Package: pyrandonaut
PyRandonautOpen-source quantum random coordinate generation for randonauts ❤️This is a Python3 module for generating quantum random coordinates. It interfaces with the QRNG at Randonautica where it gets a list ofquantum randomnumbers, converts them to coordinates and then computes thegaussian kernel density estimateof those coordinates to find a point with a statistically anomalous density, similar to how an Attractor point is generated byRandonautica.This gives you the ability to implement quantum random coordinates in your own applications. Justimport pyrandonautand off you go!If you're unfamiliar with Randonautica, the concepts of Probability Blind-Spots and Quantum Randomness, I recommend readingfatum_theory.txtwhich shipped with the original Fatum Project bot that inspired Randonautica.This videogives a lot of great background info too. If you have no idea what any of this is about and is completely new to this, watchthis videoand/or readthis article.Contributions greatly appreciated!Table of contentsIntroductionInstallationUsageAs moduleCommand line interfaceVisualizationTo-doInstallationThe module requires at least Python 3.9 to function and can be installed usingpiplike so:pip install pyrandonautThat's it!UsageAs moduleImport the module:import pyrandonautYou can now call the module functions, e.g.:# Define a starting pointmy_latitude=51.178840902136464my_longitude=-1.8261452442305293# Call get_coordinate() with starting point values and store the resultresult=pyrandonaut.get_coordinate(my_latitude,my_longitude)# Print result to screenprint(f"Go here to escape the stasis field:{result}")get_coordinate()will return a tuple with the calculated coordinate. By default it uses a radius of 5000 meters and a value of 1024 random points to base the calculation on. These values can be specified in the arguments.Functions and arguments:get_coordinate()is the main functionality of the library, generating a coordinate equivalent to an Attractor point in Randonautica. It takes the following arguments:start_latLatitude of starting position (float)start_lonLongitude of starting position (float)radiusMax radius from starting position (integer)num_pointsNumber of random points to use in calculation of kernel density estimate. Must be divisible by 1024 (integer)It returns a tuple in the following format:(latitude, longitude)random_location()Converts 2 floating point values to coordinates within
the defined radius from the starting position. It takes the following arguments:start_latLatitude of starting position (float)start_lonLongitude of starting position (float)radiusMax radius from starting position (integer)rand_float_1Random value to turn into X in coordinaterand_float_2Random value to turn into Y in coordinateIt returns a tuple in the following format:(latitude, longitude)Command-line interfaceYou can also run PyRandonaut directly in your terminal.
Example:$pythonpyrandonaut.py51.178840902136464-1.826145244230529351.20545110291186, -1.824335160309919Run the script with--helpto see the options:$pythonpyrandonaut.py--helpusage: pyrandonaut.py [-h] [-r RADIUS] [-p POINTS] [-v] LATITUDE LONGITUDEThis script interfaces with the Quantum Random Number Generator at the The Australian National University, where it gets a list of quantum random numbers, converts them to coordinates and computes the gaussian kernel density estimate of those coordinates, returning the point within the defined radius, where the density of random coordinates is highest, similar to how an Attractor point is calculated by Randonautica.positional arguments:LATITUDE    starting position latitudeLONGITUDE   starting position longitudeoptions:-h, --help  show this help message and exit-r RADIUS   max radius from starting position in meters-p POINTS   number of points to base KDE on (must be divisible by 1024)-v          verbose loggingVisualizationThis is a heatmap visualization of how the module calculates the Attractor point. An arbitrary number of points based on QRNG numbers are plotted geospatially and the place with the highest density of points is returned.  Image made usingSeabornandthis script(BETA).To-doGet people excited about the project!Add more QRNG sources (If you can help supply hardware modules for testing, please get in touch!)Make requests to ANU QRNG API asynchronousImplement heatmap generation fromopenrandonaut-botAdd ability to calculate Void and Power points as well