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_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()
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()
# 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()