Desktop graph plotter app
1. Visualize polynomial Curves easily.
2. The application is offline , so no internet issues.
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Using Python :
If you have previously have python in your system , upgrade it to atleast 3.7A) Install Anaconda Installer
B) Create a Virtual Environment : Tutorial
C) After activating the virtual environment download the dependency libraries through the "requirements.txt" file in Shell.
$pip install -r requirements.txt
D) Then write
$pip install tkintertable
D) Clone this repository.
E) Open the base folder of the repository.
F) Then copy and paste the underlying command
$ graphly4.0.1.py
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Or you can download the .exe application straight from the releases. Unzip and use for good. If that shows any error you can download via this link - https://drive.google.com/file/d/15xGd_Lo_PbSBQH7QWgr-C6AkmvAuNQU1/view?usp=sharing . When downloading it may show virus warning, you have to discard that option and download straightaway and run it without any other requirements. P.S. This .exe only works on 64-bit operating systems.
We can update the range of coefficients and powers in the corresponding entry boxes and then apply it to get the preferable range. Then move the slider to find the actual coefficient and the power of a single variable of the polynomial equation.
A) Add Values Button : After fixing the coeffiecient and the power value we should click this button to add the variable to the equation. Like initially the equation is y = 0 , then if we click the button the then equation updates into y = Ax^B where A is coefficient and B is power.
B) Delete Values Button : Deletes the last variable of the equation . If the equation is y = Ax^B + Cx^D , then clicking this button will update the equation into y = Ax^b where where A , C is coefficient and B , D is power .
C) Restart Button : Deletes all old variables and starts new.
D) Exit Button : To shut down the application.
E) Plot Button : When you have added the variables to the equation , if you click this you will find the plot.
The canvas is where we can visualize the plot , when the plot button is clicked .