Visualizations of some specific solutions of different differential equations.

Overview

Diff_sims

Visualizations of some specific solutions of different differential equations.

Heat Equation in 1 Dimension

(A very beautiful and elegant explanation for the heat equation and its solution is given here

  • The heat diffusion equation gives us the temperature at every part of a conducting 1 dimensional material (specific to the current discussion), given we specify the initial condition, and the boundary conditions.
  • The thing to be noted here is that the differential equation has a doble derivative with respect to position and a single derivative with respect to time.
  • Hence, one can say that the curvature of the position function and the slope of the time function (of course, assuming one is able to write the solution as independent functions of position and time, which we can) are the key playing factors which determine how the temperature gets diffused, so to speak.
  • The co-efficient D is the thermal diffusivity constant, and here, can be thought of to be some positive constant. (Let's henceforth assume D = 1)

heat_eqn

The Gaussian

  • If the initial temperature distribution were to be in the form of a gaussian:

gauss

This function looks like a bell shaped curve centred at the origin. In other words, it tells us that at the very centre of the rod, the temperature is the highest, and as we move along in either direction it decreases very fast, and some distance from the centre, the temperature is almost zero. This ditribustion might be due to a source which is in contact with the conductor initially, exactly at the centre.

Laying off rigor (we haven't discussed about the boundary conditions here, but a gaussian converges rather rapidly as the magnitude of x increases, so essentially we can assume that the function tends to zero at its boundaries), the solution can be written in the following manner (setting certain constats to 1):

Soln

The denominator in the exponential part, actually tells us how much spread out the bell shape is, the higher it's value, more spread out it will be. The factor multiplied in the beginning is a normalizing factor, which makes sure that the energy remains constant at all times.

Hence, intuitively, we can see that as time increases, the temperature function smooths out.

  • The above solution is by no means accurate but it helps us understand the behavior.

  • One more thing to be noted, is that as the heat starts spreading, it takes more and more time for it to move farther. This is because temperature is an axponentially decaying function of time. Link to simulation here

Extract and visualize information from Gurobi log files

GRBlogtools Extract information from Gurobi log files and generate pandas DataFrames or Excel worksheets for further processing. Also includes a wrapp

Gurobi Optimization 56 Nov 17, 2022
An intuitive library to add plotting functionality to scikit-learn objects.

Welcome to Scikit-plot Single line functions for detailed visualizations The quickest and easiest way to go from analysis... ...to this. Scikit-plot i

Reiichiro Nakano 2.3k Dec 31, 2022
Print matplotlib colors

mplcolors Tired of searching "matplotlib colors" every week/day/hour? This simple script displays them all conveniently right in your terminal emulato

Brandon Barker 32 Dec 13, 2022
ecoglib: visualization and statistics for high density microecog signals

ecoglib: visualization and statistics for high density microecog signals This library contains high-level analysis tools for "topos" and "chronos" asp

1 Nov 17, 2021
🌀❄️🌩️ This repository contains some examples for creating 2d and 3d weather plots using matplotlib and cartopy libraries in python3.

Weather-Plotting 🌀 ❄️ 🌩️ This repository contains some examples for creating 2d and 3d weather plots using matplotlib and cartopy libraries in pytho

Giannis Dravilas 21 Dec 10, 2022
GitHubPoster - Make everything a GitHub svg poster

GitHubPoster Make everything a GitHub svg poster 支持 Strava 开心词场 扇贝 Nintendo Switch GPX 多邻国 Issue

yihong 1.3k Jan 02, 2023
Joyplots in Python with matplotlib & pandas :chart_with_upwards_trend:

JoyPy JoyPy is a one-function Python package based on matplotlib + pandas with a single purpose: drawing joyplots (a.k.a. ridgeline plots). The code f

Leonardo Taccari 462 Jan 02, 2023
Visualization Website by using Dash and Heroku

Visualization Website by using Dash and Heroku You can visit the website https://payroll-expense-analysis.herokuapp.com/ In this project, I am interes

YF Liu 1 Jan 14, 2022
Missing data visualization module for Python.

missingno Messy datasets? Missing values? missingno provides a small toolset of flexible and easy-to-use missing data visualizations and utilities tha

Aleksey Bilogur 3.4k Dec 29, 2022
CompleX Group Interactions (XGI) provides an ecosystem for the analysis and representation of complex systems with group interactions.

XGI CompleX Group Interactions (XGI) is a Python package for the representation, manipulation, and study of the structure, dynamics, and functions of

Complex Group Interactions 67 Dec 28, 2022
Pebble is a stat's visualization tool, this will provide a skeleton to develop a monitoring tool.

Pebble is a stat's visualization tool, this will provide a skeleton to develop a monitoring tool.

Aravind Kumar G 2 Nov 17, 2021
A program that analyzes data from inertia measurement units installed in aircraft and generates g-exceedance curves.

A program that analyzes data from inertia measurement units installed in aircraft and generates g-exceedance curves.

Pooya 1 Dec 02, 2021
Open-questions - Open questions for Bellingcat technical contributors

Open questions for Bellingcat technical contributors These are difficult, long-term projects that would contribute to open source investigations at Be

Bellingcat 234 Dec 31, 2022
Render tokei's output to interactive sunburst chart.

Render tokei's output to interactive sunburst chart.

134 Dec 15, 2022
Param: Make your Python code clearer and more reliable by declaring Parameters

Param Param is a library providing Parameters: Python attributes extended to have features such as type and range checking, dynamically generated valu

HoloViz 304 Jan 07, 2023
3D Vision functions with end-to-end support for deep learning developers, written in Ivy.

Ivy vision focuses predominantly on 3D vision, with functions for camera geometry, image projections, co-ordinate frame transformations, forward warping, inverse warping, optical flow, depth triangul

Ivy 61 Dec 29, 2022
A python script editor for napari based on PyQode.

napari-script-editor A python script editor for napari based on PyQode. This napari plugin was generated with Cookiecutter using with @napari's cookie

Robert Haase 9 Sep 20, 2022
By default, networkx has problems with drawing self-loops in graphs.

By default, networkx has problems with drawing self-loops in graphs. It makes it hard to draw a graph with self-loops or to make a nicely looking chord diagram. This repository provides some code to

Vladimir Shitov 5 Jan 06, 2022
Productivity Tools for Plotly + Pandas

Cufflinks This library binds the power of plotly with the flexibility of pandas for easy plotting. This library is available on https://github.com/san

Jorge Santos 2.7k Dec 30, 2022