# (C) Copyright 1996-2019 ECMWF.
#
# This software is licensed under the terms of the Apache Licence Version 2.0
# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
# In applying this licence, ECMWF does not waive the privileges and immunities
# granted to it by virtue of its status as an intergovernmental organisation nor
# does it submit to any jurisdiction.
import xarray as xr
import numpy as np
from Magics import macro as magics
ref = "xarray2"
ds = xr.open_dataset('netcdf3_t_z.nc')
png = magics.output(output_name_first_page_number = "off", output_name = ref)
data = magics.mxarray(
xarray_dataset = ds,
xarray_variable_name = "z",
xarray_dimension_settings = {
"time": np.datetime64('2017-10-13T00:00:00.000000000'),
"level": 925}),
contour = magics.mcont(contour_automatic_setting = "ecmwf")
magics.plot(png, data, contour, magics.mcoast())
# (C) Copyright 1996-2019 ECMWF.
#
# This software is licensed under the terms of the Apache Licence Version 2.0
# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
# In applying this licence, ECMWF does not waive the privileges and immunities
# granted to it by virtue of its status as an intergovernmental organisation nor
# does it submit to any jurisdiction.
import xarray as xr
import numpy as np
from Magics import macro as magics
ref = "xarray1"
ds = xr.open_dataset('2t.nc')
png = magics.output(output_name_first_page_number = "off", output_name = ref)
data = magics.mxarray(xarray_dataset = ds, xarray_variable_name = "t2m")
contour = magics.mcont(contour_automatic_setting = "ecmwf")
magics.plot(png, data, contour, magics.mcoast())
# (C) Copyright 1996-2019 ECMWF.
#
# This software is licensed under the terms of the Apache Licence Version 2.0
# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
# In applying this licence, ECMWF does not waive the privileges and immunities
# granted to it by virtue of its status as an intergovernmental organisation nor
# does it submit to any jurisdiction.
import cftime
import xarray as xr
import numpy as np
from Magics import macro as magics
ref = "xarray7"
ds = xr.open_dataset('2dlatlon.nc')
time = cftime.DatetimeNoLeap(2081, 2, 15, 0, 0, 0, 0, 5, 46)
png = magics.output(output_name_first_page_number="off", output_name=ref)
data = magics.mxarray(xarray_dataset=ds,
xarray_variable_name="sic",
xarray_dimension_settings={
"bnds": 1.0,
"time": time
})
contour = magics.mcont(contour_automatic_setting="ecmwf")
magics.plot(png, data, contour, magics.mcoast())
# (C) Copyright 1996-2019 ECMWF.
#
# This software is licensed under the terms of the Apache Licence Version 2.0
# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
# In applying this licence, ECMWF does not waive the privileges and immunities
# granted to it by virtue of its status as an intergovernmental organisation nor
# does it submit to any jurisdiction.
import cftime
import xarray as xr
import numpy as np
from Magics import macro as magics
ref = "xarray3"
ds = xr.open_dataset('tos_O1_2001-2002.nc')
time = cftime.Datetime360Day(2001, 1, 16, 0, 0, 0, 0, 5, 16)
png = magics.output(output_name_first_page_number="off", output_name=ref)
data = magics.mxarray(xarray_dataset=ds,
xarray_variable_name="tos",
xarray_dimension_settings={"time": time})
contour = magics.mcont(contour_automatic_setting="ecmwf")
magics.plot(png, data, contour, magics.mcoast())
# (C) Copyright 1996-2019 ECMWF.
#
# This software is licensed under the terms of the Apache Licence Version 2.0
# which can be obtained at http://www.apache.org/licenses/LICENSE-2.0.
# In applying this licence, ECMWF does not waive the privileges and immunities
# granted to it by virtue of its status as an intergovernmental organisation nor
# does it submit to any jurisdiction.
import xarray as xr
import numpy as np
from Magics import macro as magics
ref = "xarray5"
ds = xr.open_dataset('C3S_OZONE-L4-TC-ASSIM_MSR-201608-fv0020.nc', decode_times=False)
png = magics.output(output_name_first_page_number = "off", output_name = ref)
data = magics.mxarray(xarray_dataset = ds, xarray_variable_name = "total_ozone_column")
contour = magics.mcont(contour_automatic_setting = "ecmwf")
magics.plot(png, data, contour, magics.mcoast())