kopia lustrzana https://github.com/rs1729/RS
48 wiersze
919 B
Python
48 wiersze
919 B
Python
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import os
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import sys
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import numpy as np
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import matplotlib.pyplot as plt
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import matplotlib.ticker as ticker
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if len(sys.argv) < 2:
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print("usage:")
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print("\tpython %s <fft_file.csv>" % sys.argv[0])
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sys.exit()
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fft_file = sys.argv[1]
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if not os.path.isfile(fft_file):
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print("error: %s not found" % fft_file)
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sys.exit()
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raw_data = np.genfromtxt( fft_file, delimiter=',', max_rows=1)
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data1 = raw_data[:] # max_rows=2: raw_data[0,:]
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print(data1)
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db = data1[5:]
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sr = -2.0*data1[1]
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freq_min = data1[1] / sr
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freq_max = data1[2] / sr
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fq = np.arange(freq_min, freq_max, 1.0/(data1[4]+1))
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N = len(db)
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m = np.mean(db)
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db5 = np.full(N, m)
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for n in range(2, N-2):
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db5[n] = (db[n-2]+db[n-1]+db[n]+db[n+1]+db[n+2])/5.0
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ax1 = plt.subplot(111)
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ax1.set_xlim(fq[0], fq[-1])
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ax1.plot( fq, db, color='b', linewidth=0.06, label='fft')
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ax1.plot( fq, db5, color='g', linewidth=0.4, label='fft')
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plt.show()
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