https://github.com/clima/griddingmachine.jl
Functions to read gridded data so as to feed Clima Land model
Science Score: 36.0%
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○CITATION.cff file
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✓codemeta.json file
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○.zenodo.json file
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✓DOI references
Found 2 DOI reference(s) in README -
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1 of 5 committers (20.0%) from academic institutions -
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○Scientific vocabulary similarity
Low similarity (12.1%) to scientific vocabulary
Keywords from Contributors
Repository
Functions to read gridded data so as to feed Clima Land model
Basic Info
Statistics
- Stars: 35
- Watchers: 10
- Forks: 7
- Open Issues: 2
- Releases: 20
Metadata Files
README.md
GriddingMachine.jl
Credits
Please cite our paper(s) when you use GriddingMachine:
- Y. Wang, P. Köhler, R. K. Braghiere, M. Longo, R. Doughty, A. A. Bloom, and C. Frankenberg. 2022. GriddingMachine, a database and software for Earth system modeling at global and regional scales. Scientific Data. 9: 258. DOI
About
GriddingMachine.jl includes a collection of global canopy propertie. To best utilize Pkg.Artifacts and FTP storage, GriddingMachine.jl only supports julia 1.7 and above.
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Installation
julia
julia> using Pkg;
julia> Pkg.add("GriddingMachine");
API
GriddingMachine has the following sub-modules, some of which are in development. The sub-modules are | Sub-module | Functionality | Ready to use | |:------------|:--------------------------------|:-------------| | Blender | Regrid the gridded datasets | Testing | | Collector | Distribute the gridded datasets | v0.2 | | Fetcher | Download ungridded datasets | Testing | | Indexer | Read the gridded datasets | v0.2 | | Partitioner | Sort the ungridded datasets | Testing | | Requestor | Request gridded datasets | v0.2 |
See API for more detailed information about how to use GriddingMachine.jl.
To automatically download and query the file path of the dataset, use
julia
julia> using GriddingMachine.Collector;
julia> file_path = Collector.download_artifact!("VCMAX_2X_1Y_V1");
To request a partial dataset from the server without download the entire dataset, use
julia
julia> using GriddingMachine.Requestor;
julia> dat,std = Requestor.request_LUT("VCMAX_2X_1Y_V1", 35.1, 115.2);
julia> dat,std = Requestor.request_LUT("VCMAX_2X_1Y_V1", 35.1, 115.2; interpolation=true);
Other language supports
| Language | Link to Github repository | |:---------|:----------------------------------------------------------------------------| | Matlab | octave-griddingmachine | | Octave | octave-griddingmachine | | R | r-griddingmachine | | Python | python-griddingmachine |
Data contribution
We welcome the contribution of global scale datasets to GriddingMachine.jl. To maximally promote data reuse, we ask data owners to preprocess your datasets before sharing with us, the requirements
are:
- The dataset is stored in a NetCDF file
- The dataset is either a 2D or 3D array
- The dataset is cylindrically projected (WGS84 projection)
- The first dimension of the dataset is longitude
- The second dimension of the dataset is latitude
- The third dimension (if available) is the cycle index, e.g., time
- The longitude is oriented from west to east hemisphere (-180° to 180°)
- The latitude is oriented from south to north hemisphere (-90° to 90°)
- The dataset covers the entire globe (missing data allowed)
- Missing data is labeled as NaN (not a number) rather than an unrealistic fill value
- The dataset is not scaled (linearly, exponentially, or logarithmically)
- The dataset has common units, such as μmol m⁻² s⁻¹ for maximum carboxylation rate
- The spatial resolution is uniform longitudinally and latitudinally, e.g., both at 1/2°
- The spatial resolution is an integer division of 1°, such as 1/2°, 1/12°, 1/240°
- Each grid cell represents the average value of everything inside the grid cell area (as opposing to a single point in the middle of the cell)
- The label for the data is "data" (for conveniently loading the data)
- The label for the error is "std" (for conveniently loading the error)
- The dataset must contain one data array and one error array besides the dimensions
- The dataset contains citation information in the attributes
- The dataset contains a log summarizing changes if different from original source
The reprocessed NetCDF file should contain (only) the following fields: | Field | Dimension | Description | Attributes | |:------|:----------|:--------------------------------------|:-------------| | lon | 1D | Longitude in the center of a grid | unit | | | | | description | | lat | 1D | Latitude in the center of a grid | unit | | | | | description | | ind | 1D | Cycle index (for 3D data only) | unit | | | | | description | | data | 2D/3D | Data in the center of a grid | longname | | | | | unit | | | | | about | | | | | authors | | | | | year | | | | | title | | | | | journal | | | | | doi | | | | | changeN | | std | 2D/3D | Error of data in the center of a grid | same as data | |||||
For data contributors who have limited knowledge about Github and Julia, we recommend to contribute your reprocessed data to us by tag an issue via the button New issue in the Issues Tab. See an example table here. See this google doc for an example of this data reprocessing and deployment.
For data contributors who are experienced Github and Julia users, we also welcome that your contribution of code directly. See this pull request for an example of the pull request.
Owner
- Name: Climate Modeling Alliance
- Login: CliMA
- Kind: organization
- Email: clima@caltech.edu
- Website: https://clima.caltech.edu
- Repositories: 67
- Profile: https://github.com/CliMA
An alliance of scientists, engineers and applied mathematicians, dedicated to pioneering a new, data-informed approach to climate modeling
GitHub Events
Total
- Create event: 5
- Commit comment event: 6
- Release event: 2
- Watch event: 1
- Delete event: 3
- Issue comment event: 19
- Push event: 31
- Pull request event: 8
- Fork event: 1
Last Year
- Create event: 5
- Commit comment event: 6
- Release event: 2
- Watch event: 1
- Delete event: 3
- Issue comment event: 19
- Push event: 31
- Pull request event: 8
- Fork event: 1
Committers
Last synced: over 2 years ago
Top Committers
| Name | Commits | |
|---|---|---|
| Yujie Wang | j****r@g****m | 214 |
| Emily Gu | e****5@g****m | 94 |
| github-actions[bot] | 4****] | 2 |
| Emily Gu | e****u@f****u | 2 |
| Tomas Chor | t****r@g****m | 1 |
Committer Domains (Top 20 + Academic)
Issues and Pull Requests
Last synced: about 1 year ago
All Time
- Total issues: 6
- Total pull requests: 79
- Average time to close issues: 8 days
- Average time to close pull requests: 5 days
- Total issue authors: 3
- Total pull request authors: 3
- Average comments per issue: 8.33
- Average comments per pull request: 2.11
- Merged pull requests: 65
- Bot issues: 0
- Bot pull requests: 15
Past Year
- Issues: 0
- Pull requests: 4
- Average time to close issues: N/A
- Average time to close pull requests: 22 minutes
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.5
- Merged pull requests: 4
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- Yujie-W (4)
- eviatarbach (1)
- JuliaTagBot (1)
Pull Request Authors
- Yujie-W (66)
- github-actions[bot] (15)
- tomchor (1)
Top Labels
Issue Labels
Pull Request Labels
Packages
- Total packages: 1
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Total downloads:
- julia 4 total
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 21
juliahub.com: GriddingMachine
Functions to read gridded data so as to feed Clima Land model
- Documentation: https://docs.juliahub.com/General/GriddingMachine/stable/
- License: Apache-2.0
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Latest release: 0.3.0
published over 1 year ago
Rankings
Dependencies
- actions/checkout v1 composite
- julia-actions/setup-julia v1 composite
- actions/checkout v1 composite
- julia-actions/setup-julia v1 composite
- actions/checkout v1 composite
- julia-actions/julia-runtest latest composite
- julia-actions/setup-julia v1 composite
- actions/checkout v1 composite
- codecov/codecov-action v1 composite
- julia-actions/julia-processcoverage v1 composite
- julia-actions/julia-runtest latest composite
- julia-actions/setup-julia v1 composite
- JuliaRegistries/TagBot v1 composite