Metadata-Version: 2.1
Name: pymvil
Version: 0.0.1
Summary: Multivariate Interpolation with Limits
Author-email: Vamsee Achanta <vamsee.achanta@aceengineer.com>
License: MIT License        
        Copyright (c) 2022 Vamsee Achanta        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:        
        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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        SOFTWARE.        
Project-URL: repository, https://github.com/vamseeachanta/pymvil
Project-URL: documentation, https://github.com/vamseeachanta/pymvil/blob/main/README.md
Keywords: Multivariate Interpolation,variable value at response limit,limiting operating conditions
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Requires-Python: >=3.7
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: pyyaml
Requires-Dist: pandas
Requires-Dist: numpy
Requires-Dist: plotly
Requires-Dist: tomli ; python_version < "3.11"
Provides-Extra: build
Requires-Dist: build ; extra == 'build'
Requires-Dist: twine ; extra == 'build'
Provides-Extra: dev
Requires-Dist: black ; extra == 'dev'
Requires-Dist: bumpver ; extra == 'dev'
Requires-Dist: isort ; extra == 'dev'
Requires-Dist: pytest ; extra == 'dev'

# pymvil

A Multi-Variate Interpolation for Limits (PYMVIL)
- Helps to interpolate data over a number of dependent and independent variables. 
- Interpolation method of piecewise linear is available
- The algorithm assumes that the filter variable values in coords exist in data and are same

# Usage

See https://github.com/vamseeachanta/pymvil/blob/master/src/pymvil/tests/test_mvil_csv_no_monotonic_trend.py

# Improvements

**#TODO**
- Further visualizations can be added to verify data results
    - Parameter (and detailed) charts can be converted to 3D charts to include the independent variable trends to verify output 
- Response of independent variable defined as greater than and less than (ge, le) can help create provide more flexibility to module. Currently acceptance trend is determined by assuming the first value of the group (irrespective of greater or lesser than limit) is acceptable.




### References


https://www.geeksforgeeks.org/3d-scatter-plot-using-plotly-in-python/
