semvec/pypi-packages huggingface dataset:
easy-trilateration 0.1.4
Easy Least-Squares trilateration using scipy
License: MIT


# easy-trilateration
Trilateration example using least squares method in scipy (Graphing tools included).

![](https://github.com/agusalex/easy-trilateration/blob/master/images/img2.png?raw=true)

Trilateration enables the unknown point to be found. However a since there are a number of samples a non linear least squares method needs to be used to find the solution that has the least error. 

It is distinct from triangulation which has a series of angles to an unknown point. Trilateration uses a series of distances to an unkown point.

## How to install

    pip install easy_trilateration


## How to use
### Simple Trilateration
    from easy_trilateration.model import *  
    from easy_trilateration.least_squares import easy_least_squares  
    from easy_trilateration.graph import *  
      
    if __name__ == '__main__':  
        arr = [Circle(Point(100, 100), 50),  
      Circle(Point(100, 50), 50),  
      Circle(Point(50, 50), 50),  
      Circle(Point(50, 100), 50)]  
        result, meta = easy_least_squares(arr)  
        create_circle(result, target=True)  
        draw(arr)
### Location History
    arr = Trilateration([Circle(100, 100, 70.5),
                         Circle(100, 50, 50),
                         Circle(50, 50, 0),
                         Circle(50, 100, 50)])

    arr2 = Trilateration([Circle(100, 100, 50),
                          Circle(100, 50, 70.5),
                          Circle(50, 50, 50),
                          Circle(50, 100, 0)])

    arr3 = Trilateration([Circle(100, 100, 0),
                          Circle(100, 50, 50),
                          Circle(50, 50, 70.5),
                          Circle(50, 100, 50)])

    arr4 = Trilateration([Circle(100, 100, 50),
                          Circle(100, 50, 0),
                          Circle(50, 50, 50),
                          Circle(50, 100, 70.5)])

    hist: [Trilateration] = [arr, arr2, arr3, arr4, arr]

    solve_history(hist)

    a = animate(hist)

![](https://github.com/agusalex/easy-trilateration/blob/master/images/img3.png?raw=true)

## Method
This code uses the [scipy.optimize.least_squares](https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.least_squares.html) method.
bonnibel 3.0.2
Build script generator for the jsix operating system
License: MIT
Keywords: build,ninja,generator

# Bonnibel

Bonnibel (`pb` for short) builds [Ninja][] build files for a set of modules.
Bonnibel doesn't try to hide Ninja's build files or syntax from the user. It
mostly exists to do the legwork of auto-generating all the build rules, while
letting the user control the variables used or even write custom rules.
Bonnibel's configs let you define a _project_, and a set of _modules_ within
that project to be built. You must also specify a _configuration_ file to set
the base compilation programs and arguments for earch _target_ platform.

For example, Bonnibel was created for [jsix][], where I needed the ability to
build tools or libraries for my multiple target environments (e.g., for use
both in the UEFI bootloader and in the kernel), while building the bootloader,
kernel and user-space applications all with different compiler and linker
options. See jsix's build files for an example of use.

[Ninja]: https://ninja-build.org
[jsix]: https://github.com/justinian/jsix