Metadata-Version: 2.1
Name: linear-transforms
Version: 0.0.1
Summary: Python coordinate frame transform library
Home-page: https://github.com/antonlopezr/transforms
Author: Antonio Lopez Rivera
Author-email: antonlopezr99@gmail.com
License: UNKNOWN
Description: # Transforms: Python coordinate frame transform library
        
        ![alt text](tests/coverage/coverage.svg ".coverage available in tests/coverage/")
        
        Library to ease work with 3D coordinate frame transformations, by two means:
        - Easy-to-operate-with symbolic/numerical linear transformation classes
        - LaTeX export and enhanced console printing of transformation matrices
        
        Nice experiment to learn about operator overloading.
        
        `Antonio Lopez Rivera, 2020`
        
        ---
        
        [ 1. Install ](#1-install)
        
        [ 2. Usage and Syntax ](#2-usage-and-syntax)
        
        [ 3. To-do ](#3-to-do)
        
        ## 1. Install
        
        1. Place `transforms.py` and `utilities.py` in your root directory (or another, but mind the import)
        2. `from transforms import Tx, Ty, Tz`
        
        ## 2. Usage and Syntax
        
        All code available in `demo.py`.
        
        ### `2.1 Creating a Linear Transformation`
        
        Transformation describing the position of a rotated object (by angle `a`) from its original frame of reference:
        
            Ta = Tx(a)
            
        The linear transformation class may be initialized with a `Sympy.Symbol`, or regular values for the rotation angle
        
        ### `2.2 Lambdifying a symbolic linear transformation`
        
        Turning a symbolic linear transformation to a numerical one can be done by calling the transformation itself.
        
            T_num = Ta(<VALUE>)
        
        ### `2.3 Operating with Linear Transformations`
        
        Transform concatenation is defined with the multiplication sign, as well as the addition sign. The multiplication notation is recommended.
        
            Tt = Ta*Tb*Tc
            TT = Ta+Tb+Tc
            
            Tt == TT
            
        Transform multiplication with NumPy or SymPy arrays is defined with the multiplication sign alone.
        
            r = np.array([1, 1, 1])
            
            r_tr = Tt*r
            
        ### `2.4 Inspecting matrices`
        
        #### _LaTeX_
        
        Transformations, symbolic and numerical, can be outputed to LaTeX with the function call below. The latex equation will be visible in the terminal in light blue.
        
            r_tr.to_latex()
        
        #### _Printing_
        
        Printing a transformation will output an ASCII representation in the terminal
        
            print(r_tr)
        
        ## 3. To-do
        
        1. n-dimensional transform matrix generation
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
