A benchmarking framework for solving automatic design problems that involve choosing an input that maximizes a black-box function

Design-Bench is a benchmarking framework for solving automatic design problems that involve choosing an input that maximizes a black-box function. This type of optimization is used across scientific and engineering disciplines in ways such as designing proteins and DNA sequences with particular functions, chemical formulas and molecule substructures, the morphology and controllers of robots, and many more applications. These applications have significant potential to accelerate research in biochemistry, chemical engineering, materials science, robotics and many other disciplines. We hope this […]

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Python library for dotbim

Description Open-source python library for dotbim file format. Read more about dotbim here: https://github.com/paireks/dotbim Installation How it works? For json serialization and deserialization it uses jsonpickle: https://github.com/jsonpickle/jsonpicklejsonpickle license: https://github.com/jsonpickle/jsonpickle/blob/main/LICENSE Examples Pyramid example

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Automatically install all scripts you put in the ./bin folder of this repository

Automatically install all scripts you put in the “./bin” folder of this repository Works with any executable script with a shebang pattern in the first line: !#/……… Instructions: Install with: pip install git+https://github.com/marcelotournier/autoscripts.git Note: ALWAYS add the shebang pattern in the first line, so setup.py can properly identify your script Remember that bash/sh scripts don’t work in windows 🙂 GitHub View Github    

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Monitor and study any place on Earth and in Near Real-Time (NRT) using the SentinelHub services developed by the EO research team at Sinergise

earthspy is a wrapper around methods for the download of satellite data offered in the sentinelhub Python package. This tool makes the monitoring and study of any place on Earth simple, ready to use and easily deployable for operational purposes and NRT applications. Just like a spy! Some useful capabilities: Data download in multiprocessing Data download at optimized resolutions with the Direct Download (DD) method Data download at raw resolution with the Split and Merge Downlodad (SMD) method Data storage […]

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Python implementation of the enigma machine

Python implementation of the enigma machine This is a Python implementation of Prof. Mike Pound’s Java based project as featured on the Computerphile YouTube channel: https://github.com/mikepound/enigma To run the program from the command line use python enigma.py. This will initialize the enigma machine with default settings for you to test.To try out additional options, use python enigma.py –help to get the full range of user configurable settings. As a basic example, you can set rotors, rotor positions, ring settings, reflector, […]

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Custom PyTorch ML block example for Edge Impulse

This repository is an example on how to bring a custom transfer learning model into Edge Impulse. This repository contains a small fully-connected model built in PyTorch. If you want to see a more complex PyTorch example, see edgeimpulse/yolov5. Or if you’re looking for the Keras version of this repository, see edgeimpulse/example-custom-ml-block-keras. As a primer, read the Adding custom transfer learning models page in the Edge Impulse docs. To test this locally: Create a new Edge Impulse project, and add […]

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Matplotlib on the tight theme

Lazy on demand subplots. 1️⃣ You can add subplots later, wherever you want. 2️⃣ You can manipulate subplots with numpy-like slices. 3️⃣ Oekaki warn about potentially misleading graphs. (ex: No labels or units.) 🍣 (Oekaki imports japanize-matplotlib if it’s installed.) import numpy as np import oekaki # 1️⃣: lazy draw subplots fig = oekaki.figure(strict

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A generic code base for neural network pruning, especially for pruning at initialization

This repository is meant to provide a generic code base for neural network pruning, especially for pruning at initialization (PaI). [Survey | Paper Collection] Step 1: Set up environment OS: Linux (Ubuntu 1404 and 1604 checked. It should be all right for most linux platforms. Windows and MacOS not checked.) python=3.6.9 (conda to manage environment is strongly suggested) All the dependant libraries are summarized in requirements_pt1.9.txt (PyTorch 1.9 is used). Simply install them by pip install -r requirements_pt1.9.txt. CUDA and […]

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Command Line Interface to automate module development for Bisque web application

V1.0.0 Standardizes and automates the process of creating modules that can be integrated in the Bisque web application.This command line interface (CLI) currently supports any input types supported by Bisque but can only display image and table outputs.Custom outputs or interactive parameters will require users to manually edit some files.Regardless of your application, it is a good idea to follow this guide and use the CLI to automate a big part of theprocess and avoid common bugs. Once you have […]

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Exploring the Fibonacci Sequence With Python

The Fibonacci sequence is a pretty famous sequence of integer numbers. The sequence comes up naturally in many problems and has a nice recursive definition. Learning how to generate it is an essential step in the pragmatic programmer’s journey toward mastering recursion. In this video course, you’ll focus on learning what the Fibonacci sequence is and how to generate it using Python. In this course, you’ll learn how to: Generate the Fibonacci sequence using a recursive algorithm Optimize the recursive […]

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