mirror of https://github.com/ARMmbed/mbed-os.git
90 lines
2.7 KiB
Python
90 lines
2.7 KiB
Python
"""
|
|
mbed SDK
|
|
Copyright (c) 2011-2013 ARM Limited
|
|
|
|
Licensed under the Apache License, Version 2.0 (the "License");
|
|
you may not use this file except in compliance with the License.
|
|
You may obtain a copy of the License at
|
|
|
|
http://www.apache.org/licenses/LICENSE-2.0
|
|
|
|
Unless required by applicable law or agreed to in writing, software
|
|
distributed under the License is distributed on an "AS IS" BASIS,
|
|
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
See the License for the specific language governing permissions and
|
|
limitations under the License.
|
|
"""
|
|
from numpy import sin, arange, pi
|
|
from scipy.signal import lfilter, firwin
|
|
from pylab import figure, plot, grid, show
|
|
|
|
#------------------------------------------------
|
|
# Create a signal for demonstration.
|
|
#------------------------------------------------
|
|
# 320 samples of (1000Hz + 15000 Hz) at 48 kHz
|
|
sample_rate = 48000.
|
|
nsamples = 320
|
|
|
|
F_1KHz = 1000.
|
|
A_1KHz = 1.0
|
|
|
|
F_15KHz = 15000.
|
|
A_15KHz = 0.5
|
|
|
|
t = arange(nsamples) / sample_rate
|
|
signal = A_1KHz * sin(2*pi*F_1KHz*t) + A_15KHz*sin(2*pi*F_15KHz*t)
|
|
|
|
#------------------------------------------------
|
|
# Create a FIR filter and apply it to signal.
|
|
#------------------------------------------------
|
|
# The Nyquist rate of the signal.
|
|
nyq_rate = sample_rate / 2.
|
|
|
|
# The cutoff frequency of the filter: 6KHz
|
|
cutoff_hz = 6000.0
|
|
|
|
# Length of the filter (number of coefficients, i.e. the filter order + 1)
|
|
numtaps = 29
|
|
|
|
# Use firwin to create a lowpass FIR filter
|
|
fir_coeff = firwin(numtaps, cutoff_hz/nyq_rate)
|
|
|
|
# Use lfilter to filter the signal with the FIR filter
|
|
filtered_signal = lfilter(fir_coeff, 1.0, signal)
|
|
|
|
#------------------------------------------------
|
|
# Plot the original and filtered signals.
|
|
#------------------------------------------------
|
|
|
|
# The first N-1 samples are "corrupted" by the initial conditions
|
|
warmup = numtaps - 1
|
|
|
|
# The phase delay of the filtered signal
|
|
delay = (warmup / 2) / sample_rate
|
|
|
|
figure(1)
|
|
# Plot the original signal
|
|
plot(t, signal)
|
|
|
|
# Plot the filtered signal, shifted to compensate for the phase delay
|
|
plot(t-delay, filtered_signal, 'r-')
|
|
|
|
# Plot just the "good" part of the filtered signal. The first N-1
|
|
# samples are "corrupted" by the initial conditions.
|
|
plot(t[warmup:]-delay, filtered_signal[warmup:], 'g', linewidth=4)
|
|
|
|
grid(True)
|
|
|
|
show()
|
|
|
|
#------------------------------------------------
|
|
# Print values
|
|
#------------------------------------------------
|
|
def print_values(label, values):
|
|
var = "float32_t %s[%d]" % (label, len(values))
|
|
print "%-30s = {%s}" % (var, ', '.join(["%+.10f" % x for x in values]))
|
|
|
|
print_values('signal', signal)
|
|
print_values('fir_coeff', fir_coeff)
|
|
print_values('filtered_signal', filtered_signal)
|