Moving Averages ProxyLibrary "MovingAveragesProxy"
Moving Averages Proxy - Library of all moving averages spread out in different libraries
rvwap(_src, fixedTfInput, minsInput, hoursInput, daysInput, minBarsInput)
Calculates the Rolling VWAP (customized VWAP developed by the team of TradingView)
Parameters:
_src : (float) Source. Default: close
fixedTfInput : (bool) Use a fixed time period. Default: false
minsInput : (int) Minutes. Default: 0
hoursInput : (int) Hours. Default: 0
daysInput : (int) Days. Default: 1
minBarsInput : (int) Bars. Default: 10
Returns: (float) Rolling VWAP
correlationMa(src, len, factor)
Correlation Moving Average
Parameters:
src : (float) Source. Default: close
len : (int) Length
factor : (float) Factor. Default: 1.7
Returns: (float) Correlation Moving Average
regma(src, len, lambda)
Regularized Exponential Moving Average
Parameters:
src : (float) Source. Default: close
len : (int) Length
lambda : (float) Lambda. Default: 0.5
Returns: (float) Regularized Exponential Moving Average
repma(src, len)
Repulsion Moving Average
Parameters:
src : (float) Source. Default: close
len : (int) Length
Returns: (float) Repulsion Moving Average
epma(src, length, offset)
End Point Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
offset : (float) Offset. Default: 4
Returns: (float) End Point Moving Average
lc_lsma(src, length)
1LC-LSMA (1 line code lsma with 3 functions)
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) 1LC-LSMA Moving Average
aarma(src, length)
Adaptive Autonomous Recursive Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Adaptive Autonomous Recursive Moving Average
alsma(src, length)
Adaptive Least Squares
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Adaptive Least Squares
ahma(src, length)
Ahrens Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Ahrens Moving Average
adema(src)
Ahrens Moving Average
Parameters:
src : (float) Source. Default: close
Returns: (float) Moving Average
autol(src, lenDev)
Auto-Line
Parameters:
src : (float) Source. Default: close
lenDev : (int) Length for standard deviation
Returns: (float) Auto-Line
fibowma(src, length)
Fibonacci Weighted Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Moving Average
fisherlsma(src, length)
Fisher Least Squares Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Moving Average
leoma(src, length)
Leo Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Moving Average
linwma(src, period, weight)
Linear Weighted Moving Average
Parameters:
src : (float) Source. Default: close
period : (int) Length
weight : (int) Weight
Returns: (float) Moving Average
mcma(src, length)
McNicholl Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Moving Average
srwma(src, length)
Square Root Weighted Moving Average
Parameters:
src : (float) Source. Default: close
length : (int) Length
Returns: (float) Moving Average
EDSMA(src, len)
Ehlers Dynamic Smoothed Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: EDSMA smoothing.
dema(x, t)
Double Exponential Moving Average.
Parameters:
x : Series to use ('close' is used if no argument is supplied).
t : Lookback length to use.
Returns: DEMA smoothing.
tema(src, len)
Triple Exponential Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: TEMA smoothing.
smma(src, len)
Smoothed Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: SMMA smoothing.
hullma(src, len)
Hull Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: Hull smoothing.
frama(x, t)
Fractal Reactive Moving Average.
Parameters:
x : Series to use ('close' is used if no argument is supplied).
t : Lookback length to use.
Returns: FRAMA smoothing.
kama(x, t)
Kaufman's Adaptive Moving Average.
Parameters:
x : Series to use ('close' is used if no argument is supplied).
t : Lookback length to use.
Returns: KAMA smoothing.
vama(src, len)
Volatility Adjusted Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: VAMA smoothing.
donchian(len)
Donchian Calculation.
Parameters:
len : Lookback length to use.
Returns: Average of the highest price and the lowest price for the specified look-back period.
Jurik(src, len)
Jurik Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: JMA smoothing.
xema(src, len)
Optimized Exponential Moving Average.
Parameters:
src : Series to use ('close' is used if no argument is supplied).
len : Lookback length to use.
Returns: XEMA smoothing.
ehma(src, len)
EHMA - Exponential Hull Moving Average
Parameters:
src : Source
len : Period
Returns: Exponential Hull Moving Average (EHMA)
covwema(src, len)
Coefficient of Variation Weighted Exponential Moving Average (COVWEMA)
Parameters:
src : Source
len : Period
Returns: Coefficient of Variation Weighted Exponential Moving Average (COVWEMA)
covwma(src, len)
Coefficient of Variation Weighted Moving Average (COVWMA)
Parameters:
src : Source
len : Period
Returns: Coefficient of Variation Weighted Moving Average (COVWMA)
eframa(src, len, FC, SC)
Ehlrs Modified Fractal Adaptive Moving Average (EFRAMA)
Parameters:
src : Source
len : Period
FC : Lower Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
SC : Upper Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
Returns: Ehlrs Modified Fractal Adaptive Moving Average (EFRAMA)
etma(src, len)
Exponential Triangular Moving Average (ETMA)
Parameters:
src : Source
len : Period
Returns: Exponential Triangular Moving Average (ETMA)
rma(src, len)
RMA - RSI Moving average
Parameters:
src : Source
len : Period
Returns: RSI Moving average (RMA)
thma(src, len)
THMA - Triple Hull Moving Average
Parameters:
src : Source
len : Period
Returns: Triple Hull Moving Average (THMA)
vidya(src, len)
Variable Index Dynamic Average (VIDYA)
Parameters:
src : Source
len : Period
Returns: Variable Index Dynamic Average (VIDYA)
zsma(src, len)
Zero-Lag Simple Moving Average (ZSMA)
Parameters:
src : Source
len : Period
Returns: Zero-Lag Simple Moving Average (ZSMA)
zema(src, len)
Zero-Lag Exponential Moving Average (ZEMA)
Parameters:
src : Source
len : Period
Returns: Zero-Lag Exponential Moving Average (ZEMA)
evwma(src, len)
EVWMA - Elastic Volume Weighted Moving Average
Parameters:
src : Source
len : Period
Returns: Elastic Volume Weighted Moving Average (EVWMA)
tt3(src, len, a1_t3)
Tillson T3
Parameters:
src : Source
len : Period
a1_t3 : Tillson T3 Volume Factor
Returns: Tillson T3
gma(src, len)
GMA - Geometric Moving Average
Parameters:
src : Source
len : Period
Returns: Geometric Moving Average (GMA)
wwma(src, len)
WWMA - Welles Wilder Moving Average
Parameters:
src : Source
len : Period
Returns: Welles Wilder Moving Average (WWMA)
cma(src, len)
Corrective Moving average (CMA)
Parameters:
src : Source
len : Period
Returns: Corrective Moving average (CMA)
edma(src, len)
Exponentially Deviating Moving Average (MZ EDMA)
Parameters:
src : Source
len : Period
Returns: Exponentially Deviating Moving Average (MZ EDMA)
rema(src, len)
Range EMA (REMA)
Parameters:
src : Source
len : Period
Returns: Range EMA (REMA)
sw_ma(src, len)
Sine-Weighted Moving Average (SW-MA)
Parameters:
src : Source
len : Period
Returns: Sine-Weighted Moving Average (SW-MA)
mama(src, len)
MAMA - MESA Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: MESA Adaptive Moving Average (MAMA)
fama(src, len)
FAMA - Following Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: Following Adaptive Moving Average (FAMA)
hkama(src, len)
HKAMA - Hilbert based Kaufman's Adaptive Moving Average
Parameters:
src : Source
len : Period
Returns: Hilbert based Kaufman's Adaptive Moving Average (HKAMA)
getMovingAverage(type, src, len, lsmaOffset, inputAlmaOffset, inputAlmaSigma, FC, SC, a1_t3, fixedTfInput, daysInput, hoursInput, minsInput, minBarsInput, lambda, volumeWeighted, gamma_aarma, smooth, linweight, volatility_lookback, jurik_phase, jurik_power)
Abstract proxy function that invokes the calculation of a moving average according to type
Parameters:
type : (string) Type of moving average
src : (float) Source of series (close, high, low, etc.)
len : (int) Period of loopback to calculate the average
lsmaOffset : (int) Offset for Least Squares MA
inputAlmaOffset : (float) Offset for ALMA
inputAlmaSigma : (float) Sigma for ALMA
FC : (int) Lower Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
SC : (int) Upper Shift Limit for Ehlrs Modified Fractal Adaptive Moving Average
a1_t3 : (float) Tillson T3 Volume Factor
fixedTfInput : (bool) Use a fixed time period in Rolling VWAP
daysInput : (int) Days in Rolling VWAP
hoursInput : (int) Hours in Rolling VWAP
minsInput : (int) Minutrs in Rolling VWAP
minBarsInput : (int) Bars in Rolling VWAP
lambda : (float) Regularization Constant in Regularized EMA
volumeWeighted : (bool) Apply volume weighted calculation in selected moving average
gamma_aarma : (float) Gamma for Adaptive Autonomous Recursive Moving Average
smooth : (float) Smooth for Adaptive Least Squares
linweight : (float) Weight for Volume Weighted Moving Average
volatility_lookback : (int) Loopback for Volatility Adjusted Moving Average
jurik_phase : (int) Phase for Jurik Moving Average
jurik_power : (int) Power for Jurik Moving Average
Returns: (float) Moving average
المؤشرات والاستراتيجيات
TALibrary "TA"
General technical analysis functions
div_bull(pS, iS, cp_length_after, cp_length_before, pivot_length, lookback, no_broken, pW, iW, hidW, regW)
Test for bullish divergence
Parameters:
pS : Price series (float)
iS : Indicator series (float)
cp_length_after : Bars after current (divergent) pivot low to be considered a valid pivot (optional int)
cp_length_before : Bars before current (divergent) pivot low to be considered a valid pivot (optional int)
pivot_length : Bars before and after prior pivot low to be considered valid pivot (optional int)
lookback : Bars back to search for prior pivot low (optional int)
no_broken : Flag to only consider divergence valid if the pivot-to-pivot trendline is unbroken (optional bool)
pW : Weight of change in price, used in degree of divergence calculation (optional float)
iW : Weight of change in indicator, used in degree of divergence calculation (optional float)
hidW : Weight of hidden divergence, used in degree of divergence calculation (optional float)
regW : Weight of regular divergence, used in degree of divergence calculation (optional float)
Returns:
flag = true if divergence exists (bool)
degree = degree (strength) of divergence (float)
type = 1 = regular, 2 = hidden (int)
lx1 = x coordinate 1 (int)
ly1 = y coordinate 1 (float)
lx2 = x coordinate 2 (int)
ly2 = y coordinate 2 (float)
div_bear(pS, iS, cp_length_after, cp_length_before, pivot_length, lookback, no_broken, pW, iW, hidW, regW)
Test for bearish divergence
Parameters:
pS : Price series (float)
iS : Indicator series (float)
cp_length_after : Bars after current (divergent) pivot high to be considered a valid pivot (optional int)
cp_length_before : Bars before current (divergent) pivot highto be considered a valid pivot (optional int)
pivot_length : Bars before and after prior pivot high to be considered valid pivot (optional int)
lookback : Bars back to search for prior pivot high (optional int)
no_broken : Flag to only consider divergence valid if the pivot-to-pivot trendline is unbroken (optional bool)
pW : Weight of change in price, used in degree of divergence calculation (optional float)
iW : Weight of change in indicator, used in degree of divergence calculation (optional float)
hidW : Weight of hidden divergence, used in degree of divergence calculation (optional float)
regW : Weight of regular divergence, used in degree of divergence calculation (optional float)
Returns:
flag = true if divergence exists (bool)
degree = degree (strength) of divergence (float)
type = 1 = regular, 2 = hidden (int)
lx1 = x coordinate 1 (int)
ly1 = y coordinate 1 (float)
lx2 = x coordinate 2 (int)
ly2 = y coordinate 2 (float)
AlgebraLibrary "Algebra"
Algebra functions.
line_fromXy(x1, y1, x2, y2)
Get line slope and y-intercept from coordinates
Parameters:
x1 : x coordinate 1 (int - bar index)
y1 : y coordinate 1 (float - price/value)
x2 : x coordinate 2 (int - bar index)
y2 : y coordinate 2 (float - price/value)
Returns: of line
line_getPrice(x, slope, yInt)
Get line slope and y-intercept from coordinates
Parameters:
x : x coordinate to solve for y (int - bar index)
slope : slope of line (float)
yInt : y-intercept of line (float)
Returns: y (price/value)
ConsoleLibrary "Console"
█ OVERVIEW
An easy way to output messages to a console like table using a a simple "print" function that can be called from anywhere in your code including functions.
█ Supports:
- Scrollable console messages
- Customisable number of displayed messages
- More than one "console" for different types of output if required
- The ability to choose which message to start viewing from (useful if the message list is long)
- The ability to place the console table at different positions on the chart to mitigate against
overwriting an existing table.
█ Limitations:
The "scrollbar" handle is actually a modified time widget handle. As the handle is grabbed and moved left or right across the chart bars, this script calculates the offset of the bar being pointed to from the last bar in the chart and uses that as the console message offset. However, It isn't possible to position this on the last chart bar with code.
So there are two solutions:
1) Manually change timestamp of the variable scrollStart to the current time (roughly)
eg. scrollStart = "25 Dec 2022 14:30 +0000"
2) Use a higher timeframe (Weeks or Months) and visually find the scroll bar. If it is to the right of the chart bars the console output will read NaN. Grab the handle and move it left and it will snap to the last chart candle position. If it is to the left then find it and move it to the right as needed.
█ Notes On Usage
- Import the library as console (the call will be console.print(...) )
- Assign a console variable name and call the console.initialise function
eg. var con1=console.initialise()
- Use the console.print() function to print a message or messages
This takes two parameters:
_consoleName :this is the console name you are printing to
_message: this is the message that you want to display. It is a string and can be built in the normal way using any pinescript string functions like str.tostring() etc
- Use the console.display function to display the messages.
To work as intended this display function should be placed at the last line with the following code
if i_showMessages
....if i_displayTable == "con1"
........display(con1, i_lineOffset, i_rowsToDisplay, i_gotoMsg, posn)
(More "consoles" can be written to and the example code provided with the library shows this in more detail. Also, the indents don't show in these notes)
Lastly, placement of a console.print() without a qualifying "if" statement will occur for every bar. This may be desired. If not then use under an if statement (example in the supplied code).
Happy debugging :)
-----------------------------------------------------------------------------------------------------------
initialise()
initialise: creates the message array
Parameters:
none :
Returns: message array: this is assigned to the "console" identifier
print(_consoleName, _message)
used to output the desired text string to the console
Parameters:
_consoleName : : the message array
_message : : the console message
Returns: none
display(_consoleName, _lineOffset, _rowsToDisplay, _gotoMsg, _posn)
display: placed in the last section of code. Displays the console messages
Parameters:
_consoleName : : the message array
_lineOffset : : the setting of the scroll bar (time widget)
_rowsToDisplay : : how many rows to show in the console table
_gotoMsg : : which message to display from (default is 0)
_posn : : where the console table will be displayed
Returns: none
KlintLibraryLibrary "KlintLibrary"
GetDecimals()
this is my library, for my own use
thanks for reading
UtilitiesLibrary "Utilities"
General utilities
print_series(s, skip_na, position, show_index, from_index, to_index)
Print series values
Parameters:
s : Series (string)
skip_na : Flag to skip na values (optional bool, dft = false)
position : Position to print the Table (optional string, dft = position.bottom_center)
show_index : Flag to show series indices (optional bool, dft = true)
from_index : First index to print (optional int, dft = 0)
to_index : Last index to print (optional int, dft = last_bar_index)
Returns: Table object, if series was printed
print(v, position, at_index)
Print value
Parameters:
v : Value (string)
position : Position to print the Table (optional string, dft = position.bottom_center)
at_index : Index at which to print (optional int, dft = last_bar_index)
Returns: Table object, if value was printed
lower_tf█ OVERVIEW
This library is a Pine programmer’s tool containing functions to help those who use the request.security_lower_tf() function. Its `ltf()` function helps translate user inputs into a lower timeframe string usable with request.security_lower_tf() . Another function, `ltfStats()`, accumulates statistics on processed chart bars and intrabars.
█ CONCEPTS
Chart bars
Chart bars , as referred to in our publications, are bars that occur at the current chart timeframe, as opposed to those that occur at a timeframe that is higher or lower than that of the chart view.
Intrabars
Intrabars are chart bars at a lower timeframe than the chart's. Each 1H chart bar of a 24x7 market will, for example, usually contain 60 intrabars at the LTF of 1min, provided there was market activity during each minute of the hour. Mining information from intrabars can be useful in that it offers traders visibility on the activity inside a chart bar.
Lower timeframes (LTFs)
A lower timeframe is a timeframe that is smaller than the chart's timeframe. This framework exemplifies how authors can determine which LTF to use by examining the chart's timeframe. The LTF determines how many intrabars are examined for each chart bar; the lower the timeframe, the more intrabars are analyzed.
Intrabar precision
The precision of calculations increases with the number of intrabars analyzed for each chart bar. As there is a 100K limit to the number of intrabars that can be analyzed by a script, a trade-off occurs between the number of intrabars analyzed per chart bar and the chart bars for which calculations are possible.
█ `ltf()`
This function returns a timeframe string usable with request.security_lower_tf() . It calculates the returned timeframe by taking into account a user selection between eight different calculation modes and the chart's timeframe. You send it the user's selection, along with the text corresponding to the eight choices from which the user has chosen, and the function returns a corresponding LTF string.
Because the function processes strings and doesn't require recalculation on each bar, using var to declare the variable to which its result is assigned will execute the function only once on bar zero and speed up your script:
var string ltfString = ltf(ltfModeInput, LTF1, LTF2, LTF3, LTF4, LTF5, LTF6, LTF7, LTF8)
The eight choices users can select from are of two types: the first four allow a selection from the desired amount of chart bars to be covered, the last four are choices of a fixed number of intrabars to be analyzed per chart bar. Our example code shows how to structure your input call and then make the call to `ltf()`. By changing the text associated with the `LTF1` to `LTF8` constants, you can tailor it to your preferences while preserving the functionality of `ltf()` because you will be sending those string constants as the function's arguments so it can determine the user's selection. The association between each `LTFx` constant and its calculation mode is fixed, so the order of the arguments is important when you call `ltf()`.
These are the first four modes and the `LTFx` constants corresponding to each:
Covering most chart bars (least precise) — LTF1
Covers all chart bars. This is accomplished by dividing the current timeframe in seconds by 4 and converting that number back to a string in timeframe.period format using secondsToTfString() . Due to the fact that, on premium subscriptions, the typical historical bar count is between 20-25k bars, dividing the timeframe by 4 ensures the highest level of intrabar precision possible while achieving complete coverage for the entire dataset with the maximum allowed 100K intrabars.
Covering some chart bars (less precise) — LTF2
Covering less chart bars (more precise) — LTF3
These levels offer a stepped LTF in relation to the chart timeframe with slightly more, or slightly less precision. The stepped lower timeframe tiers are calculated from the chart timeframe as follows:
Chart Timeframe Lower Timeframe
Less Precise More Precise
< 1hr 1min 1min
< 1D 15min 1min
< 1W 2hr 30min
> 1W 1D 60min
Covering the least chart bars (most precise) — LTF4
Analyzes the maximum quantity of intrabars possible by using the 1min LTF, which also allows the least amount of chart bars to be covered.
The last four modes allow the user to specify a fixed number of intrabars to analyze per chart bar. Users can choose from 12, 24, 50 or 100 intrabars, respectively corresponding to the `LTF5`, `LTF6`, `LTF7` and `LTF8` constants. The value is a target; the function will do its best to come up with a LTF producing the required number of intrabars. Because of considerations such as the length of a ticker's session, rounding of the LTF to the closest allowable timeframe, or the lowest allowable timeframe of 1min intrabars, it is often impossible for the function to find a LTF producing the exact number of intrabars. Requesting 100 intrabars on a 60min chart, for example, can only produce 60 1min intrabars. Higher chart timeframes, tickers with high liquidity or 24x7 markets will produce optimal results.
█ `ltfStats()`
`ltfStats()` returns statistics that will be useful to programmers using intrabar inspection. By analyzing the arrays returned by request.security_lower_tf() in can determine:
• intrabarsInChartBar : The number of intrabars analyzed for each chart bar.
• chartBarsCovered : The number of chart bars where intrabar information is available.
• avgIntrabars : The average number of intrabars analyzed per chart bar. Events like holidays, market activity, or reduced hours sessions can cause the number of intrabars to vary, bar to bar.
The function must be called on each bar to produce reliable results.
█ DEMONSTRATION CODE
Our example code shows how to provide users with an input from which they can select a LTF calculation mode. If you use this library's functions, feel free to reuse our input setup code, including the tooltip providing users with explanations on how it works for them.
We make a simple call to request.security_lower_tf() to fetch the close values of intrabars, but we do not use those values. We simply send the returned array to `ltfStats()` and then plot in the indicator's pane the number of intrabars examined on each bar and its average. We also display an information box showing the user's selection of the LTF calculation mode, the resulting LTF calculated by `ltf()` and some statistics.
█ NOTES
• As in several of our recent publications, this script uses secondsToTfString() to produce a timeframe string in timeframe.period format from a timeframe expressed in seconds.
• The script utilizes display.data_window and display.status_line to restrict the display of certain plots.
These new built-ins allow coders to fine-tune where a script’s plot values are displayed.
• We implement a new recommended best practice for tables which works faster and reduces memory consumption.
Using this new method, tables are declared only once with var , as usual. Then, on bar zero only, we use table.cell() calls to populate the table.
Finally, table.set_*() functions are used to update attributes of table cells on the last bar of the dataset.
This greatly reduces the resources required to render tables. We encourage all Pine Script™ programmers to do the same.
Look first. Then leap.
█ FUNCTIONS
The library contains the following functions:
ltf(userSelection, choice1, choice2, choice3, choice4, choice5, choice6, choice7, choice8)
Selects a LTF from the chart's TF, depending on the `userSelection` input string.
Parameters:
userSelection : (simple string) User-selected input string which must be one of the `choicex` arguments.
choice1 : (simple string) Input selection corresponding to "Least precise, covering most chart bars".
choice2 : (simple string) Input selection corresponding to "Less precise, covering some chart bars".
choice3 : (simple string) Input selection corresponding to "More precise, covering less chart bars".
choice4 : (simple string) Input selection corresponding to "Most precise, 1min intrabars".
choice5 : (simple string) Input selection corresponding to "~12 intrabars per chart bar".
choice6 : (simple string) Input selection corresponding to "~24 intrabars per chart bar".
choice7 : (simple string) Input selection corresponding to "~50 intrabars per chart bar".
choice8 : (simple string) Input selection corresponding to "~100 intrabars per chart bar".
Returns: (simple string) A timeframe string to be used with `request.security_lower_tf()`.
ltfStats()
Returns statistics about analyzed intrabars and chart bars covered by calls to `request.security_lower_tf()`.
Parameters:
intrabarValues : (float [ ]) The ID of a float array containing values fetched by a call to `request.security_lower_tf()`.
Returns: A 3-element tuple: [ (series int) intrabarsInChartBar, (series int) chartBarsCovered, (series float) avgIntrabars ].
HSV and HSL gradient Tools ( Built-in Drop-in replacement )Library "hsvColor"
HSV and HSL Gradient Tool Alternatives and helpers. Demo'd is built-in in the middle with HSL/HSV gradients on top/bottom
TODO: Solve for #000000 issue
rgbhsv(_col)
RGB Color to HSV Values
Parameters:
_col : Color input (#abc012 or color.name or color.rgb(0,0,0,0))
Returns: values
rgbhsv(_r, _g, _b, _t)
RGB Color to HSV Values
Parameters:
_r : Red 0 - 255
_g : Green 0 - 255
_b : Blue 0 - 255
_t : Transp 0 - 100
Returns: values
hsv(_h, _s, _v, _a)
HSV colors, Auto fix if past boundaries
Parameters:
_h : Hue Input (-360 - 360) or further
_s : Saturation 0.- 1.
_v : Value 0.- 1.
_a : Alpha 0.- 1.
Returns: Color output
hue(_col)
returns 0-359 hue on color wheel
Parameters:
_col :
Returns: 360 degree hue value
hsv_gradient(signal, _startVal, _endVal, _startCol, _endCol)
Color Gradient Replacement Function for HSV calculated Gradents
Parameters:
signal : Control signal
_startVal : start color limit
_endVal : end color limit
_startCol : start color
_endCol : end color
Returns: HSV calculated gradient
hsl_gradient(signal, _startVal, _endVal, _startCol, _endCol)
Color Gradient Replacement Function for HSV calculated Gradents
Parameters:
signal : Control signal
_startVal : start color limit
_endVal : end color limit
_startCol : start color
_endCol : end color
Returns: HSV calculated gradient
Tosch Stacked EMAs (Fibonacci)Library "Tosch_Stacked_EMAs (Fibonacci)"
stacked()
Returns true if all EMAs are stacked, either way.
bullish()
Returns true if the EMAs are stacked bullish, false otherwise
emas()
Returns the EMA values for lengths 5, 8, 13, 21, 34, 55, 89
Tosch Market Sessions (US/GB/JP)Library "Tosch Market Sessions"
Returns if the NYSE, London SE, Tokyo SE are open
@function Returns if the NYSE (US), London SE (GB), Tokyo SE (JP) are open
@returns
bus, bgb, bjp - bool: true if the corresponding exchange is open
count - int: count of how many exchanges are open at the moment
ccolor - color: color that indicates the number of open exchanges
0 => color.black
1 => color.blue
2 => color.orange
3 => color.white
Chaikin Money Flow - LibraryLibrary "Chaikin Money Flow"
cmf()
Developed by Marc Chaikin, Chaikin Money Flow measures the amount of Money Flow Volume over a specific period.
Money Flow Volume forms the basis for the Accumulation Distribution Line. Instead of a cumulative total of
Money Flow Volume, Chaikin Money Flow simply sums Money Flow Volume for a specific look-back period, typically
20 or 21 days. The resulting indicator fluctuates above/below the zero line just like an oscillator. Chartists
weigh the balance of buying or selling pressure with the absolute level of Chaikin Money Flow. Chartists can
also look for crosses above or below the zero line to identify changes on money flow.
The Accumulation Distribution Line was developed by Marc Chaikin to measure the cumulative flow of money into and
out of an index or security. The Accumulation/Distribution Line can be compared to the OBV (On Balance Volume),
which adds or subtracts volume depending on the closing price. Marc Chaikin chose a different approach, instead
of relying on the closing price, he used CLV (Close Location Value).
testJust testing how to use libraries ignore this
Just testing how to use libraries ignore this
Just testing how to use libraries ignore this
Just testing how to use libraries ignore this
Just testing how to use libraries ignore this
Library: ArrayLibrary "xarray"
Additional functions for array.
remove_duplicates(array_in)
Remove duplicates in array.
Parameters:
array_in : (int /float /string ) Array contains duplicates.
Returns: Array without duplicates.
// Example: int
import tuele99/xarray/1 as xarray
c = xarray.remove_duplicates(array.from(1, 4, 2, 1, 2))
plot(array.size(c))
plot(array.get(c, 0))
plot(array.get(c, 1))
// Example: float
import tuele99/xarray/1 as xarray
c = xarray.remove_duplicates(array.from(1.0, 4.0, 2.0, 1.0, 2.0))
plot(array.size(c))
plot(array.get(c, 0))
plot(array.get(c, 1))
// Example: string
import tuele99/xarray/1 as xarray
c = xarray.remove_duplicates(array.from("green", "red", "green", "red", "green"))
plot(array.size(c)) // value = 2
label0 = label.new(x=last_bar_index, y=0, yloc=yloc.belowbar, text=array.get(c, 0), style=label.style_label_left, color=color.new(color.black, 100), textcolor=color.green) // below text = "green"
label1 = label.new(x=last_bar_index, y=0, yloc=yloc.abovebar, text=array.get(c, 1), style=label.style_label_left, color=color.new(color.black, 100), textcolor=color.red) // above text = "red"
Demand IndexLibrary "DemandIndex"
di()
The Demand Index is a complex technical indicator that uses price and volume to assess buying and selling pressure affecting a security.
James Sibbet established six rules for using Demand Index when the technical indicator was originally published. While traders may use variations of these rules, they serve as a great baseline for using the indicator in practice.
The six rules are as follows:
A divergence between the Demand Index and price is a bearish indication.
Prices often rally to new highs following an extreme peak in the Demand Index.
Higher prices with a low Demand Index often indicate a top in the market.
The Demand Index moving through the zero line suggests a change in trend.
The Demand Index remaining near the zero line indicates weak price movement that won’t last long.
A long-term divergence between the Demand Index and price predicts a major top or bottom.
Traders should use the Demand Index in conjunction with other technical indicators and chart patterns to maximize their odds of success.
myAutoviewAlertsLibrary "myAutoviewAlerts"
My Alerts Functions - To use with autoview
@returns - These functions returns a string to use in alerts to send commands to autoview. You can open an order, place a stop or take order, close an opened order or a opened position, or open a hedge position.
@param a = String - Account Identification
@param e = String - Exchange
@param s = String - Symbol
@param b = String - Book Side
@param q = Float - Quantity
@param fp = Float - Fixed Price
@param delay = Integer - In Seconds
@param i = Integer - Account Index (to multiple accounts allerts)
@param base = String - Base Currency (bitmex) - "Tether" or "Bitcoin"
@param fsl = Float - Stop Loss Limit Price
@param c = String - Close -> "order" or "position"
@param ro = Bool - Reduce Only
@param sl = Bool - Stop Loss -> bitfinex
@param t = String - Type -> "market" or "limit"
@function f_order => Open Orders
@function f_stop => Set Stop Loss Order
@function f_take => Set Take Order
@function f_closeOrder => Close Open Orders
@function f_closePosition => Close Open Positions
@function f_hedge => To Open a Hedge Position (short 100% of balance)
AllTimeHighLowLibrary "AllTimeHighLow"
Provides functions calculating the all-time high/low of values.
hi(val)
Calculates the all-time high of a series.
Parameters:
val : Series to use (`high` is used if no argument is supplied).
Returns: The all-time high for the series.
lo(val)
Calculates the all-time low of a series.
Parameters:
val : Series to use (`low` is used if no argument is supplied).
Returns: The all-time low for the series.
L_BetaLibrary "L_Beta"
TODO: add library description here
length()
beta()
simple_beta()
index_selector()
L_Index_4khansoloLibrary "L_Index_4khansolo"
countrySelect()
colorPositron()
indexName()
indexRSI()
maRSI()
colorRSIfull()
rsiColor()
rsiFillColor()
rsiCompartments()
fiatIndexer()
colorMACD()
indexMACD()
colour()
CalulateWinLossLibrary "CalulateWinLoss"
TODO: add library description here
colorwhitered(x)
TODO: add function description here
Parameters:
x : TODO: add parameter x description here
Returns: TODO: add what function returns
colorredwhite()
cal()
myAlertsLibrary "myAlerts"
My Alerts Functions - To use with autoview
f_order(_price, _qty, _position, _account, _exchange, _i, i_qtyTypeOrder, typeMsg, syminfoticker)
- Write the entry order message
Parameters:
_price : - The order price
_qty : - The order quantity
_position : - The order side
_account : - The user account
_exchange : - The user exchange
_i : - Used for multi-accounts, this represents the index of accounts
i_qtyTypeOrder : - String used to set Thether or Bitcoin Type Orders
typeMsg : - True = Autoview; False = Metatrader
syminfoticker : - Ticker
Returns: - Returns the open order message
f_stop(_stop_price, _slLimit_price, _account, _exchange, _i, i_delayOrders, typeMsg, syminfoticker)
- Write the stop order message
Parameters:
_stop_price : - The order stop price
_slLimit_price : - The order stop limit price
_account : - The user account
_exchange : - The user exchange
_i : - Used for multi-accounts, this represents the index of accounts
i_delayOrders : - Time in seconds to delay command on autoview
typeMsg : - True = Autoview; False = Metatrader
syminfoticker : - Ticker
Returns: - Returns the open order message
f_take(_take_price, _account, _exchange, _i, i_delayOrders, typeMsg, syminfoticker)
- Write the stop order message
Parameters:
_take_price : - The order stop price
_account : - The user account
_exchange : - The user exchange
_i : - Used for multi-accounts, this represents the index of accounts
i_delayOrders : - Time in seconds to delay command on autoview
typeMsg : - True = Autoview; False = Metatrader
syminfoticker : - Ticker
Returns: - Returns the open order message
f_update(_account, _exchange, _i, i_delayOrders, typeMsg, syminfoticker)
- Write the update order message
Parameters:
_account : - The user account
_exchange : - The user exchange
_i : - Used for multi-accounts, this represents the index of accounts
i_delayOrders : - Time in seconds to delay command on autoview
typeMsg : - True = Autoview; False = Metatrader
syminfoticker : - Ticker
Returns: - Returns the open order message
f_exit(_account, _exchange, _i, i_delayOrders, typeMsg, syminfoticker)
- Write the exit order message
Parameters:
_account : - The user account
_exchange : - The user exchange
_i : - Used for multi-accounts, this represents the index of accounts
i_delayOrders : - Time in seconds to delay command on autoview
typeMsg : - True = Autoview; False = Metatrader
syminfoticker : - Ticker
Returns: - Returns the open order message
f_hedge(_account, _exchange, _i, i_delayOrders, typeMsg, syminfoticker)
- Write the exit order message
Parameters:
_account : - The user account
_exchange : - The user exchange
_i : - Used for multi-accounts, this represents the index of accounts
i_delayOrders : - Time in seconds to delay command on autoview
typeMsg : - True = Autoview; False = Metatrader
syminfoticker : - Ticker
Returns: - Returns the open order message
FunctionLAPACKdsyrkLibrary "FunctionLAPACKdsyrk"
subroutine part of LAPACK: Linear Algebra Package,
performs one of the symmetric rank k operations
.
C := alpha*A*A**T + beta*C, or C := alpha*A**T*A + beta*C,
.
where alpha and beta are scalars, C is an n by n symmetric matrix
and A is an n by k matrix in the first case and a k by n matrix
in the second case.
.
reference:
netlib.org
dsyrk(uplo, trans, n, k, alpha, a, lda, beta, c, ldc)
performs one of the symmetric rank k operations
.
C := alpha*A*A**T + beta*C, or C := alpha*A**T*A + beta*C,
.
where alpha and beta are scalars, C is an n by n symmetric matrix
and A is an n by k matrix in the first case and a k by n matrix
in the second case.
.
Parameters:
uplo : string specifies whether the upper or lower triangular part of
the array C is to be referenced as follows:
UPLO = 'U' or 'u' Only the upper triangular part of C is to be referenced.
UPLO = 'L' or 'l' Only the lower triangular part of C is to be referenced.
.
trans : string specifies the operation to be performed as follows:
TRANS = 'N' or 'n' C := alpha*A*A**T + beta*C.
TRANS = 'T' or 't' C := alpha*A**T*A + beta*C.
TRANS = 'C' or 'c' C := alpha*A**T*A + beta*C.
.
n : int specifies the order of the matrix C. N must be at least zero.
k : int On entry with:
TRANS = 'N' or 'n', K specifies the number of columns of the matrix A.
TRANS = 'T' or 't' or 'C' or 'c', K specifies the number of rows of the matrix A.
K must be at least zero.
.
alpha : float scalar.
a : matrix matrix A.
lda : int specifies the first dimension of A.
beta : float scalar.
c : matrix matrix C, is overwritten by the lower triangular part of the updated matrix.
ldc : int specifies the first dimension of C
Returns: void, C is overwritten by the lower triangular part of the updated matrix.
FunctionLAPACKdtrsmLibrary "FunctionLAPACKdtrsm"
subroutine in the LAPACK:linear algebra package, used to solve one of the following matrix equations:
op( A )*X = alpha*B, or X*op( A ) = alpha*B,
where alpha is a scalar, X and B are m by n matrices, A is a unit, or
non-unit, upper or lower triangular matrix and op( A ) is one of
op( A ) = A or op( A ) = A**T.
The matrix X is overwritten on B.
reference:
netlib.org
dtrsm(side, uplo, transa, diag, m, n, alpha, a, lda, b, ldb)
solves one of the matrix equations
op( A )*X = alpha*B, or X*op( A ) = alpha*B,
where alpha is a scalar, X and B are m by n matrices, A is a unit, or
non-unit, upper or lower triangular matrix and op( A ) is one of
op( A ) = A or op( A ) = A**T.
The matrix X is overwritten on B.
Parameters:
side : string , On entry, SIDE specifies whether op( A ) appears on the left or right of X as follows:
SIDE = 'L' or 'l' op( A )*X = alpha*B.
SIDE = 'R' or 'r' X*op( A ) = alpha*B.
uplo : string , specifies whether the matrix A is an upper or lower triangular matrix as follows:
UPLO = 'U' or 'u' A is an upper triangular matrix.
UPLO = 'L' or 'l' A is a lower triangular matrix.
transa : string , specifies the form of op( A ) to be used in the matrix multiplication as follows:
TRANSA = 'N' or 'n' op( A ) = A.
TRANSA = 'T' or 't' op( A ) = A**T.
TRANSA = 'C' or 'c' op( A ) = A**T.
diag : string , specifies whether or not A is unit triangular as follows:
DIAG = 'U' or 'u' A is assumed to be unit triangular.
DIAG = 'N' or 'n' A is not assumed to be unit triangular.
m : int , the number of rows of B. M must be at least zero.
n : int , the number of columns of B. N must be at least zero.
alpha : float , specifies the scalar alpha. When alpha is zero then A is not referenced and B need not be set before entry.
a : matrix, Triangular matrix.
lda : int , specifies the first dimension of A.
b : matrix, right-hand side matrix B, and on exit is overwritten by the solution matrix X.
ldb : int , specifies the first dimension of B.
Returns: void, modifies matrix b.
usage:
dtrsm ('L', 'U', 'N', 'N', 5, 3, 1.0, a, 7, b, 6)