chartpatternsLibrary "chartpatterns"
Library having complete chart pattern implementation
method draw(this)
draws pattern on the chart
Namespace types: Pattern
Parameters:
this (Pattern) : Pattern object that needs to be drawn
Returns: Current Pattern object
method erase(this)
erase the given pattern on the chart
Namespace types: Pattern
Parameters:
this (Pattern) : Pattern object that needs to be erased
Returns: Current Pattern object
method findPattern(this, properties, patterns)
Find patterns based on the currect zigzag object and store them in the patterns array
Namespace types: zg.Zigzag
Parameters:
this (Zigzag type from Trendoscope/ZigzagLite/2) : Zigzag object containing pivots
properties (PatternProperties) : PatternProperties object
patterns (Pattern ) : Array of Pattern objects
Returns: Current Pattern object
PatternProperties
Object containing properties for pattern scanning
Fields:
offset (series int) : Zigzag pivot offset. Set it to 1 for non repainting scan.
numberOfPivots (series int) : Number of pivots to be used in pattern search. Can be either 5 or 6
errorRatio (series float) : Error Threshold to be considered for comparing the slope of lines
flatRatio (series float) : Retracement ratio threshold used to determine if the lines are flat
checkBarRatio (series bool) : Also check bar ratio are within the limits while scanning the patterns
barRatioLimit (series float) : Bar ratio limit used for checking the bars. Used only when checkBarRatio is set to true
avoidOverlap (series bool)
patternLineWidth (series int) : Line width of the pattern trend lines
showZigzag (series bool) : show zigzag associated with pattern
zigzagLineWidth (series int) : line width of the zigzag lines. Used only when showZigzag is set to true
zigzagLineColor (series color) : color of the zigzag lines. Used only when showZigzag is set to true
showPatternLabel (series bool) : display pattern label containing the name
patternLabelSize (series string) : size of the pattern label. Used only when showPatternLabel is set to true
showPivotLabels (series bool) : Display pivot labels of the patterns marking 1-6
pivotLabelSize (series string) : size of the pivot label. Used only when showPivotLabels is set to true
pivotLabelColor (series color) : color of the pivot label outline. chart.bg_color or chart.fg_color are the appropriate values.
allowedPatterns (bool ) : array of bool encoding the allowed pattern types.
themeColors (color ) : color array of themes to be used.
Pattern
Object containing Individual Pattern data
Fields:
pivots (Pivot type from Trendoscope/ZigzagLite/2) : array of Zigzag Pivot points
trendLine1 (Line type from Trendoscope/LineWrapper/1) : First trend line joining pivots 1, 3, 5
trendLine2 (Line type from Trendoscope/LineWrapper/1) : Second trend line joining pivots 2, 4 (, 6)
properties (PatternProperties) : PatternProperties Object carrying common properties
patternColor (series color) : Individual pattern color. Lines and labels will be using this color.
ratioDiff (series float) : Difference between trendLine1 and trendLine2 ratios
zigzagLine (series polyline) : Internal zigzag line drawing Object
pivotLabels (label ) : array containning Pivot labels
patternLabel (series label) : pattern label Object
patternType (series int) : integer representing the pattern type
patternName (series string) : Type of pattern in string
Arrays
LineWrapperLibrary "LineWrapper"
Wrapper Type for Line. Useful when you want to store the line details without drawing them. Can also be used in scnearios where you collect lines to be drawn and draw together towards the end.
method draw(this)
draws line as per the wrapper object contents
Namespace types: Line
Parameters:
this (Line) : (series Line) Line object.
Returns: current Line object
method draw(this)
draws lines as per the wrapper object array
Namespace types: Line
Parameters:
this (Line ) : (series array) Array of Line object.
Returns: current Array of Line objects
method update(this)
updates or redraws line as per the wrapper object contents
Namespace types: Line
Parameters:
this (Line) : (series Line) Line object.
Returns: current Line object
method update(this)
updates or redraws lines as per the wrapper object array
Namespace types: Line
Parameters:
this (Line ) : (series array) Array of Line object.
Returns: current Array of Line objects
method delete(this)
Deletes the underlying line drawing object
Namespace types: Line
Parameters:
this (Line) : (series Line) Line object.
Returns: Current Line object
method get_price(this, bar)
get line price based on bar
Namespace types: Line
Parameters:
this (Line) : (series Line) Line object.
bar (int) : (series/int) bar at which line price need to be calculated
Returns: line price at given bar.
Line
Line Wrapper object
Fields:
p1 (chart.point)
p2 (chart.point)
xloc (series string) : (series string) See description of x1 argument. Possible values: xloc.bar_index and xloc.bar_time. Default is xloc.bar_index.
extend (series string) : (series string) If extend=extend.none, draws segment starting at point (x1, y1) and ending at point (x2, y2). If extend is equal to extend.right or extend.left, draws a ray starting at point (x1, y1) or (x2, y2), respectively. If extend=extend.both, draws a straight line that goes through these points. Default value is extend.none.
color (series color) : (series color) Line color.
style (series string) : (series string) Line style. Possible values: line.style_solid, line.style_dotted, line.style_dashed, line.style_arrow_left, line.style_arrow_right, line.style_arrow_both.
width (series int) : (series int) Line width in pixels.
obj (series line) : line object
ZigzagLiteLibrary "ZigzagLite"
Lighter version of the Zigzag Library. Without indicators and sub-component divisions
method getPrices(pivots)
Gets the array of prices from array of Pivots
Namespace types: Pivot
Parameters:
pivots (Pivot ) : array array of Pivot objects
Returns: array array of pivot prices
method getBars(pivots)
Gets the array of bars from array of Pivots
Namespace types: Pivot
Parameters:
pivots (Pivot ) : array array of Pivot objects
Returns: array array of pivot bar indices
method getPoints(pivots)
Gets the array of chart.point from array of Pivots
Namespace types: Pivot
Parameters:
pivots (Pivot ) : array array of Pivot objects
Returns: array array of pivot points
method getPoints(this)
Namespace types: Zigzag
Parameters:
this (Zigzag)
method calculate(this, ohlc, ltfHighTime, ltfLowTime)
Calculate zigzag based on input values and indicator values
Namespace types: Zigzag
Parameters:
this (Zigzag) : Zigzag object
ohlc (float ) : Array containing OHLC values. Can also have custom values for which zigzag to be calculated
ltfHighTime (int) : Used for multi timeframe zigzags when called within request.security. Default value is current timeframe open time.
ltfLowTime (int) : Used for multi timeframe zigzags when called within request.security. Default value is current timeframe open time.
Returns: current Zigzag object
method calculate(this)
Calculate zigzag based on properties embedded within Zigzag object
Namespace types: Zigzag
Parameters:
this (Zigzag) : Zigzag object
Returns: current Zigzag object
method nextlevel(this)
Namespace types: Zigzag
Parameters:
this (Zigzag)
method clear(this)
Clears zigzag drawings array
Namespace types: ZigzagDrawing
Parameters:
this (ZigzagDrawing ) : array
Returns: void
method clear(this)
Clears zigzag drawings array
Namespace types: ZigzagDrawingPL
Parameters:
this (ZigzagDrawingPL ) : array
Returns: void
method drawplain(this)
draws fresh zigzag based on properties embedded in ZigzagDrawing object without trying to calculate
Namespace types: ZigzagDrawing
Parameters:
this (ZigzagDrawing) : ZigzagDrawing object
Returns: ZigzagDrawing object
method drawplain(this)
draws fresh zigzag based on properties embedded in ZigzagDrawingPL object without trying to calculate
Namespace types: ZigzagDrawingPL
Parameters:
this (ZigzagDrawingPL) : ZigzagDrawingPL object
Returns: ZigzagDrawingPL object
method drawfresh(this, ohlc)
draws fresh zigzag based on properties embedded in ZigzagDrawing object
Namespace types: ZigzagDrawing
Parameters:
this (ZigzagDrawing) : ZigzagDrawing object
ohlc (float ) : values on which the zigzag needs to be calculated and drawn. If not set will use regular OHLC
Returns: ZigzagDrawing object
method drawcontinuous(this, ohlc)
draws zigzag based on the zigzagmatrix input
Namespace types: ZigzagDrawing
Parameters:
this (ZigzagDrawing) : ZigzagDrawing object
ohlc (float ) : values on which the zigzag needs to be calculated and drawn. If not set will use regular OHLC
Returns:
PivotCandle
PivotCandle represents data of the candle which forms either pivot High or pivot low or both
Fields:
_high (series float) : High price of candle forming the pivot
_low (series float) : Low price of candle forming the pivot
length (series int) : Pivot length
pHighBar (series int) : represents number of bar back the pivot High occurred.
pLowBar (series int) : represents number of bar back the pivot Low occurred.
pHigh (series float) : Pivot High Price
pLow (series float) : Pivot Low Price
Pivot
Pivot refers to zigzag pivot. Each pivot can contain various data
Fields:
point (chart.point) : pivot point coordinates
dir (series int) : direction of the pivot. Valid values are 1, -1, 2, -2
level (series int) : is used for multi level zigzags. For single level, it will always be 0
ratio (series float) : Price Ratio based on previous two pivots
sizeRatio (series float)
ZigzagFlags
Flags required for drawing zigzag. Only used internally in zigzag calculation. Should not set the values explicitly
Fields:
newPivot (series bool) : true if the calculation resulted in new pivot
doublePivot (series bool) : true if the calculation resulted in two pivots on same bar
updateLastPivot (series bool) : true if new pivot calculated replaces the old one.
Zigzag
Zigzag object which contains whole zigzag calculation parameters and pivots
Fields:
length (series int) : Zigzag length. Default value is 5
numberOfPivots (series int) : max number of pivots to hold in the calculation. Default value is 20
offset (series int) : Bar offset to be considered for calculation of zigzag. Default is 0 - which means calculation is done based on the latest bar.
level (series int) : Zigzag calculation level - used in multi level recursive zigzags
zigzagPivots (Pivot ) : array which holds the last n pivots calculated.
flags (ZigzagFlags) : ZigzagFlags object which is required for continuous drawing of zigzag lines.
ZigzagObject
Zigzag Drawing Object
Fields:
zigzagLine (series line) : Line joining two pivots
zigzagLabel (series label) : Label which can be used for drawing the values, ratios, directions etc.
ZigzagProperties
Object which holds properties of zigzag drawing. To be used along with ZigzagDrawing
Fields:
lineColor (series color) : Zigzag line color. Default is color.blue
lineWidth (series int) : Zigzag line width. Default is 1
lineStyle (series string) : Zigzag line style. Default is line.style_solid.
showLabel (series bool) : If set, the drawing will show labels on each pivot. Default is false
textColor (series color) : Text color of the labels. Only applicable if showLabel is set to true.
maxObjects (series int) : Max number of zigzag lines to display. Default is 300
xloc (series string) : Time/Bar reference to be used for zigzag drawing. Default is Time - xloc.bar_time.
curved (series bool) : Boolean field to print curved zigzag - used only with polyline implementation
ZigzagDrawing
Object which holds complete zigzag drawing objects and properties.
Fields:
zigzag (Zigzag) : Zigzag object which holds the calculations.
properties (ZigzagProperties) : ZigzagProperties object which is used for setting the display styles of zigzag
drawings (ZigzagObject ) : array which contains lines and labels of zigzag drawing.
ZigzagDrawingPL
Object which holds complete zigzag drawing objects and properties - polyline version
Fields:
zigzag (Zigzag) : Zigzag object which holds the calculations.
properties (ZigzagProperties) : ZigzagProperties object which is used for setting the display styles of zigzag
zigzagLabels (label )
zigzagLine (series polyline) : polyline object of zigzag lines
arraysLibrary "arraymethods"
Supplementary array methods.
delete(arr, index)
remove int object from array of integers at specific index
Parameters:
arr : int array
index : index at which int object need to be removed
Returns: void
delete(arr, index)
remove float object from array of float at specific index
Parameters:
arr : float array
index : index at which float object need to be removed
Returns: float
delete(arr, index)
remove bool object from array of bool at specific index
Parameters:
arr : bool array
index : index at which bool object need to be removed
Returns: bool
delete(arr, index)
remove string object from array of string at specific index
Parameters:
arr : string array
index : index at which string object need to be removed
Returns: string
delete(arr, index)
remove color object from array of color at specific index
Parameters:
arr : color array
index : index at which color object need to be removed
Returns: color
delete(arr, index)
remove line object from array of lines at specific index and deletes the line
Parameters:
arr : line array
index : index at which line object need to be removed and deleted
Returns: void
delete(arr, index)
remove label object from array of labels at specific index and deletes the label
Parameters:
arr : label array
index : index at which label object need to be removed and deleted
Returns: void
delete(arr, index)
remove box object from array of boxes at specific index and deletes the box
Parameters:
arr : box array
index : index at which box object need to be removed and deleted
Returns: void
delete(arr, index)
remove table object from array of tables at specific index and deletes the table
Parameters:
arr : table array
index : index at which table object need to be removed and deleted
Returns: void
delete(arr, index)
remove linefill object from array of linefills at specific index and deletes the linefill
Parameters:
arr : linefill array
index : index at which linefill object need to be removed and deleted
Returns: void
popr(arr)
remove last int object from array
Parameters:
arr : int array
Returns: int
popr(arr)
remove last float object from array
Parameters:
arr : float array
Returns: float
popr(arr)
remove last bool object from array
Parameters:
arr : bool array
Returns: bool
popr(arr)
remove last string object from array
Parameters:
arr : string array
Returns: string
popr(arr)
remove last color object from array
Parameters:
arr : color array
Returns: color
popr(arr)
remove and delete last line object from array
Parameters:
arr : line array
Returns: void
popr(arr)
remove and delete last label object from array
Parameters:
arr : label array
Returns: void
popr(arr)
remove and delete last box object from array
Parameters:
arr : box array
Returns: void
popr(arr)
remove and delete last table object from array
Parameters:
arr : table array
Returns: void
popr(arr)
remove and delete last linefill object from array
Parameters:
arr : linefill array
Returns: void
shiftr(arr)
remove first int object from array
Parameters:
arr : int array
Returns: int
shiftr(arr)
remove first float object from array
Parameters:
arr : float array
Returns: float
shiftr(arr)
remove first bool object from array
Parameters:
arr : bool array
Returns: bool
shiftr(arr)
remove first string object from array
Parameters:
arr : string array
Returns: string
shiftr(arr)
remove first color object from array
Parameters:
arr : color array
Returns: color
shiftr(arr)
remove and delete first line object from array
Parameters:
arr : line array
Returns: void
shiftr(arr)
remove and delete first label object from array
Parameters:
arr : label array
Returns: void
shiftr(arr)
remove and delete first box object from array
Parameters:
arr : box array
Returns: void
shiftr(arr)
remove and delete first table object from array
Parameters:
arr : table array
Returns: void
shiftr(arr)
remove and delete first linefill object from array
Parameters:
arr : linefill array
Returns: void
push(arr, val, maxItems)
add int to the end of an array with max items cap. Objects are removed from start to maintain max items cap
Parameters:
arr : int array
val : int object to be pushed
maxItems : max number of items array can hold
Returns: int
push(arr, val, maxItems)
add float to the end of an array with max items cap. Objects are removed from start to maintain max items cap
Parameters:
arr : float array
val : float object to be pushed
maxItems : max number of items array can hold
Returns: float
push(arr, val, maxItems)
add bool to the end of an array with max items cap. Objects are removed from start to maintain max items cap
Parameters:
arr : bool array
val : bool object to be pushed
maxItems : max number of items array can hold
Returns: bool
push(arr, val, maxItems)
add string to the end of an array with max items cap. Objects are removed from start to maintain max items cap
Parameters:
arr : string array
val : string object to be pushed
maxItems : max number of items array can hold
Returns: string
push(arr, val, maxItems)
add color to the end of an array with max items cap. Objects are removed from start to maintain max items cap
Parameters:
arr : color array
val : color object to be pushed
maxItems : max number of items array can hold
Returns: color
push(arr, val, maxItems)
add line to the end of an array with max items cap. Objects are removed and deleted from start to maintain max items cap
Parameters:
arr : line array
val : line object to be pushed
maxItems : max number of items array can hold
Returns: line
push(arr, val, maxItems)
add label to the end of an array with max items cap. Objects are removed and deleted from start to maintain max items cap
Parameters:
arr : label array
val : label object to be pushed
maxItems : max number of items array can hold
Returns: label
push(arr, val, maxItems)
add box to the end of an array with max items cap. Objects are removed and deleted from start to maintain max items cap
Parameters:
arr : box array
val : box object to be pushed
maxItems : max number of items array can hold
Returns: box
push(arr, val, maxItems)
add table to the end of an array with max items cap. Objects are removed and deleted from start to maintain max items cap
Parameters:
arr : table array
val : table object to be pushed
maxItems : max number of items array can hold
Returns: table
push(arr, val, maxItems)
add linefill to the end of an array with max items cap. Objects are removed and deleted from start to maintain max items cap
Parameters:
arr : linefill array
val : linefill object to be pushed
maxItems : max number of items array can hold
Returns: linefill
unshift(arr, val, maxItems)
add int to the beginning of an array with max items cap. Objects are removed from end to maintain max items cap
Parameters:
arr : int array
val : int object to be unshift
maxItems : max number of items array can hold
Returns: int
unshift(arr, val, maxItems)
add float to the beginning of an array with max items cap. Objects are removed from end to maintain max items cap
Parameters:
arr : float array
val : float object to be unshift
maxItems : max number of items array can hold
Returns: float
unshift(arr, val, maxItems)
add bool to the beginning of an array with max items cap. Objects are removed from end to maintain max items cap
Parameters:
arr : bool array
val : bool object to be unshift
maxItems : max number of items array can hold
Returns: bool
unshift(arr, val, maxItems)
add string to the beginning of an array with max items cap. Objects are removed from end to maintain max items cap
Parameters:
arr : string array
val : string object to be unshift
maxItems : max number of items array can hold
Returns: string
unshift(arr, val, maxItems)
add color to the beginning of an array with max items cap. Objects are removed from end to maintain max items cap
Parameters:
arr : color array
val : color object to be unshift
maxItems : max number of items array can hold
Returns: color
unshift(arr, val, maxItems)
add line to the beginning of an array with max items cap. Objects are removed and deleted from end to maintain max items cap
Parameters:
arr : line array
val : line object to be unshift
maxItems : max number of items array can hold
Returns: line
unshift(arr, val, maxItems)
add label to the beginning of an array with max items cap. Objects are removed and deleted from end to maintain max items cap
Parameters:
arr : label array
val : label object to be unshift
maxItems : max number of items array can hold
Returns: label
unshift(arr, val, maxItems)
add box to the beginning of an array with max items cap. Objects are removed and deleted from end to maintain max items cap
Parameters:
arr : box array
val : box object to be unshift
maxItems : max number of items array can hold
Returns: box
unshift(arr, val, maxItems)
add table to the beginning of an array with max items cap. Objects are removed and deleted from end to maintain max items cap
Parameters:
arr : table array
val : table object to be unshift
maxItems : max number of items array can hold
Returns: table
unshift(arr, val, maxItems)
add linefill to the beginning of an array with max items cap. Objects are removed and deleted from end to maintain max items cap
Parameters:
arr : linefill array
val : linefill object to be unshift
maxItems : max number of items array can hold
Returns: linefill
flush(arr)
remove all int objects in an array
Parameters:
arr : int array
Returns: int
flush(arr)
remove all float objects in an array
Parameters:
arr : float array
Returns: float
flush(arr)
remove all bool objects in an array
Parameters:
arr : bool array
Returns: bool
flush(arr)
remove all string objects in an array
Parameters:
arr : string array
Returns: string
flush(arr)
remove all color objects in an array
Parameters:
arr : color array
Returns: color
flush(arr)
remove and delete all line objects in an array
Parameters:
arr : line array
Returns: line
flush(arr)
remove and delete all label objects in an array
Parameters:
arr : label array
Returns: label
flush(arr)
remove and delete all box objects in an array
Parameters:
arr : box array
Returns: box
flush(arr)
remove and delete all table objects in an array
Parameters:
arr : table array
Returns: table
flush(arr)
remove and delete all linefill objects in an array
Parameters:
arr : linefill array
Returns: linefill
ZigzagLibrary "Zigzag"
Zigzag related user defined types. Depends on DrawingTypes library for basic types
method tostring(this, sortKeys, sortOrder, includeKeys)
Converts ZigzagTypes/Pivot object to string representation
Namespace types: Pivot
Parameters:
this (Pivot) : ZigzagTypes/Pivot
sortKeys (bool) : If set to true, string output is sorted by keys.
sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys (string ) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of ZigzagTypes/Pivot
method tostring(this, sortKeys, sortOrder, includeKeys)
Converts Array of Pivot objects to string representation
Namespace types: Pivot
Parameters:
this (Pivot ) : Pivot object array
sortKeys (bool) : If set to true, string output is sorted by keys.
sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys (string ) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of Pivot object array
method tostring(this)
Converts ZigzagFlags object to string representation
Namespace types: ZigzagFlags
Parameters:
this (ZigzagFlags) : ZigzagFlags object
Returns: string representation of ZigzagFlags
method tostring(this, sortKeys, sortOrder, includeKeys)
Converts ZigzagTypes/Zigzag object to string representation
Namespace types: Zigzag
Parameters:
this (Zigzag) : ZigzagTypes/Zigzagobject
sortKeys (bool) : If set to true, string output is sorted by keys.
sortOrder (int) : Applicable only if sortKeys is set to true. Positive number will sort them in ascending order whreas negative numer will sort them in descending order. Passing 0 will not sort the keys
includeKeys (string ) : Array of string containing selective keys. Optional parmaeter. If not provided, all the keys are considered
Returns: string representation of ZigzagTypes/Zigzag
method calculate(this, ohlc, indicators, indicatorNames)
Calculate zigzag based on input values and indicator values
Namespace types: Zigzag
Parameters:
this (Zigzag) : Zigzag object
ohlc (float ) : Array containing OHLC values. Can also have custom values for which zigzag to be calculated
indicators (matrix) : Array of indicator values
indicatorNames (string ) : Array of indicator names for which values are present. Size of indicators array should be equal to that of indicatorNames
Returns: current Zigzag object
method calculate(this)
Calculate zigzag based on properties embedded within Zigzag object
Namespace types: Zigzag
Parameters:
this (Zigzag) : Zigzag object
Returns: current Zigzag object
method nextlevel(this)
Calculate Next Level Zigzag based on the current calculated zigzag object
Namespace types: Zigzag
Parameters:
this (Zigzag) : Zigzag object
Returns: Next Level Zigzag object
method clear(this)
Clears zigzag drawings array
Namespace types: ZigzagDrawing
Parameters:
this (ZigzagDrawing ) : array
Returns: void
method drawplain(this)
draws fresh zigzag based on properties embedded in ZigzagDrawing object without trying to calculate
Namespace types: ZigzagDrawing
Parameters:
this (ZigzagDrawing) : ZigzagDrawing object
Returns: ZigzagDrawing object
method drawfresh(this, ohlc, indicators, indicatorNames)
draws fresh zigzag based on properties embedded in ZigzagDrawing object
Namespace types: ZigzagDrawing
Parameters:
this (ZigzagDrawing) : ZigzagDrawing object
ohlc (float ) : values on which the zigzag needs to be calculated and drawn. If not set will use regular OHLC
indicators (matrix) : Array of indicator values
indicatorNames (string ) : Array of indicator names for which values are present. Size of indicators array should be equal to that of indicatorNames
Returns: ZigzagDrawing object
method drawcontinuous(this, ohlc, indicators, indicatorNames)
draws zigzag based on the zigzagmatrix input
Namespace types: ZigzagDrawing
Parameters:
this (ZigzagDrawing) : ZigzagDrawing object
ohlc (float ) : values on which the zigzag needs to be calculated and drawn. If not set will use regular OHLC
indicators (matrix) : Array of indicator values
indicatorNames (string ) : Array of indicator names for which values are present. Size of indicators array should be equal to that of indicatorNames
Returns:
method getPrices(pivots)
Namespace types: Pivot
Parameters:
pivots (Pivot )
method getBars(pivots)
Namespace types: Pivot
Parameters:
pivots (Pivot )
Indicator
Indicator is collection of indicator values applied on high, low and close
Fields:
indicatorHigh (series float) : Indicator Value applied on High
indicatorLow (series float) : Indicator Value applied on Low
PivotCandle
PivotCandle represents data of the candle which forms either pivot High or pivot low or both
Fields:
_high (series float) : High price of candle forming the pivot
_low (series float) : Low price of candle forming the pivot
length (series int) : Pivot length
pHighBar (series int) : represents number of bar back the pivot High occurred.
pLowBar (series int) : represents number of bar back the pivot Low occurred.
pHigh (series float) : Pivot High Price
pLow (series float) : Pivot Low Price
indicators (Indicator ) : Array of Indicators - allows to add multiple
Pivot
Pivot refers to zigzag pivot. Each pivot can contain various data
Fields:
point (chart.point) : pivot point coordinates
dir (series int) : direction of the pivot. Valid values are 1, -1, 2, -2
level (series int) : is used for multi level zigzags. For single level, it will always be 0
componentIndex (series int) : is the lower level zigzag array index for given pivot. Used only in multi level Zigzag Pivots
subComponents (series int) : is the number of sub waves per each zigzag wave. Only applicable for multi level zigzags
microComponents (series int) : is the number of base zigzag components in a zigzag wave
ratio (series float) : Price Ratio based on previous two pivots
sizeRatio (series float)
subPivots (Pivot )
indicatorNames (string ) : Names of the indicators applied on zigzag
indicatorValues (float ) : Values of the indicators applied on zigzag
indicatorRatios (float ) : Ratios of the indicators applied on zigzag based on previous 2 pivots
ZigzagFlags
Flags required for drawing zigzag. Only used internally in zigzag calculation. Should not set the values explicitly
Fields:
newPivot (series bool) : true if the calculation resulted in new pivot
doublePivot (series bool) : true if the calculation resulted in two pivots on same bar
updateLastPivot (series bool) : true if new pivot calculated replaces the old one.
Zigzag
Zigzag object which contains whole zigzag calculation parameters and pivots
Fields:
length (series int) : Zigzag length. Default value is 5
numberOfPivots (series int) : max number of pivots to hold in the calculation. Default value is 20
offset (series int) : Bar offset to be considered for calculation of zigzag. Default is 0 - which means calculation is done based on the latest bar.
level (series int) : Zigzag calculation level - used in multi level recursive zigzags
zigzagPivots (Pivot ) : array which holds the last n pivots calculated.
flags (ZigzagFlags) : ZigzagFlags object which is required for continuous drawing of zigzag lines.
ZigzagObject
Zigzag Drawing Object
Fields:
zigzagLine (series line) : Line joining two pivots
zigzagLabel (series label) : Label which can be used for drawing the values, ratios, directions etc.
ZigzagProperties
Object which holds properties of zigzag drawing. To be used along with ZigzagDrawing
Fields:
lineColor (series color) : Zigzag line color. Default is color.blue
lineWidth (series int) : Zigzag line width. Default is 1
lineStyle (series string) : Zigzag line style. Default is line.style_solid.
showLabel (series bool) : If set, the drawing will show labels on each pivot. Default is false
textColor (series color) : Text color of the labels. Only applicable if showLabel is set to true.
maxObjects (series int) : Max number of zigzag lines to display. Default is 300
xloc (series string) : Time/Bar reference to be used for zigzag drawing. Default is Time - xloc.bar_time.
ZigzagDrawing
Object which holds complete zigzag drawing objects and properties.
Fields:
zigzag (Zigzag) : Zigzag object which holds the calculations.
properties (ZigzagProperties) : ZigzagProperties object which is used for setting the display styles of zigzag
drawings (ZigzagObject ) : array which contains lines and labels of zigzag drawing.
ColorPalettesThis is my first public (and I hope not the last) library providing different color palettes used for data visualization. Each palette can contain either 3 to 9 colors or 3 to 11 colors.
So there you go. Happy New Year!
I want your new year to be as colorful, vibrant and rich as these color palettes.
Dedicated to @veryfid . RIP, dude.
---
Library "ColorPalettes"
A library of various color palettes for data visualization
Reds(n)
A function to generate the sequential `Reds` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `Reds` palette.
Blues(n)
A function to generate the sequential `Blues` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `Blues` palette.
Greens(n)
A function to generate the sequential `Greens` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `Greens` palette.
Purples(n)
A function to generate the sequential `Purples` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `Purples` palette.
Oranges(n)
A function to generate the sequential `Oranges` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `Oranges` palette.
Greys(n)
A function to generate the sequential `Greys` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `Greys` palette.
YlGn(n)
A function to generate the sequential `YlGn` (Yellow/Green) palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `YlGn` palette.
YlGnBu(n)
A function to generate the sequential `YlGnBu` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `YlGnBu` palette.
GnBu(n)
A function to generate the sequential `GnBu` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `GnBu` palette.
BuGn(n)
A function to generate the sequential `BuGn` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `BuGn` palette.
PuBuGn(n)
A function to generate the sequential `PuBuGn` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `PuBuGn` palette.
PuBu(n)
A function to generate the sequential `PuBu` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `PuBu` palette.
BuPu(n)
A function to generate the sequential `BuPu` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `BuPu` palette.
RdPu(n)
A function to generate the sequential `RdPu` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `RdPu` palette.
PuRd(n)
A function to generate the sequential `PuRd` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `PuRd` palette.
OrRd(n)
A function to generate the sequential `OrRd` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `OrRd` palette.
YlOrRd(n)
A function to generate the sequential `YlOrRd` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `YlOrRd` palette.
YlOrBr(n)
A function to generate the sequential `YlOrBr` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `YlOrBr` palette.
Inferno(n)
A function to generate the sequential `Inferno` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `Inferno` palette.
Magma(n)
A function to generate the sequential `Magma` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `Magma` palette.
Plasma(n)
A function to generate the sequential `Plasma` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `Plasma` palette.
Viridis(n)
A function to generate the sequential `Viridis` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `Viridis` palette.
Cividis(n)
A function to generate the sequential `Cividis` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `Cividis` palette.
Spectral(n)
A function to generate the diverging `Spectral` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `Spectral` palette.
Turbo(n)
A function to generate the diverging `Turbo` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `Turbo` palette.
BrBG(n)
A function to generate the diverging `BrBG` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `BrBG` palette.
PiYG(n)
A function to generate the diverging `PiYG` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `PiYG` palette.
PRGn(n)
A function to generate the diverging `PRGn` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `PRGn` palette.
PuOr(n)
A function to generate the diverging `PuOr` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `PuOr` palette.
RdBu(n)
A function to generate the diverging `RdBu` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `RdBu` palette.
RdGy(n)
A function to generate the diverging `RdGy` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `RdGy` palette.
RdYlBu(n)
A function to generate the diverging `RdYlBu` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `RdYlBu` palette.
RdYlGn(n)
A function to generate the diverging `RdYlGn` palette of the specified size.
Parameters:
n (int) The size of the output palette to generate. Default is 9.
Returns: An array of colors from the `RdYlGn` palette.
ETFFinderLibLibrary "ETFFinderLib"
TODO: add library description here
etf_search_ticker(ticker)
searches the entire ETF library by ticker and identifies which ETFs hold a specific tickers.
Parameters:
ticker (string)
Returns: returns 2 arrays, holding_array (string array) and compo_array(float array)
etf_search_sectors(sector)
searches the entire ETF library by sector and pulls by desired sector
Parameters:
sector (string)
Returns: returns 2 arrays, sector_array (string array) and composition array (float array)
ETFHoldingsLibLibrary "ETFHoldingsLib"
spy_get()
: pulls SPY ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
qqq_get()
: pulls QQQ ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
arkk_get()
: pulls ARKK ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
xle_get()
: pulls XLE ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
brk_get()
: pulls BRK ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
ita_get()
: pulls ITA ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
iwm_get()
: pulls IWM ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
xlf_get()
: pulls XLF ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
xlv_get()
: pulls XLV ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
vnq_get()
: pulls VNQ ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
xbi_get()
: pulls XBI ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
blcr_get()
: pulls BLCR ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
vgt_get()
: pulls VGT ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
vwo_get()
: pulls VWO ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
vig_get()
: pulls VIG ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
vug_get()
: pulls VUG ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
vtv_get()
: pulls VTV ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
vea_get()
: pulls VEA ETF data
Returns: : tickers held (string array), percent ticker holding (float array), sectors (string array), percent secture positioning (float array)
SPTS_StatsPakLibFinally getting around to releasing the library component to the SPTS indicator!
This library is packed with a ton of great statistics functions to supplement SPTS, these functions add to the capabilities of SPTS including a forecast function.
The library includes the following functions
1. Linear Regression (single independent and single dependent)
2. Multiple Regression (2 independent variables, 1 dependent)
3. Standard Error of Residual Assessment
4. Z-Score
5. Effect Size
6. Confidence Interval
7. Paired Sample Test
8. Two Tailed T-Test
9. Qualitative assessment of T-Test
10. T-test table and p value assigner
11. Correlation of two arrays
12. Quadratic correlation (curvlinear)
13. R Squared value of 2 arrays
14. R Squared value of 2 floats
15. Test of normality
16. Forecast function which will push the desired forecasted variables into an array.
One of the biggest added functionalities of this library is the forecasting function.
This function provides an autoregressive, trainable model that will export forecasted values to 3 arrays, one contains the autoregressed forecasted results, the other two contain the upper confidence forecast and the lower confidence forecast.
Hope you enjoy and find use for this!
Library "SPTS_StatsPakLib"
f_linear_regression(independent, dependent, len, variable)
TODO: creates a simple linear regression model between two variables.
Parameters:
independent (float)
dependent (float)
len (int)
variable (float)
Returns: TODO: returns 6 float variables
result: The result of the regression model
pear_cor: The pearson correlation of the regresion model
rsqrd: the R2 of the regression model
std_err: the error of residuals
slope: the slope of the model (coefficient)
intercept: the intercept of the model (y = mx + b is y = slope x + intercept)
f_multiple_regression(y, x1, x2, input1, input2, len)
TODO: creates a multiple regression model between two independent variables and 1 dependent variable.
Parameters:
y (float)
x1 (float)
x2 (float)
input1 (float)
input2 (float)
len (int)
Returns: TODO: returns 7 float variables
result: The result of the regression model
pear_cor: The pearson correlation of the regresion model
rsqrd: the R2 of the regression model
std_err: the error of residuals
b1 & b2: the slopes of the model (coefficients)
intercept: the intercept of the model (y = mx + b is y = b1 x + b2 x + intercept)
f_stanard_error(result, dependent, length)
x TODO: performs an assessment on the error of residuals, can be used with any variable in which there are residual values (such as moving averages or more comlpex models)
param x TODO: result is the output, for example, if you are calculating the residuals of a 200 EMA, the result would be the 200 EMA
dependent: is the dependent variable. In the above example with the 200 EMA, your dependent would be the source for your 200 EMA
Parameters:
result (float)
dependent (float)
length (int)
Returns: x TODO: the standard error of the residual, which can then be multiplied by standard deviations or used as is.
f_zscore(variable, length)
TODO: Calculates the z-score
Parameters:
variable (float)
length (int)
Returns: TODO: returns float z-score
f_effect_size(array1, array2)
TODO: Calculates the effect size between two arrays of equal scale.
Parameters:
array1 (float )
array2 (float )
Returns: TODO: returns the effect size (float)
f_confidence_interval(array1, array2, ci_input)
TODO: Calculates the confidence interval between two arrays
Parameters:
array1 (float )
array2 (float )
ci_input (float)
Returns: TODO: returns the upper_bound and lower_bound cofidence interval as float values
paired_sample_t(src1, src2, len)
TODO: Performs a paired sample t-test
Parameters:
src1 (float)
src2 (float)
len (int)
Returns: TODO: Returns the t-statistic and degrees of freedom of a paired sample t-test
two_tail_t_test(array1, array2)
TODO: Perofrms a two tailed t-test
Parameters:
array1 (float )
array2 (float )
Returns: TODO: Returns the t-statistic and degrees of freedom of a two_tail_t_test sample t-test
t_table_analysis(t_stat, df)
TODO: This is to make a qualitative assessment of your paired and single sample t-test
Parameters:
t_stat (float)
df (float)
Returns: TODO: the function will return 2 string variables and 1 colour variable. The 2 string variables indicate whether the results are significant or not and the colour will
output red for insigificant and green for significant
t_table_p_value(df, t_stat)
TODO: This performs a quantaitive assessment on your t-tests to determine the statistical significance p value
Parameters:
df (float)
t_stat (float)
Returns: TODO: The function will return 1 float variable, the p value of the t-test.
cor_of_array(array1, array2)
TODO: This performs a pearson correlation assessment of two arrays. They need to be of equal size!
Parameters:
array1 (float )
array2 (float )
Returns: TODO: The function will return the pearson correlation.
quadratic_correlation(src1, src2, len)
TODO: This performs a quadratic (curvlinear) pearson correlation between two values.
Parameters:
src1 (float)
src2 (float)
len (int)
Returns: TODO: The function will return the pearson correlation (quadratic based).
f_r2_array(array1, array2)
TODO: Calculates the r2 of two arrays
Parameters:
array1 (float )
array2 (float )
Returns: TODO: returns the R2 value
f_rsqrd(src1, src2, len)
TODO: Calculates the r2 of two float variables
Parameters:
src1 (float)
src2 (float)
len (int)
Returns: TODO: returns the R2 value
test_of_normality(array, src)
TODO: tests the normal distribution hypothesis
Parameters:
array (float )
src (float)
Returns: TODO: returns 4 variables, 2 float and 2 string
Skew: the skewness of the dataset
Kurt: the kurtosis of the dataset
dist = the distribution type (recognizes 7 different distribution types)
implication = a string assessment of the implication of the distribution (qualitative)
f_forecast(output, input, train_len, forecast_length, output_array, upper_array, lower_array)
TODO: This performs a simple forecast function on a single dependent variable. It will autoregress this based on the train time, to the desired length of output,
then it will push the forecasted values to 3 float arrays, one that contains the forecasted result, 1 that contains the Upper Confidence Result and one with the lower confidence
result.
Parameters:
output (float)
input (float)
train_len (int)
forecast_length (int)
output_array (float )
upper_array (float )
lower_array (float )
Returns: TODO: Will return 3 arrays, one with the forecasted results, one with the upper confidence results, and a final with the lower confidence results. Example is given below.
MTF_DrawingsLibrary 'MTF_Drawings'
This library helps with drawing indicators and candle charts on all timeframes.
FEATURES
CHART DRAWING : Library provides functions for drawing High Time Frame (HTF) and Low Time Frame (LTF) candles.
INDICATOR DRAWING : Library provides functions for drawing various types of HTF and LTF indicators.
CUSTOM COLOR DRAWING : Library allows to color candles and indicators based on specific conditions.
LINEFILLS : Library provides functions for drawing linefills.
CATEGORIES
The functions are named in a way that indicates they purpose:
{Ind} : Function is meant only for indicators.
{Hist} : Function is meant only for histograms.
{Candle} : Function is meant only for candles.
{Draw} : Function draws indicators, histograms and candle charts.
{Populate} : Function generates necessary arrays required by drawing functions.
{LTF} : Function is meant only for lower timeframes.
{HTF} : Function is meant only for higher timeframes.
{D} : Function draws indicators that are composed of two lines.
{CC} : Function draws custom colored indicators.
USAGE
Import the library into your script.
Before using any {Draw} function it is necessary to use a {Populate} function.
Choose the appropriate one based on the category, provide the necessary arguments, and then use the {Draw} function, forwarding the arrays generated by the {Populate} function.
This doesn't apply to {Draw_Lines}, {LineFill}, or {Barcolor} functions.
EXAMPLE
import Spacex_trader/MTF_Drawings/1 as tf
//Request lower timeframe data.
Security(simple string Ticker, simple string New_LTF, float Ind) =>
float Value = request.security_lower_tf(Ticker, New_LTF, Ind)
Value
Timeframe = input.timeframe('1', 'Timeframe: ')
tf.Draw_Ind(tf.Populate_LTF_Ind(Security(syminfo.tickerid, Timeframe, ta.rsi(close, 14)), 498, color.purple), 1, true)
FUNCTION LIST
HTF_Candle(BarsBack, BodyBear, BodyBull, BordersBear, BordersBull, WickBear, WickBull, LineStyle, BoxStyle, LineWidth, HTF_Open, HTF_High, HTF_Low, HTF_Close, HTF_Bar_Index)
Populates two arrays with drawing data of the HTF candles.
Parameters:
BarsBack (int) : Bars number to display.
BodyBear (color) : Candle body bear color.
BodyBull (color) : Candle body bull color.
BordersBear (color) : Candle border bear color.
BordersBull (color) : Candle border bull color.
WickBear (color) : Candle wick bear color.
WickBull (color) : Candle wick bull color.
LineStyle (string) : Wick style (Solid-Dotted-Dashed).
BoxStyle (string) : Border style (Solid-Dotted-Dashed).
LineWidth (int) : Wick width.
HTF_Open (float) : HTF open price.
HTF_High (float) : HTF high price.
HTF_Low (float) : HTF low price.
HTF_Close (float) : HTF close price.
HTF_Bar_Index (int) : HTF bar_index.
Returns: Two arrays with drawing data of the HTF candles.
LTF_Candle(BarsBack, BodyBear, BodyBull, BordersBear, BordersBull, WickBear, WickBull, LineStyle, BoxStyle, LineWidth, LTF_Open, LTF_High, LTF_Low, LTF_Close)
Populates two arrays with drawing data of the LTF candles.
Parameters:
BarsBack (int) : Bars number to display.
BodyBear (color) : Candle body bear color.
BodyBull (color) : Candle body bull color.
BordersBear (color) : Candle border bear color.
BordersBull (color) : Candle border bull color.
WickBear (color) : Candle wick bear color.
WickBull (color) : Candle wick bull color.
LineStyle (string) : Wick style (Solid-Dotted-Dashed).
BoxStyle (string) : Border style (Solid-Dotted-Dashed).
LineWidth (int) : Wick width.
LTF_Open (float ) : LTF open price.
LTF_High (float ) : LTF high price.
LTF_Low (float ) : LTF low price.
LTF_Close (float ) : LTF close price.
Returns: Two arrays with drawing data of the LTF candles.
Draw_Candle(Box, Line, Offset)
Draws HTF or LTF candles.
Parameters:
Box (box ) : Box array with drawing data.
Line (line ) : Line array with drawing data.
Offset (int) : Offset of the candles.
Returns: Drawing of the candles.
Populate_HTF_Ind(IndValue, BarsBack, IndColor, HTF_Bar_Index)
Populates one array with drawing data of the HTF indicator.
Parameters:
IndValue (float) : Indicator value.
BarsBack (int) : Indicator lines to display.
IndColor (color) : Indicator color.
HTF_Bar_Index (int) : HTF bar_index.
Returns: An array with drawing data of the HTF indicator.
Populate_LTF_Ind(IndValue, BarsBack, IndColor)
Populates one array with drawing data of the LTF indicator.
Parameters:
IndValue (float ) : Indicator value.
BarsBack (int) : Indicator lines to display.
IndColor (color) : Indicator color.
Returns: An array with drawing data of the LTF indicator.
Draw_Ind(Line, Mult, Exe)
Draws one HTF or LTF indicator.
Parameters:
Line (line ) : Line array with drawing data.
Mult (int) : Coordinates multiplier.
Exe (bool) : Display the indicator.
Returns: Drawing of the indicator.
Populate_HTF_Ind_D(IndValue_1, IndValue_2, BarsBack, IndColor_1, IndColor_2, HTF_Bar_Index)
Populates two arrays with drawing data of the HTF indicators.
Parameters:
IndValue_1 (float) : First indicator value.
IndValue_2 (float) : Second indicator value.
BarsBack (int) : Indicator lines to display.
IndColor_1 (color) : First indicator color.
IndColor_2 (color) : Second indicator color.
HTF_Bar_Index (int) : HTF bar_index.
Returns: Two arrays with drawing data of the HTF indicators.
Populate_LTF_Ind_D(IndValue_1, IndValue_2, BarsBack, IndColor_1, IndColor_2)
Populates two arrays with drawing data of the LTF indicators.
Parameters:
IndValue_1 (float ) : First indicator value.
IndValue_2 (float ) : Second indicator value.
BarsBack (int) : Indicator lines to display.
IndColor_1 (color) : First indicator color.
IndColor_2 (color) : Second indicator color.
Returns: Two arrays with drawing data of the LTF indicators.
Draw_Ind_D(Line_1, Line_2, Mult, Exe_1, Exe_2)
Draws two LTF or HTF indicators.
Parameters:
Line_1 (line ) : First line array with drawing data.
Line_2 (line ) : Second line array with drawing data.
Mult (int) : Coordinates multiplier.
Exe_1 (bool) : Display the first indicator.
Exe_2 (bool) : Display the second indicator.
Returns: Drawings of the indicators.
Barcolor(Box, Line, BarColor)
Colors the candles based on indicators output.
Parameters:
Box (box ) : Candle box array.
Line (line ) : Candle line array.
BarColor (color ) : Indicator color array.
Returns: Colored candles.
Populate_HTF_Ind_D_CC(IndValue_1, IndValue_2, BarsBack, BullColor, BearColor, IndColor_1, HTF_Bar_Index)
Populates two array with drawing data of the HTF indicators with color based on: IndValue_1 >= IndValue_2 ? BullColor : BearColor.
Parameters:
IndValue_1 (float) : First indicator value.
IndValue_2 (float) : Second indicator value.
BarsBack (int) : Indicator lines to display.
BullColor (color) : Bull color.
BearColor (color) : Bear color.
IndColor_1 (color) : First indicator color.
HTF_Bar_Index (int) : HTF bar_index.
Returns: Three arrays with drawing and color data of the HTF indicators.
Populate_LTF_Ind_D_CC(IndValue_1, IndValue_2, BarsBack, BullColor, BearColor, IndColor_1)
Populates two arrays with drawing data of the LTF indicators with color based on: IndValue_1 >= IndValue_2 ? BullColor : BearColor.
Parameters:
IndValue_1 (float ) : First indicator value.
IndValue_2 (float ) : Second indicator value.
BarsBack (int) : Indicator lines to display.
BullColor (color) : Bull color.
BearColor (color) : Bearcolor.
IndColor_1 (color) : First indicator color.
Returns: Three arrays with drawing and color data of the LTF indicators.
Populate_HTF_Hist_CC(HistValue, IndValue_1, IndValue_2, BarsBack, BullColor, BearColor, HTF_Bar_Index)
Populates one array with drawing data of the HTF histogram with color based on: IndValue_1 >= IndValue_2 ? BullColor : BearColor.
Parameters:
HistValue (float) : Indicator value.
IndValue_1 (float) : First indicator value.
IndValue_2 (float) : Second indicator value.
BarsBack (int) : Indicator lines to display.
BullColor (color) : Bull color.
BearColor (color) : Bearcolor.
HTF_Bar_Index (int) : HTF bar_index
Returns: Two arrays with drawing and color data of the HTF histogram.
Populate_LTF_Hist_CC(HistValue, IndValue_1, IndValue_2, BarsBack, BullColor, BearColor)
Populates one array with drawing data of the LTF histogram with color based on: IndValue_1 >= IndValue_2 ? BullColor : BearColor.
Parameters:
HistValue (float ) : Indicator value.
IndValue_1 (float ) : First indicator value.
IndValue_2 (float ) : Second indicator value.
BarsBack (int) : Indicator lines to display.
BullColor (color) : Bull color.
BearColor (color) : Bearcolor.
Returns: Two array with drawing and color data of the LTF histogram.
Populate_LTF_Hist_CC_VA(HistValue, Value, BarsBack, BullColor, BearColor)
Populates one array with drawing data of the LTF histogram with color based on: HistValue >= Value ? BullColor : BearColor.
Parameters:
HistValue (float ) : Indicator value.
Value (float) : First indicator value.
BarsBack (int) : Indicator lines to display.
BullColor (color) : Bull color.
BearColor (color) : Bearcolor.
Returns: Two array with drawing and color data of the LTF histogram.
Populate_HTF_Ind_CC(IndValue, IndValue_1, BarsBack, BullColor, BearColor, HTF_Bar_Index)
Populates one array with drawing data of the HTF indicator with color based on: IndValue >= IndValue_1 ? BullColor : BearColor.
Parameters:
IndValue (float) : Indicator value.
IndValue_1 (float) : Second indicator value.
BarsBack (int) : Indicator lines to display.
BullColor (color) : Bull color.
BearColor (color) : Bearcolor.
HTF_Bar_Index (int) : HTF bar_index
Returns: Two arrays with drawing and color data of the HTF indicator.
Populate_LTF_Ind_CC(IndValue, IndValue_1, BarsBack, BullColor, BearColor)
Populates one array with drawing data of the LTF indicator with color based on: IndValue >= IndValue_1 ? BullColor : BearColor.
Parameters:
IndValue (float ) : Indicator value.
IndValue_1 (float ) : Second indicator value.
BarsBack (int) : Indicator lines to display.
BullColor (color) : Bull color.
BearColor (color) : Bearcolor.
Returns: Two arrays with drawing and color data of the LTF indicator.
Draw_Lines(BarsBack, y1, y2, LineType, Fill)
Draws price lines on indicators.
Parameters:
BarsBack (int) : Indicator lines to display.
y1 (float) : Coordinates of the first line.
y2 (float) : Coordinates of the second line.
LineType (string) : Line type.
Fill (color) : Fill color.
Returns: Drawing of the lines.
LineFill(Upper, Lower, BarsBack, FillColor)
Fills two lines with linefill HTF or LTF.
Parameters:
Upper (line ) : Upper line.
Lower (line ) : Lower line.
BarsBack (int) : Indicator lines to display.
FillColor (color) : Fill color.
Returns: Linefill of the lines.
Populate_LTF_Hist(HistValue, BarsBack, HistColor)
Populates one array with drawing data of the LTF histogram.
Parameters:
HistValue (float ) : Indicator value.
BarsBack (int) : Indicator lines to display.
HistColor (color) : Indicator color.
Returns: One array with drawing data of the LTF histogram.
Populate_HTF_Hist(HistValue, BarsBack, HistColor, HTF_Bar_Index)
Populates one array with drawing data of the HTF histogram.
Parameters:
HistValue (float) : Indicator value.
BarsBack (int) : Indicator lines to display.
HistColor (color) : Indicator color.
HTF_Bar_Index (int) : HTF bar_index.
Returns: One array with drawing data of the HTF histogram.
Draw_Hist(Box, Mult, Exe)
Draws HTF or LTF histogram.
Parameters:
Box (box ) : Box Array.
Mult (int) : Coordinates multiplier.
Exe (bool) : Display the histogram.
Returns: Drawing of the histogram.
WIPFunctionLyaponovLibrary "WIPFunctionLyaponov"
Lyapunov exponents are mathematical measures used to describe the behavior of a system over
time. They are named after Russian mathematician Alexei Lyapunov, who first introduced the concept in the
late 19th century. The exponent is defined as the rate at which a particular function or variable changes
over time, and can be positive, negative, or zero.
Positive exponents indicate that a system tends to grow or expand over time, while negative exponents
indicate that a system tends to shrink or decay. Zero exponents indicate that the system does not change
significantly over time. Lyapunov exponents are used in various fields of science and engineering, including
physics, economics, and biology, to study the long-term behavior of complex systems.
~ generated description from vicuna13b
---
To calculate the Lyapunov Exponent (LE) of a given Time Series, we need to follow these steps:
1. Firstly, you should have access to your data in some format like CSV or Excel file. If not, then you can collect it manually using tools such as stopwatches and measuring tapes.
2. Once the data is collected, clean it up by removing any outliers that may skew results. This step involves checking for inconsistencies within your dataset (e.g., extremely large or small values) and either discarding them entirely or replacing with more reasonable estimates based on surrounding values.
3. Next, you need to determine the dimension of your time series data. In most cases, this will be equal to the number of variables being measured in each observation period (e.g., temperature, humidity, wind speed).
4. Now that we have a clean dataset with known dimensions, we can calculate the LE for our Time Series using the following formula:
λ = log(||M^T * M - I||)/log(||v||)
where:
λ (Lyapunov Exponent) is the quantity that will be calculated.
||...|| denotes an Euclidean norm of a vector or matrix, which essentially means taking the square root of the sum of squares for each element in the vector/matrix.
M represents our Jacobian Matrix whose elements are given by:
J_ij = (∂fj / ∂xj) where fj is the jth variable and xj is the ith component of the initial condition vector x(t). In other words, each element in this matrix represents how much a small change in one variable affects another.
I denotes an identity matrix whose elements are all equal to 1 (or any constant value if you prefer). This term essentially acts as a baseline for comparison purposes since we want our Jacobian Matrix M^T * M to be close to it when the system is stable and far away from it when the system is unstable.
v represents an arbitrary vector whose Euclidean norm ||v|| will serve as a scaling factor in our calculation. The choice of this particular vector does not matter since we are only interested in its magnitude (i.e., length) for purposes of normalization. However, if you want to ensure that your results are accurate and consistent across different datasets or scenarios, it is recommended to use the same initial condition vector x(t) as used earlier when calculating our Jacobian Matrix M.
5. Finally, once we have calculated λ using the formula above, we can interpret its value in terms of stability/instability for our Time Series data:
- If λ < 0, then this indicates that the system is stable (i.e., nearby trajectories will converge towards each other over time).
- On the other hand, if λ > 0, then this implies that the system is unstable (i.e., nearby trajectories will diverge away from one another over time).
~ generated description from airoboros33b
---
Reference:
en.wikipedia.org
www.collimator.ai
blog.abhranil.net
www.researchgate.net
physics.stackexchange.com
---
This is a work in progress, it may contain errors so use with caution.
If you find flaws or suggest something new, please leave a comment bellow.
_measure_function(i)
helper function to get the name of distance function by a index (0 -> 13).\
Functions: SSD, Euclidean, Manhattan, Minkowski, Chebyshev, Correlation, Cosine, Camberra, MAE, MSE, Lorentzian, Intersection, Penrose Shape, Meehl.
Parameters:
i (int)
_test(L)
Helper function to test the output exponents state system and outputs description into a string.
Parameters:
L (float )
estimate(X, initial_distance, distance_function)
Estimate the Lyaponov Exponents for multiple series in a row matrix.
Parameters:
X (map)
initial_distance (float) : Initial distance limit.
distance_function (string) : Name of the distance function to be used, default:`ssd`.
Returns: List of Lyaponov exponents.
max(L)
Maximal Lyaponov Exponent.
Parameters:
L (float ) : List of Lyapunov exponents.
Returns: Highest exponent.
CommonTypesMapUtilLibrary "CommonTypesMapUtil"
Common type Container library, for central usage across other reference libraries.
ArrayBool
Fields:
v (bool )
ArrayBox
Fields:
v (box )
ArrayPoint
Fields:
v (chart.point )
ArrayColor
Fields:
v (color )
ArrayFloat
Fields:
v (float )
ArrayInt
Fields:
v (int )
ArrayLabel
Fields:
v (label )
ArrayLine
Fields:
v (line )
ArrayLinefill
Fields:
v (linefill )
ArrayString
Fields:
v (string )
ArrayTable
Fields:
v (table )
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
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)
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 .
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)
CandlesGroup_TypesLibrary "CandlesGroup_Types"
CandlesGroup Type allows you to efficiently store and access properties of all the candles in your chart.
You can easily manipulate large datasets, work with multiple timeframes, or analyze multiple symbols simultaneously. By encapsulating the properties of each candle within a CandlesGroup object, you gain a convenient and organized way to handle complex candlestick patterns and data.
For usage instructions and detailed examples, please refer to the comments and examples provided in the source code.
method init(_self)
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup)
method init(_self, propertyNames)
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup)
propertyNames (string )
method get(_self, key)
get values array from a given property name
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
key (string) : : key name of selected property. Default is "index"
Returns: values array
method size(_self)
get size of values array. By default it equals to current bar_index
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
Returns: size of values array
method push(_self, key, value)
push single value to specific property
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
key (string) : : key name of selected property
value (float) : : property value
Returns: CandlesGroup object
method push(_self, arr)
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup)
arr (float )
method populate(_self, ohlc)
populate ohlc to CandlesGroup
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
ohlc (float ) : : array of ohlc
Returns: CandlesGroup object
method populate(_self, values, propertiesNames)
populate values base on given properties Names
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
values (float ) : : array of property values
propertiesNames (string ) : : an array stores property names. Use as keys to get values
Returns: CandlesGroup object
method populate(_self)
populate values (default setup)
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
Returns: CandlesGroup object
method lookback(arr, bars_lookback)
get property value on previous candles. For current candle, use *.lookback()
Namespace types: float
Parameters:
arr (float ) : : array of selected property values
bars_lookback (int) : : number of candles lookback. 0 = current candle. Default is 0
Returns: single property value
method highest_within_bars(_self, hiSource, start, end, useIndex)
get the highest property value between specific candles
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
hiSource (string) : : key name of selected property
start (int) : : start bar for calculation. Default is candles lookback value from current candle. 'index' value is used if 'useIndex' = true
end (int) : : end bar for calculation. Default is candles lookback value from current candle. 'index' value is used if 'useIndex' = true. Default is 0
useIndex (bool) : : use index instead of lookback value. Default = false
Returns: the highest value within candles
method highest_within_bars(_self, returnWithIndex, hiSource, start, end, useIndex)
get the highest property value and bar index between specific candles
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
returnWithIndex (bool) : : the function only applicable when it is true
hiSource (string) : : key name of selected property
start (int) : : start bar for calculation. Default is candles lookback value from current candle. 'index' value is used if 'useIndex' = true
end (int) : : end bar for calculation. Default is candles lookback value from current candle. 'index' value is used if 'useIndex' = true. Default is 0
useIndex (bool) : : use index instead of lookback value. Default = false
Returns:
method highest_point_within_bars(_self, hiSource, start, end, useIndex)
get a Point object which contains highest property value between specific candles
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
hiSource (string) : : key name of selected property
start (int) : : start bar for calculation. Default is candles lookback value from current candle. 'index' value is used if 'useIndex' = true
end (int) : : end bar for calculation. Default is candles lookback value from current candle. 'index' value is used if 'useIndex' = true. Default is 0
useIndex (bool) : : use index instead of lookback value. Default = false
Returns: Point object contains highest property value
method lowest_within_bars(_self, loSource, start, end, useIndex)
get the lowest property value between specific candles
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
loSource (string) : : key name of selected property
start (int) : : start bar for calculation. Default is candles lookback value from current candle. 'index' value is used if 'useIndex' = true
end (int) : : end bar for calculation. Default is candles lookback value from current candle. 'index' value is used if 'useIndex' = true. Default is 0
useIndex (bool) : : use index instead of lookback value. Default = false
Returns: the lowest value within candles
method lowest_within_bars(_self, returnWithIndex, loSource, start, end, useIndex)
get the lowest property value and bar index between specific candles
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
returnWithIndex (bool) : : the function only applicable when it is true
loSource (string) : : key name of selected property
start (int) : : start bar for calculation. Default is candles lookback value from current candle. 'index' value is used if 'useIndex' = true
end (int) : : end bar for calculation. Default is candles lookback value from current candle. 'index' value is used if 'useIndex' = true. Default is 0
useIndex (bool) : : use index instead of lookback value. Default = false
Returns:
method lowest_point_within_bars(_self, loSource, start, end, useIndex)
get a Point object which contains lowest property value between specific candles
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
loSource (string) : : key name of selected property
start (int) : : start bar for calculation. Default is candles lookback value from current candle. 'index' value is used if 'useIndex' = true
end (int) : : end bar for calculation. Default is candles lookback value from current candle. 'index' value is used if 'useIndex' = true. Default is 0
useIndex (bool) : : use index instead of lookback value. Default = false
Returns: Point object contains lowest property value
method time2bar(_self, t)
Convert UNIX time to bar index of active chart
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
t (int) : : UNIX time
Returns: bar index
method time2bar(_self, timezone, YYYY, MMM, DD, hh, mm, ss)
Convert timestamp to bar index of active chart. User defined timezone required
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
timezone (string) : : User defined timezone
YYYY (int) : : Year
MMM (int) : : Month
DD (int) : : Day
hh (int) : : Hour. Default is 0
mm (int) : : Minute. Default is 0
ss (int) : : Second. Default is 0
Returns: bar index
method time2bar(_self, YYYY, MMM, DD, hh, mm, ss)
Convert timestamp to bar index of active chart
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
YYYY (int) : : Year
MMM (int) : : Month
DD (int) : : Day
hh (int) : : Hour. Default is 0
mm (int) : : Minute. Default is 0
ss (int) : : Second. Default is 0
Returns: bar index
method get_prop_from_time(_self, key, t)
get single property value from UNIX time
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
key (string) : : key name of selected property
t (int) : : UNIX time
Returns: single property value
method get_prop_from_time(_self, key, timezone, YYYY, MMM, DD, hh, mm, ss)
get single property value from timestamp. User defined timezone required
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
key (string) : : key name of selected property
timezone (string) : : User defined timezone
YYYY (int) : : Year
MMM (int) : : Month
DD (int) : : Day
hh (int) : : Hour. Default is 0
mm (int) : : Minute. Default is 0
ss (int) : : Second. Default is 0
Returns: single property value
method get_prop_from_time(_self, key, YYYY, MMM, DD, hh, mm, ss)
get single property value from timestamp
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
key (string) : : key name of selected property
YYYY (int) : : Year
MMM (int) : : Month
DD (int) : : Day
hh (int) : : Hour. Default is 0
mm (int) : : Minute. Default is 0
ss (int) : : Second. Default is 0
Returns: single property value
method bar2time(_self, index)
Convert bar index of active chart to UNIX time
Namespace types: CandlesGroup
Parameters:
_self (CandlesGroup) : : CandlesGroup object
index (int) : : bar index
Returns: UNIX time
Point
A point on chart
Fields:
price (series float) : : price value
bar (series int) : : bar index
bartime (series int) : : time in UNIX format of bar
Property
Property object which contains values of all candles
Fields:
name (series string) : : name of property
values (float ) : : an array stores values of all candles. Size of array = bar_index
CandlesGroup
Candles Group object which contains properties of all candles
Fields:
propertyNames (string ) : : an array stores property names. Use as keys to get values
properties (Property ) : : array of Property objects
lib_trackingLibrary "lib_tracking"
tracking highest and lowest with anchor point to track over dynamic periods, e.g. to track a Session HH/LL live and get the bar/time of the LTF wick that matches the HTF HH/LL
// DESIGN DECISION
// why anchored replacements for ta.highest / ta.highestbars / ta.lowest / ta.lowestbars:
// 1. they require a fixed length/lookback which makes it easier to calculate, but
// 2. this prevents us from tracking the HH/LL of a changing timeframe, e.g. live tracking the HH/LL of a running session or unfinished higher timeframe
// 3. tracking with anchor/start/reset flag allows to persist values until the next start/reset, so no other external storage is required
track_highest(value, reset, track_this_bar)
Parameters:
value (float)
reset (bool) : boolean flag to restart tracking from this point (a.k.a anchor)
track_this_bar (bool) : allows enabling and disabling of tracking, e.g. before a session starts or after it ends, values can be kept until next reset.
track_lowest(value, reset, track_this_bar)
Parameters:
value (float)
reset (bool) : boolean flag to restart tracking from this point (a.k.a anchor)
track_this_bar (bool) : allows enabling and disabling of tracking, e.g. before a session starts or after it ends, values can be kept until next reset.
track_hl_htf(htf, value_high, value_low)
Parameters:
htf (string) : the higher timeframe in pinescript string notation
value_high (float)
value_low (float)
Returns:
lib_arrayLibrary "lib_array"
several array functions for chained calls, batch conversion, incrementing and comparing arrays.
method sort(id, descending)
Namespace types: int
Parameters:
id (int ) : The array to sort (and return again)
descending (bool) : The sort order: order.ascending (default:false, meaning omit this param and just call myArray.sort()) or order.descending => set descending=true
@return The array that was passed as parameter id
method sort(id, descending)
Namespace types: float
Parameters:
id (float ) : The array to sort (and return again)
descending (bool) : The sort order: order.ascending (default:false, meaning omit this param and just call myArray.sort()) or order.descending => set descending=true
@return The array that was passed as parameter id
method sort(id, descending)
Namespace types: string
Parameters:
id (string ) : The array to sort (and return again)
descending (bool) : The sort order: order.ascending (default:false, meaning omit this param and just call myArray.sort()) or order.descending => set descending=true
@return The array that was passed as parameter id
method increment(id, by_value)
Namespace types: int
Parameters:
id (int ) : The array to increment (and return again)
by_value (int) : The value by which to increment (default: 1)
@return The array that was passed as parameter id
method increment(id, by_value)
Namespace types: float
Parameters:
id (float ) : The array to increment (and return again)
by_value (float) : The value by which to increment (default: 1.0)
@return The array that was passed as parameter id
method decrement(id, by_value)
Namespace types: int
Parameters:
id (int ) : The array to increment (and return again)
by_value (int) : The value by which to increment (default: 1)
@return The array that was passed as parameter id
method decrement(id, by_value)
Namespace types: float
Parameters:
id (float ) : The array to increment (and return again)
by_value (float) : The value by which to increment (default: 1.0)
@return The array that was passed as parameter id
method toint(id)
Namespace types: string
Parameters:
id (string ) : The array to convert
method toint(id)
Namespace types: float
Parameters:
id (float ) : The array to convert
method tofloat(id)
Namespace types: string
Parameters:
id (string ) : The array to convert
method tofloat(id)
Namespace types: int
Parameters:
id (int ) : The array to convert
method tostring(id)
Namespace types: int
Parameters:
id (int ) : The array to convert
method tostring(id)
Namespace types: float
Parameters:
id (float ) : The array to convert
method tobool(id)
Namespace types: float
Parameters:
id (float ) : The array to convert
method tobool(id)
Namespace types: int
Parameters:
id (int ) : The array to convert
method tobool(id)
Namespace types: string
Parameters:
id (string ) : The array to convert
method sum(id)
Namespace types: bool
Parameters:
id (bool ) : The array to convert
method enqueue(id, item, max, condition, lifo)
Namespace types: int
Parameters:
id (int ) : The array that is used as queue
item (int) : The item to enqueue (at pos 0, unless lifo = true)
max (int) : The max size of the queue
condition (bool) : An optional flag that allows disabling the adding, which in turn will prevent for in loops from ever running and save performance where not needed
lifo (bool) : An optional flag that allows to change the behavior from First In Last Out (default and consistent with pine scripts history operator with most recent elements at index 0) to a more common and resource efficient approach in programming languages: Last In First Out
Returns: The queue passed as param id
method enqueue(id, item, max, condition, lifo)
Namespace types: float
Parameters:
id (float ) : The array that is used as queue
item (float) : The item to enqueue (at pos 0, unless lifo = true)
max (int) : The max size of the queue
condition (bool) : An optional flag that allows disabling the adding, which in turn will prevent for in loops from ever running and save performance where not needed
lifo (bool) : An optional flag that allows to change the behavior from First In Last Out (default and consistent with pine scripts history operator with most recent elements at index 0) to a more common and resource efficient approach in programming languages: Last In First Out
Returns: The queue passed as param id
method enqueue(id, item, max, condition, lifo)
Namespace types: string
Parameters:
id (string ) : The array that is used as queue
item (string) : The item to enqueue (at pos 0, unless lifo = true)
max (int) : The max size of the queue
condition (bool) : An optional flag that allows disabling the adding, which in turn will prevent for in loops from ever running and save performance where not needed
lifo (bool) : An optional flag that allows to change the behavior from First In Last Out (default and consistent with pine scripts history operator with most recent elements at index 0) to a more common and resource efficient approach in programming languages: Last In First Out
Returns: The queue passed as param id
method enqueue(id, item, max, condition, lifo)
Namespace types: line
Parameters:
id (line ) : The array that is used as queue
item (line) : The item to enqueue (at pos 0, unless lifo = true)
max (int) : The max size of the queue
condition (bool) : An optional flag that allows disabling the adding, which in turn will prevent for in loops from ever running and save performance where not needed
lifo (bool) : An optional flag that allows to change the behavior from First In Last Out (default and consistent with pine scripts history operator with most recent elements at index 0) to a more common and resource efficient approach in programming languages: Last In First Out
Returns: The queue passed as param id
method enqueue(id, item, max, condition, lifo)
Namespace types: box
Parameters:
id (box ) : The array that is used as queue
item (box) : The item to enqueue (at pos 0, unless lifo = true)
max (int) : The max size of the queue
condition (bool) : An optional flag that allows disabling the adding, which in turn will prevent for in loops from ever running and save performance where not needed
lifo (bool) : An optional flag that allows to change the behavior from First In Last Out (default and consistent with pine scripts history operator with most recent elements at index 0) to a more common and resource efficient approach in programming languages: Last In First Out
Returns: The queue passed as param id
PivotLibrary "Pivot"
This library helps you store and manage pivots.
bias(isHigh, isHigher, prevWasHigher)
Helper function to calculate bias.
Parameters:
isHigh (bool) : (bool) Wether the pivot is a pivot high or not.
isHigher (bool) : (bool) Wether the pivot is a higher pivot or not.
@return (bool) The bias (true = bullish, false = bearish, na = neutral).
prevWasHigher (bool)
biasToString(bias)
Parameters:
bias (bool)
biasToColor(bias, theme)
Parameters:
bias (bool)
theme (Theme)
nameString(isHigh, isHigher)
Parameters:
isHigh (bool)
isHigher (bool)
abbrString(isHigh, isHigher)
Parameters:
isHigh (bool)
isHigher (bool)
tooltipString(y, isHigh, isHigher, bias, theme)
Parameters:
y (float)
isHigh (bool)
isHigher (bool)
bias (bool)
theme (Theme)
createLabel(x, y, isHigh, isHigher, prevWasHigher, settings)
Parameters:
x (int)
y (float)
isHigh (bool)
isHigher (bool)
prevWasHigher (bool)
settings (Settings)
new(x, y, isHigh, isHigher, settings)
Parameters:
x (int)
y (float)
isHigh (bool)
isHigher (bool)
settings (Settings)
newArray(size, initialValue)
Parameters:
size (int)
initialValue (Pivot)
method getFirst(this)
Namespace types: Pivot
Parameters:
this (Pivot )
method getLast(this, isHigh)
Namespace types: Pivot
Parameters:
this (Pivot )
isHigh (bool)
method getLastHigh(this)
Namespace types: Pivot
Parameters:
this (Pivot )
method getLastLow(this)
Namespace types: Pivot
Parameters:
this (Pivot )
method getPrev(this, numBack, isHigh)
Namespace types: Pivot
Parameters:
this (Pivot )
numBack (int)
isHigh (bool)
method getPrevHigh(this, numBack)
Namespace types: Pivot
Parameters:
this (Pivot )
numBack (int)
method getPrevLow(this, numBack)
Namespace types: Pivot
Parameters:
this (Pivot )
numBack (int)
method getText(this)
Namespace types: Pivot
Parameters:
this (Pivot)
method setX(this, value)
Namespace types: Pivot
Parameters:
this (Pivot)
value (int)
method setY(this, value)
Namespace types: Pivot
Parameters:
this (Pivot)
value (float)
method setXY(this, x, y)
Namespace types: Pivot
Parameters:
this (Pivot)
x (int)
y (float)
method setBias(this, value)
Namespace types: Pivot
Parameters:
this (Pivot)
value (int)
method setColor(this, value)
Namespace types: Pivot
Parameters:
this (Pivot)
value (color)
method setText(this, value)
Namespace types: Pivot
Parameters:
this (Pivot)
value (string)
method add(this, pivot)
Namespace types: Pivot
Parameters:
this (Pivot )
pivot (Pivot)
method updateLast(this, y, settings)
Namespace types: Pivot
Parameters:
this (Pivot )
y (float)
settings (Settings)
method update(this, y, isHigh, settings)
Namespace types: Pivot
Parameters:
this (Pivot )
y (float)
isHigh (bool)
settings (Settings)
Pivot
Stores Pivot data.
Fields:
x (series int)
y (series float)
isHigh (series bool)
isHigher (series bool)
bias (series bool)
lb (series label)
Theme
Attributes for customizable look and feel.
Fields:
size (series string)
colorDefault (series color)
colorNeutral (series color)
colorBullish (series color)
colorBearish (series color)
colored (series bool)
showTooltips (series bool)
showTooltipName (series bool)
showTooltipValue (series bool)
showTooltipBias (series bool)
Settings
All settings for the pivot.
Fields:
theme (Theme)
RelativeValue█ OVERVIEW
This library is a Pine Script™ programmer's tool offering the ability to compute relative values, which represent comparisons of current data points, such as volume, price, or custom indicators, with their analogous historical data points from corresponding time offsets. This approach can provide insightful perspectives into the intricate dynamics of relative market behavior over time.
█ CONCEPTS
Relative values
In this library, a relative value is a metric that compares a current data point in a time interval to an average of data points with corresponding time offsets across historical periods. Its purpose is to assess the significance of a value by considering the historical context within past time intervals.
For instance, suppose we wanted to calculate relative volume on an hourly chart over five daily periods, and the last chart bar is two hours into the current trading day. In this case, we would compare the current volume to the average of volume in the second hour of trading across five days. We obtain the relative volume value by dividing the current volume by this average.
This form of analysis rests on the hypothesis that substantial discrepancies or aberrations in present market activity relative to historical time intervals might help indicate upcoming changes in market trends.
Cumulative and non-cumulative values
In the context of this library, a cumulative value refers to the cumulative sum of a series since the last occurrence of a specific condition (referred to as `anchor` in the function definitions). Given that relative values depend on time, we use time-based conditions such as the onset of a new hour, day, etc. On the other hand, a non-cumulative value is simply the series value at a specific time without accumulation.
Calculating relative values
Four main functions coordinate together to compute the relative values: `maintainArray()`, `calcAverageByTime()`, `calcCumulativeSeries()`, and `averageAtTime()`. These functions are underpinned by a `collectedData` user-defined type (UDT), which stores data collected since the last reset of the timeframe along with their corresponding timestamps. The relative values are calculated using the following procedure:
1. The `averageAtTime()` function invokes the process leveraging all four of the methods and acts as the main driver of the calculations. For each bar, this function adds the current bar's source and corresponding time value to a `collectedData` object.
2. Within the `averageAtTime()` function, the `maintainArray()` function is called at the start of each anchor period. It adds a new `collectedData` object to the array and ensures the array size does not exceed the predefined `maxSize` by removing the oldest element when necessary. This method plays an essential role in limiting memory usage and ensuring only relevant data over the desired number of periods is in the calculation window.
3. Next, the `calcAverageByTime()` function calculates the average value of elements within the `data` field for each `collectedData` object that corresponds to the same time offset from each anchor condition. This method accounts for cases where the current index of a `collectedData` object exceeds the last index of any past objects by using the last available values instead.
4. For cumulative calculations, the `averageAtTime()` function utilizes the `isCumulative` boolean parameter. If true, the `calcCumulativeSeries()` function will track the running total of the source data from the last bar where the anchor condition was met, providing a cumulative sum of the source values from one anchor point to the next.
To summarize, the `averageAtTime()` function continually stores values with their corresponding times in a `collectedData` object for each bar in the anchor period. When the anchor resets, this object is added to a larger array. The array's size is limited by the specified number of periods to be averaged. To correlate data across these periods, time indexing is employed, enabling the function to compare corresponding points across multiple periods.
█ USING THIS LIBRARY
The library simplifies the complex process of calculating relative values through its intuitive functions. Follow the steps below to use this library in your scripts.
Step 1: Import the library and declare inputs
Import the library and declare variables based on the user's input. These can include the timeframe for each period, the number of time intervals to include in the average, and whether the calculation uses cumulative values. For example:
//@version=5
import TradingView/RelativeValue/1 as TVrv
indicator("Relative Range Demo")
string resetTimeInput = input.timeframe("D")
int lengthInput = input.int(5, "No. of periods")
Step 2: Define the anchor condition
With these inputs declared, create a condition to define the start of a new period (anchor). For this, we use the change in the time value from the input timeframe:
bool anchor = timeframe.change(resetTimeInput)
Step 3: Calculate the average
At this point, one can calculate the average of a value's history at the time offset from the anchor over a number of periods using the `averageAtTime()` function. In this example, we use True Range (TR) as the `source` and set `isCumulative` to false:
float pastRange = TVrv.averageAtTime(ta.tr, lengthInput, anchor, false)
Step 4: Display the data
You can visualize the results by plotting the returned series. These lines display the non-cumulative TR alongside the average value over `lengthInput` periods for relative comparison:
plot(pastRange, "Past True Range Avg", color.new(chart.bg_color, 70), 1, plot.style_columns)
plot(ta.tr, "True Range", close >= open ? color.new(color.teal, 50) : color.new(color.red, 50), 1, plot.style_columns)
This example will display two overlapping series of columns. The green and red columns depict the current TR on each bar, and the light gray columns show the average over a defined number of periods, e.g., the default inputs on an hourly chart will show the average value at the hour over the past five days. This comparative analysis aids in determining whether the range of a bar aligns with its typical historical values or if it's an outlier.
█ NOTES
• The foundational concept of this library was derived from our initial Relative Volume at Time script. This library's logic significantly boosts its performance. Keep an eye out for a forthcoming updated version of the indicator. The demonstration code included in the library emulates a streamlined version of the indicator utilizing the library functions.
• Key efficiencies in the data management are realized through array.binary_search_leftmost() , which offers a performance improvement in comparison to its loop-dependent counterpart.
• This library's architecture utilizes user-defined types (UDTs) to create custom objects which are the equivalent of variables containing multiple parts, each able to hold independent values of different types . The recently added feature was announced in this blog post.
• To enhance readability, the code substitutes array functions with equivalent methods .
Look first. Then leap.
█ FUNCTIONS
This library contains the following functions:
calcCumulativeSeries(source, anchor)
Calculates the cumulative sum of `source` since the last bar where `anchor` was `true`.
Parameters:
source (series float) : Source used for the calculation.
anchor (series bool) : The condition that triggers the reset of the calculation. The calculation is reset when `anchor` evaluates to `true`, and continues using the values accumulated since the previous reset when `anchor` is `false`.
Returns: (float) The cumulative sum of `source`.
averageAtTime(source, length, anchor, isCumulative)
Calculates the average of all `source` values that share the same time difference from the `anchor` as the current bar for the most recent `length` bars.
Parameters:
source (series float) : Source used for the calculation.
length (simple int) : The number of reset periods to consider for the average calculation of historical data.
anchor (series bool) : The condition that triggers the reset of the average calculation. The calculation is reset when `anchor` evaluates to `true`, and continues using the values accumulated since the previous reset when `anchor` is `false`.
isCumulative (simple bool) : If `true`, `source` values are accumulated until the next time `anchor` is `true`. Optional. The default is `true`.
Returns: (float) The average of the source series at the specified time difference.
cphelperLibrary "cphelper"
ACPU helper library - for private use. Not so meaningful for others.
calculate_rr(targetArray, rrArray, breakevenOnTarget1)
calculates risk reward for given targets
Parameters:
targetArray (float ) : array of targets
rrArray (float ) : array of risk reward
breakevenOnTarget1 (simple bool) : option to breakeven
Returns: array rrArray
trendPairs(l1StartX, l1StartY, l1EndX, l1EndY, l2StartX, l2StartY, l2EndX, l2EndY, zgColor)
creates trendline pairs
Parameters:
l1StartX (int) : startX of first line
l1StartY (float) : startY of first line
l1EndX (int) : endX of first line
l1EndY (float) : endY of first line
l2StartX (int) : startX of second line
l2StartY (float) : startY of second line
l2EndX (int) : endX of second line
l2EndY (float) : endY of second line
zgColor (color) : line color
Returns:
find_type(l1t, l2t, channelThreshold)
Finds type based on trendline pairs
Parameters:
l1t (line) : line1
l2t (line) : line2
channelThreshold (simple float) : theshold for channel identification
Returns: pattern type and flags
getFlags(flags)
Flatten flags
Parameters:
flags (bool ) : array of flags
Returns: - flattened flags isChannel, isTriangle, isWedge, isExpanding, isContracting, isFlat, isRising, isFalling
getType(typeNum)
Get type based on type number
Parameters:
typeNum (int) : number representing type
Returns: String value of type
getStatus(status, maxStatus)
Get status based on integer value representations
Parameters:
status (int) : integer representing current status
maxStatus (int) : integer representing max status
Returns: String status value
calculate_simple_targets(trendLines, settingsMatrix, patternTypeMapping, patternType)
Calculate targets based on trend lines
Parameters:
trendLines (line ) : trendline pair array
settingsMatrix (matrix) : matrix containing settings
patternTypeMapping (string ) : array containing pattern type mapping
patternType (int) : pattern type
Returns: arrays containing long and short calculated targets
recalculate_position(patternTypeAndStatusMatrix, targetMatrix, index, pIndex, status, maxStatus, targetValue, stopValue, dir, breakevenOnTarget1)
Recalculate position values
Parameters:
patternTypeAndStatusMatrix (matrix) : matrix containing pattern type and status
targetMatrix (matrix) : matrix containing targets
index (int) : current index
pIndex (int) : pattern index
status (int) : current status
maxStatus (int) : max status reached
targetValue (float) : current target value
stopValue (float) : current stop value
dir (int) : direction
breakevenOnTarget1 (simple bool) : flag to breakeven upon target1
Returns: new status and maxStatus values
draw_targets(longTargets, shortTargets, index, labelColor, patternName, positionIndex, longMaxStatus, longStatus, shortMaxStatus, shortStatus, tempBoxes, tempLines, tempLabels)
Draw targets on chart
Parameters:
longTargets (matrix) : matrix containing long targets
shortTargets (matrix) : matrix containing short targets
index (int) : current index
labelColor (color) : color of lines and labels
patternName (string) : Pattern name
positionIndex (int) : position on the chart
longMaxStatus (int) : max status for long
longStatus (int) : long status value
shortMaxStatus (int) : max status for short
shortStatus (int) : short status value
tempBoxes (box ) : temporary box array
tempLines (line ) : temporary lines array
tempLabels (label ) : temporary labels array
Returns: void
populate_open_stats(patternIdArray, barMatrix, patternTypeAndStatusMatrix, patternColorArray, longTargets, shortTargets, patternRRMatrix, OpenStatPosition, lblSizeOpenTrades)
Populate open stats table
Parameters:
patternIdArray (int ) : pattern Ids
barMatrix (matrix) : matrix containing bars
patternTypeAndStatusMatrix (matrix) : matrix containing pattern type and status
patternColorArray (color ) : array containing current patter colors
longTargets (matrix) : matrix of long targets
shortTargets (matrix) : matrix of short targets
patternRRMatrix (matrix) : pattern risk reward matrix
OpenStatPosition (simple string) : table position
lblSizeOpenTrades (simple string) : text size
Returns: void
draw_pattern_label(trendLines, patternFlagMatrix, patternTypeAndStatusMatrix, patternColorArray, patternFlags, patternLabelArray, zgColor, patternType, drawLabel, clearOldPatterns, safeRepaint, maxPatternsReference)
Parameters:
trendLines (line )
patternFlagMatrix (matrix)
patternTypeAndStatusMatrix (matrix)
patternColorArray (color )
patternFlags (bool )
patternLabelArray (label )
zgColor (color)
patternType (int)
drawLabel (simple bool)
clearOldPatterns (simple bool)
safeRepaint (simple bool)
maxPatternsReference (simple int)
populate_closed_stats(patternTypeAndStatusMatrix, bullishCounts, bearishCounts, bullishRetouchCounts, bearishRetouchCounts, bullishSizeMatrix, bearishSizeMatrix, bullishRR, bearishRR, ClosedStatsPosition, lblSizeClosedTrades, showSelectivePatternStats, showPatternStats, showStatsInPercentage)
Parameters:
patternTypeAndStatusMatrix (matrix)
bullishCounts (matrix)
bearishCounts (matrix)
bullishRetouchCounts (matrix)
bearishRetouchCounts (matrix)
bullishSizeMatrix (matrix)
bearishSizeMatrix (matrix)
bullishRR (matrix)
bearishRR (matrix)
ClosedStatsPosition (simple string)
lblSizeClosedTrades (simple string)
showSelectivePatternStats (simple bool)
showPatternStats (simple bool)
showStatsInPercentage (simple bool)