This article dives deep into its syntax, overloads, and practical applications of array.sum()
.
Syntax and Overloads
The array.sum()
function in Pine Script is designed to calculate the sum of elements within an array. It supports two primary data types: int
(integer) and float
(floating point numbers). Depending on the array’s data type, the function can return a sum in the form of a series float
or a series int
. Here’s a look at the syntax:
array.sum(id) → series float
array.sum(id) → series int
Arguments
id
(array<int/float>
): Represents the array object whose elements are to be summed up.
Example
To elucidate the functionality of array.sum()
, let’s consider a practical example:
//@version=5 indicator("Sum Array Example") sumArray = array.new_float(0) for index = 0 to 9 array.push(sumArray, close[index]) plot(array.sum(sumArray))
Walkthrough
sumArray = array.new_float(0)
: Initializes an empty floating-point array.for index = 0 to 9
: Iterates through the last 10 bars.array.push(sumArray, close[index])
: Adds the closing price of each bar tosumArray
.plot(array.sum(sumArray))
: Computes and plots the sum of the elements insumArray
.
Key Features and Takeaways
- Function Useability: The
array.sum()
function simplifies the process of aggregating values in an array, making it invaluable for summarizing data points within a given dataset. - Syntax and Application: With support for
int
andfloat
arrays, it caters to a wide range of numerical data types, ensuring flexibility in its application. - Practical Example: Through the example provided, it’s clear how
array.sum()
can be leveraged to sum up a series of closing prices, demonstrating its practicality in financial data analysis.
In conclusion, the array.sum()
function in Pine Script is a powerful tool for data aggregation. Its ability to handle both integers and floating-point numbers makes it versatile, and when applied as shown in the example, it can significantly aid in the analysis and visualization of financial data.