xarray
Gtk.jl
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| xarray | Gtk.jl | |
|---|---|---|
| 7 | 3 | |
| 3,404 | 288 | |
| 1.5% | 1.0% | |
| 9.7 | 2.8 | |
| 5 days ago | 12 days ago | |
| Python | Julia | |
| Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
xarray
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Request for Startups: Climate Tech
PyTorch and JAX are used heavily in climate science on the ML side. For more general analytics, not so much. Many of our users like to use Xarray as a high-level API. There has been some work to integrate Xarray with PyTorch (https://github.com/pydata/xarray/issues/3232) but we're not there yet.
The Python Array API standard should help align these different back-ends: https://data-apis.org/array-api/latest/
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Python for Data Analysis, 3rd Edition – The Open Access Version Online
Does polars have N-D labelled arrays, and if so can it perform computations on them quickly? I've been thinking of moving from pandas to xarray [0], but might consider poplars too if it has some of that functionality.
[0] https://xarray.dev/
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What is lacking in Julia ecosystem?
https://xarray.dev
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How we found and helped fix 24
bugs in 24 hours (in Tensorflow, Sentry, V8, PyTorch, Hue, and more)
Pydata's xarray
- Xarray awarded a support grant from NASA
- xarray: N-Dimensional labeled arrays and datasets in Python
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Could somebody who has experience with reading .asc files / using xarray please give me some direction?
It does seem like it isn't installed. If you take a look at the source, it catches import errors, meaning it won't error out immediately if the package isn't installed.
Gtk.jl
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What is lacking in Julia ecosystem?
I am not clear what you have in mind here. Are QT or Gtk bindings not be sufficient? Or perhaps something like CImGui?
- How to learn compilers: LLVM Edition
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JuliaCall Update: Automated Julia Installation for R Packages
Indeed, the use of BinayBuilder was an important step forward. Before we had the problem that different package would require different versions of e.g. zlib (https://github.com/JuliaGraphics/Gtk.jl/pull/387). BinayBuilder made the package installation mush more robust.
What are some alternatives?
iris - A powerful, format-agnostic, and community-driven Python package for analysing and visualising Earth science data
QML.jl - Build Qt6 QML interfaces for Julia programs.
tensorflow - An Open Source Machine Learning Framework for Everyone
CImGui.jl - Julia wrapper for cimgui
mars - Mars is a tensor-based unified framework for large-scale data computation which scales numpy, pandas, scikit-learn and Python functions.
BinDeps.jl - Tool for building binary dependencies for Julia modules
dask-awkward - Native Dask collection for awkward arrays, and the library to use it.
Descartes.jl - Software Defined Solid Modeling
Dask - Parallel computing with task scheduling
AxisArrays.jl - Performant arrays where each dimension can have a named axis with values
wxee - A Python interface between Earth Engine and xarray for processing time series data
Geodesy.jl - Work with points defined in various coordinate systems.