Visualize

This class wrap the Pytorch Tensorboard class.

Present the simulation results on Tensorboard is so easy and interactive with

Create log file and log signal

from OpenControl.visualize import Logger

logX = Logger(log_dir='results')
for i in range(100):
    logX.log('euler', [i*np.cos(i), i*np.sin(i)], i)
logX.end_log()

Analysis simulation on Tensorboard

Note

If you run the code on Google Colab shell, just load Tensorboard first

%load_ext tensorboard

then run this shell to show

%tensorboard --logdir results

Usage

_images/TensorboardUsage.png
class OpenControl.visualize.Logger(log_dir='results', filename_suffix='')

Bases: object

Real-time visualize simulation results, using Tensorboard

writer

the same as SummaryWriter

Type

class

__init__(log_dir='results', filename_suffix='')

The same as SummaryWriter

Parameters
  • log_dir (str, optional) – the direction to save the log file. Defaults to ‘results’ folder.

  • filename_suffix (str, optional) – suffix added to the name of log file. Defaults to ‘’.

end_log()

Call this function to end logging

log(section, signals, step)

Log the signals with the name of section in the step time

Parameters
  • section (str) – name of signals

  • signals (array) – signals

  • step (int) – only int type is acceptable. Please convert float timestep to int