PINE LIBRARY
Actualizado Pivot
This library was designed to create three different datasets using Bill Williams fractals. The goal is to spot trends in reversal data and ultimately use these datasets to help predict future price reversals.
First, the pivot() function is used to initialize and populate three separate arrays (high pivot[H], low pivot[L], all pivots[A]). Since each high/low price depends on the bar_index, the bar_index, pivot direction(high/low), and high/low values are compressed into a string to maintain the data's integrity ("<bar_index>_<direction>_<price>"). Once each string array is populated and organized by bar_index, all three are returned inside a tuple. The return value must be deconstructed H,L,A=pivot() for each array's values to be accessed using getPivot(). This boilerplate allows for data to be accessed more efficiently in a recursive environment. getPivot() was designed to be used inside of a for or while block to populate matrices for further analyses. Again, getPivot() return values must be exposed through deconstruction. x,d,y=getPivot(). See code for more details.
pivot(int XLR) initializes and populates arrays
Parameters
Returns - tuple[string[]]
getPivot(string[] arrayID, int index) accesses array data
Parameters
Returns - tuple[float,string,float]
First, the pivot() function is used to initialize and populate three separate arrays (high pivot[H], low pivot[L], all pivots[A]). Since each high/low price depends on the bar_index, the bar_index, pivot direction(high/low), and high/low values are compressed into a string to maintain the data's integrity ("<bar_index>_<direction>_<price>"). Once each string array is populated and organized by bar_index, all three are returned inside a tuple. The return value must be deconstructed H,L,A=pivot() for each array's values to be accessed using getPivot(). This boilerplate allows for data to be accessed more efficiently in a recursive environment. getPivot() was designed to be used inside of a for or while block to populate matrices for further analyses. Again, getPivot() return values must be exposed through deconstruction. x,d,y=getPivot(). See code for more details.
pivot(int XLR) initializes and populates arrays
Parameters
- XLR - number of bars to the left and right that must be lower for a high to be considered a pivotHigh, or vice versa. This number will drastically change the size and scope of the returned datasets. smaller values will produce much larger datasets, which might model short term price activity well. In contrast, larger values will produce smaller datasets which might model longer term price activity well.
Returns - tuple[string[]]
getPivot(string[] arrayID, int index) accesses array data
Parameters
- arrayID - the variable name for one of the three arrays returned by pivot().
- index - the index of the provided array, with 0 being the most recent pivot point. can be set to "i" in a loop to access values recursively
Returns - tuple[float,string,float]
Notas de prensa
v2Notas de prensa
v3Added:
init()
get()
Removed:
pivot()
getPivot()
Notas de prensa
v4Biblioteca Pine
Fiel al espíritu de TradingView, el autor ha publicado este código de Pine como biblioteca de código abierto, para que otros programadores de nuestra comunidad puedan reutilizarlo. ¡Enhorabuena al autor! Puede usar esta biblioteca de forma privada o en otras publicaciones de código abierto, pero su reutilización en publicaciones está sujeta a nuestras Normas internas.
Exención de responsabilidad
La información y las publicaciones no constituyen, ni deben considerarse como, asesoramiento o recomendaciones financieras, de inversión, de trading u otro tipo, proporcionadas o respaldadas por TradingView. Obtenga más información en Condiciones de uso.
Biblioteca Pine
Fiel al espíritu de TradingView, el autor ha publicado este código de Pine como biblioteca de código abierto, para que otros programadores de nuestra comunidad puedan reutilizarlo. ¡Enhorabuena al autor! Puede usar esta biblioteca de forma privada o en otras publicaciones de código abierto, pero su reutilización en publicaciones está sujeta a nuestras Normas internas.
Exención de responsabilidad
La información y las publicaciones no constituyen, ni deben considerarse como, asesoramiento o recomendaciones financieras, de inversión, de trading u otro tipo, proporcionadas o respaldadas por TradingView. Obtenga más información en Condiciones de uso.