60 lines
1.4 KiB
Python
60 lines
1.4 KiB
Python
#!/usr/bin/python
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import os
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import sys
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import glob
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import pickle
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import numpy as np
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import matplotlib.pyplot as plt
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def blocking_display_signal_map(
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data_vector: np.ndarray,
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fp: str,
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vmin: float = -80.0,
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vmax: float = -40.0
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):
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'''
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'''
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plt.scatter(data_vector[:, 3], data_vector[:, 4], s=50, c=data_vector[:, 2])
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# plt.xlim()
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# plt.ylim()
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plt.colorbar()
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plt.xlabel('loc x (m)')
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plt.ylabel('loc y (m)')
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# plt.show()
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plt.draw()
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plt.savefig(fp, dpi=50)
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# plt.pause(0.1)
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# q = input("press Enter to continue... type q to quit: ")
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# if q == 'q':
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# sys.exit()
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plt.close()
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if len(sys.argv) < 3:
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print('Usage: {} pickle_fp outputfolder'.format(sys.argv[0]))
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sys.exit(0)
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pickle_fp = sys.argv[1]
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outputfolder = sys.argv[2]
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if not os.path.isdir(outputfolder):
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try:
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os.makedirs(outputfolder)
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except BaseException:
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raise
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############################
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# load
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############################
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all_data = pickle.load(open(pickle_fp, 'rb'))
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for data in all_data:
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num_of_entries = len(data['measurements'])
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filename = (
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"{}_{}_{}_{}_{}_{}_{}entries.png"
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.format(data['country_code'], data['radio'], data['mcc'], data['mnc'], data['area'], data['cell'], num_of_entries)
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)
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blocking_display_signal_map(data['measurements'], "{}/{}".format(outputfolder, filename))
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