frc1678-lime-plotter 0.5.8

A matplotlib based plotter for FRC logs and networktables

Overview

The lime-plotter application plots data collected from robots in the First Robotics Competitions and plots them to the screen or to a PNG file. It can read data from CSV based log files, or via a networktables server (IE, from a robot over its wireless network).

Usage

Installation

Install any needed modules and the lime-plotter itself:

pip3 install --user --upgrade frc1678-lime-plotter

Things to plot are specified either via complex command line arguments with the -p switch, or via easier-to-read-and-write YAML configuration files (see the example below).

Reading from logs

lime-plotter.py can be run with a -L switch to load CSV files from a file, multiple files, or a directory. EG calling it as:

lime-plotter.py -L DIR

Will load all the files it can from the DIR directory. Table names will be assumed from the CSV file names.

Reading from FRC network tables

To read from a network table, use the -N switch to specify the network address to connect to, and optionally a -T switch to specify a default table to read from.

lime-plotter.py -N 10.0.0.1 -t nettable

Listing available tables / columns

This works for both NetworkTables and CSV logs:

lime-plotter.py -N 10.0.0.1 -l

Example configuration

The following are YAML file configuration examples.

Example single graph

The following example configuration file specifies a single plot called position and plots two overlayed graphs from the robot's drivetrain_status table:

plots:
  position:
    - x: estimated_x_position
      y: estimated_y_position
      xmax: 7
      xmin: -7
      ymax: 7
      ymin: -7
      table: drivetrain_status
      fixedAspect: True
      title: X/Y Test
    - x: profiled_x_goal
      y: profiled_y_goal
      table: drivetrain_status
      last: 100

Saving this to xy.yml and running lime-plotter.py to load logs from a 'log' directory as follows:

lime-plotter.py -L log -y xy.yml -o xytest.png

Might produce the following graph:

Example multiple graphs

To display multiple plots, configuration files can contain multiple named entries. Note that in this case the tool will try and find the right table for you; I.E. you don't need to specify the table or even x column if you don't wish.

plots:
  velocity:
    - y: linear_velocity
    - y: angular_velocity
      title: Velocity
  elevator:
    - y: elevator_height
      title: elevator Height

And run with

lime-plotter.py -L log -y multiple.yml -o multiple.yng

Will produce a graph similar to the following:

Note: you can use the -Y flag to plot only a selected set of sections of the YAML file. EG lime-plotter.py -L log -y multiple.yml -Y velocity will plot only the first graph.

Including an svg image (such as a field map)

Can be done with a 'data_source' entry inside a plot:

plots:
  - data_source: svg
    file: 2020map.svg
    xmax: 629.25 # scale svg to these dimensions
    ymax: 323.25 # (2020 dimensions in inches)
    alpha: .5

Here's a copy of the FRC 2020 map as a plottable SVG:

Including built in maps

The following map files can be specified without actually having a file present, as they're included in the package data:

• 2019map.svg
• 2020map.svg (just the playing field)
• 2020map-rev.svg (reverses the playing field top to bottom)
• 2020map-full.svg (the full field with human areas)

adding offsets for your robot's starting position

When your robot starts at a point in the field, you can adjust it's xoff and yoff values to set the offsets into the field, with 0,0 being in the bottom left.

plots:
  position:
    - x: Robot X
      y: Robot Y
      xoff: 100
      yoff: 50
      fixedAspect: true

Animation

When plotting from networktables or with the -a switch applied, a window will open that will animate the data flowing over time (live in the case of networktables). You can use the -f switch to change the frame rate (when graphing CSV files, it'll draw faster with higher values -- the default is 20; when drawing from network tables it'll use this value as the polling frequency, and should be set to the same number of milliseconds that the robot is using to update tables).

time markers

You can turn on time markers, that mark bigger dots every N seconds with configuration like:

plots:
  timemarkers:
    # plot the regular robot x/y coordinates
    - x: Robot X
      y: Robot Y
      fixedAspect: true

    # Plot a larger (size 20) dot every 1 second ontop the Robot X/Y marks
    - data_source: timer
      marker_size: 20
      x: Robot X
      y: Robot Y
      delta: 1