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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: kaikerochaalves@outlook.com or kaike.alves@estudante.ufjf.br

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.plot_and_save()

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.

Metadata

Release files for ishikawa 0.0.5

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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