Marco Zecchini / Mbed OS Example_RTOS

Rtos API example

mbed-os/tools/dev/dsp_fir.py@0:9fca2b23d0ba, 2019-02-23 (annotated)

Committer:
marcozecchini
Date:
Sat Feb 23 12:13:36 2019 +0000
Revision:
0:9fca2b23d0ba
final commit

Who changed what in which revision?

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marcozecchini 0:9fca2b23d0ba 1 """
marcozecchini 0:9fca2b23d0ba 2 mbed SDK
marcozecchini 0:9fca2b23d0ba 3 Copyright (c) 2011-2013 ARM Limited
marcozecchini 0:9fca2b23d0ba 4
marcozecchini 0:9fca2b23d0ba 5 Licensed under the Apache License, Version 2.0 (the "License");
marcozecchini 0:9fca2b23d0ba 6 you may not use this file except in compliance with the License.
marcozecchini 0:9fca2b23d0ba 7 You may obtain a copy of the License at
marcozecchini 0:9fca2b23d0ba 8
marcozecchini 0:9fca2b23d0ba 9 http://www.apache.org/licenses/LICENSE-2.0
marcozecchini 0:9fca2b23d0ba 10
marcozecchini 0:9fca2b23d0ba 11 Unless required by applicable law or agreed to in writing, software
marcozecchini 0:9fca2b23d0ba 12 distributed under the License is distributed on an "AS IS" BASIS,
marcozecchini 0:9fca2b23d0ba 13 WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
marcozecchini 0:9fca2b23d0ba 14 See the License for the specific language governing permissions and
marcozecchini 0:9fca2b23d0ba 15 limitations under the License.
marcozecchini 0:9fca2b23d0ba 16 """
marcozecchini 0:9fca2b23d0ba 17 from numpy import sin, arange, pi
marcozecchini 0:9fca2b23d0ba 18 from scipy.signal import lfilter, firwin
marcozecchini 0:9fca2b23d0ba 19 from pylab import figure, plot, grid, show
marcozecchini 0:9fca2b23d0ba 20
marcozecchini 0:9fca2b23d0ba 21 #------------------------------------------------
marcozecchini 0:9fca2b23d0ba 22 # Create a signal for demonstration.
marcozecchini 0:9fca2b23d0ba 23 #------------------------------------------------
marcozecchini 0:9fca2b23d0ba 24 # 320 samples of (1000Hz + 15000 Hz) at 48 kHz
marcozecchini 0:9fca2b23d0ba 25 sample_rate = 48000.
marcozecchini 0:9fca2b23d0ba 26 nsamples = 320
marcozecchini 0:9fca2b23d0ba 27
marcozecchini 0:9fca2b23d0ba 28 F_1KHz = 1000.
marcozecchini 0:9fca2b23d0ba 29 A_1KHz = 1.0
marcozecchini 0:9fca2b23d0ba 30
marcozecchini 0:9fca2b23d0ba 31 F_15KHz = 15000.
marcozecchini 0:9fca2b23d0ba 32 A_15KHz = 0.5
marcozecchini 0:9fca2b23d0ba 33
marcozecchini 0:9fca2b23d0ba 34 t = arange(nsamples) / sample_rate
marcozecchini 0:9fca2b23d0ba 35 signal = A_1KHz * sin(2*pi*F_1KHz*t) + A_15KHz*sin(2*pi*F_15KHz*t)
marcozecchini 0:9fca2b23d0ba 36
marcozecchini 0:9fca2b23d0ba 37 #------------------------------------------------
marcozecchini 0:9fca2b23d0ba 38 # Create a FIR filter and apply it to signal.
marcozecchini 0:9fca2b23d0ba 39 #------------------------------------------------
marcozecchini 0:9fca2b23d0ba 40 # The Nyquist rate of the signal.
marcozecchini 0:9fca2b23d0ba 41 nyq_rate = sample_rate / 2.
marcozecchini 0:9fca2b23d0ba 42
marcozecchini 0:9fca2b23d0ba 43 # The cutoff frequency of the filter: 6KHz
marcozecchini 0:9fca2b23d0ba 44 cutoff_hz = 6000.0
marcozecchini 0:9fca2b23d0ba 45
marcozecchini 0:9fca2b23d0ba 46 # Length of the filter (number of coefficients, i.e. the filter order + 1)
marcozecchini 0:9fca2b23d0ba 47 numtaps = 29
marcozecchini 0:9fca2b23d0ba 48
marcozecchini 0:9fca2b23d0ba 49 # Use firwin to create a lowpass FIR filter
marcozecchini 0:9fca2b23d0ba 50 fir_coeff = firwin(numtaps, cutoff_hz/nyq_rate)
marcozecchini 0:9fca2b23d0ba 51
marcozecchini 0:9fca2b23d0ba 52 # Use lfilter to filter the signal with the FIR filter
marcozecchini 0:9fca2b23d0ba 53 filtered_signal = lfilter(fir_coeff, 1.0, signal)
marcozecchini 0:9fca2b23d0ba 54
marcozecchini 0:9fca2b23d0ba 55 #------------------------------------------------
marcozecchini 0:9fca2b23d0ba 56 # Plot the original and filtered signals.
marcozecchini 0:9fca2b23d0ba 57 #------------------------------------------------
marcozecchini 0:9fca2b23d0ba 58
marcozecchini 0:9fca2b23d0ba 59 # The first N-1 samples are "corrupted" by the initial conditions
marcozecchini 0:9fca2b23d0ba 60 warmup = numtaps - 1
marcozecchini 0:9fca2b23d0ba 61
marcozecchini 0:9fca2b23d0ba 62 # The phase delay of the filtered signal
marcozecchini 0:9fca2b23d0ba 63 delay = (warmup / 2) / sample_rate
marcozecchini 0:9fca2b23d0ba 64
marcozecchini 0:9fca2b23d0ba 65 figure(1)
marcozecchini 0:9fca2b23d0ba 66 # Plot the original signal
marcozecchini 0:9fca2b23d0ba 67 plot(t, signal)
marcozecchini 0:9fca2b23d0ba 68
marcozecchini 0:9fca2b23d0ba 69 # Plot the filtered signal, shifted to compensate for the phase delay
marcozecchini 0:9fca2b23d0ba 70 plot(t-delay, filtered_signal, 'r-')
marcozecchini 0:9fca2b23d0ba 71
marcozecchini 0:9fca2b23d0ba 72 # Plot just the "good" part of the filtered signal. The first N-1
marcozecchini 0:9fca2b23d0ba 73 # samples are "corrupted" by the initial conditions.
marcozecchini 0:9fca2b23d0ba 74 plot(t[warmup:]-delay, filtered_signal[warmup:], 'g', linewidth=4)
marcozecchini 0:9fca2b23d0ba 75
marcozecchini 0:9fca2b23d0ba 76 grid(True)
marcozecchini 0:9fca2b23d0ba 77
marcozecchini 0:9fca2b23d0ba 78 show()
marcozecchini 0:9fca2b23d0ba 79
marcozecchini 0:9fca2b23d0ba 80 #------------------------------------------------
marcozecchini 0:9fca2b23d0ba 81 # Print values
marcozecchini 0:9fca2b23d0ba 82 #------------------------------------------------
marcozecchini 0:9fca2b23d0ba 83 def print_values(label, values):
marcozecchini 0:9fca2b23d0ba 84 var = "float32_t %s[%d]" % (label, len(values))
marcozecchini 0:9fca2b23d0ba 85 print "%-30s = {%s}" % (var, ', '.join(["%+.10f" % x for x in values]))
marcozecchini 0:9fca2b23d0ba 86
marcozecchini 0:9fca2b23d0ba 87 print_values('signal', signal)
marcozecchini 0:9fca2b23d0ba 88 print_values('fir_coeff', fir_coeff)
marcozecchini 0:9fca2b23d0ba 89 print_values('filtered_signal', filtered_signal)