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Getting Started
After you've installed, the next thing to do is try out some examples from the gallery!
To run the examples, you first have to use the unix source
command to load the CDAT environment.
conda activate [YOUR_CDAT_CONDA_ENV]
On older anaconda version it might be
source activate [YOUR_CDAT_CONDA_ENV]
Once you've loaded the environment, you should be able to run the examples. They should output a .png file that has the same image as the example.
We strongly recommend using Jupyter notebook for the tutotrials
jupyter-notebook
We also recommend using the interactive python console for figuring out how to use CDAT's scripting capabilities.
To run the interactive console, use the ipython
command, which should give you something like this:
Python 2.7.14 | packaged by conda-forge | (default, Dec 25 2017, 01:18:54)
Type "copyright", "credits" or "license" for more information.
IPython 5.5.0 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.
In [1]:
To learn more about ipython
, you can read this tutorial.
You can just type import vcs, cdms2
to load the main two modules of UV-CDAT (to learn more about them, you can check out the VCS Manual and the CDMS Manual), then hit enter.
Here's a very simple example that walks you through the most basic steps:
import vcs, cdms2, cdat_info
# Download sample data files
vcs.download_sample_data_files()
# The vcs_canvas is the root object of VCS
vcs_canvas = vcs.init()
cdms_file = cdms2.open(vcs.prefix + "/sample_data/clt.nc")
# We'll pull a variable out of the netCDF file
clt_variable = cdms_file("clt")
# And then we'll plot it using the default graphics method (a boxfill) and the default template.
vcs_canvas.plot(clt_variable)
# To output to a .png file, you can just do this:
vcs_canvas.png("clt.png")
# And that's it!
Hopefully that helps some! If you have any other questions, let us know!