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github | nickabattista/Ark-master | FitzHugh_Nagumo_PDE.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/Neurons/PDE/FitzHugh_Nagumo_PDE.m | 4,837 | utf_8 | 11b8baf57f96b55fa8f793aebbf8a477 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% This script solves the FitzHugh-Nagumo Equations in 1d, which are
% a simplified version of the more complicated Hodgkin-Huxley Equations.
%
% Author: Nick Battista
% Created: 09/11/2015
%
% Equations:
% dv/dt = D*Laplacian(v) - v*(v-a)*... |
github | nickabattista/Ark-master | FitzHugh_Nagumo_ODE.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/Neurons/ODE/FitzHugh_Nagumo_ODE.m | 3,604 | utf_8 | a3bd5dcc0ee16452a9f9503e871068aa | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% This script solves the FitzHugh-Nagumo Equations in 1d, which are
% a simplified version of the more complicated Hodgkin-Huxley Equations.
%
% Author: Nick Battista
% Created: 04/21/2019
%
% Equations:
% dv/dt = - v*(v-a)*(v-1) - w + I(t... |
github | nickabattista/Ark-master | please_Compare_Logistic.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Compare_Discrete_to_Continuous/please_Compare_Logistic.m | 2,847 | utf_8 | 1b392d5975b96baed60b1d4ca04aad34 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Compares Discrete to Continuous Logistic Equation
%
% Author: Nick Battista
% Institution: TCNJ
% Created: March 2019
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function please_Compare_Logistic(k)
%
% C... |
github | nickabattista/Ark-master | please_Compare_Predator_Prey.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Compare_Discrete_to_Continuous/please_Compare_Predator_Prey.m | 3,794 | utf_8 | 437a026212b96bf91ee068a6e5a6de97 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Compares Discrete to Continuous Predator-Prey
%
% Author: Nick Battista
% Institution: TCNJ
% Created: March 2019
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function please_Compare_Predator_Prey(b2)
%
... |
github | nickabattista/Ark-master | go_Go_SIR_ode45.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Epidemiology/ode45/go_Go_SIR_ode45.m | 4,259 | utf_8 | e6e9c66473bb2ff062aee5421711dd8a | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Solves Standard Base Case SIR Model (no deaths) using MATLAB's
% ODE 45 built in differential equation solver, which uses RK-4
% (4th Order Runge-Kutta Method)
%
% dS/dt = Lambda - mu*S - beta*S*I
% ... |
github | nickabattista/Ark-master | Opioid_ODE_Model.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Epidemiology/ode45/Opioid_ODE_Model.m | 4,458 | utf_8 | 7edcab7a41bc86c9c6455bbd8113d7d1 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% This code solves a model of a basic opioid addiction epidemic
%
%
% Author: Nick Battista
% Date Created: August 10, 2017
% Date Updated: September 23, 2017 (NAB)
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
f... |
github | nickabattista/Ark-master | compute_Jacobian_for_SIR_w_Deaths.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Epidemiology/ode45/compute_Jacobian_for_SIR_w_Deaths.m | 1,611 | utf_8 | c8af14f9401c16e45c0fadc12959fe42 |
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: sets up a Jacobian Matrix and finds eigenvalues
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function compute_Jacobian_for_SIR_w_Deaths()
%
% SIR Model Parameters
%
beta = 0.5; % rate of disease transm... |
github | nickabattista/Ark-master | go_Go_Logistic_ode45.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Epidemiology/ode45/go_Go_Logistic_ode45.m | 3,030 | utf_8 | 9e86adb726a8dbdcad2d74ba767dae09 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Solves the Logistic Equation using MATLAB's
% ODE 45 built in differential equation solver, which uses RK-4
% (4th Order Runge-Kutta Method)
%
% dP/dt = k*P*(1 - P/C)
%
% Parameters: k ... |
github | nickabattista/Ark-master | go_Go_SIR.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Epidemiology/Euler_Method/go_Go_SIR.m | 2,370 | utf_8 | 87c84e39cd53309415720450851e0d9b | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Solves Standard Base Case SIR Model (no deaths)
%
% Author: Nick Battista
% Institution: TCNJ
% Created: March 2019
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function go_Go_SIR()
%
% Clears any previous... |
github | nickabattista/Ark-master | go_Go_SIR_w_Vaccines.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Epidemiology/Euler_Method/go_Go_SIR_w_Vaccines.m | 2,663 | utf_8 | 66a6272fd616d0a84cc3bca6161ca735 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Solves SIR w/ Vaccination (and death) Model
%
% Author: Nick Battista
% Institution: TCNJ
% Created: March 2019
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function go_Go_SIR_w_Vaccines()
%
% Clears any p... |
github | nickabattista/Ark-master | go_Go_SIR_w_Deaths.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Epidemiology/Euler_Method/go_Go_SIR_w_Deaths.m | 2,578 | utf_8 | 14cb92cdc55a2122a7ee9044e861cb6d | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Solves SIR w/ Deaths Model
%
% Author: Nick Battista
% Institution: TCNJ
% Created: March 2019
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function go_Go_SIR_w_Deaths()
%
% Clears any previous plots that ... |
github | nickabattista/Ark-master | Predator_Prey.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Ecology/Predator_Prey.m | 2,201 | utf_8 | 6f2a44b347324ff4136e40a366fde1ff | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Solves Discrete Dynamical Systems in Population Ecology
%
% Author: Nick Battista
% Institution: TCNJ
% Created: March 2019
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function Predator_Prey()
%
% Clears ... |
github | nickabattista/Ark-master | go_Go_Logistic_ode45.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Ecology/go_Go_Logistic_ode45.m | 3,030 | utf_8 | 9e86adb726a8dbdcad2d74ba767dae09 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Solves the Logistic Equation using MATLAB's
% ODE 45 built in differential equation solver, which uses RK-4
% (4th Order Runge-Kutta Method)
%
% dP/dt = k*P*(1 - P/C)
%
% Parameters: k ... |
github | nickabattista/Ark-master | Depensation_Model.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Ecology/Depensation_Model.m | 1,591 | utf_8 | 968761fd252a3957555a5c6208b707e5 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Models a depensation differential equation based on the
% Logistic Model in in Ecology
%
% Author: Nick Battista
% Institution: TCNJ
% Created: March 2019
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
github | nickabattista/Ark-master | sobol_method_sensitivity_zika.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/Mizuhara/sobol_method_sensitivity_zika.m | 16,362 | utf_8 | e7ca22026dd9462bc6cd9de7a162604b | %Simulation of Brauer Zika SIR system; Morris sensitivity
clear
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Physical Parameters
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%av = [.3, 1]; Gao
%f_hv = [.3, .75]; Gao
%f_vh = [.1, .75]; Gao
%k = [1/12,1/2]; Towers
%g = [1/7,1/3]; Towers
%m = [1/20, 1/6]; Tower... |
github | nickabattista/Ark-master | Sobol_R0.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/Mizuhara/Sobol_R0.m | 8,774 | utf_8 | b91bc53d61c82cfb948a28baf1729fa0 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Performs Sobol Sensitivity Analysis For Calculating Stability
% of a Disease Free Equilibrium for the SIR Model w/ Deaths
%
% Orig. Author: Dr. Matthew S. Mizuhara (TCNJ)
%
% Modifications: Dr. Nick A. Ba... |
github | nickabattista/Ark-master | Sobol_ODE_System.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/Mizuhara/Sobol_ODE_System.m | 11,988 | utf_8 | f37cee9dc49f21c939a117adc336394a | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Performs Sobol Sensitivity Analysis For Calculating Stability
% of a Disease Free Equilibrium for the SIR Model w/ Deaths
%
% Orig. Author: Dr. Matthew Mizuhara (TCNJ)
%
% Modifications: Dr. Nick Battista... |
github | nickabattista/Ark-master | fnc_GetInputs.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/fnc_GetInputs.m | 815 | utf_8 | c0043b47041ba0bc78f08e4bfbc311b0 | %% fnc_GetInputs: give the vector of the inputs corresponding to the index
% (useful to scan all the possible combinations of the
% inputs)
%
% Usage:
% ii = fnc_GetInputs(i)
%
% Inputs:
% i scalar index of the inputs (given by fnc_GetIndex)
%
% ... |
github | nickabattista/Ark-master | GSA_GetSy_MultiOut_MultiSI.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/GSA_GetSy_MultiOut_MultiSI.m | 6,532 | utf_8 | 713a7c7a6ce495892c15cf3ec1efc17a | %% GSA_GetSy_MultiOut_MultiSI: calculate the Sobol' sensitivity indices
%
% Usage:
% [S, eS, pro] = GSA_GetSy_MultiOut_MultiSI(pro, iset, verbose)
%
% Inputs:
% pro project structure
% iset cell array or array of inputs of the considered set, they can be selected
% ... |
github | nickabattista/Ark-master | fnc_getSobolSequence.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/fnc_getSobolSequence.m | 5,664 | utf_8 | 476e90688fb596a2d7b46d05c269f9ea | %% fnc_getSobolSequence: give a set of sobol quasi-random
%
% Usage:
% X = fnc_getSobolSequence(dim, N, dbpath)
%
% Inputs:
% dim number of variables, the MAX number of variables is 40
% N number of samples
%
% Output:
% X matrix [N x dim] with the q... |
github | nickabattista/Ark-master | pro_SetModel.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/pro_SetModel.m | 737 | utf_8 | b5631a61b6e339d981141888764dbc4c | %% pro_SetModel: Set the model to the project
%
% Usage:
% pro = pro_SetModel(pro, model, name)
%
% Inputs:
% pro project structure
% model handle to the @(x)model(x,...) where x is a vector
% name optional, name of the model
%
% Output:
% pro ... |
github | nickabattista/Ark-master | GSA_FAST_GetSi.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/GSA_FAST_GetSi.m | 2,821 | utf_8 | 615e97c23d674dc13c9495ed0581ec33 | %% GSA_FAST_GetSi: calculate the FAST sensitivity indices
% Ref: Cukier, R.I., C.M. Fortuin, K.E. Shuler, A.G. Petschek and J.H.
% Schaibly (1973). Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory. Journal of Chemical Physics
%
% Max number of input variables: 50... |
github | nickabattista/Ark-master | GSA_Init_MultiOut_MultiSI.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/GSA_Init_MultiOut_MultiSI.m | 2,732 | utf_8 | 2865c383d6cf2056d97f442ab4257a9b | %% GSA_Init_MultiOut_MultiSI: initialize the variables used in the GSA computation
%
% Usage:
% pro = GSA_Init_MultiOut_MultiSI(pro)
%
% Inputs:
% pro project structure
%
% Output:
% pro updated project structure
%
% ------------------------------------------------------... |
github | nickabattista/Ark-master | GSA_GetTotalSy.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/GSA_GetTotalSy.m | 2,158 | utf_8 | eec4d448625695d12ae9bee76f277830 | %% GSA_GetTotalSy: calculate the total sensitivity S of a subset of inputs
%
% Usage:
% [Stot eStot pro] = GSA_GetTotalSy(pro, iset, verbose)
%
% Inputs:
% pro project structure
% iset cell array or array of inputs of the considered set, they can be selected
% ... |
github | nickabattista/Ark-master | pdf_Sobol.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/pdf_Sobol.m | 587 | utf_8 | c70f1059c9562b2e2191a0fc5ebdec89 | %% pdf_Sobol: Foo function for simulate a Sobol Set
%
% Usage:
% pdf_Sobol()
%
% Inputs:
% range vector [min max] range of the random variable
%
% Output:
% range vector [min max] range of the random variable
% -------------------------------------------------------------------... |
github | nickabattista/Ark-master | fnc_GetComplementaryInputs.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/fnc_GetComplementaryInputs.m | 860 | utf_8 | b49201eeff86fb5e3cf106d439e5da76 | %% fnc_GetComplementaryInputs: give the vector of the complementary inputs
%% corresponding to the index i
%
% Usage:
% cii = fnc_GetComplementaryInputs(i, n)
%
% Inputs:
% i scalar index of the inputs (given by fnc_GetIndex)
% n number of... |
github | nickabattista/Ark-master | GSA_GetTotalSy_MultiOut_MultiSI.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/GSA_GetTotalSy_MultiOut_MultiSI.m | 2,289 | utf_8 | cd64bdc0cc001ee5445fa1eeb621e1c2 | %% GSA_GetTotalSy_MultiOut_MultiSI: calculate the total sensitivity S of a subset of inputs
%
% Usage:
% [Stot, eStot, pro] = GSA_GetTotalSy_MultiOut_MultiSI(pro, iset, verbose)
%
% Inputs:
% pro project structure
% iset cell array or array of inputs of the considered set, th... |
github | nickabattista/Ark-master | pdf_LogNormal.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/pdf_LogNormal.m | 984 | utf_8 | 8896cef0cd5300b0b762f35f13e2305c | %% pdf_LogNormal: LogNormal Probability Density Function
%
% Usage:
% x = pdf_LogNormal(N, m, s)
%
% Inputs:
% N scalar, number of samples
% m mean of the lognormal distribution
% s standard deviation of the lognormal distribution
%
% Output:
% ... |
github | nickabattista/Ark-master | GSA_FAST_GetSi_MultiOut.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/GSA_FAST_GetSi_MultiOut.m | 3,673 | utf_8 | 65d7e073de6289ba1a61082a24f2539b | %% GSA_FAST_GetSi: calculate the FAST sensitivity indices for multi-output systems
% Ref: Cukier, R.I., C.M. Fortuin, K.E. Shuler, A.G. Petschek and J.H.
% Schaibly (1973). Study of the sensitivity of coupled reaction systems to uncertainties in rate coefficients. I Theory. Journal of Chemical Physics
%
% Max numb... |
github | nickabattista/Ark-master | pdf_Uniform.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/pdf_Uniform.m | 978 | utf_8 | f659aa1ae3c3b37bac6d0f07679b4dd6 | %% pdf_Uniform: Uniform Probability Density Function
%
% Usage:
% x = pdf_Uniform(N, range, seed)
%
% Inputs:
% N scalar, number of samples
% range vector [min max] range of the random variable
% seed optional, seed for the random number generator
%
% Output... |
github | nickabattista/Ark-master | GSA_GetSy.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/GSA_GetSy.m | 5,381 | utf_8 | 893c7908ac99647e1f267405a09491d7 | %% GSA_GetSy: calculate the Sobol' sensitivity indices
%
% Usage:
% [S eS pro] = GSA_GetSy(pro, iset, verbose)
%
% Inputs:
% pro project structure
% iset cell array or array of inputs of the considered set, they can be selected
% by index (1,2,3 ...) or... |
github | nickabattista/Ark-master | fnc_SampleInputs.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/fnc_SampleInputs.m | 1,960 | utf_8 | 0a48c67ce4e145af19646989a90059ae | %% fnc_SampleInputs: function that samples the input variables of a project
%
% Usage:
% [Set1 Set2] = fnc_SampleInputs(pro)
%
% Inputs:
% pro project structure
%
% Output:
% Set1, Set2 matrix with the input pdfs sampled
%
% -----------------------------------------------------... |
github | nickabattista/Ark-master | pro_Create.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/pro_Create.m | 1,220 | utf_8 | 90e9e94083a92c8114c2a3e7218fbf6d | %% pro_Create: Create an empty new project structure
%
% Usage:
% pro = pro_Create()
%
% Inputs:
%
% Output:
% pro project structure
% .Inputs.pdfs: cell-array of the model inputs with the pdf handles
% .Inputs.Names: cell-array with the i... |
github | nickabattista/Ark-master | GSA_Init.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/GSA_Init.m | 2,123 | utf_8 | 7d0dad1cfa42510cc7dde92b3e61b394 | %% GSA_Init: initialize the variables used in the GSA computation
%
% Usage:
% pro = GSA_Init(pro)
%
% Inputs:
% pro project structure
%
% Output:
% pro project structure
%
% ------------------------------------------------------------------------
% Citation: Cannavo' F... |
github | nickabattista/Ark-master | fnc_SelectInput.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/fnc_SelectInput.m | 1,288 | utf_8 | 606f98697f0d34b9abcbe755c81cc9c2 | %% fnc_SelectInput: select the input indexes from a generic list
%
% Usage:
% index = fnc_SelectInput(pro, iset)
%
% Inputs:
% pro project structure
% iset cell array or array of inputs of the considered set, they can be selected
% by index (1,2,3 ...) ... |
github | nickabattista/Ark-master | pdf_Normal.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/pdf_Normal.m | 825 | utf_8 | d49ba6d66f3efe7d058216c404a1f51c | %% pdf_Normal: Normal Probability Density Function
%
% Usage:
% x = pdf_Normal(N, mu, sigma)
%
% Inputs:
% N scalar, number of samples
% mu mean
% sigma standard deviation
%
% Output:
% x vector with the sampled data
% ... |
github | nickabattista/Ark-master | SATestModel.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/SATestModel.m | 332 | utf_8 | 91dbcf8abd962cf881b22a89207e0f4d | % calculate the real analytical values of the global sensitivity
% coefficients for the model "Sobol' function" in TestModel.m
function [D Si] = SATestModel(p)
Bi = 1./(3*((1+p).^2));
D = prod((1+Bi))-1;
L = 2^length(p);
Si = nan(1,L-1);
for i=1:(L-1)
ii = fnc_GetInputs(i);
Si(i) = prod(Bi(... |
github | nickabattista/Ark-master | fnc_GetIndex.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/fnc_GetIndex.m | 622 | utf_8 | b74b5906e01446ab95d012835f362269 | %% fnc_GetIndex: give the index of the element in the vector that
%% corresponds to the set of inputs
%
% Usage:
% i = fnc_GetIndex(C)
%
% Inputs:
% C array of input indexes
%
% Output:
% i index in the vector that contains all the variances
%
% ----------... |
github | nickabattista/Ark-master | pro_AddInput.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/pro_AddInput.m | 722 | utf_8 | b2ea9c1585cfaa09d5707d2f9a28ee4e | %% pro_AddInput: Add a model input to the project
%
% Usage:
% pro = pro_AddInput(pro, inputpdf, name, analyse)
%
% Inputs:
% pro project structure
% inputpdf reference to a @(N)pdf(N,...)
% name name of the input
%
% Output:
% pro projec... |
github | nickabattista/Ark-master | fnc_FAST_getInputs.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/fnc_FAST_getInputs.m | 1,359 | utf_8 | 7170eb2a936173aa963f7daecb42c0b6 | %% fnc_FAST_getInputs: transform the normed input in the real range inputs
%
% Usage:
% X = fnc_FAST_getInputs(pro, NormedX)
%
% Inputs:
% pro project structure
% NormedX normed inputs
%
% Output:
% X inputs in the correct ranges
%
% ----------------------... |
github | nickabattista/Ark-master | fnc_getSobolSetMatlab.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/fnc_getSobolSetMatlab.m | 789 | utf_8 | 98add8889dc4652506337915fefc47ae | %% fnc_getSobolSetMatlab: give a set of sobol quasi-random by using Matlab
% implemented functions
%
% Usage:
% X = fnc_getSobolSetMatlab(dim, N)
%
% Inputs:
% dim number of variables, the MAX number of variables is 40
% N number of samples
%
% ... |
github | nickabattista/Ark-master | TestModel2.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/ODE_Dynamical_Systems/Sensitivity/GSAT_Sensitivity/TestModel2.m | 129 | utf_8 | 361d787c542bcf214a94be2b91094ddd | % Ishigami test function (section 3.0.1)
function g = TestModel2(x)
g = sin(x(1))+5*(sin(x(2))^2) + 0.1*(x(3)^4)*sin(x(1));
|
github | nickabattista/Ark-master | Random_Walks_in_2D_Lattice.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/Random_Walks_Diffusive_Processes/Random_Walks_in_2D_Lattice.m | 2,718 | utf_8 | a8dd0d3f7dc769ae3b3541802bfb2661 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Computes Random Walks in 2D to compute root-mean-squared
% distance from starting point.
%
%
% Author: Nick Battista
% Institution: TCNJ
% Created: April 8, 2019
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
github | nickabattista/Ark-master | Diffusion_2D.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/Random_Walks_Diffusive_Processes/Diffusion_2D.m | 6,405 | utf_8 | bf1c5c526159fdbe6422092a07528cf6 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: solves Diffusion Equation in 2D and compares to Random Walkers
% in 2D on a lattice
%
%
% Author: Nick Battista
% Institution: TCNJ
% Created: April 8, 2019
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
github | nickabattista/Ark-master | Random_Walks_in_1D.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/Random_Walks_Diffusive_Processes/Random_Walks_in_1D.m | 2,691 | utf_8 | 792aad56a90df41816eb874964ad3f81 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Computes Random Walks in 1D to compute root-mean-squared
% distance from starting point.
%
%
% Author: Nick Battista
% Institution: TCNJ
% Created: April 8, 2019
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
github | nickabattista/Ark-master | Random_Walks_in_2D.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/Random_Walks_Diffusive_Processes/Random_Walks_in_2D.m | 2,452 | utf_8 | b9b682be6e347f675e29b4a3d65b7c76 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Computes Random Walks in 2D to compute root-mean-squared
% distance from starting point.
%
%
% Author: Nick Battista
% Institution: TCNJ
% Created: April 8, 2019
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%... |
github | nickabattista/Ark-master | compute_Random_Walks_2D_Lattice_Convergence.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/Random_Walks_Diffusive_Processes/Random_Walker_Convergence/compute_Random_Walks_2D_Lattice_Convergence.m | 3,765 | utf_8 | ac300c7f03a5c71f66adff56efeb17c9 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Computes error btwn simulation and theory for different numbers
% of random walkers in 2D. As # of RWs goes up, error goes down.
%
% Author: Nick Battista
% Institution: TCNJ
% Created: April 8, 2019
%
%%%%%%%%%%%%%%%%%%%%%%%... |
github | nickabattista/Ark-master | compute_Random_Walks_2D_Convergence.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/Random_Walks_Diffusive_Processes/Random_Walker_Convergence/compute_Random_Walks_2D_Convergence.m | 3,553 | utf_8 | 596fbde1f0dba70b0fff6afa4fe5e5d1 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Computes error btwn simulation and theory for different numbers
% of random walkers in 2D. As # of RWs goes up, error goes down.
%
% Author: Nick Battista
% Institution: TCNJ
% Created: April 8, 2019
%
%%%%%%%%%%%%%%%%%%%%%%%... |
github | nickabattista/Ark-master | compute_Random_Walks_1D_Convergence.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/Random_Walks_Diffusive_Processes/Random_Walker_Convergence/compute_Random_Walks_1D_Convergence.m | 3,601 | utf_8 | d6a7d4a9214e792641f99db6c5944701 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Computes error btwn simulation and theory for different numbers
% of random walkers in 1D. As # of RWs goes up, error goes down.
%
% Author: Nick Battista
% Institution: TCNJ
% Created: April 8, 2019
%
%%%%%%%%%%%%%%%%%%%%%%%... |
github | nickabattista/Ark-master | go_Go_Zombie_Model.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/Discrete_Dynamical_Systems/go_Go_Zombie_Model.m | 2,590 | utf_8 | bf0679b2de0eff1d2feb30b51765dc86 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Models a Zombie outbreak using Dynamical Systems
%
% Author: Nick Battista
% Created: Jan. 2019
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function go_Go_Zombie_Model(TFinal)
%
% Time Information / Initi... |
github | nickabattista/Ark-master | Population_Ecology.m | .m | Ark-master/MATBIO330_Mathematical_Biology/Class_Codes/Discrete_Dynamical_Systems/Ecology/Population_Ecology.m | 1,858 | utf_8 | 34aa6f090b803ab05f6a29af3c707ea3 | %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%
% FUNCTION: Solves Discrete Dynamical Systems in Population Ecology
%
% Author: Nick Battista
% Institution: TCNJ
% Created: March 2019
%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
function Population_Ecology(TFinal)
... |
github | nickabattista/Ark-master | Eulers.m | .m | Ark-master/Euler_Method/Eulers.m | 9,009 | utf_8 | bd348d60b6ed1b254925695e7b547e95 | function Eulers()
%Author: Nicholas Battista
%Created: August 12, 2014
%Date of Last Revision: August 23, 2014
%
%This function solves the following ODE:
%dy/dt = f(t,y)
%y(0) = y0
%using Eulers Method. It then does a convergence study for various h values.
%
%Note: It performs the convergence study for the known ODE... |
github | boom-lab/oce_tools-master | gasBunsen.m | .m | oce_tools-master/gas_toolbox/gasBunsen.m | 1,856 | utf_8 | 94c0adfe3ec20268a6a2ebbb53528cf7 | % beta = gasBunsen(SP,pt,gas)
% Function to calculate Bunsen coefficient
%
% USAGE:-------------------------------------------------------------------
% beta=gasBunsen(SP,pt,gas)
%
% DESCRIPTION:-------------------------------------------------------------
% Calculate the Bunsen coefficient, which is defined as the vol... |
github | boom-lab/oce_tools-master | kgas.m | .m | oce_tools-master/gas_toolbox/kgas.m | 4,654 | utf_8 | 20a6385160fb787a02149b3afb863af9 | % =========================================================================
% KGAS - gas transfer coefficient for a range of windspeed-based
% parameterizations
%
% [kv] = kgas(u10,Sc,param)
%
% -------------------------------------------------------------------------
% INPUTS:
% -------------------------------... |
github | boom-lab/oce_tools-master | fas_L13.m | .m | oce_tools-master/gas_toolbox/fas_L13.m | 6,356 | utf_8 | bc2b614f86938e6d5b49f9c201f44c0a | % Function to calculate air-sea fluxes with Liang 2013 parameterization
%
% USAGE:-------------------------------------------------------------------
%
% [Fd, Fp, Fc, Deq] = fas_L13(0.282,10,35,10,1,'O2')
% >Fd = 2.2559e-08
% >Fp = 6.8604e-08
% >Fc = 2.9961e-08
% >Deq = 0.0062
%
% DESCRIPTION:------... |
github | boom-lab/oce_tools-master | fas_S09.m | .m | oce_tools-master/gas_toolbox/fas_S09.m | 6,754 | utf_8 | f6e99dc7f66955ce601e76053f538654 | % [Fd, Fc, Fp, Deq] = fas_S09(C,u10,S,T,slp,gas,rh)
% Function to calculate air-sea gas exchange flux using Stanley 09
% parameterization
%
% USAGE:-------------------------------------------------------------------
% [Fd, Fc, Fp, Deq] = fas_S09(C,u10,S,T,slp,gas,rh)
% [Fd, Fc, Fp, Deq] = fas_S09(0.01410,5,35,10,... |
github | boom-lab/oce_tools-master | fas_N11.m | .m | oce_tools-master/gas_toolbox/fas_N11.m | 7,418 | utf_8 | ca85c60e47fa4e8b77675c14034cc8a1 | <<<<<<< HEAD
% Function to calculate air-sea bubble flux
%
% USAGE:-------------------------------------------------------------------
%
% [Fi Fe] = Fbub_N11(8,35,20,1,'O2')
%
% > Fi = 9.8910e-08
% > Fe = 2.3665e-08
%
% DESCRIPTION:-------------------------------------------------------------
%
% Calculates the equ... |
github | boom-lab/oce_tools-master | fas_Sw07.m | .m | oce_tools-master/gas_toolbox/fas_Sw07.m | 4,246 | utf_8 | aabc9958150462fd4140a234ddf0fa24 | % [Fd, Fc, Fp, Deq] = fas_Sw07(C,u10,S,T,slp,gas,rh)
% Function to calculate air-sea gas exchange flux using Sweeney 07
% parameterization (k_660 = 0.27 cm/hr)
%
% USAGE:-------------------------------------------------------------------
% [Fd, Fc, Fp, Deq] = fas_Sw07(C,u10,S,T,slp,gas,rh)
% [Fd, Fc, Fp, Deq] =... |
github | boom-lab/oce_tools-master | gasmolsol.m | .m | oce_tools-master/gas_toolbox/gasmolsol.m | 1,341 | utf_8 | 6e4780f3679e3ea17ac369365f554331 | % =========================================================================
% GASMOLSOL.M - calculates Henry's Law solubility (for a pure gas)
% in mol m-3 atm-1
%
% This is a wrapper function. See individual solubility functions for more
% details.
%
% [sol] = gasmolsol(SP,pt,gas)
%
% --------------------------------... |
github | boom-lab/oce_tools-master | calc_u10.m | .m | oce_tools-master/gas_toolbox/calc_u10.m | 2,088 | utf_8 | 09c687c95196c23b80507092d86febf5 | % u10 = calc_u10(umeas,hmeas)
%
% USAGE:-------------------------------------------------------------------
%
% [u10] = calc_u10(5,4)
%
% >u10 = 5.5302
%
% DESCRIPTION:-------------------------------------------------------------
% Scale wind speed from measurement height to 10 m height
%
% INPUTS:--------------------... |
github | boom-lab/oce_tools-master | gasmoleq.m | .m | oce_tools-master/gas_toolbox/gasmoleq.m | 3,626 | utf_8 | ef6936be137426f8dcab022b7eb2c9a6 | % =========================================================================
% [sol] = gasmoleq(SP,pt,gas)
%
% GASMOLEQ.M - calculates equilibrium solubility of a dissolved gas
% in mol/m^3 at an absolute pressure of 101325 Pa (sea pressure of 0
% dbar) including saturated water vapor.
%
% This is a wrapper fun... |
github | boom-lab/oce_tools-master | fas.m | .m | oce_tools-master/gas_toolbox/fas.m | 4,077 | utf_8 | 6f31976e074eea8855be4c2d18ef3f34 | % =========================================================================
% FAS - wrapper function for calculating air-sea gas transfer using a
% specific GE parameterization
%
% [Fs, Fc, Fp, Deq] = fas(C,u10,S,T,slp,gas,param,rh)
%
% -------------------------------------------------------------------------
% USAGE:
... |
github | boom-lab/oce_tools-master | sw_ptmp.m | .m | oce_tools-master/gas_toolbox/other_functions/sw_ptmp.m | 3,684 | utf_8 | cf912e62bc1cde2044b0471353899d97 |
function PT = sw_ptmp(S,T,P,PR)
% SW_PTMP Potential temperature
%===========================================================================
% SW_PTMP $Id: sw_ptmp.m,v 1.1 2003/12/12 04:23:22 pen078 Exp $
% Copyright (C) CSIRO, Phil Morgan 1992.
%
% USAGE: ptmp = sw_ptmp(S,T,P,PR)
%
% DESCRIPT... |
github | boom-lab/oce_tools-master | oc_url.m | .m | oce_tools-master/ocean_color/oc_url.m | 5,048 | utf_8 | 7d60af451fb1283f252c478781e4a8a7 | function [ fname ] = oc_url(t,var,varargin)
% oc_url
% -------------------------------------------------------------------------
% construncts netCDF filename for NASA Ocean Color OpenDAP server
% link - http://oceandata.sci.gsfc.nasa.gov/opendap/
% ----------------------------------------------------------------------... |
github | spm/spm5-master | spm_config_results.m | .m | spm5-master/spm_config_results.m | 4,712 | utf_8 | c9c6c0c2c47b93a33eda1a7aadfe4072 | function conf = spm_config_results
% Configuration file for results reporting
%_______________________________________________________________________
% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience
% $Id: spm_config_results.m 1563 2008-05-07 14:16:43Z ferath $
%-------------------------------------... |
github | spm/spm5-master | spm_eeg_inv_datareg.m | .m | spm5-master/spm_eeg_inv_datareg.m | 13,392 | utf_8 | 1618e2bb99be5372a0829b942500f881 | function [varargout] = spm_eeg_inv_datareg(varargin)
%==========================================================================
% Rigid registration of the EEG/MEG data and sMRI spaces
%
% FORMAT D = spm_eeg_inv_datareg(S)
% rigid co-registration
% 1: fiducials based (3 landmarks: nasion, left ear, right ea... |
github | spm/spm5-master | spm_vb_ppm_anova.m | .m | spm5-master/spm_vb_ppm_anova.m | 3,883 | utf_8 | cf4c32a78589f807a84ec4b5826260ab | function spm_vb_ppm_anova(SPM)
% Bayesian ANOVA using model comparison
% FORMAT spm_vb_ppm_anova(SPM)
%
% SPM - Data structure corresponding to a full model (ie. one
% containing all experimental conditions).
%
% This function creates images of differences in log evidence
% which characterise t... |
github | spm/spm5-master | spm_eeg_inv_vde.m | .m | spm5-master/spm_eeg_inv_vde.m | 4,817 | utf_8 | fe334e835d70d0ec1f54bf41a895ab9e | function varargout = spm_eeg_inv_vde(varargin)
% SPM_EEG_INV_VDE M-file for spm_eeg_inv_vde.fig
% SPM_EEG_INV_VDE, by itself, creates a new SPM_EEG_INV_VDE or raises the existing
% singleton*.
%
% H = SPM_EEG_INV_VDE returns the handle to a new SPM_EEG_INV_VDE or the handle to
% the existing singlet... |
github | spm/spm5-master | spm_eeg_inv_ecd_DrawDip.m | .m | spm5-master/spm_eeg_inv_ecd_DrawDip.m | 19,637 | utf_8 | d19eae00a8f30a0d46d376b1732237a5 | function varargout = spm_eeg_inv_ecd_DrawDip(action,varargin)
%___________________________________________________________________
%
% spm_eeg_inv_ecd_DrawDip
%
% Function to display the dipoles as obtained from the optim routine.
%
% Use it with arguments or not:
% - spm_eeg_inv_ecd_DrawDip('Init')
% The routi... |
github | spm/spm5-master | spm_eeg_display_ui.m | .m | spm5-master/spm_eeg_display_ui.m | 25,402 | utf_8 | 25f7e44690f054e724956833781be5da | function Heeg = spm_eeg_display_ui(varargin)
% user interface for displaying EEG/MEG channel data.
% Heeg = spm_eeg_display_ui(varargin)
%
% optional argument:
% S - struct
% fields of S:
% D - EEG struct
% Hfig - Figure (or axes) to work in (Defaults to SPM graphics window)
% rebuild - indicat... |
github | spm/spm5-master | spm_eeg_select_channels.m | .m | spm5-master/spm_eeg_select_channels.m | 10,356 | utf_8 | a742f19989b2763640c0d4fb074fcadd | function varargout = spm_eeg_select_channels(varargin)
% SPM_EEG_SELECT_CHANNELS M-file for spm_eeg_select_channels.fig
% SPM_EEG_SELECT_CHANNELS, by itself, creates a new SPM_EEG_SELECT_CHANNELS or raises the existing
% singleton*.
%
% H = SPM_EEG_SELECT_CHANNELS returns the handle to a new SPM_EEG_SELE... |
github | spm/spm5-master | spm_eeg_spm_ui.m | .m | spm5-master/spm_eeg_spm_ui.m | 6,241 | utf_8 | 06838efc9f6f9ed245832834e9095dd7 | function [SPM] = spm_eeg_spm_ui(SPM)
% user interface for calling general linear model specification for EEG
% data
% FORMAT [SPM] = spm_eeg_spm_ui(SPM)
%
%_______________________________________________________________________
%
% Specification of M/EEG designs
%________________________________________________________... |
github | spm/spm5-master | spm_vol_check.m | .m | spm5-master/spm_vol_check.m | 1,690 | utf_8 | 210f1146cb0cf92ed4da535629b23c27 | function [samef, msg, chgf] = spm_vol_check(varargin)
% FORMAT [samef, msg, chgf] = spm_vol_check(V1, V2, ...)
% checks spm_vol structs are in same space
%
% V1, V2, etc - arrays of spm_vol structs
%
% samef - true if images have same dims, mats
% msg - cell array containing helpful message... |
github | spm/spm5-master | spm_eeg_rdata_CTF275.m | .m | spm5-master/spm_eeg_rdata_CTF275.m | 7,267 | utf_8 | b651bcf377a7a29b4661c27a68df88d3 | function D = spm_eeg_rdata_CTF275(S)
%%%% function to read in CTF data to Matlab
try
timewindow = S.tw;
catch
timewindow = spm_input('do you want to read in all the data','+1','yes|no',[1 0]);
end
if timewindow ==1
timeperiod='all';
else
try
timeperiod=S.timeperiod;
catch
[Finter,Fgraph,... |
github | spm/spm5-master | spm_fmri_spm_ui.m | .m | spm5-master/spm_fmri_spm_ui.m | 18,967 | utf_8 | 66b6af6d5d22fc23cfbb10e11fcf0d6f | function [SPM] = spm_fmri_spm_ui(SPM)
% Setting up the general linear model for fMRI time-series
% FORMAT [SPM] = spm_fmri_spm_ui(SPM)
%
% creates SPM with the following fields
%
% xY: [1x1 struct] - data stucture
% nscan: [double] - vector of scans per session
% xBF: [1x1 struct] - Basis function stu... |
github | spm/spm5-master | spm_input.m | .m | spm5-master/spm_input.m | 83,619 | utf_8 | 7a6922167daf9947097ce8acfb9902eb | function varargout = spm_input(varargin)
% Comprehensive graphical and command line input function
% FORMATs (given in Programmers Help)
%_______________________________________________________________________
%
% spm_input handles most forms of interactive user input for SPM.
% (File selection is handled by spm_select... |
github | spm/spm5-master | spm_config_minc.m | .m | spm5-master/spm_config_minc.m | 2,505 | utf_8 | 47d6e77ccd421f13aeb57fc2941eccb1 | function opts = spm_config_minc
% Configuration file for minc import jobs
%_______________________________________________________________________
% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience
% John Ashburner
% $Id: spm_config_minc.m 1032 2007-12-20 14:45:55Z john $
%______________________________... |
github | spm/spm5-master | spm_realign.m | .m | spm5-master/spm_realign.m | 17,190 | utf_8 | 4b1e430488a8aa45f21f252c19f49b04 | function P = spm_realign(P,flags)
% Estimation of within modality rigid body movement parameters
% FORMAT P = spm_realign(P,flags)
%
% P - matrix of filenames {one string per row}
% All operations are performed relative to the first image.
% ie. Coregistration is to the first image, and resampling
%... |
github | spm/spm5-master | spm_config_realign_and_unwarp.m | .m | spm5-master/spm_config_realign_and_unwarp.m | 35,460 | utf_8 | fbec3386cd1dc0e8d8a2121f0e5d0359 | function opts = spm_config_realign_and_unwarp
% Configuration file for realign and unwarping jobs
%_______________________________________________________________________
% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience
% Darren R. Gitelman
% $Id: spm_config_realign_and_unwarp.m 1032 2007-12-20 14:45:5... |
github | spm/spm5-master | spm_surf.m | .m | spm5-master/spm_surf.m | 9,530 | utf_8 | 10f87454cf682a1c4a3bac82b13549a0 | function spm_surf(P,mode,thresh)
% Surface extraction.
% FORMAT spm_surf
%
% This surface extraction is not particularly sophisticated. It simply
% smooths the data slightly and extracts the surface at a threshold of
% 0.5. Optionally, a vector of thresholds can be supplied and a surface
% will be extracted for each t... |
github | spm/spm5-master | spm_write_sn.m | .m | spm5-master/spm_write_sn.m | 20,095 | utf_8 | 165d7e8750b57d3108a160ea233ec808 | function VO = spm_write_sn(V,prm,flags,extras)
% Write Out Warped Images.
% FORMAT VO = spm_write_sn(V,matname,flags,msk)
% V - Images to transform (filenames or volume structure).
% matname - Transformation information (filename or structure).
% flags - flags structure, with fields...
% interp ... |
github | spm/spm5-master | spm_DesMtx.m | .m | spm5-master/spm_DesMtx.m | 30,975 | utf_8 | fbbb25a149ba004e3f50c2089f236004 | function [X,Pnames,Index,idx,jdx,kdx]=spm_DesMtx(varargin);
% Design matrix construction from factor level and covariate vectors
% FORMAT [X,Pnames] = spm_DesMtx(<FCLevels-Constraint-FCnames> list)
% FORMAT [X,Pnames,Index,idx,jdx,kdx] = spm_DesMtx(FCLevels,Constraint,FCnames)
%
% <FCLevels-Constraints-FCnames>
% ... |
github | spm/spm5-master | spm_eeg_average_TF.m | .m | spm5-master/spm_eeg_average_TF.m | 2,660 | utf_8 | 8918d10a4b4307e86b50c10c90c4de8a |
function D=spm_eeg_average_TF(S)
%%% function to average induced TF data if standard average does not work because of out of memeory issues
% James Kilner
% $Id$
try
D = S.D;
catch
D = spm_select(1, '.*\.mat$', 'Select EEG mat file');
end
P = spm_str_manip(D, 'H');
try
D = spm_eeg_ldata(D);
catch
... |
github | spm/spm5-master | spm_config_imcalc.m | .m | spm5-master/spm_config_imcalc.m | 6,138 | utf_8 | 165df05c2186b3308b46e82029d2c079 | function opts = spm_config_imcalc
% Configuration file for image calculator
%_______________________________________________________________________
% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience
% John Ashburner
% $Id: spm_config_imcalc.m 1032 2007-12-20 14:45:55Z john $
%________________________... |
github | spm/spm5-master | spm_imatrix.m | .m | spm5-master/spm_imatrix.m | 1,535 | utf_8 | e1e622d4cffa69aa616e536b77f85d66 | function P = spm_imatrix(M)
% returns the parameters for creating an affine transformation
% FORMAT P = spm_imatrix(M)
% M - Affine transformation matrix
% P - Parameters (see spm_matrix for definitions)
%___________________________________________________________________________
% Copyright (C) 2005 Wellcome... |
github | spm/spm5-master | ctf_folder.m | .m | spm5-master/ctf_folder.m | 2,949 | utf_8 | 4e051b8e8a1e6ec08c6b7a53e6b37340 | function [ctf] = ctf_folder(folder,ctf);
% ctf_folder - get and check CTF .ds folder name
%
% [ctf] = ctf_folder( [folder], [ctf] );
%
% folder: The .ds directory of the dataset. It should be a complete path
% or given relative to the current working directory (given by pwd). The
% returned value will ensure the c... |
github | spm/spm5-master | spm_affreg.m | .m | spm5-master/spm_affreg.m | 18,881 | utf_8 | 75ec9b5af8f8965af695dc0eb74ed73c | function [M,scal] = spm_affreg(VG,VF,flags,M,scal)
% Affine registration using least squares.
% FORMAT [M,scal] = spm_affreg(VG,VF,flags,M0,scal0)
%
% VG - Vector of template volumes.
% VF - Source volume.
% flags - a structure containing various options. The fields are:
% WG - Weig... |
github | spm/spm5-master | spm_loaduint8.m | .m | spm5-master/spm_loaduint8.m | 1,375 | utf_8 | c323020909cc93a83057b28b65305214 | function udat = spm_loaduint8(V)
% Load data from file indicated by V into an array of unsigned bytes.
if size(V.pinfo,2)==1 && V.pinfo(1) == 2,
mx = 255*V.pinfo(1) + V.pinfo(2);
mn = V.pinfo(2);
else,
spm_progress_bar('Init',V.dim(3),...
['Computing max/min of ' spm_str_manip(V.fname,'t')],...
'Planes complete... |
github | spm/spm5-master | savexml.m | .m | spm5-master/savexml.m | 4,312 | utf_8 | 753fabe9a2ec52f53e55248f54e10df9 | function savexml(filename, varargin)
%SAVEXML Save workspace variables to disk in XML.
% SAVEXML FILENAME saves all workspace variables to the XML-file
% named FILENAME.xml. The data may be retrieved with LOADXML. if
% FILENAME has no extension, .xml is assumed.
%
% SAVE, by itself, creates the XML-file named 'ma... |
github | spm/spm5-master | spm_eeg_inv_electrset.m | .m | spm5-master/spm_eeg_inv_electrset.m | 16,739 | utf_8 | 16af7781a5ed0427df06e69cbafc0d66 | function [el_sphc,el_name] = spm_eeg_inv_electrset(el_set)
%------------------------------------------------------------------------
% FORMAT [el_sphc,el_name] = spm_eeg_inv_electrset(el_set) ;
% or
% FORMAT [set_Nel,set_name] = spm_eeg_inv_electrset ;
%
% Creates the electrode set on a sphere, set type is defined by ... |
github | spm/spm5-master | spm_bilinear.m | .m | spm5-master/spm_bilinear.m | 3,613 | utf_8 | 7f238feffb3fabfd9fb371f41cf46a02 | function [H0,H1,H2] = spm_bilinear(A,B,C,D,x0,N,dt)
% returns global Volterra kernels for a MIMO Bilinear system
% FORMAT [H0,H1,H2] = spm_bilinear(A,B,C,D,x0,N,dt)
% A - (n x n) df(x(0),0)/dx - n states
% B - (n x n x m) d2f(x(0),0)/dxdu - m inputs
% C - (n x m) d... |
github | spm/spm5-master | spm_powell.m | .m | spm5-master/spm_powell.m | 7,978 | utf_8 | 063a0beec40aebe20cbadf483220393b | function [p,f] = spm_powell(p,xi,tolsc,func,varargin)
% Powell optimisation method
% FORMAT [p,f] = spm_powell(p,xi,tolsc,func,varargin)
% p - Starting parameter values
% xi - columns containing directions in which to begin
% searching.
% tolsc - stopping criteria
% - optimisat... |
github | spm/spm5-master | spm_vol.m | .m | spm5-master/spm_vol.m | 5,542 | utf_8 | eb6c5a42448d73ffcb5701c148093c4f | function V = spm_vol(P)
% Get header information etc for images.
% FORMAT V = spm_vol(P)
% P - a matrix of filenames.
% V - a vector of structures containing image volume information.
% The elements of the structures are:
% V.fname - the filename of the image.
% V.dim - the x, y and z dimensions of the vo... |
github | spm/spm5-master | spm_jobman.m | .m | spm5-master/spm_jobman.m | 97,869 | utf_8 | 1db2d5463418dcdf0a80c81d7cb7705a | function varargout = spm_jobman(varargin)
% UI/Batching stuff
%_______________________________________________________________________
% This code is based on an earlier version by Philippe Ciuciu and
% Guillaume Flandin of Orsay, France.
%
% FORMAT spm_jobman
% spm_jobman('interactive')
% spm_jobman('int... |
github | spm/spm5-master | spm_bst_headmodeler.m | .m | spm5-master/spm_bst_headmodeler.m | 82,570 | utf_8 | 3a01e74cf6f9309c284033afc212220a | function [varargout] = spm_bst_headmodeler(varargin);
% SPM_BST_HEADMODELER - Solution to the MEG/EEG forward problem
% function [varargout] = bst_headmodeler(varargin);
% Authorized syntax:
% [OPTIONS] = spm_bst_headmodeler;
% [G, Gxyz, OPTIONS] = spm_bst_headmodeler(OPTIONS);
%
% ----------------------------... |
github | spm/spm5-master | spm_config_slice_timing.m | .m | spm5-master/spm_config_slice_timing.m | 7,569 | utf_8 | 2c1d50399145c9dff01b929a2de64556 | function opts = spm_config_slice_timing
% configuration file for slice timing
%____________________________________________________________________
% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience
% Darren Gitelman
% $Id: spm_config_slice_timing.m 1032 2007-12-20 14:45:55Z john $
% -------------------... |
github | spm/spm5-master | ctf_read_meg4.m | .m | spm5-master/ctf_read_meg4.m | 14,622 | utf_8 | 999fb8dfe3a3dd39bcb904c6d62c1e79 | function [ctf] = ctf_read_meg4(folder,ctf,CHAN,TIME,TRIALS,COEFS);
% ctf_read_meg4 - read meg4 format data from a CTF .ds folder
%
% [ctf] = ctf_read_meg4([folder],[ctf],[CHAN],[TIME],[TRIALS]);
%
% This function reads all or select portions of the raw meg data matrix in
% the .meg4 file within any .ds folder. It may... |
github | spm/spm5-master | spm_uw_apply.m | .m | spm5-master/spm_uw_apply.m | 15,337 | utf_8 | 9eac00bda2d4c00e4062104e135d045a | function varargout = spm_uw_apply(ds,flags)
% Reslices images volume by volume
% FORMAT spm_uw_apply(ds,[flags])
% or
% FORMAT P = spm_uw_apply(ds,[flags])
%
%
% ds - a structure created by spm_uw_estimate.m containing the fields:
% ds can also be an array of structures, each struct corr... |
github | spm/spm5-master | spm_config_ecat.m | .m | spm5-master/spm_config_ecat.m | 2,202 | utf_8 | 0fa0f021012dd7020140f0082d29bff4 | function opts = spm_config_ecat
% Configuration file for ecat import jobs
%_______________________________________________________________________
% Copyright (C) 2005 Wellcome Department of Imaging Neuroscience
% John Ashburner
% $Id: spm_config_ecat.m 512 2006-05-05 08:14:50Z volkmar $
%____________________________... |
github | spm/spm5-master | spm_read_netcdf.m | .m | spm5-master/spm_read_netcdf.m | 3,729 | utf_8 | f97b5b0974ef8ceb2fe48cbf083b73e2 | function cdf = spm_read_netcdf(fname)
% Read the header information from a NetCDF file into a data structure.
% FORMAT cdf = spm_read_netcdf(fname)
% fname - name of NetCDF file
% cdf - data structure
%
% See: http://www.unidata.ucar.edu/packages/netcdf/
% _____________________________________________________________... |
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