Python periodic table module

Related tags

Deep Learningchemistryperiodic-tablechemperiodic-table-of-elements
Overview

elemenpy

CircleCI Codacy Badge Codacy Badge

Hello! elements.py is a small Python periodic table module that is used for calling certain information about an element.

Installation

  1. Install Python and pip here, if they are not installed already.
  2. Go to your command-line interface of choice and write the command pip install elemenpy.

Usage

Elemenpy needs to be imported with the usage of import elements at the top of the Python file.

Examples of usage:

from elements import elements

print(elements.symbol(1)) # should be H
print(elements.name(27)) # should be Cobalt
print(elements.mass(59)) # should be 140.9077

Contributing

The Elemenpy team welcomes all contributions, please see the contributing guidelines file here.

Testing

Elemenpy requires pytest to run its tests in the tests/ directory. All pull requests to the main branch will be linted and tested by CircleCI. In addition, CircleCI will upload a coverage report to Codacy, allowing us to see current test coverage and other code smells.

You might also like...
Code and data for
Code and data for "TURL: Table Understanding through Representation Learning"

TURL This Repo contains code and data for "TURL: Table Understanding through Representation Learning". Environment and Setup Data Pretraining Finetuni

SunLab-OSU 63 Nov 23, 2022
Practical Single-Image Super-Resolution Using Look-Up Table
Practical Single-Image Super-Resolution Using Look-Up Table

Practical Single-Image Super-Resolution Using Look-Up Table [Paper] Dependency Python 3.6 PyTorch glob numpy pillow tqdm tensorboardx 1. Training deep

Younghyun Jo 116 Dec 23, 2022
TAPEX: Table Pre-training via Learning a Neural SQL Executor
TAPEX: Table Pre-training via Learning a Neural SQL Executor

TAPEX: Table Pre-training via Learning a Neural SQL Executor The official repository which contains the code and pre-trained models for our paper TAPE

Microsoft 157 Dec 28, 2022
deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.
deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.

deep-table implements various state-of-the-art deep learning and self-supervised learning algorithms for tabular data using PyTorch.

null 63 Oct 17, 2022
Convert Table data to approximate values with GUI

Table_Editor Convert Table data to approximate values with GUIs... usage - Import methods for extension Tables. Imported method supposed to have only

CLJ 1 Jan 10, 2022
Table-Extractor 表格抽取

(t)able-(ex)tractor 本项目旨在实现pdf表格抽取。 Models 版面分析模块（Yolo） 表格结构抽取（ResNet + Transformer） 文字识别模块（CRNN + CTC Loss） Acknowledgements TableMaster attention-i

null 2 Jan 15, 2022
Open source Python module for computer vision

About PCV PCV is a pure Python library for computer vision based on the book "Programming Computer Vision with Python" by Jan Erik Solem. More details

Jan Erik Solem 1.9k Jan 6, 2023
Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.
Web mining module for Python, with tools for scraping, natural language processing, machine learning, network analysis and visualization.

Pattern Pattern is a web mining module for Python. It has tools for: Data Mining: web services (Google, Twitter, Wikipedia), web crawler, HTML DOM par

Computational Linguistics Research Group 8.4k Jan 3, 2023
Solve a Rubiks Cube using Python Opencv and Kociemba module

Rubiks_Cube_Solver Solve a Rubiks Cube using Python Opencv and Kociemba module Main Steps Get the countours of the cube check whether there are tota

Adarsh Badagala 176 Jan 1, 2023
Releases(1.2.0)
Owner
Eric Cheng
Eric Cheng
GitHub Repository https://pypi.org/project/elemenpy/
Implementing Vision Transformer (ViT) in PyTorch

Lightning-Hydra-Template A clean and scalable template to kickstart your deep learning project 🚀 ⚡ 🔥 Click on Use this template to initialize new re

2 Dec 24, 2021
Algo-burn - Script to configure an Algorand address as a "burn" address for one or more ASA tokens

Algorand Burn Address This is a simple script to illustrate how a "burn address"

GSD 5 May 10, 2022
Python Library for learning (Structure and Parameter) and inference (Statistical and Causal) in Bayesian Networks.

pgmpy pgmpy is a python library for working with Probabilistic Graphical Models. Documentation and list of algorithms supported is at our official sit

pgmpy 2.2k Jan 03, 2023
Hooks for VCOCO

Verbs in COCO (V-COCO) Dataset This repository hosts the Verbs in COCO (V-COCO) dataset and associated code to evaluate models for the Visual Semantic

Saurabh Gupta 131 Nov 24, 2022
Code for Learning to Segment The Tail (LST)

Learning to Segment the Tail [arXiv] In this repository, we release code for Learning to Segment The Tail (LST). The code is directly modified from th

47 Nov 07, 2022
Anchor Retouching via Model Interaction for Robust Object Detection in Aerial Images

Anchor Retouching via Model Interaction for Robust Object Detection in Aerial Images In this paper, we present an effective Dynamic Enhancement Anchor

13 Dec 09, 2022
JupyterLite demo deployed to GitHub Pages 🚀

JupyterLite Demo JupyterLite deployed as a static site to GitHub Pages, for demo purposes. ✨ Try it in your browser ✨ ➡️ https://jupyterlite.github.io

JupyterLite 223 Jan 04, 2023
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition

107 Dec 02, 2022
Misc YOLOL scripts for use in the Starbase space sandbox videogame

starbase-misc Misc YOLOL scripts for use in the Starbase space sandbox videogame. Each directory contains standalone YOLOL scripts. They don't really

4 Oct 17, 2021
Explainer for black box models that predict molecule properties

Explaining why that molecule exmol is a package to explain black-box predictions of molecules. The package uses model agnostic explanations to help us

White Laboratory 172 Dec 19, 2022
TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation

TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation Zhaoyun Yin, Pichao Wang, Fan Wang, Xianzhe Xu, Hanling Zhang, Hao Li

DamoCV 25 Dec 16, 2022
Training DALL-E with volunteers from all over the Internet using hivemind and dalle-pytorch (NeurIPS 2021 demo)

Training DALL-E with volunteers from all over the Internet This repository is a part of the NeurIPS 2021 demonstration "Training Transformers Together

<a href=[email protected]"> 19 Dec 13, 2022
Understanding the Properties of Minimum Bayes Risk Decoding in Neural Machine Translation.

Understanding Minimum Bayes Risk Decoding This repo provides code and documentation for the following paper: Müller and Sennrich (2021): Understanding

ZurichNLP 13 May 01, 2022
SMIS - Semantically Multi-modal Image Synthesis(CVPR 2020)

Semantically Multi-modal Image Synthesis Project page / Paper / Demo Semantically Multi-modal Image Synthesis(CVPR2020). Zhen Zhu, Zhiliang Xu, Anshen

316 Dec 01, 2022
Official code base for the poster "On the use of Cortical Magnification and Saccades as Biological Proxies for Data Augmentation" published in NeurIPS 2021 Workshop (SVRHM)

Self-Supervised Learning (SimCLR) with Biological Plausible Image Augmentations Official code base for the poster "On the use of Cortical Magnificatio

Binxu 8 Aug 17, 2022
Python code for loading the Aschaffenburg Pose Dataset.

Aschaffenburg Pose Dataset (APD) This repository contains Python code for loading and filtering the Aschaffenburg Pose Dataset. The dataset itself and

1 Nov 26, 2021
SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification

SubOmiEmbed: Self-supervised Representation Learning of Multi-omics Data for Cancer Type Classification

Sayed Hashim 3 Nov 15, 2022
[peer review] An Arbitrary Scale Super-Resolution Approach for 3D MR Images using Implicit Neural Representation

ArSSR This repository is the pytorch implementation of our manuscript "An Arbitrary Scale Super-Resolution Approach for 3-Dimensional Magnetic Resonan

Qing Wu 19 Dec 12, 2022
Code for IntraQ, PyTorch implementation of our paper under review

IntraQ: Learning Synthetic Images with Intra-Class Heterogeneity for Zero-Shot Network Quantization paper Requirements Python = 3.7.10 Pytorch == 1.7

1 Nov 19, 2021
This repository contains the code used for Predicting Patient Outcomes with Graph Representation Learning (https://arxiv.org/abs/2101.03940).

Predicting Patient Outcomes with Graph Representation Learning This repository contains the code used for Predicting Patient Outcomes with Graph Repre

Emma Rocheteau 76 Dec 22, 2022