wps_climdex_rxnday¶
WPS wrapper for climdex.pcic's rx1day and rx5day functions
Monthly Maximum 1-day Precipitation (climdex.rx1day) This function takes a climdexInput object as input and computes the climdex index Rx1day: monthlyor annual maximum 1-day precipitation.
Monthly Maximum 5-day Consecutive Precipitation (climdex.rx5day) This function takes a climdexInput object as input and computes the climdex index Rx5day: monthlyor annual maximum 5-day consecutive precipitation.
In [1]:
import os
import requests
from birdy import WPSClient
from rpy2 import robjects
from urllib.request import urlretrieve
from importlib.resources import files
from tempfile import NamedTemporaryFile
from wps_tools.R import rda_to_vector, construct_r_out, test_rda_output
from wps_tools.testing import get_target_url
In [2]:
# Ensure we are in the working directory with access to the data
while os.path.basename(os.getcwd()) != "quail":
os.chdir('../')
In [3]:
# NBVAL_IGNORE_OUTPUT
url = get_target_url("quail")
print(f"Using quail on {url}")
Using quail on https://marble-dev01.pcic.uvic.ca/twitcher/ows/proxy/quail/wps
In [4]:
quail = WPSClient(url)
Help for individual processes can be diplayed using the ? command (ex/ bird.process?)¶
In [5]:
# NBVAL_IGNORE_OUTPUT
quail.climdex_rxnday?
Signature: quail.climdex_rxnday( climdex_input, num_days=None, loglevel='INFO', output_file='output.rda', freq='monthly', center_mean_on_last_day=False, output_formats=None, ) Docstring: Computes the mean daily diurnal temperature range. Parameters ---------- climdex_input : ComplexData:mimetype:`application/x-gzip` RDS or Rdata (.rds, .rda, .rdata) file containing R Object of type climdexInput output_file : string Filename to store the output Rdata (extension .rda) freq : {'monthly', 'annual'}string Time frequency to aggregate to num_days : {'1', '5'}positiveInteger Compute rx[1]day or rx[5]day center_mean_on_last_day : boolean Whether to center the 5-day running mean on the last day of the window, insteadof the center day. loglevel : {'CRITICAL', 'ERROR', 'WARNING', 'INFO', 'DEBUG', 'NOTSET'}string Logging level Returns ------- rda_output : ComplexData:mimetype:`application/x-gzip` Rda file containing R output data File: ~/github/quail/</tmp/quail-venv/lib/python3.8/site-packages/birdy/client/base.py-13> Type: method
Run wps_climdex_rxnday Process with rx1day with rda input¶
In [6]:
with NamedTemporaryFile(suffix=".rda", prefix="rx1day_", dir="/tmp", delete=True) as output_file:
output = quail.climdex_rxnday(
climdex_input=(files("tests") / "data/climdexInput.rda").resolve(),
freq="annual",
num_days=1,
output_file=output_file.name,
)
rx1day_url = output.get()[0]
Run wps_climdex_rxnday Process with rx5day with rds input¶
In [7]:
with NamedTemporaryFile(suffix=".rda", prefix="rx5day_", dir="/tmp", delete=True) as output_file:
output = quail.climdex_rxnday(
climdex_input=(files("tests") / "data/climdexInput.rds").resolve(),
freq="annual",
num_days=5,
center_mean_on_last_day=False,
output_file=output_file.name,
)
rx5day_url = output.get()[0]
You can also have multiple inputs
In [8]:
climdex_inputs = [
(files("tests") / "data/climdexInput.rds").resolve(),
(files("tests") / "data/climdexInput.rda").resolve(),
(files("tests") / "data/climdex_input_multiple.rda").resolve(),
]
with NamedTemporaryFile(suffix=".rda", prefix="rx5day_", dir="/tmp", delete=True) as output_file:
output = quail.climdex_rxnday(
climdex_input=climdex_inputs,
freq="annual",
num_days=5,
center_mean_on_last_day=False,
output_file=output_file.name,
)
rx5day_url = output.get()[0]
Access the output with rda_to_vector or construct_r_out from wps_tools.R
In [12]:
# NBVAL_IGNORE_OUTPUT
rx1day = rda_to_vector(rx1day_url, "rx1day1_ci")
# use print() to see whole vector
print(f"rx1day\n{rx1day}")
rx5day = rda_to_vector(rx5day_url, "rx5day1_ci")
print(f"rx5day\n{rx5day}")
rx1day 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 1972 1973 1974 NA 50.8 NA NA NA 38.1 34.8 30.2 45.2 82.3 24.9 27.9 66.3 64.8 42.7 57.9 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986 1987 1988 1989 1990 56.9 NA NA 37.2 50.0 62.0 32.2 NA 54.2 NA NA NA NA NA 58.2 91.6 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 NA 52.8 NA NA 88.0 NA 47.6 33.5 41.8 33.0 36.4 NA 76.0 NA rx5day 1959 1960 1961 1962 1963 1964 1965 1966 1967 1968 1969 1970 1971 NA 66.1 NA NA NA 77.0 78.4 83.1 97.6 94.7 73.2 64.7 102.1 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 134.9 60.0 113.1 162.8 NA NA 74.6 142.4 91.4 87.2 NA 129.6 NA 1985 1986 1987 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 NA NA NA NA 141.5 170.2 NA 87.1 NA NA 151.0 NA 84.0 1998 1999 2000 2001 2002 2003 2004 120.1 113.8 50.6 99.6 NA 164.4 NA
In [10]:
# NBVAL_IGNORE_OUTPUT
construct_r_out([rx1day_url, rx5day_url])
Out[10]:
[[R object with classes: ('numeric',) mapped to:
[ nan, 50.799999, nan, nan, ..., 36.400002, nan, 76.000000, nan]],
[R object with classes: ('numeric',) mapped to:
[ nan, 66.099999, nan, nan, ..., 99.600003, nan, 164.400000, nan],
R object with classes: ('numeric',) mapped to:
[ nan, 66.099999, nan, nan, ..., 99.600003, nan, 164.400000, nan],
R object with classes: ('numeric',) mapped to:
[ nan, 66.099999, nan, nan, ..., 99.600003, nan, 164.400000, nan],
R object with classes: ('numeric',) mapped to:
[ nan, 66.099999, nan, nan, ..., 99.600003, nan, 164.400000, nan]]]
Test output against expected output¶
In [11]:
test_rda_output(
rx1day_url, "rx1day1_ci", "expected_rxnday.rda", "expected_rx1day_annual"
)
test_rda_output(
rx5day_url, "rx5day1_ci", "expected_rxnday.rda", "expected_rx5day_annual"
)