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import numpy as np
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import matplotlib.pyplot as pl
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import warnings
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#export WRADLIB_DATA=/path/to/wradlib-data
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warnings.filterwarnings('ignore')
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from wradlib.io import read_generic_netcdf
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from wradlib.util import get_wradlib_data_file
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import os
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# A little helper function for repeated tasks
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def read_and_overview(filename):
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"""Read NetCDF using read_generic_netcdf and print upper level dictionary keys
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"""
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test = read_generic_netcdf(filename)
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print("\nPrint keys for file %s" % os.path.basename(filename))
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for key in test.keys():
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print("\t%s" % key)
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return test
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filename = '/home/soporte/Downloads/PX1000/PX-20180220-174014-E0.0-Z.nc'
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filename = get_wradlib_data_file(filename)
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test= read_and_overview(filename)
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print("Height",test['Height'])
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print("Azimuth",test['Azimuth'])
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print("Elevation",test['Elevation'])
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print("CalibH-value",test['CalibH-value'])
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print("attributes",test['attributes'])
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print("-------------------------------------------------------------------------------------")
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for key in test.keys():
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print(key,test[str(key)])
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'''
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try:
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get_ipython().magic('matplotlib inline')
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except:
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pl.ion()
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img, meta = wradlib.io.read_dx(filename)
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print("Shape of polar array: %r\n" % (img.shape,))
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print("Some meta data of the DX file:")
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#print("\tdatetime: %r" % (meta["datetime"],))
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#print("\tRadar ID: %s" % (meta["radarid"],))
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img[200:250,:]= np.ones([50,img.shape[1]])*np.nan
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img[300:360,:]= np.ones([60,img.shape[1]])*np.nan
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cgax, pm= wradlib.vis.plot_ppi(img)
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txt = pl.title('Simple PPI')
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print("coordenada angular",img[:,0],len(img[:,0]))
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print("COORDENADA 0",img[0],len(img[0]))
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cbar = pl.gcf().colorbar(pm, pad=0.075)
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#r = np.arange(40, 80)
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#az = np.arange(200, 250)
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#ax, pm = wradlib.vis.plot_ppi(img[200:250, 40:80], r, az, autoext=False)
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#ax, pm = wradlib.vis.plot_ppi(img[200:250, 40:80], r, az)
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#txt = pl.title('Sector PPI')
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pl.show()
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'''
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