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github | lcnhappe/happe-master | arrayfilter.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/dependencies/PropertyGrid-2010-09-16-mod/arrayfilter.m | 488 | utf_8 | a2649b876169e3d850372917e57a8b68 | % Filter elements of array that meet a condition.
% Copyright 2010 Levente Hunyadi
function array = arrayfilter(fun, array)
validateattributes(fun, {'function_handle'}, {'scalar'});
if isobject(array)
filter = false(size(array));
for k = 1 : numel(filter)
filter(k) = fun(array(k));
end
else
f... |
github | lcnhappe/happe-master | example_propertygrid.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/dependencies/PropertyGrid-2010-09-16-mod/example_propertygrid.m | 4,929 | utf_8 | f1e5d6dc7fc518cdb070956ff714353c | % Demonstrates how to use the property pane.
%
% See also: PropertyGrid
% Copyright 2010 Levente Hunyadi
function example_propertygrid
properties = [ ...
PropertyGridField('double', pi, ...
'Category', 'Primitive types', ...
'DisplayName', 'real double', ...
'Description', 'Standard MatLab... |
github | lcnhappe/happe-master | constructor.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/dependencies/PropertyGrid-2010-09-16-mod/constructor.m | 2,078 | utf_8 | c67e647ec8055710896666c9e83b45e0 | % Sets public properties of a MatLab object using a name-value list.
% Properties are traversed in the order they occur in the class definition.
% Copyright 2008-2009 Levente Hunyadi
function obj = constructor(obj, varargin)
assert(isobject(obj), ...
'Function operates on MatLab new-style objects only.');
if nar... |
github | lcnhappe/happe-master | nestedassign.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/dependencies/PropertyGrid-2010-09-16-mod/nestedassign.m | 1,457 | utf_8 | 12d661bb4df3c64a0707a06f7e3e6afc | % Assigns the given value to the named property of an object or structure.
% This function can deal with nested properties.
%
% Input arguments:
% obj:
% the structure, handle or value object the value should be assigned to
% name:
% a property name with dot (.) separating property names at
% different hierarc... |
github | lcnhappe/happe-master | javaArrayList.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/dependencies/PropertyGrid-2010-09-16-mod/javaArrayList.m | 740 | utf_8 | cb4ad03c4e0fc536bc1ae024bfb8920a | % Converts a MatLab array into a java.util.ArrayList.
%
% Input arguments:
% array:
% a MatLab row or column vector (with elements of any type)
%
% Output arguments:
% list:
% a java.util.ArrayList instance
%
% See also: javaArray
% Copyright 2010 Levente Hunyadi
function list = javaArrayList(array)
list = java.... |
github | lcnhappe/happe-master | hlp_scope.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/helpers/hlp_scope.m | 3,366 | utf_8 | 4544c2a11f66464cc00f860f36646304 | function varargout = hlp_scope(assignments, f, varargin)
% Execute a function within a dynamic scope of values assigned to symbols.
% Results... = hlp_scope(Assignments, Function, Arguments...)
%
% This is the only completely reliable way in MATLAB to ensure that symbols that should be assigned
% while a function is ru... |
github | lcnhappe/happe-master | hlp_fingerprint.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/helpers/hlp_fingerprint.m | 7,085 | utf_8 | ebeb87c5f5aa958473e853a153d261f9 | function fp = hlp_fingerprint(data)
% Make a fingerprint (hash) of the given data structure.
% Fingerprint = hlp_fingerprint(Data)
%
% This includes all contents; however, large arrays (such as EEG.data) are only spot-checked. For
% thorough checking, use hlp_cryptohash.
%
% In:
% Data : some data structure
%
... |
github | lcnhappe/happe-master | hlp_flattensearch.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/helpers/hlp_flattensearch.m | 4,217 | utf_8 | 9f21976c4c355a8c0ac9432e74a4d31d | function x = hlp_flattensearch(x,form)
% Flatten search() clauses in a nested data structure into a flat search() clause.
% Result = hlp_flattensearch(Expression, Output-Form)
%
% Internal tool used by utl_gridsearch to enable the specification of search parameters using
% search() clauses.
%
% In:
% Expression : s... |
github | lcnhappe/happe-master | hlp_tostring.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/helpers/hlp_tostring.m | 6,536 | utf_8 | 7c374a9f8a1954f5289b4e446ea1a30d | function str = hlp_tostring(v)
% Get an human-readable string representation of a data structure.
% String = hlp_tostring(Data)
%
% The resulting string representations are usually executable, but there are corner cases (e.g.,
% certain anonymous function handles and large data sets), which are not supported. For
% gen... |
github | lcnhappe/happe-master | hlp_config.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/helpers/hlp_config.m | 12,881 | utf_8 | 7b49f69371781d0161c3a842064a43d0 | function result = hlp_config(configname, operation, varargin)
% helper function to process human-readable config scripts.
% Result = hlp_config(FileName,Operation,VariableName,Value,NVPs...)
%
% Config scripts consist of assignments of the form name = value; to set configuration options. In
% addition, there may be any... |
github | lcnhappe/happe-master | hlp_deserialize.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/helpers/hlp_deserialize.m | 12,045 | utf_8 | 5973cf16c3a0b718e9f334724d312870 | function v = hlp_deserialize(m)
% Convert a serialized byte vector back into the corresponding MATLAB data structure.
% Data = hlp_deserialize(Bytes)
%
% In:
% Bytes : a representation of the original data as a byte stream
%
% Out:
% Data : some MATLAB data structure
%
%
% See also:
% hlp_serialize
%
% Examples:
... |
github | lcnhappe/happe-master | hlp_aggregatestructs.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/helpers/hlp_aggregatestructs.m | 7,805 | utf_8 | bab3d7ea8549fc71419a8fa5cb42447f | function res = hlp_aggregatestructs(structs,defaultop,varargin)
% Aggregate structs (recursively), using the given combiner operations.
% Result = hlp_aggregatestructs(Structs,Default-Op,Field-Ops...)
%
% This results in a single 1x1 struct which has aggregated values in its fields (e.g., arrays,
% averages, etc.). Fo... |
github | lcnhappe/happe-master | hlp_matlab_version.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/helpers/hlp_matlab_version.m | 642 | utf_8 | 56356c36dd8e15038caa4dc7b15b62b5 | function v = hlp_matlab_version()
% Get the MATLAB version in a numeric format that can be compared with <, >, etc.
persistent vers;
try
v = vers(1);
catch
v = strsplit(version,'.'); v = str2num(v{1})*100 + str2num(v{2});
vers = v;
end
% Split a string according to some delimiter(s). Not as fast as hlp_spl... |
github | lcnhappe/happe-master | hlp_trycompile.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/helpers/hlp_trycompile.m | 50,690 | utf_8 | cef0c2f78d5b912954b1826f6352d9e1 | function ok = hlp_trycompile(varargin)
% Try to auto-compile a set of binary files in a folder, and return the status.
% OK = hlp_trycompile(Options...)
%
% This function tries to ensure that a given set of functions or classes (specified by their
% MATLAB identifier), whose source files are assumed to be located in a ... |
github | lcnhappe/happe-master | hlp_serialize.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/helpers/hlp_serialize.m | 15,821 | utf_8 | 90ee89875e34a4a84c3e58d9657c04f1 | function m = hlp_serialize(v)
% Convert a MATLAB data structure into a compact byte vector.
% Bytes = hlp_serialize(Data)
%
% The original data structure can be recovered from the byte vector via hlp_deserialize.
%
% In:
% Data : some MATLAB data structure
%
% Out:
% Bytes : a representation of the original data as... |
github | lcnhappe/happe-master | hlp_varargin2struct.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/helpers/hlp_varargin2struct.m | 6,267 | utf_8 | a185d699c488adb84cda30f6db5facda | function res = hlp_varargin2struct(args, varargin)
% Convert a list of name-value pairs into a struct with values assigned to names.
% struct = hlp_varargin2struct(Varargin, Defaults)
%
% In:
% Varargin : cell array of name-value pairs and/or structs (with values assigned to names)
%
% Defaults : optional list of n... |
github | lcnhappe/happe-master | hlp_worker.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/helpers/hlp_worker.m | 5,701 | utf_8 | 912f4bd9ba397e3e40f05b77f7bf1fb5 | function hlp_worker(varargin)
% Act as a lightweight worker process for use with hlp_schedule.
% hlp_worker(Options...)
%
% Receives commands (string expressions) from the network, evaluate them, and send off the result to
% some collector (again as a string). Processing is done in a single thread.
%
% In:
% Options... |
github | lcnhappe/happe-master | hlp_superimposedata.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/helpers/hlp_superimposedata.m | 5,438 | utf_8 | 512675e236e6e374f99cf433a05bb974 | function res = hlp_superimposedata(varargin)
% Merge multiple partially populated data structures into one fully populated one.
% Result = hlp_superimposedata(Data1, Data2, Data3, ...)
%
% The function is applicable when you have cell arrays or structs/struct arrays with non-overlapping
% patterns of non-empty entries,... |
github | lcnhappe/happe-master | arg_guidialog.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/arguments/arg_guidialog.m | 10,844 | utf_8 | 9a3feeb49fd1fa36ac5971ebb38d1ab9 | function varargout = arg_guidialog(func,varargin)
% Create an input dialog that displays input fields for a Function and Parameters.
% Parameters = arg_guidialog(Function, Options...)
%
% The Parameters that are passed to the function can be used to override some of its defaults. The
% function must declare its argumen... |
github | lcnhappe/happe-master | arg_define.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/arguments/arg_define.m | 28,888 | utf_8 | 79e413010787b04cc5fec2c1d1aa0d04 | function res = arg_define(vals,varargin)
% Declare function arguments with optional defaults and built-in GUI support.
% Struct = arg_define(Values, Specification...)
% Struct = arg_define(Format, Values, Specification...)
%
% This is essentially an improved replacement for the parameter declaration line of a function.... |
github | lcnhappe/happe-master | arg_guidialog_old.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/arguments/arg_guidialog_old.m | 8,955 | utf_8 | 4da1a90f92312aea4043460655d5f6aa | function params = arg_guidialog(func,varargin)
% Create an input dialog that displays input fields for a Function and Parameters.
% Parameters = arg_guidialog(Function, Options...)
%
% The Parameters that are passed to the function can be used to override some of its defaults.
% The function must declare its arguments... |
github | lcnhappe/happe-master | arg_guidialog_ex.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/arguments/arg_guidialog_ex.m | 8,675 | utf_8 | 82a7c00e1dfc74a921a596040b742fd9 | function params = arg_guidialog(func,varargin)
% Create an input dialog that displays input fields for a Function and Parameters.
% Parameters = arg_guidialog(Function, Options...)
%
% The Parameters that are passed to the function can be used to override some of its defaults.
% The function must declare its arguments... |
github | lcnhappe/happe-master | invoke_arg_internal.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/arguments/invoke_arg_internal.m | 4,456 | utf_8 | cde8b4f57b2bc16a8b03c45c255fe35d | function spec = invoke_arg_internal(reptype,varargin) %#ok<INUSL>
% same type of invoke function as in arg_sub, arg_subswitch, etc. - but shared between
% arg, arg_norep, and arg_nogui
spec = hlp_microcache('arg',@invoke_arg,varargin{:});
% the function that does the actual work of building the argument specifier
func... |
github | lcnhappe/happe-master | arg_report.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/arguments/arg_report.m | 6,925 | utf_8 | eb8f94b9fd0693dbde5cbfa2824b7e8d | function res = arg_report(type,func,args)
% Report information of a certain Type from the given Function.
% Result = arg_report(Type,Function,Arguments)
%
% Functions that declare their arguments via arg_define() make their parameter specification
% accessible to outside functions. This can be used to display auto-gene... |
github | lcnhappe/happe-master | arg_subswitch.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/arguments/arg_subswitch.m | 17,047 | utf_8 | f8e71db07aba22fedb0dce863f122c40 | function res = arg_subswitch(varargin)
% Specify a function argument that can be one of several alternative structs.
% Spec = arg_subswitch(Names,Defaults,Alternatives,Help,Options...)
%
% The correct struct is chosen according to a selection rule (the mapper). Accessible to the
% function as a struct, and visible in t... |
github | lcnhappe/happe-master | arg_sub.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/arguments/arg_sub.m | 12,136 | utf_8 | 579d06548d7bb9eba5580ea1d6d33322 | function res = arg_sub(varargin)
% Specify an argument of a function which is a structure of sub-arguments.
% Spec = arg_sub(Names,Defaults,Source,Help,Options...)
%
% Delivered to the function as a struct, and visible in the GUI as a an expandable sub-list of
% arguments. A function may have an argument which itself c... |
github | lcnhappe/happe-master | arg_subtoggle.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/arguments/arg_subtoggle.m | 15,337 | utf_8 | 6bfc9dc025de4ebf873f2152b77f7ee4 | function res = arg_subtoggle(varargin)
% Specify an argument of a function which is a struct of sub-arguments that can be disabled.
% Spec = arg_subtoggle(Names,Default,Source,Help,Options...)
%
% Accessible to the function as a struct, and visible in the GUI as a an expandable sub-list of
% arguments (with a checkbox ... |
github | lcnhappe/happe-master | arg_tovals.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/arguments/arg_tovals.m | 2,531 | utf_8 | d6b62007b294e20f330fd415633ef2ad | function res = arg_tovals(spec,direct)
% Convert a 'rich' argument report into a 'vals' report.
% Vals = arg_tovals(Rich)
%
% In:
% Rich : a 'rich' argument report, as obtained via arg_report('rich',some_function)
%
% Direct : whether to endow the result with an 'arg_direct' flag set to true, which indicates to
%... |
github | lcnhappe/happe-master | arg_specifier.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/arguments/arg_specifier.m | 2,714 | utf_8 | 45a0f0bbe159b1d73d533fcbbf4c2576 | function spec = arg_specifier(varargin)
% Internal: create a base specifier struct for an argument.
% Specifier = arg_specifier(Overrides...)
%
% In:
% Overrides... : name-value pairs of fields that should be overridden
%
% Out:
% A specifier that is recognized by arg_define.
%
% See also:
% arg_define
%
% ... |
github | lcnhappe/happe-master | is_needing_search.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/queries/is_needing_search.m | 808 | utf_8 | b4e0ea02b09d80b71d7e2970b648578f | function res = is_needing_search(argform,args)
% test whether some argument pack requires a search or not (according to the specified argument format)
if strcmp(argform,'direct')
% a search is specified by multielement arguments
res = prod(max(1,cellfun(@length,args))) > 1;
elseif strcmp(argform,'clauses')
... |
github | lcnhappe/happe-master | is_raw_dataset.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/bcilab_partial/queries/is_raw_dataset.m | 184 | utf_8 | 6bcaef74ea534a299898aa10b68af85a | % determine whether some object is a raw EEGLAB data set with no BCILAB constituents
function res = is_raw_dataset(x)
res = all(isfield(x,{'data','srate'})) && ~isfield(x,'tracking');
|
github | lcnhappe/happe-master | shadowplot.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/tmullen-cleanline-696a7181b7d0/external/shadowplot/shadowplot.m | 7,604 | utf_8 | ae6097ee1343157565bb24e6a5f27a32 | function varargout = shadowplot(varargin)
% SHADOWPLOT Add a shadow to an existing surface or patch plot
%
% For some surface plots, it can be helpful to visualize the shadow (2D
% projection) of the surface. This can give a quick perspective on the
% data's variance.
%
% SHADOWPLOT PLANE Adds a shadow plot on th... |
github | lcnhappe/happe-master | eegplugin_MARA.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/MARA-master/eegplugin_MARA.m | 2,770 | utf_8 | 7619f29fb825e45ca839265d7d4046e0 | % eegplugin_MARA() - EEGLab plugin to classify artifactual ICs based on
% 6 features from the time domain, the frequency domain,
% and the pattern
%
% Inputs:
% fig - [integer] EEGLAB figure
% try_strings - [struct] "try" strings for menu callbacks.
% catch_strin... |
github | lcnhappe/happe-master | pop_visualizeMARAfeatures.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/MARA-master/pop_visualizeMARAfeatures.m | 4,558 | utf_8 | c888a9b58c7e7893d090883d152d5e09 | % pop_visualizeMARAfeatures() - Display features that MARA's decision
% for artifact rejection is based on
%
% Usage:
% >> pop_visualizeMARAfeatures(gcompreject, MARAinfo);
%
% Inputs:
% gcompreject - array <1 x nIC> containing 1 if component was rejected
% MARAin... |
github | lcnhappe/happe-master | processMARA.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/MARA-master/processMARA.m | 6,510 | utf_8 | 896a41c6475ec80bf7706cc7166ce7a8 | % processMARA() - Processing for Automatic Artifact Classification with MARA.
% processMARA() calls MACA and saves the identified artifactual components
% in EEG.reject.gcompreject.
% The functions optionally filters the data, runs ICA, plots components or
% reject artifactual components immediately.
%
% U... |
github | lcnhappe/happe-master | MARA.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/MARA-master/MARA.m | 12,568 | utf_8 | 5127d8f931932b5c0760a9a61a0d0b6e | % MARA() - Automatic classification of multiple artifact components
% Classies artifactual ICs based on 6 features from the time domain,
% the frequency domain, and the pattern
%
% Usage:
% >> [artcomps, info] = MARA(EEG);
%
% Inputs:
% EEG - input EEG structure
%
% Outputs:
% artcom... |
github | lcnhappe/happe-master | pop_selectcomps_MARA.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/MARA-master/pop_selectcomps_MARA.m | 7,617 | utf_8 | 3df13de5291a735a3ae902eb9b7b4349 | % pop_selectcomps_MARA() - Display components with checkbox to label
% them for artifact rejection
%
% Usage:
% >> EEG = pop_selectcomps_MARA(EEG, gcompreject_old);
%
% Inputs:
% EEG - Input dataset with rejected components (saved in
% EEG.reject.gcompreject)
%... |
github | lcnhappe/happe-master | pop_processMARA.m | .m | happe-master/Packages/eeglab14_0_0b/plugins/MARA-master/pop_processMARA.m | 5,095 | utf_8 | 7932742793cce3ca7b8caeb78ae22d82 | % pop_processMARA() - graphical interface to select MARA's actions
%
% Usage:
% >> [ALLEEG,EEG,CURRENTSET,com] = pop_processMARA(ALLEEG,EEG,CURRENTSET );
%
% Inputs and Outputs:
% ALLEEG - array of EEG dataset structures
% EEG - current dataset structure or structure array
% (EEG.re... |
github | lcnhappe/happe-master | eegplugin_MARA.m | .m | happe-master/Packages/MARA-master/eegplugin_MARA.m | 2,770 | utf_8 | 7619f29fb825e45ca839265d7d4046e0 | % eegplugin_MARA() - EEGLab plugin to classify artifactual ICs based on
% 6 features from the time domain, the frequency domain,
% and the pattern
%
% Inputs:
% fig - [integer] EEGLAB figure
% try_strings - [struct] "try" strings for menu callbacks.
% catch_strin... |
github | lcnhappe/happe-master | pop_visualizeMARAfeatures.m | .m | happe-master/Packages/MARA-master/pop_visualizeMARAfeatures.m | 4,558 | utf_8 | c888a9b58c7e7893d090883d152d5e09 | % pop_visualizeMARAfeatures() - Display features that MARA's decision
% for artifact rejection is based on
%
% Usage:
% >> pop_visualizeMARAfeatures(gcompreject, MARAinfo);
%
% Inputs:
% gcompreject - array <1 x nIC> containing 1 if component was rejected
% MARAin... |
github | lcnhappe/happe-master | processMARA.m | .m | happe-master/Packages/MARA-master/processMARA.m | 6,510 | utf_8 | 896a41c6475ec80bf7706cc7166ce7a8 | % processMARA() - Processing for Automatic Artifact Classification with MARA.
% processMARA() calls MACA and saves the identified artifactual components
% in EEG.reject.gcompreject.
% The functions optionally filters the data, runs ICA, plots components or
% reject artifactual components immediately.
%
% U... |
github | lcnhappe/happe-master | MARA.m | .m | happe-master/Packages/MARA-master/MARA.m | 12,568 | utf_8 | 5127d8f931932b5c0760a9a61a0d0b6e | % MARA() - Automatic classification of multiple artifact components
% Classies artifactual ICs based on 6 features from the time domain,
% the frequency domain, and the pattern
%
% Usage:
% >> [artcomps, info] = MARA(EEG);
%
% Inputs:
% EEG - input EEG structure
%
% Outputs:
% artcom... |
github | lcnhappe/happe-master | pop_selectcomps_MARA.m | .m | happe-master/Packages/MARA-master/pop_selectcomps_MARA.m | 7,617 | utf_8 | 3df13de5291a735a3ae902eb9b7b4349 | % pop_selectcomps_MARA() - Display components with checkbox to label
% them for artifact rejection
%
% Usage:
% >> EEG = pop_selectcomps_MARA(EEG, gcompreject_old);
%
% Inputs:
% EEG - Input dataset with rejected components (saved in
% EEG.reject.gcompreject)
%... |
github | lcnhappe/happe-master | pop_processMARA.m | .m | happe-master/Packages/MARA-master/pop_processMARA.m | 5,095 | utf_8 | 7932742793cce3ca7b8caeb78ae22d82 | % pop_processMARA() - graphical interface to select MARA's actions
%
% Usage:
% >> [ALLEEG,EEG,CURRENTSET,com] = pop_processMARA(ALLEEG,EEG,CURRENTSET );
%
% Inputs and Outputs:
% ALLEEG - array of EEG dataset structures
% EEG - current dataset structure or structure array
% (EEG.re... |
github | stefanos1316/Rosetta_Code_Research_MSR-master | haversine-formula.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/haversine-formula/matlab/haversine-formula.m | 544 | utf_8 | 4d8ed7ec87e14b539dc6bba3595059d9 | function rad = radians(degree)
% degrees to radians
rad = degree .* pi / 180;
end;
function [a,c,dlat,dlon]=haversine(lat1,lon1,lat2,lon2)
% HAVERSINE_FORMULA.AWK - converted from AWK
dlat = radians(lat2-lat1);
dlon = radians(lon2-lon1);
lat1 = radians(lat1);
lat2 = radians(lat2);
a = (sin(dlat... |
github | stefanos1316/Rosetta_Code_Research_MSR-master | bulls-and-cows-player.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/bulls-and-cows-player/matlab/bulls-and-cows-player.m | 2,012 | utf_8 | df5a15858fa8b7b20809a1d6267363fa | function BullsAndCowsPlayer
% Plays the game Bulls and Cows as the player
% Generate list of all possible numbers
nDigits = 4;
lowVal = 1;
highVal = 9;
combs = nchoosek(lowVal:highVal, nDigits);
nCombs = size(combs, 1);
nPermsPerComb = factorial(nDigits);
gList = zeros(nCombs.*nPermsPer... |
github | stefanos1316/Rosetta_Code_Research_MSR-master | honeycombs.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/honeycombs/matlab/honeycombs.m | 2,850 | utf_8 | 8ecce457b119ea563b391513719558d8 | function Honeycombs
nRows = 4; % Number of rows
nCols = 5; % Number of columns
nHexs = nRows*nCols; % Number of hexagons
rOuter = 1; % Circumradius
startX = 0; % x-coordinate of upper left hexagon
startY... |
github | stefanos1316/Rosetta_Code_Research_MSR-master | image-convolution.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/image-convolution/matlab/image-convolution.m | 7,433 | utf_8 | d070d20a112b6e944d34feac79521dd3 | function testConvImage
Im = [1 2 1 5 5 ; ...
1 2 7 9 9 ; ...
5 5 5 5 5 ; ...
5 2 2 2 2 ; ...
1 1 1 1 1 ]; % Sample image for example illustration only
Ker = [1 2 1 ; ...
2 4 2 ; ...
1 2 1 ]; % Gaussian smoothing (without normalizing)
... |
github | stefanos1316/Rosetta_Code_Research_MSR-master | bitmap-bresenhams-line-algorithm-1.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/bitmap-bresenhams-line-algorithm/matlab/bitmap-bresenhams-line-algorithm-1.m | 1,186 | utf_8 | 73849f70792c46a646e103935a779958 | %screen = Bitmap object
%startPoint = [x0,y0]
%endPoint = [x1,y1]
%color = [red,green,blue]
function bresenhamLine(screen,startPoint,endPoint,color)
if( any(color > 255) )
error 'RGB colors must be between 0 and 255';
end
%Check for vertical line, x0 == x1
if( startPoint(1) == endPoint(1) )
... |
github | stefanos1316/Rosetta_Code_Research_MSR-master | flipping-bits-game.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/flipping-bits-game/matlab/flipping-bits-game.m | 2,733 | utf_8 | b5225ac55b751f26e68d02d1049f2829 | function FlippingBitsGame(n)
% Play the flipping bits game on an n x n array
% Generate random target array
fprintf('Welcome to the Flipping Bits Game!\n')
if nargin < 1
n = input('What dimension array should we use? ');
end
Tar = logical(randi([0 1], n));
% Generate starting array by ... |
github | stefanos1316/Rosetta_Code_Research_MSR-master | abc-problem.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/abc-problem/matlab/abc-problem.m | 790 | utf_8 | 81f2c22e2247a71e1dafda16915f99f4 | function testABC
combos = ['BO' ; 'XK' ; 'DQ' ; 'CP' ; 'NA' ; 'GT' ; 'RE' ; 'TG' ; 'QD' ; ...
'FS' ; 'JW' ; 'HU' ; 'VI' ; 'AN' ; 'OB' ; 'ER' ; 'FS' ; 'LY' ; ...
'PC' ; 'ZM'];
words = {'A' 'BARK' 'BOOK' 'TREAT' 'COMMON' 'SQUAD' 'CONFUSE'};
for k = 1:length(words)
possible = canMakeWor... |
github | stefanos1316/Rosetta_Code_Research_MSR-master | iban-1.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/iban/matlab/iban-1.m | 1,028 | utf_8 | b5dcb998fd69d25b80748f43f2a8697f | function valid = validateIBAN(iban)
% Determine if International Bank Account Number is valid IAW ISO 13616
% iban - string containing account number
if length(iban) < 5
valid = false;
else
iban(iban == ' ') = ''; % Remove spaces
iban = lower([iban(5:end) iban(1:4)])+... |
github | stefanos1316/Rosetta_Code_Research_MSR-master | classes-3.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/classes/matlab/classes-3.m | 140 | utf_8 | 9f9ed312eb6b69f944bc51a63731d8c9 | %Set function
function GenericClassInstance = setValue(GenericClassInstance,newValue)
GenericClassInstance.classVariable = newValue;
end
|
github | stefanos1316/Rosetta_Code_Research_MSR-master | classes-7.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/classes/matlab/classes-7.m | 114 | utf_8 | e170f5bcd0eb8257d26831dfd9d76f38 | %Get function
function value = getValue(GenericClassInstance)
value = GenericClassInstance.classVariable;
end
|
github | stefanos1316/Rosetta_Code_Research_MSR-master | classes-2.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/classes/matlab/classes-2.m | 114 | utf_8 | e170f5bcd0eb8257d26831dfd9d76f38 | %Get function
function value = getValue(GenericClassInstance)
value = GenericClassInstance.classVariable;
end
|
github | stefanos1316/Rosetta_Code_Research_MSR-master | ethiopian-multiplication-3.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/ethiopian-multiplication/matlab/ethiopian-multiplication-3.m | 144 | utf_8 | eca009509a1c505dcdfbd6a65357e247 | %Returns a logical 1 if the number is even, 0 otherwise.
function trueFalse = isEven(number)
trueFalse = logical( mod(number,2)==0 );
end
|
github | stefanos1316/Rosetta_Code_Research_MSR-master | bulls-and-cows.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/bulls-and-cows/matlab/bulls-and-cows.m | 2,359 | utf_8 | c763a0feaf16bec664158452df37a237 | function BullsAndCows
% Plays the game Bulls and Cows as the "game master"
% Create a secret number
nDigits = 4;
lowVal = 1;
highVal = 9;
digitList = lowVal:highVal;
secret = zeros(1, 4);
for k = 1:nDigits
idx = randi(length(digitList));
secret(k) = digitList(idx);
d... |
github | stefanos1316/Rosetta_Code_Research_MSR-master | happy-numbers.m | .m | Rosetta_Code_Research_MSR-master/Scripts/Task/happy-numbers/matlab/happy-numbers.m | 441 | utf_8 | b439e5762f0d9c6de15ca3d2169f6028 | function findHappyNumbers
nHappy = 0;
k = 1;
while nHappy < 8
if isHappyNumber(k, [])
fprintf('%d ', k)
nHappy = nHappy+1;
end
k = k+1;
end
fprintf('\n')
end
function hap = isHappyNumber(k, prev)
if k == 1
hap = true;
elseif ismember(k... |
github | lcarasik/TORCHE-master | StaggeredPressureDrop.m | .m | TORCHE-master/LEGACY/MATLAB/StaggeredPressureDrop.m | 3,356 | utf_8 | f7d830d90a37536111a52f19052983fc | %Original Author: Jonah Haefner
%Last Modified: 10/27/2015
%Most Reecent Author: Jonah Haefner
%References: Julien Clayton, Lane Carasik, ...
%%%Units%%%
%a = dimensionless transverse pitch
%b = dimensionless longitudinal pitch
%v = the free stream fluid velocity in m/s
%rho = density in kg/m^3
%u = dynamic viscosity... |
github | lcarasik/TORCHE-master | InlinePressureDrop.m | .m | TORCHE-master/LEGACY/MATLAB/InlinePressureDrop.m | 3,484 | utf_8 | 8101bcce59d041d275ebc71899c2eacc | %Original Author: Julien Clayton
%Last Modified: 7/9/2016
%Most Recent Author: Jonah Haefner
%All Authors: Jonah Haefner, Julien Clayton, Lane Carasik, ...
%%%Units%%%
%a = dimensionless transverse pitch
%b = dimensionless longitudinal pitch
%v = the free stream fluid velocity in m/s
%rho = density in g/cm^3
%u = dyn... |
github | ubiquiti/ubnt_libjingle-main | readDetection.m | .m | ubnt_libjingle-main/modules/audio_processing/transient/test/readDetection.m | 927 | utf_8 | f6af5020971d028a50a4d19a31b33bcb | %
% Copyright (c) 2014 The WebRTC project authors. All Rights Reserved.
%
% Use of this source code is governed by a BSD-style license
% that can be found in the LICENSE file in the root of the source
% tree. An additional intellectual property rights grant can be found
% in the file PATENTS. All contributing pro... |
github | ubiquiti/ubnt_libjingle-main | readPCM.m | .m | ubnt_libjingle-main/modules/audio_processing/transient/test/readPCM.m | 821 | utf_8 | 76b2955e65258ada1c1e549a4fc9bf79 | %
% Copyright (c) 2014 The WebRTC project authors. All Rights Reserved.
%
% Use of this source code is governed by a BSD-style license
% that can be found in the LICENSE file in the root of the source
% tree. An additional intellectual property rights grant can be found
% in the file PATENTS. All contributing pro... |
github | ubiquiti/ubnt_libjingle-main | plotDetection.m | .m | ubnt_libjingle-main/modules/audio_processing/transient/test/plotDetection.m | 923 | utf_8 | e8113bdaf5dcfe4f50200a3ca29c3846 | %
% Copyright (c) 2014 The WebRTC project authors. All Rights Reserved.
%
% Use of this source code is governed by a BSD-style license
% that can be found in the LICENSE file in the root of the source
% tree. An additional intellectual property rights grant can be found
% in the file PATENTS. All contributing pro... |
github | ubiquiti/ubnt_libjingle-main | apmtest.m | .m | ubnt_libjingle-main/modules/audio_processing/test/apmtest.m | 9,874 | utf_8 | 17ad6af59f6daa758d983dd419e46ff0 | %
% Copyright (c) 2011 The WebRTC project authors. All Rights Reserved.
%
% Use of this source code is governed by a BSD-style license
% that can be found in the LICENSE file in the root of the source
% tree. An additional intellectual property rights grant can be found
% in the file PATENTS. All contributing pro... |
github | ubiquiti/ubnt_libjingle-main | parse_delay_file.m | .m | ubnt_libjingle-main/modules/audio_coding/neteq/test/delay_tool/parse_delay_file.m | 6,405 | utf_8 | 4cc70d6f90e1ca5901104f77a7e7c0b3 | %
% Copyright (c) 2011 The WebRTC project authors. All Rights Reserved.
%
% Use of this source code is governed by a BSD-style license
% that can be found in the LICENSE file in the root of the source
% tree. An additional intellectual property rights grant can be found
% in the file PATENTS. All contributing pro... |
github | ubiquiti/ubnt_libjingle-main | plot_neteq_delay.m | .m | ubnt_libjingle-main/modules/audio_coding/neteq/test/delay_tool/plot_neteq_delay.m | 5,967 | utf_8 | cce342fed6406ef0f12d567fe3ab6eef | %
% Copyright (c) 2011 The WebRTC project authors. All Rights Reserved.
%
% Use of this source code is governed by a BSD-style license
% that can be found in the LICENSE file in the root of the source
% tree. An additional intellectual property rights grant can be found
% in the file PATENTS. All contributing pro... |
github | ubiquiti/ubnt_libjingle-main | rtpAnalyze.m | .m | ubnt_libjingle-main/tools_webrtc/matlab/rtpAnalyze.m | 7,892 | utf_8 | 46e63db0fa96270c14a0c205bbab42e4 | function rtpAnalyze( input_file )
%RTP_ANALYZE Analyze RTP stream(s) from a txt file
% The function takes the output from the command line tool rtp_analyze
% and analyzes the stream(s) therein. First, process your rtpdump file
% through rtp_analyze (from command line):
% $ out/Debug/rtp_analyze my_file.rtp my_f... |
github | italogsfernandes/imagens-medicas-2-master | medianFilter.m | .m | imagens-medicas-2-master/toolbox/matlab/medianFilter.m | 1,257 | utf_8 | 0b72b3acb2875c12e7bbffaab80de4c7 | %% Ronaldo Sena
% ronaldo.sena@outlook.com
% December 2017
% Use it as you please. If we meet some day, and you think
% this stuff was helpful, you can buy me a beer
% Shout out to professor Ana Claudia, for the inspiring code
%
% Median filter implementation using MATLAB's processing toolbox
%
% [output... |
github | italogsfernandes/imagens-medicas-2-master | gaussianFilter.m | .m | imagens-medicas-2-master/toolbox/matlab/gaussianFilter.m | 2,259 | utf_8 | ca917db62ab616e6c91bb43b33d93bf0 | %% Ronaldo Sena
% ronaldo.sena@outlook.com
% December 2017
% Use it as you please. If we meet some day, and you think
% this stuff was helpful, you can buy me a beer
%
% Gaussian filter. Takes an image and the mask radius and
% oupts the filtered image in same type
%
% [outputImage] = gaussianFilter(inpu... |
github | italogsfernandes/imagens-medicas-2-master | quadTreeSegmentation.m | .m | imagens-medicas-2-master/toolbox/matlab/quadTreeSegmentation.m | 3,239 | utf_8 | 3274f9ad9bc68bf061743b266ae4ddb0 | %% Ronaldo Sena
% ronaldo.sena@outlook.com
% December 2017
% Use it as you please. If we meet some day, and you think
% this stuff was helpful, you can buy me a beer
%
% quadTreeSegmentation performs a tree segmentation on input image. Tree
% segmentation segments the input image in squares with similar ... |
github | italogsfernandes/imagens-medicas-2-master | butterworthFilter.m | .m | imagens-medicas-2-master/toolbox/matlab/butterworthFilter.m | 2,213 | utf_8 | f1d44f573adf23a13c9e0f0e81480220 | %% Ronaldo Sena
% ronaldo.sena@outlook.com
% December 2017
% Use it as you please. If we meet some day, and you think
% this stuff was helpful, you can buy me a beer
%
% Butterworth filter. Takes an image and the mask radius and
% oupts the filtered image in same type
%
% [outputImage] = butterworhtFilte... |
github | italogsfernandes/imagens-medicas-2-master | idealFilter.m | .m | imagens-medicas-2-master/toolbox/matlab/idealFilter.m | 2,287 | utf_8 | 73e9c1c7813ad2acb176585d59cb8aab | %% Ronaldo Sena
% ronaldo.sena@outlook.com
% December 2017
% Use it as you please. If we meet some day, and you think
% this stuff was helpful, you can buy me a beer
% Shout out to professor Ana Claudia, for the inspiring code
%
% Ideal low pass filter. Takes an image and the mask radius and
% oupts the ... |
github | italogsfernandes/imagens-medicas-2-master | k_means.m | .m | imagens-medicas-2-master/toolbox/matlab/k_means.m | 1,591 | utf_8 | 0946d0bdb704d4adc3796ad0a8efb53e | %% Ronaldo Sena
% ronaldo.sena@outlook.com
% December 2017
% Use it as you please. If we meet some day, and you think
% this stuff was helpful, you can buy me a beer
% This script is the one mentioned during the Computerphile's Image
% Segmentation video by Dr. Mike Pound.
%
% Takes a gray-scale input... |
github | italogsfernandes/imagens-medicas-2-master | geoAverageFilter.m | .m | imagens-medicas-2-master/toolbox/matlab/geoAverageFilter.m | 1,480 | utf_8 | 30906f3ec1bbcea31846b337cbd915aa | %% Ronaldo Sena
% ronaldo.sena@outlook.com
% December 2017
% Use it as you please. If we meet some day, and you think
% this stuff was helpful, you can buy me a beer
% Shout out to professor Ana Claudia, for the inspiring code.
% Also to Steve Eddins @ Mathworks!
%
% Geometric average filter implementati... |
github | italogsfernandes/imagens-medicas-2-master | averageFilter.m | .m | imagens-medicas-2-master/toolbox/matlab/averageFilter.m | 1,290 | utf_8 | a1c9d731983b078ec2bfc1447531b091 | %% Ronaldo Sena
% ronaldo.sena@outlook.com
% December 2017
% Use it as you please. If we meet some day, and you think
% this stuff was helpful, you can buy me a beer
% Shout out to professor Ana Claudia, for the inspiring code
%
% Average filter implementation using MATLAB's processing toolbox
%
% [outpu... |
github | italogsfernandes/imagens-medicas-2-master | minimumFilter.m | .m | imagens-medicas-2-master/toolbox/matlab/minimumFilter.m | 1,253 | utf_8 | dc2c5c1b743521123a571dd059341a37 | %% Ronaldo Sena
% ronaldo.sena@outlook.com
% December 2017
% Use it as you please. If we meet some day, and you think
% this stuff was helpful, you can buy me a beer
% Shout out to professor Ana Claudia, for the inspiring code
%
% Minimum filter implementation using MATLAB's processing toolbox
%
% [outpu... |
github | italogsfernandes/imagens-medicas-2-master | maximumFilter.m | .m | imagens-medicas-2-master/toolbox/matlab/maximumFilter.m | 1,254 | utf_8 | bbdd97b8ef7a62d5967dfd13de04083f | %% Ronaldo Sena
% ronaldo.sena@outlook.com
% December 2017
% Use it as you please. If we meet some day, and you think
% this stuff was helpful, you can buy me a beer
% Shout out to professor Ana Claudia, for the inspiring code
%
% Maximum filter implementation using MATLAB's processing toolbox
%
% [outpu... |
github | italogsfernandes/imagens-medicas-2-master | insertNoise.m | .m | imagens-medicas-2-master/toolbox/matlab/insertNoise.m | 4,556 | utf_8 | 77f090eeef512021c89243525ec982d0 | %% Ronaldo Sena
% ronaldo.sena@outlook.com
% December 2017
% Use it as you please. If we meet some day, and you think
% this stuff was helpful, you can buy me a beer
% Shout out to professor Ana Claudia, for the inspiring code
%
% Ideal high pass filter. Takes in an image and a mask size and
% oupts the... |
github | italogsfernandes/imagens-medicas-2-master | IM2_app.m | .m | imagens-medicas-2-master/Apps/mIM2_app/IM2_app.m | 13,520 | utf_8 | 80c70f2ad2b7d9634737a578730ca7fc | %% Ronaldo Sena
% ronaldo.sena@outlook.com
% December 2017
% Use it as you please. If we meet some day, and you think
% this stuff was helpful, you can buy me a beer
% Shout out to professor Ana Claudia, for the inspiring code
%
% GUI to process medical images
%
%
% CONFIGURAÇ... |
github | namanUIUC/NonlinearComponentAnalysis-master | swap.m | .m | NonlinearComponentAnalysis-master/src/KPCA-projectcode/swap.m | 203 | utf_8 | 6a8e44f4608a6dbb307c50c538b7eb4e | %%FUNCTION USED TO SWAP WHILE SORTING (Not relevent for pca)
function x = swap(x,i,j)
% Swap x(i) and x(j)
% Note: In practice, x should be passed by reference
val = x(i);
x(i) = x(j);
x(j) = val;
end |
github | namanUIUC/NonlinearComponentAnalysis-master | kpca_code.m | .m | NonlinearComponentAnalysis-master/src/KPCA-projectcode/kpca_code.m | 2,884 | utf_8 | defa54c6d19a8a59ee48eaee69be9ead | clear all;
clc;
% loading data
load('usps_all')
% TEST DATA : M(observation/sample points) x N(features/dimensions)
X_test = double(data(:, 1:800, 1)');
% Center Data
mu = mean(X_test);
X_centered = bsxfun(@minus, X_test, mu);
% Define kernel
kernel = 'linear';
n= 3;
%Def: M and N
M = size(X_centered,1);
N = size(... |
github | andrewwarrington/vesicle-cnn-2-master | pr_evaluate_voxel_logit.m | .m | vesicle-cnn-2-master/evaluation/pr_evaluate_voxel_logit.m | 3,951 | utf_8 | 1a0b911f8f934aa2eefb05476c76396d | function [metrics] = pr_evaluate_voxel_logit(path, h5File, channel, pp, fileOut)
% Takes inputs of the predicted volume (matrix or location) and the truth
% volume (matrix or location) and sweeps through thresholds of probability,
% evalating F1 (and F1 related metrics) at each bin. Then saves this data
% to saveloc.
... |
github | andrewwarrington/vesicle-cnn-2-master | bwdistsc1.m | .m | vesicle-cnn-2-master/Prior_art/vesicle/packages/vesiclerf/tools/bwdistsc/bwdistsc1.m | 19,630 | utf_8 | 003a8729f0ccdb35a49d8429ea605c64 | function D=bwdistsc1(bw,aspect,maxval)
% D=BWDISTSC1(BW,ASPECT,MAXVAL)
% BWDISTSC1 computes Euclidean distance transform of a binary 3D image
% BW out to a specified value MAXVAL. This allows accelerating the
% calculations in some cases with strongly nonconvex geometries, if the
% distance transform only needs to b... |
github | andrewwarrington/vesicle-cnn-2-master | classRF_predict.m | .m | vesicle-cnn-2-master/Prior_art/vesicle/packages/vesiclerf/tools/Random Forest/classRF_predict.m | 2,166 | utf_8 | 7e026fb9b31f99feae58d36b9cf6c2e0 | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Classification Random Forest
% A wrapper matlab file that calls... |
github | andrewwarrington/vesicle-cnn-2-master | classRF_train.m | .m | vesicle-cnn-2-master/Prior_art/vesicle/packages/vesiclerf/tools/Random Forest/classRF_train.m | 14,829 | utf_8 | 82a321d0a7c77f33b104acec4394c6ee | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Classification Random Forest
% A wrapper matlab file that calls... |
github | andrewwarrington/vesicle-cnn-2-master | structureTensorImage2.m | .m | vesicle-cnn-2-master/Prior_art/vesicle/packages/vesiclerf/tools/structure_tensor/structureTensorImage2.m | 2,078 | utf_8 | a9f4eb4f44095b9695bc66b79eca3cbd | %[eig1, eig2, cw] = structureTensorImage2(im, s, sg)
%s: smoothing sigma
%sg: sigma gaussian for summation weights
%window size is adapted
function [eig1, eig2, cw] = structureTensorImage2(im, s, sg)
w = 2*sg;
[gx,gy,mag] = gradientImg(double(im),s);
clear mag;
S_0_x = gx.*gx;
S_0_xy = gx.*gy;
S_0_y = gy... |
github | andrewwarrington/vesicle-cnn-2-master | gradientImg.m | .m | vesicle-cnn-2-master/Prior_art/vesicle/packages/vesiclerf/tools/structure_tensor/gradientImg.m | 413 | utf_8 | caa4df879004f65177163e8185112940 | %function [gx, gy, mag] = gradientImg(im, s)
function [gx, gy, mag] = gradientImg(im, s)
% $$$ fg = fspecial('gaussian',4*s,s);
% $$$ fs = fspecial('sobel');
% $$$
% $$$ fgy = filter2(fs,fg);
% $$$ fgx = filter2(fs',fg);
% $$$
% $$$ fgm = sqrt(fgx.^2 + fgy.^2);
% $$$
% $$$ gy = filter2(fgy,im);
% $$$ gx = filter2(... |
github | andrewwarrington/vesicle-cnn-2-master | bwdistsc1.m | .m | vesicle-cnn-2-master/vesiclerf-2/tools/bwdistsc/bwdistsc1.m | 19,630 | utf_8 | 003a8729f0ccdb35a49d8429ea605c64 | function D=bwdistsc1(bw,aspect,maxval)
% D=BWDISTSC1(BW,ASPECT,MAXVAL)
% BWDISTSC1 computes Euclidean distance transform of a binary 3D image
% BW out to a specified value MAXVAL. This allows accelerating the
% calculations in some cases with strongly nonconvex geometries, if the
% distance transform only needs to b... |
github | andrewwarrington/vesicle-cnn-2-master | classRF_predict.m | .m | vesicle-cnn-2-master/vesiclerf-2/tools/Random Forest/classRF_predict.m | 2,166 | utf_8 | 7e026fb9b31f99feae58d36b9cf6c2e0 | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Classification Random Forest
% A wrapper matlab file that calls... |
github | andrewwarrington/vesicle-cnn-2-master | classRF_train.m | .m | vesicle-cnn-2-master/vesiclerf-2/tools/Random Forest/classRF_train.m | 14,829 | utf_8 | 82a321d0a7c77f33b104acec4394c6ee | %**************************************************************
%* mex interface to Andy Liaw et al.'s C code (used in R package randomForest)
%* Added by Abhishek Jaiantilal ( abhishek.jaiantilal@colorado.edu )
%* License: GPLv2
%* Version: 0.02
%
% Calls Classification Random Forest
% A wrapper matlab file that calls... |
github | andrewwarrington/vesicle-cnn-2-master | structureTensorImage2.m | .m | vesicle-cnn-2-master/vesiclerf-2/tools/structure_tensor/structureTensorImage2.m | 2,078 | utf_8 | a9f4eb4f44095b9695bc66b79eca3cbd | %[eig1, eig2, cw] = structureTensorImage2(im, s, sg)
%s: smoothing sigma
%sg: sigma gaussian for summation weights
%window size is adapted
function [eig1, eig2, cw] = structureTensorImage2(im, s, sg)
w = 2*sg;
[gx,gy,mag] = gradientImg(double(im),s);
clear mag;
S_0_x = gx.*gx;
S_0_xy = gx.*gy;
S_0_y = gy... |
github | andrewwarrington/vesicle-cnn-2-master | gradientImg.m | .m | vesicle-cnn-2-master/vesiclerf-2/tools/structure_tensor/gradientImg.m | 413 | utf_8 | caa4df879004f65177163e8185112940 | %function [gx, gy, mag] = gradientImg(im, s)
function [gx, gy, mag] = gradientImg(im, s)
% $$$ fg = fspecial('gaussian',4*s,s);
% $$$ fs = fspecial('sobel');
% $$$
% $$$ fgy = filter2(fs,fg);
% $$$ fgx = filter2(fs',fg);
% $$$
% $$$ fgm = sqrt(fgx.^2 + fgy.^2);
% $$$
% $$$ gy = filter2(fgy,im);
% $$$ gx = filter2(... |
github | mariajantz/kalmanGUI-master | test_dist_plot.m | .m | kalmanGUI-master/test_dist_plot.m | 2,536 | utf_8 | caffe3cf8576dac3aef5983900c6bae9 | close all;
mcell = {[1 0] [0 0] [5 .5]};
pcell = {[1 .1; .1 1], [.5 0; 0 1], [1 .1; .1 .5]}; %MUST BE SQUARE POSITIVE MATRIX
plot_dist(mcell, pcell);
function plot_dist(mu_cell, phi_cell)
%define colors for the signal, model, and combined distributions
redcolors = [184 6 0; 229 136 125]/255; %dark, then light
blueco... |
github | acados/qpOASES-master | make.m | .m | qpOASES-master/interfaces/simulink/make.m | 8,234 | utf_8 | 38b8382423ef0ca7023a8d6912f0416b | function [] = make( varargin )
%MAKE Compiles the Simulink interface of qpOASES_e.
%
%Type make to compile all interfaces that
% have been modified,
%type make clean to delete all compiled interfaces,
%type make clean all to first delete and then compile
% ... |
github | acados/qpOASES-master | qpOASES_e_auxInput.m | .m | qpOASES-master/interfaces/matlab/qpOASES_e_auxInput.m | 4,464 | utf_8 | 3cda1474246b8abd61a797cea451dbd1 | %qpOASES -- An Implementation of the Online Active Set Strategy.
%Copyright (C) 2007-2015 by Hans Joachim Ferreau, Andreas Potschka,
%Christian Kirches et al. All rights reserved.
%
%qpOASES is distributed under the terms of the
%GNU Lesser General Public License 2.1 in the hope that it will be
%useful, but WITHOUT ANY... |
github | acados/qpOASES-master | make.m | .m | qpOASES-master/interfaces/matlab/make.m | 8,288 | utf_8 | 3f51786f16fadf166e502ca7a1ea2538 | function [] = make( varargin )
%MAKE Compiles the Matlab interface of qpOASES_e.
%
%Type make to compile all interfaces that
% have been modified,
%type make clean to delete all compiled interfaces,
%type make clean all to first delete and then compile
% ... |
github | acados/qpOASES-master | qpOASES_e_options.m | .m | qpOASES-master/interfaces/matlab/qpOASES_e_options.m | 10,413 | utf_8 | 7094632bf1ee692f7c7d22ac38754401 | %qpOASES -- An Implementation of the Online Active Set Strategy.
%Copyright (C) 2007-2015 by Hans Joachim Ferreau, Andreas Potschka,
%Christian Kirches et al. All rights reserved.
%
%qpOASES is distributed under the terms of the
%GNU Lesser General Public License 2.1 in the hope that it will be
%useful, but WITHOUT ANY... |
github | joe-of-all-trades/OCT_Analysis-master | datainterp.m | .m | OCT_Analysis-master/datainterp.m | 582 | utf_8 | bbf962dc7fa6305d14a041e5016ea8a5 | % This script is written by Chao-yuan Yeh. All copyrights reserved.
function output = datainterp( input, varargin)
if strcmpi(varargin, '45')
temp = diff(round(input(:,1)/sin(pi/4)));
elseif strcmpi(varargin, 'x')
temp = diff(round(input(:,1)));
elseif strcmpi(varargin, 'y')
temp = diff(round(input(:,2)))... |
github | joe-of-all-trades/OCT_Analysis-master | OCT_process_file.m | .m | OCT_Analysis-master/OCT_process_file.m | 2,548 | utf_8 | 40998a86705277ee1ce8757e6041a103 | % This script is written by Chao-Yuan Yeh. All copyrights reserved.
function OCT_process_file_pub
root_folder = uigetdir('', 'select root folder containing all OCT data');
recur_proc(root_folder)
% Consider alternative implementation using built-in genpath function
matlab_path = strsplit(matlabpath, ';');
home_path = ... |
github | yasharhezaveh/Ensai-master | Lensing_TrainingImage_Generator.m | .m | Ensai-master/src/Lensing_TrainingImage_Generator.m | 27,698 | utf_8 | 480cbc2902655c7cbff9cd903edf1d2b | function [IMS,PARAMS,src_pars,log_kappa] = Lensing_TrainingImage_Generator(nsample,random_seed, WRITE , test_or_train)
%WRITE = 1
%test_or_train = 'test'
if ~exist('WRITE','var')
WRITE = 0;
end
rng(random_seed)
zLENS = 0.5;
zSOURCE = 2.00;
h=0.71;
OmegaC=0.222;
OmegaLambda=0.734;
sigNORM=0.801;
OmegaBaryon=0.... |
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