ishikawa 0.0.1

Ishikawa is a library used to draw a fish (also known as ishikawa) diagram

Ishikawa: package to design ishikawa diagram based on matplotlib

Project description

Author: Kaike Sa Teles Rocha Alves (adapted from matplotlib)

Ishikawa: package to design ishikawa diagram based on matplotlib developed by Kaike Alves adapted from matplotlib (https://matplotlib.org/stable/gallery/specialty_plots/ishikawa_diagram.html).

Author: Kaike Sa Teles Rocha Alves (PhD)
Email: [e-mail] or [e-mail]

Github repository: https://github.com/kaikerochaalves/Ishikawa.git

Cite:

Description:

Ishikawa: package to design ishikawa diagram based on matplotlib.

Instructions

To install the library use the command:

pip install ishikawa

To import type:

from ishikawa.diagram import Ishikawa

Hyperparameters:

data : dict
A dictionary of problem categories and their associated causes.

figsize : tuple, optional
The size of the plot figure.

Example of Ishikawa:

from ishikawa.diagram import Ishikawa

# Define categories
categories = {
    'Method': ['Time consumption', 'Cost', 'Procedures', 'Inefficient process', 'Sampling'],
    'Machine': ['Faulty equipment', 'Compatibility'],
    'Material': ['Poor-quality input', 'Raw materials', 'Supplier', 'Shortage'],
    'Measurement': ['Calibration', 'Performance', 'Wrong measurements'],
    'Environment': ['Bad conditions'],
    'People': ['Lack of training', 'Managers', 'Labor shortage', 'Procedures', 'Sales strategy']
}

# Create an instance of the diagram
fishbone_diagram = Ishikawa(categories)

# Call the draw method to generate the plot
fishbone_diagram.draw()

# Show the plot
fishbone_diagram.show()

Note: Do not use more than 6 categories or 5 causes per category. Otherwise you are going to have issues with formatting.

Extra information

The fuzzy models are quite fast, but the genetic and ensembles are still a bit slow. If you think you can contribute to this project regarding the code, speed, etc., please, feel free to contact me and to do so.

Code of Conduct:

Please read the Code of Conduct for guidance.

Call for Contributions:

The project welcomes your expertise and enthusiasm!

Small improvements or fixes are always appreciated. If you are considering larger contributions to the source code, please contact by email first.