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

# 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.rerank?

Signature:
chickadee.rerank(
    obs_file,
    varname=None,
    qdm_file=None,
    analogues_object=None,
    num_cores='4',
    loglevel='INFO',
    analogues_name='analogues',
    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,
    output_formats=None,
)
Docstring:
Quantile Reranking fixes bias introduced by the Climate Analogues step

Parameters
----------
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
qdm_file : ComplexData:mimetype:`application/x-netcdf`, :mimetype:`application/x-ogc-dods`
    Filename of output from QDM step
analogues_object : ComplexData:mimetype:`application/x-gzip`
    Rdata or RDS file containing the analogues produced from the CA step
analogues_name : string
    Name of the R object containing the analogues. You may leave as defualt for RDS files.
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/birds/chickadee/</tmp/chickadee-venv/lib/python3.8/site-packages/birdy/client/base.py-4>
Type:      method

with NamedTemporaryFile(suffix=".nc", prefix="output_", dir="/tmp", delete=True) as out_file:
    output = chickadee.rerank(
        qdm_file = (files("tests") / "data/QDM_expected_output.nc").resolve(),
        obs_file = (files("tests") / "data/tiny_obs.nc").resolve(),
        varname="tasmax",
        out_file=out_file.name,
        num_cores=2,
        analogues_object=(files("tests") / "data/analogues.rda").resolve()
    )
# Use asobj=True to access the output file contents as a dataset
output_dataset_rda = output.get(asobj=True)[0]

with NamedTemporaryFile(suffix=".nc", prefix="output_", dir="/tmp", delete=False) as out_file:
    output = chickadee.rerank(
        qdm_file = (files("tests") / "data/QDM_expected_output.nc").resolve(),
        obs_file = (files("tests") / "data/tiny_obs.nc").resolve(),
        varname="tasmax",
        out_file=out_file.name,
        num_cores=2,
        analogues_object=(files("tests") / "data/analogues.rda").resolve(),
    )
output_dataset_rds = output.get(asobj=True)[0]

expected_data = Dataset((files("tests") / "data/bccaq_expected_output.nc").resolve())
for key, value in expected_data.dimensions.items():
    assert output_dataset_rds.sizes[key] == len(value)

Rerank¶

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

Run the rerank process with RDA input¶

Run the rerank process with RDS input¶

Test for expected output¶