Skip to main content

A visualization tool for job shop scheduling problems.

Project description

DOI Python Badge PyPI version License


Job Shop Scheduling Problem Visualisations

About The Project

Ths project provides visualisation for the Job Shop Scheduling Problem (JSP). This is focused on Gantt charts. The input date for the visualisation is inspired by plotly's Gantt chart api. jsp-vis is a standalone package and in designed to be used in combination with a JSP-reinforcement learning environments that follow the Gymnasium Environment standard. The render function of the environment can be used to render the Gantt chart. Typically the render function can implement different modes like human, rgb_array or ansi rendering. The jsp-vis package offers three different visualisations: console visualisation, rgb_array visualisation and window visualisation. The window visualisation is essentially only rendering the rgb_array visualisation in a window using OpenCV. The console visualisation might be used for the asni mode of a render function, the rgb_array visualisation for the rgb_array mode and the window visualisation for the human mode.

Installation

Install the package with pip:

   pip install jsp-vis

Minimal Working Example: console visualisation

from jsp_vis.console import gantt_chart_console
import pandas as pd

df = pd.DataFrame([
   {'Task': 'Job 0', 'Start': 5, 'Finish': 16, 'Resource': 'Machine 0'},
   {'Task': 'Job 0', 'Start': 28, 'Finish': 31, 'Resource': 'Machine 1'},
   {'Task': 'Job 0', 'Start': 31, 'Finish': 34, 'Resource': 'Machine 2'},
   {'Task': 'Job 0', 'Start': 34, 'Finish': 46, 'Resource': 'Machine 3'},
   {'Task': 'Job 1', 'Start': 0, 'Finish': 5, 'Resource': 'Machine 0'},
   {'Task': 'Job 1', 'Start': 5, 'Finish': 21, 'Resource': 'Machine 2'},
   {'Task': 'Job 1', 'Start': 21, 'Finish': 28, 'Resource': 'Machine 1'},
   {'Task': 'Job 1', 'Start': 28, 'Finish': 32, 'Resource': 'Machine 3'}
])
num_of_machines = 4

gantt_chart_console(df, num_of_machines)

The code above will render the following Gantt chart in the console:

Minimal Working Example: console visualisation

from jsp_vis.cv2_window import render_gantt_in_window
import pandas as pd

df = pd.DataFrame([
   {'Task': 'Job 0', 'Start': 5, 'Finish': 16, 'Resource': 'Machine 0'},
   {'Task': 'Job 0', 'Start': 28, 'Finish': 31, 'Resource': 'Machine 1'},
   {'Task': 'Job 0', 'Start': 31, 'Finish': 34, 'Resource': 'Machine 2'},
   {'Task': 'Job 0', 'Start': 34, 'Finish': 46, 'Resource': 'Machine 3'},
   {'Task': 'Job 1', 'Start': 0, 'Finish': 5, 'Resource': 'Machine 0'},
   {'Task': 'Job 1', 'Start': 5, 'Finish': 21, 'Resource': 'Machine 2'},
   {'Task': 'Job 1', 'Start': 21, 'Finish': 28, 'Resource': 'Machine 1'},
   {'Task': 'Job 1', 'Start': 28, 'Finish': 32, 'Resource': 'Machine 3'}
])
num_of_machines = 4

render_gantt_in_window(
        df=df,
        n_machines=num_of_machines,
        wait=2000 # time in ms that the `cv2`-window is open.
        # wait=None # ''None'' will keep the window open till a keyboard occurs.
    )

The code above will render the following Gantt chart in the console:

More Examples

For more examples you can have a look at the test files in the tests directory. Every visualisation has its own test file and is tested on two different jsp instances defined in the conftest.py.

License

Distributed under the MIT License. See LICENSE.txt for more information.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

jsp_vis-1.2.0.tar.gz (11.2 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

jsp_vis-1.2.0-py3-none-any.whl (9.6 kB view details)

Uploaded Python 3

File details

Details for the file jsp_vis-1.2.0.tar.gz.

File metadata

  • Download URL: jsp_vis-1.2.0.tar.gz
  • Upload date:
  • Size: 11.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.14

File hashes

Hashes for jsp_vis-1.2.0.tar.gz
Algorithm Hash digest
SHA256 8d75e96e70cc43c42455bef52dc4cd489f56c8328f3dcedee2287d5b4c905915
MD5 aa767c7570ecde13f0c440ff66d4a420
BLAKE2b-256 04e8587230a46e036ebe6106c1a91cc256048b8ee4e17c3a5b9de59163a8d6dd

See more details on using hashes here.

File details

Details for the file jsp_vis-1.2.0-py3-none-any.whl.

File metadata

  • Download URL: jsp_vis-1.2.0-py3-none-any.whl
  • Upload date:
  • Size: 9.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.14

File hashes

Hashes for jsp_vis-1.2.0-py3-none-any.whl
Algorithm Hash digest
SHA256 9097c65404f5f838676b298b0a22240799ec7fd332c8f6d1872976f512e5afc3
MD5 da7050f3bf740b70e6be6c55d490fd72
BLAKE2b-256 89e471bf6dd691bad92ee69da676e280b91bdc3ea7bb4ef467887a2f86cdb2ed

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page