Line Resample

Overview

This transform resamples a line to either simplify its geometry or to ensure it has points that are evenly spaced.

Detailed Description

Line resampling is a common operation in data processing, used to either reduce the number of points in a line (simplification) or to create a new line with a specific number of points or spacing. This transform provides two different algorithms for resampling:

  • Fixed Spacing: This algorithm creates a new line with points that are a fixed distance apart. This is useful for standardizing the number of points in a line, or for preparing a line for further analysis that requires a uniform distribution of points.
  • Douglas-Peucker: This algorithm simplifies a line by removing points that are close to the line segment. This is useful for reducing the complexity of a line while preserving its overall shape.

Neuroscience Use Cases

In neuroscience, line resampling can be used in a variety of applications:

  • Whisker Tracking: When tracking the movement of a whisker, the output is often a line with a variable number of points. Resampling the line to a fixed number of points can be useful for standardizing the data for further analysis, such as calculating the curvature or angle of the whisker over time.
  • Dendrite Tracing: When tracing the path of a dendrite from a neuron, the resulting line can be very complex. The Douglas-Peucker algorithm can be used to simplify the line, making it easier to visualize and analyze the overall shape of the dendrite.
  • Animal Tracking: When tracking the path of an animal in an open field, the resulting line can be very long and detailed. Resampling the line can help to smooth out the path and reduce the amount of data that needs to be processed.

Parameters

This transform has the following parameters:

  • algorithm: The resampling algorithm to use. This can be one of the following:
    • FixedSpacing: Resamples the line to have points that are a fixed distance apart.
    • DouglasPeucker: Simplifies the line using the Douglas-Peucker algorithm.
  • target_spacing: The desired distance between points in the resampled line. This parameter is only used when the algorithm is set to FixedSpacing.
  • epsilon: The tolerance for the Douglas-Peucker algorithm. This parameter is only used when the algorithm is set to DouglasPeucker. A larger value of epsilon will result in a more simplified line.

Example Configuration

Here is a complete example of a JSON configuration file that could be used to run this transformation. This example resamples a line to have points that are 15 pixels apart.

[
    {
        "transformations": {
            "metadata": {
                "name": "Line Resample Pipeline",
                "description": "Test line resampling on line data",
                "version": "1.0"
            },
            "steps": [
                {
                    "step_id": "1",
                    "transform_name": "Resample Line",
                    "phase": "analysis",
                    "input_key": "test_lines",
                    "output_key": "resampled_lines",
                    "parameters": {
                        "algorithm": "FixedSpacing",
                        "target_spacing": 15.0,
                        "epsilon": 2.0
                    }
                }
            ]
        }
    }
]