Competitive Programming templates that I used during the past few years.
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Updated
Sep 30, 2020 - C++
Competitive Programming templates that I used during the past few years.
A Practical and Efficient NCBI Taxonomy Toolkit, also supports creating NCBI-style taxdump files for custom taxonomies like GTDB/ICTV
TensorFlow Implementation of the paper "End-to-End Relation Extraction using LSTMs on Sequences and Tree Structures" and "Classifying Relations via Long Short Term Memory Networks along Shortest Dependency Paths" for classifying relations
Calculadora Renda Fixa
A Python package following the scikit-learn API for model-based clustering and generalized mixture modeling (latent class/profile analysis) of continuous and categorical data. StepMix handles missing values through Full Information Maximum Likelihood (FIML) and provides multiple stepwise Expectation-Maximization (EM) estimation methods.
A Generalized Suffix Tree for any Python iterable using Ukkonen's algorithm, with Lowest Common Ancestor retrieval.
Layer over brightway2 for algebraic definition of parametric models and super fast computation of LCA
Create foreground LCA models via an intuitive user interface and analyse them using Brightway2
Calculation recipes for brightway2. Instructions to becoming an LCA gourmet.
📖🌿 Interactive jupyter-book Documentation for Brightway
Gather and normalize ICT inventory data from multiple sources, to enable automation of ICT carbon and environmental impacts (LCA-inspired) assessments.
A tool to calculate a building project's impacts on biodiversity over the entire life cycle. The tool was developed as part of the "Doughnut for Urban Development" project and manual. For more information, visit https://www.home.earth/doughnut
IFC Parser is a Python script for automatical creating material takeoff from a properly exported IFC2X3 file, and converting that to JSON file format, to finally import into danish LCAByg program for calculating Carbon Footprint of buildings.
This repository contains solutions of various classical problems on SPOJ.
Latent Class analysis: This module allows users to conduct LCA, Multiple group LCA, and Multilevel LCA based on glca R package, and provide plot such as Profile plot and Radar chart within module.
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