speculator | Neural network emulation of Stellar Population Synthesis | Machine Learning library

by justinalsing Python Version: v0.2 License: MIT

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | speculator Summary

speculator is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning applications. speculator has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

This repository contains the code for neural network emulation of stellar population synsthesis (SPS) models for galaxy spectra, associated with the paper Alsing et. al 2019, arXiv 1911.11778. If you use this code, kindly cite that paper.

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Support

speculator has a low active ecosystem.

It has 6 star(s) with 2 fork(s). There are 5 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 0 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of speculator is v0.2

Quality

speculator has no bugs reported.

Security

speculator has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

speculator is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

speculator releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions are available. Examples and code snippets are not available.

Top functions reviewed by kandi - BETA

kandi has reviewed speculator and discovered the below as its top functions. This is intended to give you an instant insight into speculator implemented functionality, and help decide if they suit your requirements.

Train a PHOTULATOR model
Save the parameters to a pickle file
Call the model
Performs a training step
Performs the training step of the training step
Compute loss and gradient for the given spectra
Call forward pass through the network
Call the basis function
Compute loss and gradient for a spectra
Compute the loss and gradients for the given spectra
Performs a training step with accumulated loss
Compute the loss and gradients for the log spectra
Performs a training step of the training step
Compute loss and gradients for a given spectra
Performs a training step with accumulated gradients
Compute loss and gradients of log spectrum
Performs a single training step
Performs training step on log spectra
Performs a training step on a log spectra

Get all kandi verified functions for this library.

speculator Key Features

No Key Features are available at this moment for speculator.

speculator Examples and Code Snippets

No Code Snippets are available at this moment for speculator.

Community Discussions

Trending Discussions on speculator

Matplotlib box sizes are not equal

QUESTION

Matplotlib box sizes are not equal

Asked 2020-Jul-09 at 22:02

I have two plots with the same figsize and I want to get them to have the same box size.

Does anyone know how to achieve that?

Here is my code:

...

ANSWER

Answered 2020-Jul-09 at 22:02

Since, I don't have the data you are plotting, I couldn't check running your code: You can add

Source https://stackoverflow.com/questions/62823457

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install speculator

You can install the code with pip: pip install git+https://github.com/justinalsing/speculator.git. The code is in python3 and has the following dependencies: tensorflow (>2.0) scikit-learn numpy.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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