├── .github ├── FUNDING.yml ├── images │ ├── 12.png │ ├── 24.png │ ├── one.png │ ├── one16.png │ ├── response.png │ ├── response1.png │ ├── test │ ├── third.png │ ├── third16.png │ ├── twothird.png │ └── twothird16.png └── workflows │ └── mirror.yml ├── .gitignore ├── LICENSE ├── PyOctaveBand.py ├── README.md ├── requirements.txt └── test.py /.github/FUNDING.yml: -------------------------------------------------------------------------------- 1 | # These are supported funding model platforms 2 | 3 | github: jmrplens # Replace with up to 4 GitHub Sponsors-enabled usernames e.g., [user1, user2] 4 | patreon: # Replace with a single Patreon username 5 | open_collective: # Replace with a single Open Collective username 6 | ko_fi: jmrplens # Replace with a single Ko-fi username 7 | tidelift: # Replace with a single Tidelift platform-name/package-name e.g., npm/babel 8 | community_bridge: # Replace with a single Community Bridge project-name e.g., cloud-foundry 9 | liberapay: # Replace with a single Liberapay username 10 | issuehunt: # Replace with a single IssueHunt username 11 | otechie: # Replace with a single Otechie username 12 | custom: 'https://www.paypal.com/donate?hosted_button_id=BLP3R6VGYJB4Q' # Replace with up to 4 custom sponsorship URLs e.g., ['link1', 'link2'] 13 | -------------------------------------------------------------------------------- /.github/images/12.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jmrplens/PyOctaveBand/b5c5b2182afd44860817566f88fba7030d84fb4d/.github/images/12.png -------------------------------------------------------------------------------- /.github/images/24.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jmrplens/PyOctaveBand/b5c5b2182afd44860817566f88fba7030d84fb4d/.github/images/24.png -------------------------------------------------------------------------------- /.github/images/one.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jmrplens/PyOctaveBand/b5c5b2182afd44860817566f88fba7030d84fb4d/.github/images/one.png -------------------------------------------------------------------------------- /.github/images/one16.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jmrplens/PyOctaveBand/b5c5b2182afd44860817566f88fba7030d84fb4d/.github/images/one16.png -------------------------------------------------------------------------------- /.github/images/response.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jmrplens/PyOctaveBand/b5c5b2182afd44860817566f88fba7030d84fb4d/.github/images/response.png -------------------------------------------------------------------------------- /.github/images/response1.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jmrplens/PyOctaveBand/b5c5b2182afd44860817566f88fba7030d84fb4d/.github/images/response1.png -------------------------------------------------------------------------------- /.github/images/test: -------------------------------------------------------------------------------- 1 | test 2 | -------------------------------------------------------------------------------- /.github/images/third.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jmrplens/PyOctaveBand/b5c5b2182afd44860817566f88fba7030d84fb4d/.github/images/third.png -------------------------------------------------------------------------------- /.github/images/third16.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jmrplens/PyOctaveBand/b5c5b2182afd44860817566f88fba7030d84fb4d/.github/images/third16.png -------------------------------------------------------------------------------- /.github/images/twothird.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jmrplens/PyOctaveBand/b5c5b2182afd44860817566f88fba7030d84fb4d/.github/images/twothird.png -------------------------------------------------------------------------------- /.github/images/twothird16.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/jmrplens/PyOctaveBand/b5c5b2182afd44860817566f88fba7030d84fb4d/.github/images/twothird16.png -------------------------------------------------------------------------------- /.github/workflows/mirror.yml: -------------------------------------------------------------------------------- 1 | name: Mirror to gitlab 2 | 3 | on: 4 | push: 5 | branches: [ main, master ] 6 | workflow_dispatch: 7 | 8 | jobs: 9 | build: 10 | runs-on: ubuntu-latest 11 | 12 | steps: # <-- must use actions/checkout before mirroring! 13 | - uses: actions/checkout@v3 14 | with: 15 | fetch-depth: 0 16 | - uses: pixta-dev/repository-mirroring-action@v1 17 | with: 18 | target_repo_url: 19 | ssh://git@git.jmrp.io:${{ secrets.PORT }}/${{ github.repository }}.git 20 | ssh_private_key: # <-- use 'secrets' to pass credential information. 21 | ${{ secrets.GITLAB_SSH_PRIVATE_KEY }} 22 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Created by .ignore support plugin (hsz.mobi) 2 | ### Python template 3 | # Byte-compiled / optimized / DLL files 4 | __pycache__/ 5 | *.py[cod] 6 | *$py.class 7 | 8 | # C extensions 9 | *.so 10 | 11 | # Distribution / packaging 12 | .Python 13 | build/ 14 | develop-eggs/ 15 | dist/ 16 | downloads/ 17 | eggs/ 18 | .eggs/ 19 | lib/ 20 | lib64/ 21 | parts/ 22 | sdist/ 23 | var/ 24 | wheels/ 25 | pip-wheel-metadata/ 26 | share/python-wheels/ 27 | *.egg-info/ 28 | .installed.cfg 29 | *.egg 30 | MANIFEST 31 | 32 | # 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Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /PyOctaveBand.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) 2020. Jose M. Requena-Plens 2 | """ 3 | Octave-Band and Fractional Octave-Band filter. 4 | """ 5 | 6 | import numpy as np 7 | from scipy import signal 8 | import matplotlib.pyplot as plt 9 | 10 | # Public methods 11 | __all__ = ['octavefilter', 'getansifrequencies', 'normalizedfreq'] 12 | 13 | 14 | def octavefilter(x, fs, fraction=1, order=6, limits=None, show=0, sigbands =0): 15 | """ 16 | Filter a signal with octave or fractional octave filter bank. This 17 | method uses a Butterworth filter with Second-Order Sections 18 | coefficients. To obtain the correct coefficients, a subsampling is 19 | applied to the signal in each filtered band. 20 | 21 | :param x: Signal 22 | :param fs: Sample rate 23 | :param fraction: Bandwidth 'b'. Examples: 1/3-octave b=3, 1-octave b=1, 24 | 2/3-octave b = 3/2. [Optional] Default: 1. 25 | :param order: Order of Butterworth filter. [Optional] Default: 6. 26 | :param limits: Minimum and maximum limit frequencies. [Optional] Default 27 | [12,20000] 28 | :param show: Boolean for plot o not the filter response. 29 | :param sigbands: Boolean to also return the signal in the time domain 30 | divided into bands. A list with as many arrays as there are frequency bands. 31 | :returns: Sound Pressure Level and Frequency array 32 | """ 33 | 34 | if limits is None: 35 | limits = [12, 20000] 36 | 37 | # List type for signal var 38 | x = _typesignal(x) 39 | 40 | # Generate frequency array 41 | freq, freq_d, freq_u = _genfreqs(limits, fraction, fs) 42 | 43 | # Calculate the downsampling factor (array of integers with size [freq]) 44 | factor = _downsamplingfactor(freq_u, fs) 45 | 46 | # Get SOS filter coefficients (3D - matrix with size: [freq,order,6]) 47 | sos = _buttersosfilter(freq, freq_d, freq_u, fs, order, factor, show) 48 | 49 | if sigbands: 50 | # Create array with SPL for each frequency band 51 | spl = np.zeros([len(freq)]) 52 | xb = [] 53 | for idx in range(len(freq)): 54 | sd = signal.resample(x, round(len(x) / factor[idx])) 55 | y = signal.sosfilt(sos[idx], sd) 56 | spl[idx] = 20 * np.log10(np.std(y) / 2e-5) 57 | xb.append(signal.resample_poly(y,factor[idx],1)) 58 | return spl.tolist(), freq, xb 59 | else: 60 | # Create array with SPL for each frequency band 61 | spl = np.zeros([len(freq)]) 62 | for idx in range(len(freq)): 63 | sd = signal.resample(x, round(len(x) / factor[idx])) 64 | y = signal.sosfilt(sos[idx], sd) 65 | spl[idx] = 20 * np.log10(np.std(y) / 2e-5) 66 | return spl.tolist(), freq 67 | 68 | 69 | def _typesignal(x): 70 | if type(x) is list: 71 | return x 72 | elif type(x) is np.ndarray: 73 | return x.tolist() 74 | elif type(x) is tuple: 75 | return list(x) 76 | 77 | 78 | def _buttersosfilter(freq, freq_d, freq_u, fs, order, factor, show=0): 79 | # Initialize coefficients matrix 80 | sos = [[[]] for i in range(len(freq))] 81 | # Generate coefficients for each frequency band 82 | for idx, (lower, upper) in enumerate(zip(freq_d, freq_u)): 83 | # Downsampling to improve filter coefficients 84 | fsd = fs / factor[idx] # New sampling rate 85 | # Butterworth Filter with SOS coefficients 86 | sos[idx] = signal.butter( 87 | N=order, 88 | Wn=np.array([lower, upper]) / (fsd / 2), 89 | btype='bandpass', 90 | analog=False, 91 | output='sos') 92 | 93 | if show: 94 | _showfilter(sos, freq, freq_u, freq_d, fs, factor) 95 | 96 | return sos 97 | 98 | 99 | def _showfilter(sos, freq, freq_u, freq_d, fs, factor): 100 | wn = 8192 101 | w = np.zeros([wn, len(freq)]) 102 | h = np.zeros([wn, len(freq)], dtype=np.complex_) 103 | 104 | for idx in range(len(freq)): 105 | fsd = fs / factor[idx] # New sampling rate 106 | w[:, idx], h[:, idx] = signal.sosfreqz( 107 | sos[idx], 108 | worN=wn, 109 | whole=False, 110 | fs=fsd) 111 | 112 | fig, ax = plt.subplots() 113 | ax.semilogx(w, 20 * np.log10(abs(h) + np.finfo(float).eps), 'b') 114 | ax.grid(which='major') 115 | ax.grid(which='minor', linestyle=':') 116 | ax.set_xlabel(r'Frequency [Hz]') 117 | ax.set_ylabel('Amplitude [dB]') 118 | ax.set_title('Second-Order Sections - Butterworth Filter') 119 | plt.xlim(freq_d[0] * 0.8, freq_u[-1] * 1.2) 120 | plt.ylim(-4, 1) 121 | ax.set_xticks([16, 31.5, 63, 125, 250, 500, 1000, 2000, 4000, 8000, 16000]) 122 | ax.set_xticklabels(['16', '31.5', '63', '125', '250', '500', 123 | '1k', '2k', '4k', '8k', '16k']) 124 | plt.show() 125 | 126 | 127 | def _genfreqs(limits, fraction, fs): 128 | # Generate frequencies 129 | freq, freq_d, freq_u = getansifrequencies(fraction, limits) 130 | 131 | # Remove outer frequency to prevent filter error (fs/2 < freq) 132 | freq, freq_d, freq_u = _deleteouters(freq, freq_d, freq_u, fs) 133 | 134 | return freq, freq_d, freq_u 135 | 136 | 137 | def normalizedfreq(fraction): 138 | """ 139 | Normalized frequencies for one-octave and third-octave band. [IEC 140 | 61260-1-2014] 141 | 142 | :param fraction: Octave type, for one octave fraction=1, 143 | for third-octave fraction=3 144 | :type fraction: int 145 | :returns: frequencies array 146 | :rtype: list 147 | """ 148 | predefined = {1: _oneoctave(), 149 | 3: _thirdoctave(), 150 | } 151 | return predefined[fraction] 152 | 153 | 154 | def _thirdoctave(): 155 | # IEC 61260 - 1 - 2014 (added 12.5, 16, 20 Hz) 156 | return [12.5, 16, 20, 25, 31.5, 40, 50, 63, 80, 100, 125, 160, 200, 250, 157 | 315, 400, 500, 630, 800, 1000, 1250, 1600, 2000, 2500, 3150, 4000, 158 | 5000, 6300, 8000, 10000, 12500, 16000, 20000] 159 | 160 | 161 | def _oneoctave(): 162 | # IEC 61260 - 1 - 2014 (added 16 Hz) 163 | return [16, 31.5, 63, 125, 250, 500, 1000, 2000, 4000, 8000, 16000] 164 | 165 | 166 | def _deleteouters(freq, freq_d, freq_u, fs): 167 | idx = np.asarray(np.where(np.array(freq_u) > fs / 2)) 168 | if any(idx[0]): 169 | _printwarn('Low sampling rate, frequencies above fs/2 will be removed') 170 | freq = np.delete(freq, idx).tolist() 171 | freq_d = np.delete(freq_d, idx).tolist() 172 | freq_u = np.delete(freq_u, idx).tolist() 173 | return freq, freq_d, freq_u 174 | 175 | 176 | def getansifrequencies(fraction, limits=None): 177 | """ ANSI s1.11-2004 && IEC 61260-1-2014 178 | Array of frequencies and its edges according to the ANSI and IEC standard. 179 | 180 | :param fraction: Bandwidth 'b'. Examples: 1/3-octave b=3, 1-octave b=1, 181 | 2/3-octave b = 3/2 182 | :param limits: It is a list with the minimum and maximum frequency that 183 | the array should have. Example: [12,20000] 184 | :returns: Frequency array, lower edge array and upper edge array 185 | :rtype: list, list, list 186 | """ 187 | 188 | if limits is None: 189 | limits = [12, 20000] 190 | 191 | # Octave ratio g (ANSI s1.11, 3.2, pg. 2) 192 | g = 10 ** (3 / 10) # Or g = 2 193 | # Reference frequency (ANSI s1.11, 3.4, pg. 2) 194 | fr = 1000 195 | 196 | # Get starting index 'x' and first center frequency 197 | x = _initindex(limits[0], fr, g, fraction) 198 | freq = _ratio(g, x, fraction) * fr 199 | 200 | # Get each frequency until reach maximum frequency 201 | freq_x = 0 202 | while freq_x * _bandedge(g, fraction) < limits[1]: 203 | # Increase index 204 | x = x + 1 205 | # New frequency 206 | freq_x = _ratio(g, x, fraction) * fr 207 | # Store new frequency 208 | freq = np.append(freq, freq_x) 209 | 210 | # Get band-edges 211 | freq_d = freq / _bandedge(g, fraction) 212 | freq_u = freq * _bandedge(g, fraction) 213 | 214 | return freq.tolist(), freq_d.tolist(), freq_u.tolist() 215 | 216 | 217 | def _initindex(f, fr, g, b): 218 | if b % 2: # ODD ('x' solve from ANSI s1.11, eq. 3) 219 | return np.round( 220 | (b * np.log(f / fr) + 30 * np.log(g)) / np.log(g) 221 | ) 222 | else: # EVEN ('x' solve from ANSI s1.11, eq. 4) 223 | return np.round( 224 | (2 * b * np.log(f / fr) + 59 * np.log(g)) / (2 * np.log(g)) 225 | ) 226 | 227 | 228 | def _ratio(g, x, b): 229 | if b % 2: # ODD (ANSI s1.11, eq. 3) 230 | return g ** ((x - 30) / b) 231 | else: # EVEN (ANSI s1.11, eq. 4) 232 | return g ** ((2 * x - 59) / (2 * b)) 233 | 234 | 235 | def _bandedge(g, b): 236 | # Band-edge ratio (ANSI s1.11, 3.7, pg. 3) 237 | return g ** (1 / (2 * b)) 238 | 239 | 240 | def _printwarn(msg): 241 | print('*********\n' + msg + '\n*********') 242 | 243 | 244 | def _downsamplingfactor(freq, fs): 245 | guard = 0.10 246 | factor = (np.floor((fs / (2+guard)) / np.array(freq))).astype('int') 247 | for idx in range(len(factor)): 248 | # Factor between 1 | | 72 | | 1/3-octave | | | 73 | | 2/3-octave | | | 74 | 75 | ### Usage example 76 | 77 | This example is included in the file test.py. 78 | 79 | ```python 80 | import PyOctaveBand 81 | import numpy as np 82 | import scipy.io.wavfile 83 | 84 | # Sample rate and duration 85 | fs = 48000 86 | duration = 5 # In seconds 87 | 88 | # Time array 89 | x = np.arange(np.round(fs * duration)) / fs 90 | 91 | # Signal with 6 frequencies 92 | f1, f2, f3, f4, f5, f6 = 20, 100, 500, 2000, 4000, 15000 93 | # Multi Sine wave signal 94 | y = 100 \ 95 | * (np.sin(2 * np.pi * f1 * x) 96 | + np.sin(2 * np.pi * f2 * x) 97 | + np.sin(2 * np.pi * f3 * x) 98 | + np.sin(2 * np.pi * f4 * x) 99 | + np.sin(2 * np.pi * f5 * x) 100 | + np.sin(2 * np.pi * f6 * x)) 101 | 102 | # Filter (only octave spectra) 103 | spl, freq = PyOctaveBand.octavefilter(y, fs=fs, fraction=3, order=6, limits=[12, 20000], show=1) 104 | 105 | # Filter (get spectra and signal in bands) 106 | splb, freqb, xb = PyOctaveBand.octavefilter(y, fs=fs, fraction=3, order=6, limits=[12, 20000], show=0, sigbands=1) 107 | 108 | # Store signal in bands in separated wav files 109 | for idx in range(len(freq)): 110 | scipy.io.wavfile.write( 111 | "test_"+str(round(freq[idx]))+"_Hz.wav", 112 | fs, 113 | xb[idx]/np.max(xb[idx])) 114 | ``` 115 | 116 | The result is as follows: 117 | 118 | | One Octave filter | One-Third Octave filter | 119 | |:-------------:|:-------------:| 120 | | | | 121 | 122 | | 1/12 Octave filter | 1/24 Octave filter | 123 | |:-------------:|:-------------:| 124 | | | | 125 | 126 | # Roadmap 127 | 128 | - Add multichannel support 129 | 130 | If you have any suggestions or you found an error please, make a [Pull Request](https://github.com/jmrplens/PyOctave/pulls) or [contact me](mailto:info@jmrplens.com). 131 | 132 | # Author 133 | Jose M. Requena Plens, 2020. 134 | 135 | [![Donate](https://img.shields.io/badge/Donate-PayPal-green.svg)](https://www.paypal.com/donate?hosted_button_id=BLP3R6VGYJB4Q) 136 | [![Donate](https://img.shields.io/badge/Donate-Ko--fi-brightgreen?color=ff5f5f)](https://ko-fi.com/jmrplens) 137 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | numpy==1.23.4 2 | matplotlib==3.6.2 3 | scipy==1.9.3 -------------------------------------------------------------------------------- /test.py: -------------------------------------------------------------------------------- 1 | # Copyright (c) 2020. Jose M. Requena-Plens 2 | 3 | """ 4 | Demo test for PyOctaveBand.py 5 | """ 6 | 7 | import PyOctaveBand 8 | import numpy as np 9 | import matplotlib.pyplot as plt 10 | import scipy.io.wavfile 11 | 12 | # Sample rate and duration 13 | fs = 48000 14 | duration = 5 # In seconds 15 | 16 | # Time array 17 | x = np.arange(np.round(fs * duration)) / fs 18 | 19 | # Signal with 6 frequencies 20 | f1, f2, f3, f4, f5, f6 = 20, 100, 500, 2000, 4000, 15000 21 | # Multi Sine wave signal 22 | y = 100 \ 23 | * (np.sin(2 * np.pi * f1 * x) 24 | + np.sin(2 * np.pi * f2 * x) 25 | + np.sin(2 * np.pi * f3 * x) 26 | + np.sin(2 * np.pi * f4 * x) 27 | + np.sin(2 * np.pi * f5 * x) 28 | + np.sin(2 * np.pi * f6 * x)) 29 | 30 | # Filter (only octave spectra) 31 | spl, freq = PyOctaveBand.octavefilter(y, fs=fs, fraction=3, order=6, limits=[12, 20000], show=1) 32 | 33 | # Filter (get spectra and signal in bands) 34 | splb, freqb, xb = PyOctaveBand.octavefilter(y, fs=fs, fraction=3, order=6, limits=[12, 20000], show=0, sigbands=1) 35 | 36 | # Store signal in bands in separated wav files 37 | for idx in range(len(freq)): 38 | scipy.io.wavfile.write( 39 | "test_"+str(round(freq[idx]))+"_Hz.wav", 40 | fs, 41 | xb[idx]/np.max(xb[idx])) 42 | 43 | 44 | # Show octave spectrum 45 | fig, ax = plt.subplots() 46 | ax.semilogx(freq, spl, 'b') 47 | ax.grid(which='major') 48 | ax.grid(which='minor', linestyle=':') 49 | ax.set_xlabel(r'Frequency [Hz]') 50 | ax.set_ylabel('Level [dB]') 51 | plt.xlim(11, 25000) 52 | ax.set_xticks([16, 31.5, 63, 125, 250, 500, 1000, 2000, 4000, 8000, 16000]) 53 | ax.set_xticklabels(['16', '31.5', '63', '125', '250', '500', '1k', '2k', '4k', '8k', '16k']) 54 | plt.show() 55 | 56 | --------------------------------------------------------------------------------