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 | mkneuron/compneuro-master | PT2_1c.m | .m | compneuro-master/CNS2015 assignments/week 2/PT2_1c.m | 2,874 | utf_8 | 5c7483fa913a4c6bd631896129767f2f | function Paul1c
clc
clear all
% close all
format long
%% Choose a value of 'a'.
a=0.5;
%% Choose a fixed point that you want to investigate.
% x1_fp=0; x2_fp=0;
x1_fp=-1; x2_fp=0;
% apart from those two fixed points, you can find situations with one more
% fixed point ... |
github | mkneuron/compneuro-master | PT1_exercise2a2b(1).m | .m | compneuro-master/CNS2015 assignments/week 1/PT1_exercise2a2b(1).m | 2,504 | utf_8 | 22244d30eb62823111ed0d39b6679364 | function Paul2a2b
clc
clear all
format long
N_h=100;
h_lin=linspace(0.01,0.5,N_h);
max_err_Euler=NaN(1,N_h);
max_err_RK2=NaN(1,N_h);
max_err_RK4=NaN(1,N_h);
max_err_ODE45=NaN(1,N_h);
i=1;
for h=h_lin
%% Euler scheme
ret=solveByEuler(h,-1,0,1);
x=ret(1,:);
y=ret(2,:);
y_anal... |
github | mkneuron/compneuro-master | PT1_exercise2d2e(1).m | .m | compneuro-master/CNS2015 assignments/week 1/PT1_exercise2d2e(1).m | 1,830 | utf_8 | 07050268d46cc5d4560d660af04d8a98 | function Paul2d2e
clc
clear all
format long
h=0.01; % Step size
I=-0.5; % Constant input
tEnd=10; % End time of simulation
y10=0.0; % Initial value of y1
y20=0.5; % Initial value of y2
%% Euler scheme
ret=solveByEuler(h,I,[y10;y20],0,tEnd);
y1=ret(2,:);
y2=ret(3,:);
... |
github | mkneuron/compneuro-master | PT3_1b1.m | .m | compneuro-master/CNS2015 assignments/week 3/PT3_1b1.m | 1,292 | utf_8 | 18b6432582a8fc7a7571a07dc4297fa9 | function Paul1b1
clc
clear all
%% Specify parameter
I_lin=linspace(50,55,100);
h=0.1;
% tEnd=300;
tEnd=2000;
%% Specify initial values
v_0=-50;
u_0=0;
FR_i=1;
FR=nan(size(I_lin,2),1);
for I=I_lin
I
FR(FR_i,1)=getFiringRateAtI(v_0,u_0,I,h,tEnd);
FR_i=FR_i+1;
end
figure(2)
hold on
... |
github | mkneuron/compneuro-master | PT3_1b2.m | .m | compneuro-master/CNS2015 assignments/week 3/PT3_1b2.m | 1,447 | utf_8 | d38c4bae52b0397d36dfe613493646e1 | function Paul1b2
clc
clear all
%% Specify parameter
I=1;
vmin=-65;
vmax=35;
umin=-2*(vmax+60);
umax=-2*(vmin+60);
if (I<=(72^2/(4*0.7)-1800))
%% We have two fixed point;
v_fp=(-72+sqrt(72^2-4*0.7*(1800+I)))/(2*0.7);u_fp=-2*v_fp-120;
A=[(0.7/100)*2*v_fp+70/100 -1/100;
-0.06 ... |
github | mkneuron/compneuro-master | PT3_1a.m | .m | compneuro-master/CNS2015 assignments/week 3/PT3_1a.m | 1,167 | utf_8 | 240514dcf69a3126bec30d662d76a663 | function Paul1a
clc
clear all
%% Specify parameter
I=52; % I=51 is a critical current to make the neuron fires.
h=0.1;
tEnd=2000;
% tEnd=300;
%% Specify initial values
v_0=-50;
u_0=0;
t_lin=[0:h:tEnd];
v=nan(size(t_lin,2),1);
u=nan(size(t_lin,2),1);
t_i=1;
v(1,1)=v_0;
u(1,1)=u_0;
for t=t_lin
... |
github | dice-project/DICE-Enhancement-FG-master | dicefg.m | .m | DICE-Enhancement-FG-master/dicefg.m | 3,444 | utf_8 | e66e4471548a8d938c68637d8ee842c7 | function dicefg(configFile)
% DICEFG(configFile)
% Run DICE-FG tool using the specified configuration XML file.
version = '2.3.0';
xDoc = xmlread(configFile);
rootNode = xDoc.getDocumentElement.getChildNodes; % get the <DICE-FG> root
Node = rootNode.getFirstChild;
while ~isempty(Node)
if strcmp(Node.getNodeName, '... |
github | dice-project/DICE-Enhancement-FG-master | ssg_closed_single.m | .m | DICE-Enhancement-FG-master/lib/ssg_closed_single.m | 408 | utf_8 | e52cb2ff3b72f3b9b96e4f5dff949615 | function SS = ssg_closed_single(M, N)
% Copyright (c) 2012-2014, Imperial College London
% All rights reserved.
SS = multichoose(M, N);
end
function [v] = multichoose(n,k)
v=[];
if n==1
v=k;
return
elseif k==0
v=zeros(1,n);
else
last=0;
for i=0:k
w=multichoose(n-1,k-i);
for j=... |
github | dice-project/DICE-Enhancement-FG-master | savejson.m | .m | DICE-Enhancement-FG-master/lib/jsonlab/savejson.m | 18,983 | utf_8 | 2f510ad749556cadd303786e2549f30a | function json=savejson(rootname,obj,varargin)
%
% json=savejson(rootname,obj,filename)
% or
% json=savejson(rootname,obj,opt)
% json=savejson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a JSON (JavaScript
% Object Notation) string
%
% author: Qianqian Fa... |
github | dice-project/DICE-Enhancement-FG-master | loadjson.m | .m | DICE-Enhancement-FG-master/lib/jsonlab/loadjson.m | 16,145 | ibm852 | 7582071c5bd7f5e5f74806ce191a9078 | function data = loadjson(fname,varargin)
%
% data=loadjson(fname,opt)
% or
% data=loadjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2011/09/09, including previous works from
%
% ... |
github | dice-project/DICE-Enhancement-FG-master | loadubjson.m | .m | DICE-Enhancement-FG-master/lib/jsonlab/loadubjson.m | 13,300 | utf_8 | b15e959f758c5c2efa2711aa79c443fc | function data = loadubjson(fname,varargin)
%
% data=loadubjson(fname,opt)
% or
% data=loadubjson(fname,'param1',value1,'param2',value2,...)
%
% parse a JSON (JavaScript Object Notation) file or string
%
% authors:Qianqian Fang (fangq<at> nmr.mgh.harvard.edu)
% created on 2013/08/01
%
% $Id$
%
% input:
% fname: ... |
github | dice-project/DICE-Enhancement-FG-master | saveubjson.m | .m | DICE-Enhancement-FG-master/lib/jsonlab/saveubjson.m | 17,723 | utf_8 | 3414421172c05225dfbd4a9c8c76e6b3 | function json=saveubjson(rootname,obj,varargin)
%
% json=saveubjson(rootname,obj,filename)
% or
% json=saveubjson(rootname,obj,opt)
% json=saveubjson(rootname,obj,'param1',value1,'param2',value2,...)
%
% convert a MATLAB object (cell, struct or array) into a Universal
% Binary JSON (UBJSON) binary string
%
% author... |
github | dice-project/DICE-Enhancement-FG-master | kpcfit_ph_search.m | .m | DICE-Enhancement-FG-master/lib/kpc-toolbox/kpcfit/kpcfit_ph_search.m | 6,612 | utf_8 | 1178e55aa295825e613642dbe9e5cb0c | function [KPC_PH,score,x] = kpcfit_ph_search(E,J,options,x0,max_aph_order)
% Not for direct call, auxiliary function. Optimization-based search.
%% initialization
warning off
%optimoptions = optimset('Algorithm','active-set', ...
%optimoptions = optimset('Algorithm','trust-region-reflective', ...
optimoptions = optimse... |
github | dice-project/DICE-Enhancement-FG-master | kpcfit_ph_manual.m | .m | DICE-Enhancement-FG-master/lib/kpc-toolbox/kpcfit/kpcfit_ph_manual.m | 5,134 | utf_8 | 1a1ddffd50ff7a33b77f2f6e35a21e8a | function PH = kpcfit_ph_manual(E,varargin)
% ** beta version **
%
% PH = kpcfit_ph_manual(E,'option1','val1','option2','val2',...)
%
% DESCRIPTION
% Fit phase-type (PH) process using Kronecker Product Composition (KPC)
% method
%
% INPUT
%
% E - vector of moments of consecutive order to be fitted
%
% EXAMP... |
github | dice-project/DICE-Enhancement-FG-master | map_normalize.m | .m | DICE-Enhancement-FG-master/lib/kpc-toolbox/map/map_normalize.m | 818 | utf_8 | c8d1d0ff5ac72a37ff60ae9e612329a7 | function MAP=map_normalize(MAP)
% MAPOUT=map_normalize(MAPIN) - Try to make a MAP feasible
%
% Input:
% MAPIN: a MAP in the form of {D0,D1}
%
% Output:
% MAPOUT: MAPIN with D0 normalized to make D0+D1 an infinitesimal
% generator, with all negative entries set to zero, and with complex
% values set equal to their... |
github | dice-project/DICE-Enhancement-FG-master | map_sample.m | .m | DICE-Enhancement-FG-master/lib/kpc-toolbox/map/map_sample.m | 2,999 | utf_8 | 8a8ab2cb6669bac6493f488f32c9f6a0 | function [SAMPLES,LAST,FIRST]=map_sample(MAP,nSamples,pi,seed)
% [SAMPLES,LAST]=map_sample(MAP,NUM,S0, SEED) - Generate a random sample
% of inter-arrival times
%
% Input:
% MAP: a MAP in the form of {D0,D1}
% NUM: number of samples to be generated
% S0: phase where the MAP starts for generating the first sample (... |
github | dice-project/DICE-Enhancement-FG-master | map_isfeasible.m | .m | DICE-Enhancement-FG-master/lib/kpc-toolbox/map/map_isfeasible.m | 2,040 | utf_8 | f1979d599a9d10d2d7ceb131d1cf1b18 | function ISFEAS=map_isfeasible(MAP,TOL)
% ISFEAS=map_isfeasible(MAP) - Evaluate feasibility of a MAP process
%
% Input:
% MAP: a MAP in the form of {D0,D1}
%
% Output:
% ISFEAS: boolean 1=feasible, 0=infeasible. Numerical tolerance is based
% on the standard toolbox value in map_feastol.m
%
% Examples:
% - map_i... |
github | dice-project/DICE-Enhancement-FG-master | est_res_qmle.m | .m | DICE-Enhancement-FG-master/algorithms/est_res_qmle.m | 2,353 | utf_8 | df6ec741c35a9e72d824816c98e2afd4 | function [theta,confint] = est_res_qmle( metric,flags,dicefg_disp )
[extDelay, jobPop] = est_res_extdelay(metric,flags,dicefg_disp);
qlSamples = Inf;
% determine probability of each sampling period
for r=1:metric.NumClasses
weightTS{r} = diff(get_data(metric,'ts', metric.ResIndex, r),1);
weightTS{r} = weightTS{... |
github | zhangliliang/RPN_BF-master | fast_rcnn_get_minibatch.m | .m | RPN_BF-master/functions/fast_rcnn/fast_rcnn_get_minibatch.m | 6,639 | utf_8 | 6fc8a42795ae5283c7f1af848e441eec | function [im_blob, rois_blob, labels_blob, bbox_targets_blob, bbox_loss_blob] = fast_rcnn_get_minibatch(conf, image_roidb)
% [im_blob, rois_blob, labels_blob, bbox_targets_blob, bbox_loss_blob] ...
% = fast_rcnn_get_minibatch(conf, image_roidb)
% --------------------------------------------------------
% Fast R-CNN
... |
github | zhangliliang/RPN_BF-master | fast_rcnn_conv_feat_detect.m | .m | RPN_BF-master/functions/fast_rcnn/fast_rcnn_conv_feat_detect.m | 4,211 | utf_8 | 7757435a0286baaedd67b1aa30c1f523 | function [pred_boxes, scores] = fast_rcnn_conv_feat_detect(conf, caffe_net, im, conv_feat_blob, boxes, max_rois_num_in_gpu)
% [pred_boxes, scores] = fast_rcnn_conv_feat_detect(conf, caffe_net, im, conv_feat_blob, boxes, max_rois_num_in_gpu)
% --------------------------------------------------------
% Fast R-CNN
% Reimp... |
github | zhangliliang/RPN_BF-master | fast_rcnn_train.m | .m | RPN_BF-master/functions/fast_rcnn/fast_rcnn_train.m | 11,078 | utf_8 | efd1eee216e32ac5a0a792f2796a1f4f | function save_model_path = fast_rcnn_train(conf, imdb_train, roidb_train, varargin)
% save_model_path = fast_rcnn_train(conf, imdb_train, roidb_train, varargin)
% --------------------------------------------------------
% Fast R-CNN
% Reimplementation based on Python Fast R-CNN (https://github.com/rbgirshick/fast-rcnn)... |
github | zhangliliang/RPN_BF-master | fast_rcnn_im_detect.m | .m | RPN_BF-master/functions/fast_rcnn/fast_rcnn_im_detect.m | 4,781 | utf_8 | 76b56954f7f1f2d32f89b7d0a00e8338 | function [pred_boxes, scores] = fast_rcnn_im_detect(conf, caffe_net, im, boxes, max_rois_num_in_gpu)
% [pred_boxes, scores] = fast_rcnn_im_detect(conf, caffe_net, im, boxes, max_rois_num_in_gpu)
% --------------------------------------------------------
% Fast R-CNN
% Reimplementation based on Python Fast R-CNN (https:... |
github | zhangliliang/RPN_BF-master | fast_rcnn_test.m | .m | RPN_BF-master/functions/fast_rcnn/fast_rcnn_test.m | 8,455 | utf_8 | 1b4a7dc5b5a0d67d5458497cdc47242d | function mAP = fast_rcnn_test(conf, imdb, roidb, varargin)
% mAP = fast_rcnn_test(conf, imdb, roidb, varargin)
% --------------------------------------------------------
% Fast R-CNN
% Reimplementation based on Python Fast R-CNN (https://github.com/rbgirshick/fast-rcnn)
% Copyright (c) 2015, Shaoqing Ren
% Licensed und... |
github | zhangliliang/RPN_BF-master | fast_rcnn_prepare_image_roidb.m | .m | RPN_BF-master/functions/fast_rcnn/fast_rcnn_prepare_image_roidb.m | 5,790 | utf_8 | 217eeabed3ac683cc222b600869094a0 | function [image_roidb, bbox_means, bbox_stds] = fast_rcnn_prepare_image_roidb(conf, imdbs, roidbs, bbox_means, bbox_stds)
% [image_roidb, bbox_means, bbox_stds] = fast_rcnn_prepare_image_roidb(conf, imdbs, roidbs, cache_img, bbox_means, bbox_stds)
% Gather useful information from imdb and roidb
% pre-calculate mean... |
github | zhangliliang/RPN_BF-master | fast_rcnn_generate_sliding_windows.m | .m | RPN_BF-master/functions/fast_rcnn/fast_rcnn_generate_sliding_windows.m | 1,729 | utf_8 | a788da565d8e7d1810407473c3135094 | function roidb = fast_rcnn_generate_sliding_windows(conf, imdb, roidb, roipool_in_size)
% [pred_boxes, scores] = fast_rcnn_conv_feat_detect(conf, im, conv_feat, boxes, max_rois_num_in_gpu, net_idx)
% --------------------------------------------------------
% Fast R-CNN
% Reimplementation based on Python Fast R-CNN (htt... |
github | zhangliliang/RPN_BF-master | proposal_generate_anchors.m | .m | RPN_BF-master/functions/rpn/proposal_generate_anchors.m | 2,558 | utf_8 | 3712bef03385b5b03e207b13cc7a67a1 | function anchors = proposal_generate_anchors(cache_name, varargin)
% anchors = proposal_generate_anchors(cache_name, varargin)
% --------------------------------------------------------
% Faster R-CNN
% Copyright (c) 2015, Shaoqing Ren
% Licensed under The MIT License [see LICENSE for details]
% -----------------------... |
github | zhangliliang/RPN_BF-master | proposal_train.m | .m | RPN_BF-master/functions/rpn/proposal_train.m | 14,555 | utf_8 | 3208bf1b1292bbcad07b7884f50bb57d | function save_model_path = proposal_train(conf, imdb_train, roidb_train, varargin)
% save_model_path = proposal_train(conf, imdb_train, roidb_train, varargin)
% --------------------------------------------------------
% Faster R-CNN
% Copyright (c) 2015, Shaoqing Ren
% Licensed under The MIT License [see LICENSE for de... |
github | zhangliliang/RPN_BF-master | proposal_locate_anchors.m | .m | RPN_BF-master/functions/rpn/proposal_locate_anchors.m | 2,092 | utf_8 | 2122289a0e5dc8538186e7fbb0e4840e | function [anchors, im_scales] = proposal_locate_anchors(conf, im_size, target_scale, feature_map_size)
% [anchors, im_scales] = proposal_locate_anchors(conf, im_size, target_scale, feature_map_size)
% --------------------------------------------------------
% Faster R-CNN
% Copyright (c) 2015, Shaoqing Ren
% Licensed u... |
github | zhangliliang/RPN_BF-master | proposal_prepare_image_roidb.m | .m | RPN_BF-master/functions/rpn/proposal_prepare_image_roidb.m | 8,724 | utf_8 | 5a43f4118ad33579350e6aca2ddb186f | function [image_roidb, bbox_means, bbox_stds] = proposal_prepare_image_roidb(conf, imdbs, roidbs, bbox_means, bbox_stds)
% [image_roidb, bbox_means, bbox_stds] = proposal_prepare_image_roidb(conf, imdbs, roidbs, cache_img, bbox_means, bbox_stds)
% --------------------------------------------------------
% Faster R-CNN
... |
github | zhangliliang/RPN_BF-master | proposal_im_detect.m | .m | RPN_BF-master/functions/rpn/proposal_im_detect.m | 5,112 | utf_8 | 593894a0ed6fc3bcfa24d706877363fa | function [pred_boxes, scores, box_deltas_, anchors_, scores_] = proposal_im_detect(conf, caffe_net, im)
% [pred_boxes, scores, box_deltas_, anchors_, scores_] = proposal_im_detect(conf, im, net_idx)
% --------------------------------------------------------
% Faster R-CNN
% Copyright (c) 2015, Shaoqing Ren
% Licensed u... |
github | zhangliliang/RPN_BF-master | proposal_generate_minibatch.m | .m | RPN_BF-master/functions/rpn/proposal_generate_minibatch.m | 5,423 | utf_8 | c75bed208f9c1b041a41967f150dffed | function [input_blobs, random_scale_inds] = proposal_generate_minibatch(conf, image_roidb)
% [input_blobs, random_scale_inds] = proposal_generate_minibatch(conf, image_roidb)
% --------------------------------------------------------
% Faster R-CNN
% Copyright (c) 2015, Shaoqing Ren
% Licensed under The MIT License [se... |
github | zhangliliang/RPN_BF-master | showboxes.m | .m | RPN_BF-master/utils/showboxes.m | 2,624 | utf_8 | be6b3bca7e6364f27e7ac8d3f76a3628 | function showboxes(im, boxes, legends, color_conf)
% Draw bounding boxes on top of an image.
% showboxes(im, boxes)
%
% -------------------------------------------------------
fix_width = 800;
if isa(im, 'gpuArray')
im = gather(im);
end
imsz = size(im);
scale = fix_width / imsz(2);
im = imresize(im, scale);
if ... |
github | zhangliliang/RPN_BF-master | roidb_from_voc.m | .m | RPN_BF-master/imdb/roidb_from_voc.m | 7,325 | utf_8 | ef87ae9f2d80c96ec3b8e885bff99d7c | function roidb = roidb_from_voc(imdb, varargin)
% roidb = roidb_from_voc(imdb, rootDir)
% Builds an regions of interest database from imdb image
% database. Uses precomputed selective search boxes available
% in the R-CNN data package.
%
% Inspired by Andrea Vedaldi's MKL imdb and roidb code.
% AUTORIGHTS
% --... |
github | zhangliliang/RPN_BF-master | script_faster_rcnn_VOC2012_VGG16.m | .m | RPN_BF-master/experiments/script_faster_rcnn_VOC2012_VGG16.m | 4,761 | utf_8 | 422e6ffa70c40318fb2b15562241f22f | function script_faster_rcnn_VOC2012_VGG16()
% script_faster_rcnn_VOC2012_VGG16()
% Faster rcnn training and testing with VGG16 model
% --------------------------------------------------------
% Faster R-CNN
% Copyright (c) 2015, Shaoqing Ren
% Licensed under The MIT License [see LICENSE for details]
% -----------------... |
github | zhangliliang/RPN_BF-master | script_faster_rcnn_demo.m | .m | RPN_BF-master/experiments/script_faster_rcnn_demo.m | 6,201 | utf_8 | de9d9c512d35ec48c7117b2e09abf3d8 | function script_faster_rcnn_demo()
close all;
clc;
clear mex;
clear is_valid_handle; % to clear init_key
run(fullfile(fileparts(fileparts(mfilename('fullpath'))), 'startup'));
%% -------------------- CONFIG --------------------
opts.caffe_version = 'caffe_faster_rcnn';
opts.gpu_id = auto_select... |
github | zhangliliang/RPN_BF-master | script_faster_rcnn_VOC0712_VGG16.m | .m | RPN_BF-master/experiments/script_faster_rcnn_VOC0712_VGG16.m | 4,758 | utf_8 | 1fea2360bf8509de950d1e4e765ba6a0 | function script_faster_rcnn_VOC0712_VGG16()
% script_faster_rcnn_VOC0712_VGG16()
% Faster rcnn training and testing with VGG16 model
% --------------------------------------------------------
% Faster R-CNN
% Copyright (c) 2015, Shaoqing Ren
% Licensed under The MIT License [see LICENSE for details]
% -----------------... |
github | zhangliliang/RPN_BF-master | script_faster_rcnn_VOC0712plus_VGG16.m | .m | RPN_BF-master/experiments/script_faster_rcnn_VOC0712plus_VGG16.m | 4,781 | utf_8 | e8c645ff31d7a4ad78af2b35b75f36a3 | function script_faster_rcnn_VOC0712plus_VGG16()
% script_faster_rcnn_VOC0712plus_VGG16()
% Faster rcnn training and testing with VGG16 model
% --------------------------------------------------------
% Faster R-CNN
% Copyright (c) 2015, Shaoqing Ren
% Licensed under The MIT License [see LICENSE for details]
% ---------... |
github | zhangliliang/RPN_BF-master | script_faster_rcnn_VOC0712_ZF.m | .m | RPN_BF-master/experiments/script_faster_rcnn_VOC0712_ZF.m | 4,747 | utf_8 | 82fe0f4db24a3e5f5596da6afbb47cd6 | function script_faster_rcnn_VOC0712_ZF()
% script_faster_rcnn_VOC0712_ZF()
% Faster rcnn training and testing with Zeiler & Fergus model
% --------------------------------------------------------
% Faster R-CNN
% Copyright (c) 2015, Shaoqing Ren
% Licensed under The MIT License [see LICENSE for details]
% -------------... |
github | zhangliliang/RPN_BF-master | script_faster_rcnn_VOC2007_VGG16.m | .m | RPN_BF-master/experiments/script_faster_rcnn_VOC2007_VGG16.m | 4,758 | utf_8 | 9dfd47e9e41d95917c16d2271d221109 | function script_faster_rcnn_VOC2007_VGG16()
% script_faster_rcnn_VOC2007_VGG16()
% Faster rcnn training and testing with VGG16 model
% --------------------------------------------------------
% Faster R-CNN
% Copyright (c) 2015, Shaoqing Ren
% Licensed under The MIT License [see LICENSE for details]
% -----------------... |
github | zhangliliang/RPN_BF-master | script_faster_rcnn_VOC2007_ZF.m | .m | RPN_BF-master/experiments/script_faster_rcnn_VOC2007_ZF.m | 4,747 | utf_8 | ea0d96156ab6ee6efa0cbf9622f67a0f | function script_faster_rcnn_VOC2007_ZF()
% script_faster_rcnn_VOC2007_ZF()
% Faster rcnn training and testing with Zeiler & Fergus model
% --------------------------------------------------------
% Faster R-CNN
% Copyright (c) 2015, Shaoqing Ren
% Licensed under The MIT License [see LICENSE for details]
% -------------... |
github | zhangliliang/RPN_BF-master | gather_rpn_fast_rcnn_models.m | .m | RPN_BF-master/experiments/+Faster_RCNN_Train/gather_rpn_fast_rcnn_models.m | 5,367 | utf_8 | 7705050151a6dfb9e89a0d1481c10b9c | function gather_rpn_fast_rcnn_models(conf_proposal, conf_fast_rcnn, model, dataset)
cachedir = fullfile(pwd, 'output', 'faster_rcnn_final', model.final_model.cache_name);
mkdir_if_missing(cachedir);
% find latest model for rpn and fast rcnn
[rpn_test_net_def_file, rpn_output_model_file] = find_last... |
github | zhangliliang/RPN_BF-master | do_proposal_test.m | .m | RPN_BF-master/experiments/+Faster_RCNN_Train/do_proposal_test.m | 1,961 | utf_8 | 67338b0121c98a4d2afd5a31055753cc | function roidb_new = do_proposal_test(conf, model_stage, imdb, roidb)
aboxes = proposal_test(conf, imdb, ...
'net_def_file', model_stage.test_net_def_file, ...
'net_file', model_stage.output_model_file, ... |
github | csjunxu/PGPD_Offline_BID-master | NoiseLevel.m | .m | PGPD_Offline_BID-master/NoiseLevel.m | 3,982 | utf_8 | 369cb3e4abc1b1c7ce9e8eebb0ca8d48 | % NoiseLevel estimates noise level of input single noisy image.
%
% [nlevel th num] = NoiseLevel(img,patchsize,decim,conf,itr)
%
%Output parameters
% nlevel: estimated noise levels.
% th: threshold to extract weak texture patches at the last iteration.
% num: number of extracted weak texture patches at the last iterat... |
github | csjunxu/PGPD_Offline_BID-master | PGPD_Denoising_faster.m | .m | PGPD_Offline_BID-master/PGPD_Denoising_faster.m | 7,805 | utf_8 | 38c83c090b8617b2b3208bd2135b7b6e | %------------------------------------------------------------------------------------------------
% PGPD_Denoising_faster - Denoising by Weighted Sparse Coding
% with Learned Patch Group Prior.
% CalNonLocal_II - Calculate the non-local similar patches (Noisy Patch Groups)
% ... |
github | csjunxu/PGPD_Offline_BID-master | cal_ssim.m | .m | PGPD_Offline_BID-master/cal_ssim.m | 6,176 | utf_8 | 1c1d646ff93c59e1688f23f12a368e85 | function ssim = cal_ssim( im1, im2, b_row, b_col )
[h, w, ch] = size( im1 );
ssim = 0;
if ch==1
ssim = ssim_index( im1(b_row+1:h-b_row, b_col+1:w-b_col), im2( b_row+1:h-b_row, b_col+1:w-b_col) );
else
for i = 1:ch
ssim = ssim + ssim_index( im1(b_row+1:h-b_row, b_col+1:w-b_col, i), im2( b_row+1... |
github | csjunxu/PGPD_Offline_BID-master | PGPD_Denoising.m | .m | PGPD_Offline_BID-master/PGPD_Denoising.m | 5,248 | utf_8 | 29f878a3f80d999f08148f97faab8854 | %------------------------------------------------------------------------------------------------
% PGPD_Denoising - Denoising by Weighted Sparse Coding
% with Learned Patch Group Prior.
% CalNonLocal - Calculate the non-local similar patches (Noisy Patch Groups)
% Author: Jun Xu, csjunx... |
github | zhentaoshi/C-Lasso-master | G_H_3.m | .m | C-Lasso-master/app_civil_war/G_H_3.m | 2,259 | utf_8 | bc7fb2bd8259debb750de22fdaa35463 | function [logl, grad, Hess, G1,G2,G3]=G_H_3(mle,fe,YL,YR,x2, x3)
% this script is developed upon Dhaene and Jochmans (2015)
[T,N]=size(YL);
R=ones(T,1)*fe'+mle(1)*YR+mle(2)*x2 + mle(3) * x3;
R(R<-4) = -4;
R(R>4) = 4;
F=normcdf(R);
A=1-F;
logF=log(F);
logA=log(A);
logFA=logF+logA;
logf=-0.5*(log(2*pi)+R.*R);
B... |
github | zhentaoshi/C-Lasso-master | SSP_PLS_est.m | .m | C-Lasso-master/generic_functions/SSP_PLS_est.m | 2,764 | utf_8 | 2287fe3b6378af48d85601c341ee4603 | function [b_est, a_out, group_est] = SSP_PLS_est(N, T, y, X, K, lambda, R)
% Su, Shi and Phillips (2017)
% PLS estimation by the iterative algorithm
% INPUT:
% N
% T
% y: (TN * 1)
% X: (TN * p)
% K: number of groups to be classified
% R: maximum number of iterations
% tol: tolerence level to judge conve... |
github | zhentaoshi/C-Lasso-master | PNL_est.m | .m | C-Lasso-master/simulations/Probit_KK/PNL_est.m | 1,680 | utf_8 | 78d7134db0f7d6e07f2ef642986e6c98 |
function [b_out, a_out, c_out] = PNL_est(N, T, b_initial, a_initial, y, X, K, lam, R, tol )
global p
pen = ones(N, K);
b_out = repmat( b_initial, [ 1 1 K]) ;
a_out = zeros(K, p);
b_old = ones(N, p);
a_old = zeros(1, p);
sign_y = (2*y - 1);
cvx_quiet(true)
if K == 1
cvx_begin
cvx_solver mo... |
github | zhentaoshi/C-Lasso-master | PNL_est.m | .m | C-Lasso-master/simulations/Probit_oracle/PNL_est.m | 1,684 | utf_8 | 5a9533da9c5ada6e1fa5e52e28d95421 |
function [b_out, a_out, c_out] = PNL_est(N, T, b_initial, a_initial, y, X, K, lam, R, tol )
global p
pen = ones(N, K);
b_out = repmat( b_initial, [ 1 1 K]) ;
a_out = zeros(K, p);
b_old = ones(N, p);
a_old = zeros(1, p);
sign_y = (2*y - 1);
cvx_quiet(true)
if K == 1
cvx_begin
cvx_solver mo... |
github | zhentaoshi/C-Lasso-master | G_H.m | .m | C-Lasso-master/simulations/Probit_oracle/G_H.m | 1,500 | utf_8 | 778e59cfa1838be157e1b65d08dcbee2 | function [logl grad Hess Grho Gbeta]=G_H(mle,fe,YL,YR,X)
[T,N]=size(YL);
R=ones(T,1)*fe'+mle(1)*YR+mle(2)*X;
F=normcdf(R);
A=1-F;
logF=log(F);
logA=log(A);
logFA=logF+logA;
logf=-0.5*(log(2*pi)+R.*R);
B=exp(logf-logFA);
C=-R.*B;
D=(R.*R-1).*B;
E=YL-F;
EB=E.*B;
EC=E.*C;
ED=E.*D;
H=EC-EB.*EB;
J=ED-3*EB.*EC+2... |
github | zhentaoshi/C-Lasso-master | PNL_est.m | .m | C-Lasso-master/simulations/Probit_K3/PNL_est.m | 1,684 | utf_8 | 5a9533da9c5ada6e1fa5e52e28d95421 |
function [b_out, a_out, c_out] = PNL_est(N, T, b_initial, a_initial, y, X, K, lam, R, tol )
global p
pen = ones(N, K);
b_out = repmat( b_initial, [ 1 1 K]) ;
a_out = zeros(K, p);
b_old = ones(N, p);
a_old = zeros(1, p);
sign_y = (2*y - 1);
cvx_quiet(true)
if K == 1
cvx_begin
cvx_solver mo... |
github | zhentaoshi/C-Lasso-master | PNL_est.m | .m | C-Lasso-master/simulations/Probit_unknown_KK/PNL_est.m | 1,684 | utf_8 | 5a9533da9c5ada6e1fa5e52e28d95421 |
function [b_out, a_out, c_out] = PNL_est(N, T, b_initial, a_initial, y, X, K, lam, R, tol )
global p
pen = ones(N, K);
b_out = repmat( b_initial, [ 1 1 K]) ;
a_out = zeros(K, p);
b_old = ones(N, p);
a_old = zeros(1, p);
sign_y = (2*y - 1);
cvx_quiet(true)
if K == 1
cvx_begin
cvx_solver mo... |
github | zhentaoshi/C-Lasso-master | G_H.m | .m | C-Lasso-master/simulations/Probit_unknown_KK/G_H.m | 1,483 | utf_8 | 79add8ec7e6a69c7aa94c666d3a07da7 | function [logl grad Hess Grho Gbeta]=G_H(mle,fe,YL,YR,X)
[T,N]=size(YL);
R=ones(T,1)*fe'+mle(1)*YR+mle(2)*X;
F=normcdf(R);
A=1-F;
logF=log(F);
logA=log(A);
logFA=logF+logA;
logf=-0.5*(log(2*pi)+R.*R);
B=exp(logf-logFA);
C=-R.*B;
D=(R.*R-1).*B;
E=YL-F;
EB=E.*B;
EC=E.*C;
ED=E.*D;
H=EC-EB.*EB;
J=ED-3*EB.*EC+2*EB... |
github | nathantspencer/webknossos_toolkit-master | glob.m | .m | webknossos_toolkit-master/zip_tools/glob.m | 17,025 | utf_8 | d7ae5f5b7df0771b8c97a8f3046c3f1f | %% Expand wildcards for files and directory names
%
% Pattern matching of file and directory names, based on wildcard
% characters. This function is similar to wildcard expansion performed by
% the Unix shell and Python glob.glob function, but it can handle more
% types of wildcards.
%
% [LIST, ISDIR] = glob(... |
github | ethz-asl/mav_system_identification-master | quatskew.m | .m | mav_system_identification-master/helper_functions/quatskew.m | 513 | utf_8 | 0ea1420708408aacc392e35efbbaa219 | % takes a vector of length 3 and converts to 4x4 skew symetric matrix
function qskew = quatskew(q)
%convention: first element is real part:
qskew=zeros(4);
qskew(1,2:4)=-q(2:4);
qskew(2,3)=q(4);
qskew(2,4)=-q(3);
qskew(3,4)=q(2);
qskew=qskew-qskew';
qskew=qskew+diag(ones(1,4)*q(1));
% convention: la... |
github | Schwartz-AlaLaurila-Labs/sa-labs-analysis-master | migrateToOldAnalysis.m | .m | sa-labs-analysis-master/src/main/matlab/functional-api/migrateToOldAnalysis.m | 2,664 | utf_8 | 72ec00d60f9bec3a531fdbd63e4f0724 | function migrateToOldAnalysis(project)
% set global variable for old analysis
setOldAnalysisPath();
% copy old celldata to folder
cellDataList = project.getCellDataList();
for i = 1 : numel(cellDataList)
saveCellData(cellDataList{i}, i);
end
% create temp folder for experiment
exp = project.experimentDate;
makeT... |
github | Schwartz-AlaLaurila-Labs/sa-labs-analysis-master | createAnalysisProject.m | .m | sa-labs-analysis-master/src/main/matlab/functional-api/createAnalysisProject.m | 1,690 | utf_8 | 1db78e637c17aaec09633ccfcf2ef50f | function [project, offlineAnalysisManager] = createAnalysisProject(projectName, varargin)
import sa_labs.analysis.*;
ip = inputParser();
ip.addParameter('experiments', '', @(e) ischar(e) || iscellstr(e));
ip.addParameter('user', getenv('username'), @ischar);
ip.addParameter('description', 'Hope it will be defined lat... |
github | Schwartz-AlaLaurila-Labs/sa-labs-analysis-master | helpDocToStructure.m | .m | sa-labs-analysis-master/src/main/matlab/+sa_labs/+analysis/+ui/+util/helpDocToStructure.m | 688 | utf_8 | 8fcdef198353b44bb9dcd14480997bee | function [structure, flattenedStructure] = helpDocToStructure(name)
structure = struct();
flattenedStructure = struct();
[doc, ~] = help(which(name));
if ~ isempty(doc)
parsedDoc = strsplit(doc, '---');
try
prameterYaml = parsedDoc{1};
structure = yaml.ReadYaml(prameterYaml, 0, 0, 1);
... |
github | Schwartz-AlaLaurila-Labs/sa-labs-analysis-master | plotFeature.m | .m | sa-labs-analysis-master/src/main/matlab/+sa_labs/+analysis/+tree_browser/+plots/plotFeature.m | 1,625 | utf_8 | a2374474e368ec743c32f880f3c600cb | function plotFeature(epochGroup, parameter, axes)
% description : plotFeature helps to visualize how the feature data (yAxis) change over featureDescripion xAxis. Below 'YAML' describes the fields present in the parameter structure.
% xAxis:
% default : "xAxis"
% description: see @sa_labs.analysis.entity.FeatureD... |
github | Schwartz-AlaLaurila-Labs/sa-labs-analysis-master | simpleSpikeDetector.m | .m | sa-labs-analysis-master/src/main/matlab/+sa_labs/+analysis/+data_curator/+pre_processor/+epoch/simpleSpikeDetector.m | 3,676 | utf_8 | 4d4e57c59e394d52e91e629b2b4ca98e | function simpleSpikeDetector(epochs, parameter)
% description : Simple spike detection from SchwartzNU Analysis folder; Refer https://github.com/SchwartzNU/SymphonyAnalysis/blob/master/GUIs/SpikeDetectorGUI.m
% mode:
% default : Advanced
% description: Type of spike detection, Example- 'Simple threshold' (or) 'Adv... |
github | Schwartz-AlaLaurila-Labs/sa-labs-analysis-master | plotEpochs.m | .m | sa-labs-analysis-master/src/main/matlab/+sa_labs/+analysis/+data_curator/+plots/plotEpochs.m | 2,154 | utf_8 | 6053e585683112248e8e9b01b2c934db | function plotEpochs(epochs, parameter, axes)
% description : It plots signal from various amplifier device over stimulus duration. Below 'YAML' describes the fields present in the parameter structure.
% xAxis:
% default : Duration
% description: Stimulus duration (preTime + stimTime + tailTime)
% yAxis:
% defaul... |
github | desperado1992/caffe-yolo-2-master | classification_demo.m | .m | caffe-yolo-2-master/matlab/demo/classification_demo.m | 5,412 | utf_8 | 8f46deabe6cde287c4759f3bc8b7f819 | function [scores, maxlabel] = classification_demo(im, use_gpu)
% [scores, maxlabel] = classification_demo(im, use_gpu)
%
% Image classification demo using BVLC CaffeNet.
%
% IMPORTANT: before you run this demo, you should download BVLC CaffeNet
% from Model Zoo (http://caffe.berkeleyvision.org/model_zoo.html)
%
% *****... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | element_cov_matrix_2D.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/stochastic_process/element_cov_matrix_2D.m | 1,152 | utf_8 | cc7961a160ed4ef3a0c8fad687a4c2ef | %Generates covariance matrix for 2D Gaussian distributed (spatially) random field
%
% The random field is discretized in the midpoint of pfem finite elements.
%
%SYNOPSIS
% cov_matrix = ELEMENT_COV_MATRIX_2D(L_meshed, stdev, corr_length, pow)
%
%INPUT
% L_meshed - coordinate of the pfem mesh nodes in the element l... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | naive_fit.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/stochastic_process/fit_sp/naive_fit.m | 3,141 | utf_8 | 713caafa312801ee9d3eae0cc1670d67 | % Maximum likelihood fit of stochastic process
function naive_fit
close all
clc
% rng(333) % for reproducibility
% copulas = {'gauss'};
% marginals = {'lognormal'};
copulas = {'gauss', 't', 'gumbel', 'rotgumbel', 'rotclayton'};
marginals = {'gauss', 'lognormal', 'gumbel'};
n = length(copulas);
m ... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | shanks_trans_test.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/shanks_trans_test.m | 1,336 | utf_8 | d4611604164dfe9e42d5d91497f6a9c7 | % Shanks transformation to increase rate of convergence of limit
function shanks_trans_test
% clear variables
close all
clc
% https://en.wikipedia.org/wiki/Shanks_transformation#Example
% k and n are exchanged
% fun = @(n) 4*sum((-1).^(0:n).*(1./(2*(0:n)+1)));
ffun = @(x) sin(x)./x;
fun = @(k) ffun(2.^(-k)... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | nelson_cop.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/simple example/nelson_cop.m | 460 | utf_8 | b3ac9de76fd5d86c320d744fe9bdfb5a | function nelson_cop
theta = 10;
%Nelson #13
I = @(t) inelson(t);
x = 0:0.01:1;
y = I(x);
plot(x,y)
%Clayton
% I = @(t) 1/theta*(t.^-theta-1)./(-t.^(-theta-1));
IN = integral(I, 0,1, 'AbsTol', 1e-12, 'RelTol', 1e-6);
tau = 1 + 4*IN
%Clayton - closed form solutioon
theta/(2+theta)
function I = inelson(t)
I = n... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | ferum_veri_.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/simple example/ferum_veri_.m | 8,311 | utf_8 | 9d5208bb74b1b7fcab0f3c04bbe56ce4 |
function [probdata, analysisopt, gfundata] = ferum_veri_(R, ro_F, als)
% Clear possible old data in the Matlab workspace
clear probdata gfundata analysisopt femodel
probdata.name = {'S1';
'S2';
'R';
... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | direct_int_ktau_fun.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/simple example/direct_int_ktau_fun.m | 2,657 | utf_8 | b47576bbeec3fa731b981c5228626eb3 | % Time-variant reliability analysis with continuous stochastic process
% investigation of the effect of copula assumption
%
% g = R - S(t)
%
% R - constant
% S(t) - continuous stochastic process
function [nu_p, Pf0] = direct_int_ktau_fun(delta_t, tau_Fv)
%------------------------------------------------------------... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | annual_max.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/snow_wind_multivariate_extreme/annual_max.m | 1,972 | utf_8 | b8682883881debdbb07935814073772b | % Select annual maxima from daily observations
%
% [max_a, f_scatter] = ANNUAL_MAX(obs_data, rowNumber, years, plotFig)
%
% data - daily observations
% rowNumber - number of observations
% years - year of maxima (vector)
% plotFig - plot? y(1),n(2); n(2) - default (str,integer)
function [max_a, max_idx, f_s... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | tinv_ext.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/snow_wind_multivariate_extreme/tinv_ext.m | 1,368 | utf_8 | b3689ae2da8fa805b09b175ffbf78058 | % tinv() extension for 2 degrees of freedom!
% to evaluate points of the t distribution which gives NaN in matlab built in
% not effective but at least it is working
%=============================
% to evaluate points of the t distribution which gives NaN in matlab built in
% PP = logspace(-50, -15, 2e3);
% % PP = 1-P... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | conv_RG.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/stochastic_snow_model/conv_RG.m | 946 | utf_8 | b7a0d80736c771cbf43ae4f2bc18a419 | % Convolution RG = R-G
%
% [Probvar, pdRG] = CONV_RG(Probvar)
function [Probvar, pdRG] = conv_RG(Probvar)
rv = {'R', 'G'};
nrv = length(rv);
pds(nrv).min = NaN;
% loop over random variables
for ii = 1:nrv
if Probvar.(rv{ii}).dist == 1
pd.fx_fun = @(x) normpdf(x, Probvar.(rv{ii}).mean, Probvar.(rv{i... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | ferum_main.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/Sudret's corroding beam/beam_corrosion_Sudret/ferum_main.m | 8,965 | utf_8 | 04a3a0ae9c629a4cdc217248a3821875 | % Bruno Sudret (2008). Analytical derivation of the outcrossing rate in time-variant reliability problems. DOI:10.1080/15732470701270058
% simply supported bridge subjected to stochastic load (F) and corrosion
%[m], [year], [N]
function [probdata, analysisopt, gfundata] = ferum_main(t, als, ro_F)
% Clear possible old... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | ferum_ex1_form.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/Sudret's corroding beam/beam_corrosion_Sudret/ferum_ex1_form.m | 8,336 | utf_8 | 1b394f18711614c54496d72e11155c74 | % Bruno Sudret (2008). Analytical derivation of the outcrossing rate in time-variant reliability problems. DOI:10.1080/15732470701270058
% simply supported bridge subjected to stochastic load (F) and corrosion
%[m], [year], [N]
function [probdata, analysisopt, gfundata] = ferum_main(als, ro_F)
% Clear possible old da... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | sum_2rv.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/Sudret's corroding beam/beam_corrosion_Sudret/copula_direct_integration/sum_2rv.m | 2,834 | utf_8 | de795a144d4009c33c14621261e33766 | % Probability distribution function (pdf) of the sum of two independent random variables
%
% Convolution of two random variable -> performed using discrete Fourier transform
%
%SYNOPSYS:
% [fy, y] = SUM_2RV(pd1, pd2, n)
%
%INPUT:
% pd1
% .fx_fun handler of X1's pdf
% .mean mean value of X1
% .min ... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | form_wrapper.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/Sudret's corroding beam/beam_corrosion_Sudret/copula_direct_integration/form_wrapper.m | 7,384 | utf_8 | 1eff2437dbd6499c5d854684182c418a | % FORM analysis using FERUM
% units: [N], [m]
function [beta, formresults, probdata] = form_wrapper(r, t)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% DATA FIELDS IN 'PROBDATA' %%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Names of random variables. Default names are 'x1', 'x2', ..., if not explicitely defined.
probdata.name =... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | prod_2rv.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/Sudret's corroding beam/beam_corrosion_Sudret/copula_direct_integration/prod_2rv.m | 506 | utf_8 | 308caf15334775bb08c3be1e9fd867a4 | % Probability distribution function (pdf) of the product of two independent random variables
%
% Z = X1*X2
%
% pdz = PROD_2RV(pd1, pd2)
function pdz = prod_2rv(pd1, pd2)
fz = @(z) integral(@(x) pd1.fx_fun(x).*pd2.fx_fun(z./x).*1./abs(x), 0, inf);
pdz.fx_fun = fz;
end
% pd1.fx_fun = @(x) lognpdf(x,1,0.1);
% pd2.fx... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | construct_pdf.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/Sudret's corroding beam/beam_corrosion_Sudret/copula_direct_integration/construct_pdf.m | 10,459 | utf_8 | b467a5c72341e02df6354ef647db2e0f | % clear all
% close all
% clc
%CUSTOM FUNCTION(S):
%sum_2rv.m
%prod_2rv.m
%[mm], [year], [N]
function f = construct_pdf(t, x, method, fig)
if nargin < 4
fig = 'no';
end
%=======================
% OPTIONS
%=======================
d_scale = 1e-3; %if d_scale = 1 -> mm
qq ... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | sum_2rv_01.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/effect of copulas/Sudret's corroding beam/beam_corrosion_Sudret/copula_direct_integration/sum_2rv_01.m | 1,758 | utf_8 | c77bcc1b9a0c3b71d4e6fa1791135726 | % Probability distribution function (pdf) of the sum of two independent random variables
%
% Convolution of two random variable -> performed using discrete Fourier transform
%
%SYNOPSYS:
% [fy, y] = SUM_2RV(fx1, fx2)
%
%INPUT:
% fx1_fun handler of X1's pdf
% fx2_fun handler of X2's pdf
%
%
%OUTPUT:
%
%
%NOT... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | element_cov_matrix.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/phi2_vs_time_integration/element_cov_matrix.m | 1,335 | utf_8 | 8ba523be6bc89229d8d34f68d4fe8746 | %Generates covariance matrix for 1D Gaussian distributed (spatially) random field
%
% The random field is discretized in the midpoint of pfem finite elements.
%
%SYNOPSIS
% cov_matrix = ELEMENT_COV_MATRIX(L_meshed, stdev, corr_length, pow)
%
%INPUT
% L_meshed - coordinate of the pfem mesh nodes in the element loca... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | ferum_main_timeint.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/phi2_vs_time_integration/ferum_main_timeint.m | 8,595 | utf_8 | 4152758bee0165ecd62cb3b1a615cbc1 | % Bruno Sudret (2008). Analytical derivation of the outcrossing rate in time-variant reliability problems. DOI:10.1080/15732470701270058
% simply supported bridge subjected to stochastic load (F) and corrosion
%[m], [year], [N]
function [probdata, analysisopt, gfundata] = ferum_main_timeint
% Clear possible old data ... |
github | rozsasarpi/Effect-of-copulas-on-time-variant-reliability-master | ferum_main_stoch.m | .m | Effect-of-copulas-on-time-variant-reliability-master/Matlab/phi2_vs_time_integration/ferum_main_stoch.m | 8,971 | utf_8 | ac5f7d80988f86c6e85a5a3f4d5008d2 | % Bruno Sudret (2008). Analytical derivation of the outcrossing rate in time-variant reliability problems. DOI:10.1080/15732470701270058
% simply supported bridge subjected to stochastic load (F) and corrosion
%[m], [year], [N]
function [probdata, analysisopt, gfundata] = ferum_main_stoch(t, als, ro_F)
% Clear possib... |
github | AndyWood91/experiment_programs-master | readInImages.m | .m | experiment_programs-master/Le Pelley/EIB rewExp/functions/readInImages.m | 1,660 | utf_8 | 4fc485addd3ebcf2277e410bad21519f | %% Read in images
function [imageTexture, numImages, targetRotation] = readInImages(inputFoldername, readingTargetImages)
global MainWindow
inputFilenames = dir(inputFoldername);
testStringPos = zeros(length(inputFilenames), 1);
fullTargetRotation = zeros(length(inputFilenames), 1);
for ii = 1 : length(inputFilenam... |
github | AndyWood91/experiment_programs-master | runTrials.m | .m | experiment_programs-master/Le Pelley/EIB rewExp/functions/runTrials.m | 14,300 | utf_8 | 13b32dcba7d043cb391d4ec979ec399b | function [rewardPropCorrect, runningTotalPoints] = runTrials(exptPhase)
global DATA MainWindow
global bColour white screenWidth screenHeight
global soundPAhandle winSoundArray
global datafilename
global rewardImages numRewardImages
global neutImages numNeutImages
global baselineImages numBaselineImages
global targetI... |
github | AndyWood91/experiment_programs-master | runTrials.m | .m | experiment_programs-master/Le Pelley/VWM EG/functions/runTrials.m | 18,894 | utf_8 | c83d57cafaa5648c9b7f75b9ec5e42d3 |
function [trial, allDeviationCounter] = runTrials(exptPhase) % Return final trial number (used for collating EG data)
global MainWindow DATA datafilename EGdataFilenameBase
global xCentre yCentre
global bgdColour
global debugVersion eyeVersion
global white yellow
if debugVersion
fixationDuration = 0.5;
... |
github | AndyWood91/experiment_programs-master | awareInstructions.m | .m | experiment_programs-master/Le Pelley/Bleeder Cue/Exp1/functions/awareInstructions.m | 2,364 | utf_8 | 51f7e6eb063ec687fa9cb7d0e62173bc |
function awareInstructions()
global bigMultiplier smallMultiplier
global centOrCents
global awareInstrPause
instructStr1 = ['The eye tracking task is now finished - it''s fine to take your chin out of the chin rest.\n\nDuring this task, the amount that you could win on each trial was determined by the colour of the ... |
github | AndyWood91/experiment_programs-master | runTrials.m | .m | experiment_programs-master/Le Pelley/Bleeder Cue/Exp1/functions/runTrials.m | 27,938 | utf_8 | 4f8bff36bb6e1357df23e5372b2abb18 |
function sessionPay = runTrials(exptPhase)
global MainWindow
global scr_centre DATA datafilename p_number
global distract_col
global white black gray yellow
global bigMultiplier smallMultiplier
global stim_size stimLocs
global stimCentre aoiRadius
global fix_aoi_radius
global instrCondition
global exptSession
global ... |
github | AndyWood91/experiment_programs-master | initialInstructions.m | .m | experiment_programs-master/Le Pelley/Bleeder Cue/Exp1/functions/initialInstructions.m | 2,544 | utf_8 | 3a4c85192170c81085476c9e55ecc5c1 |
function initialInstructions()
global MainWindow white
instructStr1 = 'On each trial a cross will appear inside a circle, and a yellow spot will show you where the computer thinks your eyes are looking. You should fix your eyes on the cross. After a short time the cross will turn yellow and the spot will disappear -... |
github | AndyWood91/experiment_programs-master | exptInstructions.m | .m | experiment_programs-master/Le Pelley/Bleeder Cue/Exp1/functions/exptInstructions.m | 3,845 | utf_8 | 6081f24723895a25261adc29e8cc71ab |
function exptInstructions
global MainWindow white
global bigMultiplier smallMultiplier
global centOrCents
global instrCondition
global softTimeoutDurationLate
instructStr1 = 'The rest of this experiment is similar to the trials you have just completed. On each trial, you should move your eyes to the DIAMOND shape as... |
github | AndyWood91/experiment_programs-master | awareInstructions.m | .m | experiment_programs-master/Le Pelley/Bleeder Cue/Exp3/functions/awareInstructions.m | 2,360 | utf_8 | 68006e0e00dba442ca5d332d8fa9f4b1 |
function awareInstructions()
global bigMultiplier smallMultiplier
global centOrCents
global awareInstrPause
instructStr1 = ['The eye tracking task is now finished - it''s fine to take your chin out of the chin rest.\n\nDuring this task, the amount that you could win on each trial was determined by the colour of the ... |
github | AndyWood91/experiment_programs-master | runTrials.m | .m | experiment_programs-master/Le Pelley/Bleeder Cue/Exp3/functions/runTrials.m | 30,780 | utf_8 | c9ebbd242f1fb8323650cdea3f45191f |
function sessionPay = runTrials(exptPhase)
global MainWindow
global scr_centre DATA datafilename p_number
global distract_col
global white black gray yellow
global bigMultiplier smallMultiplier
global stim_size stimLocs
global stimCentre aoiRadius
global fix_aoi_radius
global instrCondition
global exptSession
global ... |
github | AndyWood91/experiment_programs-master | initialInstructions.m | .m | experiment_programs-master/Le Pelley/Bleeder Cue/Exp3/functions/initialInstructions.m | 2,544 | utf_8 | 3a4c85192170c81085476c9e55ecc5c1 |
function initialInstructions()
global MainWindow white
instructStr1 = 'On each trial a cross will appear inside a circle, and a yellow spot will show you where the computer thinks your eyes are looking. You should fix your eyes on the cross. After a short time the cross will turn yellow and the spot will disappear -... |
github | AndyWood91/experiment_programs-master | exptInstructions.m | .m | experiment_programs-master/Le Pelley/Bleeder Cue/Exp3/functions/exptInstructions.m | 12,965 | utf_8 | a0580c40c3568cf80e5875a3f1686802 |
function exptInstructions
global MainWindow white
global bigMultiplier smallMultiplier
global centOrCents
global instrCondition
global softTimeoutDurationLate colourName
instructStr1 = 'The rest of this experiment is similar to the trials you have just completed. On each trial, you should move your eyes to the DIAMO... |
github | AndyWood91/experiment_programs-master | awareInstructions.m | .m | experiment_programs-master/Le Pelley/Auditory Capture/functions/awareInstructions.m | 2,285 | utf_8 | 16f9314becc4dc5a4550a508a22552a1 |
function awareInstructions()
global bigMultiplier smallMultiplier
global centOrCents
global awareInstrPause
instructStr1 = ['The main task is now finished - it''s fine to take your chin out of the chin rest.\n\nDuring this task, the amount that you could win on each trial was determined by the type of beep that occu... |
github | AndyWood91/experiment_programs-master | runTrials.m | .m | experiment_programs-master/Le Pelley/Auditory Capture/functions/runTrials.m | 19,467 | utf_8 | f346fc4ce7c9eba9cdd044594de03ed1 |
function [sessionPay, accSummary] = runTrials(exptPhase)
global MainWindow
global numAudioChannels
global scr_centre DATA datafilename
global cueToneArray cueToneArrayLength toneFreq
global noiseArray noiseArrayLength
global lowestTargetVolume highestTargetVolume
global white black yellow
global bigMultiplier smallMu... |
github | AndyWood91/experiment_programs-master | initialInstructions.m | .m | experiment_programs-master/Le Pelley/Auditory Capture/functions/initialInstructions.m | 9,249 | utf_8 | d5360e260bef5c8186b76cfeffc20dce |
function initialInstructions()
global MainWindow white
global topKeyName bottomKeyName
instructStr1 = 'On each trial a cross will appear, and you should keep your eyes fixed on this cross whenever it is on the screen.\n\nShortly after the cross appears, you will hear a beep and a ''rattle'' in quick succession. Your... |
github | AndyWood91/experiment_programs-master | exptInstructions.m | .m | experiment_programs-master/Le Pelley/Auditory Capture/functions/exptInstructions.m | 2,567 | utf_8 | 9f9545d5242c267418e92f9f9904d6da |
function exptInstructions
global MainWindow white
global bigMultiplier smallMultiplier lossAmount
global centOrCents
instructStr1 = 'The rest of this experiment is similar to the trials you have just completed. On each trial, you should respond as quickly and accurately as possible, according to whether the rattle c... |
github | AndyWood91/experiment_programs-master | awareInstructions.m | .m | experiment_programs-master/Le Pelley/Reward Vs Predictiveness/functions/awareInstructions.m | 1,971 | utf_8 | 995f50f7b4e4a0acf71291c6540f8560 |
function awareInstructions()
global awareInstrPause
instructStr1 = 'The eye tracking task is now finished - it''s fine to take your chin out of the chin rest.\n\nDuring this task, the amount that you could win on each trial was determined by the colour of the coloured circle that appeared on that trial. \n\nIn the f... |
github | AndyWood91/experiment_programs-master | runTrials.m | .m | experiment_programs-master/Le Pelley/Reward Vs Predictiveness/functions/runTrials.m | 27,888 | utf_8 | 5a9404c31ccb99d24cc506f3db6448e8 |
function sessionPay = runTrials(exptPhase)
global MainWindow
global scr_centre DATA datafilename p_number
global distract_col
global white gray yellow
global bigMultiplier smallMultiplier medMultiplier
global stim_size stimLocs
global stimCentre aoiRadius
global fix_aoi_radius
global instrCondition
global softTimeout... |
github | AndyWood91/experiment_programs-master | initialInstructions.m | .m | experiment_programs-master/Le Pelley/Reward Vs Predictiveness/functions/initialInstructions.m | 2,197 | utf_8 | 0c2f1d8fd3c2aabf8862410463e71c12 |
function initialInstructions()
global MainWindow white
instructStr1 = 'On each trial a cross will appear inside a circle, and a yellow spot will show you where the computer thinks your eyes are looking. You should fix your eyes on the cross. After a short time the cross will turn yellow and the spot will disappear -... |
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