def plot_style(name, path):
print("plot_style", name, file=sys.stderr)
yaml = climetlab.plotting.style(name).data
data = None
gallery = yaml.get("gallery", {})
if "sample" in gallery:
sample = gallery["sample"]
if "source" in sample:
source = sample["source"]
data = get_source(source["name"], source.get("to_pandas"),
**source.get("args", {}))
else:
dataset = sample["dataset"]
data = get_dataset(dataset["name"], dataset.get("to_pandas"),
**dataset.get("args", {}))
else:
if "msymb" in yaml["magics"]:
data = get_dataset(
"sample-bufr-data",
to_pandas={
"columns": ("latitude", "longitude"),
"filters": {}
},
)
if "mcont" in yaml["magics"]:
data = get_dataset("sample-grib-data")
extra = gallery.get("plot_map", {})
climetlab.plot_map(data, style=name, path=path, **extra)
print("done", name, file=sys.stderr)
def test_wrapper_xarray_grib():
source = load_source("dummy-source", kind="grib", date=20000101)
ds = source.to_xarray()
lat, lon = find_lat_lon(ds)
assert lat is not None
assert lon is not None
cml.plot_map(ds)
def test_plot():
for s in load_source("file", "docs/examples/test.grib"):
plot_map(s)
# test.grib fields endStep is 0, so datetime == valid_datetime
assert s.datetime() == s.valid_datetime()
# test shape
assert s.shape == (11, 19)
def test_plot_1():
s = cml.load_source("file", climetlab_file("docs/examples/test.grib"))
assert cml.plot_map(s) is None
assert cml.plot_map(s[0]) is None
p = cml.new_plot()
p.plot_map(s[0])
p.plot_map(s[1])
assert p.show() is None
with pytest.raises(TypeError):
cml.plot_map(s, unknown=42)
def dont_test_wrapper_xarray_plot_map(coords):
source = load_source(
"dummy-source",
kind="netcdf",
dims=coords.split(","),
)
ds = source.to_xarray()
if "custom_lat" in ds.keys():
ds["custom_lat"].attrs["long_name"] = "latitude"
if "custom_lon" in ds.keys():
ds["custom_lon"].attrs["standard_name"] = "longitude"
lat, lon = find_lat_lon(ds)
assert lat is not None
assert lon is not None
cml.plot_map(ds)
def checksum_of_plot_map(ds):
with temp_file(extension=".png") as filename:
cml.plot_map(ds, path=filename)
with open(filename, "rb") as f:
return f.read()
def test_numpy_xarray():
s = cml.load_source("file", climetlab_file("docs/examples/test.grib"))
x = s.to_xarray()
cml.plot_map(x.msl.values, metadata=x.msl)
def test_numpy_xarray():
s = cml.load_source("file", "docs/examples/test.nc")
x = s.to_xarray()
cml.plot_map(x.msl.values, metadata=x.msl)
import climetlab as cml
data = cml.load_source(
"url",
("https://www.ncei.noaa.gov/data/international-best-track-archive-for-climate-stewardship-ibtracs"
"/v04r00/access/csv/ibtracs.SP.list.v04r00.csv"),
)
pd = data.to_pandas()
uma = pd[pd.NAME == "UMA:VELI"]
cml.plot_map(uma, style="cyclone-track")
from climetlab import load_source, plot_map
s = load_source("file", "docs/examples/test.grib")
plot_map(s[0], path="x.png")
plot_map(s[1], path="y.png")
# plot_map(s)
def plot_layer(name, path):
print("plot_layer", name, file=sys.stderr)
climetlab.plot_map(None, background=False, foreground=name, path=path)
print("done", name, file=sys.stderr)
def plot_projection(name, path):
print("plot_projection", name, file=sys.stderr)
climetlab.plot_map(None, projection=name, background="land-sea", path=path)
print("done", name, file=sys.stderr)
import climetlab as cml
# cml.settings.set("plotting-options", {'dump_yaml': True})
dataset = cml.load_dataset("example-dataset")
data = dataset[0]
cml.plot_map(data, foreground=False)
cml.plot_map(data, foreground=True)
cml.plot_map(data, foreground="example-foreground")
cml.plot_map(
data,
foreground=dict(
map_grid=False,
map_label=False,
map_grid_frame=True,
map_grid_frame_thickness=5,
map_boundaries=True,
),
)
# Partial update of the current `foreground`
# How to do is still to be decided
# Option 1
cml.plot_map(
data,
foreground={
def test_numpy_1():
ds = cml.load_dataset("weather-bench")
z500 = ds.to_xarray()
z = z500.sel({"time": "1979-01-01"}).z.values
cml.plot_map(z[0], metadata=z500.z)
def dont_test_plot_map_grib():
source = load_source("dummy-source", kind="grib", date=20000101)
cml.plot_map(source)
def plot():
bbox = BoundingBox(north=90, west=0, east=360, south=-90)
cml.plot_map(bounding_box=bbox, projection="polar-north")
import climetlab as cml
data = cml.load_dataset("hurricane-database", "atlantic")
print(data.home_page)
irma = data.to_pandas(name="irma", year=2017)
cml.plot_map(irma)
def test_netcdf():
for s in load_source("file", "docs/examples/test.nc"):
plot_map(s)
def test_netcdf():
for s in load_source("file", climetlab_file("docs/examples/test.nc")):
plot_map(s)
