Difference between revisions of "Visualization and analysis examples"
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Revision as of 19:25, 23 August 2019
Previous | Next | Guide to Visualization and Analysis Tools
- Python tools for visualizing and analyzing GEOS-Chem output
- Other tools for visualizing and analyzing GEOS-Chem output
- Visualization and analysis examples
Contents
Plotting examples
Comparing diagnostics from different simulations
| Script or notebook | Author | Description |
|---|---|---|
| compare_diagnostics.ipynb | Lizzie Lundgren (Harvard) | Jupyter notebook that illustrates the steps involved in comparing output from two different GEOS-Chem simulations. |
Plotting timeseries data
| Script or notebook | Author | Description |
|---|---|---|
| plot_timeseries.py | Bob Yantosca (Harvard) | Example script that plots timeseries from two different GEOS-Chem diagnostic collections (ConcAboveSfc, SpeciesConc) at a specified location. This is a good example of the using Python xarray and matplotlib packages to create line plots. |
Plotting 2D data
| Script or notebook | Author | Description |
|---|---|---|
| plot_global.py | Daniel Rothenberg | Creates a global average plot. Using cartopy_ we can easily visualize gridded model output on maps with different cartographic projections, and then configure them with any aesthetics or features such as continents, geopolitical borders, gridlines, and more. |
| plot_seasons.py | Daniel Rothenberg | For a given field timeseries, compute seasonal averages over all data and plot each average on a four-panel figure. |
| quickplot.py | Bob Yantosca (Harvard) | Creates a quick-and-dirty plot of a variable in a netCDF (HDF5, GRIB, etc. file). Uses xarray. |
