function test_suite=test_correlation_measure
% tests for cosmo_correlation_measure
%
% # For CoSMoMVPA's copyright information and license terms, #
% # see the COPYING file distributed with CoSMoMVPA. #
try % assignment of 'localfunctions' is necessary in Matlab >= 2016
test_functions=localfunctions();
catch % no problem; early Matlab versions can use initTestSuite fine
end
initTestSuite;
function test_correlation_measure_basis()
ds3=cosmo_synthetic_dataset('nchunks',3,'ntargets',4);
ds=cosmo_slice(ds3,ds3.sa.chunks<=2);
ds.sa.chunks=ds.sa.chunks+10;
ds.sa.targets=ds.sa.targets+20;
x=ds.samples(ds.sa.chunks==11,:);
y=ds.samples(ds.sa.chunks==12,:);
cxy=atanh(corr(x',y'));
diag_msk=eye(4)>0;
c_diag=mean(cxy(diag_msk));
c_off_diag=mean(cxy(~diag_msk));
delta=c_diag-c_off_diag;
c1=cosmo_correlation_measure(ds);
assertElementsAlmostEqual(delta,c1.samples,'relative',1e-5);
assertEqual(c1.sa.labels,{'corr'});
% reset state and do not show warnings
orig_warning_state=cosmo_warning();
warning_cleaner=onCleanup(@()cosmo_warning(orig_warning_state));
cosmo_warning('reset');
cosmo_warning('off');
c2=cosmo_correlation_measure(ds,'output','correlation');
assertElementsAlmostEqual(reshape(cxy,[],1),c2.samples);
assertEqual(kron((1:4)',ones(4,1)),c2.sa.half2);
assertEqual(repmat((1:4)',4,1),c2.sa.half1);
i=7;
assertElementsAlmostEqual(cxy(c2.sa.half1(i),c2.sa.half2(i)),...
c2.samples(i));
assertEqual({'half1','half2'},c2.a.sdim.labels);
assertEqual({20+(1:4)',20+(1:4)'},c2.a.sdim.values);
c4=cosmo_correlation_measure(ds3,'output','mean_by_fold');
%
for j=1:3
train_idxs=(3-j)*4+(1:4);
test_idxs=setdiff(1:12,train_idxs);
ds_sel=ds3;
ds_sel.sa.chunks(train_idxs)=2;
ds_sel.sa.chunks(test_idxs)=1;
c5=cosmo_correlation_measure(ds_sel,'output','mean');
assertElementsAlmostEqual(c5.samples, c4.samples(j));
end
% test permutations
ds4=cosmo_synthetic_dataset('nchunks',2,'ntargets',10);
rp=randperm(20);
ds4_perm=cosmo_slice(ds4,rp);
assertEqual(cosmo_correlation_measure(ds4),...
cosmo_correlation_measure(ds4_perm));
opt=struct();
opt.output='correlation';
assertEqual(cosmo_correlation_measure(ds4,opt),...
cosmo_correlation_measure(ds4_perm,opt));
function test_correlation_measure_single_target
for ntargets=2:6
ds=cosmo_synthetic_dataset('nchunks',2,'ntargets',ntargets);
ds.samples=randn(size(ds.samples));
ds.sa.targets(:)=1;
idxs=cosmo_index_unique(mod(ds.sa.chunks,2));
assert(numel(idxs)==2);
x=mean(ds.samples(idxs{1},:));
y=mean(ds.samples(idxs{2},:));
r_xy=atanh(corr(x',y'));
r_ds=cosmo_correlation_measure(ds,'template',1);
assertElementsAlmostEqual(r_xy, r_ds.samples);
end
function test_correlation_measure_regression()
helper_test_correlation_measure_regression(false);
function test_correlation_measure_regression_spearman()
if cosmo_skip_test_if_no_external('@stats')
return;
end
helper_test_correlation_measure_regression(true);
function helper_test_correlation_measure_regression(test_spearman)
% reset state and do not show warnings
orig_warning_state=cosmo_warning();
warning_cleaner=onCleanup(@()cosmo_warning(orig_warning_state));
cosmo_warning('reset');
cosmo_warning('off');
ds=cosmo_synthetic_dataset('ntargets',3,'nchunks',5,'sigma',.5);
params=get_regression_test_params(test_spearman);
n_params=numel(params);
for k=1:n_params
param=params{k};
args=param{1};
samples=param{2};
sa=param{3};
sdim=param{4};
res=cosmo_correlation_measure(ds,args{:});
% test samples
assertElementsAlmostEqual(res.samples,samples','absolute',5e-3);
% test sa
keys=fieldnames(res.sa);
assertEqual(sort(keys(:)), sort(sa(1:2:end))');
for j=1:2:numel(sa)
key=sa{j};
value=sa{j+1};
assertEqual(res.sa.(key),value(:));
end
% test sa
if isempty(sdim)
assertFalse(isfield(res,'a'))
else
keys=fieldnames(res.a.sdim);
assertEqual(sort(keys(:)), sort(sdim(1:2:end))');
for j=1:2:numel(sa)
key=sdim{j};
value=sdim{j+1};
sdim_value=res.a.sdim.(key);
assertEqual(sdim_value(:),value(:));
end
end
end
function params=get_regression_test_params(test_spearman)
% contents
% 1) input arguments
% 2) samples
% 3) sample attributes
% 4) sdim
if test_spearman
params={{{ 'corr_type' 'Spearman' },...
-0.228,...
{ 'labels' { 'corr' } },...
[]}};
else
params={{{ },...
-0.24,...
{ 'labels' { 'corr' } },...
[]},...
{{ 'template' [ -2 2 3; -1 1 2; 2 -4 -3 ] },...
2.48,...
{ 'labels' { 'corr' } },...
[]},...
{{ 'merge_func' @(x)sum(abs(x),1) },...
0.567,...
{ 'labels' { 'corr' } },...
[]},...
{{ 'post_corr_func' @(x)x+1 },...
-0.204,...
{ 'labels' { 'corr' } },...
[]},...
{{ 'output' 'mean_by_fold' },...
[ -0.289 -0.274 -0.532 -0.112 -0.269 ...
-0.0535 -0.203 -0.3 -0.198 -0.173 ],...
{ 'partition' [ 1 2 3 4 5 6 7 8 9 10 ] },...
[]},...
{{ 'output' 'correlation' },...
[ -0.649 0.0675 0.345 0.126 0.643 ...
0.413 0.266 0.399 0.0933 ],...
{ 'half1', [ 1 2 3 1 2 3 1 2 3 ],...
'half2' [ 1 1 1 2 2 2 3 3 3 ] },...
{ 'labels' { 'half1' 'half2' },...
'values' { [ 1 2 3 ]' [ 1 2 3 ]' } }
}};
end
function test_correlation_measure_exceptions
aet=@(varargin)assertExceptionThrown(@()...
cosmo_correlation_measure(varargin{:}),'');
% reset state and do not show warnings
orig_warning_state=cosmo_warning();
warning_cleaner=onCleanup(@()cosmo_warning(orig_warning_state));
cosmo_warning('reset');
cosmo_warning('off');
ds=cosmo_synthetic_dataset('nchunks',2);
aet(ds,'template',eye(4));
aet(ds,'output','foo');
aet(ds,'output','one_minus_correlation');
% single target throws exception
ds.sa.targets(:)=1;
aet(ds);
aet(ds,'template',2);
aet(ds,'template',eye(2));
ds.sa.targets(1)=2;
aet(ds);
function x=identity(x)
function test_correlation_measure_warning_shown_if_no_defaults()
orig_warning_state=cosmo_warning();
cleaner=onCleanup(@()cosmo_warning(orig_warning_state));
% reset state and do not show warnings
cosmo_warning('reset');
cosmo_warning('off');
funcs={[],@atanh};
outputs={[],'mean','raw','correlation'};
for k=1:numel(funcs)
func=funcs{k};
for j=1:numel(outputs)
output=outputs{j};
is_default_func=k<=2;
is_default_output=j<=2;
expect_warning=~(is_default_func && is_default_output);
opt=struct();
if ~isempty(func)
opt.post_corr_func=func;
end
if ~isempty(output)
opt.output=output;
end
cosmo_warning('reset');
cosmo_warning('off');
ds=cosmo_synthetic_dataset('nchunks',2);
cosmo_correlation_measure(ds,opt);
s=cosmo_warning();
showed_warning=numel(s.shown_warnings)>0;
assertEqual(expect_warning,showed_warning);
end
end
function test_correlation_measure_wrong_template_size()
ds=cosmo_synthetic_dataset('nchunks',2,'ntargets',2);
measure_args=struct();
measure_args.template = [ 1 -1 0 0 ; ...
-1 1 0 0 ; ...
0 0 1 -1 ;
0 0 -1 1 ];
measure=@cosmo_correlation_measure;
assertExceptionThrown(@()measure(ds,measure_args));
