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plot_data.py
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plot_data.py
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import glob
import act
import matplotlib.pyplot as plt
year = '2020102'
files = glob.glob('./data/sgpmetE13.b1/*.' + year + '*')
files.sort()
ds = act.io.read_arm_netcdf(files)
ds = act.qc.arm.add_dqr_to_qc(ds, variable='temp_mean')
print(ds['qc_temp_mean'].values)
#files = glob.glob('./data/nsa60noaacrnX1.b1/*.' + year + '*')
#files.sort()
#ds2 = act.io.read_arm_netcdf(files)
#ds2 = act.qc.arm.add_dqr_to_qc(ds2)
#display = act.plotting.TimeSeriesDisplay({'ARM': ds, 'NOAA': ds2}, figsize=(15, 10), subplot_shape=(2,))
#display.plot('temp_mean', subplot_index=(0,), dsname='ARM')
#display.plot('temperature', subplot_index=(0,), dsname='NOAA')
#display.qc_flag_block_plot('rh_mean', subplot_index=(1,), dsname='ARM')
display = act.plotting.TimeSeriesDisplay(ds, subplot_shape=(2,))
display.plot('temp_mean', subplot_index=(0,))
display.qc_flag_block_plot('temp_mean', subplot_index=(1,))
plt.show()