestick pattern is a bearish pattern consists of one candle.
Parameters:
c0 (simple bool) : (simple bool) Current candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
spinningTopBlack(l0, u0)
The "Spinning Top Black" is neither bullish or bearish.
Parameters:
l0 (simple float) : (simple float) Current candle's lower wick min percentage out of candle range. Optional argument, default is 34.
u0 (simple float) : (simple float) Current candle's upper wick min percentage out of candle range. Optional argument, default is 34.
spinningTopWhite(l0, u0)
The "Spinning Top White" is neither bullish or bearish.
Parameters:
l0 (simple float) : (simple float) Current candle's lower wick min percentage out of candle range. Optional argument, default is 34.
u0 (simple float) : (simple float) Current candle's upper wick min percentage out of candle range. Optional argument, default is 34.
threeBlackCrows(c2, c1, c0, n)
The "Three Black Crows" candlestick pattern is a bearish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Cuurent candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
threeWhiteSoldiers(c2, c1, c0, n)
The "Three White Soldiers" candlestick pattern is a bullish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before previous candle's body must be higher than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
c0 (simple bool) : (simple bool) Cuurent candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
triStar(order, d2, d1, d0)
The "Tri Star" candlestick pattern is a bullish/bearish pattern consists of three candles.
Parameters:
order (simple string) : (simple string) Pattern order type "bull" or "bear".
d2 (simple float) : (simple float) Before previous candle's body percentage out of candle range. Optional argument, default is 5.
d1 (simple float) : (simple float) Previous candle's body percentage out of candle range. Optional argument, default is 5.
d0 (simple float) : (simple float) Current candle's body percentage out of candle range. Optional argument, default is 5.
tweezerBottom(c1, n)
The "Tweezer Bottom" candlestick pattern is a bullish pattern consists of two candles.
Parameters:
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
tweezerTop(c1, n)
The "Tweezer Top" candlestick pattern is a bearish pattern consists of two candles.
Parameters:
c1 (simple bool) : (simple bool) Previous candle's body must be higher than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
upsideTasukiGap(c2, c1, n)
The "Tri Star" candlestick pattern is a bullish pattern consists of three candles.
Parameters:
c2 (simple bool) : (simple bool) Before Previous candle's body must be higher than average. Optional argument, default is true.
c1 (simple bool) : (simple bool) Previous candle's body must be lower than average. Optional argument, default is true.
n (simple int) : (simple int) Length of average candle's body. Optional argument, default is 14.
LibrarySupertrendLibrary "LibrarySupertrend"
selective_ma(condition, source, length)
Parameters:
condition (bool)
source (float)
length (int)
trendUp(source)
Parameters:
source (float)
smoothrng(source, sampling_period, range_mult)
Parameters:
source (float)
sampling_period (simple int)
range_mult (float)
rngfilt(source, smoothrng)
Parameters:
source (float)
smoothrng (float)
fusion(overallLength, rsiLength, mfiLength, macdLength, cciLength, tsiLength, rviLength, atrLength, adxLength)
Parameters:
overallLength (simple int)
rsiLength (simple int)
mfiLength (simple int)
macdLength (simple int)
cciLength (simple int)
tsiLength (simple int)
rviLength (simple int)
atrLength (simple int)
adxLength (simple int)
zonestrength(amplitude, wavelength)
Parameters:
amplitude (int)
wavelength (simple int)
atr_anysource(source, atr_length)
Parameters:
source (float)
atr_length (simple int)
supertrend_anysource(source, factor, atr_length)
Parameters:
source (float)
factor (float)
atr_length (simple int)
TradingToolsLibraryLibrary "TradingToolsLibrary"
Easily create advanced entries, exits, filters and qualifiers to simulate strategies. Supports DCA (Dollar Cost Averaging) Lines, Stop Losses, Take Profits (with trailing or without) & ATR.
method deepCopy(this)
This creates a deep copy instead of a shallow copy of an entry_position. This does NOT deep copy the self_pyramiding_positions array reference, since only the master entry_position needs this to track the rest of its copies for efficiency reasons. This is to prevent a feedback loop.
Namespace types: entry_position
Parameters:
this (entry_position)
Returns: entry_position
method precision_fix(this, precision)
Convert a floating point number to a precise floating point number with digit precision to avoid floating point errors in quantity calculations.
Namespace types: series float, simple float, input float, const float
Parameters:
this (float)
precision (int)
Returns: float
xSellBuyMidInterpolation(_x, _high, _low, _sellRange, _buyRange)
Creates an interpolation for a sell range and buy range but with an emphasis on reaching the _low the closer to the middle of the _sell and _buy range you go.
Parameters:
_x (float) : is the value you want to use to control interpolation bewteen the _high and _low value. This will return the lowest percentage at the mid between high and low and highest percentage at the _high and _low.
_high (float)
_low (float)
_sellRange (float)
_buyRange (float)
Returns: an interpolated float between the _high and _low supplied.
xSellBuyInterpolation(_x, _high, _low, _sellRange, _buyRange)
Creates an interpolation a sell range and buy range
Parameters:
_x (float) : is the value you want to use to control interpolation bewteen the _high and _low value.
_high (float)
_low (float)
_sellRange (float)
_buyRange (float)
Returns: an interpolated float between the _high and _low supplied.
activate_entries_and_exits(_entries, _exits, _filters, _qualifiers, _equity)
Determines activation for entries or exits. Does not place the actual orders.
Parameters:
_entries (entry_position )
_exits (exit_position )
_filters (filter )
_qualifiers (qualifier )
_equity (equity_management)
Returns: void
create_entries_and_exits(_entries, _exits, _equity)
Creates actual entry and exit orders if activated
Parameters:
_entries (entry_position )
_exits (exit_position )
_equity (equity_management)
Returns: void
filter
Fields:
disabled (series__bool)
filter_for_entries_or_exits (series__string)
filter_for_groups (series__string)
condition (series__bool)
dynamic_condition (series__bool)
use_dynamic_condition (series__bool)
use_override_default_condition (series__bool)
dynamic_condition_operator (series__string)
dynamic_condition_source (series__float)
dynamic_compare_source (series__float)
dynamic_condition_source_prior (series__float)
dynamic_compare_source_prior (series__float)
use_dynamic_compare_source (series__bool)
dynamic_condition_activate_value (series__string)
expire_condition_activate_value (series__string)
expire_condition_source (series__float)
expire_condition_source_prior (series__float)
expire_compare_source (series__float)
expire_compare_source_prior (series__float)
use_expire_compare_source (series__bool)
expire_condition_operator (series__string)
qualifier
Fields:
disabled (series__bool)
qualify_for_entries_or_exits (series__string)
qualify_for_groups (series__string)
disqualify (series__bool)
condition (series__bool)
dynamic_condition (series__bool)
use_dynamic_condition (series__bool)
use_override_default_condition (series__bool)
dynamic_condition_operator (series__string)
dynamic_condition_source (series__float)
dynamic_compare_source (series__float)
dynamic_condition_source_prior (series__float)
dynamic_compare_source_prior (series__float)
use_dynamic_compare_source (series__bool)
dynamic_condition_activate_value (series__string)
expire_after_x_bars (series__integer)
use_expire_after_x_bars (series__bool)
use_expire_condition (series__bool)
use_override_expire_condition (series__bool)
expire_condition_operator (series__string)
expire_condition_source (series__float)
expire_compare_source (series__float)
expire_condition_source_prior (series__float)
expire_compare_source_prior (series__float)
use_expire_compare_source (series__bool)
expire_condition_activate_value (series__string)
active (series__bool)
expire_after_bars_bar_index (series__integer)
expire_after_bars_bar_index_prior (series__integer)
expire_bar_count (series__integer)
expire_bar_changed (series__bool)
entry_position
Fields:
disabled (series__bool)
activate (series__bool)
active (series__bool)
override_occured (series__bool)
passDebug (array__bool)
initial_activation_price (series__float)
dca_done (series__bool)
condition (series__bool)
dynamic_condition (series__bool)
use_dynamic_condition (series__bool)
use_override_default_condition (series__bool)
dynamic_condition_operator (series__string)
dynamic_condition_source (series__float)
dynamic_compare_source (series__float)
dynamic_condition_source_prior (series__float)
dynamic_compare_source_prior (series__float)
use_dynamic_compare_source (series__bool)
dynamic_condition_activate_value (series__string)
use_cash (series__bool)
use_percent_equity (series__bool)
percent_equity_amount (series__float)
cash_amount (series__float)
position_size (series__float)
total_position_size (series__float)
prior_total_position_size (series__float)
equity_remaining (series__float)
prior_equity_remaining (series__float)
initial_equity (series__float)
use_martingale (series__bool)
martingale_win_ratio (series__float)
martingale_lose_ratio (series__float)
martingale_win_limit (series__integer)
martingale_lose_limit (series__integer)
martingale_limit_reset_mode (series__string)
use_dynamic_percent_equity (series__bool)
dynamic_percent_equity_amount (series__float)
initial_dynamic_percent_equity_amount (series__float)
dynamic_percent_equity_source (series__float)
dynamic_percent_equity_min (series__float)
dynamic_percent_equity_max (series__float)
dynamic_percent_equity_source_sell_range (series__float)
dynamic_percent_equity_source_buy_range (series__float)
dynamic_equity_interpolation_method (series__string)
total_bars (series__integer)
bar_index_at_activate (series__integer)
bars_since_active (series__integer)
time_at_activate (series__integer)
time_since_active (series__integer)
bar_index_at_activated (series__integer)
bar_index_at_pyramid_change (series__integer)
name (series__string)
id (series__string)
group (series__string)
pyramiding_limit (series__integer)
self_pyramiding_limit (series__integer)
self_pyramiding_positions (array__|entry_position|#OBJ)
new_pyramid_cancels_dca (series__bool)
num_active_long_positions (series__integer)
num_active_short_positions (series__integer)
num_active_positions (series__integer)
position_remaining (series__float)
prior_position_remaining (series__float)
direction (series__string)
allow_flip_position (series__bool)
flip_occurred (series__bool)
ignore_flip (series__bool)
use_dca (series__bool)
dca_use_limit (series__bool)
dca_num_positions (series__integer)
dca_positions (array__float)
dca_deviation_percentage (series__float)
dca_scale (series__float)
dca_percentages (series__string)
dca_close_cancels (series__bool)
dca_active_positions (series__integer)
use_atr_deviation (series__bool)
dca_atr_length (series__integer)
dca_atr_mult (series__float)
dca_atr_updates_dca_positions (series__bool)
close_price_at_order (series__float)
dca_use_deviation_atr_min (series__bool)
dca_position_quantities (array__float)
use_dca_dynamic_percent_equity (series__bool)
dca_in_use (array__bool)
dca_activated (array__bool)
dca_money_used (array__float)
dca_lines (array__line)
dca_color (series__color)
show_dca_lines (series__bool)
atr_value (series__float)
atr_value_at_activation (series__float)
use_cooldown_bars (series__bool)
cooldown_bars (series__integer)
cooldown_bar_changed (series__bool)
cooldown_bar_index (series__integer)
cooldown_bar_index_prior (series__integer)
cooldown_bar_change_count (series__integer)
expire_condition_activate_value (series__string)
expire_condition_source (series__float)
expire_condition_source_prior (series__float)
expire_compare_source (series__float)
expire_compare_source_prior (series__float)
use_expire_compare_source (series__bool)
expire_condition_operator (series__string)
exit_position
Fields:
disabled (series__bool)
id (series__string)
group (series__string)
exit_for_entries (series__string)
exit_for_groups (series__string)
total_bars (series__integer)
name (series__string)
condition (series__bool)
dynamic_condition (series__bool)
use_dynamic_condition (series__bool)
use_override_default_condition (series__bool)
dynamic_condition_operator (series__string)
dynamic_condition_source (series__float)
dynamic_compare_source (series__float)
dynamic_condition_source_prior (series__float)
dynamic_compare_source_prior (series__float)
use_dynamic_compare_source (series__bool)
dynamic_condition_activate_value (series__string)
activate (series__bool)
active (series__bool)
reset_equity (series__bool)
use_limit (series__bool)
use_alerts (series__bool)
reset_entry_cooldowns (series__bool)
prevent_new_entries_on_partial_close (series__bool)
show_activation_zone (series__bool)
use_average_position (series__bool)
source_value (series__float)
trigger_x_times (series__integer)
amount_of_times_triggered (series__integer)
quantity_percent (series__float)
trade_qty (series__float)
exit_amount (series__float)
entries_exiting_for (array__|entry_position|#OBJ)
atr_value (series__float)
update_atr (series__bool)
use_activate_after_bars (series__bool)
show_activate_after_bars (series__bool)
activate_after_bars (series__integer)
activate_after_bars_bar_changed (series__bool)
activate_after_bars_bar_index (series__integer)
activate_after_bars_bar_index_prior (series__integer)
activate_after_bars_bar_change_count (series__integer)
all_conditions_pass (series__bool)
use_close_if_profit_only (series__bool)
profit_value (series__float)
exit_type (series__string)
exit_modifier (series__string)
update_atr_with_new_pyramid (series__bool)
percentage (series__float)
activation_percentage (series__float)
atr_multiplier (series__float)
use_cancel_if_percent (series__bool)
cancel_if_percent (series__float)
activation_value (series__float)
activation_value_crossed (series__bool)
exit_value (series__float)
hypo_long_exit_value (series__float)
hypo_short_exit_value (series__float)
close_exit_value (series__float)
debug (series__float)
expire_condition_activate_value (series__string)
expire_condition_source (series__float)
expire_condition_source_prior (series__float)
expire_compare_source (series__float)
expire_compare_source_prior (series__float)
use_expire_compare_source (series__bool)
expire_condition_operator (series__string)
equity_management
Fields:
equity (series__float)
prior_equity (series__float)
position_used (series__float)
prior_position_used (series__float)
prevent_future_entries (series__bool)
minimum_order_size (series__float)
decimal_rounding_precision (series__integer)
direction (series__string)
show_order_info_in_comments (series__bool)
show_order_info_in_labels (series__bool)
allow_longs (series__bool)
allow_shorts (series__bool)
override_occured (series__bool)
flip_occured (series__bool)
num_concurrent_wins (series__integer)
num_concurrent_losses (series__integer)
first_entry (|entry_position|#OBJ)
num_win_trades (series__integer)
num_losing_trades (series__integer)
JapaneseCandlestickPatternsLibrary "JapaneseCandlestickPatterns"
Japanese Candlestick Patterns is a library of functions that enables the detection of popular Japanese candlestick patterns such as Doji, Hammer, and Engulfing, among others. The library provides a simple yet powerful way to analyze financial markets and make informed trading decisions. Japanese Candlestick Patterns library can help you identify potential trading opportunities.
isDojiCandle()
isGravestoneDojiCandle()
isDragonflyDojiCandle()
isEveningDojiStarCandle(isUpTrend)
Parameters:
isUpTrend (bool)
isLongLeggedDojiCandle()
isMorningDojiStarCandle(isDownTrend)
Parameters:
isDownTrend (bool)
isBullishCounterattackLinesCandle(isDownTrend)
Parameters:
isDownTrend (bool)
isBearishCounterattackLinesCandle(isUpTrend)
Parameters:
isUpTrend (bool)
isDarkCloudCoverCandle(isUpTrend)
Parameters:
isUpTrend (bool)
isBullishEngulfingCandle()
isBearishEngulfingCandle()
isHammerCandle(isDownTrend)
Parameters:
isDownTrend (bool)
isHangingManCandle(isUpTrend)
Parameters:
isUpTrend (bool)
isHaramiBearishCandle(isUpTrend)
Parameters:
isUpTrend (bool)
isHaramiBullishCandle(isDownTrend)
Parameters:
isDownTrend (bool)
isInNeckCandle(isDownTrend)
Parameters:
isDownTrend (bool)
isOnNeckCandle(isDownTrend)
Parameters:
isDownTrend (bool)
isPiercingCandle(isDownTrend)
Parameters:
isDownTrend (bool)
threeBlackCrowsCandle(isUpTrend)
Parameters:
isUpTrend (bool)
isThrustingNeckCandle(isDownTrend)
Parameters:
isDownTrend (bool)
isUpsideGapTwoCrowsCandle(isUpTrend)
Parameters:
isUpTrend (bool)
isAbandonedBabyTopCandle(isUpTrend)
Parameters:
isUpTrend (bool)
isAbandonedBabyBottomCandle(isDownTrend)
Parameters:
isDownTrend (bool)
isEveningStarCandle(isUpTrend)
Parameters:
isUpTrend (bool)
isInvertedHammerCandle(isDownTrend)
Parameters:
isDownTrend (bool)
isMorningStarCandle(isDownTrend)
Parameters:
isDownTrend (bool)
isShootingStarCandle(isUpTrend)
Parameters:
isUpTrend (bool)
isRisingThreeMethodsCandle(isUpTrend)
Parameters:
isUpTrend (bool)
isFallingThreeMethodsCandle(isDownTrend)
Parameters:
isDownTrend (bool)
isUpsideTasukiGapCandle(isUpTrend)
Parameters:
isUpTrend (bool)
isDownsideGapTasukiCandle(isDownTrend)
Parameters:
isDownTrend (bool)
isLongLowerShadowCandle()
isLongUpperShadowCandle()
gFancyMALibrary "gFancyMA"
printLbl(y, x, c, m, b, s)
Parameters:
y (float)
x (int)
c (color)
m (string)
b (bool)
s (string)
debugLibrary "debug"
Show Array or Matrix Elements In Table
Use anytime you want to see the elements in an array or a matrix displayed.
Effective debugger, particularly for strategies and complex logic structures.
Look in code to find instructions. Reach out if you need assistance.
Functionality includes:
Viewing the contents of an array or matrix on screen.
Track variables and variable updates using debug()
Track if and when local scopes fire using debugs()
Types Allowed:
string
float
int
string
debug(_col, _row, _name, _value, _msg, _ip)
Debug Variables in Matrix
Parameters:
_col (int) : (int) Assign Column
_row (int) : (int) Assign Row
_name (matrix) : (simple matrix) Matrix Name
_value (string) : (string) Assign variable as a string (str.tostring())
_msg (string)
_ip (int) : (int) (default 1) 1 for continuous updates. 2 for barstate.isnew updates. 3 for barstate.isconfirmed updates. -1 to only add once
Returns: Returns Variable _value output and _msg formatted as '_msg: variableOutput' in designated column and row
debug(_col, _row, _name, _value, _msg, _ip)
Parameters:
_col (int)
_row (int)
_name (matrix)
_value (float)
_msg (string)
_ip (int)
debug(_col, _row, _name, _value, _msg, _ip)
Parameters:
_col (int)
_row (int)
_name (matrix)
_value (int)
_msg (string)
_ip (int)
debug(_col, _row, _name, _value, _msg, _ip)
Parameters:
_col (int)
_row (int)
_name (matrix)
_value (bool)
_msg (string)
_ip (int)
debugs(_col, _row, _name, _msg)
Debug Scope in Matrix - Identify When Scope Is Accessed
Parameters:
_col (int) : (int) Column Number
_row (int) : (int) Row Number
_name (matrix) : (simple matrix) Matrix Name
_msg (string) : (string) Message
Returns: Message appears in debug panel using _col/_row as the identifier
viewArray(_arrayName, _pos, _txtSize, _tRows, s_index, s_border, _rowCol, bCol, _fillCond, _offset)
Array Element Display (Supports float , int , string , and bool )
Parameters:
_arrayName (float ) : ID of Array to be Displayed
_pos (string) : Position for Table
_txtSize (string) : Size of Table Cell Text
_tRows (int) : Number of Rows to Display Data In (columns will be calculated accordingly)
s_index (bool) : (Optional. Default True.) Show/Hide Index Numbers
s_border (bool) : (Optional. Default False.) Show/Hide Border
_rowCol (string)
bCol (color) : = (Optional. Default Black.) Frame/Border Color.
_fillCond (bool) : (Optional) Conditional statement. Function displays array only when true. For instances where size is not immediately known or indices are na. Default = true, indicating array size is set at bar_index 0.
_offset (int) : (Optional) Use to view historical array states. Default = 0, displaying realtime bar.
Returns: A Display of Array Values in a Table
viewArray(_arrayName, _pos, _txtSize, _tRows, s_index, s_border, _rowCol, bCol, _fillCond, _offset)
Parameters:
_arrayName (int )
_pos (string)
_txtSize (string)
_tRows (int)
s_index (bool)
s_border (bool)
_rowCol (string)
bCol (color)
_fillCond (bool)
_offset (int)
viewArray(_arrayName, _pos, _txtSize, _tRows, s_index, s_border, _rowCol, bCol, _fillCond, _offset)
Parameters:
_arrayName (string )
_pos (string)
_txtSize (string)
_tRows (int)
s_index (bool)
s_border (bool)
_rowCol (string)
bCol (color)
_fillCond (bool)
_offset (int)
viewArray(_arrayName, _pos, _txtSize, _tRows, s_index, s_border, _rowCol, bCol, _fillCond, _offset)
Parameters:
_arrayName (bool )
_pos (string)
_txtSize (string)
_tRows (int)
s_index (bool)
s_border (bool)
_rowCol (string)
bCol (color)
_fillCond (bool)
_offset (int)
viewMatrix(_matrixName, _pos, _txtSize, s_index, _resetIdx, s_border, bCol, _fillCond, _offset)
Matrix Element Display (Supports , , , and )
Parameters:
_matrixName (matrix) : ID of Matrix to be Displayed
_pos (string) : Position for Table
_txtSize (string) : Size of Table Cell Text
s_index (bool) : (Optional. Default True.) Show/Hide Index Numbers
_resetIdx (bool)
s_border (bool) : (Optional. Default False.) Show/Hide Border
bCol (color) : = (Optional. Default Black.) Frame/Border Color.
_fillCond (bool) : (Optional) Conditional statement. Function displays matrix only when true. For instances where size is not immediately known or indices are na. Default = true, indicating matrix size is set at bar_index 0.
_offset (int) : (Optional) Use to view historical matrix states. Default = 0, displaying realtime bar.
Returns: A Display of Matrix Values in a Table
viewMatrix(_matrixName, _pos, _txtSize, s_index, _resetIdx, s_border, bCol, _fillCond, _offset)
Parameters:
_matrixName (matrix)
_pos (string)
_txtSize (string)
s_index (bool)
_resetIdx (bool)
s_border (bool)
bCol (color)
_fillCond (bool)
_offset (int)
viewMatrix(_matrixName, _pos, _txtSize, s_index, _resetIdx, s_border, bCol, _fillCond, _offset)
Parameters:
_matrixName (matrix)
_pos (string)
_txtSize (string)
s_index (bool)
_resetIdx (bool)
s_border (bool)
bCol (color)
_fillCond (bool)
_offset (int)
viewMatrix(_matrixName, _pos, _txtSize, s_index, _resetIdx, s_border, bCol, _fillCond, _offset)
Parameters:
_matrixName (matrix)
_pos (string)
_txtSize (string)
s_index (bool)
_resetIdx (bool)
s_border (bool)
bCol (color)
_fillCond (bool)
_offset (int)
