elephant.test.test_spike_train_correlation module

Unit tests for the spike_train_correlation module.

class elephant.test.test_spike_train_correlation.SpikeTimeTilingCoefficientTestCase(methodName='runTest')[source]

Bases: unittest.case.TestCase

Methods

setUp()[source]
test_exist_alias()[source]
test_sttc()[source]
class elephant.test.test_spike_train_correlation.corrcoeff_TestCase(methodName='runTest')[source]

Bases: unittest.case.TestCase

Methods

setUp()[source]
test_corrcoef_binned()[source]

Test the correlation coefficient between two binned spike trains.

test_corrcoef_binned_same_spiketrains()[source]

Test if the correlation coefficient between two identical binned spike trains evaluates to a 2x2 matrix of ones.

test_corrcoef_binned_short_input()[source]

Test if input list of one binned spike train yields 1.0.

class elephant.test.test_spike_train_correlation.covariance_TestCase(methodName='runTest')[source]

Bases: unittest.case.TestCase

Methods

setUp()[source]
test_covariance_binned()[source]

Test covariance between two binned spike trains.

test_covariance_binned_same_spiketrains()[source]

Test if the covariation between two identical binned spike trains evaluates to the expected 2x2 matrix.

test_covariance_binned_short_input()[source]

Test if input list of only one binned spike train yields correct result that matches numpy.cov (covariance with itself)

class elephant.test.test_spike_train_correlation.cross_correlation_histogram_TestCase(methodName='runTest')[source]

Bases: unittest.case.TestCase

Methods

setUp()[source]
test_border_correction()[source]

Test if the border correction for bins at the edges is correctly performed

test_cross_correlation_histogram()[source]

Test generic result of a cross-correlation histogram between two binned spike trains.

test_exist_alias()[source]

Test if alias cch still exists.

test_kernel()[source]

Test if the smoothing kernel is correctly defined, and wheter it is applied properly.

test_raising_error_wrong_inputs()[source]

Check that an exception is thrown if the two spike trains are not fullfilling the requirement of the function

test_window()[source]

Test if the window parameter is correctly interpreted.