def test_declarative_figsize():
"""Test having an all float figsize."""
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.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_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_declarative_barb_earth_relative():
"""Test making a contour plot."""
import numpy as np
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 = np.arange(0, 20000, 120).tolist()
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
wind_geo = PlotGeometry()
wind_geo.geometry = wind_data['geometry']
wind_geo.fill = wind_data['fill']
wind_geo.stroke = 'none'
###########################
# Plot the cities from the 'geometry' column, marked with diamonds ('D'). Label each point
# with the name of the city, and it's probability of tropical-storm-force winds on the line
# below. Points are set to plot in white and the font color is set to black.
city_geo = PlotGeometry()
city_geo.geometry = cities['geometry']
city_geo.marker = 'D'
city_geo.labels = cities['NAME'] + '\n(' + cities['PERCENTAGE'] + ')'
city_geo.fill = 'white'
city_geo.label_facecolor = 'black'
###########################
# Add the geometry plots to a panel and container. Finally, we are left with a complete plot of
# wind speed probabilities, along with some select cities and their specific probabilities.
panel = MapPanel()
panel.title = 'NHC 5-Day Tropical-Storm-Force Wind Probabilities (Valid 12z Aug 20 2021)'
panel.plots = [wind_geo, city_geo]
panel.area = [-90, -52, 27, 48]
panel.projection = 'mer'
panel.layers = ['lakes', 'land', 'ocean', 'states', 'coastline', 'borders']
pc = PanelContainer()
pc.size = (12, 10)
pc.panels = [panel]
pc.show()
def test_declarative_plot_geometry_polygons():
"""Test that `PlotGeometry` correctly plots MultiPolygon and Polygon objects."""
from shapely.geometry import MultiPolygon, Polygon
# MultiPolygons and Polygons to plot
slgt_risk_polygon = MultiPolygon([
Polygon([
(-87.43, 41.86),
(-91.13, 41.39),
(-95.24, 40.99),
(-97.47, 40.4),
(-98.39, 41.38),
(-96.54, 42.44),
(-94.02, 44.48),
(-92.62, 45.48),
(-89.49, 45.91),
(-86.38, 44.92),
(-86.26, 43.37),
(-86.62, 42.45),
(-87.43, 41.86),
]),
Polygon([
(-74.02, 42.8),
(-72.01, 43.08),
(-71.42, 42.77),
(-71.76, 42.29),
(-72.73, 41.89),
(-73.89, 41.93),
(-74.4, 42.28),
(-74.02, 42.8),
])
])
enh_risk_polygon = Polygon([(-87.42, 43.67), (-88.44, 42.65),
(-90.87, 41.92), (-94.63, 41.84),
(-95.13, 42.22), (-95.23, 42.54),
(-94.79, 43.3), (-92.81, 43.99),
(-90.62, 44.55), (-88.51, 44.61),
(-87.42, 43.67)])
# Plot geometry, set colors and labels
geo = PlotGeometry()
geo.geometry = [slgt_risk_polygon, enh_risk_polygon]
geo.stroke = ['#DDAA00', '#FF6600']
geo.fill = None
geo.labels = ['SLGT', 'ENH']
geo.label_facecolor = ['#FFE066', '#FFA366']
geo.label_edgecolor = ['#DDAA00', '#FF6600']
geo.label_fontsize = 'large'
# Place plot in a panel and container
panel = MapPanel()
panel.area = [-125, -70, 20, 55]
panel.projection = 'lcc'
panel.title = ' '
panel.layers = ['coastline', 'borders', 'usstates']
panel.plots = [geo]
pc = PanelContainer()
pc.size = (12, 12)
pc.panels = [panel]
pc.draw()
return pc.figure
