Use this linear interpolation calculator to find a value between known data points. Get accurate results and visual representation.

Linear Interpolation

Purpose

The Linear Interpolation function helps in estimating unknown values that fall between known values. It is commonly used to find values within a set of data points.

Use Cases

• Estimating values between known data points
• Creating a smooth curve between data points

How to Use

1. Enter the known x and y values in the provided fields.
2. Input the x value for which you want to estimate the y value.
3. Click on the calculate button to get the result.

Input Values

1. X Values: Enter the known x values separated by commas (e.g., 1, 2, 3.2)
2. Y Values: Enter the corresponding y values separated by commas (e.g., 2, 3, 5.8)
3. X Value to Interpolate: Enter the x value for which you want to estimate the y value.

Output Values

1. Result: The estimated y value based on the linear interpolation.
2. Chart: A graphical representation of the known data points and the estimated value.

Any other Instruction

• Ensure that the x values are in ascending order.
• The default unit of measurement is inches.

Code Analysis

1. Convert input x and y values to floating-point arrays.
2. Use NumPy's interpolation function to calculate the estimated y value.
3. Plot the known data points and the estimated value on a chart.

Technical Parameters

x_values, y_values, x

Return Values

Result, chart

Example Expressions

You can use the following expressions to directly evaluate in a non-interactive manner using eva():

linter('1,2,3.2,4,5', '2,3,5.8,12,20', 2.5)
linter('0,1,2,3,4', '5,7,9,11,13', 2.2)

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