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/cmsis-dsp-latest/PythonWrapper/examples/
Dtestdsp.py3 from scipy import signal
78 filtered_x = signal.lfilter([3,2,1.], 1.0, [1,2,3,4,5,1,2,3,4,5])
230 signal = np.cos(2 * np.pi * np.arange(nb) / nb) variable
232 result=np.fft.fft(signal)
234 signalR = imToReal1D(signal)
242 signal = signal / 10.0 variable
243 result=np.fft.fft(signal)
246 signalR = imToReal1D(signal)
255 signal = signal / 10.0 variable
256 result=np.fft.fft(signal)
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Dtestrfft_all.py5 from scipy import signal
36 signal = np.cos(2 * np.pi * np.arange(nb) / nb)*np.cos(0.2*2 * np.pi * np.arange(nb) / nb) variable
38 ref=scipy.fft.rfft(signal)
87 result = dsp.arm_rfft_fast_f64(rfftf64,signal,0)
88 assert(len(signal) == RFFT_F_IN_LENGTH)
110 result = dsp.arm_rfft_fast_f32(rfftf32,signal,0)
111 assert(len(signal) == RFFT_F_IN_LENGTH)
133 signalQ31 = f.toQ31(signal)
167 signalQ15 = f.toQ15(signal)
Dexample.py3 from scipy import signal
44 sos = signal.zpk2sos(
49 res=signal.sosfilt(sos,sig)
Dexample_1_9.py10 from scipy import signal
34 downsamplingFilter = signal.firwin(numTaps,1.0 / decimationFactor)
116 upsamplingFilter = signal.firwin(numTaps,1.0 / upsamplingFactor)
Dcmsisdsp_tests.ipynb82 "## Creating the signal"
130 "signal = None"
138 "You can play with the slider to change the frequency of the signal.\n",
139 "Don't forget to reconvert the signal to a Q15 format if you want to test the Q15 FFT."
166 " global signal\n",
168 " signal = np.sin(2 * np.pi * np.arange(nb)*f / nb) + 0.1*np.random.randn(nb)\n",
169 " plt.plot(signal)\n",
238 "# Re-evaluate this each time you change the signal\n",
239 "signalR = imToReal1D(signal)\n",
261 "The signal must be converted to Q15 each time it is changed with the slider above."
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Ddebug.py7 from scipy import signal
Dtestmfcc.py5 import scipy.signal as sig
Dtestmfccq15.py5 import scipy.signal as sig
Dtestmfccq31.py5 import scipy.signal as sig
Dtestdsp4.py3 from scipy import signal
Dexample_1_10.py10 from scipy import signal
11 import scipy.signal.windows as win
Dtestdsp5.py7 from scipy import signal
456 filtered_x = signal.lfilter([3,2,1.], 1.0, [1,2,3,4,5,1,2,3,4,5])
Dtestdsp2.py3 from scipy import signal
DNoise suppression.ipynb57 "from scipy.signal.windows import hann\n",
288 "The signal will be rebuilt at the end with an overlap and add.\n",
382 …signal and the VAD detection. It can be used to tune the threshold for the audio signal used in th…
478 …"Plot of the signal and VAD which can be used to tune the threshdold. The threshold is different b…
617 …"Each window of samples extracted from the signal is multiplied by a Hann window in below algorith…
790 " # In a better version this could be computed from the signal length by taking the\n",
791 " # smaller power of two greater than the signal length.\n",
794 " # Compute the vad signal\n",
811 " # We pad the signal with zero. It assumes that the padding can be divided by 2.\n",
832 " # Compute the padded signal\n",
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/cmsis-dsp-latest/Testing/PatternGeneration/
DBIQUAD.py5 from scipy import signal
65 sos = signal.zpk2sos(zeros,poles,g)
93 sos = signal.zpk2sos(
100 res=signal.sosfilt(sos,sig)
149 output=signal.sosfilt(sos,samples)
150 outputB=signal.sosfilt(sos,samplesB)
DFIR.py5 from scipy import signal
82 out=signal.lfilter(pythonCoefs,[1.0],x[0:2*b])
DDecimate.py5 from scipy.signal import firwin
6 import scipy.signal
8 from scipy.signal import upfirdn
DWindow.py5 import scipy.signal.windows as win
DMFCC.py33 import scipy.signal as sig
/cmsis-dsp-latest/PythonWrapper/docs/source/
Dapi.rst16 If you use scipy signal processing functions::
18 from scipy import signal
130 …signal should be blockSize. blockSize was inferred from the size of the state array : numTaps + bl…
138 filtered_x = signal.lfilter([3,2,1.], 1.0, [1,2,3,4,5,6,7,8,9,10])
146 …the C API, we are not using complex numbers in the wrapper. So a complex signal must be converted …
170 You convert the complex signal to the format expected by the wrapper::
172 signalR = imToReal1D(signal)
174 You compute the FFT of the signal with::
/cmsis-dsp-latest/dsppp/tests/
Dfilter_test.cpp482 PVector<T,BLOCK> filter(const PVector<T,BLOCK> &signal) in filter()
496 state_.sub(TAPS-1+i,TAPS-1+i+UNROLL_FACTOR) = copy(signal.sub(i,i+UNROLL_FACTOR)); in filter()
520 state_[TAPS-1+i] = signal[i]; in filter()
529 void purec(const T *signal, T *dst) in purec()
540 state[TAPS-1+i] = signal[i]; in purec()
564 PVector<T,NB> signal; in test() local
569 init_array(signal,NB); in test()
576 PVector<T,BLOCK> res = fir.filter(signal); in test()
600 reinterpret_cast<const q15_t*>(signal.const_ptr()), in test()
/cmsis-dsp-latest/
DPythonWrapper_README.md9 The signal processing chain can thus be tested and developed in a Python environment and then easil…
97 If you use scipy signal processing functions:
99 > from scipy import signal
139 …signal should be `blockSize`. `blockSize` was inferred from the size of the state array : `numTaps…
147 > filtered_x = signal.lfilter([3,2,1.], 1.0, [1,2,3,4,5,6,7,8,9,10])
156 Let's define a signal you will use for the FFT.
159 > signal = np.cos(2 * np.pi * np.arange(nb) / nb)
163 …the C API, we are not using complex numbers in the wrapper. So a complex signal must be converted …
165 > signalR = imToReal1D(signal)
176 You compute the FFT of the signal with:
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/cmsis-dsp-latest/Scripts/
Dmfccdata.py32 import scipy.signal as sig
/cmsis-dsp-latest/PythonWrapper/examples/kws_example/
Dkws.ipynb64 "import scipy.signal\n",
66 "from scipy.signal.windows import hann\n",
197 " signal = np.hstack([waveform, zero_padding])\n",
200 " # We decompose the intput signal into overlapping window. And the signal in each window\n",
210 " reta=[zcr(x*window) for x in sliding_window_view(signal,winLength)[::audioOffset,:]]\n",
212 …" # The final signal is filtered. We have tested several variations on the feature. This filter…
214 " reta=scipy.signal.lfilter(np.ones(10)/10.0,[1],reta)\n",
229 …"Note that when you use the signal property, the speech patterns will return the content of the fi…
269 " def signal(self):\n",
400 "## Testing on a signal\n",
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