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Spatial contour plotΒΆ
This is an example of how to prepare and plot data for a contour plot
Author: Adam Theisen
from arm_test_data import DATASETS
import matplotlib.pyplot as plt
import act
met_contour_list = [
'sgpmetE15.b1.20190508.000000.cdf',
'sgpmetE31.b1.20190508.000000.cdf',
'sgpmetE32.b1.20190508.000000.cdf',
'sgpmetE33.b1.20190508.000000.cdf',
'sgpmetE34.b1.20190508.000000.cdf',
'sgpmetE35.b1.20190508.000000.cdf',
'sgpmetE36.b1.20190508.000000.cdf',
'sgpmetE37.b1.20190508.000000.cdf',
'sgpmetE38.b1.20190508.000000.cdf',
'sgpmetE39.b1.20190508.000000.cdf',
'sgpmetE40.b1.20190508.000000.cdf',
'sgpmetE9.b1.20190508.000000.cdf',
'sgpmetE13.b1.20190508.000000.cdf',
]
met_contour_filenames = [DATASETS.fetch(file) for file in met_contour_list]
time = '2019-05-08T04:00:00.000000000'
data = {}
fields = {}
wind_fields = {}
station_fields = {}
for f in met_contour_filenames:
ds = act.io.arm.read_arm_netcdf(f)
data.update({f: ds})
fields.update({f: ['lon', 'lat', 'temp_mean']})
wind_fields.update({f: ['lon', 'lat', 'wspd_vec_mean', 'wdir_vec_mean']})
station_fields.update(
{
f: [
'lon',
'lat',
'temp_mean',
'atmos_pressure',
'vapor_pressure_mean',
'rh_mean',
]
}
)
display = act.plotting.ContourDisplay(data, figsize=(8, 8))
display.create_contour(fields=fields, time=time, levels=50)
display.plot_vectors_from_spd_dir(fields=wind_fields, time=time, mesh=True, grid_delta=(0.1, 0.1))
display.plot_station(fields=station_fields, time=time, markersize=7, color='red')
plt.show()
Total running time of the script: (0 minutes 0.770 seconds)