CUPiD: CESM Unified Postprocessing and Diagnostics

Python Framework for Generating Diagnostics from CESM

Project Vision

CUPiD is a “one stop shop” that enables and integrates timeseries file generation, data standardization, diagnostics, and metrics from all CESM components.

This collaborative effort aims to simplify the user experience of running diagnostics by calling post-processing tools directly from CUPiD, running all component diagnostics from the same tool as either part of the CIME workflow or independently, and sharing python code and a standard conda environment across components.

Installing

To install CUPiD, you need to check out the code and then set up a few environments. The initial examples have hard-coded paths that require you to be on casper.

The code relies on submodules to install a few packages that are still being developed, so the git clone process requires --recurse-submodules:

$ git clone --recurse-submodules https://github.com/NCAR/CUPiD.git

Then cd into the CUPiD directory and build the necessary conda environments with

$ cd CUPiD
$ mamba env create -f environments/cupid-infrastructure.yml
$ conda activate cupid-infrastructure
$ which cupid-diagnostics
$ mamba env create -f environments/cupid-analysis.yml

Notes:

1. As of version 23.10.0, conda defaults to using mamba to solve environments. It still feels slower than running mamba directly, hence the recommendation to install with mamba env create rather than conda env create. If you do not have mamba installed, you can still use conda... it will just be significantly slower. (To see what version of conda you have installed, run conda --version.)

2. If the subdirectories in externals/ are all empty, run git submodule update --init to clone the submodules.

3. For existing users who cloned CUPiD prior to the switch from manage externals to git submodule, we recommend removing externals/ before checking out main, running git submodule update --init, and removing manage_externals (if it is still present after git submodule update --init).

4. If which cupid-diagnostics returned the error which: no cupid-diagnostics in ($PATH), then please run the following:

   $ conda activate cupid-infrastructure
   $ pip install -e .  # installs cupid

5. In the cupid-infrastructure environment, run pre-commit install to configure git to automatically run pre-commit checks when you try to commit changes from the cupid-infrastructure environment; the commit will only proceed if all checks pass. Note that CUPiD uses pre-commit to ensure code formatting guidelines are followed, and pull requests will not be accepted if they fail the pre-commit-based Github Action.

6. If you plan on contributing code to CUPiD, whether developing CUPiD itself or providing notebooks for CUPiD to run, please see the Contributor's Guide.

Running

CUPiD currently provides an example for generating diagnostics. To test the package out, try to run examples/key-metrics:

$ conda activate cupid-infrastructure
$ cd examples/key_metrics
$ # machine-dependent: request multiple compute cores
$ cupid-diagnostics
$ cupid-webpage  # Will build HTML from Jupyter Book

After the last step is finished, you can use Jupyter to view generated notebooks in ${CUPID_ROOT}/examples/key-metrics/computed_notebooks or you can view ${CUPID_ROOT}/examples/key-metrics/computed_notebooks/_build/html/index.html in a web browser.

Notes:

1. Occasionally users report the following error the first time they run CUPiD: Environment cupid-analysis specified for <YOUR-NOTEBOOK>.ipynb could not be found. The fix for this is the following:

   $ conda activate cupid-analysis
   (cupid-analysis) $ python -m ipykernel install --user --name=cupid-analysis

Furthermore, to clean the computed_notebooks folder which was generated by the cupid-diagnostics and cupid-webpage commands, you can run the following command:

$ cupid-clean

This will clean the computed_notebooks folder which is at the location pointed to by the run_dir variable in the config.yml file.

CUPiD Options

Most of CUPiD's configuration is done via the config.yml file, but there are a few command line options as well:

(cupid-infrastructure) $ cupid-diagnostics -h
Usage: cupid-diagnostics [OPTIONS] CONFIG_PATH

  Main engine to set up running all the notebooks.

Options:
  -s, --serial        Do not use LocalCluster objects
  -ts, --time-series  Run time series generation scripts prior to diagnostics
  -atm, --atmosphere  Run atmosphere component diagnostics
  -ocn, --ocean       Run ocean component diagnostics
  -lnd, --land        Run land component diagnostics
  -ice, --seaice      Run sea ice component diagnostics
  -glc, --landice     Run land ice component diagnostics
  -rof, --river-runoff Run river runoff component diagnostics
  --config_path       Path to the YAML configuration file containing specifications for notebooks (default config.yml)
  -h, --help          Show this message and exit.

Running in serial

By default, several of the example notebooks provided use a dask LocalCluster object to run in parallel. However, the --serial option will pass a logical flag to each notebook that can be used to skip starting the cluster.

# Spin up cluster (if running in parallel)
client=None
if not serial:
  cluster = LocalCluster(**lc_kwargs)
  client = Client(cluster)

client

Specifying components

If no component flags are provided, all component diagnostics listed in config.yml will be executed by default. Multiple flags can be used together to select a group of components, for example: cupid-diagnostics -ocn -ice.

Timeseries File Generation

CUPiD also has the capability to generate single variable timeseries files from history files for all components. To run timeseries, edit the config.yml file's timeseries section to fit your preferences, and then run cupid-timeseries.