Function Plugins

What Function Plugins Do

Function plugins transform one selected table column into another table column. In the main window, the user selects:

an input column,
an output column,
a function from the Functions dropdown,
an optional multiplier and offset.

PhysPlot reads the input column as a one-dimensional numeric array, calls the plugin’s transform(values) function, then writes the returned values into the output column.

Layman Example

If column 1 contains time and column 2 contains voltage, a function plugin can create a new column containing voltage squared or baseline removed voltage. The plugin only needs to know how to transform one list of numbers.

Required File Location

Put new function files in:

functions/

Use a clear filename, for example:

functions/15_normalize.py

Required Structure

Every function plugin should define:

DISPLAY_NAME: Text shown in the PhysPlot Functions dropdown.
DEFAULT_LABEL: Default label used by the app when a label is needed.
transform(values): Function that receives a one-dimensional numeric sequence and returns a sequence of the same length.

Minimal Template

"""Normalize transform for PhysPlot."""

import numpy as np

DISPLAY_NAME = "Normalize"
DEFAULT_LABEL = "Normalized"


def transform(values):
    """transform(values) -> numpy.ndarray

    Normalize the selected table column between 0 and 1.

    Parameters:
        values (Sequence[float]): One-dimensional selected table column.

    Returns:
        numpy.ndarray: Normalized values with the same length as input.
    """
    values = np.asarray(values, dtype=float)
    minimum = np.nanmin(values)
    maximum = np.nanmax(values)
    if maximum == minimum:
        return np.zeros_like(values)
    return (values - minimum) / (maximum - minimum)

Practical Rules

Return the same number of values that you received.
Use numpy.asarray(values, dtype=float) if you need NumPy operations.
Avoid changing files, opening windows, or modifying the table directly.
Handle edge cases such as blank columns, zeros, or repeated values.

Existing Examples

See:

functions/01_identity.py
functions/05_log10.py
functions/14_xrd_baseline_remove.py