Skip to main content

A graphical and compact library for the Numworks calculator and its emulator

Project description

Visual Banner

Visual

GitHub Stars GitHub Forks GitHub Issues GitHub Pull Requests GitHub License Last Commit Visiteurs

PyPI Version PyPI - Downloads Python Versions

Welcome! This project is designed for use with the Numworks graphing calculator. It allows you to add graphical functions, mainly around new drawing functions like line or circle drawing, but also mathematical classes like vectors or points, and much more!

But it's also an easy-to-use library available on PyPi, so you don't have to code on your calculator, thanks to the Numworks python emulator for computers.

Star History Chart

Table of Contents


  1. General Info
  2. How to use it
  3. Examples
  4. Tree Fractals
  5. Extensions
  6. QR-Codes
  7. FAQs

General Info


I recommend that you test the example files on your own computer, as you can drastically increase their execution speeds.

To install it on the Numworks, we have the choice :

  1. Just follow this link to the Numworks website

  2. You just need to copy and paste the code from the visual file into a new script on your Numworks account. Then upload it to your calculator.

Here's an example of what you can do with the calculator, using the example file. Click here to see it on the Numworks website.

example_visuel.png

Here's another example of what you can do with the functions provided by Visual.

example.gif

If you have any questions, go to the FAQs section, or explore all the examples here after visiting this page to install the visualcore library on your computer !

How to use it


  1. Simply use this command :
pip install visualcore
  1. Or download the github repository in .zip or clone it via this url :
https://github.com/Archange-py/Visual.git

To use it properly, you need to install several python packages on your computer, either from the command line using the requirements.txt file :

pip install -r requirements.txt

Or individually with each package.

pip install kandinsky
pip install --pre ion-numworks

And python, of course, here if you don't already have it.

You can change the emulator's OS by pressing "CTR+O" to increase speed, so you can get the most out of it without seeing everything slow down !

Examples


First of all, after you're on your computer, you need to start by importing it after installing it in the current directory, and write that on the first line of your project :

from visual import *

After that, you need to understand how this script is organized, with points and vectors for example, and how it works, with its functions. For this purpose, you have at your disposal one Jupiter Notebook containing everything that can be shown in writing for the file visual_example. Then there are plenty of example files for everything to do with graphics. You can see the results with the following images :

Example 1 Example 2 Example 3 Example 4
example_interpolate_1.png example_interpolate_2.png example_interpolate_3.png example_interpolate_4.png

We have to take a number less or equal to 0, and greater or equal to 1 for the alpha parameter

Example 1 Example 2
example_alpha_layer_1.png example_alpha_layer_2.png
Example 1 Example 2 Example 3
example_scatter_1.png example_scatter_2.png example_scatter_3.png
Example 1 Example 2 Example 3
example_plot_1.png example_plot_2.png example_plot_3.png
Example
example_lines.png
Example
example_points.png
Example
example_croix.png
Example
example_arrows.png
Example
example_vectors.png
Example 1 Example 2
example_droite_1.png example_droite_2.png
Example
example_triangles.png
Example
example_polygones.png
Example
example_cercle.png
Example 1 Example 2
example_bezier_curve.png example_bezier_curve.gif

Tree Fractals

The link to the example script: example_fractal.py
And the source script: fractal.py


example_bezier_curve.gif


Don't forget to install the lines extension here in your computer !

Basic Tree Palm Tree
fractale_basic_tree_1.png fractale_palm_red_yellow_1.png
fractale_basic_tree_2.png fractale_palm_red_yellow_2.png
fractale_basic_tree_black_1.png fractale_palm_black_1.png
fractale_basic_tree_black_2.png fractale_palm_black_2.png

Magenta Trees

fractale_magenta_1.png fractale_magenta_2.png fractale_magenta_3.png fractale_magenta_4.png
fractale_magenta_thickness_1.png fractale_magenta_thickness_2.png fractale_magenta_thickness_3.png fractale_magenta_thickness_4.png

Cyan Trees

fractale_cyan_angle_1.png fractale_cyan_angle_2.png fractale_cyan_angle_3.png
fractale_cyan_angle_4.png fractale_cyan_angle_5.png fractale_cyan_angle_6.png
fractale_cyan_angle_7.png fractale_cyan_angle_8.png fractale_cyan_angle_9.png
fractale_cyan_angle_10.png fractale_cyan_angle_11.png fractale_cyan_angle_12.png
fractale_cyan_angle_13.png

Examples of Trees

fractale_tree_blue.png fractale_tree_cyan.png fractale_tree_fushia.png
fractale_tree_green.png fractale_tree_magenta.png fractale_tree_orange.png
fractale_tree_pink.png fractale_tree_purple.png fractale_tree_red.png
fractale_tree_yellow.png fractale_tree_white.png fractale_thickness_purple.png

Angle Tree

fractale_h_magenta_purple.png fractale_h_black.png

Extensions


Here are some extensions designed to work with the calculator. However, the latest extension, Grapher, will only work on a computer. They include a number of extra features, notably a reproduction of the turtle module, and another, much simpler one, of the matplotlib.pyplot module. I'll let you discover them with some beautiful images!

You need to copy and paste the code from the extension files into a new file created on the Numworks website.

Example
example_lines.png
Example 1 Example 2
example_ellipses_1.png example_ellipses_2.png

The turtle extension has both a compact and a non-compact file for use on the computer.


Example 1 Example 2
example_2.png example_turtle.gif
Keys Short
Arrows [Up, Down, Right, Left] allows you to move around the grapher
'Maj'+'=' or '+' zoom in or out
'Maj'+'à' or '0' refocuses the graphic
'Ctr'+'o' changes the emulator, thus increasing speed

Examples

example_fonction_axes_1.png example_fonction_axes_poo_1.png example_fonction_axes_2.png
example_fonction_axes_poo_2.png example_fonction_axes_poo_3.png example_fonction_axes_poo_4.png
example_fonction_axes_poo_5.png example_fonction_axes_poo_6.png example_fonction_scatter_and_points_2.png
example_fonction_plot_and_lines_1.png example_fonction_vector_1.png example_fonction_droite_1.png

QR-Codes


Here are two QR codes to easily find the Visual library on GitHub and on the official Numworks website. Use them without restriction!

GitHub Numworks
example_2.png example_turtle.gif

FAQs


A list of frequently asked questions (for the moment there is none).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

visualcore-1.0.1.tar.gz (2.8 MB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

visualcore-1.0.1-py3-none-any.whl (31.0 kB view details)

Uploaded Python 3

File details

Details for the file visualcore-1.0.1.tar.gz.

File metadata

  • Download URL: visualcore-1.0.1.tar.gz
  • Upload date:
  • Size: 2.8 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.2

File hashes

Hashes for visualcore-1.0.1.tar.gz
Algorithm Hash digest
SHA256 1a1eccdddd77d60446ef06d7aed88e13f2a734eb45d767304a0c28ad325a4f3f
MD5 a974110026e0fe7a1c15e911fadc0f6b
BLAKE2b-256 b703d14c91223e6f7b5c214116d8d214e50a94cacdb378844e2c5a5d040b998b

See more details on using hashes here.

File details

Details for the file visualcore-1.0.1-py3-none-any.whl.

File metadata

  • Download URL: visualcore-1.0.1-py3-none-any.whl
  • Upload date:
  • Size: 31.0 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.2

File hashes

Hashes for visualcore-1.0.1-py3-none-any.whl
Algorithm Hash digest
SHA256 a76f5e6717586205e55ed7c911e3a4af183fcc2cbe639a97cfea16b8760af5d1
MD5 cac3c85d81e45e92edc05ef692d01809
BLAKE2b-256 ca573302229795b3710077f7a8ac2744c019010f91a64cfd0b5cf172b13b6d55

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page