Filter Results
95826 results
This is part of clij release 1.5.6 https://github.com/clij/clij/releases/tag/1.5.6
Data Types:
  • Software/Code
New features for this release: util to convert raw input inertial navigation data to csv format changed use of ISO 8601 format in util that gets positions from a date time
Data Types:
  • Software/Code
v0.20.0
Data Types:
  • Software/Code
This tool takes FreeSurfer aseg.mgz files and generates homologous mesh representations of subcortical ROI boundaries and vertex-wise shape features for statistical analysis. Please cite the following work when using this tool: 1. Gutman, B.A., Madsen, S.K., Toga, A.W., Thompson, P.M.: A Family of Fast Spherical Registration Algorithms for Cortical Shapes. In: Multimodal Brain Image Analysis, vol. 8159, pp. 246-257. Springer International Publishing (2013) 2. Gutman, B.A., Wang, Y., Rajagopalan, P., Toga, A.W., Thompson, P.M.: Shape matching with medial curves and 1-D group-wise registration. In: Biomedical Imaging (ISBI), 2012 9th IEEE International Symposium on, pp. 716-719. (2012)
Data Types:
  • Software/Code
Bug Fixes: TODO: Describe any bug fixes Enhancements: TODO: Describe any new features or enhancements
Data Types:
  • Software/Code
Tools for interacting with the publicly available California Delta Fish Salvage Database, including continuous deployment of data access, analysis, and presentation.
Data Types:
  • Software/Code
MeshArrays v0.2.7 Diff since v0.2.6 add meta structure containing unit, position, and names defaultmeta = varmeta(missing,fill(0.5,3),"unknown","unknown") support for non-default varmeta is limited to constructors, similar, read and exchange similar() uses defaultmeta by default -- unless optional argument m is provided (e.g. in read and exchanges) fill in meta data for grid variables at the time when they are defined via read / similar / MeshArray() in GridLoad & GridOfOnes show method now prints out meta for gcmarray Project.toml now depends on Unitful.jl for varmeta data structure rename mygrid,GridVariables as γ,Γ throughout packages GridOfOnes now returns both γ,Γ documentation updates/improvements Closed issues: stable documentation did not update with v0.2.5; the dev documentation is now up to date though (#36) Merged pull requests: add meta and version to gcmarray struct (#38) (@gaelforget) Meta part 2 -- update documentation & show method wrt meta (#39) (@gaelforget) Meta p3 (#40) (@gaelforget)
Data Types:
  • Software/Code
A JavaScript library to create a new version of a Zenodo upload with a file. Makes a draft copy of an existing Zenodo upload. After overwriting the file and version the upload is published. Can be used to create a DOI for a updated data file. A Zenodo upload must already exist using this library. Added Perform checksum check and discard on match (#5)
Data Types:
  • Software/Code
First full release of PFExpTools! Contains curation and time course processing functionality.
Data Types:
  • Software/Code
# Description This version contains a collection of documented and reproducible Jupyter notebooks and datasets that are part of an introductory graduate level course offered to students with little or no programming experience in environmental sciences, soil science, and agronomy. The material is aimed at individuals seeking to be more productive, work faster, handle larger datasets, stimulate creative data analysis, develop code for self-teaching environmental processes, and generate reproducible science. # Source Repository: https://github.com/andres-patrignani/pynotes Documented notebooks: https://andres-patrignani.github.io/pynotes/ # Integrations docsify for generating online documentation: https://docsify.js.org/ binder for generating interactive notebooks: https://mybinder.org/ # Datasets Nearly 50 unique datasets of weather variables, crop yields, soil moisture, soil temperature, and cosmic-ray neutrons. # Code A total of 120+ Jupyter notebooks exploring patterns in environmental observations. Teaching of environmental properties and processes is made through the exploration of time series, feature detection using digital images, basic statistical analyses, model optimization, and the implementation of one- and two-dimensional models with deterministic and stochastic components. # License Licensed under Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0)
Data Types:
  • Software/Code
2