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github | AllenDowney/PhysicalModelingInMatlab-master | comp_err2.m | .m | PhysicalModelingInMatlab-master/code/other/comp_err2.m | 634 | utf_8 | 0827e847cc8190f954e8e287f3ed988a | function [rms] = comp_err (ang, noise, ang_error)
sum = zeros(size(ang));
N=2;
for i=1:N
[ G, H ] = data_gen (ang, noise, ang_error);
rot = ang_rot(ang)
[ rot_out, quat, ang_out, av ] = tiax_Joel (G,H);
rot_out = quat_rot(quat)
% rot_err is the rotation that takes rot o... |
github | AllenDowney/PhysicalModelingInMatlab-master | particle.m | .m | PhysicalModelingInMatlab-master/code/other/particle.m | 640 | utf_8 | f7ee05338baeabf68dca3f08da84aaaa | function dXdt = particle(t, X)
P = X(1:3);
V = X(4:6);
A = acceleration(t, P, V);
dXdt = [V; A];
end
function A = acceleration(t, P, V)
% t is the current time, P is the position of the particle in
% 3-space, V is the velocity of the particle.
q = 1;
m = 1;
B = mfield(t, P);
F = q * c... |
github | AllenDowney/PhysicalModelingInMatlab-master | ramp.m | .m | PhysicalModelingInMatlab-master/code/other/ramp.m | 5,409 | utf_8 | 41d5fc2f8ec378398b64e94e8baf3b65 | % Simulation of a skateboarder on a ramp.
% Allen B. Downey
function res = bisection_func(flag)
% if flag is 1, run the animation at the critical velocity
% (minium that gets over the ramp)
% otherwise, run a bisection search for the critical velocity
if flag
v = 5.357540588225950; % init... |
github | AllenDowney/PhysicalModelingInMatlab-master | testing.m | .m | PhysicalModelingInMatlab-master/code/other/testing.m | 859 | utf_8 | da145e09b5c05f66c66c6497efc00379 | function [x y] = projectile()
% example from page 312 of Gilat,
% MATLAB: An Introduction with Applications
syms V X ang real
syms v0 g t positive
ihat = [1; 0];
jhat = [0; 1];
X0 = [0; 0];
V0 = pol2vec(v0, ang);
A = -g * jhat;
V = V0 + int(A, t);
X = X0 + int(V, t);
Y... |
github | AllenDowney/PhysicalModelingInMatlab-master | sym_worksheet.m | .m | PhysicalModelingInMatlab-master/code/other/sym_worksheet.m | 14,143 | utf_8 | 9bddfee9cf117a08a0c5bf8e6c6dbe94 | function res = sym_examples(func)
f = str2func(func);
f();
end
function res = example_3_1()
% page 51 of Wolfson and Pasachoff
r = 160; % km
degrees = 35; % degrees
R = degr2vec(degrees, r)
end
function res = example_3_2()
% page 52 of Wolfson and Pasachoff
end
function res = example_3_4... |
github | AllenDowney/PhysicalModelingInMatlab-master | ramp3.m | .m | PhysicalModelingInMatlab-master/code/other/ramp3.m | 4,495 | utf_8 | 077258436c6ecf7a6ba1a9a4e3f207dc | function res = find_zero()
res = fzero(@ramp_func, 9);
end
function res = ramp_func(v)
% run the simulation until the ramp touches the ground
% and return the x coordinate of the rider relative to
% the end of the ramp
% ramp_height is the height of the ramp in meters
% ramp_dist is the horizo... |
github | AllenDowney/PhysicalModelingInMatlab-master | pendulum2.m | .m | PhysicalModelingInMatlab-master/code/other/pendulum2.m | 951 | utf_8 | 509ea804b3640bc5d12117311050276f | function res = pendulum()
% declare the symbols
syms g m1 l1 positive
syms x1 y1 t real
syms X V T L real
syms th1 om1 aa1 real
th1ft = sym('th1(t)');
om1ft = sym('om1(t)');
X = pol2vec(l1, th1ft-pi/2);
V = diff(X, t);
vsq = dot(V, V);
V = m1 * g * X(2);
T = m1 * vsq ... |
github | AllenDowney/PhysicalModelingInMatlab-master | projectile2.m | .m | PhysicalModelingInMatlab-master/code/other/projectile2.m | 418 | utf_8 | 8bb6a6a380e5141a28d3f4991c5d6cc1 | function dXdt = f(t, X)
% this function take a vector with 4 components, [x, y, x', y']
% and returns a column vector with components [x', y', x'', y'']
% it uses the function acceleration to compute x'' and y''.
V = X(3:4);
A = acceleration(V)
dXdt = [vx; vy; A];
end
function A = acceleration(V)
% this function tak... |
github | AllenDowney/PhysicalModelingInMatlab-master | fyt.m | .m | PhysicalModelingInMatlab-master/code/other/fyt.m | 292 | utf_8 | 3d45c06f78801c15d32fd064eefc1440 | function e = solvand (i)
% if I am trying to reach a balance of a, how much will I be off by?
a = 300000;
e = balance(i) - a;
end
function b = balance (i)
% given interest rate i, monthly payment p, how much money
% will I have after n months?
p = 200;
n = 300;
b = p/i * ((i+1)^n - 1);
end
|
github | AllenDowney/PhysicalModelingInMatlab-master | projectile.m | .m | PhysicalModelingInMatlab-master/code/other/projectile.m | 237 | utf_8 | 92c812704f19d93a86701d79f3a73b5a | function dXdt = f(t, X)
x = X(1);
y = X(2);
vx = X(3)
vy = X(4);
ax = fx(t, x, y, vx, vy)
ay = fy(t, x, y, vx, vy)
dXdt = [vx; vy; ax; ay];
end
function a = fx(t, x, y, vx, vy)
a = 0
end
function a = fy(t, x, y, vx, vy)
a = -9.8
end
|
github | AllenDowney/PhysicalModelingInMatlab-master | moody.m | .m | PhysicalModelingInMatlab-master/code/other/moody.m | 133 | utf_8 | edb5ce7c1922c62af8b703e2aa2100e7 | function moody()
[T, Y] = ode45(@test_func, [0,1.5], 1);
plot(T, Y)
end
function res = test_func(t, y)
res = y ^ 2;
end
|
github | AllenDowney/PhysicalModelingInMatlab-master | mysqrt.m | .m | PhysicalModelingInMatlab-master/code/other/mysqrt.m | 203 | utf_8 | 1401958fec920f1aedee35ceadeb607e | function root = mysqrt(a)
est = a;
for i=1:8
est = est - f(est, a) / fp(est);
end
root = est;
end
function y = f(x, b)
y = x^2 - b;
end
function y = fp(x)
y = 2*x;
end
|
github | AllenDowney/PhysicalModelingInMatlab-master | magpart.m | .m | PhysicalModelingInMatlab-master/code/other/magpart.m | 1,657 | utf_8 | 24fab0e2ddcc2699165d56a981c6c06f | function magpart(te)
% te is the duration of the time range
% initial conditions
P = [-0.1 0 0]';
V = [0.1 0.1 0]';
% call ode45
[T, M] = ode45(@part, [0, te], [P; V]);
% plot the results
X = M(:,1);
Y = M(:,2);
Z = M(:,3);
comet3(X, Y, Z);
%XY = M(:, 1:2)
%plot(T,X)
... |
github | AllenDowney/PhysicalModelingInMatlab-master | interest.m | .m | PhysicalModelingInMatlab-master/code/other/interest.m | 292 | utf_8 | 3d45c06f78801c15d32fd064eefc1440 | function e = solvand (i)
% if I am trying to reach a balance of a, how much will I be off by?
a = 300000;
e = balance(i) - a;
end
function b = balance (i)
% given interest rate i, monthly payment p, how much money
% will I have after n months?
p = 200;
n = 300;
b = p/i * ((i+1)^n - 1);
end
|
github | AllenDowney/PhysicalModelingInMatlab-master | manny1.m | .m | PhysicalModelingInMatlab-master/code/other/manny1.m | 2,867 | utf_8 | 10d82049d1436fc2ef8407911f7b31c0 | e =
function res = manny()
% find the velocity that _just_ gets the ball over the wall
initial_guess = 45; % m/s
velocity = fzero(@crossover_func, initial_guess);
res = velocity;
end
function res = crossover_func(velocity)
% this function crosses through zero when the height of the ball a... |
github | AllenDowney/PhysicalModelingInMatlab-master | data_gen3.m | .m | PhysicalModelingInMatlab-master/code/other/data_gen3.m | 447 | utf_8 | 35a214d2072768e3c7bcd63b8c8d43c6 | % takes input of roll, pitch and heading angles and outputs accel and mag
% data in body frame with noise
function [ G,H ] = data_gen (ang, noise)
% g is grav, Hh is horizontal and Hv is vertical component of mag field
% in Earth's frame
g = 9.8;
Hh = 4E4;
Hv = 2E4;
gnoise = noise*g;
hnoise = noise*(Hh^2+Hv^2)^0.5;
%... |
github | AllenDowney/PhysicalModelingInMatlab-master | lacrosse.m | .m | PhysicalModelingInMatlab-master/code/other/lacrosse.m | 5,142 | utf_8 | 42554d9db839fc961a9afd24bfea7dd6 | % Simulation of a bouncing lacrosse ball.
% Allen B. Downey
% The ball is modeled as a thin shell around a core, connected
% by a torsional spring. When the ball is in contact with the
% ground, the shell stops rotating and the core rotates relative
% shell, causing a displacement between the angle of the core
% and ... |
github | AllenDowney/PhysicalModelingInMatlab-master | sym_examples.m | .m | PhysicalModelingInMatlab-master/code/other/sym_examples.m | 16,583 | utf_8 | 3ba1771fda5734c714544cf29d0db8e8 | function res = sym_examples(func)
f = str2func(func);
f();
end
function res = example_3_1()
% page 51 of Wolfson and Pasachoff
r = 160; % km
degrees = 35; % degrees
R = degr2vec(degrees, r)
end
function res = example_3_2()
% page 52 of Wolfson and Pasachoff
R1 = degr2vec(30, 2);
R... |
github | AllenDowney/PhysicalModelingInMatlab-master | flying_duck.m | .m | PhysicalModelingInMatlab-master/code/other/flying_duck.m | 603 | utf_8 | 656cce1b5815b09e59820cee57296adc | function [t, h] = duck(v0)
exact = 2 * 10 / 9.8
dts = [0.0001 0.001 0.01 0.1];
for i = 1:length(dts)
[T, V, H] = euler(v0, dts(i));
h(i) = max(H);
t(i) = (T(end) - exact) / exact
end
loglog(dts, t)
end
function [T, V, H] = euler(v0, dt)
T(1) = 0;
H(1) = 0;
V(1) =... |
github | AllenDowney/PhysicalModelingInMatlab-master | koch.m | .m | PhysicalModelingInMatlab-master/code/other/koch.m | 1,063 | utf_8 | 24503ffe612720432d93fb6a71cc36a7 | function koch ()
clf; axis equal
title 'quadric Koch curve by Allen'
subplot(2,2,1)
koch_square (1)
subplot (2,2,2)
koch_square (2)
subplot (2,2,3)
koch_square (3)
subplot (2,2,4)
koch_square (4)
function koch_square (n)
v1 = [0,0];
v2 = [1,0];
v3 = [1,1];
v4... |
github | AllenDowney/PhysicalModelingInMatlab-master | vector_examples.m | .m | PhysicalModelingInMatlab-master/code/other/vector_examples.m | 15,511 | utf_8 | 18b76c1eea4d28b061eff1dcf918c2b0 | function res = sym_examples(func)
f = str2func(func);
f();
end
function res = example_3_1()
% Example 3-1 on page 51 of Wolfson and Pasachoff
r = 160; % km
degrees = 35; % degrees
R = degr2vec(r, degrees)
end
function res = example_3_2()
% Example 3-2 on page 52 of Wolfson and Pasachoff
... |
github | AllenDowney/PhysicalModelingInMatlab-master | double_pend.m | .m | PhysicalModelingInMatlab-master/code/other/double_pend.m | 1,486 | utf_8 | 06df2acd5535620b6456c19417b10368 | function res = double_pendulum()
syms x1 y1 x2 y2 t real
syms g m1 m2 l1 l2 real
syms V T L real
syms th1 th2 om1 om2 aa1 aa2 real
x1 = l1 * sin(th1);
y1 = -l1 * cos(th1);
x2 = x1 + l2 * sin(th2);
y2 = y1 - l2 * cos(th2);
vx1 = mydiff(x1, 1)
vy1 = mydiff(y1, 1)
vx2 = mydiff... |
github | AllenDowney/PhysicalModelingInMatlab-master | allen_ramp.m | .m | PhysicalModelingInMatlab-master/code/other/allen_ramp.m | 5,166 | utf_8 | 684fe3aa529ef04479ff2d1fec73aed3 | function res = bisection_func(flag)
% if flag is 1, run the animation at the critical velocity
% (minimum that gets over the ramp)
% otherwise, run a bisection search for the critical velocity
if flag
v = 8.360417154065374; % initial velocity of the rider/board
ramp_func(v, 1.0);
... |
github | AllenDowney/PhysicalModelingInMatlab-master | double_pend3.m | .m | PhysicalModelingInMatlab-master/code/other/double_pend3.m | 2,191 | utf_8 | a94b07d9b9e14ed0005151076a7f18c4 | function res = double_pendulum()
syms g m1 m2 l1 l2 positive
syms V T L real
syms th1 th2 om1 om2 aa1 aa2 real
X1 = pol2vec(l1, th1-pi/2);
X2 = X1 + pol2vec(l2, th2-pi/2);
V1 = mydiff(X1, 1);
V2 = mydiff(X2, 1);
v1sq = dot(V1, V1);
v2sq = dot(V2, V2);
V = m1 * g * X1(2) + m2 ... |
github | AllenDowney/PhysicalModelingInMatlab-master | double_pend2.m | .m | PhysicalModelingInMatlab-master/code/other/double_pend2.m | 2,208 | utf_8 | 9f1aa549e730db0e34192e6de3cd9450 | function res = double_pendulum()
syms g m1 m2 l1 l2 positive
syms V T L real
syms t th1 th2 om1 om2 aa1 aa2 real
th1 = sym('th1(t)');
th2 = sym('th2(t)');
X1 = pol2vec(l1, th1-pi/2);
X2 = X1 + pol2vec(l2, th2-pi/2);
V1 = diff(X1, t);
V2 = diff(X2, t);
v1sq = dot(V1, V1);
... |
github | AllenDowney/PhysicalModelingInMatlab-master | pendulum.m | .m | PhysicalModelingInMatlab-master/code/other/pendulum.m | 1,132 | utf_8 | 95c400c13866f15b21444ae45dba06ae | function res = pendulum()
% declare the symbols
syms g m1 l1
syms x1 y1 t
syms V T L
syms th1 om1 aa1
X = pol2vec(l1, th1-pi/2);
V = mydiff(X, t);
vsq = dot(V, V);
V = m1 * g * X(2);
T = m1 * vsq / 2;
L = T - V
% take derivatives
dLdom1 = diff(L, om1);
ddt1 = ... |
github | AllenDowney/PhysicalModelingInMatlab-master | corn.m | .m | PhysicalModelingInMatlab-master/code/other/corn.m | 2,363 | utf_8 | 74c691be1c2961e078cd42b7c9d70766 | function res = corn()
% run a simulation of the enzyme action in fuel alcohol production
% and return the time (in hours) to reduce the unavailable starch
% concentation to 0.01 (mMol/L)
options = odeset('Events', @event_func);
tend = 50 * 60 * 60; % 50 hours in seconds
Sinit... |
github | AllenDowney/PhysicalModelingInMatlab-master | newton.m | .m | PhysicalModelingInMatlab-master/code/other/newton.m | 2,573 | utf_8 | ac84e80f3e4cea4d66c65e7bd04b7c53 | function [ euler, quat ] = newton ( G, H )
% THIS FUNCTION IS NOT CURRENTLY WORKING.
% Inputs: Two matrices, G accelerometer data and H magentometer data.
% Output: Euler angles and quaternions for rotations.
% Euler output is: [ phi, theta, psi ];
% Quaternion output is: [ q0, w ] where w = { q1, q2, q3 } a vector d... |
github | AllenDowney/PhysicalModelingInMatlab-master | pendulum1.m | .m | PhysicalModelingInMatlab-master/code/other/pendulum1.m | 1,132 | utf_8 | 95c400c13866f15b21444ae45dba06ae | function res = pendulum()
% declare the symbols
syms g m1 l1
syms x1 y1 t
syms V T L
syms th1 om1 aa1
X = pol2vec(l1, th1-pi/2);
V = mydiff(X, t);
vsq = dot(V, V);
V = m1 * g * X(2);
T = m1 * vsq / 2;
L = T - V
% take derivatives
dLdom1 = diff(L, om1);
ddt1 = ... |
github | mzahiri/Walker-master | passivewalker.m | .m | Walker-master/Code/passivewalker.m | 11,539 | utf_8 | a14368ea616ebe4a51f9c3117e1d6fd7 |
function passivewalker(flag)
clc
clear all
close all
format long
global check;
if nargin == 0
flag = 1; %simulates simplest walker by default
end
walker.M = 10000; walker.m = 1.0; walker.I = 0.00; walker.l = 1.0; walker.w = 0.0;
walker.c = 1.0; walker.r = 0.0; walker.g = 1.0; wa... |
github | mzahiri/Walker-master | pw2.m | .m | Walker-master/Code/pw2.m | 12,235 | utf_8 | db9495b6f8c3a904a6f4c1f9dab20d60 |
function passivewalker(flag)
clc
clear all
close all
format long
if nargin == 0
flag = 1; %simulates simplest walker by default
end
walker.M = 10000; walker.m = 1.0; walker.I = 0.00; walker.l = 1.0; walker.w = 0.0;
walker.c = 1.0; walker.r = 0.0; walker.g = 1.0; walker.gam =0.01823;... |
github | mzahiri/Walker-master | passivewalker.m | .m | Walker-master/Code/simple-2/passivewalker.m | 6,262 | utf_8 | 186044fe1d14ed5fec845c40f6615a5e |
function passivewalker(flag)
clc
clear all
close all
format long
global check;
%% c = COM on the leg from hip, w = COM fore-aft offset, r = radius of feet
%% M = hip mass, m = leg mass, I = leg inertia, l = leg length
walker.M = 10000; walker.m = 1.0; walker.I = 0.00; walker.l ... |
github | kunaljathal/Music-FX-Library-master | fixChorus.m | .m | Music-FX-Library-master/fixChorus.m | 1,012 | utf_8 | 6cc78c4859b297491eb69c7a9a1c3bb5 | % Kunal Jathal
% Fixed Delay Chorus
% ===================
% We want to implement a simple chorus filter i.e. just the following
% difference equation:
% y[n] = x[n] + b0 * x[n - K]
% We want to take in the following arguments:
% Delay Coefficient (b0)
% Input Signal (x[n])
% Delay Amount (K) (in MILLISECONDS) - th... |
github | kunaljathal/Music-FX-Library-master | varChorus.m | .m | Music-FX-Library-master/varChorus.m | 2,164 | utf_8 | 037182ae863446f624fed1df1fe16650 | % Kunal Jathal
% Variable Delay Chorus
% =====================
% Now, we want to implement a variable delay chorus filter, i.e. the
% difference equation:
% y[n] = x[n] + b0 * x[n - g[n]]
% We want to take in the following arguments:
% Delay Coefficient (b0)
% Input Signal (x[n])
% Delay Amount (g[n]) - this is now... |
github | kunaljathal/Music-FX-Library-master | compressor.m | .m | Music-FX-Library-master/compressor.m | 2,950 | utf_8 | 26dae3fe42e55a28b17ee3aa577cf54c | % Kunal Jathal
% N19194426
% DST 2 - Assignment 2
%
% Question 2 (a)
%
function compressor(inputSignal, threshold, slope, gainMatching)
% Error check the threshold and slope
if ((abs(threshold) > 1) || (abs(slope) > 1))
error('Both the threshold and slope need to be under 1');
end
% Get the original signal
[ori... |
github | kunaljathal/Music-FX-Library-master | allPassChorus.m | .m | Music-FX-Library-master/allPassChorus.m | 4,879 | utf_8 | a693eb0c471bbb2e56fdc628e2db2b41 | % Kunal Jathal
%
% Chorus function using LFO and an All Pass Filter for fractional delay
% =====================================================================
% We want to implement a FRACTIONAL delay chorus filter
% y[n] = x[n] + b0 * x[n - g[n]]
% We want to take in the following arguments:
% Delay Coefficient ... |
github | kunaljathal/Music-FX-Library-master | WahWah_v1.m | .m | Music-FX-Library-master/WahWah_v1.m | 6,810 | utf_8 | bc44022206dc52cce41705a04219b805 | % Kunal Jathal
% N19194426
% DST 2 - Assignment 3
%
% Question 2
%
% The simplest Wah Wah 'Pedal' in the world.
% ===========================================
function varargout = WahWah_v1(varargin)
% WAHWAH_V1 MATLAB code for WahWah_v1.fig
% WAHWAH_V1, by itself, creates a new WAHWAH_V1 or raises the existing
... |
github | kunaljathal/Music-FX-Library-master | deEsser.m | .m | Music-FX-Library-master/deEsser.m | 4,242 | utf_8 | 44b35f368851a2ba6f23aadf9202bfc3 |
function deEsser(inputSignal, threshold, slope, gainMatching, lowerFreqLimit, upperFreqLimit)
% define Bark band edges and center frequencies
barkEdges = [0 100 200 300 400 510 630 770 920 1080 1270 ...
1480 1720 2000 2320 2700 3150 3700 4400 5300 6400 7700 9500 12000 15500];
% Error check the threshold and slope
i... |
github | kunaljathal/Music-FX-Library-master | fracChorus.m | .m | Music-FX-Library-master/fracChorus.m | 2,914 | utf_8 | 1ae6767034ee4be127684992524dec97 | % Kunal Jathal
% Fractional Delay Chorus
% =======================
% Now, we want to implement a FRACTIONAL delay chorus filter
% y[n] = x[n] + b0 * x[n - g[n]]
% We want to take in the following arguments:
% Delay Coefficient (b0)
% Input Signal (x[n])
% Delay Amount (g[n]) - this is now a function of time. So we ... |
github | mvansegbroeck-zz/ivectool-master | ISDvectorEM_P1_s1_f2.m | .m | ivectool-master/ivec/ISDvectorEM_P1_s1_f2.m | 2,836 | utf_8 | b894271087168dcc771f82f4606f0233 | % P1. E STEP OF EM TRAINING
function ISDvectorEM_P1_s1_f2(TrainMatName,TrainLabelName,StasticsMatName,N_Rank,Idx_iteration,nbClassesTrain,n_MeansuperDim,T_init,InvSigma1,matrix1,nMixNum,nVecSize,ProjectMatrixPool,log_N_s_table,log_N_s_table_length,log_N_s_table_interval,W_init,InvSigma2,matrix2)
%load(LastModelMa... |
github | mvansegbroeck-zz/ivectool-master | ISDvectorEM_P2_s1.m | .m | ivectool-master/ivec/ISDvectorEM_P2_s1.m | 3,778 | utf_8 | 2a0e1d6881c6aa364d373e64e2890754 | % P2. M STEP OF EM TRAINING, ACCUMULATION OVER SPLIT FILES
function ISDvectorEM_P2_s1(LastModelMatName,trainingset,nb_splits,NewModelMatName,ivec_dim,odir)
load (LastModelMatName);
ProjectMatrixPool_=cell(size(ProjectMatrixPool,3));
for i=1:size(ProjectMatrixPool,3)
ProjectMatrixPool_{i}=ProjectMatrixPo... |
github | mvansegbroeck-zz/ivectool-master | ISDvectorEM_P0_s1.m | .m | ivectool-master/ivec/ISDvectorEM_P0_s1.m | 1,494 | utf_8 | eec24f1a626163103f7c8fd025e6caf8 | % P0. INITIALIZE PARAMETERS FOR EM TRAINING
function ISDvectorEM_P0_s1(trainingdir, N_Rank, nMixNum, featType, nVecSize, nbClassesTrain)
%clear all;
%N_Rank=400;
% 600(for RATS) = dimension of i-vector, related to the #Gaussians, in the GMM and the amount of the data
%nMixNum=128;
% 2048 (for RATS)
Idx_ite... |
github | mvansegbroeck-zz/ivectool-master | make_gfcc.m | .m | ivectool-master/ivec/make_gfcc.m | 8,426 | utf_8 | 7f4de9d5934ddf6baf6f1a2817da972e | function make_gfcc(wav_list)
% Generate MFCC features in HTK format (*.mfc)
% for the files given in the database file
% wav_list: list of wav files to be processed
if ~exist('wav_list', 'var')
fprintf(1, 'Input file list is missing!\n');
exit;
end
fd=fopen(wav_list,'r');
list_files=textscan... |
github | mvansegbroeck-zz/ivectool-master | Compute_DET.m | .m | ivectool-master/ivec/DETware_v2.1/Compute_DET.m | 4,264 | utf_8 | 6bbbdac6f97b52ea4458058f88c248bf | function [Pmiss, Pfa] = Compute_DET(true_scores, false_scores)
%function [Pmiss, Pfa] = Compute_DET (true_scores, false_scores)
%
% Compute_DET computes the (observed) miss/false_alarm probabilities
% for a set of detection output scores.
%
% true_scores (false_scores) are detection output scores for a set of
% det... |
github | mvansegbroeck-zz/ivectool-master | Plot_DET.m | .m | ivectool-master/ivec/DETware_v2.1/Plot_DET.m | 3,604 | utf_8 | 68c057dc7d5ce51d832102a23cb692dd | function h = Plot_DET (Pmiss, Pfa, plot_code, opt_thickness)
%function h = Plot_DET (Pmiss, Pfa, plot_code, opt_thickness)
%
% Plot_DET plots detection performance tradeoff on a DET plot
% and returns the handle for plotting.
%
% Pmiss and Pfa are the vectors of miss and corresponding false
% alarm probabilities to... |
github | mvansegbroeck-zz/ivectool-master | ppndf.m | .m | ivectool-master/ivec/DETware_v2.1/ppndf.m | 3,906 | utf_8 | 9fc6ba84330e74b6dc6094b95a34bd31 | function norm_dev = ppndf (cum_prob)
%function ppndf (prob)
%The input to this function is a cumulative probability.
%The output from this function is the Normal deviate
%that corresponds to that probability. For example:
% INPUT OUTPUT
% 0.001 -3.090
% 0.01 -2.326
% 0.1 -1.282
% 0.5 0.0
% 0.9 ... |
github | rsagroup/rsatoolbox_matlab-master | modelRDMs_demo2.m | .m | rsatoolbox_matlab-master/Demos/modelRDMs_demo2.m | 1,163 | utf_8 | 9660723aa413065309981a8e198f5957 | % modelRDMs is a user-editable function which specifies the models which
% brain-region RDMs should be compared to, and which specifies which kinds of
% analysis should be performed.
%
% Models should be stored in the "Models" struct as a single field labeled
% with the model's name (use underscores in stead ... |
github | rsagroup/rsatoolbox_matlab-master | simulationOptions_demo.m | .m | rsatoolbox_matlab-master/Demos/simulationOptions_demo.m | 2,959 | utf_8 | c7f0701dee0ea6c4461cfa9b9ac88fc5 | % simulationOptions_demo
%
% This function is used to make a simulationOptions struct for use in the
% simulation part of the demo. The options should be set to personal
% preference.
%
% Cai Wingfield 7-2010
%__________________________________________________________________________
% Copyright (C) 2010 Medical Resea... |
github | rsagroup/rsatoolbox_matlab-master | defineUserOptions2.m | .m | rsatoolbox_matlab-master/Demos/defineUserOptions2.m | 5,018 | utf_8 | a145cf333eacda6b7ddca816096e0c97 | % projectOptions_demo is a nullary function which initialises a struct
% containing the preferences and details for a particular project; in this case
% the demo for the toolbox. It should be edited to taste before a project is
% run, and a new one created for each substantially different project (though
% the opti... |
github | rsagroup/rsatoolbox_matlab-master | simulationOptions_demo_LDt.m | .m | rsatoolbox_matlab-master/Demos/simulationOptions_demo_LDt.m | 2,841 | utf_8 | d41b7be54be5f415a9245f96e5aa7730 | % simulationOptions_demo
%
% This function is used to make a simulationOptions struct for use in the
% simulation part of the demo. The options should be set to personal
% preference.
%
% Cai Wingfield 7-2010
%__________________________________________________________________________
% Copyright (C) 2010 Medical Resea... |
github | rsagroup/rsatoolbox_matlab-master | projectOptions_demo.m | .m | rsatoolbox_matlab-master/Demos/projectOptions_demo.m | 5,032 | utf_8 | 719615c2e54ea4d6e193a2b813741bd9 | % projectOptions_demo is a nullary function which initialises a struct
% containing the preferences and details for a particular project; in this case
% the demo for the toolbox. It should be edited to taste before a project is
% run, and a new one created for each substantially different project (though
% the... |
github | rsagroup/rsatoolbox_matlab-master | projectOptions_DEMO1.m | .m | rsatoolbox_matlab-master/Demos/projectOptions_DEMO1.m | 3,199 | utf_8 | 0f849d0c8c32362043d8bc2db92d8fec | % This function which initialises a struct containing the preferences and
% details for a particular project; in this case the demo for the toolbox.
% It should be edited to taste before a project is run, and a new one
% created for each substantially different project (though the options
% struct will be saved eac... |
github | rsagroup/rsatoolbox_matlab-master | runSearchlightLDC.m | .m | rsatoolbox_matlab-master/+rsa/runSearchlightLDC.m | 4,709 | utf_8 | f742f9deeeabe84a23555350be127a9d | function runSearchlightLDC(searchLight,varargin)
% runSearchlightLDC(searchLight,varargin)
% Wrapper for the main searchlight function rsa_runSearchlight
% This version calculates the LDC from an SPM first-level analysis
% New Version takes into account the first-level design matrix
%
% INPUT:
% searchLi... |
github | rsagroup/rsatoolbox_matlab-master | concatenateRDMs.m | .m | rsatoolbox_matlab-master/+rsa/+rdm/concatenateRDMs.m | 1,304 | utf_8 | e94aee03769d01742977510fd459d365 | function RDMsOut = concatenateRDMs(varargin)
% RDMsOut = concatenateRDMs(RDMs1[, RDMs2[, ...]])
% concatenates a number of wrapped RDMs (RDM structures).
% the main difference between this function and the similar one called
% 'concatRDMs' is that this function requires the input to be wrapped RDM
% st
% CW 5-2010, 6-... |
github | rsagroup/rsatoolbox_matlab-master | averageRDMs_subjectSession.m | .m | rsatoolbox_matlab-master/+rsa/+rdm/averageRDMs_subjectSession.m | 4,264 | utf_8 | edf85b5ec9bdf9c26d417d36ea920204 | function RDMs = averageRDMs_subjectSession(varargin)
% RDMs = averageRDMs_subjectSession(RDMs): returns the input unchanged (no
% operation). RDMs = averageRDMs_subjectSession(RDMs, 'subject'): computes
% the subject-averaged RDMs. RDMs = averageRDMs_subjectSession(RDMs,
% 'session') RDMs = averageRDMs_subjectSession(R... |
github | rsagroup/rsatoolbox_matlab-master | exportfig.m | .m | rsatoolbox_matlab-master/+rsa/+fig/exportfig.m | 16,831 | utf_8 | b853b90bbcaba9d8af0986ebba1f7d8a | function exportfig(varargin)
%EXPORTFIG Export a figure to Encapsulated Postscript.
% EXPORTFIG(H, FILENAME) writes the figure H to FILENAME. H is
% a figure handle and FILENAME is a string that specifies the
% name of the output file.
%
% EXPORTFIG(...,PARAM1,VAL1,PARAM2,VAL2,...) specifies
% parame... |
github | rsagroup/rsatoolbox_matlab-master | addComparisonBars.m | .m | rsatoolbox_matlab-master/+rsa/+fig/addComparisonBars.m | 1,785 | utf_8 | 9a859018a9453467eb8ce8cdcbb0ace4 | % this function adds the pairwise copmparison bars to a figure; the 'hold on'
% should have been set before executing this function
% pairWisePs: an nxn pairwise comparison matrix. This is supposed to be
% sorted in descending order of average values (large to small heights)
% a horizontal bar would be displayed ... |
github | rsagroup/rsatoolbox_matlab-master | fMRISearchlight.m | .m | rsatoolbox_matlab-master/+rsa/+fmri/fMRISearchlight.m | 24,662 | utf_8 | 79083f57cc9af57fc82cf17551620bc5 | function [varargout] = fMRISearchlight(fullBrainVols, binaryMasks_nS, models, betaCorrespondence, userOptions)
%
% fMRISearchlight is a function which takes some full brain volumes of data,
% some binary masks and some models and perfoms a searchlight in the data within
% each mask, matching to each of the models. Sav... |
github | rsagroup/rsatoolbox_matlab-master | crossvalIPMraw.m | .m | rsatoolbox_matlab-master/+rsa/+spm/crossvalIPMraw.m | 6,493 | utf_8 | 29502724c505d6e0a4c1676e65a58dc1 | function G = crossvalIPMraw(Y,SPM,conditionVec,varargin)
% function dist=rsa.spm.crossvalIPMraw(Y,SPM,conditionVec,varargin);
% First, gets the regression coefficent from the SPM, and prewhitens them.
% Prewhiten can be controlled using different methods (run-wise or overall).
% The same code is used in rsa.spm.noi... |
github | rsagroup/rsatoolbox_matlab-master | spm_create_vol.m | .m | rsatoolbox_matlab-master/+rsa/+spm/spm_create_vol.m | 5,060 | utf_8 | 3b5408bd0f3dd0f5ab2278da9aae7907 | function V = spm_create_vol(V,varargin)
% Create a volume
% FORMAT V = spm_create_vol(V)
% V - image volume information (see spm_vol.m)
%____________________________________________________________________________
% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience
% John Ashburner
% $Id: spm_create_vol.m... |
github | rsagroup/rsatoolbox_matlab-master | getDataFromSPM.m | .m | rsatoolbox_matlab-master/+rsa/+spm/getDataFromSPM.m | 4,400 | utf_8 | 523e6fe1b3b1c4d81efd6fe20ccce8d5 | function betas = getDataFromSPM(userOptions)
%
% getDataFromSPM is a function which will extract from the SPM metadata the
% correspondence between the beta image filenames and the condition and session
% number.
%
% function betas = getDataFromSPM(userOptions)
%
% betas --- The array of info.
% be... |
github | rsagroup/rsatoolbox_matlab-master | makeGifti.m | .m | rsatoolbox_matlab-master/+rsa/+gifti/makeGifti.m | 1,756 | utf_8 | 053d379ddd936b504573dc0b1275933d | function makeGifti(file,varargin)
% function rsa_makeGifti(file,varargin)
% Convert file into the GIFTI file format and write it into
% the same directory. Aligns surface with the volume anatomical for the
% subject.
%
% INPUTS
% file: full path and file name for the file to be converted
%
% USEROPTIONS / VARARGIN:
... |
github | rsagroup/rsatoolbox_matlab-master | save_gii.m | .m | rsatoolbox_matlab-master/+rsa/+gifti/save_gii.m | 21,903 | utf_8 | 8be3caec981ac345280ccccf033321d3 | function rsa_save_gii(this,filename,encoding)
% Save GIfTI object in a GIfTI format file
% FORMAT save(this,filename)
% this - GIfTI object
% filename - name of GIfTI file to be created [Default: 'untitled.gii']
% encoding - optional argument to specify encoding format, among
% ASCII, Base64Binary, G... |
github | rsagroup/rsatoolbox_matlab-master | save.m | .m | rsatoolbox_matlab-master/+rsa/@gifti/save.m | 20,267 | utf_8 | aa5357fe19c7be85f66b8f1f38d1dc38 | function save(this,filename,encoding)
% Save GIfTI object in a GIfTI format file
% FORMAT save(this,filename)
% this - GIfTI object
% filename - name of GIfTI file that will be created
% encoding - optional argument to specify encoding format, among
% ASCII, Base64Binary, GZipBase64Binary, ExternalFi... |
github | rsagroup/rsatoolbox_matlab-master | gifti.m | .m | rsatoolbox_matlab-master/+rsa/@gifti/gifti.m | 3,622 | utf_8 | 770f3ed1f17658bff49edbacd0062416 | function this = gifti(varargin)
% GIfTI Geometry file format class
% Geometry format under the Neuroimaging Informatics Technology Initiative
% (NIfTI):
% http://www.nitrc.org/projects/gifti/
% http://nifti.nimh.nih.gov/
%_____________________________________________________________... |
github | rsagroup/rsatoolbox_matlab-master | read_gifti_file.m | .m | rsatoolbox_matlab-master/+rsa/@gifti/private/read_gifti_file.m | 5,738 | utf_8 | 8ba32dfda235fde9c266c2fee680204f | function this = read_gifti_file(filename, this)
% Low level reader of GIfTI 1.0 files
% FORMAT this = read_gifti_file(filename, this)
% filename - XML GIfTI filename
% this - structure with fields 'metaData', 'label' and 'data'.
%__________________________________________________________________________
% Cop... |
github | rsagroup/rsatoolbox_matlab-master | isintent.m | .m | rsatoolbox_matlab-master/+rsa/@gifti/private/isintent.m | 2,098 | utf_8 | 24b5f1aa2d6630fd9e8c6b38b40cb76f | function [a, b] = isintent(this,intent)
% Correspondance between fieldnames and NIfTI intents
% FORMAT ind = isintent(this,intent)
% this - GIfTI object
% intent - fieldnames
% a - indices of found intent(s)
% b - indices of dataarrays of found intent(s)
%____________________________________________... |
github | rsagroup/rsatoolbox_matlab-master | ceilingAvgRDMcorr.m | .m | rsatoolbox_matlab-master/+rsa/+stat/ceilingAvgRDMcorr.m | 12,980 | utf_8 | e3023f3f40eba60be02de3b3ef113618 | function [ceiling_upperBound, ceiling_lowerBound, bestFitRDM]=ceilingAvgRDMcorr(refRDMestimates,RDMcorrelationType,monitor)
% Given a set of reference RDM estimates (e.g. from multiple subjects) in
% argument refRDMestimates, this function estimates upper and lower bounds
% on the ceiling, i.e. the highest average... |
github | rsagroup/rsatoolbox_matlab-master | fisherDiscrTRDM.m | .m | rsatoolbox_matlab-master/+rsa/+stat/fisherDiscrTRDM.m | 3,927 | utf_8 | f8e1cec7130187b350332053c5ff5e9c | function [RDM_fdtFolded_ltv, cv2RDM_fdt_sq] = fisherDiscrTRDM(Xa, Ya, Xb, Yb, condPredIs, RDMmask)
% USAGE
% [RDM_fdtFolded, sdRDM_fdt] = fisherDiscrTRDM(Xa, Ya, Xb, Yb[, condPredIs, RDMmask)
%
%
% computes a lower-triangular vector of Linear Discriminat t-statistics
% (RDM_fdtFolded_ltv) and a folded sym... |
github | rsagroup/rsatoolbox_matlab-master | exhaustivePermutations.m | .m | rsatoolbox_matlab-master/+rsa/+stat/exhaustivePermutations.m | 3,779 | utf_8 | e9e4ff52f3626c4a481afc95e4060993 | % permutations = exhaustivePermutations(n[, cap])
%
% n number of items to be permuted
% cap (optional) stop after finding this many
% permutations each row is a permutation; they'll be in lexicographic order
%
% Cai Wingfield 3-2010
function permutations = exhaustivePermutations(varargin)
% The following algor... |
github | rsagroup/rsatoolbox_matlab-master | randomPermutation.m | .m | rsatoolbox_matlab-master/+rsa/+stat/randomPermutation.m | 1,208 | utf_8 | cc190d60c8fedc5dc5b1ee0cc51b2dcf | function indicesOut = randomPermutation(n)
% generates a random vector of n integer numbers from 1 to n. The numbers
% are randomly placed in the vector.
% Cai Wingfield 2-2010
%__________________________________________________________________________
% Copyright (C) 2010 Medical Research Council
import rsa.*
import ... |
github | YingzhouLi/HMat-master | mempty.m | .m | HMat-master/HMat.m/src/@HMatrix/mempty.m | 1,366 | utf_8 | 0a971d973c880acc576ec6a660dad220 | function C = mempty(A,B)
C = HMatrix();
C.height = A.height;
C.width = B.width;
C.EPS = A.EPS;
C.MAXRANK = A.MAXRANK;
if A.blockType == 'E' || B.blockType == 'E'
C.blockType = 'E';
elseif A.blockType == 'D' || B.blockType == 'D'
C.blockType = 'D';
C.DMat = zeros(A.height,B.width);
elseif A.blockType == 'L... |
github | YingzhouLi/HMat-master | mrdivide.m | .m | HMat-master/HMat.m/src/@HMatrix/mrdivide.m | 4,234 | utf_8 | 9a7f72f8d0a21033822280e6ef09f59e | function C = mrdivide( A, B )
if isa(A,'HMatrix') && isa(B,'HMatrix')
C = mempty(A,B');
C = hmrdivideh(A,B,C);
elseif isa(A,'LRMatrix') && isa(B,'HMatrix')
C = LRMatrix(A.UMat,A.VMat'/B,A.EPS,A.MAXRANK);
elseif isa(B,'HMatrix')
C = dmrdivideh(A,B);
elseif isa(A,'HMatrix')
C = H2D(A)/B;
end
end
fu... |
github | YingzhouLi/HMat-master | times.m | .m | HMat-master/HMat.m/src/@HMatrix/times.m | 2,458 | utf_8 | 2ee8d5e3a704a9f90e7a271f037eb6a6 | function C = times( A, B )
if isa(A,'HMatrix') && isa(B,'HMatrix')
C = htimesh(A,B);
elseif isa(A,'HMatrix') && isa(B,'LRMatrix')
C = htimesl(A,B);
elseif isa(A,'LRMatrix') && isa(B,'HMatrix')
C = ltimesh(A,B);
else
C = H2D(A) .* H2D(B);
end
end
function C = htimesh(A,B)
if A.blockType == 'L'
LR... |
github | YingzhouLi/HMat-master | plus.m | .m | HMat-master/HMat.m/src/@HMatrix/plus.m | 2,502 | utf_8 | 967f44ae9cd4f48f430f8936d4698add | function C = plus( A, B )
if isa(A,'HMatrix') && isa(B,'HMatrix')
C = hplush(A,B);
elseif isa(A,'HMatrix') && isa(B,'LRMatrix')
C = hplusl(A,B);
elseif isa(A,'LRMatrix') && isa(B,'HMatrix')
C = lplush(A,B);
else
C = H2D(A) + H2D(B);
end
end
function C = hplush(A,B)
if A.blockType == 'L'
LRMat = ... |
github | YingzhouLi/HMat-master | mtimes.m | .m | HMat-master/HMat.m/src/@HMatrix/mtimes.m | 3,957 | utf_8 | fa65e015ca77b6604980a654a72f2f15 | function C = mtimes( A, B )
if isa(A,'HMatrix') && isa(B,'HMatrix')
C = mempty(A,B);
C = hmtimesh(A,B,C);
elseif isa(A,'HMatrix') && isa(B,'LRMatrix')
C = LRMatrix(A*B.UMat,B.VMat,B.EPS,B.MAXRANK);
elseif isa(A,'LRMatrix') && isa(B,'HMatrix')
C = LRMatrix(A.UMat,A.VMat'*B,A.EPS,A.MAXRANK);
elseif isa(A... |
github | YingzhouLi/HMat-master | mldivide.m | .m | HMat-master/HMat.m/src/@HMatrix/mldivide.m | 4,227 | utf_8 | 12fee6e6b0bf0446430700a09010c16c | function C = mldivide( A, B )
if isa(A,'HMatrix') && isa(B,'HMatrix')
C = mempty(A',B);
C = hmldivideh(A,B,C);
elseif isa(A,'HMatrix') && isa(B,'LRMatrix')
C = LRMatrix(A\B.UMat,B.VMat,B.EPS,B.MAXRANK);
elseif isa(A,'HMatrix')
C = hmldivided(A,B);
elseif isa(B,'HMatrix')
C = A\H2D(B);
end
end
fun... |
github | YingzhouLi/HMat-master | minus.m | .m | HMat-master/HMat.m/src/@HMatrix/minus.m | 2,508 | utf_8 | 28caf906a55cdf0be1465de58a9ad0df | function C = minus( A, B )
if isa(A,'HMatrix') && isa(B,'HMatrix')
C = hminush(A,B);
elseif isa(A,'HMatrix') && isa(B,'LRMatrix')
C = hminusl(A,B);
elseif isa(A,'LRMatrix') && isa(B,'HMatrix')
C = lminush(A,B);
else
C = H2D(A) - H2D(B);
end
end
function C = hminush(A,B)
if A.blockType == 'L'
LRM... |
github | vislab-tecnico-lisboa/vizzy-master | WaistLeftArmFwdKinVizzy.m | .m | vizzy-master/vizzy_description/kinematic_description_matlab/waist_left_arm_fwd_kin/WaistLeftArmFwdKinVizzy.m | 6,029 | utf_8 | c1855a112fccab3118872cb8e8bf65d8 | % Edited by Plinio Moreno
% Lisbon Nov 2014
% This function computes the vizzy left arm forward kinematic as
% described by the CAD files. The kinematics include the
% waist. Parameters are given according to the DH notation. Global
% forward kinematic is given by T_Ro0 * T_0n.
%
% Usage:
%
% [T_Ro0, T_0n, rpy_R... |
github | vislab-tecnico-lisboa/vizzy-master | WaistRightArmFwdKinVizzy.m | .m | vizzy-master/vizzy_description/kinematic_description_matlab/waist_right_arm_fwd_kin/WaistRightArmFwdKinVizzy.m | 5,911 | utf_8 | 72942fae1a146259ee94c77452d565ad | % Edited by Plinio Moreno
% Lisbon Nov 2014
% This function computes the vizzy right arm forward kinematic as
% described by the CAD files. The kinematics include the
% waist. Parameters are given according to the DH notation. Global
% forward kinematic is given by T_Ro0 * T_0n.
%
% Usage:
%
% [T_Ro0, T_0n, rpy_... |
github | vislab-tecnico-lisboa/vizzy-master | WaistHeadFwdKinVizzy.m | .m | vizzy-master/vizzy_description/kinematic_description_matlab/waist_head_fwd_kin/WaistHeadFwdKinVizzy.m | 8,042 | utf_8 | cf0c082286b43c174908978fec5a9593 | % Edited by Plinio Moreno
% Lisbon Nov 2014
% This function computes the vizzy head forward kinematic as
% described by the CAD files, including the inertial sensor.
% The kinematics include the
% iCub waist. Parameters are given according to the DH notation. Global
% forward kinematic for the right eye are give... |
github | vislab-tecnico-lisboa/vizzy-master | RightWristThumbFwdKinVizzy.m | .m | vizzy-master/vizzy_description/kinematic_description_matlab/right_wrist_fingers_fwd_kin/RightWristThumbFwdKinVizzy.m | 3,438 | utf_8 | cf9ce01d8b958b1962065c9b99aa1510 | % Edited by Plinio Moreno
% Lisbon Nov 2014
% This function computes the vizzy left arm forward kinematic as
% described by the CAD files. The kinematics include the
% waist. Parameters are given according to the DH notation. Global
% forward kinematic is given by T_Ro0 * T_0n.
%
% Usage:
%
% [T_Ro0, T_0n, rpy_R... |
github | poliquin/io273-master | gibbs2.m | .m | io273-master/ps3/gibbs2.m | 10,367 | utf_8 | 5422f07a32a24498ba5e0667c18edd12 | %% Question 2 - Gibbs
% These functions estimate the Gibbs sampler for pset 3.
function [ALPHA, BETA, SIGMA, ystr] = gibbs2(Y,X,runs,initbeta,initsigma)
% Returns results from Gibbs Multinomial Probit
% INPUTS
% Y = N by 1 vector
% X = N*K by P vector
% P denotes the number of parameters ... |
github | poliquin/io273-master | gibbs.m | .m | io273-master/ps3/gibbs.m | 10,948 | utf_8 | 7041d705df4e1fbe13c3ae24d04d1cff | %% Question 2 - Gibbs
% These functions estimate the Gibbs sampler for pset 3.
function [ALPHA, BETA, SIGMA, ystr] = gibbs(Y,X,runs,initbeta,initsigma)
% Returns results from Gibbs Multinomial Probit
% INPUTS
% Y = N by 1 vector
% X = N*K by P vector
% P denotes the number of parameters
... |
github | poliquin/io273-master | moment_inequalities.m | .m | io273-master/ps2/moment_inequalities.m | 3,940 | utf_8 | b5c1ff94f79926d2ebf1ddb86d6eaed0 | % moment_inequalities - Simulation estimator for entry without
% assumptions on order of entry. Procedure based on Ciliberto and Tamer
% (2009).
function obj = moment_inequalities(theta, mu, markets,firms, entry, u)
% model parameters
MU = mu;
ALPHA = theta(1); BETA = theta(2); DELTA = theta(3); SIGMA = thet... |
github | poliquin/io273-master | hessdiag.m | .m | io273-master/ps2/derivest/hessdiag.m | 2,034 | utf_8 | ff31ada116a5b893f0b1b7ad4ef6336f | function [HD,err,finaldelta] = hessdiag(fun,x0)
% HESSDIAG: diagonal elements of the Hessian matrix (vector of second partials)
% usage: [HD,err,finaldelta] = hessdiag(fun,x0)
%
% When all that you want are the diagonal elements of the hessian
% matrix, it will be more efficient to call HESSDIAG than HESSIAN.
% HESSDIA... |
github | poliquin/io273-master | hessian.m | .m | io273-master/ps2/derivest/hessian.m | 5,157 | utf_8 | 8e0bddd9a2df4151adbee6e016f767cf | function [hess,err] = hessian(fun,x0)
% hessian: estimate elements of the Hessian matrix (array of 2nd partials)
% usage: [hess,err] = hessian(fun,x0)
%
% Hessian is NOT a tool for frequent use on an expensive
% to evaluate objective function, especially in a large
% number of dimensions. Its computation will use rough... |
github | poliquin/io273-master | jacobianest.m | .m | io273-master/ps2/derivest/jacobianest.m | 5,850 | utf_8 | eb3dd9ff0c56b1eb7316f8237dbee253 | function [jac,err] = jacobianest(fun,x0)
% gradest: estimate of the Jacobian matrix of a vector valued function of n variables
% usage: [jac,err] = jacobianest(fun,x0)
%
%
% arguments: (input)
% fun - (vector valued) analytical function to differentiate.
% fun must be a function of the vector or array x0.
%
%... |
github | poliquin/io273-master | gradest.m | .m | io273-master/ps2/derivest/gradest.m | 2,374 | utf_8 | 8164711b2f9bdaae657fae039afd34f0 | function [grad,err,finaldelta] = gradest(fun,x0)
% gradest: estimate of the gradient vector of an analytical function of n variables
% usage: [grad,err,finaldelta] = gradest(fun,x0)
%
% Uses derivest to provide both derivative estimates
% and error estimates. fun needs not be vectorized.
%
% arguments: (input)
% fun ... |
github | poliquin/io273-master | derivest.m | .m | io273-master/ps2/derivest/derivest.m | 23,018 | utf_8 | 3198e9636b2275d707eec59dbb9b8a2f | function [der,errest,finaldelta] = derivest(fun,x0,varargin)
% DERIVEST: estimate the n'th derivative of fun at x0, provide an error estimate
% usage: [der,errest] = DERIVEST(fun,x0) % first derivative
% usage: [der,errest] = DERIVEST(fun,x0,prop1,val1,prop2,val2,...)
%
% Derivest will perform numerical differentiatio... |
github | poliquin/io273-master | sec3q2c.m | .m | io273-master/ps1/sec3q2c.m | 4,283 | utf_8 | 37a43ce0433f6c76008fa38b2dbf2d21 | function [] = sec3q2c()
% SEC3Q2C Estimate demand/supply model under different conduct assumptions
runs = 1; % number of times to run each model
data = load('data/100_3.mat');
cost = data.cost;
eta = data.eta;
prices = data.prices;
prods = data.prods;
%profits = data.profits;
shares = data.shares;
%surplus = data.s... |
github | poliquin/io273-master | mktsim.m | .m | io273-master/ps1/mktsim.m | 6,049 | utf_8 | eeb034d4880ed9bd848b5712d04103c5 | function [shares, prices, prods, profits, surplus, xi, W, z, eta] = mktsim(j, m)
%MKTSIM Draw j products in m markets for BLP simulation.
% Simulate 500 individuals per market for m markets with j products,
% creating characteristics, cost shifters, prices, and market shares.
% Input arguments:
... |
github | poliquin/io273-master | merger_foc.m | .m | io273-master/ps1/merger_foc.m | 776 | utf_8 | d1315f019e9766ce6bce1637ae60d697 | function foc = merger_foc(P,MC,X,BETA,ALPHA,XI,NU,SIGMA,merger)
[shares, sim_DS,sim_XDS]=merger_shr(P,X,BETA,ALPHA,XI,NU,SIGMA);
%MERGER_EQUILIBRIUM:
coeffmat = [0,1,0;1,0,1;0,0,0];
if merger
foc = shares + (P-MC).*sim_DS + coeffmat*(P-MC).*sim_XDS;
else
foc = shares + (P-MC).*sim_... |
github | ENSTABretagneRobotics/moos-ivp-enstabretagne-master | text.m | .m | moos-ivp-enstabretagne-master/scripts/kml/@kml/text.m | 1,699 | utf_8 | e223a6c06b55ec49f50f03f9ad27196e | function target = text(this,long,lat,alt,txt,varargin)
%KML.TEXT(long,lat,alt,txt) Writes the text given by txt at the coordinates
% given by long, lat and alt. To write in more than one coordinate, pass an
% array of coordinates, and a cell of texts, with the same number of members.
%
% Copyright 2012 Rafa... |
github | ENSTABretagneRobotics/moos-ivp-enstabretagne-master | poly.m | .m | moos-ivp-enstabretagne-master/scripts/kml/@kml/poly.m | 1,252 | utf_8 | e9e479698670f5053c919a1bcfd72f88 | function target = poly(this,long,lat,varargin)
%KML.POLY(long,lat) Draw a closed polygon with vertices given by long, lat.
% To change the altitude of the polygon, use KML.POLY(...,'altitude', 10000)
%
% Copyright 2012 Rafael Fernandes de Oliveira (rafael@rafael.aero)
% $Revision: 2.3 $ $Date: 2012/09/05 0... |
github | ENSTABretagneRobotics/moos-ivp-enstabretagne-master | transfer.m | .m | moos-ivp-enstabretagne-master/scripts/kml/@kml/transfer.m | 6,885 | utf_8 | c26057fea7de2d53b610a075ccec1655 | function target = transfer(this,axisHandle,varargin)
%KML.TRANSFER(ax) Transfer the axis from the handle ax to the KML as an overlay.
% Example:
% k = kml;
% t = linspace(0,2*pi,1000);
% figure;
% plot(t,sin(t));
% k.transfer(gca)
% k.run
%
% The corners of the overlay are taken from the axis limits... |
github | SimonSegerblomRex/tdoa-master | matchingdelays.m | .m | tdoa-master/matlab/matchingdelays.m | 1,518 | utf_8 | cd02e41f2593e253b1ea19d037f3f983 | function uref = matchingdelays(u,settings)
%MATCHINGDELAYS - Limits the delay candidates
%
% This function...
%
% uref = MATCHINGDELAYS(u,settings)
%
% Input:
% u - delay data output from getdelays
% settings - struct that must have...
%
% Output:
% uref - delays for
channels = sett... |
github | DobyRahnev/Confidence-leak-master | spear.m | .m | Confidence-leak-master/helperFunctions/spear.m | 2,353 | utf_8 | 3df82b087c5ebe9f07043b7c0d7658d4 | function [r,t,p]=spear(x,y)
%Syntax: [r,t,p]=spear(x,y)
%__________________________
%
% Spearman's rank correalation coefficient.
%
% r is the Spearman's rank correlation coefficient.
% t is the t-ratio of r.
% p is the corresponding p-value.
% x is the first data series (column).
% y is the second data serie... |
github | DobyRahnev/Confidence-leak-master | type2ag.m | .m | Confidence-leak-master/helperFunctions/type2ag.m | 6,791 | utf_8 | e7b49c612ccf6c07129982eca84104ca | function [obs_Ag, exp_Ag, ROCpoints] = type2ag(nR_S1, nR_S2, eqvar, doPlot)
% [obs_Ag, exp_Ag, ROCpoints] = type2ag(nR_S1, nR_S2, eqvar, doPlot)
%
% input
% nR_S1, nR_S2 : response counts for S1 and S2 stimuli
% eqvar : 1 if assuming equal variance SDT model, 0 otherwise (requires
% SDT_MLE_fit)
% doPlot : Plot... |
github | andreikarpau/DataScienceRepo-master | submit.m | .m | DataScienceRepo-master/Machine Learning Course Projects/Recommender Systems/submit.m | 17,515 | utf_8 | f1320acecad5e41355ce270b4195c3db | function submit(partId, webSubmit)
%SUBMIT Submit your code and output to the ml-class servers
% SUBMIT() will connect to the ml-class server and submit your solution
fprintf('==\n== [ml-class] Submitting Solutions | Programming Exercise %s\n==\n', ...
homework_id());
if ~exist('partId', 'var') || isem... |
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