plateform stringclasses 1
value | repo_name stringlengths 13 113 | name stringlengths 3 74 | ext stringclasses 1
value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
|---|---|---|---|---|---|---|---|---|
github | eunnieverse/AcousticEigen-master | Density2_air.m | .m | AcousticEigen-master/sample/matlab_Anshuman/final_working_2D_version_of_3D_air_Anshuman/Density2_air.m | 17,697 | utf_8 | 61412bbd21ccdf9938323722845735f8 | % Compute Nonlocal density - Array of Helmholtz resonators
% Using Zwikker-Konten model for slits
% Taking into account Zwikker-Konten waves in the cavity-- Horozontally
function [rho, chi]=Density2_air(omega,k)
%constantes
cstphys3_air;
%cstphys3
st=sqrt( omega.*rho0.*((ht./2).^2)./eta ); % define... |
github | eunnieverse/AcousticEigen-master | Wavenumber2.m | .m | AcousticEigen-master/sample/matlab_Anshuman/final_working_2D_air_2015/Wavenumber2.m | 3,031 | utf_8 | a45f62681ba8a353c9300d747eb6a8f2 | % Find the macroscopic wave number - Helmholtz resonator
% Using Zwikker-Konten model for slits
% Taking into account Zwikker-Konten waves in the cavity-- Vertically
function [q]=Wavenumber2(omega, nbptklpi)
%constantes
cstphys3
st=sqrt( omega.*rho0.*((ht./2).^2)./eta ); % define parameter
sn=sqrt... |
github | eunnieverse/AcousticEigen-master | Density2.m | .m | AcousticEigen-master/sample/matlab_Anshuman/final_working_2D_air_2015/Density2.m | 17,162 | utf_8 | 4f5773329baa1d3ac8ceb5c47cc49561 | % Compute Nonlocal density - Array of Helmholtz resonators
% Using Zwikker-Konten model for slits
% Taking into account Zwikker-Konten waves in the cavity-- Horozontally
function [rho, chi]=Density2(omega,k)
%constantes
cstphys3;
st=sqrt( omega.*rho0.*((ht./2).^2)./eta ); % define parameter
sn=sqr... |
github | eunnieverse/AcousticEigen-master | Wavenumber2.m | .m | AcousticEigen-master/sample/matlab_Anshuman/final_working_3D_air_code_2015/Wavenumber2.m | 2,752 | utf_8 | e4f06cdcf4c94973c66d418f4acb6ea9 | % Find the macroscopic wave number - Helmholtz resonator
% Using Zwikker-Konten model for slits
% Taking into account Zwikker-Konten waves in the cavity-- Vertically
function [q]=Wavenumber2(omega, nbptklpi)
%constantes
%cstphys3_water
q=0*omega;
cstphys3
rhot = rho0./Fr(nu,omega, dt/2, ht/2); % effective d... |
github | eunnieverse/AcousticEigen-master | Density2.m | .m | AcousticEigen-master/sample/matlab_Anshuman/final_working_3D_air_code_2015/Density2.m | 20,163 | utf_8 | abc26ea1b97038e35f96ca2f0cee3ae4 | % Compute Nonlocal density - Array of Helmholtz resonators
% Using Zwikker-Konten model for slits
% Taking into account Zwikker-Konten waves in the cavity-- Horozontally
function [rho, chi]=Density2(omega,k)
f0=10i;%-1i*k;
%constantes
%cstphys3_water;
cstphys3
rhot = rho0./Fr(nu,omega, dt/2, ht/2); % effe... |
github | eunnieverse/AcousticEigen-master | Wavenumber2_water.m | .m | AcousticEigen-master/sample/matlab_Anshuman/final_working_2D_water_2015/Wavenumber2_water.m | 3,080 | utf_8 | 8006e901ef94ce89b6693e5848c94b58 | % Find the macroscopic wave number - Helmholtz resonator
% Using Zwikker-Konten model for slits
% Taking into account Zwikker-Konten waves in the cavity-- Vertically
function [q]=Wavenumber2_water(omega, nbptklpi)
%constantes
cstphys3_water
%cstphys3
st=sqrt( omega.*rho0.*((ht./2).^2)./eta ); % de... |
github | eunnieverse/AcousticEigen-master | Density2_water.m | .m | AcousticEigen-master/sample/matlab_Anshuman/final_working_2D_water_2015/Density2_water.m | 17,234 | utf_8 | 4551ecf7b7176162d7ba63032809ec40 | % Compute Nonlocal density - Array of Helmholtz resonators
% Using Zwikker-Konten model for slits
% Taking into account Zwikker-Konten waves in the cavity-- Horozontally
function [rho, chi]=Density2_water(omega,k)
%constantes
cstphys3_water;
%cstphys3
st=sqrt( omega.*rho0.*((ht./2).^2)./eta ); % de... |
github | eunnieverse/AcousticEigen-master | Wavenumber2.m | .m | AcousticEigen-master/sample/matlab_Anshuman/3D_water_nonlocal_not_working_Anshuman/Wavenumber2.m | 2,793 | utf_8 | 5482666581718e5261b8db52b6e4d7c4 | % Find the macroscopic wave number - Helmholtz resonator
% Using Zwikker-Konten model for slits
% Taking into account Zwikker-Konten waves in the cavity-- Vertically
function [q]=Wavenumber2(omega, nbptklpi)
%constantes
%cstphys3_water
q=0*omega;
cstphys3
rhot = rho0./Fr(nu,omega, dt/2, ht/2); % effective d... |
github | eunnieverse/AcousticEigen-master | Density2.m | .m | AcousticEigen-master/sample/matlab_Anshuman/3D_water_nonlocal_not_working_Anshuman/Density2.m | 10,596 | utf_8 | 19976075ae813cfb9354acb289a2b189 | % Compute Nonlocal density - Array of Helmholtz resonators
% Using Zwikker-Konten model for slits
% Taking into account Zwikker-Konten waves in the cavity-- Horozontally
function [rho, chi]=Density2(omega,k)
f0=10i;%-1i*k;
%constantes
%cstphys3_water;
cstphys3
rhot = rho0./Fr(nu,omega, dt/2, ht/2); % effe... |
github | metocean/diwasp-master | infospec.m | .m | diwasp-master/infospec.m | 1,538 | utf_8 | 2aef3288510753f421fd6c23444477d9 | function [H,Tp,DTp,Dp]=infospec(SM,fsplit)
%DIWASP V1.4 function
%infospec: calculates and displays information about a directional spectrum
%
%[Hsig,Tp,DTp,Dp]=infospec(SM)
%
%Outputs:
%Hsig Signficant wave height
%Tp Peak period
%DTp Direction of spectral peak
%Dp Dominant direction
%
%Inputs:
%S... |
github | alexanderlerch/ACA-Code-master | ToolBlockAudio.m | .m | ACA-Code-master/ToolBlockAudio.m | 883 | utf_8 | f3e1398d8a7ffb1a28f567f2209561d8 | %blocks audio signal into overlapping blocks
%>
%> @param x: audio signal (dimension length x 1)
%> @param iBlockLength: target block size
%> @param iHopLength: target hopsize
%> @param f_s: sample rate
%>
%> @retval x_b (dimension iNumOfBlocks x iBlockLength)
%> @retval t time stamps for blocks
% =====================... |
github | alexanderlerch/ACA-Code-master | ToolMel2Freq.m | .m | ACA-Code-master/ToolMel2Freq.m | 771 | utf_8 | a29918db735e712ff9fe99e4e63d73b4 | %converts frequency to mel
%>
%> @param fMel: frequency
%> @param cModel: 'Fant','Shaughnessy', or 'Umesh'
%>
%> @retval Hertz value
% ======================================================================
function [fInHz] = ToolMel2Freq(fMel, cModel)
if (nargin < 2)
cModel = 'Fant';
end
% set fu... |
github | alexanderlerch/ACA-Code-master | ToolNormalizeAudio.m | .m | ACA-Code-master/ToolNormalizeAudio.m | 404 | utf_8 | 7c67b3e37a3459d6c3a1c22f6f6f8db9 | %normalizes audio signal
%>
%> @param x: audio signal (dimension length x channels)
%>
%> @retval x_norm (dimension length x 1)
% ======================================================================
function [x_norm] = ToolNormalizeAudio(x)
x_norm = x;
if (length(x) > 1)
fMax = max(abs(x), [], 'a... |
github | alexanderlerch/ACA-Code-master | ToolMfccFb.m | .m | ACA-Code-master/ToolMfccFb.m | 1,202 | utf_8 | 0051021cacfc671777760ebe7e7abf9b | %> see function mfcc.m from Slaneys Auditory Toolbox
function [H] = ToolMfccFb (iMagSpecLength, f_s)
% initialization
f_start = 133.3333;
iNumLinFilters = 13;
iNumLogFilters = 27;
iNumFilters = iNumLinFilters + iNumLogFilters;
linearSpacing = 66.66666666;
logSpacing ... |
github | alexanderlerch/ACA-Code-master | ComputePitch.m | .m | ACA-Code-master/ComputePitch.m | 2,739 | utf_8 | 535286fb1f39ab6db631a5c3e26a0dae | %computes the fundamental frequency of the (monophonic) audio
%>
%> supported pitch trackers are:
%> 'SpectralAcf',
%> 'SpectralHps',
%> 'TimeAcf',
%> 'TimeAmdf',
%> 'TimeAuditory',
%> 'TimeZeroCrossings',
%>
%> @param cPitchTrackName: feature to compute, e.g. 'SpectralHps'
%> @param x: time domain sample data, d... |
github | alexanderlerch/ACA-Code-master | FeatureSpectralMfccs.m | .m | ACA-Code-master/FeatureSpectralMfccs.m | 1,114 | utf_8 | 945c72b84d908fac9fd3a426b800db8e | %computes the MFCCs from the magnitude spectrum (see Slaney)
%> called by ::ComputeFeature
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval vmfcc mel frequency cepstral coefficients
% ========================================================... |
github | alexanderlerch/ACA-Code-master | FeatureSpectralTonalPowerRatio.m | .m | ACA-Code-master/FeatureSpectralTonalPowerRatio.m | 982 | utf_8 | bd309fc594c1eb0d502dc34d8df8696c | %computes the tonal power ratio from the magnitude spectrum
%> called by ::ComputeFeature
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data (unused)
%> @param G_T: energy threshold
%>
%> @retval vtpr tonal power ratio
% ============================================... |
github | alexanderlerch/ACA-Code-master | ComputeMelSpectrogram.m | .m | ACA-Code-master/ComputeMelSpectrogram.m | 2,976 | utf_8 | 31dc3bd99dc1e307a41afd65f04933d2 | %computes a mel spectrogram from the audio data
%>
%> @param x: time domain sample data, dimension channels X samples
%> @param f_s: sample rate of audio data
%> @param bLogarithmic: levels (true) or magnitudes (false)
%> @param afWindow: FFT window of length iBlockLength (default: hann), can be [] empty
%> @param iBlo... |
github | alexanderlerch/ACA-Code-master | FeatureTimeMaxAcf.m | .m | ACA-Code-master/FeatureTimeMaxAcf.m | 1,611 | utf_8 | 7d348acca64227e4e953e90023ac394f | %computes the ACF maxima of a time domain signal
%> called by ::ComputeFeature
%>
%> @param x: audio signal
%> @param iBlockLength: block length in samples
%> @param iHopLength: hop length in samples
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval vta autocorrelation maximum
%> @retval t time stamp
% ==... |
github | alexanderlerch/ACA-Code-master | ToolGmm.m | .m | ACA-Code-master/ToolGmm.m | 2,910 | utf_8 | b55e2457fedb899047415427d2ccc51b | %gaussian mixture model
%>
%> @param FeatureMatrix: features for all train observations (dimension iNumFeatures x iNumObservations)
%> @param k: number of gaussians
%> @param numMaxIter: maximum number of iterations (stop if not converged before)
%> @param prevState: internal state that can be stored to continue cluste... |
github | alexanderlerch/ACA-Code-master | ToolSimpleKnn.m | .m | ACA-Code-master/ToolSimpleKnn.m | 1,198 | utf_8 | 6d54f9b5519e0f6ea36081384697dcce | %performs knn classification
%>
%> @param TestFeatureVector: features for test observation (length iNumFeatures)
%> @param TrainFeatureMatrix: features for all train observations (dimension iNumFeatures x iNumObservations)
%> @param TrainClassIndices: audio signal (length iNumObservations)
%> @param k: number of points... |
github | alexanderlerch/ACA-Code-master | ToolFreq2Midi.m | .m | ACA-Code-master/ToolFreq2Midi.m | 349 | utf_8 | 46285fae04d5bf9fba6bfc0a56547d2c | %converts frequency to MIDI pitch
%>
%> @param fInHz: frequency
%> @param f_A4: tuning frequency
%>
%> @retval p MIDI pitch
% ======================================================================
function [p] = ToolFreq2Midi(fInHz, f_A4)
% set tuning freq
if (nargin < 2)
f_A4 = 440;
end
p = 6... |
github | alexanderlerch/ACA-Code-master | ToolInstFreq.m | .m | ACA-Code-master/ToolInstFreq.m | 410 | utf_8 | fbff3c0ddde9dff705e080ae32c793c2 | function [f_I] = ToolInstFreq(X,iHop,fs)
% get phase
phi = angle(X);
% phase offset
omega = pi*iHop/size(X,2)*(0:size(X,2)-1);
% unwrapped difference
deltaphi = omega + princarg_I(phi(2,:)-phi(1,:)-omega);
% instantaneous frequency
f_I = deltaphi/iHop/... |
github | alexanderlerch/ACA-Code-master | NoveltyLaroche.m | .m | ACA-Code-master/NoveltyLaroche.m | 559 | utf_8 | 20e33988272c796090e758478e0650c2 | %computes the novelty measure used by laroche
%> called by ::ComputeNoveltyFunction
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval d_lar novelty measure
% ======================================================================
function [d_... |
github | alexanderlerch/ACA-Code-master | FeatureSpectralFlux.m | .m | ACA-Code-master/FeatureSpectralFlux.m | 510 | utf_8 | e870fdd5740e095ceb9ee035fabb9efc | %computes the spectral flux from the magnitude spectrum
%> called by ::ComputeFeature
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval v spectral flux
% ======================================================================
function [vsf] =... |
github | alexanderlerch/ACA-Code-master | NoveltyHainsworth.m | .m | ACA-Code-master/NoveltyHainsworth.m | 556 | utf_8 | fd88b73df1fb66e886586a5b9932f16c | %computes the novelty measure used by Hainsworth
%> called by ::ComputeNoveltyFunction
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval d_hai novelty measure
% ======================================================================
function ... |
github | alexanderlerch/ACA-Code-master | PitchTimeAcf.m | .m | ACA-Code-master/PitchTimeAcf.m | 1,583 | utf_8 | 15a4bababc1f8741f5b70113dd880277 | %computes the lag of the autocorrelation function
%> called by ::ComputePitch
%>
%> @param x: audio signal
%> @param iBlockLength: block length in samples
%> @param iHopLength: hop length in samples
%> @param f_s: sample rate of audio data
%>
%> @retval f_0 acf lag (in Hz)
%> @retval t time stamp of f_0 estimate (in s... |
github | alexanderlerch/ACA-Code-master | FeatureSpectralSlope.m | .m | ACA-Code-master/FeatureSpectralSlope.m | 632 | utf_8 | 42b443d5040ffe4a6a583b7a6b0682ba | %computes the spectral slope from the magnitude spectrum
%> called by ::ComputeFeature
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval vssl spectral slope
% ======================================================================
function [v... |
github | alexanderlerch/ACA-Code-master | ToolViterbi.m | .m | ACA-Code-master/ToolViterbi.m | 1,839 | utf_8 | 062148dbafb226267dce6147474642f7 | %computes path through a probability matrix with Viterbi
%>
%> @param P_E: emmission probability matrix (S X N)
%> @param P_T: transition probability matrix (S X S)
%> @param p_s: start probability vector (S X 1)
%> @param bUseLogLikelihood: flag (default: false)
%>
%> @retval p path vector with matrix row indices (N)
... |
github | alexanderlerch/ACA-Code-master | ComputeNoveltyFunction.m | .m | ACA-Code-master/ComputeNoveltyFunction.m | 2,433 | utf_8 | a2dc46fc00e484a627610d74bfddf7c7 | %computes the novelty function for onset detection
%>
%> supported novelty measures are:
%> 'Flux',
%> 'Laroche',
%> 'Hainsworth'
%>
%> @param cNoveltyName: name of the novelty measure
%> @param x: time domain sample data, dimension channels X samples
%> @param f_s: sample rate of audio data
%> @param afWindow: FFT ... |
github | alexanderlerch/ACA-Code-master | FeatureTimeStd.m | .m | ACA-Code-master/FeatureTimeStd.m | 760 | utf_8 | 3fad3a8c434ab11cfdbe7582e1eccb5b | %computes the standard deviation of a time domain signal
%> called by ::ComputeFeature
%>
%> @param x: audio signal
%> @param iBlockLength: block length in samples
%> @param iHopLength: hop length in samples
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval vstd standard deviation
%> @retval t time stamp
... |
github | alexanderlerch/ACA-Code-master | PitchTimeAmdf.m | .m | ACA-Code-master/PitchTimeAmdf.m | 1,332 | utf_8 | 4dcc734fa19c128064c346ba97249d5b | %computes the lag of the average magnitude difference function
%> called by ::ComputePitch
%>
%> @param x: audio signal
%> @param iBlockLength: block length in samples
%> @param iHopLength: hop length in samples
%> @param f_s: sample rate of audio data
%>
%> @retval f_0 amdf lag (in Hz)
%> @retval t time stamp of f_0 ... |
github | alexanderlerch/ACA-Code-master | ToolPca.m | .m | ACA-Code-master/ToolPca.m | 501 | utf_8 | c2d55d1dab97db9932e5d36e34e968f0 | %principal component analysis
%>
%> @param V: input matrix (features X observations)
%>
%> @retval U_pc transformed features (score)
%> @retval T transformation matrix (loading)
%> @retval eigenvalues (latent)
% ======================================================================
function [U_pc,T,eigenvalues] = ToolP... |
github | alexanderlerch/ACA-Code-master | ToolMidi2Freq.m | .m | ACA-Code-master/ToolMidi2Freq.m | 319 | utf_8 | 50cef204f3652f7f66818750b3c1cf59 | %converts MIDI pitch to frequency
%>
%> @param p: MIDI pitch
%> @param f_A4: tuning frequency
%>
%> @retval f frequency
% ======================================================================
function [f] = ToolMidi2Freq(p, f_A4)
if (nargin < 2)
f_A4 = 440;
end
f = f_A4 * 2.^((p-69)/12);
end
|
github | alexanderlerch/ACA-Code-master | FeatureSpectralFlatness.m | .m | ACA-Code-master/FeatureSpectralFlatness.m | 561 | utf_8 | 2301930f9855f0e2a4671b422bbd158b | %computes the spectral flatness from the magnitude spectrum
%> called by ::ComputeFeature
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval vtf spectral flatness
% ======================================================================
functi... |
github | alexanderlerch/ACA-Code-master | ComputeBeatHisto.m | .m | ACA-Code-master/ComputeBeatHisto.m | 2,562 | utf_8 | 96fbdd88c24c7a2d42ff1ec142348c7b | %computes a simple beat histogram
%>
%> supported computation methods are:
%> 'Corr',
%> 'FFT',
%>
%> @param x: time domain sample data, dimension channels X samples
%> @param f_s: sample rate of audio data
%> @param cMethod: method of beat histogram computation (default: 'FFT')
%> @param afWindow: FFT window of leng... |
github | alexanderlerch/ACA-Code-master | ExampleMusicSpeechClassification.m | .m | ACA-Code-master/ExampleMusicSpeechClassification.m | 2,726 | utf_8 | 5b9c62ff777d5eb6df1174de6a91021b | function ExampleMusicSpeechClassification(cDatasetPath)
if (nargin<1)
% this script is written for the GTZAN music/speech dataset
% modify this path or use the function parameter to specify your
% dataset path
cDatasetPath = 'd:\dataset\music_speech\';
end
if (exist('Comput... |
github | alexanderlerch/ACA-Code-master | ToolFreq2Bark.m | .m | ACA-Code-master/ToolFreq2Bark.m | 785 | utf_8 | aa8fe703b11d8b47805b5fe55f39216f | %converts frequency to bark
%>
%> @param fInHz: frequency
%> @param cModel: 'Schroeder','Terhardt', 'Zwicker', or 'Traunmuller'
%>
%> @retval bark value
% ======================================================================
function [bark] = ToolFreq2Bark(fInHz, cModel)
if (nargin < 2)
cModel = 'Schroede... |
github | alexanderlerch/ACA-Code-master | NoveltyFlux.m | .m | ACA-Code-master/NoveltyFlux.m | 579 | utf_8 | 0841bdddb47dada52808a2426d3c9f9d | %computes the novelty measure per Spectral Flux
%> called by ::ComputeNoveltyFunction
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval d_flux novelty measure
% ======================================================================
function ... |
github | alexanderlerch/ACA-Code-master | FeatureSpectralCentroid.m | .m | ACA-Code-master/FeatureSpectralCentroid.m | 574 | utf_8 | 44288446d5af92043eefbbe20b5deebc | %computes the spectral centroid from the (squared) magnitude spectrum
%> called by ::ComputeFeature
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data
%>
%> @retval v spectral centroid (in Hz)
% =====================================================================... |
github | alexanderlerch/ACA-Code-master | ComputeChords.m | .m | ACA-Code-master/ComputeChords.m | 3,606 | utf_8 | 2f33f325676424e1c1f90a7d284e857b | %computes the chords of the input audio (super simple variant)
%>
%> @param x: time domain sample data, dimension samples X channels
%> @param f_s: sample rate of audio data
%> @param iBlockLength: internal block length (default: 4096 samples)
%> @param iHopLength: internal hop length (default: 2048 samples)
%>
%> @ret... |
github | alexanderlerch/ACA-Code-master | PitchSpectralAcf.m | .m | ACA-Code-master/PitchSpectralAcf.m | 1,110 | utf_8 | af0449770382a87182e8ff3396c92172 | %computes the maximum of the spectral autocorrelation function
%> called by ::ComputePitch
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data
%>
%> @retval f_0 acf maximum location (in Hz)
% ======================================================================
fu... |
github | alexanderlerch/ACA-Code-master | FeatureTimePeakEnvelope.m | .m | ACA-Code-master/FeatureTimePeakEnvelope.m | 1,636 | utf_8 | aa05c0e41dd69ca4cf03b8360aec6543 | %computes two peak envelope measures for a time domain signal
%> called by ::ComputeFeature
%>
%> @param x: audio signal
%> @param iBlockLength: block length in samples
%> @param iHopLength: hop length in samples
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval vppm peak envelope (1,:: max, 2,:: PPM)
%> ... |
github | alexanderlerch/ACA-Code-master | ComputeFeature.m | .m | ACA-Code-master/ComputeFeature.m | 3,021 | utf_8 | f29bc2ce81cd57c684be623db3a81eb7 | %computes a feature from the audio data
%>
%> supported features are:
%> 'SpectralCentroid',
%> 'SpectralCrestFactor',
%> 'SpectralDecrease',
%> 'SpectralFlatness',
%> 'SpectralFlux',
%> 'SpectralKurtosis',
%> 'SpectralMfccs',
%> 'SpectralPitchChroma',
%> 'SpectralRolloff',
%> 'SpectralSkewness',
%> 'Spectra... |
github | alexanderlerch/ACA-Code-master | FeatureSpectralSpread.m | .m | ACA-Code-master/FeatureSpectralSpread.m | 825 | utf_8 | c9f2fdb507acf1a7afff3726200c0ea9 | %computes the spectral spread from the magnitude spectrum
%> called by ::ComputeFeature
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data
%>
%> @retval vss spectral spread (in Hz)
% ======================================================================
function [... |
github | alexanderlerch/ACA-Code-master | ToolSimpleDtw.m | .m | ACA-Code-master/ToolSimpleDtw.m | 1,292 | utf_8 | 3d5b9894ce6c48cdd96b6255bb1e833a | %computes path through a distance matrix with simple Dynamic Time
%> Warping
%>
%> @param D: distance matrix
%>
%> @retval p path with matrix indices
%> @retval C cost matrix
% ======================================================================
function [p, C] = ToolSimpleDtw(D)
% cost initialization
C = z... |
github | alexanderlerch/ACA-Code-master | FeatureTimeAcfCoeff.m | .m | ACA-Code-master/FeatureTimeAcfCoeff.m | 1,234 | utf_8 | 65187467a17d464acfc8bfbbfbd4f98d | %computes the ACF coefficients of a time domain signal
%> called by ::ComputeFeature
%>
%> @param x: audio signal
%> @param iBlockLength: block length in samples
%> @param iHopLength: hop length in samples
%> @param f_s: sample rate of audio data (unused)
%> @param eta: index (or vector of indices) of coeff result
%>
%... |
github | alexanderlerch/ACA-Code-master | FeatureSpectralRolloff.m | .m | ACA-Code-master/FeatureSpectralRolloff.m | 763 | utf_8 | a791d6eba142cd768ebfb828d99a6425 | %computes the spectral rolloff from the magnitude spectrum
%> called by ::ComputeFeature
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data
%> @param kappa: cutoff ratio
%>
%> @retval vsr spectral rolloff (in Hz)
% =================================================... |
github | alexanderlerch/ACA-Code-master | ComputeKey.m | .m | ACA-Code-master/ComputeKey.m | 2,047 | utf_8 | fd1c2cbd9c34731d7f62268bdb0c7bf8 | %computes the key of the input audio (super simple variant)
%>
%> @param x: time domain sample data, dimension samples X channels
%> @param f_s: sample rate of audio data
%> @param afWindow: FFT window of length iBlockLength (default: hann), can be [] empty
%> @param iBlockLength: internal block length (default: 4096 s... |
github | alexanderlerch/ACA-Code-master | FeatureTimeZeroCrossingRate.m | .m | ACA-Code-master/FeatureTimeZeroCrossingRate.m | 795 | utf_8 | f49bac7e7cdf2b72153efa727ea57aa5 | %computes the zero crossing rate from a time domain signal
%> called by ::ComputeFeature
%>
%> @param x: audio signal
%> @param iBlockLength: block length in samples
%> @param iHopLength: hop length in samples
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval vzc zero crossing rate
%> @retval t time stamp... |
github | alexanderlerch/ACA-Code-master | ToolSimpleKmeans.m | .m | ACA-Code-master/ToolSimpleKmeans.m | 2,387 | utf_8 | 0b588bea4e043b2f38fc93fe65f24a71 | %performs kmeans clustering
%>
%> @param V: features for all train observations (dimension iNumFeatures x iNumObservations)
%> @param k: number of clusters
%> @param numMaxIter: maximum number of iterations (stop if not converged before)
%> @param prevState: internal state that can be stored to continue clustering late... |
github | alexanderlerch/ACA-Code-master | ToolLooCrossVal.m | .m | ACA-Code-master/ToolLooCrossVal.m | 1,253 | utf_8 | 5fbb3919dc2e8546f4cec32bf302f77f | %Leave One Out Cross Validation with Nearest Neighbor Classifier
%>
%> @param FeatureMatrix: features (dimension iNumFeatures x iNumObservations)
%> @param ClassIdx: vector with class indices (length iNumObservations, starting from 0)
%>
%> @retval Acc overall accuracy after Cross-Validation
% =========================... |
github | alexanderlerch/ACA-Code-master | FeatureTimeRms.m | .m | ACA-Code-master/FeatureTimeRms.m | 1,204 | utf_8 | 3733866161530487e0078197202b802f | %computes the RMS of a time domain signal
%> called by ::ComputeFeature
%>
%> @param x: audio signal
%> @param iBlockLength: block length in samples
%> @param iHopLength: hop length in samples
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval vrms root mean square (row 1: block-based rms, row 2: single po... |
github | alexanderlerch/ACA-Code-master | ComputeFingerprint.m | .m | ACA-Code-master/ComputeFingerprint.m | 2,593 | utf_8 | e72c5cd9980002465dec1ac2bfa53de7 | %computes a fingerprint of the audio data (only the subfingerprint, one
%fingerprint is comprised of 256 consecutive subfingerprints.
%>
%> @param x: time domain sample data,
%> @param f_s: sample rate of audio data
%>
%> @retval F series of subfingerprints
%> @retval tf time stamps for the subfingerprints
% =========... |
github | alexanderlerch/ACA-Code-master | FeatureSpectralKurtosis.m | .m | ACA-Code-master/FeatureSpectralKurtosis.m | 798 | utf_8 | c7e473512707ce57ad110a3a5508c521 | %computes the spectral kurtosis from the magnitude spectrum
%> called by ::ComputeFeature
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval vsk spectral kurtosis
% ======================================================================
functi... |
github | alexanderlerch/ACA-Code-master | ComputeSpectrogram.m | .m | ACA-Code-master/ComputeSpectrogram.m | 2,062 | utf_8 | de533610583c599ff044bd70a7828136 | %computes a mel spectrogram from the audio data
%>
%> @param x: time domain sample data, dimension channels X samples
%> @param f_s: sample rate of audio data
%> @param afWindow: FFT window of length iBlockLength (default: hann), can be [] empty
%> @param iBlockLength: internal block length (default: 4096 samples)
%> @... |
github | alexanderlerch/ACA-Code-master | ToolSeqFeatureSel.m | .m | ACA-Code-master/ToolSeqFeatureSel.m | 1,967 | utf_8 | 1d97adfee044361c0f3d5c622e00ee40 | %computes Sequential Forward Feature Selection wrapping a nearest neighbor
%classifier
%>
%> @param V: features (dimension iNumFeatures x iNumObservations)
%> @param ClassIdx: vector with class indices (length iNumObservations)
%> @param iNumFeatures2Select: target number of features (optional)
%>
%> @retval selFeature... |
github | alexanderlerch/ACA-Code-master | ToolDownmix.m | .m | ACA-Code-master/ToolDownmix.m | 346 | utf_8 | 6605347b90174dad3d6145094c5aed34 | %downmixes audio signal
%>
%> @param x: audio signal (dimension length x channels)
%>
%> @retval x_downmix (dimension length x 1)
% ======================================================================
function [x_downmix] = ToolDownmix(x)
if (size(x, 2) > 1)
x_downmix = mean(x, 2);
else
x... |
github | alexanderlerch/ACA-Code-master | FeatureSpectralDecrease.m | .m | ACA-Code-master/FeatureSpectralDecrease.m | 637 | utf_8 | 0ae746df9b7090cd28660dd4dd094817 | %computes the spectral decrease from the magnitude spectrum
%> called by ::ComputeFeature
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval vsk spectral decrease
% ======================================================================
functi... |
github | alexanderlerch/ACA-Code-master | FeatureSpectralSkewness.m | .m | ACA-Code-master/FeatureSpectralSkewness.m | 790 | utf_8 | 744e563ff132b9859458027d039f3d9e | %computes the spectral skewness from the magnitude spectrum
%> called by ::ComputeFeature
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval v spectral skewness
% ======================================================================
function... |
github | alexanderlerch/ACA-Code-master | ToolSimpleNmf.m | .m | ACA-Code-master/ToolSimpleNmf.m | 2,019 | utf_8 | 7c784cca05eef0d0e75e0a9cd8977505 | %computes nmf (implementation inspired by
%https://github.com/cwu307/NmfDrumToolbox/blob/master/src/PfNmf.m)
%>
%> @param X: non-negative matrix to factorize (usually ifreq x iObservations)
%> @param iRank: nmf rank
%> @param iMaxIteration: maximum number of iterations (default: 300)
%> @param fSparsity: sparsity weigh... |
github | alexanderlerch/ACA-Code-master | PitchTimeAuditory.m | .m | ACA-Code-master/PitchTimeAuditory.m | 2,147 | utf_8 | ab9057eb9153280b19d236b93845ad8e | %computes the f_0 via a simple "auditory" approach
%> called by ::ComputePitch
%>
%> @param x: audio signal
%> @param iBlockLength: block length in samples
%> @param iHopLength: hop length in samples
%> @param f_s: sample rate of audio data
%>
%> @retval f_0 fundamental frequency estimate (in Hz)
%> @retval t time sta... |
github | alexanderlerch/ACA-Code-master | ToolGammatoneFb.m | .m | ACA-Code-master/ToolGammatoneFb.m | 3,574 | utf_8 | f38632ad433fcf60de574207564e7c8c | %computes a gammatone filterbank
%> see function MakeERBFilters.m from Slaneys Auditory Toolbox
%>
%> @param afAudioData: time domain sample data, dimension channels X samples
%> @param f_s: sample rate of audio data
%> @param iNumBands: number of filter bands
%> @param f_low: start frequency
%>
%> @retval X filtered s... |
github | alexanderlerch/ACA-Code-master | PitchSpectralHps.m | .m | ACA-Code-master/PitchSpectralHps.m | 807 | utf_8 | 0a7a68a4734f979600fd2f5fd2463f14 | %computes the maximum of the Harmonic Product Spectrum
%> called by ::ComputePitch
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data
%>
%> @retval f_0 HPS maximum (in Hz)
% ======================================================================
function [f_0] = Pi... |
github | alexanderlerch/ACA-Code-master | ToolFreq2Mel.m | .m | ACA-Code-master/ToolFreq2Mel.m | 668 | utf_8 | d6ceefd4518c3e29f266641a6d0219d4 | %converts frequency to mel
%>
%> @param fInHz: frequency
%> @param cModel: 'Fant','Shaughnessy', or 'Umesh'
%>
%> @retval mel pitch value
% ======================================================================
function [mel] = ToolFreq2Mel(fInHz, cModel)
if (nargin < 2)
cModel = 'Fant';
end
% set... |
github | alexanderlerch/ACA-Code-master | FeatureSpectralPitchChroma.m | .m | ACA-Code-master/FeatureSpectralPitchChroma.m | 1,472 | utf_8 | 0befb87f42b383708be9ed0bbf3e2c36 | %computes the pitch chroma from the magnitude spectrum
%> called by ::ComputeFeature
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data
%>
%> @retval vpc pitch chroma
% ======================================================================
function [vpc] = FeatureS... |
github | alexanderlerch/ACA-Code-master | PitchTimeZeroCrossings.m | .m | ACA-Code-master/PitchTimeZeroCrossings.m | 1,007 | utf_8 | 27170512d6e1e9dc37bbf291a8e45383 | %computes f_0 through zero crossing distances
%> called by ::ComputePitch
%>
%> @param x: audio signal
%> @param iBlockLength: block length in samples
%> @param iHopLength: hop length in samples
%> @param f_s: sample rate of audio data
%>
%> @retval f_0 double zero crossing distance (in Hz)
%> @retval t time stamp of ... |
github | alexanderlerch/ACA-Code-master | FeatureSpectralCrestFactor.m | .m | ACA-Code-master/FeatureSpectralCrestFactor.m | 504 | utf_8 | b145b2e92dd38ed4bd2336f2a51e0805 | %computes the spectral crest from the magnitude spectrum
%> called by ::ComputeFeature
%>
%> @param X: spectrogram (dimension FFTLength X Observations)
%> @param f_s: sample rate of audio data (unused)
%>
%> @retval vtsc spectral crest factor
% ======================================================================
func... |
github | MichiganTechRoboticsLab/SLAM-Scan-Matching-master | psm.m | .m | SLAM-Scan-Matching-master/PSM/psm.m | 7,527 | utf_8 | 6679d80298481d393552022bcbcba279 | %% MainFunction
function [ offset, iter, avg_err, axs, ays, aths, errs, dxs, dys, dths, stoperr ] = psm( offset, scan, ref, varargin )
%% setupParser
p = inputParser;
p.addParameter('PM_STOP_COND', .0004, @(x)isnumeric(x));
p.addParameter('PM_MAX_ITER', 60, @(x)isnumeric(x));
p.addParameter('PM_MAX_... |
github | MichiganTechRoboticsLab/SLAM-Scan-Matching-master | gicp.m | .m | SLAM-Scan-Matching-master/GICP/gicp.m | 5,711 | utf_8 | fa1e6f595613e42f6ce1e92ba527def2 | function [ offset, numIterations, lastCost ] = gicp( offset, new_data, ref, varargin )
%UNTITLED Summary of this function goes here
% Detailed explantion goes here
p = inputParser;
p.addParameter('costThresh', .004, @(x)isnumeric(x));
p.addParameter('minMatchDist', 2.0, @(x)isnumeric(x));
... |
github | MichiganTechRoboticsLab/SLAM-Scan-Matching-master | icp1.m | .m | SLAM-Scan-Matching-master/ICP/icp1/icp1.m | 18,588 | utf_8 | 260e5cde8fe592efeb0ff26fa318c748 | function [TR, TT, ER, t] = icp1(q,p,varargin)
% Perform the Iterative Closest Point algorithm on three dimensional point
% clouds.
%
% [TR, TT] = icp(q,p) returns the rotation matrix TR and translation
% vector TT that minimizes the distances from (TR * p + TT) to q.
% p is a 3xm matrix and q is a 3xn matrix.
%
% [TR... |
github | ela-rana/HIVSimulation-master | gridxy.m | .m | HIVSimulation-master/gridxy.m | 4,900 | utf_8 | 8e635fd7f79259b0e0ba54b1ce8c72a5 | % % Copyright (c) 2009, Jos van der Geest
% % All rights reserved.
% %
% % Redistribution and use in source and binary forms, with or without
% % modification, are permitted provided that the following conditions are
% % met:
% %
% % * Redistributions of source code must retain the above copyright
% % notic... |
github | genie-model/cgenie-master | plot_target.m | .m | cgenie-master/genie-matlab/plot_target.m | 10,160 | utf_8 | c53f848ecf5ff1a6001fba5540d7d853 | % ------------------------------PLOT_TARGET-------------------------------
% ------------------------------------------------------------------------
% Description: Plots the target diagram of Jolliff et al.(2009) for
% model skill assessment.
%
% plot_target has been designed to be accomodate most uses of the target... |
github | genie-model/cgenie-master | plot_taylordiag.m | .m | cgenie-master/genie-matlab/plot_taylordiag.m | 17,036 | utf_8 | c79f5934280b24a0a72d04d99e2b8136 | % TAYLORDIAG Plot a Taylor Diagram
%
% [hp ht axl] = taylordiag(STDs,RMSs,CORs,['option',value])
%
% Plot a Taylor diagram from statistics of different series.
%
% INPUTS:
% STDs: Standard deviations
% RMSs: Centered Root Mean Square Difference
% CORs: Correlation
%
% Each of these inputs are one dimensional with same... |
github | genie-model/cgenie-master | calc_allstats_target.m | .m | cgenie-master/genie-matlab/calc_allstats_target.m | 3,756 | utf_8 | 72d881656a00579d2c25de4127286aa6 | % STATM Compute statistics from 2 series
%
% STATM = calc_allstats(Cr,Cf)
%
% Compute statistics from 2 series considering Cr as the reference.
%
% Inputs:
% Cr and Cf are of same length and uni-dimensional. They may contain NaNs.
%
% Outputs:
% STATM(1,:) => Mean
% STATM(2,:) => Standard Deviation (scaled by N)
% ... |
github | genie-model/cgenie-master | calc_allstats.m | .m | cgenie-master/genie-matlab/calc_allstats.m | 3,756 | utf_8 | 72d881656a00579d2c25de4127286aa6 | % STATM Compute statistics from 2 series
%
% STATM = calc_allstats(Cr,Cf)
%
% Compute statistics from 2 series considering Cr as the reference.
%
% Inputs:
% Cr and Cf are of same length and uni-dimensional. They may contain NaNs.
%
% Outputs:
% STATM(1,:) => Mean
% STATM(2,:) => Standard Deviation (scaled by N)
% ... |
github | genie-model/cgenie-master | plot_taylor.m | .m | cgenie-master/genie-matlab/plot_taylor.m | 10,197 | utf_8 | a4184a67e8a147139dd4bbb5de8fff43 | % Taylor diagram for summarizing model performance
%
% Taylor, 2001 - JGR, 106(D7)
%
% Program adapted from the IDL routine from K.E. Taylor
% (simplified version including less options)
%
% ---- Call :
% plot_taylor(tsig,rsig,tcorr,out,name_experiment,title)
%
% ---- Input:
% Needed:
% tsig : Standard ... |
github | genie-model/cgenie-master | pdftops.m | .m | cgenie-master/genie-matlab/export_fig/pdftops.m | 2,962 | utf_8 | fc695d9dae7025244e0f02be5116be46 | function varargout = pdftops(cmd)
%PDFTOPS Calls a local pdftops executable with the input command
%
% Example:
% [status result] = pdftops(cmd)
%
% Attempts to locate a pdftops executable, finally asking the user to
% specify the directory pdftops was installed into. The resulting path is
% stored for future refere... |
github | genie-model/cgenie-master | isolate_axes.m | .m | cgenie-master/genie-matlab/export_fig/isolate_axes.m | 3,447 | utf_8 | c6ed56010868279f32b86dfa9815d524 | %ISOLATE_AXES Isolate the specified axes in a figure on their own
%
% Examples:
% fh = isolate_axes(ah)
% fh = isolate_axes(ah, vis)
%
% This function will create a new figure containing the axes/uipanels
% specified, and also their associated legends and colorbars. The objects
% specified must all be in the same f... |
github | genie-model/cgenie-master | pdf2eps.m | .m | cgenie-master/genie-matlab/export_fig/pdf2eps.m | 1,473 | utf_8 | cb8bb442a3d65a64025c32693704d89e | %PDF2EPS Convert a pdf file to eps format using pdftops
%
% Examples:
% pdf2eps source dest
%
% This function converts a pdf file to eps format.
%
% This function requires that you have pdftops, from the Xpdf suite of
% functions, installed on your system. This can be downloaded from:
% http://www.foolabs.com/xpdf ... |
github | genie-model/cgenie-master | print2array.m | .m | cgenie-master/genie-matlab/export_fig/print2array.m | 6,276 | utf_8 | 259fd52e4431efae4d76ca22d1d8dac8 | %PRINT2ARRAY Exports a figure to an image array
%
% Examples:
% A = print2array
% A = print2array(figure_handle)
% A = print2array(figure_handle, resolution)
% A = print2array(figure_handle, resolution, renderer)
% [A bcol] = print2array(...)
%
% This function outputs a bitmap image of the given figure, at t... |
github | genie-model/cgenie-master | eps2pdf.m | .m | cgenie-master/genie-matlab/export_fig/eps2pdf.m | 5,017 | utf_8 | bc81caea32035f06d8cb08ea1ccdc81f | %EPS2PDF Convert an eps file to pdf format using ghostscript
%
% Examples:
% eps2pdf source dest
% eps2pdf(source, dest, crop)
% eps2pdf(source, dest, crop, append)
% eps2pdf(source, dest, crop, append, gray)
% eps2pdf(source, dest, crop, append, gray, quality)
%
% This function converts an eps file to pdf f... |
github | genie-model/cgenie-master | copyfig.m | .m | cgenie-master/genie-matlab/export_fig/copyfig.m | 814 | utf_8 | 1844a9d51dbe52ce3927c9eac5ee672e | %COPYFIG Create a copy of a figure, without changing the figure
%
% Examples:
% fh_new = copyfig(fh_old)
%
% This function will create a copy of a figure, but not change the figure,
% as copyobj sometimes does, e.g. by changing legends.
%
% IN:
% fh_old - The handle of the figure to be copied. Default: gcf.
%
% OU... |
github | genie-model/cgenie-master | user_string.m | .m | cgenie-master/genie-matlab/export_fig/user_string.m | 2,462 | utf_8 | dd1a7fa5b4f2be6320fc2538737a2f3e | %USER_STRING Get/set a user specific string
%
% Examples:
% string = user_string(string_name)
% saved = user_string(string_name, new_string)
%
% Function to get and set a string in a system or user specific file. This
% enables, for example, system specific paths to binaries to be saved.
%
% IN:
% string_name - ... |
github | genie-model/cgenie-master | export_fig.m | .m | cgenie-master/genie-matlab/export_fig/export_fig.m | 29,548 | utf_8 | 3612e1262313930072086167762d84f5 | %EXPORT_FIG Exports figures suitable for publication
%
% Examples:
% im = export_fig
% [im alpha] = export_fig
% export_fig filename
% export_fig filename -format1 -format2
% export_fig ... -nocrop
% export_fig ... -transparent
% export_fig ... -native
% export_fig ... -m<val>
% export_fig ... -r<val... |
github | genie-model/cgenie-master | ghostscript.m | .m | cgenie-master/genie-matlab/export_fig/ghostscript.m | 4,505 | utf_8 | 18a672bb6982a1fbc6b21b3ab52b0fc9 | %GHOSTSCRIPT Calls a local GhostScript executable with the input command
%
% Example:
% [status result] = ghostscript(cmd)
%
% Attempts to locate a ghostscript executable, finally asking the user to
% specify the directory ghostcript was installed into. The resulting path
% is stored for future reference.
%
% Once ... |
github | genie-model/cgenie-master | gen_topo_7.m | .m | cgenie-master/genie-matlab/yoolarator/gen_topo_7.m | 29,631 | utf_8 | b37805dc57ddfe6c691e807fd4695d37 | function [new_topo landsea2] = gen_topo_7(tblon, tblat, btopo, nlon, nlat, ndep, smpar, filename, oldmask);
% GEN_TOPO_7
%
% ***********************************************************************
% *** Generates a GOLDSTEIN topography **********************************
% ****************************************... |
github | genie-model/cgenie-master | gen_topo_6.m | .m | cgenie-master/genie-matlab/yoolarator/gen_topo_6.m | 28,922 | utf_8 | 833ca0a68d2c6dc86d2337375bc62d75 | function [new_topo landsea2] = gen_topo_6(blon, blat, btopo, nlon, nlat, ndep, smpar, filename, oldmask);
% GEN_TOPO_6 Generates a GOLDSTEIN topography
%
% Returns a 'world.k1' file for GOLDSTEIN. Restricted at
% the moment insofar as it still requires an the user to
% somehow specify the land drainage pattern.... |
github | mathworks/Enigma-master | plugBoard.m | .m | Enigma-master/@plugBoard/plugBoard.m | 7,878 | utf_8 | dc8caf5b49a3790cf46ebee93b1ba691 | classdef plugBoard < handle
% This class is a plugBoard
% part of the Enigma M3 Emulator
% Copyright 2015, The MathWorks Inc.
% Properties
properties (SetAccess= protected)
Connections = diag(true(1,26)) % Binary connectivity matrix
end
% Events
events
NewConnection % Fire... |
github | mathworks/Enigma-master | evaluateEnteredChar.m | .m | Enigma-master/@enigmaApp/evaluateEnteredChar.m | 3,212 | utf_8 | 3ffc917fb15ec0600e30fc918d5da4f2 | function evaluateEnteredChar(app,str)
% EVALUATEENTEREDCHAR - Evaluate actions based on entered characters
% part of the Enigma M3 Emulator
% Copyright 2015, The MathWorks Inc
switch str
case num2cell('A':'Z')
% Check if there is enough space in notepad
% before running new character... |
github | mathworks/Enigma-master | catchMouseScroll.m | .m | Enigma-master/@enigmaApp/catchMouseScroll.m | 795 | utf_8 | 41b8e0702d59c263e511ed7eceb67f43 | function catchMouseScroll(app,src,evt)
% CATCHMOUSESCROLL - Catch mouse scroll over rotors
% part of the Enigma M3 Emulator
% Copyright 2015, The MathWorks Inc.
src.Units = 'Normalized';
curPoint = src.CurrentPoint;
if evt.VerticalScrollCount > 0
scrollDir = 1;
else
scrollDir = -1;
end
src.Units = 'Pixels';
... |
github | mathworks/Enigma-master | respondToProcessedMessageEvent.m | .m | Enigma-master/@enigmaApp/respondToProcessedMessageEvent.m | 2,021 | utf_8 | b2f0033c74c659a63599387dc866e30e | function respondToProcessedMessageEvent(app)
% RESPONDTOPROCESSEDMESSAGEEVENT - ProcessedMessage event triggers this
% function to update diary window with input and processed messages
% part of the Enigma M3 Emulator
% Copyright 2015, The MathWorks Inc
% Get machine logs
inputStr = app.enigmaObj.InputLog;
output... |
github | mathworks/Enigma-master | preferences.m | .m | Enigma-master/@enigmaApp/preferences.m | 11,204 | utf_8 | d95839b6ce62bb7bd664556e4894f93e | function preferences(eApp)
% PREFERENCES UI to configure Enigma Machine preferences.
% part of the Enigma M3 Emulator
% Copyright 2015, The MathWorks Inc.
% Configure available menu choices
availRotorValues = {'Rotor I' ;
'Rotor II' ;
'Rotor III' ;
'Rotor IV' ;
'Rotor V' ;
'Rotor VI' ;
... |
github | mathworks/Enigma-master | catchMouseMotion.m | .m | Enigma-master/@enigmaApp/catchMouseMotion.m | 2,703 | utf_8 | b10aca36a59a911ca92538160131108f | function catchMouseMotion(app,src)
% CATCHMOUSEMOTION - Catch motion of mouse to determine mouse icon
% part of the Enigma M3 Emulator
% Copyright 2015, The MathWorks Inc.
% Determine location of mouse
src.Units = 'Normalized';
curPoint = src.CurrentPoint;
src.Units = 'Pixels';
% If over any wheel, change to scroll... |
github | jebej/MatlabWebSocket-master | ditto.m | .m | MatlabWebSocket-master/test/ditto.m | 668 | utf_8 | 32e10e58b708e97a055cc94ac52cdc2e | function client = ditto()
DITTO_IP = 'ditto.eclipse.org';
DITTO_PORT = '80';
THING_FEATURE = '';
THING_USR = 'demo1';
THING_PWD = 'demo';
address = get_address(DITTO_IP, DITTO_PORT, THING_FEATURE);
headers = get_headers(THING_USR, THING_PWD);
client = SimpleClient(address, headers);
client.send('START-SEND-MESSAGES'... |
github | ThomasTram/LASAGNA_public-master | test_linear_system.m | .m | LASAGNA_public-master/test_linear_system.m | 1,546 | utf_8 | 16100de4ed266de04d2cf209d2131bcd | function test_linear_system
clear;
clc;
load('west0479.mat')
A = west0479;
x = [(1:479)', (-479:1:-1)'];
z = (1-1i)*x;
rng(11);
Aimag = 2*(rand(nnz(A),1)-0.5);
Az_mat = A;
Az_mat(find(Az_mat)) = Az_mat(find(Az_mat))+Aimag*1i;
b = A*x;
bz = Az_mat*z;
xsol = A\b;
zsol = Az_mat\bz;
relreal = abs(1-xso... |
github | ThomasTram/LASAGNA_public-master | load_and_plot.m | .m | LASAGNA_public-master/load_and_plot.m | 10,290 | utf_8 | f0a9f1a24ce2e087006bb701dc787d60 | function S = ouput_matrix
%Read output matrix:
clear;clc;
close all;
%filename = 'output/sim_alpha_1.mat'
%momentum bin of special interest: in [1; vres]
mbin = 51;
analytic_static = true;
Ti_lowtemp = 6;%MeV
filename = 'output/dump.mat';
%filename = 'output/ref.mat';
%filename = 'dump_004_008.mat';
load(... |
github | ThomasTram/LASAGNA_public-master | thermalisation_cartoon.m | .m | LASAGNA_public-master/thermalisation_cartoon.m | 4,261 | utf_8 | bb7d1dde33409a1b366dd9bc99c857aa | function Do_thermalisation_cartoon
clc;clear;
close all
%filename = 'd:\Shared\lasagna_svn\te_IH_0_ndf\dump_004_008.mat'
%filename = 'd:\Shared\lasagna_svn\dump_004_008.mat'
%filename = 'd:\Shared\chaos\dump_004_008.mat'
filename = 'd:\Shared\chaos\test_004_008.mat'
dump_at_x = [0.1,1,2,3,5,10];
load(file... |
github | ThomasTram/LASAGNA_public-master | lepton_number_thermalisation.m | .m | LASAGNA_public-master/lepton_number_thermalisation.m | 17,706 | utf_8 | 9f2afd3b3103fd3346712c09d2db4b4a | function lepton_number_thermalisation(varargin)
close all
if nargin==0
clear; clc;
prefix_filename = 'radau_tmp';
% prefix_filename = 'aa_IH_1em2';
%dirname = 'd:\Shared\lasagna_svn\thermal_NH_3\';
%dirname = 'd:\Shared\lasagna_radau\output\run1\';
%dirname = 'd:\Shared\lasagna_radau\outp... |
github | ThomasTram/LASAGNA_public-master | eps2pdf.m | .m | LASAGNA_public-master/eps2pdf.m | 11,112 | utf_8 | 637147b7f7b2ad8396177ce661f6088d | function [result,msg] = eps2pdf(epsFile,fullGsPath,orientation)
%EPS2PDF Converts an eps file to a pdf file using GhostScript (GS)
%
% [result,msg] = eps2pdf(epsFile,fullGsPath,orientation)
%
% - epsFile: eps file name to be converted to pdf file
% - fullGsPath: (optional) FULL GS path, including the... |
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