scholarly journals AQUAMI: An open source Python package and GUI for the automatic quantitative analysis of morphologically complex multiphase materials

2017 ◽  
Vol 139 ◽  
pp. 320-329 ◽  
Author(s):  
Joshua Stuckner ◽  
Katherine Frei ◽  
Ian McCue ◽  
Michael J. Demkowicz ◽  
Mitsuhiro Murayama
Keyword(s):  
Quantitative Analysis ◽  
Open Source ◽  
Multiphase Materials ◽  
Python Package

scholarly journals SynBiopython: an open-source software library for Synthetic Biology

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Jing Wui Yeoh ◽  
Neil Swainston ◽  
Peter Vegh ◽  
Valentin Zulkower ◽  
Pablo Carbonell ◽  
...  
Keyword(s):  
Synthetic Biology ◽  
Open Source ◽  
Open Source Software ◽  
Development Projects ◽  
Software Library ◽  
Current State ◽  
Starting Point ◽  
Common Problems ◽  
Data Tracking ◽  
Python Package

Abstract Advances in hardware automation in synthetic biology laboratories are not yet fully matched by those of their software counterparts. Such automated laboratories, now commonly called biofoundries, require software solutions that would help with many specialized tasks such as batch DNA design, sample and data tracking, and data analysis, among others. Typically, many of the challenges facing biofoundries are shared, yet there is frequent wheel-reinvention where many labs develop similar software solutions in parallel. In this article, we present the first attempt at creating a standardized, open-source Python package. A number of tools will be integrated and developed that we envisage will become the obvious starting point for software development projects within biofoundries globally. Specifically, we describe the current state of available software, present usage scenarios and case studies for common problems, and finally describe plans for future development. SynBiopython is publicly available at the following address: http://synbiopython.org.

scholarly journals QuakeMigrate: a Modular, Open-Source Python Package for Automatic Earthquake Detection and Location

2021 ◽  
Author(s):  
Tom Winder ◽  
Conor Bacon ◽  
Jonathan Smith ◽  
Thomas Hudson ◽  
Tim Greenfield ◽  
...  
Keyword(s):  
Open Source ◽  
Earthquake Detection ◽  
Python Package

scholarly journals DEBoost: A Python Library for Weighted Distance Ensembling in Machine Learning

2020 ◽  
Author(s):  
Wei Hao Khoong
Keyword(s):  
Machine Learning ◽  
Open Source ◽  
Data Preprocessing ◽  
Weighted Distance ◽  
Open Source License ◽  
Classification Tasks ◽  
Python Package

In this paper, we introduce deboost, a Python library devoted to weighted distance ensembling of predictions for regression and classification tasks. Its backbone resides on the scikit-learn library for default models and data preprocessing functions. It offers flexible choices of models for the ensemble as long as they contain the predict method, like the models available from scikit-learn. deboost is released under the MIT open-source license and can be downloaded from the Python Package Index (PyPI) at https://pypi.org/project/deboost. The source scripts are also available on a GitHub repository at https://github.com/weihao94/DEBoost.

scholarly journals The Complexities of Metal Detecting Policy and Practice: A Response to Samuel Hardy, ‘Quantitative Analysis of Open-Source Data on Metal Detecting for Cultural Property’ (Cogent Social Sciences 3, 2017)

2018 ◽  
Vol 4 (1) ◽  
pp. 322-333 ◽  
Author(s):  
Pieterjan Deckers ◽  
Andres Dobat ◽  
Natasha Ferguson ◽  
Stijn Heeren ◽  
Michael Lewis ◽  
...  
Keyword(s):  
Social Sciences ◽  
Quantitative Analysis ◽  
Cultural Heritage ◽  
Open Source ◽  
Cultural Property ◽  
Quantitative Approach ◽  
Policy And Practice ◽  
Basic Assumptions ◽  
Open Source Data ◽  
Source Data

Abstract In his paper ‘Quantitative analysis of open-source data on metal detecting for cultural property’, Samuel Hardy suggested that permissive policy is ineffective in minimizing the damage done to cultural heritage by non-professional metal detecting. This response paper contests the basic assumptions upon which this analysis is based. While Hardy‘s comparative, quantitative approach is laudable, it is founded in a biased and simplistic outlook on the metal detecting phenomenon.

scholarly journals PySeqLab: an open source Python package for sequence labeling and segmentation

2017 ◽  
Vol 33 (21) ◽  
pp. 3497-3499 ◽  
Author(s):  
Ahmed Allam ◽  
Michael Krauthammer
Keyword(s):  
Open Source ◽  
Sequence Labeling ◽  
Python Package

scholarly journals Geophysical tutorial: Euler deconvolution of potential-field data

2014 ◽  
Vol 33 (4) ◽  
pp. 448-450 ◽  
Author(s):  
Leonardo Uieda ◽  
Vanderlei C. Oliveira ◽  
Valéria C. F. Barbosa
Keyword(s):  
Open Source ◽  
Potential Field ◽  
Field Data ◽  
Synthetic Data ◽  
Euler Deconvolution ◽  
Potential Field Data ◽  
Python Package

In this tutorial, we will talk about a widely used method of interpretation for potential-field data called Euler de-convolution. Our goal is to demonstrate its usefulness and, most important, to call attention to some pitfalls encountered in interpretation of the results. The code and synthetic data required to reproduce our results and figures can be found in the accompanying IPython notebooks ( ipython.org/notebook ) at dx.doi.org/10.6084/m9.figshare.923450 or github.com/pinga-lab/paper-tle-euler-tutorial . The note-books also expand the analysis presented here. We encourage you to download the data and try them on your software of choice. For this tutorial, we will use the implementation in the open-source Python package Fatiando a Terra ( fatiando.org ).

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