Pine Script: How Can You Hide Plots?

In Pine Script, plots are the visual representations of data on your TradingView charts. While displaying data is crucial, there are scenarios where hiding plots becomes essential for a cleaner and more efficient trading experience. This article dives deep into the techniques and considerations for effectively managing plot visibility in your Pine Script indicators and strategies.

Why Hide Plots? Use Cases and Benefits

Hiding plots serves several critical purposes:

• Clarity: Decluttering the chart by removing irrelevant or redundant information.
• Conditional Analysis: Displaying specific plots only when certain conditions are met, focusing on relevant data.
• Strategy Optimization: Isolating specific components of a trading strategy during backtesting.
• User Customization: Providing users with options to selectively view the data that interests them.

Understanding Plot Visibility in TradingView

By default, all plots defined using the plot() function are visible on the chart. However, Pine Script offers mechanisms to control this visibility, allowing for dynamic and flexible chart management.

Methods for Hiding Plots

Using the display Argument in plot() function

The plot() function includes a display argument that controls plot visibility. Setting display=display.none hides the plot.

//@version=5
indicator("Simple Plot Example", overlay=true)

sma_value = ta.sma(close, 20)

plot(sma_value, title="SMA", color=color.blue, display=display.none) // Plot is hidden

Conditional Plotting with if Statements

You can use if statements to control whether a plot is generated based on specific conditions. This approach prevents the plot from being created in the first place when the condition is not met.

//@version=5
indicator("Conditional Plot", overlay=true)

show_plot = close > open

if show_plot
    plot(close, title="Closing Price", color=color.green)

In this example, the closing price is only plotted if it’s greater than the opening price.

Employing User-Defined Inputs to Toggle Plot Visibility

Create an input option to allow users to toggle plot visibility directly from the indicator settings.

//@version=5
indicator("Toggle Plot", overlay=true)

showSMA = input.bool(true, "Show SMA?")
sma_value = ta.sma(close, 20)

plot(showSMA ? sma_value : na, title="SMA", color=color.blue)

Here, a boolean input (showSMA) controls whether the Simple Moving Average (SMA) is plotted. na (not a number) is used to effectively hide the plot when showSMA is false.

Advanced Techniques and Considerations

Hiding Multiple Plots Simultaneously

For indicators with numerous plots, consider using a global input variable to control the visibility of multiple plots at once. Functions can also be utilized to reduce code duplication.

Combining Plot Hiding with Strategy Backtesting

When backtesting strategies, hiding plots can improve performance by reducing the amount of data that needs to be processed, especially when visualizing intermediate calculations isn’t necessary.

Impact of Hidden Plots on Indicator Performance

Hiding plots, especially conditionally, can positively impact indicator performance by reducing the computational overhead. However, the impact is usually negligible unless you are dealing with very complex calculations and a high number of plots.

Practical Examples and Code Snippets

Simple Moving Average with Hide/Show Option

//@version=5
indicator("SMA with Toggle", overlay=true)

length = input.int(20, title="SMA Length")
showSMA = input.bool(true, "Show SMA?")
sma_value = ta.sma(close, length)

plot(showSMA ? sma_value : na, title="SMA", color=color.blue)

Volume-Based Indicator with Dynamic Plot Control

//@version=5
indicator("Volume Indicator", overlay=false)

showVolume = input.bool(true, "Show Volume?")
avgVolume = ta.sma(volume, 30)

plot(showVolume ? volume : na, title="Volume", color=color.green, style=plot.style_columns)
plot(showVolume ? avgVolume : na, title="Avg. Volume", color=color.red)

Conclusion

Effective plot management is crucial for creating clear, efficient, and user-friendly Pine Script indicators and strategies. By mastering the techniques discussed in this article, you can optimize your charts for better analysis and decision-making.

Best Practices for Plot Management in Pine Script

• Plan Ahead: Determine which plots are essential and which can be hidden by default.
• User Customization: Provide users with options to control plot visibility.
• Conditional Logic: Use conditional plotting to display data only when relevant.
• Performance Optimization: Hide unnecessary plots during backtesting to improve performance.

Troubleshooting Common Issues

• Plot Not Hiding: Double-check the display argument and conditional logic.
• Input Not Working: Ensure the input variable is correctly used in the plot condition.
• Performance Degradation: If performance is an issue, simplify calculations or reduce the number of visible plots.