import os
from birdy import WPSClient
from wps_tools.testing import get_target_url
from importlib.resources import files
from tempfile import NamedTemporaryFile
from netCDF4 import Dataset

# Ensure we are in the working directory with access to the data
while os.path.basename(os.getcwd()) != "chickadee":
    os.chdir('../')

# NBVAL_IGNORE_OUTPUT
url = get_target_url("chickadee")
print(f"Using chickadee on {url}")

Using chickadee on https://marble-dev01.pcic.uvic.ca/twitcher/ows/proxy/chickadee/wps

chickadee = WPSClient(url)

# NBVAL_IGNORE_OUTPUT
chickadee.ci?

Signature:
chickadee.ci(
    gcm_file,
    obs_file=None,
    varname=None,
    num_cores='4',
    loglevel='INFO',
    units_bool=True,
    n_pr_bool=True,
    tasmax_units='celsius',
    tasmin_units='celsius',
    pr_units='kg m-2 d-1',
    max_gb=1.0,
    start_date=datetime.date(1971, 1, 1),
    end_date=datetime.date(2005, 12, 31),
    out_file=None,
)
Docstring:
Climate Imprint (CI) downscaling

Parameters
----------
gcm_file : ComplexData:mimetype:`application/x-netcdf`, :mimetype:`application/x-ogc-dods`
    Filename of GCM simulations
obs_file : ComplexData:mimetype:`application/x-netcdf`, :mimetype:`application/x-ogc-dods`
    Filename of high-res gridded historical observations
varname : string
    Name of the NetCDF variable to downscale (e.g. 'tasmax')
out_file : string
    Filename to create with the climate imprint outputs
num_cores : {'1', '2', '3', '4'}positiveInteger
    The number of cores to use for parallel execution
loglevel : {'CRITICAL', 'ERROR', 'WARNING', 'INFO', 'DEBUG', 'NOTSET'}string
    Logging level
units_bool : boolean
    Check the input units and convert them to the target output units
n_pr_bool : boolean
    Check for and eliminate negative precipitation values
tasmax_units : string
    Units used for tasmax in output file
tasmin_units : string
    Units used for tasmin in output file
pr_units : string
    Units used for pr in output file
max_gb : float
    Anapproximately how much RAM to use in the chunk I/O loop. It’s best to set this to about 1/3 to 1/4 of what you want the high-water mark to be
start_date : date
    Defines the stat of the calibration period
end_date : date
    Defines the end of the calibration period

Returns
-------
output : ComplexData:mimetype:`application/x-netcdf`
    Output Netcdf File
File:      ~/code/chickadee/</home/eyvorchuk/code/chickadee/chickadee-venv/lib/python3.8/site-packages/birdy/client/base.py-1>
Type:      method

with NamedTemporaryFile(suffix=".nc", prefix="output_", dir="/tmp", delete=True) as out_file:
    output = chickadee.ci(
        gcm_file = (files("tests") / "data/tiny_gcm.nc").resolve(),
        obs_file = (files("tests") / "data/tiny_obs.nc").resolve(),
        out_file = out_file.name,
        varname="tasmax",
    )

# NBVAL_IGNORE_OUTPUT
from wps_tools.output_handling import nc_to_dataset, auto_construct_outputs

output_dataset = nc_to_dataset(output.get()[0])
output_dataset

<class 'netCDF4._netCDF4.Dataset'>
root group (NETCDF3_CLASSIC data model, file format NETCDF3):
    dimensions(sizes): lon(26), lat(26), time(3651)
    variables(dimensions): float64 lon(lon), float64 lat(lat), float64 time(time), float32 tasmax(time, lat, lon)
    groups:

# NBVAL_IGNORE_OUTPUT
auto_construct_outputs(output.get())

[<class 'netCDF4._netCDF4.Dataset'>
 root group (NETCDF3_CLASSIC data model, file format NETCDF3):
     dimensions(sizes): lon(26), lat(26), time(3651)
     variables(dimensions): float64 lon(lon), float64 lat(lat), float64 time(time), float32 tasmax(time, lat, lon)
     groups: ]

expected_data = Dataset((files("tests") / "data/CI_expected_output.nc").resolve())
for key, value in expected_data.dimensions.items():
    assert str(output_dataset.dimensions[key]) == str(value)

output.get()[0]

'https://marble-dev01.pcic.uvic.ca/wpsoutputs/f0cca536-303f-11f0-a57a-0242ac120006/output_qf7vkijf.nc'

wps_CI¶

wps_CI is a process that runs the ci.netcdf.wrapper function of ClimDown package. To get started, first instatiate the client. Here, the client will try to connect to a remote chickadee instance using the url parameter.¶

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

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

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