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value | path stringlengths 12 229 | size int64 23 843k | source_encoding stringclasses 9
values | md5 stringlengths 32 32 | text stringlengths 23 843k |
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github | msyamkumar/vision-panorama-master | vl_test_ihashsum.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_ihashsum.m | 581 | utf_8 | edc283062469af62056b0782b171f5fc | function results = vl_test_ihashsum(varargin)
% VL_TEST_IHASHSUM
vl_test_init ;
function s = setup()
rand('state',0) ;
s.data = uint8(round(16*rand(2,100))) ;
sel = find(all(s.data==0)) ;
s.data(1,sel)=1 ;
function test_hash(s)
D = size(s.data,1) ;
K = 5 ;
h = zeros(1,K,'uint32') ;
id = zeros(D,K,'uint8');
next = zer... |
github | msyamkumar/vision-panorama-master | vl_test_grad.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_grad.m | 434 | utf_8 | 4d03eb33a6a4f68659f868da95930ffb | function results = vl_test_grad(varargin)
% VL_TEST_GRAD
vl_test_init ;
function s = setup()
s.I = rand(150,253) ;
s.I_small = rand(2,2) ;
function test_equiv(s)
vl_assert_equal(gradient(s.I), vl_grad(s.I)) ;
function test_equiv_small(s)
vl_assert_equal(gradient(s.I_small), vl_grad(s.I_small)) ;
function test_equiv... |
github | msyamkumar/vision-panorama-master | vl_test_whistc.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_whistc.m | 1,384 | utf_8 | 81c446d35c82957659840ab2a579ec2c | function results = vl_test_whistc(varargin)
% VL_TEST_WHISTC
vl_test_init ;
function test_acc()
x = ones(1, 10) ;
e = 1 ;
o = 1:10 ;
vl_assert_equal(vl_whistc(x, o, e), 55) ;
function test_basic()
x = 1:10 ;
e = 1:10 ;
o = ones(1, 10) ;
vl_assert_equal(histc(x, e), vl_whistc(x, o, e)) ;
x = linspace(-1,11,100) ;
o =... |
github | msyamkumar/vision-panorama-master | vl_test_roc.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_roc.m | 1,019 | utf_8 | 9b2ae71c9dc3eda0fc54c65d55054d0c | function results = vl_test_roc(varargin)
% VL_TEST_ROC
vl_test_init ;
function s = setup()
s.scores0 = [5 4 3 2 1] ;
s.scores1 = [5 3 4 2 1] ;
s.labels = [1 1 -1 -1 -1] ;
function test_perfect_tptn(s)
[tpr,tnr] = vl_roc(s.labels,s.scores0) ;
vl_assert_almost_equal(tpr, [0 1 2 2 2 2] / 2) ;
vl_assert_almost_equal(tnr,... |
github | msyamkumar/vision-panorama-master | vl_test_dsift.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_dsift.m | 2,048 | utf_8 | fbbfb16d5a21936c1862d9551f657ccc | function results = vl_test_dsift(varargin)
% VL_TEST_DSIFT
vl_test_init ;
function s = setup()
I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
s.I = rgb2gray(single(I)) ;
function test_fast_slow(s)
binSize = 4 ; % bin size in pixels
magnif = 3 ; % bin size / keypoint scale
scale = binSize... |
github | msyamkumar/vision-panorama-master | vl_test_alldist2.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_alldist2.m | 2,284 | utf_8 | 89a787e3d83516653ae8d99c808b9d67 | function results = vl_test_alldist2(varargin)
% VL_TEST_ALLDIST
vl_test_init ;
% TODO: test integer classes
function s = setup()
vl_twister('state', 0) ;
s.X = 3.1 * vl_twister(10,10) ;
s.Y = 4.7 * vl_twister(10,7) ;
function test_null_args(s)
vl_assert_equal(...
vl_alldist2(zeros(15,12), zeros(15,0), 'kl2'), ...
... |
github | msyamkumar/vision-panorama-master | vl_test_fisher.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_fisher.m | 2,097 | utf_8 | c9afd9ab635bd412cbf8be3c2d235f6b | function results = vl_test_fisher(varargin)
% VL_TEST_FISHER
vl_test_init ;
function s = setup()
randn('state',0) ;
dimension = 5 ;
numData = 21 ;
numComponents = 3 ;
s.x = randn(dimension,numData) ;
s.mu = randn(dimension,numComponents) ;
s.sigma2 = ones(dimension,numComponents) ;
s.prior = ones(1,numComponents) ;
s... |
github | msyamkumar/vision-panorama-master | vl_test_imsmooth.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_imsmooth.m | 1,837 | utf_8 | 718235242cad61c9804ba5e881c22f59 | function results = vl_test_imsmooth(varargin)
% VL_TEST_IMSMOOTH
vl_test_init ;
function s = setup()
I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
I = max(min(vl_imdown(I),1),0) ;
s.I = single(I) ;
function test_pad_by_continuity(s)
% Convolving a constant signal padded with continuity does not change... |
github | msyamkumar/vision-panorama-master | vl_test_svmtrain.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_svmtrain.m | 4,277 | utf_8 | 071b7c66191a22e8236fda16752b27aa | function results = vl_test_svmtrain(varargin)
% VL_TEST_SVMTRAIN
vl_test_init ;
end
function s = setup()
randn('state',0) ;
Np = 10 ;
Nn = 10 ;
xp = diag([1 3])*randn(2, Np) ;
xn = diag([1 3])*randn(2, Nn) ;
xp(1,:) = xp(1,:) + 2 + 1 ;
xn(1,:) = xn(1,:) - 2 + 1 ;
s.x = [xp xn] ;
s.y = [ones(1,Np) ... |
github | msyamkumar/vision-panorama-master | vl_test_phow.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_phow.m | 549 | utf_8 | f761a3bb218af855986263c67b2da411 | function results = vl_test_phow(varargin)
% VL_TEST_PHOPW
vl_test_init ;
function s = setup()
s.I = im2double(imread(fullfile(vl_root,'data','spots.jpg'))) ;
s.I = single(s.I) ;
function test_gray(s)
[f,d] = vl_phow(s.I, 'color', 'gray') ;
assert(size(d,1) == 128) ;
function test_rgb(s)
[f,d] = vl_phow(s.I, 'color',... |
github | msyamkumar/vision-panorama-master | vl_test_kmeans.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_kmeans.m | 3,632 | utf_8 | 0e1d6f4f8101c8982a0e743e0980c65a | function results = vl_test_kmeans(varargin)
% VL_TEST_KMEANS
% Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson.
% All rights reserved.
%
% This file is part of the VLFeat library and is made available under
% the terms of the BSD license (see the COPYING file).
vl_test_init ;
function s = setup()
randn('sta... |
github | msyamkumar/vision-panorama-master | vl_test_hikmeans.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_hikmeans.m | 463 | utf_8 | dc3b493646e66316184e86ff4e6138ab | function results = vl_test_hikmeans(varargin)
% VL_TEST_IKMEANS
vl_test_init ;
function s = setup()
rand('state',0) ;
s.data = uint8(rand(2,1000) * 255) ;
function test_basic(s)
[tree, assign] = vl_hikmeans(s.data,3,100) ;
assign_ = vl_hikmeanspush(tree, s.data) ;
vl_assert_equal(assign,assign_) ;
function test_elka... |
github | msyamkumar/vision-panorama-master | vl_test_aib.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_aib.m | 1,277 | utf_8 | 78978ae54e7ebe991d136336ba4bf9c6 | function results = vl_test_aib(varargin)
% VL_TEST_AIB
vl_test_init ;
function s = setup()
s = [] ;
function test_basic(s)
Pcx = [.3 .3 0 0
0 0 .2 .2] ;
% This results in the AIB tree
%
% 1 - \
% 5 - \
% 2 - / \
% - 7
% 3 - \ /
% 6 - /
% 4 - /
%
% coded by the map [5 ... |
github | msyamkumar/vision-panorama-master | vl_test_plotbox.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_plotbox.m | 414 | utf_8 | aa06ce4932a213fb933bbede6072b029 | function results = vl_test_plotbox(varargin)
% VL_TEST_PLOTBOX
vl_test_init ;
function test_basic(s)
figure(1) ; clf ;
vl_plotbox([-1 -1 1 1]') ;
xlim([-2 2]) ;
ylim([-2 2]) ;
close(1) ;
function test_multiple(s)
figure(1) ; clf ;
randn('state', 0) ;
vl_plotbox(randn(4,10)) ;
close(1) ;
function test_style(s)
figure... |
github | msyamkumar/vision-panorama-master | vl_test_imarray.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_imarray.m | 795 | utf_8 | c5e6a5aa8c2e63e248814f5bd89832a8 | function results = vl_test_imarray(varargin)
% VL_TEST_IMARRAY
vl_test_init ;
function test_movie_rgb(s)
A = rand(23,15,3,4) ;
B = vl_imarray(A,'movie',true) ;
function test_movie_indexed(s)
cmap = get(0,'DefaultFigureColormap') ;
A = uint8(size(cmap,1)*rand(23,15,4)) ;
A = min(A,size(cmap,1)-1) ;
B = vl_imarray(A,'m... |
github | msyamkumar/vision-panorama-master | vl_test_homkermap.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_homkermap.m | 1,903 | utf_8 | c157052bf4213793a961bde1f73fb307 | function results = vl_test_homkermap(varargin)
% VL_TEST_HOMKERMAP
vl_test_init ;
function check_ker(ker, n, window, period)
args = {n, ker, 'window', window} ;
if nargin > 3
args = {args{:}, 'period', period} ;
end
x = [-1 -.5 0 .5 1] ;
y = linspace(0,2,100) ;
for conv = {@single, @double}
x = feval(conv{1}, x) ;... |
github | msyamkumar/vision-panorama-master | vl_test_slic.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_slic.m | 200 | utf_8 | 12a6465e3ef5b4bcfd7303cd8a9229d4 | function results = vl_test_slic(varargin)
% VL_TEST_SLIC
vl_test_init ;
function s = setup()
s.im = im2single(vl_impattern('roofs1')) ;
function test_slic(s)
segmentation = vl_slic(s.im, 10, 0.1) ;
|
github | msyamkumar/vision-panorama-master | vl_test_ikmeans.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_ikmeans.m | 466 | utf_8 | 1ee2f647ac0035ed0d704a0cd615b040 | function results = vl_test_ikmeans(varargin)
% VL_TEST_IKMEANS
vl_test_init ;
function s = setup()
rand('state',0) ;
s.data = uint8(rand(2,1000) * 255) ;
function test_basic(s)
[centers, assign] = vl_ikmeans(s.data,100) ;
assign_ = vl_ikmeanspush(s.data, centers) ;
vl_assert_equal(assign,assign_) ;
function test_elk... |
github | msyamkumar/vision-panorama-master | vl_test_mser.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_mser.m | 242 | utf_8 | 1ad33563b0c86542a2978ee94e0f4a39 | function results = vl_test_mser(varargin)
% VL_TEST_MSER
vl_test_init ;
function s = setup()
s.im = im2uint8(rgb2gray(vl_impattern('roofs1'))) ;
function test_mser(s)
[regions,frames] = vl_mser(s.im) ;
mask = vl_erfill(s.im, regions(1)) ;
|
github | msyamkumar/vision-panorama-master | vl_test_inthist.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_inthist.m | 811 | utf_8 | 459027d0c54d8f197563a02ab66ef45d | function results = vl_test_inthist(varargin)
% VL_TEST_INTHIST
vl_test_init ;
function s = setup()
rand('state',0) ;
s.labels = uint32(8*rand(123, 76, 3)) ;
function test_basic(s)
l = 10 ;
hist = vl_inthist(s.labels, 'numlabels', l) ;
hist_ = inthist_slow(s.labels, l) ;
vl_assert_equal(double(hist),hist_) ;
function... |
github | msyamkumar/vision-panorama-master | vl_test_imdisttf.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_imdisttf.m | 1,885 | utf_8 | ae921197988abeb984cbcdf9eaf80e77 | function results = vl_test_imdisttf(varargin)
% VL_TEST_DISTTF
vl_test_init ;
function test_basic()
for conv = {@single, @double}
conv = conv{1} ;
I = conv([0 0 0 ; 0 -2 0 ; 0 0 0]) ;
D = vl_imdisttf(I);
assert(isequal(D, conv(- [0 1 0 ; 1 2 1 ; 0 1 0]))) ;
I(2,2) = -3 ;
[D,map] = vl_imdisttf(I) ;
asse... |
github | msyamkumar/vision-panorama-master | vl_test_vlad.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_vlad.m | 1,977 | utf_8 | d3797288d6edb1d445b890db3780c8ce | function results = vl_test_vlad(varargin)
% VL_TEST_VLAD
vl_test_init ;
function s = setup()
randn('state',0) ;
s.x = randn(128,256) ;
s.mu = randn(128,16) ;
assignments = rand(16, 256) ;
s.assignments = bsxfun(@times, assignments, 1 ./ sum(assignments,1)) ;
function test_basic (s)
x = [1, 2, 3] ;
mu = [0, 0, 0] ;
a... |
github | msyamkumar/vision-panorama-master | vl_test_pr.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_pr.m | 3,763 | utf_8 | 4d1da5ccda1a7df2bec35b8f12fdd620 | function results = vl_test_pr(varargin)
% VL_TEST_PR
vl_test_init ;
function s = setup()
s.scores0 = [5 4 3 2 1] ;
s.scores1 = [5 3 4 2 1] ;
s.labels = [1 1 -1 -1 -1] ;
function test_perfect_tptn(s)
[rc,pr] = vl_pr(s.labels,s.scores0) ;
vl_assert_almost_equal(pr, [1 1/1 2/2 2/3 2/4 2/5]) ;
vl_assert_almost_equal(rc, ... |
github | msyamkumar/vision-panorama-master | vl_test_hog.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_hog.m | 1,555 | utf_8 | eed7b2a116d142040587dc9c4eb7cd2e | function results = vl_test_hog(varargin)
% VL_TEST_HOG
vl_test_init ;
function s = setup()
s.im = im2single(vl_impattern('roofs1')) ;
[x,y]= meshgrid(linspace(-1,1,128)) ;
s.round = single(x.^2+y.^2);
s.imSmall = s.im(1:128,1:128,:) ;
s.imSmall = s.im ;
s.imSmallFlipped = s.imSmall(:,end:-1:1,:) ;
function test_basic... |
github | msyamkumar/vision-panorama-master | vl_test_argparse.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_argparse.m | 795 | utf_8 | e72185b27206d0ee1dfdc19fe77a5be6 | function results = vl_test_argparse(varargin)
% VL_TEST_ARGPARSE
vl_test_init ;
function test_basic()
opts.field1 = 1 ;
opts.field2 = 2 ;
opts.field3 = 3 ;
opts_ = opts ;
opts_.field1 = 3 ;
opts_.field2 = 10 ;
opts = vl_argparse(opts, {'field2', 10, 'field1', 3}) ;
assert(isequal(opts, opts_)) ;
opts_.field1 = 9 ;
... |
github | msyamkumar/vision-panorama-master | vl_test_liop.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_liop.m | 1,023 | utf_8 | a162be369073bed18e61210f44088cf3 | function results = vl_test_liop(varargin)
% VL_TEST_SIFT
vl_test_init ;
function s = setup()
randn('state',0) ;
s.patch = randn(65,'single') ;
xr = -32:32 ;
[x,y] = meshgrid(xr) ;
s.blob = - single(x.^2+y.^2) ;
function test_basic(s)
d = vl_liop(s.patch) ;
function test_blob(s)
% with a blob, all local intensity ord... |
github | msyamkumar/vision-panorama-master | vl_test_binsearch.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/xtest/vl_test_binsearch.m | 1,339 | utf_8 | 85dc020adce3f228fe7dfb24cf3acc63 | function results = vl_test_binsearch(varargin)
% VL_TEST_BINSEARCH
vl_test_init ;
function test_inf_bins()
x = [-inf -1 0 1 +inf] ;
vl_assert_equal(vl_binsearch([], x), [0 0 0 0 0]) ;
vl_assert_equal(vl_binsearch([-inf 0], x), [1 1 2 2 2]) ;
vl_assert_equal(vl_binsearch([-inf], x), [1 1 1 1 1]) ;
vl_a... |
github | msyamkumar/vision-panorama-master | vl_roc.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/plotop/vl_roc.m | 10,113 | utf_8 | 22fd8ff455ee62a96ffd94b9074eafeb | function [tpr,tnr,info] = vl_roc(labels, scores, varargin)
%VL_ROC ROC curve.
% [TPR,TNR] = VL_ROC(LABELS, SCORES) computes the Receiver Operating
% Characteristic (ROC) curve [1]. LABELS is a row vector of ground
% truth labels, greater than zero for a positive sample and smaller
% than zero for a negative o... |
github | msyamkumar/vision-panorama-master | vl_click.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/plotop/vl_click.m | 2,661 | utf_8 | 6982e869cf80da57fdf68f5ebcd05a86 | function P = vl_click(N,varargin) ;
% VL_CLICK Click a point
% P=VL_CLICK() let the user click a point in the current figure and
% returns its coordinates in P. P is a two dimensiona vectors where
% P(1) is the point X-coordinate and P(2) the point Y-coordinate. The
% user can abort the operation by pressing any k... |
github | msyamkumar/vision-panorama-master | vl_pr.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/plotop/vl_pr.m | 9,138 | utf_8 | c7fe6832d2b6b9917896810c52a05479 | function [recall, precision, info] = vl_pr(labels, scores, varargin)
%VL_PR Precision-recall curve.
% [RECALL, PRECISION] = VL_PR(LABELS, SCORES) computes the
% precision-recall (PR) curve. LABELS are the ground truth labels,
% greather than zero for a positive sample and smaller than zero for
% a negative on... |
github | msyamkumar/vision-panorama-master | vl_ubcread.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/sift/vl_ubcread.m | 3,015 | utf_8 | e8ddd3ecd87e76b6c738ba153fef050f | function [f,d] = vl_ubcread(file, varargin)
% SIFTREAD Read Lowe's SIFT implementation data files
% [F,D] = VL_UBCREAD(FILE) reads the frames F and the descriptors D
% from FILE in UBC (Lowe's original implementation of SIFT) format
% and returns F and D as defined by VL_SIFT().
%
% VL_UBCREAD(FILE, 'FORMAT', '... |
github | msyamkumar/vision-panorama-master | vl_frame2oell.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/sift/vl_frame2oell.m | 2,806 | utf_8 | c93792632f630743485fa4c2cf12d647 | function eframes = vl_frame2oell(frames)
% VL_FRAMES2OELL Convert a geometric frame to an oriented ellipse
% EFRAME = VL_FRAME2OELL(FRAME) converts the generic FRAME to an
% oriented ellipses EFRAME. FRAME and EFRAME can be matrices, with
% one frame per column.
%
% A frame is either a point, a disc, an orien... |
github | msyamkumar/vision-panorama-master | vl_plotsiftdescriptor.m | .m | vision-panorama-master/vlfeat-0.9.20/toolbox/sift/vl_plotsiftdescriptor.m | 5,114 | utf_8 | a4e125a8916653f00143b61cceda2f23 | function h=vl_plotsiftdescriptor(d,f,varargin)
% VL_PLOTSIFTDESCRIPTOR Plot SIFT descriptor
% VL_PLOTSIFTDESCRIPTOR(D) plots the SIFT descriptor D. If D is a
% matrix, it plots one descriptor per column. D has the same format
% used by VL_SIFT().
%
% VL_PLOTSIFTDESCRIPTOR(D,F) plots the SIFT descriptors warpe... |
github | msyamkumar/vision-panorama-master | phow_caltech101.m | .m | vision-panorama-master/vlfeat-0.9.20/apps/phow_caltech101.m | 11,594 | utf_8 | 7f4890a2e6844ca56debbfe23cca64f3 | function phow_caltech101()
% PHOW_CALTECH101 Image classification in the Caltech-101 dataset
% This program demonstrates how to use VLFeat to construct an image
% classifier on the Caltech-101 data. The classifier uses PHOW
% features (dense SIFT), spatial histograms of visual words, and a
% Chi2 SVM. To speedu... |
github | msyamkumar/vision-panorama-master | sift_mosaic.m | .m | vision-panorama-master/vlfeat-0.9.20/apps/sift_mosaic.m | 4,621 | utf_8 | 8fa3ad91b401b8f2400fb65944c79712 | function mosaic = sift_mosaic(im1, im2)
% SIFT_MOSAIC Demonstrates matching two images using SIFT and RANSAC
%
% SIFT_MOSAIC demonstrates matching two images based on SIFT
% features and RANSAC and computing their mosaic.
%
% SIFT_MOSAIC by itself runs the algorithm on two standard test
% images. Use SIFT_MOSAI... |
github | msyamkumar/vision-panorama-master | encodeImage.m | .m | vision-panorama-master/vlfeat-0.9.20/apps/recognition/encodeImage.m | 5,278 | utf_8 | 5d9dc6161995b8e10366b5649bf4fda4 | function descrs = encodeImage(encoder, im, varargin)
% ENCODEIMAGE Apply an encoder to an image
% DESCRS = ENCODEIMAGE(ENCODER, IM) applies the ENCODER
% to image IM, returning a corresponding code vector PSI.
%
% IM can be an image, the path to an image, or a cell array of
% the same, to operate on multiple ... |
github | msyamkumar/vision-panorama-master | experiments.m | .m | vision-panorama-master/vlfeat-0.9.20/apps/recognition/experiments.m | 6,905 | utf_8 | 1e4a4911eed4a451b9488b9e6cc9b39c | function experiments()
% EXPERIMENTS Run image classification experiments
% The experimens download a number of benchmark datasets in the
% 'data/' subfolder. Make sure that there are several GBs of
% space available.
%
% By default, experiments run with a lite option turned on. This
% quickly runs all... |
github | msyamkumar/vision-panorama-master | getDenseSIFT.m | .m | vision-panorama-master/vlfeat-0.9.20/apps/recognition/getDenseSIFT.m | 1,679 | utf_8 | 2059c0a2a4e762226d89121408c6e51c | function features = getDenseSIFT(im, varargin)
% GETDENSESIFT Extract dense SIFT features
% FEATURES = GETDENSESIFT(IM) extract dense SIFT features from
% image IM.
% Author: Andrea Vedaldi
% Copyright (C) 2013 Andrea Vedaldi
% All rights reserved.
%
% This file is part of the VLFeat library and is made availab... |
github | michaelcrawley/Processing_Codes-master | Work4Cat5Prob1v2.m | .m | Processing_Codes-master/MATLAB/Projects/LEE/Work4Cat5Prob1v2.m | 6,997 | utf_8 | 0dda86e24f1e247a3da09485ba68808b | function [grab,X,Y,t] = Work4Cat5Prob1v2(dx)
%Linearized Euler Equation solver for NASA ICASE_LaRC CAA Workshop 4, benchmark Category 5, Problem 1
%Version 2 uses dimensional variables, unlike version 1
%Inputs: dx: non-dimensionalized grid spacing (axial and radial spacings will be equal)
%Constants
h... |
github | michaelcrawley/Processing_Codes-master | Work4Cat5Prob1.m | .m | Processing_Codes-master/MATLAB/Projects/LEE/Work4Cat5Prob1.m | 6,843 | utf_8 | 1e63b7d05b9b046169cbc00a11b94080 | function [grab,X,Y] = Work4Cat5Prob1(dx)
%Linearized Euler Equation solver for NASA ICASE_LaRC CAA Workshop 4, benchmark Category 5, Problem 1
%Inputs: dx: normalized grid spacing (axial and radial spacings will be equal)
%Constants
h = 0;
b = 1.3;
Rhalf = h+b;
T_amb = 300;
Tj = 600; %R... |
github | michaelcrawley/Processing_Codes-master | NF_Average_v3.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/NF_Average_v3.m | 13,700 | utf_8 | 9c51510c721c23b9cecdc4d6d24258f2 | function NF_Average_v3(src_dir,flist,out_dir,savename,cal_dir,params)
%Function acts as an initial processing routine for nearfield/farfield
%acoustic data with trigger signal. Function computes the averaged waveform
%for each channel and then filters this averaged waveform to remove the
%actuator self noise. Outputs a... |
github | michaelcrawley/Processing_Codes-master | WaveletFilterEnergyRatio.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/WaveletFilterEnergyRatio.m | 1,901 | utf_8 | 2c90ad60b7e30d7248ec29ed352fe95f | function [ER,alpha] = WaveletFilterEnergyRatio(sig,dt,mother,param,J,da,amax)
if ~exist('mother','var') || isempty(mother), mother = 'morlet'; end %mother wavelet
if ~exist('param','var'), param = []; end %wavelet parameter
if ~exist('J','var') || isempty(J), J = 300; end %number of wavelet scales
... |
github | michaelcrawley/Processing_Codes-master | Wavelet_Decompose2DInst_V3.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/Wavelet_Decompose2DInst_V3.m | 9,054 | utf_8 | 6db859b948be75c6a4efad75102950ca | function Wavelet_Decompose2DInst_V3(src_dir,flist,out_dir,a,windowfun,flag,cpus)
tic;
%Constants
if ~exist('windowfun','var')||isempty(windowfun), windowfun = @rectwin; end
if ~exist('flag','var')||isempty(flag), flag = 'pblocks.smp'; end
if ~exist('cpus','var')||isempty(cpus), cpus = 1; end
... |
github | michaelcrawley/Processing_Codes-master | Wavelet_Decompose2DInst_V4_unfinished.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/Wavelet_Decompose2DInst_V4_unfinished.m | 6,857 | utf_8 | 5905a31373012fa67c0717e1a1cdadaa | function Wavelet_Decompose2DInst_V4(src_dir,flist,out_dir,a,flag,cpus)
%Computes STCWT in the physical domain, whereas V3 computed in the Fourier
%domain!
tic;
%Constants
if ~exist('flag','var')||isempty(flag), flag = 'pblocks.p'; end
if ~exist('cpus','var')||isempty(cpus), cpus = 1; end
%Para... |
github | michaelcrawley/Processing_Codes-master | FilterSignal.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/FilterSignal.m | 11,455 | utf_8 | 9307d1ee34ab48757e077bd8cd577588 | function FilterSignal(src_dir,flist,cal_dir,out_dir)
%this is a test function, the purpose of which is to filter out the
%actuator self noise of the nearfield microphone signals before
%phase-averaging (as opposed to the previous method where it was done
%afterwards).
%Temporary Constants
p... |
github | michaelcrawley/Processing_Codes-master | contwt.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/contwt.m | 5,661 | utf_8 | d71a1e92d5b07c0cf9905438d8accab8 | %WAVELET 1D Wavelet transform with optional singificance testing
%
% [WAVE,PERIOD,SCALE,COI,DJ, PARAMOUT, K] = contwt(Y,DT,PAD,DJ,S0,J1,MOTHER,PARAM)
%
% Computes the continuous wavelet transform of the vector Y (length N),
% with sampling rate DT.
%
% By default, the Morlet wavelet (k0=6) is used.
% The wav... |
github | michaelcrawley/Processing_Codes-master | NF_Average_v2.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/NF_Average_v2.m | 11,600 | utf_8 | 92817955404f22454d24f92b596a6886 | function NF_Average_v2(src_dir,flist,out_dir,savename,cal_dir,params)
%Function acts as an initial processing routine for nearfield/farfield
%acoustic data with trigger signal. Function computes the averaged waveform
%for each channel and then filters this averaged waveform to remove the
%actuator self noise. Outputs a... |
github | michaelcrawley/Processing_Codes-master | iSubBlocks_EXP.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/iSubBlocks_EXP.m | 2,985 | utf_8 | 35a069e6f4f87e6363bd83a7db8f014b | function [output a_indices] = iSubBlocks_EXP(signal,trigger,pp,offset)
%Identifies forcing indices and reshapes signal into forcing-blocks,
%rather than acquisition blocks. Nresample is the resample ratio (i.e.
%for a physical sample rate of 200 kHz and Nresample = 10, the data is
%resampled at 2 MHz). ... |
github | michaelcrawley/Processing_Codes-master | NF_PreprocessingTMP.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/NF_PreprocessingTMP.m | 14,459 | utf_8 | 492bd1467f2449e4ecd1d26f755ea6dc | function NF_PreprocessingTMP(src_dir,flist,cal_dir,out_dir,cpus)
%This is a test function, the purpose of which is to preprocess the
%data files. For the forced cases, it will filter out the
%actuator self noise of the nearfield microphone signals before
%phase-averaging (as opposed to the previous met... |
github | michaelcrawley/Processing_Codes-master | Wavelet_Decompose2DInst_V4_2_unfinished.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/Wavelet_Decompose2DInst_V4_2_unfinished.m | 8,881 | utf_8 | b471ec4a1e064826a73508723ac87482 | function Wavelet_Decompose2DInst_V4_2(src_dir,flist,out_dir,a,flag,cpus)
%Computes STCWT in the physical domain, whereas V3 computed in the Fourier
%domain! In this code, the wavelet filter is first computed in the Fourier
%domain, and then transformed into the physical domain.
tic;
%Constants
if ~exist('fl... |
github | michaelcrawley/Processing_Codes-master | Wavelet_Decompose2DInst_V2.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/Wavelet_Decompose2DInst_V2.m | 8,569 | utf_8 | 33e4f00c2c804acc0f2d80aa6f615c3e | function Wavelet_Decompose2DInst_V2(src_dir,flist,out_dir,a,windowfun,flag,cpus)
%Constants
if ~exist('windowfun','var')||isempty(windowfun), windowfun = @tukeywin; end
if ~exist('flag','var')||isempty(flag), flag = 'pblocks.p'; end
if ~exist('cpus','var')||isempty(cpus), cpus = 1; end
%Parame... |
github | michaelcrawley/Processing_Codes-master | Wavelet_Decompose2DInst_V4.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/Wavelet_Decompose2DInst_V4.m | 10,960 | utf_8 | 191ab6eb8e1eb48f6eaa9d2e22ca4d50 | function Wavelet_Decompose2DInst_V4(src_dir,flist,out_dir,optset,cpus)
tic;
%Set options
if ~exist('optset','var'), optset = []; end
if ~isfield(optset,'windowfun'), optset.windowfun = @rectwin; end
if ~isfield(optset,'flag'), optset.flag = 'pblocks.smp'; end
if ~isfield(optset,'mot... |
github | michaelcrawley/Processing_Codes-master | NF_Average.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/NF_Average.m | 11,446 | utf_8 | d31de5575b1ae1e17fc8dd24d5f80ed2 | function NF_Average(src_dir,flist,out_dir,savename,cal_dir)
%Function acts as an initial processing routine for nearfield/farfield
%acoustic data with trigger signal. Function computes the averaged waveform
%for each channel and then filters this averaged waveform to remove the
%actuator self noise. Outputs are saved i... |
github | michaelcrawley/Processing_Codes-master | wave_bases.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/wave_bases.m | 3,095 | utf_8 | 0748b4ea4f9a7481bb57b9e453ecba6c | %WAVE_BASES 1D Wavelet functions Morlet, Paul, or DOG
%
% [DAUGHTER,FOURIER_FACTOR,COI,DOFMIN, PARAMOUT] = ...
% wave_bases(MOTHER,K,SCALE,PARAM);
%
% Computes the wavelet function as a function of Fourier frequency,
% used for the wavelet transform in Fourier space.
% (This program is called automatically... |
github | michaelcrawley/Processing_Codes-master | Wavelet_Decompose2DInst_V15_unfinished.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/Wavelet_Decompose2DInst_V15_unfinished.m | 8,775 | utf_8 | 019debc42a384f7c6e3a0028a3adbbbb | function Wavelet_Decompose2DInst_V15(src_dir,flist,out_dir,a,windowfun,flag,cpus)
%Constants
if ~exist('windowfun','var')||isempty(windowfun), windowfun = @tukeywin; end
if ~exist('flag','var')||isempty(flag), flag = 'pblocks.p'; end
if ~exist('cpus','var')||isempty(cpus), cpus = 1; end
%Param... |
github | michaelcrawley/Processing_Codes-master | NF_Preprocessing_Addendum.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/NF_Preprocessing_Addendum.m | 3,018 | utf_8 | b4dcb0be2ab25c7412017979636b5754 | function NF_Preprocessing_Addendum(proc_dir,src_dir,flist,params)
%Constants
load(params,'pp');
pp.NCh = length([pp.NFCh pp.FFCh])+1;
for n = 1:length(flist)
data = load([proc_dir filesep flist{n}]);
trigger.sig = ReadTrigger(src_dir,data.filename,pp);
if data.phys... |
github | michaelcrawley/Processing_Codes-master | Wavelet_Decompose2DInst_VLES.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/Wavelet_Decompose2DInst_VLES.m | 10,992 | utf_8 | c41f0a29b0144399d4887c4819f25429 | function Wavelet_Decompose2DInst_VLES(src_dir,flist,out_dir,optset,cpus)
tic;
%Set options
if ~exist('optset','var'), optset = []; end
if ~isfield(optset,'window'), optset.windowfun = @rectwin; end
if ~isfield(optset,'flag'), optset.flag = 'pblocks.smp'; end
if ~isfield(optset,'moth... |
github | michaelcrawley/Processing_Codes-master | NF_Preprocessing.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/NF_Preprocessing.m | 15,817 | utf_8 | aadad2f0cde117250089e8610b843e99 | function NF_Preprocessing(src_dir,flist,cal_dir,out_dir,params,cpus)
%This is a test function, the purpose of which is to preprocess the
%data files. For the forced cases, it will filter out the
%actuator self noise of the nearfield microphone signals before
%phase-averaging (as opposed to the previous... |
github | michaelcrawley/Processing_Codes-master | NF_Preprocessing_EXP.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/NF_Preprocessing_EXP.m | 15,445 | utf_8 | 8ae9e3b870d5f5fe85ef13b9a688a119 | function NF_Preprocessing_EXP(src_dir,flist,cal_dir,out_dir,cpus)
%This is an experimental function, the purpose of which is to preprocess the
%data files. For the forced cases, it will filter out the
%actuator self noise of the nearfield microphone signals before
%phase-averaging (as opposed to the pr... |
github | michaelcrawley/Processing_Codes-master | NF_Preprocessing_old.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/Old/NF_Preprocessing_old.m | 16,729 | utf_8 | cf803fe5286118e812d3087a23bfaadf | function NF_Preprocessing(src_dir,flist,cal_dir,out_dir,params,cpus)
%This is a test function, the purpose of which is to preprocess the
%data files. For the forced cases, it will filter out the
%actuator self noise of the nearfield microphone signals before
%phase-averaging (as opposed to the previous... |
github | michaelcrawley/Processing_Codes-master | contwt.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/ani_data_code/All Codes/contwt.m | 5,692 | utf_8 | 67fec3bdc78b5bb8b77dffee7bbf6282 | %WAVELET 1D Wavelet transform with optional singificance testing
%
% [WAVE,PERIOD,SCALE,COI,DJ, PARAMOUT, K] = contwt(Y,DT,PAD,DJ,S0,J1,MOTHER,PARAM)
%
% Computes the continuous wavelet transform of the vector Y (length N),
% with sampling rate DT.
%
% By default, the Morlet wavelet (k0=6) is used.
% The wav... |
github | michaelcrawley/Processing_Codes-master | wave_bases.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/ani_data_code/All Codes/wave_bases.m | 3,095 | utf_8 | 0748b4ea4f9a7481bb57b9e453ecba6c | %WAVE_BASES 1D Wavelet functions Morlet, Paul, or DOG
%
% [DAUGHTER,FOURIER_FACTOR,COI,DOFMIN, PARAMOUT] = ...
% wave_bases(MOTHER,K,SCALE,PARAM);
%
% Computes the wavelet function as a function of Fourier frequency,
% used for the wavelet transform in Fourier space.
% (This program is called automatically... |
github | michaelcrawley/Processing_Codes-master | parse_pressure_fname.m | .m | Processing_Codes-master/MATLAB/Projects/Nearfield Pressure/ani_data_code/All Codes/parse_pressure_fname.m | 4,793 | utf_8 | 329f72cfd970644d83f8c3d059521a24 | function info = parse_pressure_fname(fname_w_ext,M_j,D,info_in)
% Parsing a filename like
% 'M0.9_m(00)(00)_F0.00_PW0.0_T19.5_IA00_On00000_R00.NOS'
% OR
% 'M0.9_m(00)(00)_F2.02_PWAUH_T16.3_IA00_On00255_R00.NOS'
% Parsing a filename like 'M13_X01_R1p09_WF_m00_F2.10_DAUH_T12.9.lvm'.
% Mach #,
%... |
github | michaelcrawley/Processing_Codes-master | iSTCWT1D_old.m | .m | Processing_Codes-master/MATLAB/Projects/Wavelet Transform/iSTCWT1D_old.m | 1,815 | utf_8 | f9f31ad1710d4fd8710a3f2f9387f821 | function [xn] = iSTCWT1D(wave,scales,omegaks,mother,param)
%Integrate over scales - take real part only
wave = real(wave);
N = size(wave);
[a,c] = meshgrid(scales{2},scales{1}); %meshgrid assumes inputs are DIM2,DIM1
a = repmat(a,[1 1 N(3:4)]);
c = repmat(c,[1 1 N(3:4)]);
wave = wave./a./... |
github | michaelcrawley/Processing_Codes-master | iCWT2D.m | .m | Processing_Codes-master/MATLAB/Projects/Wavelet Transform/iCWT2D.m | 1,227 | utf_8 | 16f48cb32754b7019ecbe34a40e6e9ee | function [xn] = iCWT2D(wave,scale,omegak,mother,param)
%Grab mother wavelet
mother = wavebases(mother,param);
%Take real part of wavelet coefficients, normalize by scales, and sum
N = size(wave);
wave = real(wave);
[S2,S1] = meshgrid(sqrt(scale{2}),sqrt(scale{1}));
S1 = repmat(S1,[1 1, N(3... |
github | michaelcrawley/Processing_Codes-master | STCWT2D.m | .m | Processing_Codes-master/MATLAB/Projects/Wavelet Transform/STCWT2D.m | 1,596 | utf_8 | 86d88b5f11cde2f87048072bf6ab6553 | function [wave,s,c] = STCWT2D(sig,dt,dx,dj,dq,mother,param)
%Computes 1-Dimensional Continuous Wavelet Transform using Fourier method.
%%%%%%%%%%%%%%%%[UNFINISHED]%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Inputs:
% sig: signal (M,N)
% dt: period between M-samples
% dx... |
github | michaelcrawley/Processing_Codes-master | CWT2D.m | .m | Processing_Codes-master/MATLAB/Projects/Wavelet Transform/CWT2D.m | 2,294 | utf_8 | ae5e15f02b9a6120d8ea07afb50d5337 | function [wave,freq,s,omegak] = CWT2D(sig,dt,dj,mother,param)
%Computes 2-Dimensional Continuous Wavelet Transform using Fourier method.
%Inputs:
% x: signal (M,N)
% dt: period between samples (2,1)
% dq: scale spacings (2,1)
% mother: mother wavelet ... |
github | michaelcrawley/Processing_Codes-master | contwt.m | .m | Processing_Codes-master/MATLAB/Projects/Wavelet Transform/contwt.m | 5,661 | utf_8 | d71a1e92d5b07c0cf9905438d8accab8 | %WAVELET 1D Wavelet transform with optional singificance testing
%
% [WAVE,PERIOD,SCALE,COI,DJ, PARAMOUT, K] = contwt(Y,DT,PAD,DJ,S0,J1,MOTHER,PARAM)
%
% Computes the continuous wavelet transform of the vector Y (length N),
% with sampling rate DT.
%
% By default, the Morlet wavelet (k0=6) is used.
% The wav... |
github | michaelcrawley/Processing_Codes-master | STCWT1D_old.m | .m | Processing_Codes-master/MATLAB/Projects/Wavelet Transform/STCWT1D_old.m | 3,563 | utf_8 | 3d31e6d4c16091730f73755706c1369d | function [wave,scales,omegaks] = STCWT1D(sig,dt,dj,whan,ca,mother,param)
%Computes (1+1)-Dimensional Spatio-Temporal Continuous Wavelet Transform
%using Fourier method. Based off of Kikuchi 2010.
%Inputs:
% sig: signal (M,N), where DIM1 is time
% dt: period between samples (2,1)
% ... |
github | michaelcrawley/Processing_Codes-master | wave_bases.m | .m | Processing_Codes-master/MATLAB/Projects/Wavelet Transform/wave_bases.m | 3,095 | utf_8 | 0748b4ea4f9a7481bb57b9e453ecba6c | %WAVE_BASES 1D Wavelet functions Morlet, Paul, or DOG
%
% [DAUGHTER,FOURIER_FACTOR,COI,DOFMIN, PARAMOUT] = ...
% wave_bases(MOTHER,K,SCALE,PARAM);
%
% Computes the wavelet function as a function of Fourier frequency,
% used for the wavelet transform in Fourier space.
% (This program is called automatically... |
github | michaelcrawley/Processing_Codes-master | parse_pressure_fname.m | .m | Processing_Codes-master/MATLAB/Projects/Wavelet Transform/parse_pressure_fname.m | 4,793 | utf_8 | 329f72cfd970644d83f8c3d059521a24 | function info = parse_pressure_fname(fname_w_ext,M_j,D,info_in)
% Parsing a filename like
% 'M0.9_m(00)(00)_F0.00_PW0.0_T19.5_IA00_On00000_R00.NOS'
% OR
% 'M0.9_m(00)(00)_F2.02_PWAUH_T16.3_IA00_On00255_R00.NOS'
% Parsing a filename like 'M13_X01_R1p09_WF_m00_F2.10_DAUH_T12.9.lvm'.
% Mach #,
%... |
github | michaelcrawley/Processing_Codes-master | Process_AoAS_Sweep.m | .m | Processing_Codes-master/MATLAB/Projects/Aerodynamic Characterization/Process_AoAS_Sweep.m | 9,357 | utf_8 | 29c8ec35195bf8e4c042ef6c58f57056 | function aero = Process_AoAS_Sweep(src,params)
%%%%%%%%%% Necessary fields for params struct
% Velocity Wind tunnel velocity (m/s)
% loadcell type of load cell used, and orientation
% Area Reference Surface Area
% Chord Reference Chord length
% span Reference Spa... |
github | michaelcrawley/Processing_Codes-master | deriv.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Zhuang/3D/deriv.m | 633 | utf_8 | ef21d099a50c74f207ff5a710ecf9112 | %=================================
function dz=deriv(y,z,alpha,c,m,nmode)
% y - independent variable
% z - dependent variable
% alpha - complex wave number
% c = omega/alpha
% dz = dz/dy at y
dz=zeros(4,1);
[u,u1]=u_sub(y);
[tep,tep1]=t_sub(y,m);
cmc=u-c;
dz(1)=z(2);
dz(2)=(2*u1/cmc-tep1/tep-1./... |
github | michaelcrawley/Processing_Codes-master | RKF45.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Zhuang/3D/RKF45.m | 4,612 | utf_8 | 308f244cabe364bfae68b74f20f5f500 | function [z,y]=RKF45(z1,ystart,yend,abserr,alpha,c,m,nmode)
% this code integrates a system of first order ordinary diferential
% equations by runge-kutta-fehberg-45 method with automatic estimation
% of local error and step size adjustment.
% number of equations in the ODE system = size of z1.
%
% [input]
% ... |
github | michaelcrawley/Processing_Codes-master | comp.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Zhuang/3D/comp.m | 6,292 | utf_8 | 86681ebb8d2d68c2db06b1fab5cf41fa | % This code is about inviscid compressible disturbance solution
% search for complex eigenvalue alpha for specified range of real omg
% For axisymmetric jet flow
%==========summary of computation process==================================
% There are a range of real omg(s)
% For every omg, search for the righ... |
github | michaelcrawley/Processing_Codes-master | incom_huerre.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Zhuang/2D/incom_huerre.m | 4,860 | utf_8 | 4b3d3f9f3fee99394a7e9867b8580088 | % This code is to verify results in Prof. Koochesfahani's paper
% incom-huerre.m --- inviscid incompressible disturbance solution
% search for complex eigenvalue alpha for specified range of real omg
%==========summary of computation process==================================
% There are a range of real omg(s)
%... |
github | michaelcrawley/Processing_Codes-master | RKF45.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Zhuang/2D/RKF45.m | 4,124 | utf_8 | 821b84a0ecead98188afe3c308fa2bb0 |
function [z,y]=RKF45(z1,ystart,yend,abserr,alpha,c)
% this code integrates a system of first order ordinary diferential
% equations by runge-kutta-fehberg-45 method with automatic estimation
% of local error and step size adjustment.
% number of equations in the ODE system = size of z1.
%
% [input]
% z1 - ... |
github | michaelcrawley/Processing_Codes-master | AxiJetTv1.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Rel/3D/AxiJetTv1.m | 6,745 | utf_8 | 58110d6982442daeab903fe92c755a1b | function [] = AxiJetTv1(m,nmode,omgR,alph,Rt,tr,savedir)
%Inputs:
%m: Mach number
%nmode: Azimuthal mode
%omgR: Omega range
%alph: Initial guess for alpha
%Rt: R/theta
%tr: temperature ratio (T_infinity/T_jet)
version = 'T.1.6.0.0';
tic;
i = 1;
filecheck = 1;
filename = ... |
github | michaelcrawley/Processing_Codes-master | AxiJetVv1.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Rel/3D/AxiJetVv1.m | 7,439 | utf_8 | 2256526939847da5e696ef1f94af36a6 | function [] = AxiJetVv1(m,nmode,omgR,alph,Rt,tr,savedir)
%Inputs:
%m: Mach number
%nmode: Azimuthal mode
%omgR: Omega range
%alph: Initial guess for alpha
%Rt: R/theta
%tr: temperature ratio (T_infinity/T_jet)
version = 'V.1.2.2';
tic;
i = 1;
filecheck = 1;
filename = st... |
github | michaelcrawley/Processing_Codes-master | temp.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Dev/3D/temp.m | 5,211 | utf_8 | c252903ab9c64eb89589e8e2941541aa | function [master] = temp(m,nmode,omgR,alph,Rt,tr)
%Inputs:
%m: Mach number
%nmode: Azimuthal mode
%omgR: Omega range
%alph: Initial guess for alpha
%Rt: R/theta
%tr: temperature ratio (T_infinity/T_jet)
%Velocity Profile
U = @(y,Rt) 0.5*(1+tanh(0.25*Rt*(1./y-y)));
%Temperatu... |
github | michaelcrawley/Processing_Codes-master | AxiJet.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Dev/3D/AxiJet.m | 7,010 | utf_8 | b9beb43ac3a685496da638f70af174dc | function [] = AxiJet(m,nmode,omgR,alph,Rt,tr)
%Inputs:
%m: Mach number
%nmode: Azimuthal mode
%omgR: Omega range
%alph: Initial guess for alpha
%Rt: R/theta
%tr: temperature ratio (T_infinity/T_jet)
direct = 'Z:\My Documents\Matlab\Instability Analysis\';
version = 1.0;
tic;
... |
github | michaelcrawley/Processing_Codes-master | comp2.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Dev/3D/comp2.m | 12,240 | utf_8 | b3408aea702361dd1fee56e63477cf7c | function [pomg,palphr,palphi, zreal, zimag, ysave] = comp2(m,nmode, omgall,alph,Rt,tr,omega)
%Inputs: Jet Mach number u_j/a_infity, nmode azimuthal mode, frequency range (omg), initial guessed alph
% This code is about inviscid compressible disturbance solution
% search for complex eigenvalue alpha for specified r... |
github | michaelcrawley/Processing_Codes-master | xLST.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Dev/3D/xLST/xLST.m | 16,995 | utf_8 | d11844912e84e19e402a05dd34188214 | function [data] = xLST(m,nmode,tr,omega,ialpha,x,y,U, varargin)
%This code performs spatial linear stability theory calculations on PIV
%data throughout the entire domain. A curvefitting routine is used on
%the PIV data to calculate R/theta at each streamwise location, which
%is then passed to the LST ... |
github | michaelcrawley/Processing_Codes-master | LST.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Dev/3D/xLST/Trash/LST.m | 3,615 | utf_8 | 2dafdaede4fa42a07a8871098173a975 | function [alpha,phi] = LST(m,nmode,Rt,tr,omega,ialpha)
%Analysis based on Spatial Linear Stability Theory, for Axisymmetric
%Jet Flow. This code uses curve fitted data.
%inputs:
%m: Mach Number
%nmode: Azimuthal Mode
%Rt: R/theta
%tr: Temperature Ratio
%omega: angular frequency
%ial... |
github | michaelcrawley/Processing_Codes-master | LSTv3.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Dev/3D/xLST/Trash/LSTv3.m | 3,692 | utf_8 | 148d0e21121be492a2701a625c7f5b97 | function [alpha,phi] = LSTv3(m,nmode,tau,A,tr,omega,ialpha)
%Analysis based on Spatial Linear Stability Theory, for Axisymmetric
%Jet Flow. This code uses curve fitted data.
%inputs:
%m: Mach Number
%nmode: Azimuthal Mode
%Rt: R/theta
%tr: Temperature Ratio
%omega: angular frequency
... |
github | michaelcrawley/Processing_Codes-master | LSTv2.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Dev/3D/xLST/Trash/LSTv2.m | 3,766 | utf_8 | cee6ce6891e9418d91256ea70ba9c1aa | function [alpha,phi] = LSTv2(m,nmode,tr,Ufun,Uparams,U1fun,U1params,yPIV,omega,ialpha)
%Analysis based on Spatial Linear Stability Theory, for Axisymmetric
%Jet Flow. This code uses PIV data for the velocity profile.
%inputs:
%m: Mach Number
%nmode: Azimuthal Mode
%tr: Temperature Ratio
%U: ... |
github | michaelcrawley/Processing_Codes-master | LSTv1.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Dev/3D/xLST/Trash/Newton-Raphson/LSTv1.m | 3,682 | utf_8 | 437ac1dbb05b66cc086d100132c2ab9e | function [talpha phi] = LSTv1(m,nmode,omega,alph,Rt,tr)
%Inputs:
%m: Mach number
%nmode: Azimuthal mode
%omgR: Omega range
%alph: Initial guess for alpha
%Rt: R/theta
%tr: temperature ratio (T_infinity/T_jet)
%version = T.1.0.0.0;
%Velocity Profile
U = @(y,Rt) 0.5*(1+tanh(0.2... |
github | michaelcrawley/Processing_Codes-master | xLST.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Dev/3D/xLST/Trash/Nelder-Mead/xLST.m | 7,226 | utf_8 | 33ca158594105423628535bb41645e57 | function[] = xLST(m,nmode,tr,omega,ialpha,x,y,U, varargin)
%This code performs spatial linear stability theory calculations on PIV
%data throughout the entire domain. A curvefitting routine is used on
%the PIV data to calculate R/theta at each streamwise location, which
%is then passed to the LST funct... |
github | michaelcrawley/Processing_Codes-master | incom_huerre.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Dev/2D/incom_huerre.m | 5,361 | utf_8 | ca55397ebe1773b4c6a038b9bc3a6a6c | % This code is to verify results in Prof. Koochesfahani's paper
% incom-huerre.m --- inviscid incompressible disturbance solution
% search for complex eigenvalue alpha for specified range of real omg
%==========summary of computation process==================================
% There are a range of real omg(s)
%... |
github | michaelcrawley/Processing_Codes-master | RKF45.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Dev/2D/RKF45.m | 4,124 | utf_8 | 821b84a0ecead98188afe3c308fa2bb0 |
function [z,y]=RKF45(z1,ystart,yend,abserr,alpha,c)
% this code integrates a system of first order ordinary diferential
% equations by runge-kutta-fehberg-45 method with automatic estimation
% of local error and step size adjustment.
% number of equations in the ODE system = size of z1.
%
% [input]
% z1 - ... |
github | michaelcrawley/Processing_Codes-master | PlanarShearLayer.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Dev/2D/PlanarShearLayer.m | 3,489 | utf_8 | ca51ac3a29c84d7c84b8ff3477f7be13 | function [master] = PlanarShearLayer(omgR,alph,L,W)
l = length(omgR);
y1 = -8;%Define range for velocity profile
y2 = 8;
itrmax = 100; %Max iterations to find alpha
tol=1.e-5; %tolerance for found alpha
abserr=1.e-5;%tolerance for ode solver
talpha = zeros(size(omgR));
mul... |
github | michaelcrawley/Processing_Codes-master | mNumericalDerivative2.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Dev/Direct/Shear layer/mNumericalDerivative2.m | 4,582 | utf_8 | cac03f8ad0388574ca2a9575e48c60d0 | function [coefm] = mNumericalDerivative2(Dorder, Horder, h, N, varargin)
%Generate matrix to numerically derivate matrix given constant step size
%Code Version: 1.0 @ 2011-03-04
%This is not complete; DRP scheme is only available for central
%differencing
%Inputs:
% Dorder: Derivative Order
... |
github | michaelcrawley/Processing_Codes-master | AxiJetv1.m | .m | Processing_Codes-master/MATLAB/Projects/Instability Analysis/Old/AxiJetv1.m | 7,433 | utf_8 | 258688ff27a98096c1639172507b58a8 | function [] = AxiJetv1(m,nmode,omgR,alph,Rt,tr,savedir)
%Inputs:
%m: Mach number
%nmode: Azimuthal mode
%omgR: Omega range
%alph: Initial guess for alpha
%Rt: R/theta
%tr: temperature ratio (T_infinity/T_jet)
version = 1.21;
tic;
i = 1;
filecheck = 1;
filename = strcat(s... |
github | michaelcrawley/Processing_Codes-master | micOrientationCorrect.m | .m | Processing_Codes-master/MATLAB/Old/Old (Martin)/SoundProcessing/micOrientationCorrect.m | 6,318 | utf_8 | df87d21595937ba6371a9defc9d5bd8f | function CA = micOrientationCorrect(F, th, A)
%This program corrects spectra for microphone orientation based on the
%value given in the vector "th" in degrees. Normal microphone incidence is
%indicated by th==0.
%Correction is based on the difference in dB between the response at 0
%angle incidence as compared to one... |
github | michaelcrawley/Processing_Codes-master | NormDistance.m | .m | Processing_Codes-master/MATLAB/Old/Old (Martin)/SoundProcessing/NormDistance.m | 3,951 | utf_8 | fcb242f7b8be783fa983fd5d922832fc | function [Aout, al, ph] = NormDistance(varargin)
%Corrects acoustic results for distance based on noise source location or
%simple radial propagation depending on inputs. The noise source location
%calculation is at the end of this file.
%
%CALLS
% [Aout, al, ph] = NormDistance(A,Std,R,ChPol,NormD,dBShift)
% - Co... |
github | michaelcrawley/Processing_Codes-master | micOrientationCorrect.m | .m | Processing_Codes-master/MATLAB/Old/Acoustics/micOrientationCorrect.m | 6,281 | utf_8 | f27deb5bb8a14e4728bbfb649cedaba0 | function CA = micOrientationCorrect(F, th, A)
%This program corrects spectra for microphone orientation based on the
%value given in the vector "th" in degrees. Normal microphone incidence is
%indicated by th==0.
%Correction is based on the difference in dB between the response at 0
%angle incidence as compared to one... |
github | michaelcrawley/Processing_Codes-master | NormDistance.m | .m | Processing_Codes-master/MATLAB/Old/Acoustics/NormDistance.m | 3,433 | utf_8 | 45383d18bf48f8a9961c22a18d2bfbe2 | function [Aout, al] = NormDistance(varargin)
%Corrects acoustic results for distance based on noise source location or
%simple radial propagation depending on inputs. The noise source location
%calculation is at the end of this file.
%
%CALLS
% [Aout, al] = NormDistance(A,Std,R,ChPol,NormD,dBShift)
% - Corrects b... |
github | michaelcrawley/Processing_Codes-master | ndnanfilter.m | .m | Processing_Codes-master/MATLAB/General Use/Utilities/ndnanfilter.m | 16,192 | utf_8 | 6bc8f6caa0c1e0e465d0c3d7db47b6e3 | function [Y,W] = ndnanfilter(X,HWIN,F,DIM,WINOPT,PADOPT,WNAN)
% NDNANFILTER N-dimensional zero-phase digital filter, ignoring NaNs.
%
% Syntax:
% Y = ndnanfilter(X,HWIN,F);
% Y = ndnanfilter(X,HWIN,F,DIM);
% Y = ndnanfilter(X,HWIN,F,DIM,WINOPT);
% Y = ndnanfilter(X,HWIN,F,DIM,WINOPT,... |
github | michaelcrawley/Processing_Codes-master | questdlg_timeout.m | .m | Processing_Codes-master/MATLAB/General Use/Utilities/questdlg_timeout.m | 16,148 | utf_8 | 80c6242ec67bd1ab14cafeb5dcfe29c3 | function ButtonName=questdlg_timeout(Question,Title,timeout,Btn1,Btn2,Btn3,Default)
%QUESTDLG Question dialog box.
% ButtonName = QUESTDLG(Question) creates a modal dialog box that
% automatically wraps the cell array or string (vector or matrix)
% Question to fit an appropriately sized window. The name of the
% b... |
github | michaelcrawley/Processing_Codes-master | mmpolyfit.m | .m | Processing_Codes-master/MATLAB/General Use/Utilities/mmpolyfit.m | 8,247 | utf_8 | f6b5359ce18dd24fe100569bf7f55c1a | function varargout=mmpolyfit(varargin)
% Fit Polynomial to Data with Constraints. (MM)
% P=MMPOLYFIT(X,Y,N) finds the coefficients of a polynomial P(X) of degree
% N that fits the data Y in a least-squares sense. P is a row vector of
% length N+1 containing the polynomial coefficients in descending order,
% P(1)*X^N + ... |
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