Notebooks em Python para Métodos Eletromagnéticos

Overview

GeoSci Labs

binder pypi License SimPEG

This is a repository of code used to power the notebooks and interactive examples for https://em.geosci.xyz and https://gpg.geosci.xyz.

The examples are based on code available in SimPEG.

Why

Interactive visualizations are a powerful way to interrogate mathematical equations. The goal of this repository is to be the home for code that can be plugged into jupyter notebooks so that we can play with the governing equations of geophysical electromagnetics.

Scope

The repository contains the python code to run the ipython-widget style apps in http://github.com/geoscixyz/geosci-labs. These are mainly plotting code and some simple analytics. More complex numerical simulations depend on SimPEG

Usage

The notebooks can be run online through Binder, or downloaded and run locally.

Binder

Binder

  1. Launch the binder by clicking on the badge above or going to: https://mybinder.org/v2/gh/geoscixyz/geosci-labs/master?filepath=notebooks%2Findex.ipynb. This can sometimes take a couple minutes, so be patient...

  2. Select the notebook of interest from the contents

  3. Run the Jupyter notebook

Binder-steps

Locally

To run them locally, you will need to have python installed, preferably through anaconda.

You can then clone this reposiroty. From a command line, run

git clone https://github.com/geoscixyz/geosci-labs.git

Then cd into geosci-labs

cd geosci-labs

To setup your software environment, we recommend you use the provided conda environment

conda env create -f environment.yml
conda activate geosci-labs

alternatively, you can install dependencies through pypi

pip install -r requirements.txt

You can then launch Jupyter

jupyter notebook

Jupyter will then launch in your web-browser.

Running the notebooks

Each cell of code can be run with shift + enter or you can run the entire notebook by selecting cell, Run All in the toolbar.

cell-run-all

For more information on running Jupyter notebooks, see the Jupyter Documentation

Using in a course

Issues

If you run into problems or bugs, please let us know by creating an issue in this repository.

For Contributors

We are glad you are interested in contributing! Please check out the contributing guide for ideas of how to get involved.

Owner
Victor Cezar Tocantins
Victor Cezar Tocantins
TumorInsight is a Brain Tumor Detection and Classification model built using RESNET50 architecture.

A Brain Tumor Detection and Classification Model built using RESNET50 architecture. The model is also deployed as a web application using Flask framework.

Pranav Khurana 0 Aug 17, 2021
Official pytorch code for SSC-GAN: Semi-Supervised Single-Stage Controllable GANs for Conditional Fine-Grained Image Generation(ICCV 2021)

SSC-GAN_repo Pytorch implementation for 'Semi-Supervised Single-Stage Controllable GANs for Conditional Fine-Grained Image Generation'.PDF SSC-GAN:Sem

tyty 4 Aug 28, 2022
Pytorch Lightning code guideline for conferences

Deep learning project seed Use this seed to start new deep learning / ML projects. Built in setup.py Built in requirements Examples with MNIST Badges

Pytorch Lightning 1k Jan 06, 2023
Neural Nano-Optics for High-quality Thin Lens Imaging

Neural Nano-Optics for High-quality Thin Lens Imaging Project Page | Paper | Data Ethan Tseng, Shane Colburn, James Whitehead, Luocheng Huang, Seung-H

Ethan Tseng 39 Dec 05, 2022
Official release of MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis of Pancreatic Cancer axriv: http://arxiv.org/abs/2112.13513

MSHT: Multi-stage Hybrid Transformer for the ROSE Image Analysis This is the official page of the MSHT with its experimental script and records. We de

Tianyi Zhang 53 Dec 27, 2022
Code for Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions

EMS-COLS-recourse Initial Code for Low-Cost Algorithmic Recourse for Users With Uncertain Cost Functions Folder structure: data folder contains raw an

Prateek Yadav 1 Nov 25, 2022
Regularized Frank-Wolfe for Dense CRFs: Generalizing Mean Field and Beyond

CRF - Conditional Random Fields A library for dense conditional random fields (CRFs). This is the official accompanying code for the paper Regularized

Đ.Khuê Lê-Huu 21 Nov 26, 2022
Simultaneous Demand Prediction and Planning

Simultaneous Demand Prediction and Planning Dependencies Python packages: Pytorch, scikit-learn, Pandas, Numpy, PyYAML Data POI: data/poi Road network

Yizong Wang 1 Sep 01, 2022
Dilated Convolution for Semantic Image Segmentation

Multi-Scale Context Aggregation by Dilated Convolutions Introduction Properties of dilated convolution are discussed in our ICLR 2016 conference paper

Fisher Yu 764 Dec 26, 2022
Solving reinforcement learning tasks which require language and vision

Multimodal Reinforcement Learning JAX implementations of the following multimodal reinforcement learning approaches. Dual-coding Episodic Memory from

Henry Prior 31 Feb 26, 2022
This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model inference.

PyTorch Infer Utils This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model infer

Alex Gorodnitskiy 11 Mar 20, 2022
Exploring Simple Siamese Representation Learning

G-SimSiam A PyTorch implementation which refers to repo for the paper Exploring Simple Siamese Representation Learning by Xinlei Chen & Kaiming He Add

zhuyun 1 Dec 19, 2021
[ICCV 2021] Counterfactual Attention Learning for Fine-Grained Visual Categorization and Re-identification

Counterfactual Attention Learning Created by Yongming Rao*, Guangyi Chen*, Jiwen Lu, Jie Zhou This repository contains PyTorch implementation for ICCV

Yongming Rao 90 Dec 31, 2022
Avatarify Python - Avatars for Zoom, Skype and other video-conferencing apps.

Avatarify Python - Avatars for Zoom, Skype and other video-conferencing apps.

Ali Aliev 15.3k Jan 05, 2023
Sdf sparse conv - Deep Learning on SDF for Classifying Brain Biomarkers

Deep Learning on SDF for Classifying Brain Biomarkers To reproduce the results f

1 Jan 25, 2022
Official source code to CVPR'20 paper, "When2com: Multi-Agent Perception via Communication Graph Grouping"

When2com: Multi-Agent Perception via Communication Graph Grouping This is the PyTorch implementation of our paper: When2com: Multi-Agent Perception vi

34 Nov 09, 2022
This repo holds codes of the ICCV21 paper: Visual Alignment Constraint for Continuous Sign Language Recognition.

VAC_CSLR This repo holds codes of the paper: Visual Alignment Constraint for Continuous Sign Language Recognition.(ICCV 2021) [paper] Prerequisites Th

Yuecong Min 64 Dec 19, 2022
a minimal terminal with python 😎😉

Meterm a terminal with python 😎 How to use Clone Project: $ git clone https://github.com/motahharm/meterm.git Run: in Terminal: meterm.exe Or pip ins

Motahhar.Mokfi 5 Jan 28, 2022
Random Forests for Regression with Missing Entries

Random Forests for Regression with Missing Entries These are specific codes used in the article: On the Consistency of a Random Forest Algorithm in th

Irving Gómez-Méndez 1 Nov 15, 2021
YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone

YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone In our recent paper we propose the YourTTS model. YourTTS bri

Edresson Casanova 390 Dec 29, 2022