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 | tsajed/nmr-pred-master | secularity.m | .m | nmr-pred-master/spinach/kernel/legacy/secularity.m | 437 | utf_8 | 4dececf297c793c5ecc049c8cc08358f | % A trap for legacy function calls.
%
% i.kuprov@soton.ac.uk
function secularity(varargin)
% Direct the user to the new function
error('This function is deprecated, use assume() instead.');
end
% You told us you would release Spinach on 1 October 2011 and you actually
% released Spinach on 1 October 20... |
github | tsajed/nmr-pred-master | contour_plot.m | .m | nmr-pred-master/spinach/kernel/legacy/contour_plot.m | 597 | utf_8 | 0a8656a515a8827cca670b531c450d13 | % A trap for legacy function calls.
%
% i.kuprov@soton.ac.uk
function contour_plot(varargin)
% Direct the user to the new function
error('This function is deprecated, use plot_2d() instead.');
end
% According to a trade legend, Uhlenbeck and Goudsmit (students of
% Ehrenfest when they stumbled upon an e... |
github | tsajed/nmr-pred-master | combnk.m | .m | nmr-pred-master/spinach/kernel/external/combnk.m | 1,407 | utf_8 | 9e6b7b79ccf707597f84b82264aee2da | % All combinations of the N elements in V taken K at a time.
% C = COMBNK(V,K) produces a matrix, with K columns. Each row of C has
% K of the elements in the vector V. C has N!/K!(N-K)! rows. K must be
% a nonnegative integer.
%
% Copyright 1993-2004 The MathWorks, Inc.
% $Revision: 2.12.2.2 $ $Date: 20... |
github | tsajed/nmr-pred-master | phantom3d.m | .m | nmr-pred-master/spinach/kernel/external/phantom3d.m | 7,917 | utf_8 | 54651ef6f65a0fe3d1d5e068339b469b | % Three-dimensional analogue of MATLAB Shepp-Logan phantom. Generates a 3D
% head phantom that can be used to test 3-D reconstruction algorithms.
%
% DEF is a string that specifies the type of head phantom to generate.
% Valid values are:
%
% 'Shepp-Logan' A test image used widely by rese... |
github | tsajed/nmr-pred-master | lgwt.m | .m | nmr-pred-master/spinach/kernel/external/lgwt.m | 1,126 | utf_8 | ac4205aaceb3726f4eea42d9460d9ec6 | % This script is for computing definite integrals using Legendre-Gauss
% Quadrature. Computes the Legendre-Gauss nodes and weights on an interval
% [a,b] with truncation order N
%
% Suppose you have a continuous function f(x) which is defined on [a,b]
% which you can evaluate at any x in [a,b]. Simply evaluate i... |
github | tsajed/nmr-pred-master | b2r.m | .m | nmr-pred-master/spinach/kernel/external/b2r.m | 1,889 | utf_8 | 20310193c425104c056c7e75205b86af | % Blue -> white -> red color map. White always corresponds
% to value zero.
%
% Cunjie Zhang
% Ilya Kuprov
function newmap=b2r(cmin,cmax)
% Check the input
if nargin~=2
error('incorrect number of input arguments.')
end
if cmin>=cmax
error('the first argument must be smaller than the second one.... |
github | tsajed/nmr-pred-master | jacobianest.m | .m | nmr-pred-master/spinach/kernel/external/jacobianest.m | 5,840 | utf_8 | 4c955378155f9dffa7cf48c2abaab7d7 | 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 | tsajed/nmr-pred-master | expv.m | .m | nmr-pred-master/spinach/kernel/external/expv.m | 4,863 | utf_8 | c8732ae90e0aa822b4d89d0835ebf115 | % [w, err, hump] = expv( t, A, v, tol, m )
% EXPV computes an approximation of w = exp(t*A)*v for a
% general matrix A using Krylov subspace projection techniques.
% It does not compute the matrix exponential in isolation but instead,
% it computes directly the action of the exponential operator on the
% operan... |
github | tsajed/nmr-pred-master | fourdif.m | .m | nmr-pred-master/spinach/kernel/external/fourdif.m | 2,782 | utf_8 | a00d709f10e1499cbbbdaad00c7907a4 | % The function [x, DM] = fourdif(N,m) computes the m'th derivative Fourier
% spectral differentiation matrix on grid with N equispaced points in [0,2pi)
%
% Input:
% N: Size of differentiation matrix.
% M: Derivative required (non-negative integer)
%
% Output:
% x: Equispaced points 0, 2pi/N... |
github | tsajed/nmr-pred-master | simps.m | .m | nmr-pred-master/spinach/kernel/external/simps.m | 3,044 | utf_8 | f3d545adb2c382d803770cbc778b8c92 | % Simpson's numerical integration.
%
% Z = SIMPS(Y) computes an approximation of the integral of Y using
% Simpson's method (with unit spacing). To compute the integral for
% spacing different from one, multiply Z by the spacing increment.
%
% For vectors, SIMPS(Y) is the integral of Y. For matrices, SIMPS(Y)
%... |
github | unamfi/Cuantizacion-vectorial-master | LPCC.m | .m | Cuantizacion-vectorial-master/LPCC.m | 2,289 | utf_8 | 3352b9c3cd158718279a760df20b0e89 | %% LPCC
function LPCCres = LPCC(s)
[R LPC p] = lpc(s);
Q = 3*p/2;
for i=1:1:length(LPC)
C = zeros(1,Q+1);
C(1) = log(sqrt(R{i}(1)));
for m=1:Q
if m>=1 && m<=p
C(m+1)=LPC{i}(m);
for k=1:m-1
... |
github | unamfi/Cuantizacion-vectorial-master | Itakura.m | .m | Cuantizacion-vectorial-master/Itakura.m | 97 | utf_8 | a77eac098d163cc4aa6e1add2ecccb08 | %% ITAKURA
function d = Itakura(y,Ry,x)
d = log((x*Ry*transpose(x))/(y*Ry*transpose(y))); |
github | unamfi/Cuantizacion-vectorial-master | kMedias.m | .m | Cuantizacion-vectorial-master/kMedias.m | 1,202 | utf_8 | ef907879c1d603d0e3a63604aae4a1e7 | %% K-MEDIAS
function centroides = kMedias(vectores,k)
for i = 1:k
z{i} = vectores{i};
zAnt{i} = zeros(1,length(vectores{i}));
end
while notEqual(z,zAnt,k)
zAnt = z;
display('entro')
for vector = 1:length(vectores)
... |
github | shuoli-robotics/ppzr-master | dialog.m | .m | ppzr-master/sw/logalizer/dialog.m | 34,826 | utf_8 | 5407ab492113a3d0358e62c19dc1feab | %--------------------------------------------------------------------
%A simple MATLAB GUI for paparazzi autopilot log-file plotting
%Paparazzi Project [http://www.nongnu.org/paparazzi/]
%by Roman Krashhanitsa 28/10/2005
%adjustable parabeters:
% maxnum - increase if dialog window hangs up or doesnt refresh
% Nres - nu... |
github | shuoli-robotics/ppzr-master | dialog.m | .m | ppzr-master/sw/logalizer/matlab_log/dialog.m | 41,728 | utf_8 | 8a40368512745e70d158a49ee08c5926 | %--------------------------------------------------------------------
%A simple MATLAB GUI for paparazzi autopilot log-file plotting
%Paparazzi Project [http://www.nongnu.org/paparazzi/]
%by Roman Krashhanitsa 28/10/2005
%adjustable parabeters:
% maxnum - increase if dialog window hangs up or doesnt refresh
% Nres - nu... |
github | shuoli-robotics/ppzr-master | tilt.m | .m | ppzr-master/sw/logalizer/matlab/tilt.m | 3,005 | utf_8 | 28f19a8ce44283009a8f4ba0410e4c0b | %
% this is a 2 states kalman filter used to fuse the readings of a
% two axis accelerometer and one axis gyro.
% The filter estimates the angle and the gyro bias.
%
%
function [angle, bias, rate, cov] = tilt(status, gyro, accel)
TILT_UNINIT = 0;
TILT_PREDICT = 1;
TILT_UPDATE = 2;
persistent tilt_angle; %... |
github | shuoli-robotics/ppzr-master | theta_of_accel.m | .m | ppzr-master/sw/logalizer/matlab/theta_of_accel.m | 186 | utf_8 | a68d408f14dcafd800965d810c91c1c1 | %
% return pitch angle from an accelerometer reading
% under assumption that acceleration is vertical
%
function [theta] = theta_of_accel(accel)
theta = -asin( accel(1) / norm(accel)); |
github | shuoli-robotics/ppzr-master | eulers_of_quat.m | .m | ppzr-master/sw/logalizer/matlab/eulers_of_quat.m | 334 | utf_8 | aa4e8f9fcedb41872e29eb098aefa7d3 | %
% initialise euler angles from a quaternion
%
function [eulers] = eulers_of_quat(quat)
q0 = quat(1);
q1 = quat(2);
q2 = quat(3);
q3 = quat(4);
phi = atan2(2*(q2*q3 + q0*q1), (q0^2 - q1^2 - q2^2 + q3^2));
theta = asin(-2*(q1*q3 - q0*q2));
psi = atan2(2*(q1*q2 + q0*q3), (q0^2 + q1^2 - q2^2 - q3^2));
eulers = [phi t... |
github | shuoli-robotics/ppzr-master | synth_data.m | .m | ppzr-master/sw/logalizer/matlab/synth_data.m | 923 | utf_8 | c23bbe3eb4319edf0890fc9bc4b033c2 |
%
% build synthetic data
%
function [t, rates, quat] = synth_data(dt, nb_samples)
t_end = dt * (nb_samples - 1);
t = 0:dt:t_end;
rates = zeros(3, nb_samples);
omega_q = 15;
amp_q = 2;
osc_start = floor(nb_samples/2);
osc_end = floor(osc_start+2*pi/(omega_q*dt));
for idx=osc_start:osc_end
rates(2, idx) = -amp_q*(... |
github | shuoli-robotics/ppzr-master | theta_of_quat.m | .m | ppzr-master/sw/logalizer/matlab/theta_of_quat.m | 182 | utf_8 | 1b15a8391b14bd82c12a4031d009657c | %
% initialise euler angles from a quaternion
%
function [theta] = theta_of_quat(quat)
q0 = quat(1);
q1 = quat(2);
q2 = quat(3);
q3 = quat(4);
theta = asin(-2*(q1*q3 - q0*q2));
|
github | shuoli-robotics/ppzr-master | synth_imu.m | .m | ppzr-master/sw/logalizer/matlab/synth_imu.m | 382 | utf_8 | eb83cb7d22000974d367cc96ef11e37f |
%
% build synthetic imu data
%
function [gyro, accel, mag] = synth_imu(rates, quat)
nb_samples = length(rates);
g_ned = [ 0
0
258.3275];
h_ned = [ 166.8120
0.0
203.3070];
for idx = 1:nb_samples
dcm = dcm_of_quat(quat(:, idx));
accel(:, idx) = sim_accel(g_ned, dcm);
mag(:, idx) = sim_mag(h_n... |
github | shuoli-robotics/ppzr-master | sfun_ahrs.m | .m | ppzr-master/sw/logalizer/matlab/sfun_ahrs.m | 7,062 | utf_8 | 738df5f0b69d65203e9e7dea9d2b8c41 |
function [sys,x0,str,ts] = sfun_ahrs(t,x,u,flag)
AHRS_UNINIT = 0;
AHRS_STEP_PHI = 1;
AHRS_STEP_THETA = 2;
AHRS_STEP_PSI = 3;
persistent ahrs_state;
persistent ahrs_quat; % first four elements of our state
persistent ahrs_biases;% last three elements of our state
persistent ahrs_rates; % we get unbiased body... |
github | shuoli-robotics/ppzr-master | quat_of_eulers.m | .m | ppzr-master/sw/logalizer/matlab/quat_of_eulers.m | 629 | utf_8 | 8783ebf9fadbb74652d2a366c9064c02 |
%
% initialise a quaternion from euler angles
%
function [quat] = quat_of_eulers(eulers)
phi2 = eulers(1) / 2.0;
theta2 = eulers(2) / 2.0;
psi2 = eulers(3) / 2.0;
sinphi2 = sin( phi2 );
cosphi2 = cos( phi2 );
sintheta2 = sin( theta2 );
costheta2 = cos( theta2 );
sinpsi2 = sin( psi2 );
cospsi2 = c... |
github | shuoli-robotics/ppzr-master | dcm_of_quat.m | .m | ppzr-master/sw/logalizer/matlab/dcm_of_quat.m | 481 | utf_8 | b9950e5f461f13427a7c670158a92c14 | %
% initialise a DCM from a quaternion
%
function [dcm] = dcm_of_quat(quat)
q0 = quat(1);
q1 = quat(2);
q2 = quat(3);
q3 = quat(4);
dcm00 = q0^2 + q1^2 - q2^2 - q3^2;
dcm01 = 2 * (q1*q2 + q0*q3);
dcm02 = 2 * (q1*q3 - q0*q2);
dcm10 = 2 * (q1*q2 - q0*q3);
dcm11 = q0^2 - q1^2 + q2^2 - q3^2;
dcm12 = 2 * (q2*q3 + q0*q1);... |
github | shuoli-robotics/ppzr-master | ahrs.m | .m | ppzr-master/sw/logalizer/matlab/ahrs.m | 4,335 | utf_8 | 5723f910e49a91fc556660bc06826fa8 |
function [quat, biases] = ahrs(status, gyro, accel, mag)
AHRS_UNINIT = 0;
AHRS_STEP_PHI = 1;
AHRS_STEP_THETA = 2;
AHRS_STEP_PSI = 3;
persistent ahrs_quat;
persistent ahrs_biases;
persistent ahrs_rates;
persistent ahrs_P; % covariance matrix
persistent ahrs_Q; % estimate noise variance
ahrs_dt = 0.01... |
github | shuoli-robotics/ppzr-master | range_meter_accel_kalman.m | .m | ppzr-master/sw/logalizer/matlab/range_meter_accel_kalman.m | 2,603 | utf_8 | e73c363bd661f2f111583fc707bf8fde | %
%
%
%
function [sys,x0,str,ts] = range_meter_accel_kalman(t,x,u,flag)
period = 0.015625;
persistent X; % state (Z, Zdot, Zdotdot)
persistent P; % error covariance
switch flag,
%%%%%%%%%%%%%%%%%%
% Initialization %
%%%%%%%%%%%%%%%%%%
case 0,
X=[0. 0. 0.]';
P=[1. 0. 0.
0. 1. 0.
... |
github | shuoli-robotics/ppzr-master | psi_of_quat.m | .m | ppzr-master/sw/logalizer/matlab/psi_of_quat.m | 205 | utf_8 | 821c1b678bcc85fbf97dd6fe3a1b3e3d | %
% initialise euler angles from a quaternion
%
function [psi] = psi_of_quat(quat)
q0 = quat(1);
q1 = quat(2);
q2 = quat(3);
q3 = quat(4);
psi = atan2(2*(q1*q2 + q0*q3), (q0^2 + q1^2 - q2^2 - q3^2));
|
github | shuoli-robotics/ppzr-master | phi_of_quat.m | .m | ppzr-master/sw/logalizer/matlab/phi_of_quat.m | 205 | utf_8 | 577a048517be0669ac35e0f7fc8f3b30 | %
% initialise euler angles from a quaternion
%
function [phi] = phi_of_quat(quat)
q0 = quat(1);
q1 = quat(2);
q2 = quat(3);
q3 = quat(4);
phi = atan2(2*(q2*q3 + q0*q1), (q0^2 - q1^2 - q2^2 + q3^2));
|
github | shuoli-robotics/ppzr-master | phi_of_accel.m | .m | ppzr-master/sw/logalizer/matlab/phi_of_accel.m | 175 | utf_8 | 7f341eaa185852c295e0a3d39219d885 | %
% returns roll angle from an accelerometer reading
% under assumption that acceleration is vertical
%
function [phi] = phi_of_accel(accel)
phi = atan2(accel(2), accel(3)); |
github | shuoli-robotics/ppzr-master | dcm_of_eulers.m | .m | ppzr-master/sw/logalizer/matlab/dcm_of_eulers.m | 607 | utf_8 | d49ff8d4658100d798e02d14b725d7b8 | %
% initialise a DCM from a set of eulers
%
function [dcm] = dcm_of_eulers(eulers)
phi = eulers(1);
theta = eulers(2);
psi = eulers(3);
dcm00 = cos(theta) * cos(psi);
dcm01 = cos(theta) * sin(psi);
dcm02 = -sin(theta);
dcm10 = sin(phi) * sin(theta) * cos(psi) - cos(phi) * sin(psi);
dcm11 = sin(phi) * sin(theta) * si... |
github | shuoli-robotics/ppzr-master | psi_of_mag.m | .m | ppzr-master/sw/logalizer/matlab/psi_of_mag.m | 1,076 | utf_8 | 04a2ed36a67c0a29c793684357f7f95d | %
% return yaw angle from a magnetometer reading, knowing roll and pitch
%
% The rotation matrix to rotate from NED frame to body frame without
% rotating in the yaw axis is:
%
% [ 1 0 0 ] [ cos(Theta) 0 -sin(Theta) ]
% [ 0 cos(Phi) sin(Phi) ] [ 0 1 0 ]
% [ 0 -sin(Phi) cos(Phi)... |
github | shuoli-robotics/ppzr-master | normalize_quat.m | .m | ppzr-master/sw/logalizer/matlab/normalize_quat.m | 84 | utf_8 | 059325b9c340c1295d2d86b71c7f0d02 |
function [quat_out] = normalize_quat(quat_in)
quat_out = quat_in / norm(quat_in);
|
github | shuoli-robotics/ppzr-master | plot_prop.m | .m | ppzr-master/sw/logalizer/matlab/plot_prop.m | 1,636 | utf_8 | a1b37b753e6331884f03d5edc92a7ad1 | %
% plot a serie of measures realised with the black 10*4.5 prop
%
function [] = plot_prop()
rpm = [ 2800 3350 3720 4450 5250 ];
thrust_g = [ 122 175 219 310 445 ];
torque_g = [ 10 16 19 26 44 ];
omega = rpm / 60 * 2 * pi;
omega_square = omega.^2;
thrust_n = thrust_g .* (... |
github | shuoli-robotics/ppzr-master | eulers_ahrs.m | .m | ppzr-master/sw/logalizer/matlab/eulers_ahrs.m | 3,448 | utf_8 | ff18ecc6efcad8ecea4cb1c04b4153e3 |
function [eulers, biases] = eulers_ahrs(status, gyro, accel, mag, dt)
AHRS_UNINIT = 0;
AHRS_PREDICT = 1;
AHRS_UPDATE_PHI = 2;
AHRS_UPDATE_THETA = 3;
AHRS_UPDATE_PSI = 4;
persistent ahrs_eulers;
persistent ahrs_biases;
persistent ahrs_rates;
persistent ahrs_P;
if (status == AHRS_UNINIT)
[ahrs_eul... |
github | shuoli-robotics/ppzr-master | eulers_of_quat.m | .m | ppzr-master/sw/airborne/test/ahrs/plot/eulers_of_quat.m | 789 | utf_8 | e5d898a1c84e280d2b3097f8a270c990 | %% EULERS OF QUATERNION
%
% [euler] = eulers_of_quat(quat)
%
% transposes a quaternion to euler angles
function [euler] = eulers_of_quat(quat)
algebra_common;
if size(quat)(2)==4
quat = quat';
transpose = 1;
end
dcm00 = 1.0 - 2*(quat(Q_QY,:).*quat(Q_QY,:) + quat(Q_QZ,:).*quat(Q_QZ,:));
dcm01 ... |
github | shuoli-robotics/ppzr-master | unwrap.m | .m | ppzr-master/sw/airborne/test/ahrs/plot/unwrap.m | 360 | utf_8 | 88eb2f76dedb25dfbdeb635ff1af9f1e | %% unwrap
%
% [unwraped] = unwrap(wraped)
%
%
function [unwraped] = unwrap(wraped)
unwraped = zeros(length(wraped), 1);
cnt = 0;
for i=2:length(wraped)
dif = wraped(i) - wraped(i-1);
if (dif > pi/2)
cnt=cnt-1;
elseif (dif <-pi/2)
cnt=cnt+1;
end
unwraped(i) =... |
github | shuoli-robotics/ppzr-master | deg_of_rad.m | .m | ppzr-master/sw/airborne/test/ahrs/plot/deg_of_rad.m | 124 | utf_8 | b8cf99172588f77a253dd84982a9d2e7 | %% degres of radians
%
% [deg] = deg_of_rad(rad)
%
%
function [deg] = deg_of_rad(rad)
deg = rad * 180 / pi;
endfunction |
github | wpisailbot/boat-master | MovableBallastSimulation.m | .m | boat-master/control/matlab/MovableBallastSimulation.m | 8,602 | utf_8 | 6afbd0132248cfbb2917460b1eed281a | function MovableBallastSimulation(x0, phigoal)
global Vmax ka ks kssq ku kf J Jmb rightingweight;
global Kfast Kslow pgoal;
pgoal = phigoal;
stage1 = 16/64;
stage2 = 16/64;
G = stage1 * stage2;
Vmax = 12;
mbmass = 10;
J = 12 * 1.2^2; % kg * m^2
Jmb = mbmass * .7^2; % kg * m^2
MBMotorStallTorque = 9.8 / G; % N-m
MBMoto... |
github | Yadaizi/LLC-image-classification-master | sp_find_sift_grid.m | .m | LLC-image-classification-master/sift/sp_find_sift_grid.m | 4,187 | utf_8 | 029daeb5a3d4d49bb26b0e1a64cc4b97 | function sift_arr = sp_find_sift_grid(I, grid_x, grid_y, patch_size, sigma_edge)
% parameters
num_angles = 8;
num_bins = 4;
num_samples = num_bins * num_bins;
alpha = 9;
if nargin < 5
sigma_edge = 1;
end
angle_step = 2 * pi / num_angles;
angles = 0:angle_step:2*pi;
angles(num_angles+1) = []; % bin ... |
github | erlichlab/elutils-master | test_nonblocking.m | .m | elutils-master/+net/test_nonblocking.m | 617 | utf_8 | 8e2a79f129ba256b08ce855cf41c2630 | function zmqlistener = test_nonblocking()
zmqlistener = timer();
zmqlistener.StartFcn = @setup_zmq;
zmqlistener.TimerFcn = @wait_for_msg;
zmqlistener.ExecutionMode = 'fixedSpacing';
zmqlistener.BusyMode = 'drop';
zmqlistener.Period = 2;
zmqlistener.TasksToExecute = +inf;
zmqlistener.Star... |
github | erlichlab/elutils-master | zmqhelper.m | .m | elutils-master/+net/zmqhelper.m | 5,299 | utf_8 | 66a815982b07bdab722a7ad311761f8b | classdef zmqhelper < handle
% The ZMQHandler class is a wrapper for the jeromq java class.
%
%
properties
url
socktype
socket
subscriptions
end
methods
function obj = zmqhelper(varargin)
if nargin == 0
... |
github | erlichlab/elutils-master | sig4inv.m | .m | elutils-master/+stats/sig4inv.m | 114 | utf_8 | 832d02d929f5449eafd190461040b711 |
function x=sig4inv(beta,y)
%% sig4
y0=beta(1);
a=beta(2);
x0=beta(3);
b=beta(4);
x = -b*log((a./(y-y0))-1)+x0; |
github | erlichlab/elutils-master | KernelRegressionA.m | .m | elutils-master/+stats/KernelRegressionA.m | 4,999 | utf_8 | dab81ba78e55468e744502b7999bcd76 | classdef KernelRegressionA
properties
baseline_per_trial = false
core_kernel % this is the matrix for a single kernel. Will use it as a convolution kernel
core_kernel_matrix % This is the core_kernel convolued with the event times.
event_times
kernel_bin_size = 0.01 % seconds
kernel_dof = 50
kernel_dur... |
github | erlichlab/elutils-master | sig4.m | .m | elutils-master/+stats/sig4.m | 173 | utf_8 | ff976a6673d16b218ccb1651af766178 | % y=sig4(beta,x)
% y0=beta(1);
% a=beta(2);
% x0=beta(3);
% b=beta(4);
function y=sig4(beta,x)
y0=beta(1);
a=beta(2);
x0=beta(3);
b=beta(4);
y=y0+a./(1+ exp(-(x-x0)./b)); |
github | erlichlab/elutils-master | nanstderr.m | .m | elutils-master/+stats/nanstderr.m | 142 | utf_8 | d09ca0d1a2ee8c2b698c5055f9e29d0e |
function y = nanstderr(x,dim)
if nargin==1
dim=1;
end
gd=sum(~isnan(x),dim);
y=nanstd(x,0,dim)./sqrt(gd-1);
y(y==Inf)=nan;
y(gd==0)=nan;
|
github | erlichlab/elutils-master | cellmean.m | .m | elutils-master/+stats/cellmean.m | 326 | utf_8 | 3582f4fc2f25ad0b0db1325cfddfabf2 |
function [mu, se]=cellmean(M,varargin)
% [mu, se]=cellmean(M,varargin)
dim=1;
utils.overridedefaults(who,varargin)
mu=nan(1,numel(M));
se=mu;
for fx=1:numel(M)
if numel(M{fx})<2
mu(fx)=nan;
se(fx)=nan;
else
mu(fx)=nanmean(M{fx},dim);
se(fx)=stats.nanstderr(M{fx},dim);
e... |
github | erlichlab/elutils-master | bootsigmoid_val.m | .m | elutils-master/+stats/bootsigmoid_val.m | 1,722 | utf_8 | 06b7b18967ce489fc03a39b3af42dbb8 | function [p,D]=bootsigmoid(A,B,varargin)
% [p,D]=bootsigmoid(A,B,varargin)
% Takes two sets of N x 2 binomial data A and B, and fits sigmoids to them
% both. It then uses the mean and covariance of the fits to calculate the
% distance (using the projection of the fits onto fisher's linear
% discriminant) of the fits. ... |
github | erlichlab/elutils-master | sig4_invB.m | .m | elutils-master/+stats/sig4_invB.m | 181 | utf_8 | c08cb89c2c6b4038f98284bc884f552e | % y=sig4(beta,x)
% y0=beta(1);
% a=beta(2);
% x0=beta(3);
% b=beta(4);
function y=sig4_invB(beta,x)
y0=beta(1);
a=beta(2);
x0=beta(3);
b=1./beta(4);
y=y0+a./(1+ exp(-(x-x0)./b)); |
github | erlichlab/elutils-master | sig2.m | .m | elutils-master/+stats/sig2.m | 120 | utf_8 | c287dd7909e5ebcb805a5626775fe6f9 | % y=sig2(beta,x)
% x0=beta(3);
% b=beta(4);
function y=sig2(beta,x)
x0=beta(1);
b=beta(2);
y=1./(1+ exp(-(x-x0)./b)); |
github | erlichlab/elutils-master | flda.m | .m | elutils-master/+stats/flda.m | 1,152 | utf_8 | 9bdfccc574b6158b470380ab74d3a6af |
function v=flda(varargin)
% v = flda(G1,G2)
% v = flda(mean1,mean2,cov1,cov2,n1,n2)
%
% v is fisher's linear discriminant between the two "groups" of data
% Using syntax 1
% G1 is an n x d matrix
% G2 is an m x d matrix
% Using syntax 2
% Group1 has mean mu1, covariance cov1, and n1 number of samples
% Group2 has mean... |
github | erlichlab/elutils-master | binned2.m | .m | elutils-master/+stats/binned2.m | 3,374 | utf_8 | b96f93e8a24ff24b02339784a67566ca | function [xbinc, ybinc, mu, se, n]=binned2(x,y,z, varargin)
% [binc, mu, se, n]=binned2(x,y,z,bin_e)
% Takes a vector x and a vector y and returns mean and standard error of
% values of z for bins of x and y.
%
% Input:
% x 1xn vector of x values to bin
% y 1xn vector of y values to bin
% z 1xn vector of z... |
github | erlichlab/elutils-master | align_hv.m | .m | elutils-master/+stats/align_hv.m | 3,594 | utf_8 | 5e557d2b0e614ee7d069e455658e2889 | function [offset,inc_t,x,y]=align_hv(ev,ts,val,varargin)
% [offset,inc_t,x,y]=align_hv(ev, ts,val, varargin)
%
% pairs={'pre' 3;...
% 'post' 3;...
% 'binsz' 0.001;...
% 'meanflg' 0;...
% 'krn' 0.25;...
% 'max_offset' 1;...
% 'pre_mask', -inf;...
% 'p... |
github | erlichlab/elutils-master | sig3.m | .m | elutils-master/+stats/sig3.m | 239 | utf_8 | 031ac0a7d8b32a57722315ef985581b3 | % y=sig4(beta,x)
% y0=beta(1);
% a=beta(2);
% x0=beta(3);
% b=beta(4);
function y=sig3(beta,X)
x0=beta(1);
b=beta(2);
w=beta(3);
dx=X(:,2)-X(:,1);
L=X(:,1);
R=X(:,2);
w=min(max(w,0),1);
y=1./(1+ exp(-(dx-x0)./((1+w*R+(1-w)*L).^b))); |
github | erlichlab/elutils-master | stderr.m | .m | elutils-master/+stats/stderr.m | 101 | utf_8 | 70cccd93f718ca93def51627c9e5d4da |
function y=stderr(x,dim)
if ~exist('dim','var')
dim=1;
end
y=std(x,0,dim)/sqrt(size(x,dim)-1); |
github | erlichlab/elutils-master | sig5.m | .m | elutils-master/+stats/sig5.m | 265 | utf_8 | 0e840ad915c8b249461ff617952c70f1 | % y=sig4(beta,x)
% y0=beta(1);
% a=beta(2);
% x0=beta(3);
% b=beta(4);
function y=sig5(beta,X)
y0=beta(1);
a=beta(2);
x0=beta(3);
b=beta(4);
w=beta(5);
dx=X(:,2)-X(:,1);
rx=X(:,2);
lx=X(:,1);
w=min(max(0,w),1);
y=y0+a./(1+ exp(-(dx-x0)./((w*rx+(1-w)*lx).^b))); |
github | erlichlab/elutils-master | untiedrank.m | .m | elutils-master/+stats/untiedrank.m | 1,862 | utf_8 | 6209b20bdf331ab606146b08e4c2e830 | function r = untiedrank(x)
% function r = untiedrank(x)
%
% Similar to tiedrank, but arbitrarily breaks ties (with consistency each
% time called)
% reset random number generator to same start
% RandStream.setDefaultStream(RandStream('mrg32k3a','Seed',10));
RandStream.setGlobalStream(RandStream('mrg32k3a','Seed',10));... |
github | erlichlab/elutils-master | softplus.m | .m | elutils-master/+stats/softplus.m | 337 | utf_8 | 7d105e1e04014e4ca55b507a27f2307e |
function y=softplus(beta,x)
% y=softplus(beta,x)
% a=beta(1);
% x0=beta(2);
% b=beta(3);
a=beta(1);
x0=beta(2);
b=beta(3);
y = a.*(log(1 + exp((x - x0).*b)));
y/a = log(1 + exp(x-x0)*b)
exp(y/a) = 1 + exp(x-x0)*b
exp(y/a) - 1 = exp(x-x0)*b
b*(exp(y/a) - 1 = exp(x-x0)
log(b*exp(y) - a - 1) = x - x0
y = log(b*(e... |
github | erlichlab/elutils-master | sig4m.m | .m | elutils-master/+stats/sig4m.m | 219 | utf_8 | 05fdc096552ca475647fbe1ea82ca18f | % y=sig4(beta,x)
% y0=beta(1);
% a=beta(2);
% x0=beta(3);
% b=beta(4);
function y=sig4m(beta,X)
y0=beta(1);
a=beta(2);
x0=beta(3);
b=beta(4);
dx=X(:,2)-X(:,1);
sx=X(:,2)+X(:,1);
y=y0+a./(1+ exp(-(dx-x0)./(sx.^b))); |
github | erlichlab/elutils-master | number_of_pairs.m | .m | elutils-master/+stats/number_of_pairs.m | 1,817 | utf_8 | 98688df40539000277d8a7cf6dd31647 | % [n] = number_of_pairs(sh, p) Compute number of expected simultaneously-recorded pairs of "interesting" neurons
%
% Given a histogram of (# of sessions) versus (# of single-units recorded
% per session), and given a probability of a neuron being an "interesting"
% neuron (i.e., having a high enough firing rate, task... |
github | erlichlab/elutils-master | loglikelihood.m | .m | elutils-master/+stats/loglikelihood.m | 917 | utf_8 | e4392f988006d99eee42fadd1ad6a4a0 | % [L,bic]=loglikelihood(M,y,np)
%
% Input
% M: a vector of probabilities (model predictions)
% y: a vector of binomial outcomes
% np: the number of parameters in the model
%
% Output
% L: the log likelihood
% bic: the bayesian information criteria
function [L,bic]=loglikelihood(M,y,np)
% if isnumeric(M)
N = nan+... |
github | erlichlab/elutils-master | rm_nans.m | .m | elutils-master/+db/rm_nans.m | 333 | utf_8 | 0cf78edb18bd0054cdeece3c5559a2c9 |
function S = rm_nans(S)
% This is useful since NaNs can't be sent to the DB.
fnames = fieldnames(S);
for fx = 1:numel(fnames)
try
if isnan(S.(fnames{fx}))
S = rmfield(S,fnames{fx});
end
catch me
% Skip for fields that can't be tested for nan.
e... |
github | erlichlab/elutils-master | labdb.m | .m | elutils-master/+db/labdb.m | 12,393 | utf_8 | b2b6dd69cc2d0ad6541952434691faa5 | classdef (Sealed) labdb < handle
% Class labdb
% This is a wrapper class for the JDBC MySQL driver.
% It has several features which are generally useful
% 1. It reads credentials configurations from ~/.dbconf so that you don't have to type in credentials or store them in code.
% 2. It maintains a single connection per ... |
github | erlichlab/elutils-master | drawgaussian.m | .m | elutils-master/+draw/drawgaussian.m | 2,055 | utf_8 | 5ec4d56c987f84917fba34d436c525cd | %drawgaussian Draw the 1-sigma lines for a 2d gaussian
%
% [h] = drawgaussian(mean, [sigmax, sigmay, r | C], ...
% {'angstart', 0}, {'angend', 360}, {'useC', 0})
%
% Draws the nth-sigma lines for a gaussian in the current
% figure. Since it uses LINE to do this, it returns a handle to
% that line.
%
%... |
github | erlichlab/elutils-master | shadeplot2.m | .m | elutils-master/+draw/shadeplot2.m | 8,902 | utf_8 | 5dd5f789c4d2ec7140fb7028dc7f27ec | function fhand=shadeplot2(x,y1,y2,varargin)
%
% shadeplot2(x,y1,y2,settings)
% plots two shaded regions without the use of alpha, this allows the renderer to be
% set as painters rather than openGL, giving a vector rather than raster image.
% use shadeplot to quickly view graphs and choose colors, use shadeplo... |
github | erlichlab/elutils-master | histsig.m | .m | elutils-master/+draw/histsig.m | 2,024 | utf_8 | 316408eb6cf67188ef14a168aadd6c59 | function [ hx]=histsig(x, x_sig, varargin)
% [ hx]=histsig(x, x_sig, x_lim)
inpd = @utils.inputordefault;
[origin, args]=inpd('origin', 0.1, varargin);
[wdth, args]=inpd('width',0.2,args);
[hist_h, args]=inpd('height',0.180,args);
[num_bins, args]=inpd('n_bins',17,args);
[bins, args]=inpd('bins',[],args);
[ax, args]... |
github | erlichlab/elutils-master | isosum_psycho.m | .m | elutils-master/+draw/isosum_psycho.m | 2,131 | utf_8 | 26192d5421145a85a198eccfe1297c00 | % [X Y E]= isosum_psycho(x1,x2,wr,varargin)
% A function to plot psychometrics with isosum lines.
function [X Y E bfit bci]= isosum_psycho(x1,x2,wr,varargin)
nsumbins=5;
sum_bin_e=[];
x_bin_e=[];
nxbins=6;
ax=[];
plot_it=true;
clrs=[.85 0 0;
0 .1 .8;
0 .8 .1;
.8 0 1;
1 .5 0;
... |
github | erlichlab/elutils-master | unity.m | .m | elutils-master/+draw/unity.m | 474 | utf_8 | a15b90de629093e2f2703b1e54bcfe07 | % This function draws an unity line on the plot.
%h=unity(ax,s)
% ax (optional) plot to this axis, default gca
% s (optional) use this linestyle, default ':k'
function h=unity(ax,s)
if nargin<2
s=':k';
end
if nargin<1
ax=gca;
end
bax=ax;
for axx=1:numel(bax)
ax=bax(axx);
oldhold=get(ax,'NextPlot');
xlim=get(ax, ... |
github | erlichlab/elutils-master | task_timing.m | .m | elutils-master/+draw/task_timing.m | 1,446 | utf_8 | fda761f48f0aeadf229643406b1b62b1 | function task_timing(statetable, varargin)
% draw.task_timing(statetable)
%
% names = { "Start Cue", "Nose in Fixation","Target Cue","Go Sound", "Nose in Target"}';
% start_state = [ 0, 0.15, 0.3, 1.3, 1.65]';
% stop_state = [ 0.15, 1.5, 1.65, 1.35, 1.8]';
% color = cellfun(@(x)x/255, {[48, 110, 29], [0,0,0], [4... |
github | erlichlab/elutils-master | psychoplot4.m | .m | elutils-master/+draw/psychoplot4.m | 2,729 | utf_8 | c0531293fb3a8721188984342248cd17 | function varargout=psychoplot4(x_vals, varargin)
% [stats]=psychoplot4(x_vals, went_right)
% [stats]=psychoplot4(x_vals, hits, sides)
%
% Fits a 4 parameter sigmoid to psychophysical data
%
% x_vals the experimenter controlled value on each trial.
% went_right a vector of [0,1]'s the same length as x_vals des... |
github | erlichlab/elutils-master | twodcomp.m | .m | elutils-master/+draw/twodcomp.m | 2,055 | utf_8 | a7d4f275c6ed7c0318d26d909ff0fa0a | function ax=twodcomp(A,B,varargin)
plot_type='surf';
plot_ax='v';
ax_h=0.2;
ax_w=0.2;
ax_h_off=0.1;
ax_w_off=0.1;
x=1:size(A,2);
y=1:size(A,1);
fig=[];
gap=0.05;
cmin=min([A(:);B(:);B(:)-A(:)]);
cmax=max([A(:);B(:);B(:)-A(:)]);
ax=[];
plot_colorbar=false;
utils.overridedefaults(who,varargin)
if isempty(fig)
fig... |
github | erlichlab/elutils-master | scatter_histhist.m | .m | elutils-master/+draw/scatter_histhist.m | 2,816 | utf_8 | 9c312dad3bd2fb8084a228d6f093dac5 |
function [hm, hx, hy]=scatter_histhist(x, x_sig, y,y_sig, varargin)
% [hm, hx, hy]=scatter_histhist(x, x_sig, y,y_sig, x_lim, y_lim)
% Optional arguments:
% width, hist_height, num_bins, x_label, y_label
%
% E.g
% x = randn(150,1)*2;
% y = randn(250,1)*4+3;
% y = randn(150,1)*4+3;
% xsig = abs(x)>2;
% ysig = y<0;
% d... |
github | erlichlab/elutils-master | mloads.m | .m | elutils-master/+json/mloads.m | 3,833 | utf_8 | 82b3ff741f68f9d2bac6ea80362a2e77 | function out = mloads(jstr, varargin)
% out = mdumps(obj, ['compress'])
% function that takes a matlab object (cell array, struct, vector) and converts it into json.
% It also creates a "sister" json object that describes the type and dimension of the "leaf" elements.
if isempty(jstr)
out = {};
... |
github | erlichlab/elutils-master | mdumps.m | .m | elutils-master/+json/mdumps.m | 2,894 | utf_8 | 8b81ff9b34a969aa5abdc3df1b2797f2 | function out = mdumps(obj, varargin)
% out = mdumps(obj, ['compress'])
% function that takes a matlab object (cell array, struct, vector) and converts it into json.
% It also creates a "sister" json object that describes the type and dimension of the "leaf" elements.
% Warning: Simple cell arrays (e.g. cell-arrays o... |
github | erlichlab/elutils-master | showerror.m | .m | elutils-master/+utils/showerror.m | 639 | utf_8 | c92f2f93b75dac33946442eaacee08f3 |
function out = showerror(le, varargin)
if nargin==0
le=lasterror;
end
[print_stack, args] = utils.inputordefault('print_stack', true, varargin);
utils.inputordefault(args)
if nargout > 0
out = sprintf('\n%s \n%s\n',le.identifier, le.message);
if print_stack
for xi=1:numel(le.stack)
ou... |
github | erlichlab/elutils-master | date_diff.m | .m | elutils-master/+utils/date_diff.m | 1,805 | utf_8 | 1f82c41c56b44b8e57ed1e0569bc93c5 | function out = date_diff(date1, date2, interval)
% out = date_diff(date1, date2, interval)
% Inputs
% date1 a date in yyyy-mm-dd or yyyy-mm-dd hh:mm:ss format
% date2 a date in yyyy-mm-dd or yyyy-mm-dd hh:mm:ss format
% interval one of 'year','day','hour','minute','second'
%
% Note: date1 and date2 can either ... |
github | erlichlab/elutils-master | overridedefaults.m | .m | elutils-master/+utils/overridedefaults.m | 3,788 | utf_8 | b307fdb8db5be4b0fa55b1d70d931d3a | %parseargs [opts] = overridedefaults(varnames, arguments, ignore_unknowns)
%
% Variable argument parsing
%
% function is meant to be used in the context of other functions
% which have variable arguments. Typically, the function using
% variable argument parsing would be written with the following
% header:
%
% fu... |
github | erlichlab/elutils-master | adaptive_mult.m | .m | elutils-master/+utils/adaptive_mult.m | 2,123 | utf_8 | 89328d00b41e6d0ae7f634db36b37b2c | % [val] = adaptive_mult(val, hit, {'hit_frac', 0}, {'stableperf', 0.75}, ...
% {'mx', 1}, {'mn', 0}, {'do_callback', 0})
%
% Implements multiplicative staircase adaptation of a variable.
%
% PARAMETERS:
% -----------
%
% val The value to be adapted.
%
% hit Pass this as 1 if lates... |
github | erlichlab/elutils-master | parseargs.m | .m | elutils-master/+utils/parseargs.m | 6,636 | utf_8 | c8ed076c97d377f6a6807576765b9992 | %parseargs [opts] = parseargs(arguments, pairs, singles, ignore_unknowns)
%
% Variable argument parsing-- supersedes parseargs_example. This
% function is meant to be used in the context of other functions
% which have variable arguments. Typically, the function using
% variable argument parsing would be written with... |
github | erlichlab/elutils-master | to_string_date.m | .m | elutils-master/+utils/to_string_date.m | 2,465 | utf_8 | 3b79081714a1f10ba59298abc6fa29bb | % [str] = to_string_date(din, ['format', {'dashes'|'nodashes'})
%
% Takes a din that stands for a date and turns it into a string format that
% can be used to look for data files or that can be used with the SQL
% database.
%
% PARAMETERS:
% -----------
%
% din An integer. If it is an integer of magnitude less ... |
github | erlichlab/elutils-master | adaptive_step.m | .m | elutils-master/+utils/adaptive_step.m | 2,067 | utf_8 | 9f6646a5feea5b49c15bbcaab948d83d | % [val] = adaptive_step(val, hit, {'hit_step', 0}, {'stableperf', 0.75}, ...
% {'mx', 1}, {'mn', 0}, {'do_callback', 0})
%
% Implements staircase adaptation of a variable.
%
% PARAMETERS:
% -----------
%
% val The value to be adapted.
%
% hit Pass this as 1 if latest trial was in ... |
github | erlichlab/elutils-master | combinator.m | .m | elutils-master/+utils/combinator.m | 12,572 | utf_8 | b7227c1ea589711f5b1cacffff096fb1 | function [A] = combinator(N,K,s1,s2)
%COMBINATOR Perform basic permutation and combination samplings.
% COMBINATOR will return one of 4 different samplings on the set 1:N,
% taken K at a time. These samplings are given as follows:
%
% PERMUTATIONS WITH REPETITION/REPLACEMENT
% COMBINATOR(N,K,'p','r') -... |
github | erlichlab/elutils-master | MakeSpectrumNoise.m | .m | elutils-master/+sound/MakeSpectrumNoise.m | 2,511 | utf_8 | 1ad790feb7a4eab9a9dd378d9caba9ef | % function [snd] = MakeSpectrumNoise(SRate, F1, F2, Duration, Kontrast, ...
% CRatio, varargin)
%
% This function generates a sound whose power spectrum is white except for
% two Gaussian peaks at F1 and F2 (each with std = sigma). The contrast of
% each peak is defined as C_i = (P_i ... |
github | erlichlab/elutils-master | cosyne_ramp.m | .m | elutils-master/+sound/cosyne_ramp.m | 887 | utf_8 | 94b4e864d3b54de9f7a28cca9a9bfcb4 | % [snd] = cosyne_ramp(snd, srate, ramp_ms)
%
% Takes a sound in the 1-dimensional vector snd, and assuming that the
% samplerate for it is srate samples/sec, multiplies it by a cosyne ramp of
% ramp_ms milliseconds (i.e., the cosyne function goes from min to max in
% ramp_ms, meaning it has a whole-cycle a period of 2*... |
github | erlichlab/elutils-master | MakeBupperSwoop.m | .m | elutils-master/+sound/MakeBupperSwoop.m | 6,598 | utf_8 | 08ef1f9c6e0298e251130dfbe2ca6e26 | %MakeBupperSwoop.m [monosound]=MakeBupperSwoop(SRate, Att, StartFreq, ...
% EndFreq, BeforeBreakDuration, AfterBreakDuration,...
% Breaklen, Tau)
%
% Makes a sound:
%
% SRate: sampling rate, in samples/sec
% Attenuation
% StartFreq starting frequency of the... |
github | erlichlab/elutils-master | MakeSwoop.m | .m | elutils-master/+sound/MakeSwoop.m | 2,192 | utf_8 | 09ee5917bcea33f5d8c9b389ce7ef88d | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MakeSwoop
% Generate the individual tone pips as an accessory to PrepareSweep.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MakeSwoop
% Usage:
% Beep=MakeSwoop( SRate, Attenuation, Frequency, Durati... |
github | erlichlab/elutils-master | MakeBeep.m | .m | elutils-master/+sound/MakeBeep.m | 1,862 | utf_8 | e6730035baf6efe94fb226b17bff9e9e | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MakeBeep
% Generate the individual tone pips as an accessory to PrepareSweep.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MakeBeep
% Usage:
% Beep=MakeBeep( SRate, Attenuation, Frequency, Duration,... |
github | erlichlab/elutils-master | MakeChord2.m | .m | elutils-master/+sound/MakeChord2.m | 2,265 | utf_8 | d4e4da484d1e93df77d03709404f2dcf | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MakeChord2
% Generate Chord.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Usage:
% Beep=MakeChord( SRate, Attenuation, BaseFreq, NTones, Duration, [RiseFall] )
% Create a chord with base frequency '... |
github | erlichlab/elutils-master | MakeSwoop2.m | .m | elutils-master/+sound/MakeSwoop2.m | 1,742 | utf_8 | 06d44b69c6c79cd89c41fb2f3d72696b | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MakeSwoop2
% Generate the individual tone pips as an accessory to PrepareSweep.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MakeSwoop2
% Usage:
% Beep=MakeSwoop( SRate, Attenuation, Frequency, Dura... |
github | erlichlab/elutils-master | MakeSigmoidSwoop3.m | .m | elutils-master/+sound/MakeSigmoidSwoop3.m | 4,319 | utf_8 | 4b75bae0f81f56a8e851319eef4dccf6 | %MakeSigmoidSwoop3.m [monosound]=MakeSigmoidSwoop3(SRate, Att, StartFreq, ...
% EndFreq, BeforeBreakDuration, AfterBreakDuration,...
% Breaklen, Tau, [RiseFall=3] )
%
% Makes a sound:
%
% SRate: sampling rate, in samples/sec
% Attenuation
% StartFreq starti... |
github | erlichlab/elutils-master | MakeChord.m | .m | elutils-master/+sound/MakeChord.m | 2,135 | utf_8 | 00364a0eb3f67051ad1e59e125a86d24 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MakeChord
% Generate Chord.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Usage:
% Beep=MakeChord( SRate, Attenuation, BaseFreq, NTones, Duration, [RiseFall] )
% Create a chord with base frequency 'B... |
github | erlichlab/elutils-master | MakeSigmoidSwoop2.m | .m | elutils-master/+sound/MakeSigmoidSwoop2.m | 2,507 | utf_8 | db64fa6d40a96528a57c83acd4ae8d39 | %MakeSigmoidSwoop2.m [Beep]=MakeSigmoidSwoop(SRate, SPL, StartFreq, EndFreq, Duration, Tau, Breaklen, [RiseFall=5] )
%
% Makes a sound:
%
% SRate: sampling rate, in samples/sec
% Attenuation
% StartFreq starting frequency of the sound, in Hz
% EndFreq ending frequency of the sound, in Hz
% Durat... |
github | erlichlab/elutils-master | MakeClick.m | .m | elutils-master/+sound/MakeClick.m | 1,391 | utf_8 | 6e51c9a71deabd3dacbf01b3c4d7b57e | % [click] = MakeClick({'sigma', 0.0001}, {'power', 1.2})
%
% Makes a single, sharp, brief, broad-band "click!" of amplitude 0.7.
%
% Gets the sampling rate from protocolobj; then makes a
% Gaussian-like function, exp(-|t|^power / (2*sigma^power)) : a
% Guassian would have power=2; then takes the derivative of this
% ... |
github | erlichlab/elutils-master | MakeBeep4Winsound.m | .m | elutils-master/+sound/MakeBeep4Winsound.m | 1,818 | utf_8 | 83fd71b44c3e6b281395e603e3add516 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MakeBeep4Winsound
% Generate the individual tone pips as an accessory to PlayTones.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function Beep=MakeBeep4Winsound( SRate, Attenuation, Frequency, Durati... |
github | erlichlab/elutils-master | Make2Sines.m | .m | elutils-master/+sound/Make2Sines.m | 2,539 | utf_8 | 492ef41bbfe84d1b25ae431055ed018e | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Make2Sines
% Generate two sine tones with delay.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Usage:
% Beep=Make2Sines( SRate, Attenuation, F1, F2, ToneDuration, Delay, [RiseFall] )
% Create s... |
github | erlichlab/elutils-master | MakeSigmoidSwoop.m | .m | elutils-master/+sound/MakeSigmoidSwoop.m | 2,211 | utf_8 | 3f9b0adbb2823476b55a5c7f9523c9bb | %MakeSigmoidSwoopm.m [Beep]=MakeSigmoidSwoop(SRate, Attenuation, StartFreq, EndFreq, Duration, Tau, Breaklen, [RiseFall=5] )
%
% Makes a sound:
%
% SRate: sampling rate, in samples/sec
% Attenuation
% StartFreq starting frequency of the sound, in Hz
% EndFreq ending frequency of the sound, in Hz
% ... |
github | erlichlab/elutils-master | MakeFMWiggle.m | .m | elutils-master/+sound/MakeFMWiggle.m | 2,621 | utf_8 | 14f4272f26b69bb9edcbd12b347726ad | %MakeFMWiggle.m [monosound]=MakeFMWiggle(SRate, Att, Duration, CarrierFreq, ...
% FMFreq, FMAmp, [RiseFall=3] {'volume_factor', 1, 'PPfilter_name', ''})
%
% Makes a sinusoidally wiggling frequency pure tone (i.e., a sinusoidally frequency modulated sine wave):
%
% SRate: sampling rate, i... |
github | erlichlab/elutils-master | make_pbup.m | .m | elutils-master/+sound/make_pbup.m | 8,806 | utf_8 | 87fd9aa4ca3b776517cfe0782df11b6d | % [snd lrate rrate data] = make_pbup(R, g, srate, T, varargin)
%
% Makes Poisson bups
% bup events from the left and right speakers are independent Poisson
% events
%
% =======
% inputs:
%
% R total rate (in clicks/sec) of bups from both left and right
% speakers (r_L + r_R). Note that if distractor_rate > 0, th... |
github | erlichlab/elutils-master | MakeEdge.m | .m | elutils-master/+sound/MakeEdge.m | 783 | utf_8 | 8536b947788790f936e5ead9be58a078 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% MakeEdge
% Generate the rising/falling edge as an accessory to MakeBeep.
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function Edge=MakeEdge( SRate, RiseFall )
% Usage:
% Edge=MakeEdge( SRate, RiseFa... |
github | erlichlab/elutils-master | singlebup.m | .m | elutils-master/+sound/singlebup.m | 1,377 | utf_8 | 0be7b1a1e09b4be4290028c14fac66ae | % [snd] = singlebup(srate, att, { 'width', 5}, {'ramp', 2}, {'basefreq', 2000}, ...
% {'ntones' 5}, {'PPfilter_fname', ''}); ...
function [snd] = singlebup(srate, att, varargin)
width=5 ;
ramp = 2 ;
basefreq = 2000 ;
ntones = 5 ;
PPfilter_... |
github | virati/SGView-master | SG_view.m | .m | SGView-master/SG_view.m | 78,170 | utf_8 | 012bb7c3e7682c1678c29a1f1369c165 | %%
%Written by: Vineet Tiruvadi 2013-2016
%SG Viewer
%Main Gui for rapid viewing and spectral figures of BrainRadio and hdEEG
%data for MaybergLab.
function varargout = SG_view(varargin)
% SG_VIEW MATLAB code for SG_view.fig
% SG_VIEW, by itself, creates a new SG_VIEW or raises the existing
% singleton*.DBS9... |
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