wps_split_merged_climos¶

wps_split_merged_climos is a process that runs the split_merged_climos module of PCIC Climate Explorer Data Preparation Tools. Here, the client will try to connect to a remote Thunderbird instance using the url parameter.¶

In [1]:
from birdy import WPSClient
from importlib import resources
import os
from wps_tools.testing import get_target_url
from wps_tools.output_handling import get_metalink_content

# Ensure we are in the working directory with access to the data
while os.path.basename(os.getcwd()) != "thunderbird":
    os.chdir('../')
In [2]:
# NBVAL_IGNORE_OUTPUT
url = get_target_url("thunderbird")
print(f"Using thunderbird on {url}")

Using thunderbird on https://marble-dev01.pcic.uvic.ca/twitcher/ows/proxy/thunderbird/wps
In [3]:
thunderbird = WPSClient(url)

Help for individual processes can be diplayed using the ? command (ex. bird.process?).¶

In [4]:
# NBVAL_IGNORE_OUTPUT
thunderbird.split_merged_climos?

Signature: thunderbird.split_merged_climos(netcdf=None, loglevel='INFO')
Docstring:
Split climo means files into one file per time interval

Parameters
----------
netcdf : ComplexData:mimetype:`application/x-netcdf`, :mimetype:`application/x-ogc-dods`
    NetCDF files to process
loglevel : {'CRITICAL', 'ERROR', 'WARNING', 'INFO', 'DEBUG', 'NOTSET'}string
    Logging level

Returns
-------
output : ComplexData:mimetype:`application/metalink+xml; version=4.0`
    Metalink object between output files
File:      ~/code/thunderbird/</home/eyvorchuk/.cache/pypoetry/virtualenvs/thunderbird-7g6X3rbj-py3.10/lib/python3.10/site-packages/birdy/client/base.py-3>
Type:      method

We can use the docstring to ensure we provide the appropriate parameters.¶

In [5]:
# Test local and opendap files
daccs_host = os.getenv("DACCS_HOST", "marble-dev01.pcic.uvic.ca")
ref = resources.files('tests') / 'data/tiny_downscaled_tasmax_climos.nc'
with resources.as_file(ref) as tasmax_climos_local:
    hydromodel_climos_opendap = f"https://{daccs_host}/twitcher/ows/proxy/thredds/dodsC/datasets/storage/data/projects/comp_support/daccs/test-data/tiny_hydromodel_gcm_climos.nc"
    multiple_inputs = [tasmax_climos_local, hydromodel_climos_opendap]
    output = thunderbird.split_merged_climos(multiple_inputs)
In [6]:
split_filepaths = get_metalink_content(output.get()[0])

Once the process has completed we can extract the results and ensure it is what we expected.¶

In [7]:
# Check number of output files
assert len(split_filepaths) == len(multiple_inputs) * 3     # 3 output files (aClim, sClim and mClim) for each input file

# Check number of output files corresponding to each interval
aClims = [sf for sf in split_filepaths if 'aClim' in sf]    # annual
sClims = [sf for sf in split_filepaths if 'sClim' in sf]    # seasonal
mClims = [sf for sf in split_filepaths if 'mClim' in sf]    # monthly

assert len(aClims) == len(multiple_inputs)
assert len(sClims) == len(multiple_inputs)
assert len(mClims) == len(multiple_inputs)