mirror of https://github.com/ARMmbed/mbed-os.git
74 lines
2.1 KiB
Python
74 lines
2.1 KiB
Python
from numpy import sin, arange, pi
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from scipy.signal import lfilter, firwin
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from pylab import figure, plot, grid, show
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#------------------------------------------------
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# Create a signal for demonstration.
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#------------------------------------------------
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# 320 samples of (1000Hz + 15000 Hz) at 48 kHz
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sample_rate = 48000.
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nsamples = 320
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F_1KHz = 1000.
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A_1KHz = 1.0
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F_15KHz = 15000.
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A_15KHz = 0.5
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t = arange(nsamples) / sample_rate
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signal = A_1KHz * sin(2*pi*F_1KHz*t) + A_15KHz*sin(2*pi*F_15KHz*t)
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#------------------------------------------------
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# Create a FIR filter and apply it to signal.
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#------------------------------------------------
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# The Nyquist rate of the signal.
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nyq_rate = sample_rate / 2.
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# The cutoff frequency of the filter: 6KHz
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cutoff_hz = 6000.0
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# Length of the filter (number of coefficients, i.e. the filter order + 1)
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numtaps = 29
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# Use firwin to create a lowpass FIR filter
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fir_coeff = firwin(numtaps, cutoff_hz/nyq_rate)
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# Use lfilter to filter the signal with the FIR filter
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filtered_signal = lfilter(fir_coeff, 1.0, signal)
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#------------------------------------------------
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# Plot the original and filtered signals.
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#------------------------------------------------
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# The first N-1 samples are "corrupted" by the initial conditions
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warmup = numtaps - 1
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# The phase delay of the filtered signal
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delay = (warmup / 2) / sample_rate
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figure(1)
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# Plot the original signal
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plot(t, signal)
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# Plot the filtered signal, shifted to compensate for the phase delay
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plot(t-delay, filtered_signal, 'r-')
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# Plot just the "good" part of the filtered signal. The first N-1
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# samples are "corrupted" by the initial conditions.
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plot(t[warmup:]-delay, filtered_signal[warmup:], 'g', linewidth=4)
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grid(True)
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show()
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#------------------------------------------------
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# Print values
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#------------------------------------------------
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def print_values(label, values):
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var = "float32_t %s[%d]" % (label, len(values))
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print "%-30s = {%s}" % (var, ', '.join(["%+.10f" % x for x in values]))
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print_values('signal', signal)
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print_values('fir_coeff', fir_coeff)
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print_values('filtered_signal', filtered_signal)
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