Ishikawa is a library used to draw a fish (also known as ishikawa) diagram
Reason this release was yanked:
outdated version
Project description
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.
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