def test_latlon():
"""Test our handling of lat/lon information."""
data = xr.open_dataset(get_test_data('irma_gfs_example.nc', as_file_obj=False))
img = ImagePlot()
img.data = data
img.field = 'Temperature_isobaric'
img.level = 500 * units.hPa
img.time = datetime(2017, 9, 5, 15, 0, 0)
contour = ContourPlot()
contour.data = data
contour.field = 'Geopotential_height_isobaric'
contour.level = img.level
contour.time = img.time
panel = MapPanel()
panel.projection = 'lcc'
panel.area = 'us'
panel.plots = [img, contour]
pc = PanelContainer()
pc.panel = panel
pc.draw()
return pc.figure
def test_latlon():
"""Test our handling of lat/lon information."""
data = xr.open_dataset(get_test_data('irma_gfs_example.nc', as_file_obj=False))
img = ImagePlot()
img.data = data
img.field = 'Temperature_isobaric'
img.level = 500 * units.hPa
img.time = datetime(2017, 9, 5, 15, 0, 0)
img.colorbar = None
contour = ContourPlot()
contour.data = data
contour.field = 'Geopotential_height_isobaric'
contour.level = img.level
contour.time = img.time
panel = MapPanel()
panel.projection = 'lcc'
panel.area = 'us'
panel.plots = [img, contour]
pc = PanelContainer()
pc.panel = panel
pc.draw()
return pc.figure
def test_show():
"""Test that show works properly."""
pc = PanelContainer()
# Matplotlib warns when using show with Agg
with warnings.catch_warnings():
warnings.simplefilter('ignore', UserWarning)
pc.show()
def test_show(set_agg_backend):
"""Test that show works properly."""
pc = PanelContainer()
# Matplotlib warns when using show with Agg
with warnings.catch_warnings():
warnings.simplefilter('ignore', UserWarning)
pc.show()
def test_save():
"""Test that our saving function works."""
pc = PanelContainer()
fobj = BytesIO()
pc.save(fobj, format='png')
fobj.seek(0)
# Test that our file object had something written to it.
assert fobj.read()
def test_save():
"""Test that our saving function works."""
pc = PanelContainer()
fobj = BytesIO()
pc.save(fobj, format='png')
fobj.seek(0)
# Test that our file object had something written to it.
assert fobj.read()
def test_panel():
"""Test the functionality of the panel property."""
panel = MapPanel()
pc = PanelContainer()
pc.panels = [panel]
assert pc.panel is panel
pc.panel = panel
assert pc.panel is panel
def test_panel():
"""Test the functionality of the panel property."""
panel = MapPanel()
pc = PanelContainer()
pc.panels = [panel]
assert pc.panel is panel
pc.panel = panel
assert pc.panel is panel
def test_copy():
"""Test that the copy method works for all classes in `declarative.py`."""
# Copies of plot objects
objects = [ImagePlot(), ContourPlot(), FilledContourPlot(), BarbPlot(), PlotObs(),
PlotGeometry()]
for obj in objects:
obj.time = datetime.now()
copied_obj = obj.copy()
assert obj is not copied_obj
assert obj.time == copied_obj.time
# Copies of MapPanel and PanelContainer
obj = MapPanel()
obj.title = 'Sample Text'
copied_obj = obj.copy()
assert obj is not copied_obj
assert obj.title == copied_obj.title
obj = PanelContainer()
obj.size = (10, 10)
copied_obj = obj.copy()
assert obj is not copied_obj
assert obj.size == copied_obj.size
# Copies of plots in MapPanels should not point to same location in memory
obj = MapPanel()
obj.plots = [PlotObs(), PlotGeometry(), BarbPlot(), FilledContourPlot(), ContourPlot(),
ImagePlot()]
copied_obj = obj.copy()
for i in range(len(obj.plots)):
assert obj.plots[i] is not copied_obj.plots[i]
def test_global():
"""Test that we can set global extent."""
data = xr.open_dataset(GiniFile(get_test_data('NHEM-MULTICOMP_1km_IR_20151208_2100.gini')))
img = ImagePlot()
img.data = data
img.field = 'IR'
panel = MapPanel()
panel.area = 'global'
panel.plots = [img]
pc = PanelContainer()
pc.panel = panel
pc.draw()
return pc.figure
def test_ndim_error_vector(cfeature):
"""Make sure we get a useful error when the field is not set."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
barbs = BarbPlot()
barbs.data = data
barbs.field = ['u_wind', 'v_wind']
barbs.level = None
panel = MapPanel()
panel.area = (-110, -60, 25, 55)
panel.projection = 'lcc'
panel.plots = [barbs]
pc = PanelContainer()
pc.panel = panel
with pytest.raises(ValueError):
pc.draw()
def test_declarative_image():
"""Test making an image plot."""
data = xr.open_dataset(GiniFile(get_test_data('NHEM-MULTICOMP_1km_IR_20151208_2100.gini')))
img = ImagePlot()
img.data = data.metpy.parse_cf('IR')
img.colormap = 'Greys_r'
panel = MapPanel()
panel.title = 'Test'
panel.plots = [img]
pc = PanelContainer()
pc.panel = panel
pc.draw()
assert panel.ax.get_title() == 'Test'
return pc.figure
def test_declarative_image():
"""Test making an image plot."""
data = xr.open_dataset(GiniFile(get_test_data('NHEM-MULTICOMP_1km_IR_20151208_2100.gini')))
img = ImagePlot()
img.data = data.metpy.parse_cf('IR')
img.colormap = 'Greys_r'
panel = MapPanel()
panel.title = 'Test'
panel.plots = [img]
pc = PanelContainer()
pc.panel = panel
pc.draw()
assert panel.ax.get_title() == 'Test'
return pc.figure
def test_projection_object():
"""Test that we can pass a custom map projection."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.level = 700 * units.hPa
contour.field = 'Temperature'
panel = MapPanel()
panel.area = (-110, -60, 25, 55)
panel.projection = ccrs.Mercator()
panel.layers = [cfeature.LAKES]
panel.plots = [contour]
pc = PanelContainer()
pc.panel = panel
pc.draw()
return pc.figure
def test_projection_object(ccrs, cfeature):
"""Test that we can pass a custom map projection."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.level = 700 * units.hPa
contour.field = 'Temperature'
panel = MapPanel()
panel.area = (-110, -60, 25, 55)
panel.projection = ccrs.Mercator()
panel.layers = [cfeature.LAKES]
panel.plots = [contour]
pc = PanelContainer()
pc.panel = panel
pc.draw()
return pc.figure
def test_ndim_error_scalar(cfeature):
"""Make sure we get a useful error when the field is not set."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Temperature'
contour.level = None
panel = MapPanel()
panel.area = (-110, -60, 25, 55)
panel.projection = 'lcc'
panel.layers = [cfeature.LAKES]
panel.plots = [contour]
pc = PanelContainer()
pc.panel = panel
with pytest.raises(ValueError):
pc.draw()
def test_declarative_sfc_obs_full(ccrs):
"""Test making a full surface observation plot."""
data = pd.read_csv(get_test_data('SFC_obs.csv', as_file_obj=False),
infer_datetime_format=True, parse_dates=['valid'])
obs = PlotObs()
obs.data = data
obs.time = datetime(1993, 3, 12, 13)
obs.time_window = timedelta(minutes=15)
obs.level = None
obs.fields = ['tmpf', 'dwpf', 'emsl', 'cloud_cover', 'wxsym']
obs.locations = ['NW', 'SW', 'NE', 'C', 'W']
obs.colors = ['red', 'green', 'black', 'black', 'blue']
obs.formats = [None, None, lambda v: format(10 * v, '.0f')[-3:], 'sky_cover',
'current_weather']
obs.vector_field = ('uwind', 'vwind')
obs.reduce_points = 1
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.area = (-124, -72, 20, 53)
panel.area = 'il'
panel.projection = ccrs.PlateCarree()
panel.layers = ['coastline', 'borders', 'states']
panel.plots = [obs]
# Bringing it all together
pc = PanelContainer()
pc.size = (10, 10)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_declarative_smooth_field():
"""Test the smoothing of the field with smooth_field trait."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Geopotential_height'
contour.level = 700 * units.hPa
contour.contours = list(range(0, 4000, 30))
contour.linewidth = 1
contour.linecolor = 'black'
contour.smooth_field = 3
panel = MapPanel()
panel.area = 'us'
panel.projection = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour]
pc = PanelContainer()
pc.size = (10.5, 10.5)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_declarative_contour_convert_units(fix_is_closed_polygon):
"""Test making a contour plot."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Temperature'
contour.level = 700 * units.hPa
contour.contours = 30
contour.linewidth = 1
contour.linecolor = 'red'
contour.linestyle = 'dashed'
contour.clabels = True
contour.plot_units = 'degC'
panel = MapPanel()
panel.area = 'us'
panel.proj = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_declarative_colored_barbs(ccrs):
"""Test making a surface plot with a colored barb (gh-1274)."""
data = pd.read_csv(get_test_data('SFC_obs.csv', as_file_obj=False),
infer_datetime_format=True, parse_dates=['valid'])
obs = PlotObs()
obs.data = data
obs.time = datetime(1993, 3, 12, 13)
obs.level = None
obs.vector_field = ('uwind', 'vwind')
obs.vector_field_color = 'red'
obs.reduce_points = .5
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.projection = ccrs.PlateCarree()
panel.area = 'NE'
panel.layers = ['states']
panel.plots = [obs]
# Bringing it all together
pc = PanelContainer()
pc.size = (10, 10)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_declarative_station_plot_fontsize():
"""Test adjusting the font size for station plots in PlotObs."""
data = parse_metar_file(get_test_data('metar_20190701_1200.txt',
as_file_obj=False), year=2019, month=7)
obs = PlotObs()
obs.data = data
obs.time = datetime(2019, 7, 1, 12)
obs.time_window = timedelta(minutes=15)
obs.level = None
obs.fields = ['cloud_coverage', 'air_temperature', 'dew_point_temperature',
'air_pressure_at_sea_level', 'current_wx1_symbol']
obs.plot_units = [None, 'degF', 'degF', None, None]
obs.locations = ['C', 'NW', 'SW', 'NE', 'W']
obs.formats = ['sky_cover', None, None, lambda v: format(v * 10, '.0f')[-3:],
'current_weather']
obs.reduce_points = 3
obs.vector_field = ['eastward_wind', 'northward_wind']
obs.fontsize = 8
panel = MapPanel()
panel.area = 'centus'
panel.projection = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [obs]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_declarative_colorbar_fontsize():
"""Test adjusting the font size of a colorbar."""
data = xr.open_dataset(get_test_data('GFS_test.nc', as_file_obj=False))
cfill = FilledContourPlot()
cfill.data = data
cfill.field = 'Temperature_isobaric'
cfill.level = 300 * units.hPa
cfill.time = datetime(2010, 10, 26, 12)
cfill.contours = list(range(210, 250, 2))
cfill.colormap = 'BuPu'
cfill.colorbar = 'horizontal'
cfill.colorbar_fontsize = 'x-small'
panel = MapPanel()
panel.area = (-124, -72, 20, 53)
panel.projection = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [cfill]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_declarative_title_fontsize():
"""Test adjusting the font size of a MapPanel's title text."""
data = xr.open_dataset(get_test_data('NAM_test.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Geopotential_height_isobaric'
contour.level = 300 * units.hPa
contour.linewidth = 2
contour.contours = list(range(0, 2000, 12))
contour.scale = 1e-1
panel = MapPanel()
panel.area = (-124, -72, 20, 53)
panel.projection = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour]
panel.title = '300 mb Geopotential Height'
panel.title_fontsize = 20
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_declarative_multiple_sfc_obs_change_units(ccrs):
"""Test making a surface observation plot."""
data = parse_metar_file(get_test_data('metar_20190701_1200.txt', as_file_obj=False),
year=2019, month=7)
obs = PlotObs()
obs.data = data
obs.time = datetime(2019, 7, 1, 12)
obs.time_window = timedelta(minutes=15)
obs.level = None
obs.fields = ['air_temperature', 'dew_point_temperature', 'air_pressure_at_sea_level']
obs.locations = ['NW', 'W', 'NE']
obs.colors = ['red', 'green', 'black']
obs.reduce_points = 0.75
obs.plot_units = ['degF', 'degF', None]
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.projection = ccrs.PlateCarree()
panel.area = 'in'
panel.layers = ['states']
panel.plots = [obs]
# Bringing it all together
pc = PanelContainer()
pc.size = (12, 12)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_attribute_error_station(ccrs):
"""Make sure we get a useful error when the station variable is not found."""
data = pd.read_csv(get_test_data('SFC_obs.csv', as_file_obj=False),
infer_datetime_format=True, parse_dates=['valid'])
data.rename(columns={'station': 'location'}, inplace=True)
obs = PlotObs()
obs.data = data
obs.time = datetime(1993, 3, 12, 12)
obs.level = None
obs.fields = ['tmpf']
obs.time_window = timedelta(minutes=15)
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.projection = ccrs.PlateCarree()
panel.area = 'in'
panel.layers = ['states']
panel.plots = [obs]
panel.title = f'Surface Observations for {obs.time}'
# Bringing it all together
pc = PanelContainer()
pc.size = (10, 10)
pc.panels = [panel]
with pytest.raises(AttributeError):
pc.draw()
def test_declarative_upa_obs():
"""Test making a full upperair observation plot."""
data = pd.read_csv(get_test_data('UPA_obs.csv', as_file_obj=False))
obs = PlotObs()
obs.data = data
obs.time = datetime(1993, 3, 14, 0)
obs.level = 500 * units.hPa
obs.fields = ['temperature', 'dewpoint', 'height']
obs.locations = ['NW', 'SW', 'NE']
obs.formats = [None, None, lambda v: format(v, '.0f')[:3]]
obs.vector_field = ('u_wind', 'v_wind')
obs.vector_field_length = 7
obs.reduce_points = 0
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.area = (-124, -72, 20, 53)
panel.projection = 'lcc'
panel.layers = ['coastline', 'borders', 'states', 'land']
panel.plots = [obs]
# Bringing it all together
pc = PanelContainer()
pc.size = (15, 10)
pc.panels = [panel]
pc.draw()
obs.level = 300 * units.hPa
return pc.figure
def test_declarative_sfc_obs_changes(ccrs):
"""Test making a surface observation plot, changing the field."""
data = pd.read_csv(get_test_data('SFC_obs.csv', as_file_obj=False),
infer_datetime_format=True, parse_dates=['valid'])
obs = PlotObs()
obs.data = data
obs.time = datetime(1993, 3, 12, 12)
obs.level = None
obs.fields = ['tmpf']
obs.colors = ['black']
obs.time_window = timedelta(minutes=15)
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.projection = ccrs.PlateCarree()
panel.area = 'in'
panel.layers = ['states']
panel.plots = [obs]
panel.title = f'Surface Observations for {obs.time}'
# Bringing it all together
pc = PanelContainer()
pc.size = (10, 10)
pc.panels = [panel]
pc.draw()
obs.fields = ['dwpf']
obs.colors = ['green']
return pc.figure
def test_declarative_sfc_text():
"""Test making a surface observation plot with text."""
data = pd.read_csv(get_test_data('SFC_obs.csv', as_file_obj=False),
infer_datetime_format=True, parse_dates=['valid'])
obs = PlotObs()
obs.data = data
obs.time = datetime(1993, 3, 12, 12)
obs.time_window = timedelta(minutes=15)
obs.level = None
obs.fields = ['station']
obs.colors = ['black']
obs.formats = ['text']
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.projection = 'lcc'
panel.area = 'in'
panel.layers = ['states']
panel.plots = [obs]
# Bringing it all together
pc = PanelContainer()
pc.size = (10, 10)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_declarative_smooth_contour():
"""Test making a contour plot using smooth_contour."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Temperature'
contour.level = 700 * units.hPa
contour.contours = 30
contour.linewidth = 1
contour.linecolor = 'red'
contour.smooth_contour = 5
panel = MapPanel()
panel.area = 'us'
panel.projection = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour]
pc = PanelContainer()
pc.size = (8.0, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_plotobs_units_with_formatter(ccrs):
"""Test using PlotObs with a field that both has units and a custom formatter."""
df = pd.read_csv(get_test_data('SFC_obs.csv', as_file_obj=False),
infer_datetime_format=True, parse_dates=['valid'])
df.units = {'alti': 'inHg'}
# Plot desired data
obs = PlotObs()
obs.data = df
obs.time = datetime(1993, 3, 12, 12)
obs.time_window = timedelta(minutes=15)
obs.level = None
obs.fields = ['alti']
obs.plot_units = ['hPa']
obs.locations = ['NE']
# Set a format for plotting MSLP
obs.formats = [lambda v: format(v * 10, '.0f')[-3:]]
obs.reduce_points = 0.75
# Panel for plot with Map features
panel = MapPanel()
panel.layout = (1, 1, 1)
panel.projection = 'lcc'
panel.area = 'in'
panel.plots = [obs]
# Bringing it all together
pc = PanelContainer()
pc.panels = [panel]
pc.size = (10, 10)
pc.draw()
return pc.figure
def test_declarative_global_gfs():
"""Test making a global contour plot using GFS."""
data = xr.open_dataset(get_test_data('GFS_global.nc', as_file_obj=False))
cntr = ContourPlot()
cntr.data = data
cntr.time = datetime(2021, 1, 30, 12)
cntr.field = 'Geopotential_height_isobaric'
cntr.level = 300 * units.hPa
cntr.contours = np.arange(0, 100000, 120).tolist()
cntr.linecolor = 'darkblue'
cntr.linewidth = 1
panel = MapPanel()
panel.area = [-180, 180, 10, 90]
panel.projection = 'ps'
panel.layers = ['coastline']
panel.plots = [cntr]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_declarative_barb_scale():
"""Test making a contour plot."""
data = xr.open_dataset(get_test_data('GFS_test.nc', as_file_obj=False))
barb = BarbPlot()
barb.data = data
barb.level = 300 * units.hPa
barb.field = ['u-component_of_wind_isobaric', 'v-component_of_wind_isobaric']
barb.skip = (3, 3)
barb.earth_relative = False
barb.scale = 2
panel = MapPanel()
panel.area = 'us'
panel.projection = 'data'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [barb]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
barb.level = 700 * units.hPa
return pc.figure
def test_declarative_overlay_projections():
"""Test making a contour plot."""
data = xr.open_dataset(get_test_data('NAM_test.nc', as_file_obj=False))
data2 = xr.open_dataset(get_test_data('GFS_test.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Geopotential_height_isobaric'
contour.level = 300 * units.hPa
contour.linecolor = 'red'
contour.linestyle = '-'
contour.linewidth = 2
contour.contours = np.arange(0, 20000, 120).tolist()
contour2 = ContourPlot()
contour2.data = data2
contour2.field = 'Geopotential_height_isobaric'
contour2.level = 300 * units.hPa
contour2.linecolor = 'blue'
contour2.linestyle = '-'
contour2.linewidth = 2
contour2.contours = np.arange(0, 20000, 120).tolist()
panel = MapPanel()
panel.area = (-124, -72, 20, 53)
panel.projection = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour, contour2]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_declarative_gridded_scale():
"""Test making a contour plot."""
data = xr.open_dataset(get_test_data('NAM_test.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Geopotential_height_isobaric'
contour.level = 300 * units.hPa
contour.linewidth = 2
contour.contours = np.arange(0, 2000, 12).tolist()
contour.scale = 1e-1
contour.clabels = True
panel = MapPanel()
panel.area = (-124, -72, 20, 53)
panel.projection = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_declarative_barb_earth_relative():
"""Test making a contour plot."""
data = xr.open_dataset(get_test_data('NAM_test.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Geopotential_height_isobaric'
contour.level = 300 * units.hPa
contour.linecolor = 'red'
contour.linestyle = '-'
contour.linewidth = 2
contour.contours = range(0, 20000, 120)
barb = BarbPlot()
barb.data = data
barb.level = 300 * units.hPa
barb.time = datetime(2016, 10, 31, 12)
barb.field = ['u-component_of_wind_isobaric', 'v-component_of_wind_isobaric']
barb.skip = (5, 5)
barb.color = 'black'
barb.barblength = 6.5
barb.earth_relative = False
panel = MapPanel()
panel.area = (-124, -72, 20, 53)
panel.projection = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour, barb]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_declarative_barb_options():
"""Test making a contour plot."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
barb = BarbPlot()
barb.data = data
barb.level = 300 * units.hPa
barb.field = ['u_wind', 'v_wind']
barb.skip = (10, 10)
barb.color = 'blue'
barb.pivot = 'tip'
barb.barblength = 6.5
panel = MapPanel()
panel.area = 'us'
panel.projection = 'data'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [barb]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
def test_declarative_events():
"""Test that resetting traitlets properly propagates."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Temperature'
contour.level = 850 * units.hPa
contour.contours = 30
contour.linewidth = 1
contour.linecolor = 'red'
img = ImagePlot()
img.data = data
img.field = 'v_wind'
img.level = 700 * units.hPa
img.colormap = 'hot'
img.image_range = (3000, 5000)
panel = MapPanel()
panel.area = 'us'
panel.proj = 'lcc'
panel.layers = ['coastline', 'borders', 'states']
panel.plots = [contour, img]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
# Update some properties to make sure it regenerates the figure
contour.linewidth = 2
contour.linecolor = 'green'
contour.level = 700 * units.hPa
contour.field = 'Specific_humidity'
img.field = 'Geopotential_height'
img.colormap = 'plasma'
return pc.figure
def test_declarative_contour():
"""Test making a contour plot."""
data = xr.open_dataset(get_test_data('narr_example.nc', as_file_obj=False))
contour = ContourPlot()
contour.data = data
contour.field = 'Temperature'
contour.level = 700 * units.hPa
contour.contours = 30
contour.linewidth = 1
contour.linecolor = 'red'
panel = MapPanel()
panel.area = 'us'
panel.proj = 'lcc'
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [contour]
pc = PanelContainer()
pc.size = (8, 8)
pc.panels = [panel]
pc.draw()
return pc.figure
########################### # Create a contour plot of temperature contour = ContourPlot() contour.data = narr contour.field = 'Temperature' contour.level = 850 * units.hPa contour.linecolor = 'red' contour.contours = 15 ########################### # Create an image plot of Geopotential height img = ImagePlot() img.data = narr img.field = 'Geopotential_height' img.level = 850 * units.hPa ########################### # Plot the data on a map panel = MapPanel() panel.area = 'us' panel.layers = ['coastline', 'borders', 'states', 'rivers', 'ocean', 'land'] panel.title = 'NARR Example' panel.plots = [contour, img] pc = PanelContainer() pc.size = (10, 8) pc.panels = [panel] pc.show()
# Distributed under the terms of the BSD 3-Clause License.
# SPDX-License-Identifier: BSD-3-Clause
"""
Simple Plotting
===============
Demonstrate the use of MetPy's simplified plotting interface.
Plots a sample satellite image file.
"""
import xarray as xr
from metpy.cbook import get_test_data
from metpy.io import GiniFile
from metpy.plots import ImagePlot, MapPanel, PanelContainer
data = xr.open_dataset(GiniFile(get_test_data('NHEM-MULTICOMP_1km_IR_20151208_2100.gini')))
img = ImagePlot()
img.data = data
img.field = 'IR'
img.colormap = 'Greys_r'
panel = MapPanel()
panel.plots = [img]
pc = PanelContainer()
pc.panels = [panel]
pc.show()
