Numerical Analysis toolkit centred around PDEs, for demonstration and understanding purposes not production

Related tags

Data AnalysisNumerics
Overview

Numerics

Numerical Analysis toolkit centred around PDEs, for demonstration and understanding purposes not production

Use procedure:

  • Initialise a new instance of the PDE class, all calculations and variables will be managed by this object

    Inputs:

  •      dt - timestep
    
  •      tlim - time to solve up to
    
  •      dx - x spacing, by default a uniform grid is used
    
  •      xlims - np.array([lower, upper]) bounds of x domain
    
  • instance.setSystem: Set the governing equation of the PDE in the form dU/dt = lambda U,x,t: some function

  • instance.setInitConds: Set the initial conditions of U in the form lambda x: some function

  • instance.solve: Integrate the system to time tlim using the input integrator (ie RK4, an explicit 4th order Runge Kutta method)

Note on Chebyshev pseudo-spectral differentiator:

  • To use this differentiator, the local x coords must be set to the Gauss-Lobatto-Chebyshev collocation points using instance.chebyx(N) where N is the number of points

Known issues:

  • 6th order error finite difference matrices can behave badly near domain edges
  • fft derivative can cause steady state errors as it implicitly assumes periodic behaviour outside of domain
  • Chebyshev differentiator is unstable in current iteration, particularly for higher orders and at the domain boundary, most likely due to Gibb's phenomenon
  • More of a use detail, but fft and Chebyshev differentiators rely on compact support. If in doubt, use the finite differencing differentiator

Future implementations:

  • Support for boundary conditions
  • More integration schemes
  • Potentially support for multiple spatial dimensions
Owner
George Whittle
George Whittle
PySpark Structured Streaming ROS Kafka ApacheSpark Cassandra

PySpark-Structured-Streaming-ROS-Kafka-ApacheSpark-Cassandra The purpose of this project is to demonstrate a structured streaming pipeline with Apache

Zekeriyya Demirci 5 Nov 13, 2022
Pandas and Dask test helper methods with beautiful error messages.

beavis Pandas and Dask test helper methods with beautiful error messages. test helpers These test helper methods are meant to be used in test suites.

Matthew Powers 18 Nov 28, 2022
Predictive Modeling & Analytics on Home Equity Line of Credit

Predictive Modeling & Analytics on Home Equity Line of Credit Data (Python) HMEQ Data Set In this assignment we will use Python to examine a data set

Dhaval Patel 1 Jan 09, 2022
Processo de ETL (extração, transformação, carregamento) realizado pela equipe no projeto final do curso da Soul Code Academy.

Processo de ETL (extração, transformação, carregamento) realizado pela equipe no projeto final do curso da Soul Code Academy.

Débora Mendes de Azevedo 1 Feb 03, 2022
Python tools for querying and manipulating BIDS datasets.

PyBIDS is a Python library to centralize interactions with datasets conforming BIDS (Brain Imaging Data Structure) format.

Brain Imaging Data Structure 180 Dec 18, 2022
University Challenge 2021 With Python

University Challenge 2021 This repository contains: The TeX file of the technical write-up describing the University / HYPER Challenge 2021 under late

2 Nov 27, 2021
Snakemake workflow for converting FASTQ files to self-contained CRAM files with maximum lossless compression.

Snakemake workflow: name A Snakemake workflow for description Usage The usage of this workflow is described in the Snakemake Workflow Catalog. If

Algorithms for reproducible bioinformatics (Koesterlab) 1 Dec 16, 2021
Single machine, multiple cards training; mix-precision training; DALI data loader.

Template Script Category Description Category script comparison script train.py, loader.py for single-machine-multiple-cards training train_DP.py, tra

2 Jun 27, 2022
Python Project on Pro Data Analysis Track

Udacity-BikeShare-Project: Python Project on Pro Data Analysis Track Basic Data Exploration with pandas on Bikeshare Data Basic Udacity project using

Belal Mohammed 0 Nov 10, 2021
t-SNE and hierarchical clustering are popular methods of exploratory data analysis, particularly in biology.

tree-SNE t-SNE and hierarchical clustering are popular methods of exploratory data analysis, particularly in biology. Building on recent advances in s

Isaac Robinson 61 Nov 21, 2022
INFO-H515 - Big Data Scalable Analytics

INFO-H515 - Big Data Scalable Analytics Jacopo De Stefani, Giovanni Buroni, Théo Verhelst and Gianluca Bontempi - Machine Learning Group Exercise clas

Yann-Aël Le Borgne 58 Dec 11, 2022
Vectorizers for a range of different data types

Vectorizers for a range of different data types

Tutte Institute for Mathematics and Computing 69 Dec 29, 2022
Flood modeling by 2D shallow water equation

hydraulicmodel Flood modeling by 2D shallow water equation. Refer to Hunter et al (2005), Bates et al. (2010). Diffusive wave approximation Local iner

6 Nov 30, 2022
small package with utility functions for analyzing (fly) calcium imaging data

fly2p Tools for analyzing two-photon (2p) imaging data collected with Vidrio Scanimage software and micromanger. Loading scanimage data relies on scan

Hannah Haberkern 3 Dec 14, 2022
Analyze the Gravitational wave data stored at LIGO/VIRGO observatories

Gravitational-Wave-Analysis This project showcases how to analyze the Gravitational wave data stored at LIGO/VIRGO observatories, using Python program

1 Jan 23, 2022
A crude Hy handle on Pandas library

Quickstart Hyenas is a curde Hy handle written on top of Pandas API to allow for more elegant access to data-scientist's powerhouse that is Pandas. In

Peter Výboch 4 Sep 05, 2022
Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis

Validated, scalable, community developed variant calling, RNA-seq and small RNA analysis. You write a high level configuration file specifying your in

Blue Collar Bioinformatics 917 Jan 03, 2023
Produces a summary CSV report of an Amber Electric customer's energy consumption and cost data.

Amber Electric Usage Summary This is a command line tool that produces a summary CSV report of an Amber Electric customer's energy consumption and cos

Graham Lea 12 May 26, 2022
Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences

Synthetic data need to preserve the statistical properties of real data in terms of their individual behavior and (inter-)dependences. Copula and functional Principle Component Analysis (fPCA) are st

32 Dec 20, 2022
Repositori untuk menyimpan material Long Course STMKGxHMGI tentang Geophysical Python for Seismic Data Analysis

Long Course "Geophysical Python for Seismic Data Analysis" Instruktur: Dr.rer.nat. Wiwit Suryanto, M.Si Dipersiapkan oleh: Anang Sahroni Waktu: Sesi 1

Anang Sahroni 0 Dec 04, 2021