This is a short introduction for using OceanSpy on the Johns Hopkins University SciServer system using sample datasets.
OceanSpy and its dependencies are preinstalled on SciServer. There is no need to download and install it unless you wish to run OceanSpy on your local machine or server. Steps to do that are described in the Installation section.
The following steps explain how to navigate through the basics of OceanSpy on SciServer. Steps 1 to 5 describe how to create a container on SciServer with a set of example datasets to work on.
Go to www.sciserver.org.
Log in or create a new account.
Create container, then use the following settings:
Interactive Docker Compute Domain
Steps 6 to 8 describe how to get started with using the container. Information about which directories to work in and their descriptions are detailed below the container images once they are created on SciServer.
Click on the name of the new container.
Steps 9 to 15 demonstrate a subset of the commonly used OceanSpy commands.
Copy and paste the following lines in the first notebook cell to import OceanSpy, and open the get started dataset:
import oceanspy as ospy od = ospy.open_oceandataset.from_catalog('get_started')
Use the following line to extract a limited geographic range of the dataset:
od_cutout = od.subsample.cutout(YRange=[69.6, 71.4], XRange=[-21, -15], ZRange=[0, -100])
Use the following line to plot a map of weighted mean temperature:
ax = od_cutout.plot.horizontal_section(varName='Temp', meanAxes=['Z', 'time'], center=False)
Use the following line to compute the potential density anomaly:
od_cutout = od_cutout.compute.potential_density_anomaly()
Use the following line to store the cutout in netCDF format:
The netCDF file can be download and used for post-processing offline, or kept on SciServer. Any software of choice can be used to re-open the netCDF file. To re-open the file using OceanSpy, use the following command:
od_cutout = ospy.open_oceandataset.from_netcdf('filename.nc')
Opening the netCDF file using OceanSpy will allows the use of OceanSpy’s functions whether it be on SciServer or a local machine. For example, the following line plots an animated TS diagram color-coded by potential density anomaly (computed in step 12):
anim = od_cutout.animate.TS_diagram(colorName='Sigma0', meanAxes='Z')
Check out Tutorial, Use Cases, and API reference to learn more about OceanSpy and its features, and feel free to open an issue here, or to send an email to email@example.com if you have any questions.
The schematic below shows how OceanSpy is designed to be used by the oceanographic community.