def _load(self,
domain="NW",
variable="rainfall",
year=2016,
month=8,
part=3):
url = "{url}/radar/radar_coords_{domain}.npz".format(url=self.URL,
domain=domain)
coords = np.load(download_and_cache(url), allow_pickle=True)
resolution = 0.01
lats = coords["lats"] - resolution / 2
lons = coords["lons"] + resolution / 2
url = "{url}/radar/{variable}_{domain}_{year}_{month:02d}.{part}.npz".format(
url=self.URL,
domain=domain,
variable=variable,
year=year,
month=month,
part=part,
)
path = download_and_cache(url)
content = np.load(path, allow_pickle=True)
data = content["data"]
times = content["dates"]
# missing = content['miss_dates']
self.variable = variable
ds = xr.Dataset(
{
variable: (["time", "y", "x"], data),
"x": (["x"], range(0, data.shape[2])),
"y": (["y"], range(0, data.shape[1])),
},
coords={
"lon": (["y", "x"], lons),
"lat": (["y", "x"], lats),
"time": times,
},
)
self.north = np.amax(lats)
self.south = np.amin(lats)
self.east = np.amax(lons)
self.west = np.amin(lons)
ds["lon"].attrs["standard_name"] = "longitude"
ds["lat"].attrs["standard_name"] = "latitude"
ds["time"].attrs["standard_name"] = "time"
ds["x"].attrs["axis"] = "X"
ds["y"].attrs["axis"] = "Y"
self._xarray = ds
def _param_id_dict():
if not PARAMS:
path = download_and_cache(URL)
with open(path) as f:
entries = json.load(f)
for entry in entries["parameters"]:
PARAMS[int(entry["param_id"])] = entry
return PARAMS
def __init__(self, domain="NW", date="20160101"):
url = "{url}/ground_stations/{domain}_{date}.csv".format(url=self.URL,
domain=domain,
date=date)
self.path = download_and_cache(url)
self._pandas = pd.read_csv(self.path,
parse_dates=[4],
infer_datetime_format=True)
def _load(self, bassin="atlantic", url=None):
if url is None:
url = URLS[bassin.lower()]
path = download_and_cache(url)
p = []
with open(path) as f:
lines = f
for line in lines:
if line[0] in (" ", "<", "\n"):
continue
bassin = line[0:2]
number = int(line[2:4])
year = int(line[4:8])
name = line[18:28].strip().lower()
# id = line[0:8]
# http://www.aoml.noaa.gov/hrd/hurdat/hurdat2-format-may2015.pdf
for _ in range(0, int(line[33:36])):
line = next(lines)
knots = float(line[38:41])
pressure = np.NaN if line[43] == "-" else float(
line[43:47])
time = "%s-%s-%sZ%s:%s" % (
line[0:4],
line[4:6],
line[6:8],
line[10:12],
line[12:14],
)
p.append(
dict(
# id=id,
bassin=bassin,
number=number,
year=year,
name=name,
time=parse_date(time),
type=line[16],
status=line[19:21],
lat=float(line[23:27]) * SIGN[line[27]],
lon=float(line[30:35]) * SIGN[line[35]],
knots=knots,
category=category(knots),
pressure=pressure,
))
self.cyclones = self.annotate(pd.DataFrame(p), style="cyclone-track")
def load_remote(self, name):
catalogs = self.settings("datasets-catalogs-urls")
for catalog in catalogs:
url = f"{catalog}/{name}.yaml"
path = download_and_cache(
url,
update_if_out_of_date=True,
return_none_on_404=True,
)
if path:
LOG.debug("Found dataset at %s", url)
return self.load_yaml(path)
return None
def test_download_4():
url = "https://get.ecmwf.int/test-data/climetlab/input/missing.txt"
r = download_and_cache(url, return_none_on_404=True)
assert r is None, r
def test_download_3():
with settings.temporary("download-out-of-date-urls", True):
url = "https://get.ecmwf.int/test-data/climetlab/input/test.txt"
download_and_cache(url)
def test_download_2():
url = "https://github.com/ecmwf/climetlab/raw/main/docs/examples/test.grib"
download_and_cache(url)
def test_download_1():
url = "https://github.com/ecmwf/climetlab/raw/main/docs/examples/test.grib?_=%s" % (
time.time(), )
download_and_cache(url)
def cf_standard_names(version=78):
path = download_and_cache(URL.format(version=version))
xmldoc = minidom.parse(path)
entries = xmldoc.getElementsByTagName("entry")
for entry in entries:
yield entry.attributes["id"].value
