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- Running unit tests for scipy
- NumPy version 2.0.0.dev8672
- NumPy is installed in /usr/lib/python2.6/site-packages/numpy
- SciPy version 0.9.0.dev6651
- SciPy is installed in /usr/lib/python2.6/site-packages/scipy
- Python version 2.6.4 (r264:75706, Jun 4 2010, 18:20:16) [GCC 4.4.4 20100503 (Red Hat 4.4.4-2)]
- nose version 0.11.3
- nose.config: INFO: Excluding tests matching ['f2py_ext', 'f2py_f90_ext', 'gen_ext', 'pyrex_ext', 'swig_ext']
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/fftpack/convolve.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/integrate/vode.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/interpolate/dfitpack.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/io/matlab/mio5_utils.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/io/matlab/mio_utils.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/io/matlab/streams.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/lib/blas/cblas.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/lib/blas/fblas.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/lib/lapack/atlas_version.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/lib/lapack/calc_lwork.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/lib/lapack/clapack.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/lib/lapack/flapack.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/linalg/atlas_version.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/linalg/calc_lwork.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/linalg/cblas.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/linalg/clapack.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/linalg/fblas.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/linalg/flapack.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/optimize/minpack2.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/optimize/moduleTNC.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/signal/sigtools.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/signal/spline.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/spatial/ckdtree.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/special/lambertw.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/special/orthogonal_eval.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/special/specfun.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/stats/futil.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/stats/mvn.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/stats/statlib.so is executable; skipped
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/stats/vonmises_cython.so is executable; skipped
- Tests cophenet(Z) on tdist data set. ... ok
- Tests cophenet(Z, Y) on tdist data set. ... ok
- Tests correspond(Z, y) on linkage and CDMs over observation sets of different sizes. ... ok
- Tests correspond(Z, y) on linkage and CDMs over observation sets of different sizes. Correspondance should be false. ... ok
- Tests correspond(Z, y) on linkage and CDMs over observation sets of different sizes. Correspondance should be false. ... ok
- Tests correspond(Z, y) with empty linkage and condensed distance matrix. ... ok
- Tests num_obs_linkage with observation matrices of multiple sizes. ... ok
- Tests fcluster(Z, criterion='maxclust', t=2) on a random 3-cluster data set. ... ok
- Tests fcluster(Z, criterion='maxclust', t=3) on a random 3-cluster data set. ... ok
- Tests fcluster(Z, criterion='maxclust', t=4) on a random 3-cluster data set. ... ok
- Tests fclusterdata(X, criterion='maxclust', t=2) on a random 3-cluster data set. ... ok
- Tests fclusterdata(X, criterion='maxclust', t=3) on a random 3-cluster data set. ... ok
- Tests fclusterdata(X, criterion='maxclust', t=4) on a random 3-cluster data set. ... ok
- Tests from_mlab_linkage on empty linkage array. ... ok
- Tests from_mlab_linkage on linkage array with multiple rows. ... ok
- Tests from_mlab_linkage on linkage array with single row. ... ok
- Tests inconsistency matrix calculation (depth=1) on a complete linkage. ... ok
- Tests inconsistency matrix calculation (depth=2) on a complete linkage. ... ok
- Tests inconsistency matrix calculation (depth=3) on a complete linkage. ... ok
- Tests inconsistency matrix calculation (depth=4) on a complete linkage. ... ok
- Tests inconsistency matrix calculation (depth=1, dataset=Q) with single linkage. ... ok
- Tests inconsistency matrix calculation (depth=2, dataset=Q) with single linkage. ... ok
- Tests inconsistency matrix calculation (depth=3, dataset=Q) with single linkage. ... ok
- Tests inconsistency matrix calculation (depth=4, dataset=Q) with single linkage. ... ok
- Tests inconsistency matrix calculation (depth=1) on a single linkage. ... ok
- Tests inconsistency matrix calculation (depth=2) on a single linkage. ... ok
- Tests inconsistency matrix calculation (depth=3) on a single linkage. ... ok
- Tests inconsistency matrix calculation (depth=4) on a single linkage. ... ok
- Tests is_isomorphic on test case #1 (one flat cluster, different labellings) ... ok
- Tests is_isomorphic on test case #2 (two flat clusters, different labelings) ... ok
- Tests is_isomorphic on test case #3 (no flat clusters) ... ok
- Tests is_isomorphic on test case #4A (3 flat clusters, different labelings, isomorphic) ... ok
- Tests is_isomorphic on test case #4B (3 flat clusters, different labelings, nonisomorphic) ... ok
- Tests is_isomorphic on test case #4C (3 flat clusters, different labelings, isomorphic) ... ok
- Tests is_isomorphic on test case #5A (1000 observations, 2 random clusters, random permutation of the labeling). Run 3 times. ... ok
- Tests is_isomorphic on test case #5B (1000 observations, 3 random clusters, random permutation of the labeling). Run 3 times. ... ok
- Tests is_isomorphic on test case #5C (1000 observations, 5 random clusters, random permutation of the labeling). Run 3 times. ... ok
- Tests is_isomorphic on test case #5A (1000 observations, 2 random clusters, random permutation of the labeling, slightly nonisomorphic.) Run 3 times. ... ok
- Tests is_isomorphic on test case #5B (1000 observations, 3 random clusters, random permutation of the labeling, slightly nonisomorphic.) Run 3 times. ... ok
- Tests is_isomorphic on test case #5C (1000 observations, 5 random clusters, random permutation of the labeling, slightly non-isomorphic.) Run 3 times. ... ok
- Tests is_monotonic(Z) on 1x4 linkage. Expecting True. ... ok
- Tests is_monotonic(Z) on 2x4 linkage. Expecting False. ... ok
- Tests is_monotonic(Z) on 2x4 linkage. Expecting True. ... ok
- Tests is_monotonic(Z) on 3x4 linkage (case 1). Expecting False. ... ok
- Tests is_monotonic(Z) on 3x4 linkage (case 2). Expecting False. ... ok
- Tests is_monotonic(Z) on 3x4 linkage (case 3). Expecting False ... ok
- Tests is_monotonic(Z) on 3x4 linkage. Expecting True. ... ok
- Tests is_monotonic(Z) on an empty linkage. ... ok
- Tests is_monotonic(Z) on clustering generated by single linkage on Iris data set. Expecting True. ... ok
- Tests is_monotonic(Z) on clustering generated by single linkage on tdist data set. Perturbing. Expecting False. ... ok
- Tests is_valid_im(R) on im over 2 observations. ... ok
- Tests is_valid_im(R) on im over 3 observations. ... ok
- Tests is_valid_im(R) with 3 columns. ... ok
- Tests is_valid_im(R) on im on observation sets between sizes 4 and 15 (step size 3). ... ok
- Tests is_valid_im(R) on im on observation sets between sizes 4 and 15 (step size 3) with negative link counts. ... ok
- Tests is_valid_im(R) on im on observation sets between sizes 4 and 15 (step size 3) with negative link height means. ... ok
- Tests is_valid_im(R) on im on observation sets between sizes 4 and 15 (step size 3) with negative link height standard deviations. ... ok
- Tests is_valid_im(R) with 5 columns. ... ok
- Tests is_valid_im(R) with empty inconsistency matrix. ... ok
- Tests is_valid_im(R) with integer type. ... ok
- Tests is_valid_linkage(Z) on linkage over 2 observations. ... ok
- Tests is_valid_linkage(Z) on linkage over 3 observations. ... ok
- Tests is_valid_linkage(Z) with 3 columns. ... ok
- Tests is_valid_linkage(Z) on linkage on observation sets between sizes 4 and 15 (step size 3). ... ok
- Tests is_valid_linkage(Z) on linkage on observation sets between sizes 4 and 15 (step size 3) with negative counts. ... ok
- Tests is_valid_linkage(Z) on linkage on observation sets between sizes 4 and 15 (step size 3) with negative distances. ... ok
- Tests is_valid_linkage(Z) on linkage on observation sets between sizes 4 and 15 (step size 3) with negative indices (left). ... ok
- Tests is_valid_linkage(Z) on linkage on observation sets between sizes 4 and 15 (step size 3) with negative indices (right). ... ok
- Tests is_valid_linkage(Z) with 5 columns. ... ok
- Tests is_valid_linkage(Z) with empty linkage. ... ok
- Tests is_valid_linkage(Z) with integer type. ... ok
- Tests leaders using a flat clustering generated by single linkage. ... ok
- Tests leaves_list(Z) on a 1x4 linkage. ... ok
- Tests leaves_list(Z) on a 2x4 linkage. ... ok
- Tests leaves_list(Z) on the Iris data set using average linkage. ... ok
- Tests leaves_list(Z) on the Iris data set using centroid linkage. ... ok
- Tests leaves_list(Z) on the Iris data set using complete linkage. ... ok
- Tests leaves_list(Z) on the Iris data set using median linkage. ... ok
- Tests leaves_list(Z) on the Iris data set using single linkage. ... ok
- Tests leaves_list(Z) on the Iris data set using ward linkage. ... ok
- Tests linkage(Y, 'average') on the tdist data set. ... ok
- Tests linkage(Y, 'centroid') on the Q data set. ... ok
- Tests linkage(Y, 'complete') on the Q data set. ... ok
- Tests linkage(Y, 'complete') on the tdist data set. ... ok
- Tests linkage(Y) where Y is a 0x4 linkage matrix. Exception expected. ... ok
- Tests linkage(Y, 'single') on the Q data set. ... ok
- Tests linkage(Y, 'single') on the tdist data set. ... ok
- Tests linkage(Y, 'weighted') on the Q data set. ... ok
- Tests linkage(Y, 'weighted') on the tdist data set. ... ok
- Tests maxdists(Z) on the Q data set using centroid linkage. ... ok
- Tests maxdists(Z) on the Q data set using complete linkage. ... ok
- Tests maxdists(Z) on the Q data set using median linkage. ... ok
- Tests maxdists(Z) on the Q data set using single linkage. ... ok
- Tests maxdists(Z) on the Q data set using Ward linkage. ... ok
- Tests maxdists(Z) on empty linkage. Expecting exception. ... ok
- Tests maxdists(Z) on linkage with one cluster. ... ok
- Tests maxinconsts(Z, R) on the Q data set using centroid linkage. ... ok
- Tests maxinconsts(Z, R) on the Q data set using complete linkage. ... ok
- Tests maxinconsts(Z, R) on the Q data set using median linkage. ... ok
- Tests maxinconsts(Z, R) on the Q data set using single linkage. ... ok
- Tests maxinconsts(Z, R) on the Q data set using Ward linkage. ... ok
- Tests maxinconsts(Z, R) on linkage and inconsistency matrices with different numbers of clusters. Expecting exception. ... ok
- Tests maxinconsts(Z, R) on empty linkage. Expecting exception. ... ok
- Tests maxinconsts(Z, R) on linkage with one cluster. ... ok
- Tests maxRstat(Z, R, 0) on the Q data set using centroid linkage. ... ok
- Tests maxRstat(Z, R, 0) on the Q data set using complete linkage. ... ok
- Tests maxRstat(Z, R, 0) on the Q data set using median linkage. ... ok
- Tests maxRstat(Z, R, 0) on the Q data set using single linkage. ... ok
- Tests maxRstat(Z, R, 0) on the Q data set using Ward linkage. ... ok
- Tests maxRstat(Z, R, 0) on linkage and inconsistency matrices with different numbers of clusters. Expecting exception. ... ok
- Tests maxRstat(Z, R, 0) on empty linkage. Expecting exception. ... ok
- Tests maxRstat(Z, R, 0) on linkage with one cluster. ... ok
- Tests maxRstat(Z, R, 1) on the Q data set using centroid linkage. ... ok
- Tests maxRstat(Z, R, 1) on the Q data set using complete linkage. ... ok
- Tests maxRstat(Z, R, 1) on the Q data set using median linkage. ... ok
- Tests maxRstat(Z, R, 1) on the Q data set using single linkage. ... ok
- Tests maxRstat(Z, R, 1) on the Q data set using Ward linkage. ... ok
- Tests maxRstat(Z, R, 1) on linkage and inconsistency matrices with different numbers of clusters. Expecting exception. ... ok
- Tests maxRstat(Z, R, 1) on empty linkage. Expecting exception. ... ok
- Tests maxRstat(Z, R, 1) on linkage with one cluster. ... ok
- Tests maxRstat(Z, R, 2) on the Q data set using centroid linkage. ... ok
- Tests maxRstat(Z, R, 2) on the Q data set using complete linkage. ... ok
- Tests maxRstat(Z, R, 2) on the Q data set using median linkage. ... ok
- Tests maxRstat(Z, R, 2) on the Q data set using single linkage. ... ok
- Tests maxRstat(Z, R, 2) on the Q data set using Ward linkage. ... ok
- Tests maxRstat(Z, R, 2) on linkage and inconsistency matrices with different numbers of clusters. Expecting exception. ... ok
- Tests maxRstat(Z, R, 2) on empty linkage. Expecting exception. ... ok
- Tests maxRstat(Z, R, 2) on linkage with one cluster. ... ok
- Tests maxRstat(Z, R, 3) on the Q data set using centroid linkage. ... ok
- Tests maxRstat(Z, R, 3) on the Q data set using complete linkage. ... ok
- Tests maxRstat(Z, R, 3) on the Q data set using median linkage. ... ok
- Tests maxRstat(Z, R, 3) on the Q data set using single linkage. ... ok
- Tests maxRstat(Z, R, 3) on the Q data set using Ward linkage. ... ok
- Tests maxRstat(Z, R, 3) on linkage and inconsistency matrices with different numbers of clusters. Expecting exception. ... ok
- Tests maxRstat(Z, R, 3) on empty linkage. Expecting exception. ... ok
- Tests maxRstat(Z, R, 3) on linkage with one cluster. ... ok
- Tests maxRstat(Z, R, 3.3). Expecting exception. ... ok
- Tests maxRstat(Z, R, -1). Expecting exception. ... ok
- Tests maxRstat(Z, R, 4). Expecting exception. ... ok
- Tests num_obs_linkage(Z) on linkage over 2 observations. ... ok
- Tests num_obs_linkage(Z) on linkage over 3 observations. ... ok
- Tests num_obs_linkage(Z) on linkage on observation sets between sizes 4 and 15 (step size 3). ... ok
- Tests num_obs_linkage(Z) with empty linkage. ... ok
- Tests to_mlab_linkage on linkage array with multiple rows. ... ok
- Tests to_mlab_linkage on empty linkage array. ... ok
- Tests to_mlab_linkage on linkage array with single row. ... ok
- test_hierarchy.load_testing_files ... ok
- Ticket #505. ... ok
- Testing that kmeans2 init methods work. ... ok
- Testing simple call to kmeans2 with rank 1 data. ... ok
- Testing simple call to kmeans2 with rank 1 data. ... ok
- Testing simple call to kmeans2 and its results. ... ok
- Regression test for #546: fail when k arg is 0. ... ok
- This will cause kmean to have a cluster with no points. ... ok
- test_kmeans_simple (test_vq.TestKMean) ... ok
- test_large_features (test_vq.TestKMean) ... ok
- test_py_vq (test_vq.TestVq) ... ok
- test_py_vq2 (test_vq.TestVq) ... ok
- test_vq (test_vq.TestVq) ... ok
- Test special rank 1 vq algo, python implementation. ... ok
- nose.selector: INFO: /usr/lib/python2.6/site-packages/scipy/cluster/tests/vq_test.py is executable; skipped
- test_definition (test_basic.TestDoubleFFT) ... ok
- test_djbfft (test_basic.TestDoubleFFT) ... ok
- test_n_argument_real (test_basic.TestDoubleFFT) ... ok
- test_definition (test_basic.TestDoubleIFFT) ... ok
- test_definition_real (test_basic.TestDoubleIFFT) ... ok
- test_djbfft (test_basic.TestDoubleIFFT) ... ok
- test_random_complex (test_basic.TestDoubleIFFT) ... ok
- test_random_real (test_basic.TestDoubleIFFT) ... ok
- test_axes_argument (test_basic.TestFftn) ... ok
- test_definition (test_basic.TestFftn) ... ok
- test_shape_argument (test_basic.TestFftn) ... ok
- test_shape_argument_more (test_basic.TestFftn) ... ok
- test_shape_axes_argument (test_basic.TestFftn) ... ok
- test_shape_axes_argument2 (test_basic.TestFftn) ... ok
- test_definition (test_basic.TestFftnSingle) ... ok
- test_definition (test_basic.TestIRFFTDouble) ... ok
- test_djbfft (test_basic.TestIRFFTDouble) ... ok
- test_random_real (test_basic.TestIRFFTDouble) ... ok
- test_definition (test_basic.TestIRFFTSingle) ... ok
- test_djbfft (test_basic.TestIRFFTSingle) ... ok
- test_random_real (test_basic.TestIRFFTSingle) ... ok
- test_definition (test_basic.TestIfftnDouble) ... ok
- test_random_complex (test_basic.TestIfftnDouble) ... ok
- test_definition (test_basic.TestIfftnSingle) ... ok
- test_random_complex (test_basic.TestIfftnSingle) ... ok
- test_complex (test_basic.TestLongDoubleFailure) ... ok
- test_real (test_basic.TestLongDoubleFailure) ... ok
- test_definition (test_basic.TestRFFTDouble) ... ok
- test_djbfft (test_basic.TestRFFTDouble) ... ok
- test_definition (test_basic.TestRFFTSingle) ... ok
- test_djbfft (test_basic.TestRFFTSingle) ... ok
- test_definition (test_basic.TestSingleFFT) ... ok
- test_djbfft (test_basic.TestSingleFFT) ... ok
- test_n_argument_real (test_basic.TestSingleFFT) ... ok
- test_definition (test_basic.TestSingleIFFT) ... ok
- test_definition_real (test_basic.TestSingleIFFT) ... ok
- test_djbfft (test_basic.TestSingleIFFT) ... ok
- test_random_complex (test_basic.TestSingleIFFT) ... ok
- test_random_real (test_basic.TestSingleIFFT) ... ok
- fft returns wrong result with axes parameter. ... ok
- test_definition (test_helper.TestFFTFreq) ... ok
- test_definition (test_helper.TestFFTShift) ... ok
- test_inverse (test_helper.TestFFTShift) ... ok
- test_definition (test_helper.TestRFFTFreq) ... ok
- test_definition (test_pseudo_diffs.TestDiff) ... ok
- test_expr (test_pseudo_diffs.TestDiff) ... ok
- test_expr_large (test_pseudo_diffs.TestDiff) ... ok
- test_int (test_pseudo_diffs.TestDiff) ... ok
- test_period (test_pseudo_diffs.TestDiff) ... ok
- test_random_even (test_pseudo_diffs.TestDiff) ... ok
- test_random_odd (test_pseudo_diffs.TestDiff) ... ok
- test_sin (test_pseudo_diffs.TestDiff) ... ok
- test_zero_nyquist (test_pseudo_diffs.TestDiff) ... ok
- test_definition (test_pseudo_diffs.TestHilbert) ... ok
- test_random_even (test_pseudo_diffs.TestHilbert) ... ok
- test_random_odd (test_pseudo_diffs.TestHilbert) ... ok
- test_tilbert_relation (test_pseudo_diffs.TestHilbert) ... ok
- test_definition (test_pseudo_diffs.TestIHilbert) ... ok
- test_itilbert_relation (test_pseudo_diffs.TestIHilbert) ... ok
- test_definition (test_pseudo_diffs.TestITilbert) ... ok
- test_definition (test_pseudo_diffs.TestShift) ... ok
- test_definition (test_pseudo_diffs.TestTilbert) ... ok
- test_random_even (test_pseudo_diffs.TestTilbert) ... ok
- test_random_odd (test_pseudo_diffs.TestTilbert) ... ok
- test_axis (test_real_transforms.TestDCTIDouble) ... ok
- test_definition (test_real_transforms.TestDCTIDouble) ... ok
- test_axis (test_real_transforms.TestDCTIFloat) ... ok
- test_definition (test_real_transforms.TestDCTIFloat) ... ok
- test_axis (test_real_transforms.TestDCTIIDouble) ... ok
- test_definition (test_real_transforms.TestDCTIIDouble) ... ok
- Test correspondance with matlab (orthornomal mode). ... ok
- test_axis (test_real_transforms.TestDCTIIFloat) ... ok
- test_definition (test_real_transforms.TestDCTIIFloat) ... ok
- Test correspondance with matlab (orthornomal mode). ... ok
- test_axis (test_real_transforms.TestDCTIIIDouble) ... ok
- test_definition (test_real_transforms.TestDCTIIIDouble) ... ok
- Test orthornomal mode. ... ok
- test_axis (test_real_transforms.TestDCTIIIFloat) ... ok
- test_definition (test_real_transforms.TestDCTIIIFloat) ... ok
- Test orthornomal mode. ... ok
- test_definition (test_real_transforms.TestIDCTIDouble) ... ok
- test_definition (test_real_transforms.TestIDCTIFloat) ... ok
- test_definition (test_real_transforms.TestIDCTIIDouble) ... ok
- test_definition (test_real_transforms.TestIDCTIIFloat) ... ok
- test_definition (test_real_transforms.TestIDCTIIIDouble) ... ok
- test_definition (test_real_transforms.TestIDCTIIIFloat) ... ok
- Check the dop853 solver ... ok
- Check the dopri5 solver ... ok
- Check the vode solver ... ok
- Check the dop853 solver ... ok
- Check the dopri5 solver ... ok
- Check the vode solver ... ok
- Check the zvode solver ... ok
- test_odeint (test_integrate.TestOdeint) ... ok
- test_algebraic_log_weight (test_quadpack.TestQuad) ... ok
- test_cauchypv_weight (test_quadpack.TestQuad) ... ok
- test_cosine_weighted_infinite (test_quadpack.TestQuad) ... ok
- test_double_integral (test_quadpack.TestQuad) ... ok
- test_indefinite (test_quadpack.TestQuad) ... ok
- test_sine_weighted_finite (test_quadpack.TestQuad) ... ok
- test_sine_weighted_infinite (test_quadpack.TestQuad) ... ok
- test_singular (test_quadpack.TestQuad) ... ok
- test_triple_integral (test_quadpack.TestQuad) ... ok
- test_typical (test_quadpack.TestQuad) ... ok
- Test the first few degrees, for evenly spaced points. ... ok
- Test newton_cotes with points that are not evenly spaced. ... ok
- test_non_dtype (test_quadrature.TestQuadrature) ... ok
- test_quadrature (test_quadrature.TestQuadrature) ... ok
- test_quadrature_rtol (test_quadrature.TestQuadrature) ... ok
- test_romb (test_quadrature.TestQuadrature) ... ok
- test_romberg (test_quadrature.TestQuadrature) ... ok
- test_romberg_rtol (test_quadrature.TestQuadrature) ... ok
- test_bilinearity (test_fitpack.TestLSQBivariateSpline) ... /usr/lib/python2.6/site-packages/scipy/interpolate/fitpack2.py:670: UserWarning:
- The coefficients of the spline returned have been computed as the
- minimal norm least-squares solution of a (numerically) rank deficient
- system (deficiency=7). If deficiency is large, the results may be
- inaccurate. Deficiency may strongly depend on the value of eps.
- warnings.warn(message)
- ok
- Test whether empty inputs returns an empty output. Ticket 1014 ... ok
- test_integral (test_fitpack.TestLSQBivariateSpline) ... ok
- test_linear_constant (test_fitpack.TestLSQBivariateSpline) ... ok
- test_defaults (test_fitpack.TestRectBivariateSpline) ... ok
- test_evaluate (test_fitpack.TestRectBivariateSpline) ... ok
- test_integral (test_fitpack.TestSmoothBivariateSpline) ... /usr/lib/python2.6/site-packages/scipy/interpolate/fitpack2.py:601: UserWarning:
- The required storage space exceeds the available storage space: nxest
- or nyest too small, or s too small.
- The weighted least-squares spline corresponds to the current set of
- knots.
- warnings.warn(message)
- ok
- test_linear_1d (test_fitpack.TestSmoothBivariateSpline) ... ok
- test_linear_constant (test_fitpack.TestSmoothBivariateSpline) ... ok
- Test whether empty input returns an empty output. Ticket 1014 ... ok
- test_linear_1d (test_fitpack.TestUnivariateSpline) ... ok
- test_linear_constant (test_fitpack.TestUnivariateSpline) ... ok
- test_preserve_shape (test_fitpack.TestUnivariateSpline) ... ok
- test_subclassing (test_fitpack.TestUnivariateSpline) ... ok
- test_interpolate.TestInterp1D.test_bounds('linear',) ... ok
- test_interpolate.TestInterp1D.test_bounds('linear',) ... ok
- test_interpolate.TestInterp1D.test_bounds('cubic',) ... ok
- test_interpolate.TestInterp1D.test_bounds('cubic',) ... ok
- test_interpolate.TestInterp1D.test_bounds('nearest',) ... ok
- test_interpolate.TestInterp1D.test_bounds('nearest',) ... ok
- test_interpolate.TestInterp1D.test_bounds('slinear',) ... ok
- test_interpolate.TestInterp1D.test_bounds('slinear',) ... ok
- test_interpolate.TestInterp1D.test_bounds('zero',) ... ok
- test_interpolate.TestInterp1D.test_bounds('zero',) ... ok
- test_interpolate.TestInterp1D.test_bounds('quadratic',) ... ok
- test_interpolate.TestInterp1D.test_bounds('quadratic',) ... ok
- test_interpolate.TestInterp1D.test_complex(<type 'numpy.complex64'>, 'linear') ... ok
- test_interpolate.TestInterp1D.test_complex(<type 'numpy.complex128'>, 'linear') ... ok
- test_interpolate.TestInterp1D.test_complex(<type 'numpy.complex64'>, 'nearest') ... ok
- test_interpolate.TestInterp1D.test_complex(<type 'numpy.complex128'>, 'nearest') ... ok
- test_interpolate.TestInterp1D.test_complex(<type 'numpy.complex64'>, 'cubic') ... ok
- test_interpolate.TestInterp1D.test_complex(<type 'numpy.complex128'>, 'cubic') ... ok
- test_interpolate.TestInterp1D.test_complex(<type 'numpy.complex64'>, 'slinear') ... ok
- test_interpolate.TestInterp1D.test_complex(<type 'numpy.complex128'>, 'slinear') ... ok
- test_interpolate.TestInterp1D.test_complex(<type 'numpy.complex64'>, 'quadratic') ... ok
- test_interpolate.TestInterp1D.test_complex(<type 'numpy.complex128'>, 'quadratic') ... ok
- test_interpolate.TestInterp1D.test_complex(<type 'numpy.complex64'>, 'zero') ... ok
- test_interpolate.TestInterp1D.test_complex(<type 'numpy.complex128'>, 'zero') ... ok
- Check the actual implementation of spline interpolation. ... ok
- Check that the attributes are initialized appropriately by the ... ok
- Check the actual implementation of linear interpolation. ... ok
- test_interpolate.TestInterp1D.test_nd('linear',) ... ok
- test_interpolate.TestInterp1D.test_nd('linear',) ... ok
- test_interpolate.TestInterp1D.test_nd('cubic',) ... ok
- test_interpolate.TestInterp1D.test_nd('cubic',) ... ok
- test_interpolate.TestInterp1D.test_nd('slinear',) ... ok
- test_interpolate.TestInterp1D.test_nd('slinear',) ... ok
- test_interpolate.TestInterp1D.test_nd('quadratic',) ... ok
- test_interpolate.TestInterp1D.test_nd('quadratic',) ... ok
- test_interpolate.TestInterp1D.test_nd('nearest',) ... ok
- test_interpolate.TestInterp1D.test_nd('nearest',) ... ok
- test_interpolate.TestInterp1D.test_nd_zero_spline ... KNOWNFAIL: zero-order splines fail for the last point
- Check the actual implementation of nearest-neighbour interpolation. ... ok
- Make sure that appropriate exceptions are raised when invalid values ... ok
- Check the actual implementation of zero-order spline interpolation. ... KNOWNFAIL: zero-order splines fail for the last point
- test_interp2d (test_interpolate.TestInterp2D) ... ok
- test_interp2d_meshgrid_input (test_interpolate.TestInterp2D) ... ok
- test_lagrange (test_interpolate.TestLagrange) ... ok
- test_block_average_above (test_interpolate_wrapper.Test) ... ok
- test_linear (test_interpolate_wrapper.Test) ... ok
- test_linear2 (test_interpolate_wrapper.Test) ... ok
- test_logarithmic (test_interpolate_wrapper.Test) ... ok
- test_nearest (test_interpolate_wrapper.Test) ... ok
- test_append (test_polyint.CheckBarycentric) ... ok
- test_delayed (test_polyint.CheckBarycentric) ... ok
- test_lagrange (test_polyint.CheckBarycentric) ... ok
- test_scalar (test_polyint.CheckBarycentric) ... ok
- test_shapes_1d_vectorvalue (test_polyint.CheckBarycentric) ... ok
- test_shapes_scalarvalue (test_polyint.CheckBarycentric) ... ok
- test_shapes_vectorvalue (test_polyint.CheckBarycentric) ... ok
- test_vector (test_polyint.CheckBarycentric) ... ok
- test_wrapper (test_polyint.CheckBarycentric) ... ok
- test_derivative (test_polyint.CheckKrogh) ... ok
- test_derivatives (test_polyint.CheckKrogh) ... ok
- test_empty (test_polyint.CheckKrogh) ... ok
- test_hermite (test_polyint.CheckKrogh) ... ok
- test_high_derivative (test_polyint.CheckKrogh) ... ok
- test_lagrange (test_polyint.CheckKrogh) ... ok
- test_low_derivatives (test_polyint.CheckKrogh) ... ok
- test_scalar (test_polyint.CheckKrogh) ... ok
- test_shapes_1d_vectorvalue (test_polyint.CheckKrogh) ... ok
- test_shapes_scalarvalue (test_polyint.CheckKrogh) ... ok
- test_shapes_scalarvalue_derivative (test_polyint.CheckKrogh) ... ok
- test_shapes_vectorvalue (test_polyint.CheckKrogh) ... ok
- test_shapes_vectorvalue_derivative (test_polyint.CheckKrogh) ... ok
- test_vector (test_polyint.CheckKrogh) ... ok
- test_wrapper (test_polyint.CheckKrogh) ... ok
- test_construction (test_polyint.CheckPiecewise) ... ok
- test_derivative (test_polyint.CheckPiecewise) ... ok
- test_derivatives (test_polyint.CheckPiecewise) ... ok
- test_incremental (test_polyint.CheckPiecewise) ... ok
- test_scalar (test_polyint.CheckPiecewise) ... ok
- test_shapes_scalarvalue (test_polyint.CheckPiecewise) ... ok
- test_shapes_scalarvalue_derivative (test_polyint.CheckPiecewise) ... ok
- test_shapes_vectorvalue (test_polyint.CheckPiecewise) ... ok
- test_shapes_vectorvalue_1d (test_polyint.CheckPiecewise) ... ok
- test_shapes_vectorvalue_derivative (test_polyint.CheckPiecewise) ... ok
- test_vector (test_polyint.CheckPiecewise) ... ok
- test_wrapper (test_polyint.CheckPiecewise) ... ok
- test_exponential (test_polyint.CheckTaylor) ... ok
- test_rbf.test_rbf_interpolation('multiquadric',) ... ok
- test_rbf.test_rbf_interpolation('multiquadric',) ... ok
- test_rbf.test_rbf_interpolation('multiquadric',) ... ok
- test_rbf.test_rbf_interpolation('inverse multiquadric',) ... ok
- test_rbf.test_rbf_interpolation('inverse multiquadric',) ... ok
- test_rbf.test_rbf_interpolation('inverse multiquadric',) ... ok
- test_rbf.test_rbf_interpolation('gaussian',) ... ok
- test_rbf.test_rbf_interpolation('gaussian',) ... ok
- test_rbf.test_rbf_interpolation('gaussian',) ... ok
- test_rbf.test_rbf_interpolation('cubic',) ... ok
- test_rbf.test_rbf_interpolation('cubic',) ... ok
- test_rbf.test_rbf_interpolation('cubic',) ... ok
- test_rbf.test_rbf_interpolation('quintic',) ... ok
- test_rbf.test_rbf_interpolation('quintic',) ... ok
- test_rbf.test_rbf_interpolation('quintic',) ... ok
- test_rbf.test_rbf_interpolation('thin-plate',) ... Warning: divide by zero encountered in log
- Warning: invalid value encountered in multiply
- Warning: divide by zero encountered in log
- Warning: invalid value encountered in multiply
- Warning: divide by zero encountered in log
- Warning: invalid value encountered in multiply
- ok
- test_rbf.test_rbf_interpolation('thin-plate',) ... Warning: divide by zero encountered in log
- Warning: invalid value encountered in multiply
- Warning: divide by zero encountered in log
- Warning: invalid value encountered in multiply
- ok
- test_rbf.test_rbf_interpolation('thin-plate',) ... Warning: divide by zero encountered in log
- Warning: invalid value encountered in multiply
- Warning: divide by zero encountered in log
- Warning: invalid value encountered in multiply
- ok
- test_rbf.test_rbf_interpolation('linear',) ... ok
- test_rbf.test_rbf_interpolation('linear',) ... ok
- test_rbf.test_rbf_interpolation('linear',) ... ok
- test_rbf.test_rbf_regularity('multiquadric', 0.050000000000000003) ... ok
- test_rbf.test_rbf_regularity('inverse multiquadric', 0.02) ... ok
- test_rbf.test_rbf_regularity('gaussian', 0.01) ... ok
- test_rbf.test_rbf_regularity('cubic', 0.14999999999999999) ... ok
- test_rbf.test_rbf_regularity('quintic', 0.10000000000000001) ... ok
- test_rbf.test_rbf_regularity('thin-plate', 0.10000000000000001) ... Warning: divide by zero encountered in log
- Warning: invalid value encountered in multiply
- Warning: divide by zero encountered in log
- Warning: invalid value encountered in multiply
- ok
- test_rbf.test_rbf_regularity('linear', 0.20000000000000001) ... ok
- Check that the Rbf class can be constructed with the default ... ok
- Check that the Rbf class can be constructed with function=callable. ... ok
- Ticket #629 ... ok
- test_byteordercodes.test_native ... ok
- test_byteordercodes.test_to_numpy ... ok
- test_mio.test_load('double', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testdouble_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testdouble_4.2c_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testdouble_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testdouble_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testdouble_7.1_GLNX86.mat'], {'testdouble': array([[ 0. , 0.78539816, 1.57079633, 2.35619449, 3.14159265, ... ok
- test_mio.test_load('string', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststring_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststring_4.2c_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststring_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststring_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststring_6.1_SOL2.mat'], {'teststring': array([u'"Do nine men interpret?" "Nine men," I nod.'], ... ok
- test_mio.test_load('complex', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testcomplex_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testcomplex_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testcomplex_4.2c_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testcomplex_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testcomplex_6.1_SOL2.mat'], {'testcomplex': array([[ 1.00000000e+00 +0.00000000e+00j, ... ok
- test_mio.test_load('matrix', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testmatrix_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testmatrix_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testmatrix_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testmatrix_4.2c_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testmatrix_7.4_GLNX86.mat'], {'testmatrix': array([[ 1., 2., 3., 4., 5.], ... ok
- test_mio.test_load('sparse', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparse_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparse_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparse_4.2c_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparse_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparse_7.1_GLNX86.mat'], {'testsparse': <3x5 sparse matrix of type '<type 'numpy.float64'>' ... ok
- test_mio.test_load('sparsecomplex', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparsecomplex_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparsecomplex_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparsecomplex_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparsecomplex_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparsecomplex_4.2c_SOL2.mat'], {'testsparsecomplex': <3x5 sparse matrix of type '<type 'numpy.complex128'>' ... ok
- test_mio.test_load('multi', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testmulti_4.2c_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testmulti_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testmulti_7.4_GLNX86.mat'], {'a': array([[ 1., 2., 3., 4., 5.], ... ok
- test_mio.test_load('minus', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testminus_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testminus_4.2c_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testminus_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testminus_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testminus_7.4_GLNX86.mat'], {'testminus': array([[-1]])}) ... ok
- test_mio.test_load('onechar', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testonechar_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testonechar_4.2c_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testonechar_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testonechar_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testonechar_6.5.1_GLNX86.mat'], {'testonechar': array([u'r'], ... ok
- test_mio.test_load('cell', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testcell_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testcell_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testcell_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testcell_7.1_GLNX86.mat'], {'testcell': array([[[u'This cell contains this string and 3 arrays of increasing length'], ... ok
- test_mio.test_load('scalarcell', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testscalarcell_7.4_GLNX86.mat'], {'testscalarcell': array([[[[1]]]], dtype=object)}) ... ok
- test_mio.test_load('emptycell', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testemptycell_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testemptycell_5.3_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testemptycell_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testemptycell_7.4_GLNX86.mat'], {'testemptycell': array([[[[1]], [[2]], [], [], [[3]]]], dtype=object)}) ... ok
- test_mio.test_load('stringarray', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststringarray_4.2c_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststringarray_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststringarray_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststringarray_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststringarray_7.1_GLNX86.mat'], {'teststringarray': array([u'one ', u'two ', u'three'], ... ok
- test_mio.test_load('3dmatrix', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/test3dmatrix_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/test3dmatrix_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/test3dmatrix_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/test3dmatrix_7.4_GLNX86.mat'], {'test3dmatrix': array([[[ 1, 7, 13, 19], ... ok
- test_mio.test_load('struct', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststruct_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststruct_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststruct_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststruct_7.1_GLNX86.mat'], {'teststruct': array([[ ([u'Rats live on no evil star.'], [[1.4142135623730951, 2.7182818284590451, 3.1415926535897931]], [[(1.4142135623730951+1.4142135623730951j), (2.7182818284590451+2.7182818284590451j), (3.1415926535897931+3.1415926535897931j)]])]], ... ok
- test_mio.test_load('cellnest', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testcellnest_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testcellnest_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testcellnest_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testcellnest_7.4_GLNX86.mat'], {'testcellnest': array([[[[1]], [[[[2]] [[3]] [[[[4]] [[5]]]]]]]], dtype=object)}) ... ok
- test_mio.test_load('structnest', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststructnest_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststructnest_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststructnest_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststructnest_6.1_SOL2.mat'], {'teststructnest': array([[([[1]], [[(array([u'number 3'], ... ok
- test_mio.test_load('structarr', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststructarr_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststructarr_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststructarr_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/teststructarr_7.1_GLNX86.mat'], {'teststructarr': array([[([[1]], [[2]]), ([u'number 1'], [u'number 2'])]], ... ok
- test_mio.test_load('object', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testobject_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testobject_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testobject_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testobject_6.1_SOL2.mat'], {'testobject': MatlabObject([[([u'x'], [u' x = INLINE_INPUTS_{1};'], [u'x'], [[0]], [[1]], [[1]])]], ... ok
- test_mio.test_load('unicode', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testunicode_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testunicode_7.4_GLNX86.mat'], {'testunicode': array([ u'Japanese: \n\u3059\u3079\u3066\u306e\u4eba\u9593\u306f\u3001\u751f\u307e\u308c\u306a\u304c\u3089\u306b\u3057\u3066\u81ea\u7531\u3067\u3042\u308a\u3001\n\u304b\u3064\u3001\u5c0a\u53b3\u3068\u6a29\u5229\u3068 \u306b\u3064\u3044\u3066\u5e73\u7b49\u3067\u3042\u308b\u3002\n\u4eba\u9593\u306f\u3001\u7406\u6027\u3068\u826f\u5fc3\u3068\u3092\u6388\u3051\u3089\u308c\u3066\u304a\u308a\u3001\n\u4e92\u3044\u306b\u540c\u80de\u306e\u7cbe\u795e\u3092\u3082\u3063\u3066\u884c\u52d5\u3057\u306a\u3051\u308c\u3070\u306a\u3089\u306a\u3044\u3002'], ... ok
- test_mio.test_load('sparse', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparse_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparse_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparse_4.2c_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparse_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparse_7.1_GLNX86.mat'], {'testsparse': <3x5 sparse matrix of type '<type 'numpy.float64'>' ... ok
- test_mio.test_load('sparsecomplex', ['/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparsecomplex_6.5.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparsecomplex_6.1_SOL2.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparsecomplex_7.1_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparsecomplex_7.4_GLNX86.mat', '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testsparsecomplex_4.2c_SOL2.mat'], {'testsparsecomplex': <3x5 sparse matrix of type '<type 'numpy.complex128'>' ... ok
- test_mio.test_round_trip('double_round_trip', {'testdouble': array([[ 0. , 0.78539816, 1.57079633, 2.35619449, 3.14159265, ... ok
- test_mio.test_round_trip('string_round_trip', {'teststring': array([u'"Do nine men interpret?" "Nine men," I nod.'], ... ok
- test_mio.test_round_trip('complex_round_trip', {'testcomplex': array([[ 1.00000000e+00 +0.00000000e+00j, ... ok
- test_mio.test_round_trip('matrix_round_trip', {'testmatrix': array([[ 1., 2., 3., 4., 5.], ... ok
- test_mio.test_round_trip('sparse_round_trip', {'testsparse': <3x5 sparse matrix of type '<type 'numpy.float64'>' ... ok
- test_mio.test_round_trip('sparsecomplex_round_trip', {'testsparsecomplex': <3x5 sparse matrix of type '<type 'numpy.complex128'>' ... ok
- test_mio.test_round_trip('multi_round_trip', {'a': array([[ 1., 2., 3., 4., 5.], ... ok
- test_mio.test_round_trip('minus_round_trip', {'testminus': array([[-1]])}, '4') ... ok
- test_mio.test_round_trip('onechar_round_trip', {'testonechar': array([u'r'], ... ok
- test_mio.test_round_trip('cell_round_trip', {'testcell': array([[[u'This cell contains this string and 3 arrays of increasing length'], ... ok
- test_mio.test_round_trip('scalarcell_round_trip', {'testscalarcell': array([[[[1]]]], dtype=object)}, '5') ... ok
- test_mio.test_round_trip('emptycell_round_trip', {'testemptycell': array([[[[1]], [[2]], [], [], [[3]]]], dtype=object)}, '5') ... ok
- test_mio.test_round_trip('stringarray_round_trip', {'teststringarray': array([u'one ', u'two ', u'three'], ... ok
- test_mio.test_round_trip('3dmatrix_round_trip', {'test3dmatrix': array([[[ 1, 7, 13, 19], ... ok
- test_mio.test_round_trip('struct_round_trip', {'teststruct': array([[ ([u'Rats live on no evil star.'], [[1.4142135623730951, 2.7182818284590451, 3.1415926535897931]], [[(1.4142135623730951+1.4142135623730951j), (2.7182818284590451+2.7182818284590451j), (3.1415926535897931+3.1415926535897931j)]])]], ... ok
- test_mio.test_round_trip('cellnest_round_trip', {'testcellnest': array([[[[1]], [[[[2]] [[3]] [[[[4]] [[5]]]]]]]], dtype=object)}, '5') ... ok
- test_mio.test_round_trip('structnest_round_trip', {'teststructnest': array([[([[1]], [[(array([u'number 3'], ... ok
- test_mio.test_round_trip('structarr_round_trip', {'teststructarr': array([[([[1]], [[2]]), ([u'number 1'], [u'number 2'])]], ... ok
- test_mio.test_round_trip('object_round_trip', {'testobject': MatlabObject([[([u'x'], [u' x = INLINE_INPUTS_{1};'], [u'x'], [[0]], [[1]], [[1]])]], ... ok
- test_mio.test_round_trip('unicode_round_trip', {'testunicode': array([ u'Japanese: \n\u3059\u3079\u3066\u306e\u4eba\u9593\u306f\u3001\u751f\u307e\u308c\u306a\u304c\u3089\u306b\u3057\u3066\u81ea\u7531\u3067\u3042\u308a\u3001\n\u304b\u3064\u3001\u5c0a\u53b3\u3068\u6a29\u5229\u3068 \u306b\u3064\u3044\u3066\u5e73\u7b49\u3067\u3042\u308b\u3002\n\u4eba\u9593\u306f\u3001\u7406\u6027\u3068\u826f\u5fc3\u3068\u3092\u6388\u3051\u3089\u308c\u3066\u304a\u308a\u3001\n\u4e92\u3044\u306b\u540c\u80de\u306e\u7cbe\u795e\u3092\u3082\u3063\u3066\u884c\u52d5\u3057\u306a\u3051\u308c\u3070\u306a\u3089\u306a\u3044\u3002'], ... ok
- test_mio.test_round_trip('sparse_round_trip', {'testsparse': <3x5 sparse matrix of type '<type 'numpy.float64'>' ... ok
- test_mio.test_round_trip('sparsecomplex_round_trip', {'testsparsecomplex': <3x5 sparse matrix of type '<type 'numpy.complex128'>' ... ok
- test_mio.test_round_trip('objectarray_round_trip', {'testobjectarray': MatlabObject([[([u'x'], [u' x = INLINE_INPUTS_{1};'], [u'x'], [[0]], [[1]], [[1]]), ... ok
- test_mio.test_gzip_simple ... ok
- test_mio.test_mat73 ... ok
- test_mio.test_warnings(<type 'exceptions.DeprecationWarning'>, <function find_mat_file at 0x9cf55dc>, '/usr/lib/python2.6/site-packages/scipy/io/matlab/tests/data/testdouble_7.1_GLNX86.mat') ... ok
- Regression test for #653. ... ok
- test_mio.test_structname_len ... ok
- test_mio.test_4_and_long_field_names_incompatible ... ok
- test_mio.test_long_field_names ... ok
- test_mio.test_long_field_names_in_struct ... ok
- test_mio.test_cell_with_one_thing_in_it ... ok
- test_mio.test_writer_properties([], []) ... ok
- test_mio.test_writer_properties(['avar'], ['avar']) ... ok
- test_mio.test_writer_properties(False, False) ... ok
- test_mio.test_writer_properties(True, True) ... ok
- test_mio.test_writer_properties(False, False) ... ok
- test_mio.test_writer_properties(True, True) ... ok
- test_mio.test_use_small_element(True,) ... ok
- test_mio.test_use_small_element(True,) ... ok
- test_mio.test_save_dict ... ok
- test_mio.test_1d_shape((5, 1), (5, 1)) ... ok
- test_mio.test_1d_shape((1, 5), (1, 5)) ... ok
- test_mio.test_1d_shape((5, 1), (5, 1)) ... ok
- test_mio.test_1d_shape((1, 5), (1, 5)) ... ok
- test_mio.test_1d_shape((5, 1), (5, 1)) ... ok
- test_mio.test_1d_shape((1, 5), (1, 5)) ... ok
- test_mio.test_compression(array([[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., ... ok
- test_mio.test_compression(array([[ 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., ... ok
- test_mio.test_compression(True,) ... ok
- test_mio.test_compression(array([[ 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., ... ok
- test_mio.test_compression(array([[ 1., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., ... ok
- test_mio.test_single_object ... ok
- test_mio.test_skip_variable(True,) ... ok
- test_mio.test_skip_variable(True,) ... ok
- test_mio.test_skip_variable(True,) ... ok
- test_mio.test_empty_struct((1, 1), (1, 1)) ... ok
- test_mio.test_empty_struct(dtype('object'), dtype('object')) ... ok
- test_mio.test_empty_struct(True,) ... ok
- test_mio.test_empty_struct(array([], ... ok
- test_mio.test_recarray(array([[ 0.5]]), 0.5) ... ok
- test_mio.test_recarray(array([u'python'], ... ok
- test_mio.test_recarray(array([[ 0.5]]), 0.5) ... ok
- test_mio.test_recarray(array([u'python'], ... ok
- test_mio.test_recarray(dtype([('f1', '|O4'), ('f2', '|O4')]), dtype([('f1', '|O4'), ('f2', '|O4')])) ... ok
- test_mio.test_recarray(array([[ 99.]]), 99) ... ok
- test_mio.test_recarray(array([u'not perl'], ... ok
- test_mio.test_save_object(array([[1]]), 1) ... ok
- test_mio.test_save_object(array([u'a string'], ... ok
- test_mio.test_save_object(array([[1]]), 1) ... ok
- test_mio.test_save_object(array([u'a string'], ... ok
- test_mio.test_read_opts(array([[0, 1, 2, 3, 4, 5]]), array([[0, 1, 2, 3, 4, 5]])) ... ok
- test_mio.test_read_opts(array([0, 1, 2, 3, 4, 5]), array([0, 1, 2, 3, 4, 5])) ... ok
- test_mio.test_read_opts(array([[0, 1, 2, 3, 4, 5]]), array([[0, 1, 2, 3, 4, 5]])) ... ok
- test_mio.test_read_opts(array([[0, 1, 2, 3, 4, 5]]), array([[0, 1, 2, 3, 4, 5]])) ... ok
- test_mio.test_read_opts(<type 'exceptions.Exception'>, <bound method MatFile5Reader_future.get_variables of <test_mio.MatFile5Reader_future object at 0xa31034c>>) ... ok
- test_mio.test_read_opts(array([[0, 1, 2, 3, 4, 5]]), array([[0, 1, 2, 3, 4, 5]])) ... ok
- test_mio.test_read_opts(array([u'a string'], ... ok
- test_mio.test_read_opts(array([[u'a', u' ', u's', u't', u'r', u'i', u'n', u'g']], ... ok
- test_mio.test_read_opts(array([u'a string'], ... ok
- test_mio.test_empty_string(array([], ... ok
- test_mio.test_empty_string(array([], ... ok
- test_mio.test_empty_string(array([], ... ok
- test_mio.test_mat4_3d(<type 'exceptions.DeprecationWarning'>, <functools.partial object at 0xa2cf3c4>, <StringIO.StringIO instance at 0xa310c0c>, {'a': array([[[ 0, 1, 2, 3], ... ok
- test_mio.test_mat4_3d(array([[ 0, 1, 2, 3], ... ok
- test_mio.test_func_read(True,) ... ok
- test_mio.test_func_read(<class 'scipy.io.matlab.miobase.MatWriteError'>, <bound method MatFile5Writer.put_variables of <scipy.io.matlab.mio5.MatFile5Writer object at 0xa2f7d0c>>, {'__version__': '1.0', '__header__': 'MATLAB 5.0 MAT-file, Platform: GLNX86, Created on: Fri Feb 20 15:26:59 2009', 'testfunc': MatlabFunction([[ ([u'/opt/matlab-2007a'], [u'/'], [u'@'], [[(array([u'afunc'], ... ok
- test_mio.test_mat_dtype('u', 'u') ... ok
- test_mio.test_mat_dtype('f', 'f') ... ok
- test_mio.test_sparse_in_struct(matrix([[ 1., 0., 0., 0.], ... ok
- test_mio.test_mat_struct_squeeze ... ok
- test_mio.test_str_round(array([u'Hello', u'Foob '], ... ok
- test_mio.test_str_round(array([u'Hello', u'Foob '], ... ok
- test_mio.test_str_round(array([u'Hello', u'Foob '], ... ok
- test_mio5_utils.test_byteswap(16777216L, 16777216L) ... ok
- test_mio5_utils.test_byteswap(1L, 1L) ... ok
- test_mio5_utils.test_byteswap(65536L, 65536L) ... ok
- test_mio5_utils.test_byteswap(256L, 256L) ... ok
- test_mio5_utils.test_byteswap(256L, 256L) ... ok
- test_mio5_utils.test_byteswap(65536L, 65536L) ... ok
- test_mio5_utils.test_read_tag(<type 'exceptions.IOError'>, <built-in method read_tag of scipy.io.matlab.mio5_utils.VarReader5 object at 0xa2e902c>) ... ok
- test_mio5_utils.test_read_tag(<type 'exceptions.ValueError'>, <built-in method read_tag of scipy.io.matlab.mio5_utils.VarReader5 object at 0xa2e902c>) ... ok
- test_mio5_utils.test_read_stream('\x05\x00\x04\x00\x01\x00\x00\x00', '\x05\x00\x04\x00\x01\x00\x00\x00') ... ok
- test_mio5_utils.test_read_numeric(1, True) ... ok
- test_mio5_utils.test_read_numeric(0, False) ... ok
- test_mio5_utils.test_read_numeric(array([30], dtype=uint16), 30) ... ok
- test_mio5_utils.test_read_numeric(array([30], dtype=uint16), 30) ... ok
- test_mio5_utils.test_read_numeric(array([30], dtype=uint16), 30) ... ok
- test_mio5_utils.test_read_numeric(array([30], dtype=uint16), 30) ... ok
- test_mio5_utils.test_read_numeric(array([30], dtype=uint16), 30) ... ok
- test_mio5_utils.test_read_numeric(array([30], dtype=uint16), 30) ... ok
- test_mio5_utils.test_read_numeric(0, False) ... ok
- test_mio5_utils.test_read_numeric(1, True) ... ok
- test_mio5_utils.test_read_numeric(array([30], dtype=uint16), 30) ... ok
- test_mio5_utils.test_read_numeric(array([30], dtype=uint16), 30) ... ok
- test_mio5_utils.test_read_numeric(array([30], dtype=uint16), 30) ... ok
- test_mio5_utils.test_read_numeric(array([30], dtype=uint16), 30) ... ok
- test_mio5_utils.test_read_numeric(array([30], dtype=uint16), 30) ... ok
- test_mio5_utils.test_read_numeric(array([30], dtype=uint16), 30) ... ok
- test_mio5_utils.test_read_numeric(1, True) ... ok
- test_mio5_utils.test_read_numeric(0, False) ... ok
- test_mio5_utils.test_read_numeric(array([1]), 1) ... ok
- test_mio5_utils.test_read_numeric(array([1]), 1) ... ok
- test_mio5_utils.test_read_numeric(array([1]), 1) ... ok
- test_mio5_utils.test_read_numeric(array([1]), 1) ... ok
- test_mio5_utils.test_read_numeric(array([1]), 1) ... ok
- test_mio5_utils.test_read_numeric(array([1]), 1) ... ok
- test_mio5_utils.test_read_numeric(0, False) ... ok
- test_mio5_utils.test_read_numeric(1, True) ... ok
- test_mio5_utils.test_read_numeric(array([1]), 1) ... ok
- test_mio5_utils.test_read_numeric(array([1]), 1) ... ok
- test_mio5_utils.test_read_numeric(array([1]), 1) ... ok
- test_mio5_utils.test_read_numeric(array([1]), 1) ... ok
- test_mio5_utils.test_read_numeric(array([1]), 1) ... ok
- test_mio5_utils.test_read_numeric(array([1]), 1) ... ok
- test_mio5_utils.test_read_numeric(1, True) ... ok
- test_mio5_utils.test_read_numeric(0, False) ... ok
- test_mio5_utils.test_read_numeric(array([-1], dtype=int16), -1) ... ok
- test_mio5_utils.test_read_numeric(array([-1], dtype=int16), -1) ... ok
- test_mio5_utils.test_read_numeric(array([-1], dtype=int16), -1) ... ok
- test_mio5_utils.test_read_numeric(array([-1], dtype=int16), -1) ... ok
- test_mio5_utils.test_read_numeric(array([-1], dtype=int16), -1) ... ok
- test_mio5_utils.test_read_numeric(array([-1], dtype=int16), -1) ... ok
- test_mio5_utils.test_read_numeric(0, False) ... ok
- test_mio5_utils.test_read_numeric(1, True) ... ok
- test_mio5_utils.test_read_numeric(array([-1], dtype=int16), -1) ... ok
- test_mio5_utils.test_read_numeric(array([-1], dtype=int16), -1) ... ok
- test_mio5_utils.test_read_numeric(array([-1], dtype=int16), -1) ... ok
- test_mio5_utils.test_read_numeric(array([-1], dtype=int16), -1) ... ok
- test_mio5_utils.test_read_numeric(array([-1], dtype=int16), -1) ... ok
- test_mio5_utils.test_read_numeric(array([-1], dtype=int16), -1) ... ok
- test_mio5_utils.test_read_numeric_writeable(True,) ... ok
- test_mio_funcs.test_jottings ... ok
- test_mio_utils.test_cproduct(1, 1) ... ok
- test_mio_utils.test_cproduct(1, 1) ... ok
- test_mio_utils.test_cproduct(3, 3) ... ok
- test_mio_utils.test_cproduct(3, 3) ... ok
- test_mio_utils.test_squeeze_element(array([ 0., 0., 0.]), array([ 0., 0., 0.])) ... ok
- test_mio_utils.test_squeeze_element(True,) ... ok
- test_mio_utils.test_squeeze_element(True,) ... ok
- test_mio_utils.test_chars_strings(array([u'learn ', u'python', u'fast ', u'here '], ... ok
- test_mio_utils.test_chars_strings(array([[u'learn ', u'python'], ... ok
- test_mio_utils.test_chars_strings(array([[[u'learn ', u'python'], ... ok
- test_mio_utils.test_chars_strings(array([u'learn ', u'python', u'fast ', u'here '], ... ok
- test_mio_utils.test_chars_strings(array([u''], ... ok
- test_streams.test_make_stream(True,) ... ok
- test_streams.test_make_stream(True,) ... ok
- test_streams.test_make_stream(True,) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(5, 5) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(7, 7) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(6, 6) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(5, 5) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(7, 7) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(6, 6) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(5, 5) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(7, 7) ... ok
- test_streams.test_tell_seek(0, 0) ... ok
- test_streams.test_tell_seek(6, 6) ... ok
- test_streams.test_read('a\x00string', 'a\x00string') ... ok
- test_streams.test_read('a\x00st', 'a\x00st') ... ok
- test_streams.test_read('a\x00st', 'a\x00st') ... ok
- test_streams.test_read('ring', 'ring') ... ok
- test_streams.test_read(<type 'exceptions.IOError'>, <built-in function _read_into>, <scipy.io.matlab.streams.FileStream object at 0xa30ac2c>, 2) ... ok
- test_streams.test_read('a\x00st', 'a\x00st') ... ok
- test_streams.test_read('ring', 'ring') ... ok
- test_streams.test_read(<type 'exceptions.IOError'>, <built-in function _read_string>, <scipy.io.matlab.streams.FileStream object at 0xa30ac2c>, 2) ... ok
- test_streams.test_read('a\x00string', 'a\x00string') ... ok
- test_streams.test_read('a\x00st', 'a\x00st') ... ok
- test_streams.test_read('a\x00st', 'a\x00st') ... ok
- test_streams.test_read('ring', 'ring') ... ok
- test_streams.test_read(<type 'exceptions.IOError'>, <built-in function _read_into>, <scipy.io.matlab.streams.GenericStream object at 0xa30a6ec>, 2) ... ok
- test_streams.test_read('a\x00st', 'a\x00st') ... ok
- test_streams.test_read('ring', 'ring') ... ok
- test_streams.test_read(<type 'exceptions.IOError'>, <built-in function _read_string>, <scipy.io.matlab.streams.GenericStream object at 0xa30a6ec>, 2) ... ok
- test_streams.test_read('a\x00string', 'a\x00string') ... ok
- test_streams.test_read('a\x00st', 'a\x00st') ... ok
- test_streams.test_read('a\x00st', 'a\x00st') ... ok
- test_streams.test_read('ring', 'ring') ... ok
- test_streams.test_read(<type 'exceptions.IOError'>, <built-in function _read_into>, <scipy.io.matlab.streams.cStringStream object at 0xa30a6cc>, 2) ... ok
- test_streams.test_read('a\x00st', 'a\x00st') ... ok
- test_streams.test_read('ring', 'ring') ... ok
- test_streams.test_read(<type 'exceptions.IOError'>, <built-in function _read_string>, <scipy.io.matlab.streams.cStringStream object at 0xa30a6cc>, 2) ... ok
- test_idlsave.TestArrayDimensions.test_1d ... ok
- test_idlsave.TestArrayDimensions.test_2d ... ok
- test_idlsave.TestArrayDimensions.test_3d ... ok
- test_idlsave.TestArrayDimensions.test_4d ... ok
- test_idlsave.TestArrayDimensions.test_5d ... ok
- test_idlsave.TestArrayDimensions.test_6d ... ok
- test_idlsave.TestArrayDimensions.test_7d ... ok
- test_idlsave.TestArrayDimensions.test_8d ... ok
- test_idlsave.TestCompressed.test_byte ... ok
- test_idlsave.TestCompressed.test_complex32 ... ok
- test_idlsave.TestCompressed.test_complex64 ... ok
- test_idlsave.TestCompressed.test_compressed ... ok
- test_idlsave.TestCompressed.test_float32 ... ok
- test_idlsave.TestCompressed.test_float64 ... ok
- test_idlsave.TestCompressed.test_heap_pointer ... ok
- test_idlsave.TestCompressed.test_int16 ... ok
- test_idlsave.TestCompressed.test_int32 ... ok
- test_idlsave.TestCompressed.test_int64 ... ok
- test_idlsave.TestCompressed.test_object_reference ... ok
- test_idlsave.TestCompressed.test_string ... ok
- test_idlsave.TestCompressed.test_structure ... ok
- test_idlsave.TestCompressed.test_uint16 ... ok
- test_idlsave.TestCompressed.test_uint32 ... ok
- test_idlsave.TestCompressed.test_uint64 ... ok
- test_idlsave.TestIdict.test_idict ... ok
- test_idlsave.TestPointers.test_pointers ... ok
- test_idlsave.TestScalars.test_byte ... ok
- test_idlsave.TestScalars.test_complex32 ... ok
- test_idlsave.TestScalars.test_complex64 ... ok
- test_idlsave.TestScalars.test_float32 ... ok
- test_idlsave.TestScalars.test_float64 ... ok
- test_idlsave.TestScalars.test_heap_pointer ... ok
- test_idlsave.TestScalars.test_int16 ... ok
- test_idlsave.TestScalars.test_int32 ... ok
- test_idlsave.TestScalars.test_int64 ... ok
- test_idlsave.TestScalars.test_object_reference ... ok
- test_idlsave.TestScalars.test_string ... ok
- test_idlsave.TestScalars.test_structure ... ok
- test_idlsave.TestScalars.test_uint16 ... ok
- test_idlsave.TestScalars.test_uint32 ... ok
- test_idlsave.TestScalars.test_uint64 ... ok
- test_idlsave.TestStructures.test_arrays ... ok
- test_idlsave.TestStructures.test_arrays_replicated ... ok
- test_idlsave.TestStructures.test_scalars ... ok
- test_idlsave.TestStructures.test_scalars_replicated ... ok
- test_random_rect_real (test_mmio.TestMMIOArray) ... ok
- test_random_symmetric_real (test_mmio.TestMMIOArray) ... ok
- test_simple (test_mmio.TestMMIOArray) ... ok
- test_simple_complex (test_mmio.TestMMIOArray) ... ok
- test_simple_hermitian (test_mmio.TestMMIOArray) ... ok
- test_simple_real (test_mmio.TestMMIOArray) ... ok
- test_simple_rectangular (test_mmio.TestMMIOArray) ... ok
- test_simple_rectangular_real (test_mmio.TestMMIOArray) ... ok
- test_simple_skew_symmetric (test_mmio.TestMMIOArray) ... ok
- test_simple_skew_symmetric_float (test_mmio.TestMMIOArray) ... ok
- test_simple_symmetric (test_mmio.TestMMIOArray) ... ok
- test_complex_write_read (test_mmio.TestMMIOCoordinate) ... ok
- test_empty_write_read (test_mmio.TestMMIOCoordinate) ... ok
- read a general matrix ... ok
- read a hermitian matrix ... ok
- read a skew-symmetric matrix ... ok
- read a symmetric matrix ... ok
- read a symmetric pattern matrix ... ok
- test_real_write_read (test_mmio.TestMMIOCoordinate) ... ok
- test_sparse_formats (test_mmio.TestMMIOCoordinate) ... ok
- test_netcdf.test_read_write_files(True,) ... ok
- test_netcdf.test_read_write_files('Created for a test', 'Created for a test') ... ok
- test_netcdf.test_read_write_files('days since 2008-01-01', 'days since 2008-01-01') ... ok
- test_netcdf.test_read_write_files((11,), (11,)) ... ok
- test_netcdf.test_read_write_files(10, 10) ... ok
- test_netcdf.test_read_write_files(False,) ... ok
- test_netcdf.test_read_write_files('Created for a test', 'Created for a test') ... ok
- test_netcdf.test_read_write_files('days since 2008-01-01', 'days since 2008-01-01') ... ok
- test_netcdf.test_read_write_files((11,), (11,)) ... ok
- test_netcdf.test_read_write_files(10, 10) ... ok
- test_netcdf.test_read_write_files(False,) ... ok
- test_netcdf.test_read_write_files('Created for a test', 'Created for a test') ... ok
- test_netcdf.test_read_write_files('days since 2008-01-01', 'days since 2008-01-01') ... ok
- test_netcdf.test_read_write_files((11,), (11,)) ... ok
- test_netcdf.test_read_write_files(10, 10) ... ok
- test_netcdf.test_read_write_sio('Created for a test', 'Created for a test') ... ok
- test_netcdf.test_read_write_sio('days since 2008-01-01', 'days since 2008-01-01') ... ok
- test_netcdf.test_read_write_sio((11,), (11,)) ... ok
- test_netcdf.test_read_write_sio(10, 10) ... ok
- test_netcdf.test_read_write_sio(<type 'exceptions.ValueError'>, <class 'scipy.io.netcdf.netcdf_file'>, <StringIO.StringIO instance at 0xa311eec>, 'r', True) ... ok
- test_netcdf.test_read_write_sio('Created for a test', 'Created for a test') ... ok
- test_netcdf.test_read_write_sio('days since 2008-01-01', 'days since 2008-01-01') ... ok
- test_netcdf.test_read_write_sio((11,), (11,)) ... ok
- test_netcdf.test_read_write_sio(10, 10) ... ok
- test_netcdf.test_read_write_sio(2, 2) ... ok
- test_netcdf.test_read_write_sio('Created for a test', 'Created for a test') ... ok
- test_netcdf.test_read_write_sio('days since 2008-01-01', 'days since 2008-01-01') ... ok
- test_netcdf.test_read_write_sio((11,), (11,)) ... ok
- test_netcdf.test_read_write_sio(10, 10) ... ok
- test_netcdf.test_read_write_sio(2, 2) ... ok
- test_netcdf.test_read_example_data ... ok
- test_cast_to_fp (test_recaster.TestRecaster) ... /usr/lib/python2.6/site-packages/scipy/io/recaster.py:328: ComplexWarning: Casting complex values to real discards the imaginary part
- test_arr = arr.astype(T)
- ok
- test_init (test_recaster.TestRecaster) ... ok
- test_recasts (test_recaster.TestRecaster) ... /usr/lib/python2.6/site-packages/scipy/io/recaster.py:375: ComplexWarning: Casting complex values to real discards the imaginary part
- return arr.astype(idt)
- ok
- test_smallest_int_sctype (test_recaster.TestRecaster) ... ok
- test_wavfile.test_read_1 ... /usr/lib/python2.6/site-packages/scipy/io/wavfile.py:30: WavFileWarning: Unfamiliar format bytes
- warnings.warn("Unfamiliar format bytes", WavFileWarning)
- /usr/lib/python2.6/site-packages/scipy/io/wavfile.py:120: WavFileWarning: chunk not understood
- warnings.warn("chunk not understood", WavFileWarning)
- ok
- test_wavfile.test_read_2 ... ok
- test_wavfile.test_read_fail ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>i2'), 1) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>i2'), 2) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>i2'), 5) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>i2'), 1) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>i2'), 2) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>i2'), 5) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('int16'), 1) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('int16'), 2) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('int16'), 5) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('int16'), 1) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('int16'), 2) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('int16'), 5) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>i4'), 1) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>i4'), 2) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>i4'), 5) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>i4'), 1) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>i4'), 2) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>i4'), 5) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('int32'), 1) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('int32'), 2) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('int32'), 5) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('int32'), 1) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('int32'), 2) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('int32'), 5) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>i8'), 1) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>i8'), 2) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>i8'), 5) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>i8'), 1) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>i8'), 2) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>i8'), 5) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('int64'), 1) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('int64'), 2) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('int64'), 5) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('int64'), 1) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('int64'), 2) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('int64'), 5) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('uint8'), 1) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('uint8'), 2) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('uint8'), 5) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('uint8'), 1) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('uint8'), 2) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('uint8'), 5) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>u2'), 1) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>u2'), 2) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>u2'), 5) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>u2'), 1) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>u2'), 2) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>u2'), 5) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('uint16'), 1) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('uint16'), 2) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('uint16'), 5) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('uint16'), 1) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('uint16'), 2) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('uint16'), 5) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>u4'), 1) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>u4'), 2) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>u4'), 5) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>u4'), 1) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>u4'), 2) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>u4'), 5) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('uint32'), 1) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('uint32'), 2) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('uint32'), 5) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('uint32'), 1) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('uint32'), 2) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('uint32'), 5) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>u8'), 1) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>u8'), 2) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('>u8'), 5) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>u8'), 1) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>u8'), 2) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('>u8'), 5) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('uint64'), 1) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('uint64'), 2) ... ok
- test_wavfile.test_write_roundtrip(8000, dtype('uint64'), 5) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('uint64'), 1) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('uint64'), 2) ... ok
- test_wavfile.test_write_roundtrip(32000, dtype('uint64'), 5) ... ok
- test_blas (test_blas.TestBLAS) ... ok
- test_axpy (test_blas.TestCBLAS1Simple) ... ok
- test_amax (test_blas.TestFBLAS1Simple) ... ok
- test_asum (test_blas.TestFBLAS1Simple) ... ok
- test_axpy (test_blas.TestFBLAS1Simple) ... ok
- test_copy (test_blas.TestFBLAS1Simple) ... ok
- test_dot (test_blas.TestFBLAS1Simple) ... ok
- test_nrm2 (test_blas.TestFBLAS1Simple) ... ok
- test_scal (test_blas.TestFBLAS1Simple) ... ok
- test_swap (test_blas.TestFBLAS1Simple) ... ok
- test_gemv (test_blas.TestFBLAS2Simple) ... ok
- test_ger (test_blas.TestFBLAS2Simple) ... ok
- test_gemm (test_blas.TestFBLAS3Simple) ... ok
- test_gemm2 (test_blas.TestFBLAS3Simple) ... ok
- test_default_a (test_fblas.TestCaxpy) ... ok
- test_simple (test_fblas.TestCaxpy) ... ok
- test_x_and_y_stride (test_fblas.TestCaxpy) ... ok
- test_x_bad_size (test_fblas.TestCaxpy) ... ok
- test_x_stride (test_fblas.TestCaxpy) ... ok
- test_y_bad_size (test_fblas.TestCaxpy) ... ok
- test_y_stride (test_fblas.TestCaxpy) ... ok
- test_simple (test_fblas.TestCcopy) ... ok
- test_x_and_y_stride (test_fblas.TestCcopy) ... ok
- test_x_bad_size (test_fblas.TestCcopy) ... ok
- test_x_stride (test_fblas.TestCcopy) ... ok
- test_y_bad_size (test_fblas.TestCcopy) ... ok
- test_y_stride (test_fblas.TestCcopy) ... ok
- test_default_beta_y (test_fblas.TestCgemv) ... ok
- test_simple (test_fblas.TestCgemv) ... ok
- test_simple_transpose (test_fblas.TestCgemv) ... ok
- test_simple_transpose_conj (test_fblas.TestCgemv) ... ok
- test_x_stride (test_fblas.TestCgemv) ... ok
- test_x_stride_assert (test_fblas.TestCgemv) ... ok
- test_x_stride_transpose (test_fblas.TestCgemv) ... ok
- test_y_stride (test_fblas.TestCgemv) ... ok
- test_y_stride_assert (test_fblas.TestCgemv) ... ok
- test_y_stride_transpose (test_fblas.TestCgemv) ... ok
- test_simple (test_fblas.TestCscal) ... ok
- test_x_bad_size (test_fblas.TestCscal) ... ok
- test_x_stride (test_fblas.TestCscal) ... ok
- test_simple (test_fblas.TestCswap) ... ok
- test_x_and_y_stride (test_fblas.TestCswap) ... ok
- test_x_bad_size (test_fblas.TestCswap) ... ok
- test_x_stride (test_fblas.TestCswap) ... ok
- test_y_bad_size (test_fblas.TestCswap) ... ok
- test_y_stride (test_fblas.TestCswap) ... ok
- test_default_a (test_fblas.TestDaxpy) ... ok
- test_simple (test_fblas.TestDaxpy) ... ok
- test_x_and_y_stride (test_fblas.TestDaxpy) ... ok
- test_x_bad_size (test_fblas.TestDaxpy) ... ok
- test_x_stride (test_fblas.TestDaxpy) ... ok
- test_y_bad_size (test_fblas.TestDaxpy) ... /usr/lib/python2.6/site-packages/scipy/lib/blas/tests/test_fblas.py:86: ComplexWarning: Casting complex values to real discards the imaginary part
- self.blas_func(x,y,n=3,incy=5)
- ok
- test_y_stride (test_fblas.TestDaxpy) ... ok
- test_simple (test_fblas.TestDcopy) ... ok
- test_x_and_y_stride (test_fblas.TestDcopy) ... ok
- test_x_bad_size (test_fblas.TestDcopy) ... ok
- test_x_stride (test_fblas.TestDcopy) ... ok
- test_y_bad_size (test_fblas.TestDcopy) ... /usr/lib/python2.6/site-packages/scipy/lib/blas/tests/test_fblas.py:196: ComplexWarning: Casting complex values to real discards the imaginary part
- self.blas_func(x,y,n=3,incy=5)
- ok
- test_y_stride (test_fblas.TestDcopy) ... ok
- test_default_beta_y (test_fblas.TestDgemv) ... ok
- test_simple (test_fblas.TestDgemv) ... ok
- test_simple_transpose (test_fblas.TestDgemv) ... ok
- test_simple_transpose_conj (test_fblas.TestDgemv) ... ok
- test_x_stride (test_fblas.TestDgemv) ... ok
- test_x_stride_assert (test_fblas.TestDgemv) ... ok
- test_x_stride_transpose (test_fblas.TestDgemv) ... ok
- test_y_stride (test_fblas.TestDgemv) ... ok
- test_y_stride_assert (test_fblas.TestDgemv) ... ok
- test_y_stride_transpose (test_fblas.TestDgemv) ... ok
- test_simple (test_fblas.TestDscal) ... ok
- test_x_bad_size (test_fblas.TestDscal) ... ok
- test_x_stride (test_fblas.TestDscal) ... ok
- test_simple (test_fblas.TestDswap) ... ok
- test_x_and_y_stride (test_fblas.TestDswap) ... ok
- test_x_bad_size (test_fblas.TestDswap) ... ok
- test_x_stride (test_fblas.TestDswap) ... ok
- test_y_bad_size (test_fblas.TestDswap) ... /usr/lib/python2.6/site-packages/scipy/lib/blas/tests/test_fblas.py:279: ComplexWarning: Casting complex values to real discards the imaginary part
- self.blas_func(x,y,n=3,incy=5)
- ok
- test_y_stride (test_fblas.TestDswap) ... ok
- test_default_a (test_fblas.TestSaxpy) ... ok
- test_simple (test_fblas.TestSaxpy) ... ok
- test_x_and_y_stride (test_fblas.TestSaxpy) ... ok
- test_x_bad_size (test_fblas.TestSaxpy) ... ok
- test_x_stride (test_fblas.TestSaxpy) ... ok
- test_y_bad_size (test_fblas.TestSaxpy) ... ok
- test_y_stride (test_fblas.TestSaxpy) ... ok
- test_simple (test_fblas.TestScopy) ... ok
- test_x_and_y_stride (test_fblas.TestScopy) ... ok
- test_x_bad_size (test_fblas.TestScopy) ... ok
- test_x_stride (test_fblas.TestScopy) ... ok
- test_y_bad_size (test_fblas.TestScopy) ... ok
- test_y_stride (test_fblas.TestScopy) ... ok
- test_default_beta_y (test_fblas.TestSgemv) ... ok
- test_simple (test_fblas.TestSgemv) ... ok
- test_simple_transpose (test_fblas.TestSgemv) ... ok
- test_simple_transpose_conj (test_fblas.TestSgemv) ... ok
- test_x_stride (test_fblas.TestSgemv) ... ok
- test_x_stride_assert (test_fblas.TestSgemv) ... ok
- test_x_stride_transpose (test_fblas.TestSgemv) ... ok
- test_y_stride (test_fblas.TestSgemv) ... ok
- test_y_stride_assert (test_fblas.TestSgemv) ... ok
- test_y_stride_transpose (test_fblas.TestSgemv) ... ok
- test_simple (test_fblas.TestSscal) ... ok
- test_x_bad_size (test_fblas.TestSscal) ... ok
- test_x_stride (test_fblas.TestSscal) ... ok
- test_simple (test_fblas.TestSswap) ... ok
- test_x_and_y_stride (test_fblas.TestSswap) ... ok
- test_x_bad_size (test_fblas.TestSswap) ... ok
- test_x_stride (test_fblas.TestSswap) ... ok
- test_y_bad_size (test_fblas.TestSswap) ... ok
- test_y_stride (test_fblas.TestSswap) ... ok
- test_default_a (test_fblas.TestZaxpy) ... ok
- test_simple (test_fblas.TestZaxpy) ... ok
- test_x_and_y_stride (test_fblas.TestZaxpy) ... ok
- test_x_bad_size (test_fblas.TestZaxpy) ... ok
- test_x_stride (test_fblas.TestZaxpy) ... ok
- test_y_bad_size (test_fblas.TestZaxpy) ... ok
- test_y_stride (test_fblas.TestZaxpy) ... ok
- test_simple (test_fblas.TestZcopy) ... ok
- test_x_and_y_stride (test_fblas.TestZcopy) ... ok
- test_x_bad_size (test_fblas.TestZcopy) ... ok
- test_x_stride (test_fblas.TestZcopy) ... ok
- test_y_bad_size (test_fblas.TestZcopy) ... ok
- test_y_stride (test_fblas.TestZcopy) ... ok
- test_default_beta_y (test_fblas.TestZgemv) ... ok
- test_simple (test_fblas.TestZgemv) ... ok
- test_simple_transpose (test_fblas.TestZgemv) ... ok
- test_simple_transpose_conj (test_fblas.TestZgemv) ... ok
- test_x_stride (test_fblas.TestZgemv) ... ok
- test_x_stride_assert (test_fblas.TestZgemv) ... ok
- test_x_stride_transpose (test_fblas.TestZgemv) ... ok
- test_y_stride (test_fblas.TestZgemv) ... ok
- test_y_stride_assert (test_fblas.TestZgemv) ... ok
- test_y_stride_transpose (test_fblas.TestZgemv) ... ok
- test_simple (test_fblas.TestZscal) ... ok
- test_x_bad_size (test_fblas.TestZscal) ... ok
- test_x_stride (test_fblas.TestZscal) ... ok
- test_simple (test_fblas.TestZswap) ... ok
- test_x_and_y_stride (test_fblas.TestZswap) ... ok
- test_x_bad_size (test_fblas.TestZswap) ... ok
- test_x_stride (test_fblas.TestZswap) ... ok
- test_y_bad_size (test_fblas.TestZswap) ... ok
- test_y_stride (test_fblas.TestZswap) ... ok
- test_clapack_dsyev (test_esv.TestEsv) ... SKIP: Skipping test: test_clapack_dsyev
- Clapack empty, skip clapack test
- test_clapack_dsyevr (test_esv.TestEsv) ... SKIP: Skipping test: test_clapack_dsyevr
- Clapack empty, skip clapack test
- test_clapack_dsyevr_ranges (test_esv.TestEsv) ... SKIP: Skipping test: test_clapack_dsyevr_ranges
- Clapack empty, skip clapack test
- test_clapack_ssyev (test_esv.TestEsv) ... SKIP: Skipping test: test_clapack_ssyev
- Clapack empty, skip clapack test
- test_clapack_ssyevr (test_esv.TestEsv) ... SKIP: Skipping test: test_clapack_ssyevr
- Clapack empty, skip clapack test
- test_clapack_ssyevr_ranges (test_esv.TestEsv) ... SKIP: Skipping test: test_clapack_ssyevr_ranges
- Clapack empty, skip clapack test
- test_dsyev (test_esv.TestEsv) ... ok
- test_dsyevr (test_esv.TestEsv) ... ok
- test_dsyevr_ranges (test_esv.TestEsv) ... ok
- test_ssyev (test_esv.TestEsv) ... ok
- test_ssyevr (test_esv.TestEsv) ... ok
- test_ssyevr_ranges (test_esv.TestEsv) ... ok
- test_clapack_dsygv_1 (test_gesv.TestSygv) ... SKIP: Skipping test: test_clapack_dsygv_1
- Clapack empty, skip flapack test
- test_clapack_dsygv_2 (test_gesv.TestSygv) ... SKIP: Skipping test: test_clapack_dsygv_2
- Clapack empty, skip flapack test
- test_clapack_dsygv_3 (test_gesv.TestSygv) ... SKIP: Skipping test: test_clapack_dsygv_3
- Clapack empty, skip flapack test
- test_clapack_ssygv_1 (test_gesv.TestSygv) ... SKIP: Skipping test: test_clapack_ssygv_1
- Clapack empty, skip flapack test
- test_clapack_ssygv_2 (test_gesv.TestSygv) ... SKIP: Skipping test: test_clapack_ssygv_2
- Clapack empty, skip flapack test
- test_clapack_ssygv_3 (test_gesv.TestSygv) ... SKIP: Skipping test: test_clapack_ssygv_3
- Clapack empty, skip flapack test
- test_dsygv_1 (test_gesv.TestSygv) ... ok
- test_dsygv_2 (test_gesv.TestSygv) ... ok
- test_dsygv_3 (test_gesv.TestSygv) ... ok
- test_ssygv_1 (test_gesv.TestSygv) ... ok
- test_ssygv_2 (test_gesv.TestSygv) ... ok
- test_ssygv_3 (test_gesv.TestSygv) ... ok
- test_clapack_dgebal (test_lapack.TestLapack) ... SKIP: Skipping test: test_clapack_dgebal
- Clapack empty, skip flapack test
- test_clapack_dgehrd (test_lapack.TestLapack) ... SKIP: Skipping test: test_clapack_dgehrd
- Clapack empty, skip flapack test
- test_clapack_sgebal (test_lapack.TestLapack) ... SKIP: Skipping test: test_clapack_sgebal
- Clapack empty, skip flapack test
- test_clapack_sgehrd (test_lapack.TestLapack) ... SKIP: Skipping test: test_clapack_sgehrd
- Clapack empty, skip flapack test
- test_dgebal (test_lapack.TestLapack) ... ok
- test_dgehrd (test_lapack.TestLapack) ... ok
- test_sgebal (test_lapack.TestLapack) ... ok
- test_sgehrd (test_lapack.TestLapack) ... ok
- test_random (test_basic.TestDet) ... ok
- test_random_complex (test_basic.TestDet) ... ok
- test_simple (test_basic.TestDet) ... ok
- test_simple_complex (test_basic.TestDet) ... ok
- test_random (test_basic.TestInv) ... ok
- test_random_complex (test_basic.TestInv) ... ok
- test_simple (test_basic.TestInv) ... ok
- test_simple_complex (test_basic.TestInv) ... ok
- test_random_complex_exact (test_basic.TestLstsq) ... ok
- test_random_complex_overdet (test_basic.TestLstsq) ... ok
- test_random_exact (test_basic.TestLstsq) ... ok
- test_random_overdet (test_basic.TestLstsq) ... ok
- test_random_overdet_large (test_basic.TestLstsq) ... ok
- test_simple_exact (test_basic.TestLstsq) ... ok
- test_simple_overdet (test_basic.TestLstsq) ... ok
- test_simple_underdet (test_basic.TestLstsq) ... ok
- test_basic.TestNorm.test_zero_norm ... ok
- test_simple (test_basic.TestPinv) ... ok
- test_simple_0det (test_basic.TestPinv) ... ok
- test_simple_cols (test_basic.TestPinv) ... ok
- test_simple_rows (test_basic.TestPinv) ... ok
- test_20Feb04_bug (test_basic.TestSolve) ... ok
- test_nils_20Feb04 (test_basic.TestSolve) ... ok
- test_random (test_basic.TestSolve) ... ok
- test_random_complex (test_basic.TestSolve) ... ok
- test_random_sym (test_basic.TestSolve) ... ok
- test_random_sym_complex (test_basic.TestSolve) ... ok
- test_simple (test_basic.TestSolve) ... ok
- test_simple_complex (test_basic.TestSolve) ... ok
- test_simple_sym (test_basic.TestSolve) ... ok
- test_simple_sym_complex (test_basic.TestSolve) ... ok
- test_bad_shape (test_basic.TestSolveBanded) ... ok
- test_complex (test_basic.TestSolveBanded) ... ok
- test_real (test_basic.TestSolveBanded) ... ok
- test_00_deprecation_warning (test_basic.TestSolveHBanded) ... ok
- test_01_complex (test_basic.TestSolveHBanded) ... ok
- test_01_float32 (test_basic.TestSolveHBanded) ... ok
- test_01_lower (test_basic.TestSolveHBanded) ... ok
- test_01_upper (test_basic.TestSolveHBanded) ... ok
- test_02_complex (test_basic.TestSolveHBanded) ... ok
- test_02_float32 (test_basic.TestSolveHBanded) ... ok
- test_02_lower (test_basic.TestSolveHBanded) ... ok
- test_02_upper (test_basic.TestSolveHBanded) ... ok
- test_03_upper (test_basic.TestSolveHBanded) ... ok
- test_bad_shapes (test_basic.TestSolveHBanded) ... ok
- test_axpy (test_blas.TestCBLAS1Simple) ... ok
- test_amax (test_blas.TestFBLAS1Simple) ... ok
- test_asum (test_blas.TestFBLAS1Simple) ... ok
- test_axpy (test_blas.TestFBLAS1Simple) ... ok
- test_complex_dotc (test_blas.TestFBLAS1Simple) ... ok
- test_complex_dotu (test_blas.TestFBLAS1Simple) ... ok
- test_copy (test_blas.TestFBLAS1Simple) ... ok
- test_dot (test_blas.TestFBLAS1Simple) ... ok
- test_nrm2 (test_blas.TestFBLAS1Simple) ... ok
- test_scal (test_blas.TestFBLAS1Simple) ... ok
- test_swap (test_blas.TestFBLAS1Simple) ... ok
- test_gemv (test_blas.TestFBLAS2Simple) ... ok
- test_ger (test_blas.TestFBLAS2Simple) ... ok
- test_gemm (test_blas.TestFBLAS3Simple) ... ok
- test_lapack (test_build.TestF77Mismatch) ... ok
- test_datanotshared (test_decomp.TestDataNotShared) ... ok
- test_simple (test_decomp.TestDiagSVD) ... ok
- Test matrices giving some Nan generalized eigen values. ... Warning: invalid value encountered in divide
- ok
- Check that passing a non-square array raises a ValueError. ... ok
- Check that passing arrays of with different shapes raises a ValueError. ... ok
- test_simple (test_decomp.TestEig) ... ok
- test_simple_complex (test_decomp.TestEig) ... ok
- Test singular pair ... Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- ok
- Compare dgbtrf LU factorisation with the LU factorisation result ... ok
- Compare dgbtrs solutions for linear equation system A*x = b ... ok
- Compare dsbev eigenvalues and eigenvectors with ... ok
- Compare dsbevd eigenvalues and eigenvectors with ... ok
- Compare dsbevx eigenvalues and eigenvectors ... ok
- Compare eigenvalues and eigenvectors of eig_banded ... ok
- Compare eigenvalues of eigvals_banded with those of linalg.eig. ... ok
- Compare zgbtrf LU factorisation with the LU factorisation result ... ok
- Compare zgbtrs solutions for linear equation system A*x = b ... ok
- Compare zhbevd eigenvalues and eigenvectors ... ok
- Compare zhbevx eigenvalues and eigenvectors ... ok
- test_simple (test_decomp.TestEigVals) ... ok
- test_simple_complex (test_decomp.TestEigVals) ... ok
- test_simple_tr (test_decomp.TestEigVals) ... ok
- test_random (test_decomp.TestHessenberg) ... ok
- test_random_complex (test_decomp.TestHessenberg) ... ok
- test_simple (test_decomp.TestHessenberg) ... ok
- test_simple2 (test_decomp.TestHessenberg) ... ok
- test_simple_complex (test_decomp.TestHessenberg) ... ok
- test_hrectangular (test_decomp.TestLU) ... ok
- test_hrectangular_complex (test_decomp.TestLU) ... ok
- Check lu decomposition on medium size, rectangular matrix. ... ok
- Check lu decomposition on medium size, rectangular matrix. ... ok
- test_simple (test_decomp.TestLU) ... ok
- test_simple2 (test_decomp.TestLU) ... ok
- test_simple2_complex (test_decomp.TestLU) ... ok
- test_simple_complex (test_decomp.TestLU) ... ok
- test_vrectangular (test_decomp.TestLU) ... ok
- test_vrectangular_complex (test_decomp.TestLU) ... ok
- test_hrectangular (test_decomp.TestLUSingle) ... ok
- test_hrectangular_complex (test_decomp.TestLUSingle) ... ok
- Check lu decomposition on medium size, rectangular matrix. ... ok
- Check lu decomposition on medium size, rectangular matrix. ... ok
- test_simple (test_decomp.TestLUSingle) ... ok
- test_simple2 (test_decomp.TestLUSingle) ... ok
- test_simple2_complex (test_decomp.TestLUSingle) ... ok
- test_simple_complex (test_decomp.TestLUSingle) ... ok
- test_vrectangular (test_decomp.TestLUSingle) ... ok
- test_vrectangular_complex (test_decomp.TestLUSingle) ... ok
- test_lu (test_decomp.TestLUSolve) ... ok
- test_random (test_decomp.TestQR) ... ok
- test_random_complex (test_decomp.TestQR) ... ok
- test_random_tall (test_decomp.TestQR) ... ok
- test_random_tall_e (test_decomp.TestQR) ... ok
- test_random_trap (test_decomp.TestQR) ... ok
- test_simple (test_decomp.TestQR) ... ok
- test_simple_complex (test_decomp.TestQR) ... ok
- test_simple_tall (test_decomp.TestQR) ... ok
- test_simple_tall_e (test_decomp.TestQR) ... ok
- test_simple_trap (test_decomp.TestQR) ... ok
- test_random (test_decomp.TestRQ) ... ok
- test_simple (test_decomp.TestRQ) ... ok
- test_random (test_decomp.TestSVD) ... ok
- test_random_complex (test_decomp.TestSVD) ... ok
- test_simple (test_decomp.TestSVD) ... ok
- test_simple_complex (test_decomp.TestSVD) ... ok
- test_simple_overdet (test_decomp.TestSVD) ... ok
- test_simple_singular (test_decomp.TestSVD) ... ok
- test_simple_underdet (test_decomp.TestSVD) ... ok
- test_simple (test_decomp.TestSVDVals) ... ok
- test_simple_complex (test_decomp.TestSVDVals) ... ok
- test_simple_overdet (test_decomp.TestSVDVals) ... ok
- test_simple_overdet_complex (test_decomp.TestSVDVals) ... ok
- test_simple_underdet (test_decomp.TestSVDVals) ... ok
- test_simple_underdet_complex (test_decomp.TestSVDVals) ... ok
- test_simple (test_decomp.TestSchur) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', True, True, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'f', True, True, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', True, False, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'f', True, False, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', True, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'f', True, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', True, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'f', True, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', True, True, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'f', True, True, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', True, False, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'f', True, False, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', True, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'f', True, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', True, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'f', True, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', False, True, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'f', False, True, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', False, False, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'f', False, False, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', False, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'f', False, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', False, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'f', False, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', False, True, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'f', False, True, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', False, False, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'f', False, False, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', False, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'f', False, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'f', False, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'f', False, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', True, True, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'd', True, True, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', True, False, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'd', True, False, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', True, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'd', True, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', True, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'd', True, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', True, True, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'd', True, True, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', True, False, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'd', True, False, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', True, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'd', True, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', True, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'd', True, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', False, True, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'd', False, True, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', False, False, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'd', False, False, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', False, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'd', False, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', False, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'd', False, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', False, True, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'd', False, True, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', False, False, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'd', False, False, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', False, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'd', False, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'd', False, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'd', False, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', True, True, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'F', True, True, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', True, False, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'F', True, False, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', True, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'F', True, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', True, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'F', True, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', True, True, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'F', True, True, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', True, False, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'F', True, False, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', True, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'F', True, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', True, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'F', True, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', False, True, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'F', False, True, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', False, False, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'F', False, False, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', False, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'F', False, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', False, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'F', False, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', False, True, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'F', False, True, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', False, False, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'F', False, False, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', False, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'F', False, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'F', False, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'F', False, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', True, True, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'D', True, True, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', True, False, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'D', True, False, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', True, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'D', True, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', True, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'D', True, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', True, True, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'D', True, True, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', True, False, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'D', True, False, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', True, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'D', True, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', True, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'D', True, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', False, True, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'D', False, True, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', False, False, True, None) ... ok
- test_decomp.test_eigh('general ', 6, 'D', False, False, True, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', False, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'D', False, True, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', False, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'D', False, False, True, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', False, True, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'D', False, True, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', False, False, False, None) ... ok
- test_decomp.test_eigh('general ', 6, 'D', False, False, False, None) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', False, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'D', False, True, False, (2, 4)) ... ok
- test_decomp.test_eigh('ordinary', 6, 'D', False, False, False, (2, 4)) ... ok
- test_decomp.test_eigh('general ', 6, 'D', False, False, False, (2, 4)) ... ok
- test_decomp.test_eigh_integer ... ok
- Check linalg works with non-aligned memory ... ok
- Check linalg works with non-aligned memory ... ok
- Check that complex objects don't need to be completely aligned ... ok
- test_decomp.test_lapack_misaligned ... KNOWNFAIL: Ticket #1152, triggers a segfault in rare cases.
- test_random (test_decomp_cholesky.TestCholesky) ... ok
- test_random_complex (test_decomp_cholesky.TestCholesky) ... ok
- test_simple (test_decomp_cholesky.TestCholesky) ... ok
- test_simple_complex (test_decomp_cholesky.TestCholesky) ... ok
- test_lower_complex (test_decomp_cholesky.TestCholeskyBanded) ... ok
- test_lower_real (test_decomp_cholesky.TestCholeskyBanded) ... ok
- test_upper_complex (test_decomp_cholesky.TestCholeskyBanded) ... ok
- test_upper_real (test_decomp_cholesky.TestCholeskyBanded) ... ok
- test_default_a (test_fblas.TestCaxpy) ... ok
- test_simple (test_fblas.TestCaxpy) ... ok
- test_x_and_y_stride (test_fblas.TestCaxpy) ... ok
- test_x_bad_size (test_fblas.TestCaxpy) ... ok
- test_x_stride (test_fblas.TestCaxpy) ... ok
- test_y_bad_size (test_fblas.TestCaxpy) ... ok
- test_y_stride (test_fblas.TestCaxpy) ... ok
- test_simple (test_fblas.TestCcopy) ... ok
- test_x_and_y_stride (test_fblas.TestCcopy) ... ok
- test_x_bad_size (test_fblas.TestCcopy) ... ok
- test_x_stride (test_fblas.TestCcopy) ... ok
- test_y_bad_size (test_fblas.TestCcopy) ... ok
- test_y_stride (test_fblas.TestCcopy) ... ok
- test_default_beta_y (test_fblas.TestCgemv) ... ok
- test_simple (test_fblas.TestCgemv) ... ok
- test_simple_transpose (test_fblas.TestCgemv) ... ok
- test_simple_transpose_conj (test_fblas.TestCgemv) ... ok
- test_x_stride (test_fblas.TestCgemv) ... ok
- test_x_stride_assert (test_fblas.TestCgemv) ... ok
- test_x_stride_transpose (test_fblas.TestCgemv) ... ok
- test_y_stride (test_fblas.TestCgemv) ... ok
- test_y_stride_assert (test_fblas.TestCgemv) ... ok
- test_y_stride_transpose (test_fblas.TestCgemv) ... ok
- test_simple (test_fblas.TestCscal) ... ok
- test_x_bad_size (test_fblas.TestCscal) ... ok
- test_x_stride (test_fblas.TestCscal) ... ok
- test_simple (test_fblas.TestCswap) ... ok
- test_x_and_y_stride (test_fblas.TestCswap) ... ok
- test_x_bad_size (test_fblas.TestCswap) ... ok
- test_x_stride (test_fblas.TestCswap) ... ok
- test_y_bad_size (test_fblas.TestCswap) ... ok
- test_y_stride (test_fblas.TestCswap) ... ok
- test_default_a (test_fblas.TestDaxpy) ... ok
- test_simple (test_fblas.TestDaxpy) ... ok
- test_x_and_y_stride (test_fblas.TestDaxpy) ... ok
- test_x_bad_size (test_fblas.TestDaxpy) ... ok
- test_x_stride (test_fblas.TestDaxpy) ... ok
- test_y_bad_size (test_fblas.TestDaxpy) ... /usr/lib/python2.6/site-packages/scipy/linalg/tests/test_fblas.py:89: ComplexWarning: Casting complex values to real discards the imaginary part
- self.blas_func(x,y,n=3,incy=5)
- ok
- test_y_stride (test_fblas.TestDaxpy) ... ok
- test_simple (test_fblas.TestDcopy) ... ok
- test_x_and_y_stride (test_fblas.TestDcopy) ... ok
- test_x_bad_size (test_fblas.TestDcopy) ... ok
- test_x_stride (test_fblas.TestDcopy) ... ok
- test_y_bad_size (test_fblas.TestDcopy) ... /usr/lib/python2.6/site-packages/scipy/linalg/tests/test_fblas.py:199: ComplexWarning: Casting complex values to real discards the imaginary part
- self.blas_func(x,y,n=3,incy=5)
- ok
- test_y_stride (test_fblas.TestDcopy) ... ok
- test_default_beta_y (test_fblas.TestDgemv) ... ok
- test_simple (test_fblas.TestDgemv) ... ok
- test_simple_transpose (test_fblas.TestDgemv) ... ok
- test_simple_transpose_conj (test_fblas.TestDgemv) ... ok
- test_x_stride (test_fblas.TestDgemv) ... ok
- test_x_stride_assert (test_fblas.TestDgemv) ... ok
- test_x_stride_transpose (test_fblas.TestDgemv) ... ok
- test_y_stride (test_fblas.TestDgemv) ... ok
- test_y_stride_assert (test_fblas.TestDgemv) ... ok
- test_y_stride_transpose (test_fblas.TestDgemv) ... ok
- test_simple (test_fblas.TestDscal) ... ok
- test_x_bad_size (test_fblas.TestDscal) ... ok
- test_x_stride (test_fblas.TestDscal) ... ok
- test_simple (test_fblas.TestDswap) ... ok
- test_x_and_y_stride (test_fblas.TestDswap) ... ok
- test_x_bad_size (test_fblas.TestDswap) ... ok
- test_x_stride (test_fblas.TestDswap) ... ok
- test_y_bad_size (test_fblas.TestDswap) ... /usr/lib/python2.6/site-packages/scipy/linalg/tests/test_fblas.py:282: ComplexWarning: Casting complex values to real discards the imaginary part
- self.blas_func(x,y,n=3,incy=5)
- ok
- test_y_stride (test_fblas.TestDswap) ... ok
- test_default_a (test_fblas.TestSaxpy) ... ok
- test_simple (test_fblas.TestSaxpy) ... ok
- test_x_and_y_stride (test_fblas.TestSaxpy) ... ok
- test_x_bad_size (test_fblas.TestSaxpy) ... ok
- test_x_stride (test_fblas.TestSaxpy) ... ok
- test_y_bad_size (test_fblas.TestSaxpy) ... ok
- test_y_stride (test_fblas.TestSaxpy) ... ok
- test_simple (test_fblas.TestScopy) ... ok
- test_x_and_y_stride (test_fblas.TestScopy) ... ok
- test_x_bad_size (test_fblas.TestScopy) ... ok
- test_x_stride (test_fblas.TestScopy) ... ok
- test_y_bad_size (test_fblas.TestScopy) ... ok
- test_y_stride (test_fblas.TestScopy) ... ok
- test_default_beta_y (test_fblas.TestSgemv) ... ok
- test_simple (test_fblas.TestSgemv) ... ok
- test_simple_transpose (test_fblas.TestSgemv) ... ok
- test_simple_transpose_conj (test_fblas.TestSgemv) ... ok
- test_x_stride (test_fblas.TestSgemv) ... ok
- test_x_stride_assert (test_fblas.TestSgemv) ... ok
- test_x_stride_transpose (test_fblas.TestSgemv) ... ok
- test_y_stride (test_fblas.TestSgemv) ... ok
- test_y_stride_assert (test_fblas.TestSgemv) ... ok
- test_y_stride_transpose (test_fblas.TestSgemv) ... ok
- test_simple (test_fblas.TestSscal) ... ok
- test_x_bad_size (test_fblas.TestSscal) ... ok
- test_x_stride (test_fblas.TestSscal) ... ok
- test_simple (test_fblas.TestSswap) ... ok
- test_x_and_y_stride (test_fblas.TestSswap) ... ok
- test_x_bad_size (test_fblas.TestSswap) ... ok
- test_x_stride (test_fblas.TestSswap) ... ok
- test_y_bad_size (test_fblas.TestSswap) ... ok
- test_y_stride (test_fblas.TestSswap) ... ok
- test_default_a (test_fblas.TestZaxpy) ... ok
- test_simple (test_fblas.TestZaxpy) ... ok
- test_x_and_y_stride (test_fblas.TestZaxpy) ... ok
- test_x_bad_size (test_fblas.TestZaxpy) ... ok
- test_x_stride (test_fblas.TestZaxpy) ... ok
- test_y_bad_size (test_fblas.TestZaxpy) ... ok
- test_y_stride (test_fblas.TestZaxpy) ... ok
- test_simple (test_fblas.TestZcopy) ... ok
- test_x_and_y_stride (test_fblas.TestZcopy) ... ok
- test_x_bad_size (test_fblas.TestZcopy) ... ok
- test_x_stride (test_fblas.TestZcopy) ... ok
- test_y_bad_size (test_fblas.TestZcopy) ... ok
- test_y_stride (test_fblas.TestZcopy) ... ok
- test_default_beta_y (test_fblas.TestZgemv) ... ok
- test_simple (test_fblas.TestZgemv) ... ok
- test_simple_transpose (test_fblas.TestZgemv) ... ok
- test_simple_transpose_conj (test_fblas.TestZgemv) ... ok
- test_x_stride (test_fblas.TestZgemv) ... ok
- test_x_stride_assert (test_fblas.TestZgemv) ... ok
- test_x_stride_transpose (test_fblas.TestZgemv) ... ok
- test_y_stride (test_fblas.TestZgemv) ... ok
- test_y_stride_assert (test_fblas.TestZgemv) ... ok
- test_y_stride_transpose (test_fblas.TestZgemv) ... ok
- test_simple (test_fblas.TestZscal) ... ok
- test_x_bad_size (test_fblas.TestZscal) ... ok
- test_x_stride (test_fblas.TestZscal) ... ok
- test_simple (test_fblas.TestZswap) ... ok
- test_x_and_y_stride (test_fblas.TestZswap) ... ok
- test_x_bad_size (test_fblas.TestZswap) ... ok
- test_x_stride (test_fblas.TestZswap) ... ok
- test_y_bad_size (test_fblas.TestZswap) ... ok
- test_y_stride (test_fblas.TestZswap) ... ok
- test_gebal (test_lapack.TestFlapackSimple) ... ok
- test_gehrd (test_lapack.TestFlapackSimple) ... ok
- test_clapack (test_lapack.TestLapack) ... ok
- test_flapack (test_lapack.TestLapack) ... ok
- test_zero (test_matfuncs.TestExpM) ... /usr/lib/python2.6/site-packages/scipy/linalg/matfuncs.py:94: ComplexWarning: Casting complex values to real discards the imaginary part
- return dot(dot(vr,diag(exp(s))),vri).astype(t)
- ok
- test_nils (test_matfuncs.TestLogM) ... ok
- test_defective1 (test_matfuncs.TestSignM) ... ok
- test_defective2 (test_matfuncs.TestSignM) ... ok
- test_defective3 (test_matfuncs.TestSignM) ... ok
- test_nils (test_matfuncs.TestSignM) ... ok
- test_bad (test_matfuncs.TestSqrtM) ... ok
- test_special_matrices.TestBlockDiag.test_bad_arg ... ok
- test_special_matrices.TestBlockDiag.test_basic ... ok
- test_special_matrices.TestBlockDiag.test_dtype ... ok
- test_special_matrices.TestBlockDiag.test_no_args ... ok
- test_special_matrices.TestBlockDiag.test_scalar_and_1d_args ... ok
- test_basic (test_special_matrices.TestCirculant) ... ok
- test_bad_shapes (test_special_matrices.TestCompanion) ... ok
- test_basic (test_special_matrices.TestCompanion) ... ok
- test_basic (test_special_matrices.TestHadamard) ... ok
- test_basic (test_special_matrices.TestHankel) ... ok
- test_special_matrices.TestKron.test_basic ... ok
- test_bad_shapes (test_special_matrices.TestLeslie) ... ok
- test_basic (test_special_matrices.TestLeslie) ... ok
- test_basic (test_special_matrices.TestToeplitz) ... ok
- test_complex_01 (test_special_matrices.TestToeplitz) ... ok
- Scalar arguments still produce a 2D array. ... ok
- test_scalar_01 (test_special_matrices.TestToeplitz) ... ok
- test_scalar_02 (test_special_matrices.TestToeplitz) ... ok
- test_scalar_03 (test_special_matrices.TestToeplitz) ... ok
- test_scalar_04 (test_special_matrices.TestToeplitz) ... ok
- test_2d (test_special_matrices.TestTri) ... ok
- test_basic (test_special_matrices.TestTri) ... ok
- test_diag (test_special_matrices.TestTri) ... ok
- test_diag2d (test_special_matrices.TestTri) ... ok
- test_basic (test_special_matrices.TestTril) ... ok
- test_diag (test_special_matrices.TestTril) ... ok
- test_basic (test_special_matrices.TestTriu) ... ok
- test_diag (test_special_matrices.TestTriu) ... ok
- test_logsumexp (test_maxentropy.TestMaxentropy) ... ok
- test_simple (test_maxentropy.TestMaxentropy) ... ok
- test_doccer.test_unindent('Another test\n with some indent', 'Another test\n with some indent') ... ok
- test_doccer.test_unindent('Another test, one line', 'Another test, one line') ... ok
- test_doccer.test_unindent('Another test\n with some indent', 'Another test\n with some indent') ... ok
- test_doccer.test_unindent_dict('Another test\n with some indent', 'Another test\n with some indent') ... ok
- test_doccer.test_unindent_dict('Another test, one line', 'Another test, one line') ... ok
- test_doccer.test_unindent_dict('Another test\n with some indent', 'Another test\n with some indent') ... ok
- test_doccer.test_docformat('Docstring\n Another test\n with some indent\n Another test, one line\n Another test\n with some indent\n', 'Docstring\n Another test\n with some indent\n Another test, one line\n Another test\n with some indent\n') ... ok
- test_doccer.test_docformat('Single line doc Another test\n with some indent', 'Single line doc Another test\n with some indent') ... ok
- test_doccer.test_decorator(' Docstring\n Another test\n with some indent\n ', ' Docstring\n Another test\n with some indent\n ') ... ok
- test_doccer.test_decorator(' Docstring\n Another test\n with some indent\n ', ' Docstring\n Another test\n with some indent\n ') ... ok
- test_bytescale (test_pilutil.TestPILUtil) ... ok
- test_imresize (test_pilutil.TestPILUtil) ... ok
- test_imresize2 (test_pilutil.TestPILUtil) ... ok
- test_imresize3 (test_pilutil.TestPILUtil) ... ok
- Test generator for parametric tests ... ok
- Test generator for parametric tests ... ok
- Test generator for parametric tests ... ok
- test_filters.test_ticket_701 ... ok
- test_filters.test_orders_gauss(0, array([ 0.])) ... ok
- test_filters.test_orders_gauss(0, array([ 0.])) ... ok
- test_filters.test_orders_gauss(<type 'exceptions.ValueError'>, <function gaussian_filter at 0x9dcfa04>, array([ 0.]), 1, -1) ... ok
- test_filters.test_orders_gauss(<type 'exceptions.ValueError'>, <function gaussian_filter at 0x9dcfa04>, array([ 0.]), 1, 4) ... ok
- test_filters.test_orders_gauss(0, array([ 0.])) ... ok
- test_filters.test_orders_gauss(0, array([ 0.])) ... ok
- test_filters.test_orders_gauss(<type 'exceptions.ValueError'>, <function gaussian_filter1d at 0x9dcfaac>, array([ 0.]), 1, -1, -1) ... ok
- test_filters.test_orders_gauss(<type 'exceptions.ValueError'>, <function gaussian_filter1d at 0x9dcfaac>, array([ 0.]), 1, -1, 4) ... ok
- test_io.test_imread ... ok
- affine_transform 1 ... ok
- affine transform 2 ... ok
- affine transform 3 ... ok
- affine transform 4 ... ok
- affine transform 5 ... ok
- affine transform 6 ... ok
- affine transform 7 ... ok
- affine transform 8 ... ok
- affine transform 9 ... ok
- affine transform 10 ... ok
- affine transform 11 ... ok
- affine transform 12 ... ok
- affine transform 13 ... ok
- affine transform 14 ... ok
- affine transform 15 ... ok
- affine transform 16 ... ok
- affine transform 17 ... ok
- affine transform 18 ... ok
- affine transform 19 ... ok
- affine transform 20 ... ok
- affine transform 21 ... ok
- binary closing 1 ... ok
- binary closing 2 ... ok
- binary dilation 1 ... ok
- binary dilation 2 ... ok
- binary dilation 3 ... ok
- binary dilation 4 ... ok
- binary dilation 5 ... ok
- binary dilation 6 ... ok
- binary dilation 7 ... ok
- binary dilation 8 ... ok
- binary dilation 9 ... ok
- binary dilation 10 ... ok
- binary dilation 11 ... ok
- binary dilation 12 ... ok
- binary dilation 13 ... ok
- binary dilation 14 ... ok
- binary dilation 15 ... ok
- binary dilation 16 ... ok
- binary dilation 17 ... ok
- binary dilation 18 ... ok
- binary dilation 19 ... ok
- binary dilation 20 ... ok
- binary dilation 21 ... ok
- binary dilation 22 ... ok
- binary dilation 23 ... ok
- binary dilation 24 ... ok
- binary dilation 25 ... ok
- binary dilation 26 ... ok
- binary dilation 27 ... ok
- binary dilation 28 ... ok
- binary dilation 29 ... ok
- binary dilation 30 ... ok
- binary dilation 31 ... ok
- binary dilation 32 ... ok
- binary dilation 33 ... ok
- binary dilation 34 ... ok
- binary dilation 35 ... ok
- binary erosion 1 ... ok
- binary erosion 2 ... ok
- binary erosion 3 ... ok
- binary erosion 4 ... ok
- binary erosion 5 ... ok
- binary erosion 6 ... ok
- binary erosion 7 ... ok
- binary erosion 8 ... ok
- binary erosion 9 ... ok
- binary erosion 10 ... ok
- binary erosion 11 ... ok
- binary erosion 12 ... ok
- binary erosion 13 ... ok
- binary erosion 14 ... ok
- binary erosion 15 ... ok
- binary erosion 16 ... ok
- binary erosion 17 ... ok
- binary erosion 18 ... ok
- binary erosion 19 ... ok
- binary erosion 20 ... ok
- binary erosion 21 ... ok
- binary erosion 22 ... ok
- binary erosion 23 ... ok
- binary erosion 24 ... ok
- binary erosion 25 ... ok
- binary erosion 26 ... ok
- binary erosion 27 ... ok
- binary erosion 28 ... ok
- binary erosion 29 ... ok
- binary erosion 30 ... ok
- binary erosion 31 ... ok
- binary erosion 32 ... ok
- binary erosion 33 ... ok
- binary erosion 34 ... ok
- binary erosion 35 ... ok
- binary erosion 36 ... ok
- binary fill holes 1 ... ok
- binary fill holes 2 ... ok
- binary fill holes 3 ... ok
- binary opening 1 ... ok
- binary opening 2 ... ok
- binary propagation 1 ... ok
- binary propagation 2 ... ok
- black tophat 1 ... ok
- black tophat 2 ... ok
- boundary modes ... ok
- boundary modes 2 ... ok
- center of mass 1 ... ok
- center of mass 2 ... ok
- center of mass 3 ... ok
- center of mass 4 ... ok
- center of mass 5 ... ok
- center of mass 6 ... ok
- center of mass 7 ... ok
- center of mass 8 ... ok
- center of mass 9 ... ok
- correlation 1 ... ok
- correlation 2 ... ok
- correlation 3 ... ok
- correlation 4 ... ok
- correlation 5 ... ok
- correlation 6 ... ok
- correlation 7 ... ok
- correlation 8 ... ok
- correlation 9 ... ok
- correlation 10 ... ok
- correlation 11 ... ok
- correlation 12 ... ok
- correlation 13 ... ok
- correlation 14 ... ok
- correlation 15 ... ok
- correlation 16 ... ok
- correlation 17 ... ok
- correlation 18 ... ok
- correlation 19 ... ok
- correlation 20 ... ok
- correlation 21 ... ok
- correlation 22 ... ok
- correlation 23 ... ok
- correlation 24 ... ok
- correlation 25 ... ok
- brute force distance transform 1 ... ok
- brute force distance transform 2 ... ok
- brute force distance transform 3 ... ok
- brute force distance transform 4 ... ok
- brute force distance transform 5 ... ok
- brute force distance transform 6 ... ok
- chamfer type distance transform 1 ... ok
- chamfer type distance transform 2 ... ok
- chamfer type distance transform 3 ... ok
- euclidean distance transform 1 ... ok
- euclidean distance transform 2 ... ok
- euclidean distance transform 3 ... ok
- euclidean distance transform 4 ... ok
- line extension 1 ... ok
- line extension 2 ... ok
- line extension 3 ... ok
- line extension 4 ... ok
- line extension 5 ... ok
- line extension 6 ... ok
- line extension 7 ... ok
- line extension 8 ... ok
- line extension 9 ... ok
- line extension 10 ... ok
- extrema 1 ... ok
- extrema 2 ... ok
- extrema 3 ... ok
- extrema 4 ... ok
- find_objects 1 ... ok
- find_objects 2 ... ok
- find_objects 3 ... ok
- find_objects 4 ... ok
- find_objects 5 ... ok
- find_objects 6 ... ok
- find_objects 7 ... ok
- find_objects 8 ... ok
- find_objects 9 ... ok
- ellipsoid fourier filter for complex transforms 1 ... ok
- ellipsoid fourier filter for real transforms 1 ... ok
- gaussian fourier filter for complex transforms 1 ... ok
- gaussian fourier filter for real transforms 1 ... ok
- shift filter for complex transforms 1 ... /usr/lib/python2.6/site-packages/scipy/ndimage/tests/test_ndimage.py:56: ComplexWarning: Casting complex values to real discards the imaginary part
- a = a.astype(numpy.float64)
- /usr/lib/python2.6/site-packages/scipy/ndimage/tests/test_ndimage.py:58: ComplexWarning: Casting complex values to real discards the imaginary part
- b = b.astype(numpy.float64)
- ok
- shift filter for real transforms 1 ... ok
- uniform fourier filter for complex transforms 1 ... ok
- uniform fourier filter for real transforms 1 ... ok
- gaussian filter 1 ... ok
- gaussian filter 2 ... ok
- gaussian filter 3 ... ok
- gaussian filter 4 ... ok
- gaussian filter 5 ... ok
- gaussian filter 6 ... ok
- gaussian gradient magnitude filter 1 ... ok
- gaussian gradient magnitude filter 2 ... ok
- gaussian laplace filter 1 ... ok
- gaussian laplace filter 2 ... ok
- generation of a binary structure 1 ... ok
- generation of a binary structure 2 ... ok
- generation of a binary structure 3 ... ok
- generation of a binary structure 4 ... ok
- generic filter 1 ... ok
- generic 1d filter 1 ... ok
- generic gradient magnitude 1 ... ok
- generic laplace filter 1 ... ok
- geometric transform 1 ... ok
- geometric transform 2 ... ok
- geometric transform 3 ... ok
- geometric transform 4 ... ok
- geometric transform 5 ... ok
- geometric transform 6 ... ok
- geometric transform 7 ... ok
- geometric transform 8 ... ok
- geometric transform 10 ... ok
- geometric transform 13 ... ok
- geometric transform 14 ... ok
- geometric transform 15 ... ok
- geometric transform 16 ... ok
- geometric transform 17 ... ok
- geometric transform 18 ... ok
- geometric transform 19 ... ok
- geometric transform 20 ... ok
- geometric transform 21 ... ok
- geometric transform 22 ... ok
- geometric transform 23 ... ok
- geometric transform 24 ... ok
- grey closing 1 ... ok
- grey closing 2 ... ok
- grey dilation 1 ... ok
- grey dilation 2 ... ok
- grey dilation 3 ... ok
- grey erosion 1 ... ok
- grey erosion 2 ... ok
- grey erosion 3 ... ok
- grey opening 1 ... ok
- grey opening 2 ... ok
- histogram 1 ... ok
- histogram 2 ... ok
- histogram 3 ... ok
- binary hit-or-miss transform 1 ... ok
- binary hit-or-miss transform 2 ... ok
- binary hit-or-miss transform 3 ... ok
- iterating a structure 1 ... ok
- iterating a structure 2 ... ok
- iterating a structure 3 ... ok
- label 1 ... ok
- label 2 ... ok
- label 3 ... ok
- label 4 ... ok
- label 5 ... ok
- label 6 ... ok
- label 7 ... ok
- label 8 ... ok
- label 9 ... ok
- label 10 ... ok
- label 11 ... ok
- label 12 ... ok
- label 13 ... ok
- laplace filter 1 ... ok
- laplace filter 2 ... ok
- map coordinates 1 ... ok
- map coordinates 2 ... ok
- maximum 1 ... ok
- maximum 2 ... ok
- maximum 3 ... ok
- maximum 4 ... ok
- Ticket #501 ... ok
- maximum filter 1 ... ok
- maximum filter 2 ... ok
- maximum filter 3 ... ok
- maximum filter 4 ... ok
- maximum filter 5 ... ok
- maximum filter 6 ... ok
- maximum filter 7 ... ok
- maximum filter 8 ... ok
- maximum filter 9 ... ok
- maximum position 1 ... ok
- maximum position 2 ... ok
- maximum position 3 ... ok
- maximum position 4 ... ok
- maximum position 5 ... ok
- maximum position 6 ... ok
- mean 1 ... ok
- mean 2 ... ok
- mean 3 ... ok
- mean 4 ... Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- ok
- minimum 1 ... ok
- minimum 2 ... ok
- minimum 3 ... ok
- minimum 4 ... ok
- minimum filter 1 ... ok
- minimum filter 2 ... ok
- minimum filter 3 ... ok
- minimum filter 4 ... ok
- minimum filter 5 ... ok
- minimum filter 6 ... ok
- minimum filter 7 ... ok
- minimum filter 8 ... ok
- minimum filter 9 ... ok
- minimum position 1 ... ok
- minimum position 2 ... ok
- minimum position 3 ... ok
- minimum position 4 ... ok
- minimum position 5 ... ok
- minimum position 6 ... ok
- minimum position 7 ... ok
- morphological gradient 1 ... ok
- morphological gradient 2 ... ok
- morphological laplace 1 ... ok
- morphological laplace 2 ... ok
- prewitt filter 1 ... ok
- prewitt filter 2 ... ok
- prewitt filter 3 ... ok
- prewitt filter 4 ... ok
- rank filter 1 ... ok
- rank filter 2 ... ok
- rank filter 3 ... ok
- rank filter 4 ... ok
- rank filter 5 ... ok
- rank filter 6 ... ok
- rank filter 7 ... ok
- median filter 8 ... ok
- rank filter 9 ... ok
- rank filter 10 ... ok
- rank filter 11 ... ok
- rank filter 12 ... ok
- rank filter 13 ... ok
- rank filter 14 ... ok
- rotate 1 ... ok
- rotate 2 ... ok
- rotate 3 ... ok
- rotate 4 ... ok
- rotate 5 ... ok
- rotate 6 ... ok
- rotate 7 ... ok
- rotate 8 ... ok
- shift 1 ... ok
- shift 2 ... ok
- shift 3 ... ok
- shift 4 ... ok
- shift 5 ... ok
- shift 6 ... ok
- shift 7 ... ok
- shift 8 ... ok
- shift 9 ... ok
- sobel filter 1 ... ok
- sobel filter 2 ... ok
- sobel filter 3 ... ok
- sobel filter 4 ... ok
- spline filter 1 ... ok
- spline filter 2 ... ok
- spline filter 3 ... ok
- spline filter 4 ... ok
- spline filter 5 ... ok
- standard deviation 1 ... Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- ok
- standard deviation 2 ... ok
- standard deviation 3 ... ok
- standard deviation 4 ... ok
- standard deviation 5 ... ok
- standard deviation 6 ... ok
- sum 1 ... ok
- sum 2 ... ok
- sum 3 ... ok
- sum 4 ... ok
- sum 5 ... ok
- sum 6 ... ok
- sum 7 ... ok
- sum 8 ... ok
- sum 9 ... ok
- sum 10 ... ok
- sum 11 ... ok
- sum 12 ... ok
- uniform filter 1 ... ok
- uniform filter 2 ... ok
- uniform filter 3 ... ok
- uniform filter 4 ... ok
- uniform filter 5 ... ok
- uniform filter 6 ... ok
- variance 1 ... Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- ok
- variance 2 ... ok
- variance 3 ... ok
- variance 4 ... ok
- variance 5 ... ok
- variance 6 ... ok
- watershed_ift 1 ... ok
- watershed_ift 2 ... ok
- watershed_ift 3 ... ok
- watershed_ift 4 ... ok
- watershed_ift 5 ... ok
- watershed_ift 6 ... ok
- watershed_ift 7 ... ok
- white tophat 1 ... ok
- white tophat 2 ... ok
- zoom 1 ... ok
- zoom 2 ... ok
- zoom by affine transformation 1 ... ok
- Regression test for #413: median_filter does not handle bytes orders. ... ok
- Ticket #643 ... ok
- test_explicit (test_odr.TestODR) ... ok
- test_implicit (test_odr.TestODR) ... ok
- test_lorentz (test_odr.TestODR) ... ok
- test_multi (test_odr.TestODR) ... ok
- test_pearson (test_odr.TestODR) ... ok
- test_simple (test_cobyla.TestCobyla) ... ok
- test_one_argument (test_minpack.TestCurveFit) ... ok
- test_two_argument (test_minpack.TestCurveFit) ... ok
- fsolve without gradient, equal pipes -> equal flows ... ok
- fsolve with gradient, equal pipes -> equal flows ... ok
- test_basic (test_minpack.TestLeastSq) ... ok
- test_full_output (test_minpack.TestLeastSq) ... ok
- test_input_untouched (test_minpack.TestLeastSq) ... ok
- test_nnls (test_nnls.TestNNLS) ... ok
- test_anderson (test_nonlin.TestNonlin) ... ok
- test_anderson2 (test_nonlin.TestNonlin) ... ok
- test_broyden1 (test_nonlin.TestNonlin) ... ok
- test_broyden1modified (test_nonlin.TestNonlin) ... ok
- test_broyden2 (test_nonlin.TestNonlin) ... ok
- test_broyden3 (test_nonlin.TestNonlin) ... ok
- test_broydengeneralized (test_nonlin.TestNonlin) ... ok
- test_exciting (test_nonlin.TestNonlin) ... ok
- test_linearmixing (test_nonlin.TestNonlin) ... ok
- test_vackar (test_nonlin.TestNonlin) ... ok
- Broyden-Fletcher-Goldfarb-Shanno optimization routine ... ok
- brent algorithm ... ok
- conjugate gradient optimization routine ... ok
- Test fminbound ... ok
- test_fminbound_scalar (test_optimize.TestOptimize) ... ok
- limited-memory bound-constrained BFGS algorithm ... ok
- line-search Newton conjugate gradient optimization routine ... FAIL
- Nelder-Mead simplex algorithm ... ok
- Powell (direction set) optimization routine ... ok
- test_tnc (test_optimize.TestTnc) ... ok
- Ticket #1214 ... ok
- Ticket #1074 ... ok
- test_bound_approximated (test_slsqp.TestSLSQP) ... ok
- test_bound_equality_given (test_slsqp.TestSLSQP) ... ok
- test_bound_equality_inequality_given (test_slsqp.TestSLSQP) ... ok
- test_unbounded_approximated (test_slsqp.TestSLSQP) ... ok
- test_unbounded_given (test_slsqp.TestSLSQP) ... ok
- test_bisect (test_zeros.TestBasic) ... ok
- test_brenth (test_zeros.TestBasic) ... ok
- test_brentq (test_zeros.TestBasic) ... ok
- test_deriv_zero_warning (test_zeros.TestBasic) ... ok
- test_ridder (test_zeros.TestBasic) ... ok
- test_lowpass (test_filter_design.TestFirWin) ... Warning: invalid value encountered in divide
- ok
- test_hilbert (test_filter_design.TestRemez) ... ok
- Regression test for #651: better handling of badly conditioned ... ok
- test_simple (test_filter_design.TestTf2zpk) ... ok
- test_ltisys.TestSS2TF.test_basic(3, 3, 3) ... ok
- test_ltisys.TestSS2TF.test_basic(1, 3, 3) ... ok
- test_ltisys.TestSS2TF.test_basic(1, 1, 1) ... ok
- test_ltisys.Test_impulse2.test_01 ... ok
- Specify the desired time values for the output. ... ok
- Specify an initial condition as a scalar. ... ok
- Specify an initial condition as a list. ... ok
- test_ltisys.Test_impulse2.test_05 ... ok
- test_ltisys.Test_impulse2.test_06 ... ok
- test_ltisys.Test_lsim2.test_01 ... ok
- test_ltisys.Test_lsim2.test_02 ... ok
- test_ltisys.Test_lsim2.test_03 ... ok
- test_ltisys.Test_lsim2.test_04 ... ok
- test_ltisys.Test_lsim2.test_05 ... /usr/lib/python2.6/site-packages/scipy/signal/filter_design.py:247: BadCoefficients: Badly conditioned filter coefficients (numerator): the results may be meaningless
- "results may be meaningless", BadCoefficients)
- ok
- Test use of the default values of the arguments `T` and `U`. ... ok
- test_ltisys.Test_step2.test_01 ... ok
- Specify the desired time values for the output. ... ok
- Specify an initial condition as a scalar. ... ok
- Specify an initial condition as a list. ... ok
- test_ltisys.Test_step2.test_05 ... ok
- test_ltisys.Test_step2.test_06 ... ok
- test_2d_arrays (test_signaltools.OldTestConvolve) ... ok
- test_basic (test_signaltools.OldTestConvolve) ... ok
- test_complex (test_signaltools.OldTestConvolve) ... ok
- test_same_mode (test_signaltools.OldTestConvolve) ... ok
- test_valid_mode (test_signaltools.OldTestConvolve) ... ok
- test_zero_order (test_signaltools.OldTestConvolve) ... ok
- test_2d_arrays (test_signaltools.OldTestConvolve2d) ... ok
- test_fillvalue (test_signaltools.OldTestConvolve2d) ... ok
- test_same_mode (test_signaltools.OldTestConvolve2d) ... ok
- test_sym_boundary (test_signaltools.OldTestConvolve2d) ... ok
- test_valid_mode (test_signaltools.OldTestConvolve2d) ... ok
- test_valid_mode2 (test_signaltools.OldTestConvolve2d) ... ok
- test_wrap_boundary (test_signaltools.OldTestConvolve2d) ... ok
- test_basic (test_signaltools.TestCSpline1DEval) ... ok
- test_2d_arrays (test_signaltools.TestConvolve) ... ok
- test_basic (test_signaltools.TestConvolve) ... ok
- test_complex (test_signaltools.TestConvolve) ... ok
- test_same_mode (test_signaltools.TestConvolve) ... ok
- test_valid_mode (test_signaltools.TestConvolve) ... ok
- test_zero_order (test_signaltools.TestConvolve) ... ok
- test_rank1_full (test_signaltools.TestCorrelateComplex128) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateComplex128) ... ok
- test_rank1_same (test_signaltools.TestCorrelateComplex128) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateComplex128) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateComplex128) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateComplex128) ... ok
- test_rank3 (test_signaltools.TestCorrelateComplex128) ... ok
- test_rank3_old (test_signaltools.TestCorrelateComplex128) ... ok
- test_rank1_full (test_signaltools.TestCorrelateComplex192) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateComplex192) ... ok
- test_rank1_same (test_signaltools.TestCorrelateComplex192) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateComplex192) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateComplex192) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateComplex192) ... ok
- test_rank3 (test_signaltools.TestCorrelateComplex192) ... ok
- test_rank3_old (test_signaltools.TestCorrelateComplex192) ... ok
- test_rank1_full (test_signaltools.TestCorrelateComplex64) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateComplex64) ... ok
- test_rank1_same (test_signaltools.TestCorrelateComplex64) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateComplex64) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateComplex64) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateComplex64) ... ok
- test_rank3 (test_signaltools.TestCorrelateComplex64) ... ok
- test_rank3_old (test_signaltools.TestCorrelateComplex64) ... ok
- test_rank1_full (test_signaltools.TestCorrelateDecimal) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateDecimal) ... ok
- test_rank1_same (test_signaltools.TestCorrelateDecimal) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateDecimal) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateDecimal) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateDecimal) ... ok
- test_rank3_all (test_signaltools.TestCorrelateDecimal) ... ok
- test_rank3_all_old (test_signaltools.TestCorrelateDecimal) ... ok
- test_rank3_same (test_signaltools.TestCorrelateDecimal) ... ok
- test_rank3_same_old (test_signaltools.TestCorrelateDecimal) ... ok
- test_rank3_valid (test_signaltools.TestCorrelateDecimal) ... ok
- test_rank3_valid_old (test_signaltools.TestCorrelateDecimal) ... ok
- test_rank1_full (test_signaltools.TestCorrelateFloat32) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateFloat32) ... ok
- test_rank1_same (test_signaltools.TestCorrelateFloat32) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateFloat32) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateFloat32) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateFloat32) ... ok
- test_rank3_all (test_signaltools.TestCorrelateFloat32) ... ok
- test_rank3_all_old (test_signaltools.TestCorrelateFloat32) ... ok
- test_rank3_same (test_signaltools.TestCorrelateFloat32) ... ok
- test_rank3_same_old (test_signaltools.TestCorrelateFloat32) ... ok
- test_rank3_valid (test_signaltools.TestCorrelateFloat32) ... ok
- test_rank3_valid_old (test_signaltools.TestCorrelateFloat32) ... ok
- test_rank1_full (test_signaltools.TestCorrelateFloat64) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateFloat64) ... ok
- test_rank1_same (test_signaltools.TestCorrelateFloat64) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateFloat64) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateFloat64) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateFloat64) ... ok
- test_rank3_all (test_signaltools.TestCorrelateFloat64) ... ok
- test_rank3_all_old (test_signaltools.TestCorrelateFloat64) ... ok
- test_rank3_same (test_signaltools.TestCorrelateFloat64) ... ok
- test_rank3_same_old (test_signaltools.TestCorrelateFloat64) ... ok
- test_rank3_valid (test_signaltools.TestCorrelateFloat64) ... ok
- test_rank3_valid_old (test_signaltools.TestCorrelateFloat64) ... ok
- test_rank1_full (test_signaltools.TestCorrelateFloat96) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateFloat96) ... ok
- test_rank1_same (test_signaltools.TestCorrelateFloat96) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateFloat96) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateFloat96) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateFloat96) ... ok
- test_rank3_all (test_signaltools.TestCorrelateFloat96) ... ok
- test_rank3_all_old (test_signaltools.TestCorrelateFloat96) ... ok
- test_rank3_same (test_signaltools.TestCorrelateFloat96) ... ok
- test_rank3_same_old (test_signaltools.TestCorrelateFloat96) ... ok
- test_rank3_valid (test_signaltools.TestCorrelateFloat96) ... ok
- test_rank3_valid_old (test_signaltools.TestCorrelateFloat96) ... ok
- test_rank1_full (test_signaltools.TestCorrelateInt) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateInt) ... ok
- test_rank1_same (test_signaltools.TestCorrelateInt) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateInt) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateInt) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateInt) ... ok
- test_rank3_all (test_signaltools.TestCorrelateInt) ... ok
- test_rank3_all_old (test_signaltools.TestCorrelateInt) ... ok
- test_rank3_same (test_signaltools.TestCorrelateInt) ... ok
- test_rank3_same_old (test_signaltools.TestCorrelateInt) ... ok
- test_rank3_valid (test_signaltools.TestCorrelateInt) ... ok
- test_rank3_valid_old (test_signaltools.TestCorrelateInt) ... ok
- test_rank1_full (test_signaltools.TestCorrelateInt16) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateInt16) ... ok
- test_rank1_same (test_signaltools.TestCorrelateInt16) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateInt16) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateInt16) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateInt16) ... ok
- test_rank3_all (test_signaltools.TestCorrelateInt16) ... ok
- test_rank3_all_old (test_signaltools.TestCorrelateInt16) ... ok
- test_rank3_same (test_signaltools.TestCorrelateInt16) ... ok
- test_rank3_same_old (test_signaltools.TestCorrelateInt16) ... ok
- test_rank3_valid (test_signaltools.TestCorrelateInt16) ... ok
- test_rank3_valid_old (test_signaltools.TestCorrelateInt16) ... ok
- test_rank1_full (test_signaltools.TestCorrelateInt8) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateInt8) ... ok
- test_rank1_same (test_signaltools.TestCorrelateInt8) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateInt8) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateInt8) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateInt8) ... ok
- test_rank3_all (test_signaltools.TestCorrelateInt8) ... ok
- test_rank3_all_old (test_signaltools.TestCorrelateInt8) ... ok
- test_rank3_same (test_signaltools.TestCorrelateInt8) ... ok
- test_rank3_same_old (test_signaltools.TestCorrelateInt8) ... ok
- test_rank3_valid (test_signaltools.TestCorrelateInt8) ... ok
- test_rank3_valid_old (test_signaltools.TestCorrelateInt8) ... ok
- test_rank1_full (test_signaltools.TestCorrelateUint16) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateUint16) ... ok
- test_rank1_same (test_signaltools.TestCorrelateUint16) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateUint16) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateUint16) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateUint16) ... ok
- test_rank3_all (test_signaltools.TestCorrelateUint16) ... ok
- test_rank3_all_old (test_signaltools.TestCorrelateUint16) ... ok
- test_rank3_same (test_signaltools.TestCorrelateUint16) ... ok
- test_rank3_same_old (test_signaltools.TestCorrelateUint16) ... ok
- test_rank3_valid (test_signaltools.TestCorrelateUint16) ... ok
- test_rank3_valid_old (test_signaltools.TestCorrelateUint16) ... ok
- test_rank1_full (test_signaltools.TestCorrelateUint32) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateUint32) ... ok
- test_rank1_same (test_signaltools.TestCorrelateUint32) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateUint32) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateUint32) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateUint32) ... ok
- test_rank3_all (test_signaltools.TestCorrelateUint32) ... ok
- test_rank3_all_old (test_signaltools.TestCorrelateUint32) ... ok
- test_rank3_same (test_signaltools.TestCorrelateUint32) ... ok
- test_rank3_same_old (test_signaltools.TestCorrelateUint32) ... ok
- test_rank3_valid (test_signaltools.TestCorrelateUint32) ... ok
- test_rank3_valid_old (test_signaltools.TestCorrelateUint32) ... ok
- test_rank1_full (test_signaltools.TestCorrelateUint64) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateUint64) ... ok
- test_rank1_same (test_signaltools.TestCorrelateUint64) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateUint64) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateUint64) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateUint64) ... ok
- test_rank3_all (test_signaltools.TestCorrelateUint64) ... ok
- test_rank3_all_old (test_signaltools.TestCorrelateUint64) ... ok
- test_rank3_same (test_signaltools.TestCorrelateUint64) ... ok
- test_rank3_same_old (test_signaltools.TestCorrelateUint64) ... ok
- test_rank3_valid (test_signaltools.TestCorrelateUint64) ... ok
- test_rank3_valid_old (test_signaltools.TestCorrelateUint64) ... ok
- test_rank1_full (test_signaltools.TestCorrelateUint8) ... ok
- test_rank1_full_old (test_signaltools.TestCorrelateUint8) ... ok
- test_rank1_same (test_signaltools.TestCorrelateUint8) ... ok
- test_rank1_same_old (test_signaltools.TestCorrelateUint8) ... ok
- test_rank1_valid (test_signaltools.TestCorrelateUint8) ... ok
- test_rank1_valid_old (test_signaltools.TestCorrelateUint8) ... ok
- test_rank3_all (test_signaltools.TestCorrelateUint8) ... ok
- test_rank3_all_old (test_signaltools.TestCorrelateUint8) ... ok
- test_rank3_same (test_signaltools.TestCorrelateUint8) ... ok
- test_rank3_same_old (test_signaltools.TestCorrelateUint8) ... ok
- test_rank3_valid (test_signaltools.TestCorrelateUint8) ... ok
- test_rank3_valid_old (test_signaltools.TestCorrelateUint8) ... ok
- test_signaltools.TestDecimate.test_basic ... ok
- test_2d_complex_same (test_signaltools.TestFFTConvolve) ... ok
- test_2d_real_same (test_signaltools.TestFFTConvolve) ... ok
- test_complex (test_signaltools.TestFFTConvolve) ... ok
- test_random_data (test_signaltools.TestFFTConvolve) ... ok
- test_real (test_signaltools.TestFFTConvolve) ... ok
- test_real_same_mode (test_signaltools.TestFFTConvolve) ... ok
- test_real_valid_mode (test_signaltools.TestFFTConvolve) ... ok
- test_zero_order (test_signaltools.TestFFTConvolve) ... ok
- test_signaltools.TestFiltFilt.test_basic ... ok
- test_signaltools.TestHilbert.test_hilbert_axisN(array([[ 0.+2.30940108j, 6.+2.30940108j, 12.+2.30940108j], ... ok
- test_signaltools.TestHilbert.test_hilbert_axisN(array([ 0.+2.30940108j, 1.-1.15470054j, 2.-1.15470054j, 3.-1.15470054j, ... ok
- test_signaltools.TestHilbert.test_hilbert_axisN((3, 20), [3, 20]) ... ok
- test_signaltools.TestHilbert.test_hilbert_axisN((20, 3), [20, 3]) ... ok
- test_signaltools.TestHilbert.test_hilbert_axisN(array([ 4.44089210e-17-1.7201583j , 1.00000000e+00-2.04779451j, ... ok
- test_signaltools.TestHilbert.test_hilbert_theoretical ... ok
- Regression test for #880: empty array for zi crashes. ... ok
- test_rank1 (test_signaltools.TestLinearFilterComplex128) ... ok
- test_rank2 (test_signaltools.TestLinearFilterComplex128) ... ok
- test_rank2_init_cond_a0 (test_signaltools.TestLinearFilterComplex128) ... ok
- test_rank2_init_cond_a1 (test_signaltools.TestLinearFilterComplex128) ... ok
- test_rank3 (test_signaltools.TestLinearFilterComplex128) ... ok
- Regression test for #880: empty array for zi crashes. ... ok
- test_rank1 (test_signaltools.TestLinearFilterComplex64) ... ok
- test_rank2 (test_signaltools.TestLinearFilterComplex64) ... ok
- test_rank2_init_cond_a0 (test_signaltools.TestLinearFilterComplex64) ... ok
- test_rank2_init_cond_a1 (test_signaltools.TestLinearFilterComplex64) ... ok
- test_rank3 (test_signaltools.TestLinearFilterComplex64) ... ok
- Regression test for #880: empty array for zi crashes. ... ok
- test_rank1 (test_signaltools.TestLinearFilterComplexxxiExtended28) ... ok
- test_rank2 (test_signaltools.TestLinearFilterComplexxxiExtended28) ... ok
- test_rank2_init_cond_a0 (test_signaltools.TestLinearFilterComplexxxiExtended28) ... ok
- test_rank2_init_cond_a1 (test_signaltools.TestLinearFilterComplexxxiExtended28) ... ok
- test_rank3 (test_signaltools.TestLinearFilterComplexxxiExtended28) ... ok
- Regression test for #880: empty array for zi crashes. ... ok
- test_rank1 (test_signaltools.TestLinearFilterDecimal) ... ok
- test_rank2 (test_signaltools.TestLinearFilterDecimal) ... ok
- test_rank2_init_cond_a0 (test_signaltools.TestLinearFilterDecimal) ... ok
- test_rank2_init_cond_a1 (test_signaltools.TestLinearFilterDecimal) ... ok
- test_rank3 (test_signaltools.TestLinearFilterDecimal) ... ok
- Regression test for #880: empty array for zi crashes. ... ok
- test_rank1 (test_signaltools.TestLinearFilterFloat32) ... ok
- test_rank2 (test_signaltools.TestLinearFilterFloat32) ... ok
- test_rank2_init_cond_a0 (test_signaltools.TestLinearFilterFloat32) ... ok
- test_rank2_init_cond_a1 (test_signaltools.TestLinearFilterFloat32) ... ok
- test_rank3 (test_signaltools.TestLinearFilterFloat32) ... ok
- Regression test for #880: empty array for zi crashes. ... ok
- test_rank1 (test_signaltools.TestLinearFilterFloat64) ... ok
- test_rank2 (test_signaltools.TestLinearFilterFloat64) ... ok
- test_rank2_init_cond_a0 (test_signaltools.TestLinearFilterFloat64) ... ok
- test_rank2_init_cond_a1 (test_signaltools.TestLinearFilterFloat64) ... ok
- test_rank3 (test_signaltools.TestLinearFilterFloat64) ... ok
- Regression test for #880: empty array for zi crashes. ... ok
- test_rank1 (test_signaltools.TestLinearFilterFloatExtended) ... ok
- test_rank2 (test_signaltools.TestLinearFilterFloatExtended) ... ok
- test_rank2_init_cond_a0 (test_signaltools.TestLinearFilterFloatExtended) ... ok
- test_rank2_init_cond_a1 (test_signaltools.TestLinearFilterFloatExtended) ... ok
- test_rank3 (test_signaltools.TestLinearFilterFloatExtended) ... ok
- test_basic (test_signaltools.TestMedFilt) ... ok
- Ticket #1124. Ensure this does not segfault. ... ok
- test_basic (test_signaltools.TestOrderFilt) ... ok
- test_basic (test_signaltools.TestWiener) ... ok
- test_hyperbolic_at_zero (test_waveforms.TestChirp) ... ok
- test_hyperbolic_freq_01 (test_waveforms.TestChirp) ... ok
- test_hyperbolic_freq_02 (test_waveforms.TestChirp) ... ok
- test_hyperbolic_freq_03 (test_waveforms.TestChirp) ... ok
- test_integer_all (test_waveforms.TestChirp) ... ok
- test_integer_f0 (test_waveforms.TestChirp) ... ok
- test_integer_f1 (test_waveforms.TestChirp) ... ok
- test_integer_t1 (test_waveforms.TestChirp) ... ok
- test_linear_at_zero (test_waveforms.TestChirp) ... ok
- test_linear_freq_01 (test_waveforms.TestChirp) ... ok
- test_linear_freq_02 (test_waveforms.TestChirp) ... ok
- test_logarithmic_at_zero (test_waveforms.TestChirp) ... ok
- test_logarithmic_freq_01 (test_waveforms.TestChirp) ... ok
- test_logarithmic_freq_02 (test_waveforms.TestChirp) ... ok
- test_logarithmic_freq_03 (test_waveforms.TestChirp) ... ok
- test_quadratic_at_zero (test_waveforms.TestChirp) ... ok
- test_quadratic_at_zero2 (test_waveforms.TestChirp) ... ok
- test_quadratic_freq_01 (test_waveforms.TestChirp) ... ok
- test_quadratic_freq_02 (test_waveforms.TestChirp) ... ok
- test_unknown_method (test_waveforms.TestChirp) ... ok
- test_integer_bw (test_waveforms.TestGaussPulse) ... ok
- test_integer_bwr (test_waveforms.TestGaussPulse) ... ok
- test_integer_fc (test_waveforms.TestGaussPulse) ... ok
- test_integer_tpr (test_waveforms.TestGaussPulse) ... ok
- test_sweep_poly_const (test_waveforms.TestSweepPoly) ... ok
- test_sweep_poly_cubic (test_waveforms.TestSweepPoly) ... ok
- Use an array of coefficients instead of a poly1d. ... ok
- Use a list of coefficients instead of a poly1d. ... ok
- test_sweep_poly_linear (test_waveforms.TestSweepPoly) ... ok
- test_sweep_poly_quad1 (test_waveforms.TestSweepPoly) ... ok
- test_sweep_poly_quad2 (test_waveforms.TestSweepPoly) ... ok
- test_cascade (test_wavelets.TestWavelets) ... ok
- test_daub (test_wavelets.TestWavelets) ... ok
- test_morlet (test_wavelets.TestWavelets) ... ok
- test_qmf (test_wavelets.TestWavelets) ... ok
- test_windows.TestChebWin.test_cheb_even ... ok
- test_windows.TestChebWin.test_cheb_odd ... ok
- test_windows.TestGetWindow.test_boxcar ... ok
- test_windows.TestGetWindow.test_cheb_even ... ok
- test_windows.TestGetWindow.test_cheb_odd ... ok
- Getting factors of complex matrix ... SKIP: Skipping test: test_complex_lu
- UMFPACK appears not to be compiled
- Getting factors of real matrix ... SKIP: Skipping test: test_real_lu
- UMFPACK appears not to be compiled
- Getting factors of complex matrix ... SKIP: Skipping test: test_complex_lu
- UMFPACK appears not to be compiled
- Getting factors of real matrix ... SKIP: Skipping test: test_real_lu
- UMFPACK appears not to be compiled
- Prefactorize (with UMFPACK) matrix for solving with multiple rhs ... SKIP: Skipping test: test_factorized_umfpack
- UMFPACK appears not to be compiled
- Prefactorize matrix for solving with multiple rhs ... SKIP: Skipping test: test_factorized_without_umfpack
- UMFPACK appears not to be compiled
- Solve with UMFPACK: double precision complex ... SKIP: Skipping test: test_solve_complex_umfpack
- UMFPACK appears not to be compiled
- Solve: single precision complex ... SKIP: Skipping test: test_solve_complex_without_umfpack
- UMFPACK appears not to be compiled
- Solve with UMFPACK: double precision, sparse rhs ... SKIP: Skipping test: test_solve_sparse_rhs
- UMFPACK appears not to be compiled
- Solve with UMFPACK: double precision ... SKIP: Skipping test: test_solve_umfpack
- UMFPACK appears not to be compiled
- Solve: single precision ... SKIP: Skipping test: test_solve_without_umfpack
- UMFPACK appears not to be compiled
- test_singular (test_linsolve.TestLinsolve) ... ok
- test_smoketest (test_linsolve.TestLinsolve) ... ok
- test_twodiags (test_linsolve.TestLinsolve) ... ok
- test_linsolve.TestSplu.test_lu_refcount ... ok
- test_linsolve.TestSplu.test_spilu_nnz0 ... ok
- test_linsolve.TestSplu.test_spilu_smoketest ... ok
- test_linsolve.TestSplu.test_splu_basic ... ok
- test_linsolve.TestSplu.test_splu_nnz0 ... ok
- test_linsolve.TestSplu.test_splu_perm ... ok
- test_linsolve.TestSplu.test_splu_smoketest ... ok
- test_complex_nonsymmetric_modes (test_arpack.TestEigenComplexNonSymmetric) ... ok
- test_complex_symmetric_modes (test_arpack.TestEigenComplexSymmetric) ... ok
- test_nonsymmetric_modes (test_arpack.TestEigenNonSymmetric) ... ok
- test_starting_vector (test_arpack.TestEigenNonSymmetric) ... ok
- test_starting_vector (test_arpack.TestEigenSymmetric) ... ok
- test_symmetric_modes (test_arpack.TestEigenSymmetric) ... ok
- test_simple_complex (test_arpack.TestSparseSvd) ... KNOWNFAIL: Complex sparse SVD not implemented (depends on Hermitian support in eigen_symmetric
- test_simple_real (test_arpack.TestSparseSvd) ... ok
- test (test_speigs.TestEigs) ... ok
- test_lobpcg.test_Small ... ok
- test_lobpcg.test_ElasticRod ... ok
- test_lobpcg.test_MikotaPair ... ok
- test_callback (test_iterative.TestGMRES) ... ok
- test whether all methods converge ... ok
- test whether maxiter is respected ... ok
- test whether all methods accept a trivial preconditioner ... ok
- Check that QMR works with left and right preconditioners ... ok
- test_outer_v (test_lgmres.TestLGMRES) ... ok
- test_preconditioner (test_lgmres.TestLGMRES) ... ok
- test_lsqr.test_basic ... ok
- test_basic (test_interface.TestAsLinearOperator) ... ok
- test_matvec (test_interface.TestLinearOperator) ... ok
- test_iterative.test_gmres_basic ... ok
- test_abs (test_base.TestBSR) ... ok
- test_add (test_base.TestBSR) ... ok
- adding a dense matrix to a sparse matrix ... ok
- test_add_sub (test_base.TestBSR) ... ok
- test_asfptype (test_base.TestBSR) ... ok
- test_astype (test_base.TestBSR) ... ok
- test_bsr_matvec (test_base.TestBSR) ... ok
- test_bsr_matvecs (test_base.TestBSR) ... ok
- check native BSR format constructor ... ok
- construct from dense ... ok
- Check whether the copy=True and copy=False keywords work ... ok
- Does the matrix's .diagonal() method work? ... ok
- test_elementwise_divide (test_base.TestBSR) ... ok
- test_elementwise_multiply (test_base.TestBSR) ... ok
- test_eliminate_zeros (test_base.TestBSR) ... ok
- create empty matrices ... ok
- Test manipulating empty matrices. Fails in SciPy SVN <= r1768 ... ok
- test_from_array (test_base.TestBSR) ... ok
- test_from_list (test_base.TestBSR) ... ok
- test_from_matrix (test_base.TestBSR) ... ok
- test_from_sparse (test_base.TestBSR) ... ok
- test_getcol (test_base.TestBSR) ... ok
- test_getrow (test_base.TestBSR) ... ok
- test_idiv_scalar (test_base.TestBSR) ... ok
- test_imag (test_base.TestBSR) ... ok
- test_imul_scalar (test_base.TestBSR) ... ok
- test_invalid_shapes (test_base.TestBSR) ... ok
- test_matmat_dense (test_base.TestBSR) ... ok
- test_matmat_sparse (test_base.TestBSR) ... ok
- test_matvec (test_base.TestBSR) ... ok
- Does the matrix's .mean(axis=...) method work? ... ok
- test_mu (test_base.TestBSR) ... ok
- test_mul_scalar (test_base.TestBSR) ... ok
- test_neg (test_base.TestBSR) ... ok
- test_nonzero (test_base.TestBSR) ... ok
- test_pow (test_base.TestBSR) ... ok
- test_radd (test_base.TestBSR) ... ok
- test_real (test_base.TestBSR) ... ok
- test_repr (test_base.TestBSR) ... ok
- test_rmatvec (test_base.TestBSR) ... ok
- test_rmul_scalar (test_base.TestBSR) ... ok
- test_rsub (test_base.TestBSR) ... ok
- test that A*x works for x with shape () (1,) and (1,1) ... ok
- test_sparse_format_conversions (test_base.TestBSR) ... ok
- test_str (test_base.TestBSR) ... ok
- test_sub (test_base.TestBSR) ... ok
- subtracting a dense matrix to/from a sparse matrix ... ok
- Does the matrix's .sum(axis=...) method work? ... ok
- test_toarray (test_base.TestBSR) ... ok
- test_tobsr (test_base.TestBSR) ... ok
- test_todense (test_base.TestBSR) ... ok
- test_transpose (test_base.TestBSR) ... ok
- test_abs (test_base.TestCOO) ... ok
- test_add (test_base.TestCOO) ... ok
- adding a dense matrix to a sparse matrix ... ok
- test_asfptype (test_base.TestCOO) ... ok
- test_astype (test_base.TestCOO) ... ok
- unsorted triplet format ... ok
- unsorted triplet format with duplicates (which are summed) ... ok
- empty matrix ... ok
- from dense matrix ... ok
- Check whether the copy=True and copy=False keywords work ... ok
- Does the matrix's .diagonal() method work? ... ok
- test_elementwise_divide (test_base.TestCOO) ... ok
- test_elementwise_multiply (test_base.TestCOO) ... ok
- create empty matrices ... ok
- Test manipulating empty matrices. Fails in SciPy SVN <= r1768 ... ok
- test_from_array (test_base.TestCOO) ... ok
- test_from_list (test_base.TestCOO) ... ok
- test_from_matrix (test_base.TestCOO) ... ok
- test_from_sparse (test_base.TestCOO) ... ok
- test_getcol (test_base.TestCOO) ... ok
- test_getrow (test_base.TestCOO) ... ok
- test_imag (test_base.TestCOO) ... ok
- test_invalid_shapes (test_base.TestCOO) ... ok
- test_matmat_dense (test_base.TestCOO) ... ok
- test_matmat_sparse (test_base.TestCOO) ... ok
- test_matvec (test_base.TestCOO) ... ok
- Does the matrix's .mean(axis=...) method work? ... ok
- test_mul_scalar (test_base.TestCOO) ... ok
- test_neg (test_base.TestCOO) ... ok
- test_nonzero (test_base.TestCOO) ... ok
- test_pow (test_base.TestCOO) ... ok
- test_radd (test_base.TestCOO) ... ok
- test_real (test_base.TestCOO) ... ok
- test_repr (test_base.TestCOO) ... ok
- test_rmatvec (test_base.TestCOO) ... ok
- test_rmul_scalar (test_base.TestCOO) ... ok
- test_rsub (test_base.TestCOO) ... ok
- test that A*x works for x with shape () (1,) and (1,1) ... ok
- test_sparse_format_conversions (test_base.TestCOO) ... ok
- test_str (test_base.TestCOO) ... ok
- test_sub (test_base.TestCOO) ... ok
- subtracting a dense matrix to/from a sparse matrix ... ok
- Does the matrix's .sum(axis=...) method work? ... ok
- test_toarray (test_base.TestCOO) ... ok
- test_tobsr (test_base.TestCOO) ... ok
- test_todense (test_base.TestCOO) ... ok
- test_transpose (test_base.TestCOO) ... ok
- test_abs (test_base.TestCSC) ... ok
- test_add (test_base.TestCSC) ... ok
- adding a dense matrix to a sparse matrix ... ok
- test_add_sub (test_base.TestCSC) ... ok
- test_asfptype (test_base.TestCSC) ... ok
- test_astype (test_base.TestCSC) ... ok
- test_constructor1 (test_base.TestCSC) ... ok
- test_constructor2 (test_base.TestCSC) ... ok
- test_constructor3 (test_base.TestCSC) ... ok
- using (data, ij) format ... ok
- infer dimensions from arrays ... ok
- Check whether the copy=True and copy=False keywords work ... ok
- Does the matrix's .diagonal() method work? ... ok
- test_elementwise_divide (test_base.TestCSC) ... ok
- test_elementwise_multiply (test_base.TestCSC) ... ok
- test_eliminate_zeros (test_base.TestCSC) ... ok
- create empty matrices ... ok
- Test manipulating empty matrices. Fails in SciPy SVN <= r1768 ... ok
- test_fancy_indexing (test_base.TestCSC) ... ok
- test_fancy_indexing_randomized (test_base.TestCSC) ... ok
- test_fancy_indexing_set (test_base.TestCSC) ... KNOWNFAIL: Fancy indexing is known to be broken for CSC matrices
- test_from_array (test_base.TestCSC) ... ok
- test_from_list (test_base.TestCSC) ... ok
- test_from_matrix (test_base.TestCSC) ... ok
- test_from_sparse (test_base.TestCSC) ... ok
- Test for new slice functionality (EJS) ... ok
- test_get_slices (test_base.TestCSC) ... ok
- Test for new slice functionality (EJS) ... ok
- test_getcol (test_base.TestCSC) ... ok
- test_getelement (test_base.TestCSC) ... ok
- test_getrow (test_base.TestCSC) ... ok
- test_idiv_scalar (test_base.TestCSC) ... ok
- test_imag (test_base.TestCSC) ... ok
- test_imul_scalar (test_base.TestCSC) ... ok
- test_invalid_shapes (test_base.TestCSC) ... ok
- test_matmat_dense (test_base.TestCSC) ... ok
- test_matmat_sparse (test_base.TestCSC) ... ok
- test_matvec (test_base.TestCSC) ... ok
- Does the matrix's .mean(axis=...) method work? ... ok
- test_mu (test_base.TestCSC) ... ok
- test_mul_scalar (test_base.TestCSC) ... ok
- test_neg (test_base.TestCSC) ... ok
- test_nonzero (test_base.TestCSC) ... ok
- test_pow (test_base.TestCSC) ... ok
- test_radd (test_base.TestCSC) ... ok
- test_real (test_base.TestCSC) ... ok
- test_repr (test_base.TestCSC) ... ok
- test_rmatvec (test_base.TestCSC) ... ok
- test_rmul_scalar (test_base.TestCSC) ... ok
- test_rsub (test_base.TestCSC) ... ok
- test_setelement (test_base.TestCSC) ... ok
- test that A*x works for x with shape () (1,) and (1,1) ... ok
- Test whether the lu_solve command segfaults, as reported by Nils ... ok
- test_sort_indices (test_base.TestCSC) ... ok
- test_sparse_format_conversions (test_base.TestCSC) ... ok
- test_str (test_base.TestCSC) ... ok
- test_sub (test_base.TestCSC) ... ok
- subtracting a dense matrix to/from a sparse matrix ... ok
- Does the matrix's .sum(axis=...) method work? ... ok
- test_toarray (test_base.TestCSC) ... ok
- test_tobsr (test_base.TestCSC) ... ok
- test_todense (test_base.TestCSC) ... ok
- test_transpose (test_base.TestCSC) ... ok
- test_unsorted_arithmetic (test_base.TestCSC) ... ok
- test_abs (test_base.TestCSR) ... ok
- test_add (test_base.TestCSR) ... ok
- adding a dense matrix to a sparse matrix ... ok
- test_add_sub (test_base.TestCSR) ... ok
- test_asfptype (test_base.TestCSR) ... ok
- test_astype (test_base.TestCSR) ... ok
- test_constructor1 (test_base.TestCSR) ... ok
- test_constructor2 (test_base.TestCSR) ... ok
- test_constructor3 (test_base.TestCSR) ... ok
- using (data, ij) format ... ok
- infer dimensions from arrays ... ok
- Check whether the copy=True and copy=False keywords work ... ok
- Does the matrix's .diagonal() method work? ... ok
- test_elementwise_divide (test_base.TestCSR) ... ok
- test_elementwise_multiply (test_base.TestCSR) ... ok
- test_eliminate_zeros (test_base.TestCSR) ... ok
- create empty matrices ... ok
- Test manipulating empty matrices. Fails in SciPy SVN <= r1768 ... ok
- test_fancy_indexing (test_base.TestCSR) ... ok
- test_fancy_indexing_randomized (test_base.TestCSR) ... ok
- test_fancy_indexing_set (test_base.TestCSR) ... KNOWNFAIL: Fancy indexing is known to be broken for CSR matrices
- test_from_array (test_base.TestCSR) ... ok
- test_from_list (test_base.TestCSR) ... ok
- test_from_matrix (test_base.TestCSR) ... ok
- test_from_sparse (test_base.TestCSR) ... ok
- Test for new slice functionality (EJS) ... ok
- test_get_slices (test_base.TestCSR) ... ok
- Test for new slice functionality (EJS) ... ok
- test_getcol (test_base.TestCSR) ... ok
- test_getelement (test_base.TestCSR) ... ok
- test_getrow (test_base.TestCSR) ... ok
- test_idiv_scalar (test_base.TestCSR) ... ok
- test_imag (test_base.TestCSR) ... ok
- test_imul_scalar (test_base.TestCSR) ... ok
- test_invalid_shapes (test_base.TestCSR) ... ok
- test_matmat_dense (test_base.TestCSR) ... ok
- test_matmat_sparse (test_base.TestCSR) ... ok
- test_matvec (test_base.TestCSR) ... ok
- Does the matrix's .mean(axis=...) method work? ... ok
- test_mu (test_base.TestCSR) ... ok
- test_mul_scalar (test_base.TestCSR) ... ok
- test_neg (test_base.TestCSR) ... ok
- test_nonzero (test_base.TestCSR) ... ok
- test_pow (test_base.TestCSR) ... ok
- test_radd (test_base.TestCSR) ... ok
- test_real (test_base.TestCSR) ... ok
- test_repr (test_base.TestCSR) ... ok
- test_rmatvec (test_base.TestCSR) ... ok
- test_rmul_scalar (test_base.TestCSR) ... ok
- test_rsub (test_base.TestCSR) ... ok
- test_setelement (test_base.TestCSR) ... ok
- test that A*x works for x with shape () (1,) and (1,1) ... ok
- Test whether the lu_solve command segfaults, as reported by Nils ... ok
- test_sort_indices (test_base.TestCSR) ... ok
- test_sparse_format_conversions (test_base.TestCSR) ... ok
- test_str (test_base.TestCSR) ... ok
- test_sub (test_base.TestCSR) ... ok
- subtracting a dense matrix to/from a sparse matrix ... ok
- Does the matrix's .sum(axis=...) method work? ... ok
- test_toarray (test_base.TestCSR) ... ok
- test_tobsr (test_base.TestCSR) ... ok
- test_todense (test_base.TestCSR) ... ok
- test_transpose (test_base.TestCSR) ... ok
- test_unsorted_arithmetic (test_base.TestCSR) ... ok
- test_abs (test_base.TestDIA) ... ok
- test_add (test_base.TestDIA) ... ok
- adding a dense matrix to a sparse matrix ... ok
- test_add_sub (test_base.TestDIA) ... ok
- test_asfptype (test_base.TestDIA) ... ok
- test_astype (test_base.TestDIA) ... ok
- test_constructor1 (test_base.TestDIA) ... ok
- Check whether the copy=True and copy=False keywords work ... ok
- Does the matrix's .diagonal() method work? ... ok
- test_elementwise_divide (test_base.TestDIA) ... ok
- test_elementwise_multiply (test_base.TestDIA) ... ok
- create empty matrices ... ok
- Test manipulating empty matrices. Fails in SciPy SVN <= r1768 ... ok
- test_from_array (test_base.TestDIA) ... ok
- test_from_list (test_base.TestDIA) ... ok
- test_from_matrix (test_base.TestDIA) ... ok
- test_from_sparse (test_base.TestDIA) ... ok
- test_getcol (test_base.TestDIA) ... ok
- test_getrow (test_base.TestDIA) ... ok
- test_imag (test_base.TestDIA) ... ok
- test_invalid_shapes (test_base.TestDIA) ... ok
- test_matmat_dense (test_base.TestDIA) ... ok
- test_matmat_sparse (test_base.TestDIA) ... ok
- test_matvec (test_base.TestDIA) ... ok
- Does the matrix's .mean(axis=...) method work? ... ok
- test_mu (test_base.TestDIA) ... ok
- test_mul_scalar (test_base.TestDIA) ... ok
- test_neg (test_base.TestDIA) ... ok
- test_nonzero (test_base.TestDIA) ... ok
- test_pow (test_base.TestDIA) ... ok
- test_radd (test_base.TestDIA) ... ok
- test_real (test_base.TestDIA) ... ok
- test_repr (test_base.TestDIA) ... ok
- test_rmatvec (test_base.TestDIA) ... ok
- test_rmul_scalar (test_base.TestDIA) ... ok
- test_rsub (test_base.TestDIA) ... ok
- test that A*x works for x with shape () (1,) and (1,1) ... ok
- test_sparse_format_conversions (test_base.TestDIA) ... ok
- test_str (test_base.TestDIA) ... ok
- test_sub (test_base.TestDIA) ... ok
- subtracting a dense matrix to/from a sparse matrix ... ok
- Does the matrix's .sum(axis=...) method work? ... ok
- test_toarray (test_base.TestDIA) ... ok
- test_tobsr (test_base.TestDIA) ... ok
- test_todense (test_base.TestDIA) ... ok
- test_transpose (test_base.TestDIA) ... ok
- test_abs (test_base.TestDOK) ... ok
- test_add (test_base.TestDOK) ... ok
- adding a dense matrix to a sparse matrix ... ok
- test_asfptype (test_base.TestDOK) ... ok
- test_astype (test_base.TestDOK) ... ok
- Test provided by Andrew Straw. Fails in SciPy <= r1477. ... ok
- Check whether the copy=True and copy=False keywords work ... ok
- test_ctor (test_base.TestDOK) ... ok
- Does the matrix's .diagonal() method work? ... ok
- test_elementwise_divide (test_base.TestDOK) ... ok
- test_elementwise_multiply (test_base.TestDOK) ... ok
- create empty matrices ... ok
- Test manipulating empty matrices. Fails in SciPy SVN <= r1768 ... ok
- test_from_array (test_base.TestDOK) ... ok
- test_from_list (test_base.TestDOK) ... ok
- test_from_matrix (test_base.TestDOK) ... ok
- test_from_sparse (test_base.TestDOK) ... ok
- test_getcol (test_base.TestDOK) ... ok
- test_getelement (test_base.TestDOK) ... ok
- test_getrow (test_base.TestDOK) ... ok
- test_imag (test_base.TestDOK) ... ok
- test_invalid_shapes (test_base.TestDOK) ... ok
- test_matmat_dense (test_base.TestDOK) ... ok
- test_matmat_sparse (test_base.TestDOK) ... ok
- test_matvec (test_base.TestDOK) ... ok
- Does the matrix's .mean(axis=...) method work? ... ok
- test_mul_scalar (test_base.TestDOK) ... ok
- test_mult (test_base.TestDOK) ... ok
- test_neg (test_base.TestDOK) ... ok
- test_nonzero (test_base.TestDOK) ... ok
- test_pow (test_base.TestDOK) ... ok
- test_radd (test_base.TestDOK) ... ok
- test_real (test_base.TestDOK) ... ok
- test_repr (test_base.TestDOK) ... ok
- test_rmatvec (test_base.TestDOK) ... ok
- test_rmul_scalar (test_base.TestDOK) ... ok
- test_rsub (test_base.TestDOK) ... ok
- Test for slice functionality (EJS) ... ok
- test_setelement (test_base.TestDOK) ... ok
- test that A*x works for x with shape () (1,) and (1,1) ... ok
- Test whether the lu_solve command segfaults, as reported by Nils ... ok
- test_sparse_format_conversions (test_base.TestDOK) ... ok
- test_str (test_base.TestDOK) ... ok
- test_sub (test_base.TestDOK) ... ok
- subtracting a dense matrix to/from a sparse matrix ... ok
- Does the matrix's .sum(axis=...) method work? ... ok
- test_toarray (test_base.TestDOK) ... ok
- test_tobsr (test_base.TestDOK) ... ok
- test_todense (test_base.TestDOK) ... ok
- test_transpose (test_base.TestDOK) ... ok
- test_abs (test_base.TestLIL) ... ok
- test_add (test_base.TestLIL) ... ok
- adding a dense matrix to a sparse matrix ... ok
- test_add_sub (test_base.TestLIL) ... ok
- test_asfptype (test_base.TestLIL) ... ok
- test_astype (test_base.TestLIL) ... ok
- Check whether the copy=True and copy=False keywords work ... ok
- Does the matrix's .diagonal() method work? ... ok
- test_dot (test_base.TestLIL) ... ok
- test_elementwise_divide (test_base.TestLIL) ... ok
- test_elementwise_multiply (test_base.TestLIL) ... ok
- create empty matrices ... ok
- Test manipulating empty matrices. Fails in SciPy SVN <= r1768 ... ok
- test_fancy_indexing (test_base.TestLIL) ... ok
- test_fancy_indexing_randomized (test_base.TestLIL) ... KNOWNFAIL: Fancy indexing is known to be broken for LIL matrices
- test_fancy_indexing_set (test_base.TestLIL) ... KNOWNFAIL: Fancy indexing is known to be broken for LIL matrices
- test_from_array (test_base.TestLIL) ... ok
- test_from_list (test_base.TestLIL) ... ok
- test_from_matrix (test_base.TestLIL) ... ok
- test_from_sparse (test_base.TestLIL) ... ok
- Test for new slice functionality (EJS) ... ok
- test_get_slices (test_base.TestLIL) ... ok
- Test for new slice functionality (EJS) ... ok
- test_getcol (test_base.TestLIL) ... ok
- test_getelement (test_base.TestLIL) ... ok
- test_getrow (test_base.TestLIL) ... ok
- test_idiv_scalar (test_base.TestLIL) ... ok
- test_imag (test_base.TestLIL) ... ok
- test_imul_scalar (test_base.TestLIL) ... ok
- test_inplace_ops (test_base.TestLIL) ... ok
- test_invalid_shapes (test_base.TestLIL) ... ok
- Tests whether a lil_matrix can be constructed from a ... ok
- test_lil_iteration (test_base.TestLIL) ... ok
- Tests whether a row of one lil_matrix can be assigned to ... ok
- test_lil_sequence_assignment (test_base.TestLIL) ... ok
- test_lil_slice_assignment (test_base.TestLIL) ... ok
- test_matmat_dense (test_base.TestLIL) ... ok
- test_matmat_sparse (test_base.TestLIL) ... ok
- test_matvec (test_base.TestLIL) ... ok
- Does the matrix's .mean(axis=...) method work? ... ok
- test_mu (test_base.TestLIL) ... ok
- test_mul_scalar (test_base.TestLIL) ... ok
- test_neg (test_base.TestLIL) ... ok
- test_nonzero (test_base.TestLIL) ... ok
- test_point_wise_multiply (test_base.TestLIL) ... ok
- test_pow (test_base.TestLIL) ... ok
- test_radd (test_base.TestLIL) ... ok
- test_real (test_base.TestLIL) ... ok
- test_repr (test_base.TestLIL) ... ok
- test_reshape (test_base.TestLIL) ... ok
- test_rmatvec (test_base.TestLIL) ... ok
- test_rmul_scalar (test_base.TestLIL) ... ok
- test_rsub (test_base.TestLIL) ... ok
- test_scalar_mul (test_base.TestLIL) ... ok
- test_setelement (test_base.TestLIL) ... ok
- test that A*x works for x with shape () (1,) and (1,1) ... ok
- Test whether the lu_solve command segfaults, as reported by Nils ... ok
- test_sparse_format_conversions (test_base.TestLIL) ... ok
- test_str (test_base.TestLIL) ... ok
- test_sub (test_base.TestLIL) ... ok
- subtracting a dense matrix to/from a sparse matrix ... ok
- Does the matrix's .sum(axis=...) method work? ... ok
- test_toarray (test_base.TestLIL) ... ok
- test_tobsr (test_base.TestLIL) ... ok
- test_todense (test_base.TestLIL) ... ok
- test_transpose (test_base.TestLIL) ... ok
- test_bmat (test_construct.TestConstructUtils) ... ok
- test_eye (test_construct.TestConstructUtils) ... ok
- test_hstack (test_construct.TestConstructUtils) ... ok
- test_identity (test_construct.TestConstructUtils) ... ok
- test_kron (test_construct.TestConstructUtils) ... ok
- test_kronsum (test_construct.TestConstructUtils) ... ok
- test_lil_diags (test_construct.TestConstructUtils) ... ok
- test_rand (test_construct.TestConstructUtils) ... ok
- test_spdiags (test_construct.TestConstructUtils) ... ok
- test_vstack (test_construct.TestConstructUtils) ... ok
- test_tril (test_extract.TestExtract) ... ok
- test_triu (test_extract.TestExtract) ... ok
- test_count_blocks (test_spfuncs.TestSparseFunctions) ... ok
- test_cs_graph_components (test_spfuncs.TestSparseFunctions) ... ok
- test_estimate_blocksize (test_spfuncs.TestSparseFunctions) ... ok
- test_scale_rows_and_cols (test_spfuncs.TestSparseFunctions) ... ok
- test_getdtype (test_sputils.TestSparseUtils) ... ok
- test_isdense (test_sputils.TestSparseUtils) ... ok
- test_isintlike (test_sputils.TestSparseUtils) ... ok
- test_isscalarlike (test_sputils.TestSparseUtils) ... ok
- test_issequence (test_sputils.TestSparseUtils) ... ok
- test_isshape (test_sputils.TestSparseUtils) ... ok
- test_upcast (test_sputils.TestSparseUtils) ... ok
- Tests cdist(X, 'braycurtis') on random data. ... ok
- Tests cdist(X, 'canberra') on random data. ... ok
- Tests cdist(X, 'chebychev') on random data. ... ok
- Tests cdist(X, 'cityblock') on random data. ... ok
- Tests cdist(X, 'correlation') on random data. ... ok
- Tests cdist(X, 'cosine') on random data. ... ok
- Tests cdist(X, 'dice') on random data. ... ok
- Tests cdist(X, 'euclidean') on random data. ... ok
- Tests cdist(X, u'euclidean') using unicode metric string ... ok
- Tests cdist(X, 'hamming') on random boolean data. ... ok
- Tests cdist(X, 'hamming') on random data. ... ok
- Tests cdist(X, 'jaccard') on random boolean data. ... ok
- Tests cdist(X, 'jaccard') on random data. ... ok
- Tests cdist(X, 'kulsinski') on random data. ... ok
- Tests cdist(X, 'mahalanobis') on random data. ... ok
- Tests cdist(X, 'matching') on random data. ... ok
- Tests cdist(X, 'minkowski') on random data. (p=1.23) ... ok
- Tests cdist(X, 'minkowski') on random data. (p=3.8) ... ok
- Tests cdist(X, 'minkowski') on random data. (p=4.6) ... ok
- Tests cdist(X, 'rogerstanimoto') on random data. ... ok
- Tests cdist(X, 'russellrao') on random data. ... ok
- Tests cdist(X, 'seuclidean') on random data. ... ok
- Tests cdist(X, 'sokalmichener') on random data. ... ok
- Tests cdist(X, 'sokalsneath') on random data. ... ok
- Tests cdist(X, 'sqeuclidean') on random data. ... ok
- Tests cdist(X, 'wminkowski') on random data. (p=1.23) ... ok
- Tests cdist(X, 'wminkowski') on random data. (p=3.8) ... ok
- Tests cdist(X, 'wminkowski') on random data. (p=4.6) ... ok
- Tests cdist(X, 'yule') on random data. ... ok
- Tests is_valid_dm(*) on an assymetric distance matrix. Exception expected. ... ok
- Tests is_valid_dm(*) on an assymetric distance matrix. False expected. ... ok
- Tests is_valid_dm(*) on a correct 1x1. True expected. ... ok
- Tests is_valid_dm(*) on a correct 2x2. True expected. ... ok
- Tests is_valid_dm(*) on a correct 3x3. True expected. ... ok
- Tests is_valid_dm(*) on a correct 4x4. True expected. ... ok
- Tests is_valid_dm(*) on a correct 5x5. True expected. ... ok
- Tests is_valid_dm(*) on a 1D array. Exception expected. ... ok
- Tests is_valid_dm(*) on a 1D array. False expected. ... ok
- Tests is_valid_dm(*) on a 3D array. Exception expected. ... ok
- Tests is_valid_dm(*) on a 3D array. False expected. ... ok
- Tests is_valid_dm(*) on an int16 array. Exception expected. ... ok
- Tests is_valid_dm(*) on an int16 array. False expected. ... ok
- Tests is_valid_dm(*) on a distance matrix with a nonzero diagonal. Exception expected. ... ok
- Tests is_valid_dm(*) on a distance matrix with a nonzero diagonal. False expected. ... ok
- Tests is_valid_y(*) on 100 improper condensed distance matrices. Expecting exception. ... ok
- Tests is_valid_y(*) on a correct 2x2 condensed. True expected. ... ok
- Tests is_valid_y(*) on a correct 3x3 condensed. True expected. ... ok
- Tests is_valid_y(*) on a correct 4x4 condensed. True expected. ... ok
- Tests is_valid_y(*) on a correct 5x5 condensed. True expected. ... ok
- Tests is_valid_y(*) on a 2D array. Exception expected. ... ok
- Tests is_valid_y(*) on a 2D array. False expected. ... ok
- Tests is_valid_y(*) on a 3D array. Exception expected. ... ok
- Tests is_valid_y(*) on a 3D array. False expected. ... ok
- Tests is_valid_y(*) on an int16 array. Exception expected. ... ok
- Tests is_valid_y(*) on an int16 array. False expected. ... ok
- Tests num_obs_dm(D) on a 0x0 distance matrix. Expecting exception. ... ok
- Tests num_obs_dm(D) on a 1x1 distance matrix. ... ok
- Tests num_obs_dm(D) on a 2x2 distance matrix. ... ok
- Tests num_obs_dm(D) on a 3x3 distance matrix. ... ok
- Tests num_obs_dm(D) on a 4x4 distance matrix. ... ok
- Tests num_obs_dm with observation matrices of multiple sizes. ... ok
- Tests num_obs_y(y) on a condensed distance matrix over 1 observations. Expecting exception. ... ok
- Tests num_obs_y(y) on a condensed distance matrix over 2 observations. ... ok
- Tests num_obs_y(y) on 100 improper condensed distance matrices. Expecting exception. ... ok
- Tests num_obs_y(y) on a condensed distance matrix over 3 observations. ... ok
- Tests num_obs_y(y) on a condensed distance matrix over 4 observations. ... ok
- Tests num_obs_y(y) on a condensed distance matrix between 5 and 15 observations. ... ok
- Tests num_obs_y with observation matrices of multiple sizes. ... ok
- Tests pdist(X, 'canberra') to see if the two implementations match on the Iris data set. ... ok
- Tests pdist(X, 'canberra') to see if Canberra gives the right result as reported in Scipy bug report 711. ... ok
- Tests pdist(X, 'chebychev') on the Iris data set. ... ok
- Tests pdist(X, 'chebychev') on the Iris data set. (float32) ... ok
- Tests pdist(X, 'test_chebychev') [the non-C implementation] on the Iris data set. ... ok
- Tests pdist(X, 'chebychev') on random data. ... ok
- Tests pdist(X, 'chebychev') on random data. (float32) ... ok
- Tests pdist(X, 'test_chebychev') [the non-C implementation] on random data. ... ok
- Tests pdist(X, 'cityblock') on the Iris data set. ... ok
- Tests pdist(X, 'cityblock') on the Iris data set. (float32) ... ok
- Tests pdist(X, 'test_cityblock') [the non-C implementation] on the Iris data set. ... ok
- Tests pdist(X, 'cityblock') on random data. ... ok
- Tests pdist(X, 'cityblock') on random data. (float32) ... ok
- Tests pdist(X, 'test_cityblock') [the non-C implementation] on random data. ... ok
- Tests pdist(X, 'correlation') on the Iris data set. ... ok
- Tests pdist(X, 'correlation') on the Iris data set. (float32) ... ok
- Tests pdist(X, 'test_correlation') [the non-C implementation] on the Iris data set. ... ok
- Tests pdist(X, 'correlation') on random data. ... ok
- Tests pdist(X, 'correlation') on random data. (float32) ... ok
- Tests pdist(X, 'test_correlation') [the non-C implementation] on random data. ... ok
- Tests pdist(X, 'cosine') on the Iris data set. ... ok
- Tests pdist(X, 'cosine') on the Iris data set. ... ok
- Tests pdist(X, 'test_cosine') [the non-C implementation] on the Iris data set. ... ok
- Tests pdist(X, 'cosine') on random data. ... ok
- Tests pdist(X, 'cosine') on random data. (float32) ... ok
- Tests pdist(X, 'test_cosine') [the non-C implementation] on random data. ... ok
- Tests pdist(X, 'hamming') on random data. ... ok
- Tests pdist(X, 'hamming') on random data. (float32) ... ok
- Tests pdist(X, 'test_hamming') [the non-C implementation] on random data. ... ok
- Tests pdist(X, 'dice') to see if the two implementations match on random double input data. ... ok
- Tests dice(*,*) with mtica example #1. ... ok
- Tests dice(*,*) with mtica example #2. ... ok
- Tests pdist(X, 'jaccard') on random data. ... ok
- Tests pdist(X, 'jaccard') on random data. (float32) ... ok
- Tests pdist(X, 'test_jaccard') [the non-C implementation] on random data. ... ok
- Tests pdist(X, 'euclidean') on the Iris data set. ... ok
- Tests pdist(X, 'euclidean') on the Iris data set. (float32) ... ok
- Tests pdist(X, 'test_euclidean') [the non-C implementation] on the Iris data set. ... ok
- Tests pdist(X, 'euclidean') with unicode metric string ... ok
- Tests pdist(X, 'euclidean') on random data (float32). ... ok
- Tests pdist(X, 'test_euclidean') [the non-C implementation] on random data. ... ok
- Tests pdist(X, 'hamming') on random data. ... ok
- Tests pdist(X, 'hamming') on random data. ... ok
- Tests pdist(X, 'test_hamming') [the non-C implementation] on random data. ... ok
- Tests pdist(X, 'jaccard') to see if the two implementations match on random double input data. ... ok
- Tests jaccard(*,*) with mtica example #1. ... ok
- Tests jaccard(*,*) with mtica example #2. ... ok
- Tests pdist(X, 'jaccard') on random data. ... ok
- Tests pdist(X, 'jaccard') on random data. (float32) ... ok
- Tests pdist(X, 'test_jaccard') [the non-C implementation] on random data. ... ok
- Tests pdist(X, 'kulsinski') to see if the two implementations match on random double input data. ... ok
- Tests pdist(X, 'matching') to see if the two implementations match on random boolean input data. ... ok
- Tests matching(*,*) with mtica example #1 (nums). ... ok
- Tests matching(*,*) with mtica example #2. ... ok
- Tests pdist(X, 'minkowski') on iris data. ... ok
- Tests pdist(X, 'minkowski') on iris data. (float32) ... ok
- Tests pdist(X, 'test_minkowski') [the non-C implementation] on iris data. ... ok
- Tests pdist(X, 'minkowski') on random data. ... ok
- Tests pdist(X, 'minkowski') on random data. (float32) ... ok
- Tests pdist(X, 'test_minkowski') [the non-C implementation] on random data. ... ok
- Tests pdist(X, 'rogerstanimoto') to see if the two implementations match on random double input data. ... ok
- Tests rogerstanimoto(*,*) with mtica example #1. ... ok
- Tests rogerstanimoto(*,*) with mtica example #2. ... ok
- Tests pdist(X, 'russellrao') to see if the two implementations match on random double input data. ... ok
- Tests russellrao(*,*) with mtica example #1. ... ok
- Tests russellrao(*,*) with mtica example #2. ... ok
- Tests pdist(X, 'seuclidean') on the Iris data set. ... ok
- Tests pdist(X, 'seuclidean') on the Iris data set (float32). ... ok
- Tests pdist(X, 'test_seuclidean') [the non-C implementation] on the Iris data set. ... ok
- Tests pdist(X, 'seuclidean') on random data. ... ok
- Tests pdist(X, 'seuclidean') on random data (float32). ... ok
- Tests pdist(X, 'test_sqeuclidean') [the non-C implementation] on random data. ... ok
- Tests pdist(X, 'sokalmichener') to see if the two implementations match on random double input data. ... ok
- Tests pdist(X, 'sokalsneath') to see if the two implementations match on random double input data. ... ok
- Tests sokalsneath(*,*) with mtica example #1. ... ok
- Tests sokalsneath(*,*) with mtica example #2. ... ok
- Tests pdist(X, 'yule') to see if the two implementations match on random double input data. ... ok
- Tests yule(*,*) with mtica example #1. ... ok
- Tests yule(*,*) with mtica example #2. ... ok
- Tests squareform on a 1x1 matrix. ... ok
- Tests squareform on a 2x2 matrix. ... ok
- Tests squareform on an empty matrix. ... ok
- Tests squareform on an empty vector. ... ok
- Tests squareform on a square matrices of multiple sizes. ... ok
- Tests squareform on a 1-D array, length=1. ... ok
- Loading test data files for the scipy.spatial.distance tests. ... ok
- test_kdtree.test_count_neighbors.test_large_radius ... ok
- test_kdtree.test_count_neighbors.test_multiple_radius ... ok
- test_kdtree.test_count_neighbors.test_one_radius ... ok
- test_kdtree.test_random.test_approx ... ok
- test_kdtree.test_random.test_m_nearest ... ok
- test_kdtree.test_random.test_nearest ... ok
- test_kdtree.test_random.test_points_near ... ok
- test_kdtree.test_random.test_points_near_l1 ... ok
- test_kdtree.test_random.test_points_near_linf ... ok
- test_kdtree.test_random_ball.test_found_all ... ok
- test_kdtree.test_random_ball.test_in_ball ... ok
- test_kdtree.test_random_ball_approx.test_found_all ... ok
- test_kdtree.test_random_ball_approx.test_in_ball ... ok
- test_kdtree.test_random_ball_far.test_found_all ... ok
- test_kdtree.test_random_ball_far.test_in_ball ... ok
- test_kdtree.test_random_ball_l1.test_found_all ... ok
- test_kdtree.test_random_ball_l1.test_in_ball ... ok
- test_kdtree.test_random_ball_linf.test_found_all ... ok
- test_kdtree.test_random_ball_linf.test_in_ball ... ok
- test_kdtree.test_random_compiled.test_approx ... ok
- test_kdtree.test_random_compiled.test_m_nearest ... ok
- test_kdtree.test_random_compiled.test_nearest ... ok
- test_kdtree.test_random_compiled.test_points_near ... ok
- test_kdtree.test_random_compiled.test_points_near_l1 ... ok
- test_kdtree.test_random_compiled.test_points_near_linf ... ok
- test_kdtree.test_random_far.test_approx ... ok
- test_kdtree.test_random_far.test_m_nearest ... ok
- test_kdtree.test_random_far.test_nearest ... ok
- test_kdtree.test_random_far.test_points_near ... ok
- test_kdtree.test_random_far.test_points_near_l1 ... ok
- test_kdtree.test_random_far.test_points_near_linf ... ok
- test_kdtree.test_random_far_compiled.test_approx ... ok
- test_kdtree.test_random_far_compiled.test_m_nearest ... ok
- test_kdtree.test_random_far_compiled.test_nearest ... ok
- test_kdtree.test_random_far_compiled.test_points_near ... ok
- test_kdtree.test_random_far_compiled.test_points_near_l1 ... ok
- test_kdtree.test_random_far_compiled.test_points_near_linf ... ok
- test_kdtree.test_rectangle.test_max_inside ... ok
- test_kdtree.test_rectangle.test_max_one_side ... ok
- test_kdtree.test_rectangle.test_max_two_sides ... ok
- test_kdtree.test_rectangle.test_min_inside ... ok
- test_kdtree.test_rectangle.test_min_one_side ... ok
- test_kdtree.test_rectangle.test_min_two_sides ... ok
- test_kdtree.test_rectangle.test_split ... ok
- test_kdtree.test_small.test_approx ... ok
- test_kdtree.test_small.test_m_nearest ... ok
- test_kdtree.test_small.test_nearest ... ok
- test_kdtree.test_small.test_nearest_two ... ok
- test_kdtree.test_small.test_points_near ... ok
- test_kdtree.test_small.test_points_near_l1 ... ok
- test_kdtree.test_small.test_points_near_linf ... ok
- test_kdtree.test_small_compiled.test_approx ... ok
- test_kdtree.test_small_compiled.test_m_nearest ... ok
- test_kdtree.test_small_compiled.test_nearest ... ok
- test_kdtree.test_small_compiled.test_nearest_two ... ok
- test_kdtree.test_small_compiled.test_points_near ... ok
- test_kdtree.test_small_compiled.test_points_near_l1 ... ok
- test_kdtree.test_small_compiled.test_points_near_linf ... ok
- test_kdtree.test_small_nonleaf.test_approx ... ok
- test_kdtree.test_small_nonleaf.test_m_nearest ... ok
- test_kdtree.test_small_nonleaf.test_nearest ... ok
- test_kdtree.test_small_nonleaf.test_nearest_two ... ok
- test_kdtree.test_small_nonleaf.test_points_near ... ok
- test_kdtree.test_small_nonleaf.test_points_near_l1 ... ok
- test_kdtree.test_small_nonleaf.test_points_near_linf ... ok
- test_kdtree.test_small_nonleaf_compiled.test_approx ... ok
- test_kdtree.test_small_nonleaf_compiled.test_m_nearest ... ok
- test_kdtree.test_small_nonleaf_compiled.test_nearest ... ok
- test_kdtree.test_small_nonleaf_compiled.test_nearest_two ... ok
- test_kdtree.test_small_nonleaf_compiled.test_points_near ... ok
- test_kdtree.test_small_nonleaf_compiled.test_points_near_l1 ... ok
- test_kdtree.test_small_nonleaf_compiled.test_points_near_linf ... ok
- test_kdtree.test_sparse_distance_matrix.test_consistency_with_neighbors ... ok
- test_kdtree.test_sparse_distance_matrix.test_zero_distance ... ok
- test_kdtree.test_two_random_trees.test_all_in_ball ... ok
- test_kdtree.test_two_random_trees.test_found_all ... ok
- test_kdtree.test_two_random_trees_far.test_all_in_ball ... ok
- test_kdtree.test_two_random_trees_far.test_found_all ... ok
- test_kdtree.test_two_random_trees_linf.test_all_in_ball ... ok
- test_kdtree.test_two_random_trees_linf.test_found_all ... ok
- test_kdtree.test_vectorization.test_single_query ... ok
- test_kdtree.test_vectorization.test_single_query_all_neighbors ... ok
- test_kdtree.test_vectorization.test_single_query_multiple_neighbors ... ok
- test_kdtree.test_vectorization.test_vectorized_query ... ok
- test_kdtree.test_vectorization.test_vectorized_query_all_neighbors ... ok
- test_kdtree.test_vectorization.test_vectorized_query_multiple_neighbors ... ok
- test_kdtree.test_vectorization_compiled.test_single_query ... ok
- test_kdtree.test_vectorization_compiled.test_single_query_multiple_neighbors ... ok
- test_kdtree.test_vectorization_compiled.test_vectorized_query ... ok
- test_kdtree.test_vectorization_compiled.test_vectorized_query_multiple_neighbors ... ok
- test_kdtree.test_vectorization_compiled.test_vectorized_query_noncontiguous_values ... ok
- test_kdtree.test_random_ball_vectorized ... ok
- test_kdtree.test_distance_l2 ... ok
- test_kdtree.test_distance_l1 ... ok
- test_kdtree.test_distance_linf ... ok
- test_kdtree.test_distance_vectorization ... ok
- test_kdtree.test_distance_matrix ... ok
- test_kdtree.test_distance_matrix_looping ... ok
- test_kdtree.test_onetree_query(<scipy.spatial.kdtree.KDTree object at 0xb0dbfec>, 0.10000000000000001) ... ok
- test_kdtree.test_onetree_query(<scipy.spatial.kdtree.KDTree object at 0xa5e41cc>, 0.10000000000000001) ... ok
- test_kdtree.test_onetree_query(<scipy.spatial.kdtree.KDTree object at 0xa5e41cc>, 0.001) ... ok
- test_kdtree.test_onetree_query(<scipy.spatial.kdtree.KDTree object at 0xa5e41cc>, 1.0000000000000001e-05) ... ok
- test_kdtree.test_onetree_query(<scipy.spatial.kdtree.KDTree object at 0xa5e41cc>, 9.9999999999999995e-07) ... ok
- test_ai_zeros (test_basic.TestAiry) ... ok
- test_airy (test_basic.TestAiry) ... ok
- test_airye (test_basic.TestAiry) ... ok
- test_bi_zeros (test_basic.TestAiry) ... ok
- test_assoc_laguerre (test_basic.TestAssocLaguerre) ... ok
- test_bernoulli (test_basic.TestBernoulli) ... ok
- test_i0 (test_basic.TestBessel) ... ok
- test_i0_series (test_basic.TestBessel) ... ok
- test_i0e (test_basic.TestBessel) ... ok
- test_i1 (test_basic.TestBessel) ... ok
- test_i1_series (test_basic.TestBessel) ... ok
- test_i1e (test_basic.TestBessel) ... ok
- test_it2i0k0 (test_basic.TestBessel) ... ok
- test_it2j0y0 (test_basic.TestBessel) ... ok
- test_iti0k0 (test_basic.TestBessel) ... ok
- test_itj0y0 (test_basic.TestBessel) ... ok
- test_iv (test_basic.TestBessel) ... ok
- test_iv_cephes_vs_amos (test_basic.TestBessel) ... Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: divide by zero encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- Warning: overflow encountered in iv
- ok
- test_iv_hyperg_poles (test_basic.TestBessel) ... ok
- test_iv_series (test_basic.TestBessel) ... ok
- test_ive (test_basic.TestBessel) ... ok
- test_ivp (test_basic.TestBessel) ... ok
- test_ivp0 (test_basic.TestBessel) ... ok
- test_j0 (test_basic.TestBessel) ... ok
- test_j1 (test_basic.TestBessel) ... ok
- test_jacobi (test_basic.TestBessel) ... ok
- test_jn (test_basic.TestBessel) ... ok
- test_jn_zeros (test_basic.TestBessel) ... ok
- test_jn_zeros_slow (test_basic.TestBessel) ... ok
- test_jnjnp_zeros (test_basic.TestBessel) ... ok
- test_jnp_zeros (test_basic.TestBessel) ... ok
- test_jnyn_zeros (test_basic.TestBessel) ... ok
- test_jv (test_basic.TestBessel) ... ok
- test_jv_cephes_vs_amos (test_basic.TestBessel) ... ok
- test_jve (test_basic.TestBessel) ... ok
- test_jvp (test_basic.TestBessel) ... ok
- test_k0 (test_basic.TestBessel) ... ok
- test_k0e (test_basic.TestBessel) ... ok
- test_k1 (test_basic.TestBessel) ... ok
- test_k1e (test_basic.TestBessel) ... ok
- test_kn (test_basic.TestBessel) ... ok
- test_kv0 (test_basic.TestBessel) ... ok
- test_kv1 (test_basic.TestBessel) ... ok
- test_kv2 (test_basic.TestBessel) ... ok
- test_kv_cephes_vs_amos (test_basic.TestBessel) ... ok
- test_kve (test_basic.TestBessel) ... ok
- test_kvp_n1 (test_basic.TestBessel) ... ok
- test_kvp_n2 (test_basic.TestBessel) ... ok
- test_kvp_v0n1 (test_basic.TestBessel) ... ok
- test_negv (test_basic.TestBessel) ... ok
- Real-valued Bessel I overflow ... ok
- test_ticket_623 (test_basic.TestBessel) ... ok
- Negative-order Bessels ... ok
- Real-valued Bessel domains ... ok
- test_y0 (test_basic.TestBessel) ... ok
- test_y0_zeros (test_basic.TestBessel) ... ok
- test_y1 (test_basic.TestBessel) ... ok
- test_y1_zeros (test_basic.TestBessel) ... ok
- test_y1p_zeros (test_basic.TestBessel) ... ok
- test_yn (test_basic.TestBessel) ... ok
- test_yn_zeros (test_basic.TestBessel) ... ok
- test_ynp_zeros (test_basic.TestBessel) ... ok
- test_ynp_zeros_large_order (test_basic.TestBessel) ... KNOWNFAIL: cephes/yv is not eps accurate for large orders on all platforms, and has nan/inf issues
- test_yv (test_basic.TestBessel) ... ok
- test_yv_cephes_vs_amos (test_basic.TestBessel) ... KNOWNFAIL: cephes/yv is not eps accurate for large orders on all platforms, and has nan/inf issues
- test_yv_cephes_vs_amos_only_small_orders (test_basic.TestBessel) ... ok
- test_yve (test_basic.TestBessel) ... ok
- test_yvp (test_basic.TestBessel) ... ok
- test_besselpoly (test_basic.TestBesselpoly) ... ok
- test_beta (test_basic.TestBeta) ... ok
- test_betainc (test_basic.TestBeta) ... ok
- test_betaincinv (test_basic.TestBeta) ... ok
- test_betaln (test_basic.TestBeta) ... ok
- test_airy (test_basic.TestCephes) ... ok
- test_airye (test_basic.TestCephes) ... ok
- test_bdtr (test_basic.TestCephes) ... ok
- test_bdtrc (test_basic.TestCephes) ... ok
- test_bdtri (test_basic.TestCephes) ... ok
- test_bdtrik (test_basic.TestCephes) ... ok
- test_bdtrin (test_basic.TestCephes) ... ok
- test_bei (test_basic.TestCephes) ... ok
- test_beip (test_basic.TestCephes) ... ok
- test_ber (test_basic.TestCephes) ... ok
- test_berp (test_basic.TestCephes) ... ok
- test_besselpoly (test_basic.TestCephes) ... ok
- test_beta (test_basic.TestCephes) ... ok
- test_betainc (test_basic.TestCephes) ... ok
- test_betaincinv (test_basic.TestCephes) ... ok
- test_betaln (test_basic.TestCephes) ... ok
- test_btdtr (test_basic.TestCephes) ... ok
- test_btdtri (test_basic.TestCephes) ... ok
- test_btdtria (test_basic.TestCephes) ... ok
- test_btdtrib (test_basic.TestCephes) ... ok
- test_cbrt (test_basic.TestCephes) ... ok
- test_chdtr (test_basic.TestCephes) ... ok
- test_chdtrc (test_basic.TestCephes) ... ok
- test_chdtri (test_basic.TestCephes) ... ok
- test_chdtriv (test_basic.TestCephes) ... ok
- test_chndtr (test_basic.TestCephes) ... ok
- test_chndtridf (test_basic.TestCephes) ... ok
- test_chndtrinc (test_basic.TestCephes) ... ok
- test_chndtrix (test_basic.TestCephes) ... ok
- test_cosdg (test_basic.TestCephes) ... ok
- test_cosm1 (test_basic.TestCephes) ... ok
- test_cotdg (test_basic.TestCephes) ... ok
- test_dawsn (test_basic.TestCephes) ... ok
- test_ellipe (test_basic.TestCephes) ... ok
- test_ellipeinc (test_basic.TestCephes) ... ok
- test_ellipj (test_basic.TestCephes) ... ok
- test_ellipk (test_basic.TestCephes) ... ok
- test_ellipkinc (test_basic.TestCephes) ... ok
- test_erf (test_basic.TestCephes) ... ok
- test_erfc (test_basic.TestCephes) ... ok
- test_exp1 (test_basic.TestCephes) ... ok
- test_exp10 (test_basic.TestCephes) ... ok
- test_exp1_reg (test_basic.TestCephes) ... ok
- test_exp2 (test_basic.TestCephes) ... ok
- test_expi (test_basic.TestCephes) ... ok
- test_expm1 (test_basic.TestCephes) ... ok
- test_expn (test_basic.TestCephes) ... ok
- test_fdtr (test_basic.TestCephes) ... ok
- test_fdtrc (test_basic.TestCephes) ... ok
- test_fdtri (test_basic.TestCephes) ... Warning: invalid value encountered in fdtri
- ok
- test_fdtridfd (test_basic.TestCephes) ... ok
- test_fresnel (test_basic.TestCephes) ... ok
- test_gamma (test_basic.TestCephes) ... ok
- test_gammainc (test_basic.TestCephes) ... ok
- test_gammaincc (test_basic.TestCephes) ... ok
- test_gammainccinv (test_basic.TestCephes) ... ok
- test_gammaln (test_basic.TestCephes) ... ok
- test_gdtr (test_basic.TestCephes) ... ok
- test_gdtrc (test_basic.TestCephes) ... ok
- test_gdtria (test_basic.TestCephes) ... ok
- test_gdtrib (test_basic.TestCephes) ... ok
- test_gdtrix (test_basic.TestCephes) ... ok
- test_hankel1 (test_basic.TestCephes) ... ok
- test_hankel1e (test_basic.TestCephes) ... ok
- test_hankel2 (test_basic.TestCephes) ... ok
- test_hankel2e (test_basic.TestCephes) ... ok
- test_hyp1f1 (test_basic.TestCephes) ... ok
- test_hyp1f2 (test_basic.TestCephes) ... ok
- test_hyp2f0 (test_basic.TestCephes) ... ok
- test_hyp2f1 (test_basic.TestCephes) ... ok
- test_hyp3f0 (test_basic.TestCephes) ... ok
- test_hyperu (test_basic.TestCephes) ... ok
- test_i0 (test_basic.TestCephes) ... ok
- test_i0e (test_basic.TestCephes) ... ok
- test_i1 (test_basic.TestCephes) ... ok
- test_i1e (test_basic.TestCephes) ... ok
- test_it2i0k0 (test_basic.TestCephes) ... ok
- test_it2j0y0 (test_basic.TestCephes) ... ok
- test_it2struve0 (test_basic.TestCephes) ... ok
- test_itairy (test_basic.TestCephes) ... ok
- test_iti0k0 (test_basic.TestCephes) ... ok
- test_itj0y0 (test_basic.TestCephes) ... ok
- test_itmodstruve0 (test_basic.TestCephes) ... ok
- test_itstruve0 (test_basic.TestCephes) ... ok
- test_iv (test_basic.TestCephes) ... ok
- test_j0 (test_basic.TestCephes) ... ok
- test_j1 (test_basic.TestCephes) ... ok
- test_jn (test_basic.TestCephes) ... ok
- test_jv (test_basic.TestCephes) ... ok
- test_k0 (test_basic.TestCephes) ... ok
- test_k0e (test_basic.TestCephes) ... ok
- test_k1 (test_basic.TestCephes) ... ok
- test_k1e (test_basic.TestCephes) ... ok
- test_kei (test_basic.TestCephes) ... ok
- test_keip (test_basic.TestCephes) ... ok
- test_ker (test_basic.TestCephes) ... ok
- test_kerp (test_basic.TestCephes) ... ok
- test_kn (test_basic.TestCephes) ... ok
- test_kolmogi (test_basic.TestCephes) ... ok
- test_kolmogorov (test_basic.TestCephes) ... ok
- test_log1p (test_basic.TestCephes) ... ok
- test_lpmv (test_basic.TestCephes) ... ok
- test_mathieu_a (test_basic.TestCephes) ... ok
- test_mathieu_b (test_basic.TestCephes) ... ok
- test_mathieu_cem (test_basic.TestCephes) ... ok
- test_mathieu_modcem1 (test_basic.TestCephes) ... ok
- test_mathieu_modcem2 (test_basic.TestCephes) ... ok
- test_mathieu_modsem1 (test_basic.TestCephes) ... ok
- test_mathieu_modsem2 (test_basic.TestCephes) ... ok
- test_mathieu_sem (test_basic.TestCephes) ... ok
- test_modfresnelm (test_basic.TestCephes) ... ok
- test_modfresnelp (test_basic.TestCephes) ... ok
- test_nbdtr (test_basic.TestCephes) ... ok
- test_nbdtrc (test_basic.TestCephes) ... ok
- test_nbdtri (test_basic.TestCephes) ... ok
- test_nbdtrin (test_basic.TestCephes) ... ok
- test_ncfdtr (test_basic.TestCephes) ... ok
- test_ncfdtri (test_basic.TestCephes) ... ok
- test_ncfdtridfd (test_basic.TestCephes) ... ok
- test_nctdtr (test_basic.TestCephes) ... ok
- test_nctdtrinc (test_basic.TestCephes) ... ok
- test_nctdtrit (test_basic.TestCephes) ... ok
- test_ndtr (test_basic.TestCephes) ... ok
- test_ndtri (test_basic.TestCephes) ... ok
- test_nrdtrimn (test_basic.TestCephes) ... ok
- test_nrdtrisd (test_basic.TestCephes) ... ok
- test_obl_ang1 (test_basic.TestCephes) ... ok
- test_obl_ang1_cv (test_basic.TestCephes) ... ok
- test_obl_rad1 (test_basic.TestCephes) ... ok
- test_obl_rad1_cv (test_basic.TestCephes) ... ok
- test_obl_rad2 (test_basic.TestCephes) ... ok
- test_obl_rad2_cv (test_basic.TestCephes) ... ok
- test_pbdv (test_basic.TestCephes) ... ok
- test_pbvv (test_basic.TestCephes) ... ok
- test_pbwa (test_basic.TestCephes) ... ok
- test_pdtr (test_basic.TestCephes) ... ok
- test_pdtrc (test_basic.TestCephes) ... ok
- test_pdtri (test_basic.TestCephes) ... ok
- test_pdtrik (test_basic.TestCephes) ... ok
- test_pro_ang1 (test_basic.TestCephes) ... ok
- test_pro_ang1_cv (test_basic.TestCephes) ... ok
- test_pro_rad1 (test_basic.TestCephes) ... ok
- test_pro_rad1_cv (test_basic.TestCephes) ... ok
- test_pro_rad2 (test_basic.TestCephes) ... ok
- test_pro_rad2_cv (test_basic.TestCephes) ... ok
- test_psi (test_basic.TestCephes) ... ok
- test_radian (test_basic.TestCephes) ... ok
- test_rgamma (test_basic.TestCephes) ... ok
- test_round (test_basic.TestCephes) ... ok
- test_shichi (test_basic.TestCephes) ... ok
- test_sici (test_basic.TestCephes) ... ok
- test_sindg (test_basic.TestCephes) ... ok
- test_smirnov (test_basic.TestCephes) ... ok
- test_smirnovi (test_basic.TestCephes) ... ok
- test_spence (test_basic.TestCephes) ... ok
- test_stdtr (test_basic.TestCephes) ... ok
- test_stdtridf (test_basic.TestCephes) ... ok
- test_stdtrit (test_basic.TestCephes) ... ok
- test_struve (test_basic.TestCephes) ... ok
- test_tandg (test_basic.TestCephes) ... ok
- test_tklmbda (test_basic.TestCephes) ... ok
- test_wofz (test_basic.TestCephes) ... ok
- test_y0 (test_basic.TestCephes) ... ok
- test_y1 (test_basic.TestCephes) ... ok
- test_yn (test_basic.TestCephes) ... ok
- test_yv (test_basic.TestCephes) ... ok
- test_zeta (test_basic.TestCephes) ... ok
- test_zetac (test_basic.TestCephes) ... ok
- test_ellipe (test_basic.TestEllip) ... ok
- test_ellipeinc (test_basic.TestEllip) ... ok
- test_ellipj (test_basic.TestEllip) ... ok
- Regression test for #912. ... ok
- test_ellipk (test_basic.TestEllip) ... ok
- test_ellipkinc (test_basic.TestEllip) ... ok
- test_erf (test_basic.TestErf) ... ok
- test_erf_zeros (test_basic.TestErf) ... ok
- test_erfcinv (test_basic.TestErf) ... ok
- test_erfinv (test_basic.TestErf) ... ok
- test_errprint (test_basic.TestErf) ... ok
- test_euler (test_basic.TestEuler) ... Warning: invalid value encountered in divide
- ok
- test_exp10 (test_basic.TestExp) ... ok
- test_exp10more (test_basic.TestExp) ... ok
- test_exp2 (test_basic.TestExp) ... ok
- test_exp2more (test_basic.TestExp) ... ok
- test_expm1 (test_basic.TestExp) ... ok
- test_expm1more (test_basic.TestExp) ... ok
- test_fresnel (test_basic.TestFresnel) ... ok
- test_fresnel_zeros (test_basic.TestFresnel) ... ok
- test_fresnelc_zeros (test_basic.TestFresnel) ... ok
- test_fresnels_zeros (test_basic.TestFresnel) ... ok
- test_modfresnelm (test_basic.TestFresnelIntegral) ... ok
- test_modfresnelp (test_basic.TestFresnelIntegral) ... ok
- test_975 (test_basic.TestGamma) ... ok
- test_gamma (test_basic.TestGamma) ... ok
- test_gammainc (test_basic.TestGamma) ... ok
- test_gammaincc (test_basic.TestGamma) ... ok
- test_gammainccinv (test_basic.TestGamma) ... ok
- test_gammaincinv (test_basic.TestGamma) ... ok
- test_gammaln (test_basic.TestGamma) ... ok
- test_rgamma (test_basic.TestGamma) ... ok
- test_hankel1 (test_basic.TestHankel) ... ok
- test_hankel1e (test_basic.TestHankel) ... ok
- test_hankel2 (test_basic.TestHankel) ... ok
- test_hankl2e (test_basic.TestHankel) ... ok
- test_negv (test_basic.TestHankel) ... ok
- test_h1vp (test_basic.TestHyper) ... ok
- test_h2vp (test_basic.TestHyper) ... ok
- test_hyp0f1 (test_basic.TestHyper) ... ok
- test_hyp1f1 (test_basic.TestHyper) ... ok
- test_hyp1f2 (test_basic.TestHyper) ... ok
- test_hyp2f0 (test_basic.TestHyper) ... ok
- test_hyp2f1 (test_basic.TestHyper) ... ok
- test_hyp3f0 (test_basic.TestHyper) ... ok
- test_hyperu (test_basic.TestHyper) ... ok
- test_bei (test_basic.TestKelvin) ... ok
- test_bei_zeros (test_basic.TestKelvin) ... ok
- test_beip (test_basic.TestKelvin) ... ok
- test_beip_zeros (test_basic.TestKelvin) ... ok
- test_ber (test_basic.TestKelvin) ... ok
- test_ber_zeros (test_basic.TestKelvin) ... ok
- test_berp (test_basic.TestKelvin) ... ok
- test_berp_zeros (test_basic.TestKelvin) ... ok
- test_kei (test_basic.TestKelvin) ... ok
- test_kei_zeros (test_basic.TestKelvin) ... ok
- test_keip (test_basic.TestKelvin) ... ok
- test_keip_zeros (test_basic.TestKelvin) ... ok
- test_kelvin (test_basic.TestKelvin) ... ok
- test_kelvin_zeros (test_basic.TestKelvin) ... ok
- test_ker (test_basic.TestKelvin) ... ok
- test_ker_zeros (test_basic.TestKelvin) ... ok
- test_kerp (test_basic.TestKelvin) ... ok
- test_kerp_zeros (test_basic.TestKelvin) ... ok
- test_genlaguerre (test_basic.TestLaguerre) ... ok
- test_laguerre (test_basic.TestLaguerre) ... ok
- test_lmbda (test_basic.TestLambda) ... ok
- test_legendre (test_basic.TestLegendre) ... ok
- test_lpmn (test_basic.TestLegendreFunctions) ... ok
- test_lpmv (test_basic.TestLegendreFunctions) ... ok
- test_lpn (test_basic.TestLegendreFunctions) ... ok
- test_lqmn (test_basic.TestLegendreFunctions) ... ok
- test_lqmn_shape (test_basic.TestLegendreFunctions) ... ok
- test_lqn (test_basic.TestLegendreFunctions) ... ok
- test_log1p (test_basic.TestLog1p) ... ok
- test_log1pmore (test_basic.TestLog1p) ... ok
- test_mathieu_a (test_basic.TestMathieu) ... ok
- test_mathieu_even_coef (test_basic.TestMathieu) ... ok
- test_mathieu_odd_coef (test_basic.TestMathieu) ... ok
- test_obl_cv_seq (test_basic.TestOblCvSeq) ... ok
- test_pbdn_seq (test_basic.TestParabolicCylinder) ... ok
- test_pbdv (test_basic.TestParabolicCylinder) ... ok
- test_pbdv_gradient (test_basic.TestParabolicCylinder) ... ok
- test_pbdv_points (test_basic.TestParabolicCylinder) ... ok
- test_pbdv_seq (test_basic.TestParabolicCylinder) ... ok
- test_pbvv_gradient (test_basic.TestParabolicCylinder) ... ok
- test_polygamma (test_basic.TestPolygamma) ... ok
- test_pro_cv_seq (test_basic.TestProCvSeq) ... ok
- test_psi (test_basic.TestPsi) ... ok
- test_radian (test_basic.TestRadian) ... ok
- test_radianmore (test_basic.TestRadian) ... ok
- test_riccati_jn (test_basic.TestRiccati) ... ok
- test_riccati_yn (test_basic.TestRiccati) ... ok
- test_round (test_basic.TestRound) ... ok
- test_sph_harm (test_basic.TestSpherical) ... ok
- test_sph_in (test_basic.TestSpherical) ... ok
- test_sph_inkn (test_basic.TestSpherical) ... ok
- test_sph_jn (test_basic.TestSpherical) ... ok
- test_sph_jnyn (test_basic.TestSpherical) ... ok
- test_sph_kn (test_basic.TestSpherical) ... ok
- test_sph_yn (test_basic.TestSpherical) ... ok
- Regression test for #679 ... ok
- test_basic.TestStruve.test_some_values ... ok
- Check Struve function versus its power series ... ok
- test_specialpoints (test_basic.TestTandg) ... ok
- test_tandg (test_basic.TestTandg) ... ok
- test_tandgmore (test_basic.TestTandg) ... ok
- test_0 (test_basic.TestTrigonometric) ... ok
- test_cbrt (test_basic.TestTrigonometric) ... ok
- test_cbrtmore (test_basic.TestTrigonometric) ... ok
- test_cosdg (test_basic.TestTrigonometric) ... ok
- test_cosdgmore (test_basic.TestTrigonometric) ... ok
- test_cosm1 (test_basic.TestTrigonometric) ... ok
- test_cotdg (test_basic.TestTrigonometric) ... ok
- test_cotdgmore (test_basic.TestTrigonometric) ... ok
- test_sinc (test_basic.TestTrigonometric) ... ok
- test_sindg (test_basic.TestTrigonometric) ... ok
- test_sindgmore (test_basic.TestTrigonometric) ... ok
- test_specialpoints (test_basic.TestTrigonometric) ... ok
- test_basic.test_sph_harm(array((0.28209479177387814+0j)), 0.28209479177387814) ... ok
- test_basic.test_sph_harm(array((0.19313710101159479+0j)), 0.19313710101159473) ... ok
- test_basic.test_sph_harm(array((0.38627420202318968+0j)), 0.38627420202318957) ... ok
- test_basic.test_sph_harm(array((0.38627420202318957-9.4606768423053307e-17j)), (0.38627420202318957-9.4606768423053307e-17j)) ... ok
- test_basic.test_sph_harm(array((1.1521668490919394e-17+0.18816934037548774j)), (1.1521668490919398e-17+0.18816934037548777j)) ... ok
- test_basic.test_sph_harm(array((1.6935260841945282e-18+0.027658293277811382j)), (1.6935260841945294e-18+0.027658293277811399j)) ... ok
- test_basic.test_chi2_smalldf ... ok
- test_basic.test_chi2c_smalldf ... ok
- test_basic.test_chi2_inv_smalldf ... ok
- test_data.test_boost(<Data for arccosh: acosh_data_ipp-acosh_data>,) ... ok
- test_data.test_boost(<Data for arccosh (complex): acosh_data_ipp-acosh_data>,) ... ok
- test_data.test_boost(<Data for arcsinh: asinh_data_ipp-asinh_data>,) ... ok
- test_data.test_boost(<Data for arcsinh (complex): asinh_data_ipp-asinh_data>,) ... ok
- test_data.test_boost(<Data for arctanh: atanh_data_ipp-atanh_data>,) ... ok
- test_data.test_boost(<Data for arctanh (complex): atanh_data_ipp-atanh_data>,) ... ok
- test_data.test_boost(<Data for beta: beta_exp_data_ipp-beta_exp_data>,) ... ok
- test_data.test_boost(<Data for beta: beta_exp_data_ipp-beta_exp_data>,) ... ok
- test_data.test_boost(<Data for beta: beta_small_data_ipp-beta_small_data>,) ... ok
- test_data.test_boost(<Data for cbrt: cbrt_data_ipp-cbrt_data>,) ... ok
- test_data.test_boost(<Data for psi: digamma_data_ipp-digamma_data>,) ... ok
- test_data.test_boost(<Data for psi (complex): digamma_data_ipp-digamma_data>,) ... ok
- test_data.test_boost(<Data for psi: digamma_neg_data_ipp-digamma_neg_data>,) ... ok
- test_data.test_boost(<Data for psi (complex): digamma_neg_data_ipp-digamma_neg_data>,) ... ok
- test_data.test_boost(<Data for psi: digamma_root_data_ipp-digamma_root_data>,) ... ok
- test_data.test_boost(<Data for psi (complex): digamma_root_data_ipp-digamma_root_data>,) ... ok
- test_data.test_boost(<Data for psi: digamma_small_data_ipp-digamma_small_data>,) ... ok
- test_data.test_boost(<Data for psi (complex): digamma_small_data_ipp-digamma_small_data>,) ... ok
- test_data.test_boost(<Data for ellipk_: ellint_k_data_ipp-ellint_k_data>,) ... ok
- test_data.test_boost(<Data for ellipe_: ellint_e_data_ipp-ellint_e_data>,) ... ok
- test_data.test_boost(<Data for ellipeinc_: ellint_e2_data_ipp-ellint_e2_data>,) ... ok
- test_data.test_boost(<Data for erf: erf_data_ipp-erf_data>,) ... ok
- test_data.test_boost(<Data for erf (complex): erf_data_ipp-erf_data>,) ... ok
- test_data.test_boost(<Data for erfc: erf_data_ipp-erf_data>,) ... ok
- test_data.test_boost(<Data for erf: erf_large_data_ipp-erf_large_data>,) ... ok
- test_data.test_boost(<Data for erf (complex): erf_large_data_ipp-erf_large_data>,) ... ok
- test_data.test_boost(<Data for erfc: erf_large_data_ipp-erf_large_data>,) ... Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for erf: erf_small_data_ipp-erf_small_data>,) ... Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for erf (complex): erf_small_data_ipp-erf_small_data>,) ... Warning: invalid value encountered in erf
- Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for erfc: erf_small_data_ipp-erf_small_data>,) ... ok
- test_data.test_boost(<Data for erfinv: erf_inv_data_ipp-erf_inv_data>,) ... ok
- test_data.test_boost(<Data for erfcinv: erfc_inv_data_ipp-erfc_inv_data>,) ... ok
- test_data.test_boost(<Data for exp1: expint_1_data_ipp-expint_1_data>,) ... ok
- test_data.test_boost(<Data for exp1 (complex): expint_1_data_ipp-expint_1_data>,) ... ok
- test_data.test_boost(<Data for expi: expinti_data_ipp-expinti_data>,) ... ok
- test_data.test_boost(<Data for expi: expinti_data_double_ipp-expinti_data_double>,) ... ok
- test_data.test_boost(<Data for expn: expint_small_data_ipp-expint_small_data>,) ... ok
- test_data.test_boost(<Data for expn: expint_data_ipp-expint_data>,) ... ok
- test_data.test_boost(<Data for gamma: test_gamma_data_ipp-near_0>,) ... ok
- test_data.test_boost(<Data for gamma: test_gamma_data_ipp-near_1>,) ... ok
- test_data.test_boost(<Data for gamma: test_gamma_data_ipp-near_2>,) ... ok
- test_data.test_boost(<Data for gamma: test_gamma_data_ipp-near_m10>,) ... ok
- test_data.test_boost(<Data for gamma: test_gamma_data_ipp-near_m55>,) ... ok
- test_data.test_boost(<Data for gamma (complex): test_gamma_data_ipp-near_0>,) ... ok
- test_data.test_boost(<Data for gamma (complex): test_gamma_data_ipp-near_1>,) ... ok
- test_data.test_boost(<Data for gamma (complex): test_gamma_data_ipp-near_2>,) ... ok
- test_data.test_boost(<Data for gamma (complex): test_gamma_data_ipp-near_m10>,) ... ok
- test_data.test_boost(<Data for gamma (complex): test_gamma_data_ipp-near_m55>,) ... ok
- test_data.test_boost(<Data for gammaln: test_gamma_data_ipp-near_0>,) ... ok
- test_data.test_boost(<Data for gammaln: test_gamma_data_ipp-near_1>,) ... Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for gammaln: test_gamma_data_ipp-near_2>,) ... Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for gammaln: test_gamma_data_ipp-near_m10>,) ... ok
- test_data.test_boost(<Data for gammaln: test_gamma_data_ipp-near_m55>,) ... ok
- test_data.test_boost(<Data for log1p: log1p_expm1_data_ipp-log1p_expm1_data>,) ... ok
- test_data.test_boost(<Data for expm1: log1p_expm1_data_ipp-log1p_expm1_data>,) ... ok
- test_data.test_boost(<Data for iv: bessel_i_data_ipp-bessel_i_data>,) ... Warning: overflow encountered in iv
- Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for iv (complex): bessel_i_data_ipp-bessel_i_data>,) ... Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for iv: bessel_i_int_data_ipp-bessel_i_int_data>,) ... Warning: overflow encountered in iv
- Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for iv (complex): bessel_i_int_data_ipp-bessel_i_int_data>,) ... Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for jv: bessel_j_int_data_ipp-bessel_j_int_data>,) ... ok
- test_data.test_boost(<Data for jv (complex): bessel_j_int_data_ipp-bessel_j_int_data>,) ... ok
- test_data.test_boost(<Data for jv: bessel_j_large_data_ipp-bessel_j_large_data>,) ... ok
- test_data.test_boost(<Data for jv (complex): bessel_j_large_data_ipp-bessel_j_large_data>,) ... ok
- test_data.test_boost(<Data for jv: bessel_j_int_data_ipp-bessel_j_int_data>,) ... ok
- test_data.test_boost(<Data for jv (complex): bessel_j_int_data_ipp-bessel_j_int_data>,) ... ok
- test_data.test_boost(<Data for jv: bessel_j_data_ipp-bessel_j_data>,) ... Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for jv (complex): bessel_j_data_ipp-bessel_j_data>,) ... Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for kn: bessel_k_int_data_ipp-bessel_k_int_data>,) ... KNOWNFAIL: Known bug in Cephes kn implementation
- test_data.test_boost(<Data for kv: bessel_k_int_data_ipp-bessel_k_int_data>,) ... Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for kv (complex): bessel_k_int_data_ipp-bessel_k_int_data>,) ... Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for kv: bessel_k_data_ipp-bessel_k_data>,) ... Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for kv (complex): bessel_k_data_ipp-bessel_k_data>,) ... Warning: invalid value encountered in divide
- ok
- test_data.test_boost(<Data for yn: bessel_y01_data_ipp-bessel_y01_data>,) ... ok
- test_data.test_boost(<Data for yn: bessel_yn_data_ipp-bessel_yn_data>,) ... ok
- test_data.test_boost(<Data for yv: bessel_yn_data_ipp-bessel_yn_data>,) ... ok
- test_data.test_boost(<Data for yv (complex): bessel_yn_data_ipp-bessel_yn_data>,) ... ok
- test_data.test_boost(<Data for yv: bessel_yv_data_ipp-bessel_yv_data>,) ... KNOWNFAIL: Known bug in Cephes yv implementation
- test_data.test_boost(<Data for yv (complex): bessel_yv_data_ipp-bessel_yv_data>,) ... ok
- test_data.test_boost(<Data for zeta_: zeta_data_ipp-zeta_data>,) ... ok
- test_data.test_boost(<Data for zeta_: zeta_neg_data_ipp-zeta_neg_data>,) ... ok
- test_data.test_boost(<Data for zeta_: zeta_1_up_data_ipp-zeta_1_up_data>,) ... ok
- test_data.test_boost(<Data for zeta_: zeta_1_below_data_ipp-zeta_1_below_data>,) ... ok
- test_data.test_boost(<Data for gammaincinv: gamma_inv_data_ipp-gamma_inv_data>,) ... ok
- test_data.test_boost(<Data for gammaincinv: gamma_inv_big_data_ipp-gamma_inv_big_data>,) ... ok
- test_lambertw.test_values ... Warning: invalid value encountered in subtract
- Warning: invalid value encountered in divide
- ok
- test_lambertw.test_ufunc ... ok
- test_mpmath.test_expi_complex ... SKIP: Skipping test: test_expi_complex
- mpmath library is not present
- test_mpmath.test_hyp2f1_strange_points ... SKIP: Skipping test: test_hyp2f1_strange_points
- mpmath library is not present
- test_mpmath.test_hyp2f1_real_some_points ... SKIP: Skipping test: test_hyp2f1_real_some_points
- mpmath library is not present
- test_mpmath.test_hyp2f1_some_points_2 ... SKIP: Skipping test: test_hyp2f1_some_points_2
- mpmath library is not present
- test_mpmath.test_hyp2f1_real_some ... SKIP: Skipping test: test_hyp2f1_real_some
- mpmath library is not present
- test_mpmath.test_erf_complex ... SKIP: Skipping test: test_erf_complex
- mpmath library is not present
- test_orthogonal.TestCall.test_call ... Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- ok
- test_chebyc (test_orthogonal.TestCheby) ... Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- ok
- test_chebys (test_orthogonal.TestCheby) ... ok
- test_chebyt (test_orthogonal.TestCheby) ... ok
- test_chebyu (test_orthogonal.TestCheby) ... ok
- test_gegenbauer (test_orthogonal.TestGegenbauer) ... ok
- test_hermite (test_orthogonal.TestHermite) ... ok
- test_hermitenorm (test_orthogonal.TestHermite) ... ok
- test_orthogonal_eval.TestPolys.test_chebyc ... Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- ok
- test_orthogonal_eval.TestPolys.test_chebys ... ok
- test_orthogonal_eval.TestPolys.test_chebyt ... ok
- test_orthogonal_eval.TestPolys.test_chebyu ... ok
- test_orthogonal_eval.TestPolys.test_gegenbauer ... ok
- test_orthogonal_eval.TestPolys.test_genlaguerre ... ok
- test_orthogonal_eval.TestPolys.test_hermite ... ok
- test_orthogonal_eval.TestPolys.test_hermitenorm ... ok
- test_orthogonal_eval.TestPolys.test_jacobi ... ok
- test_orthogonal_eval.TestPolys.test_laguerre ... ok
- test_orthogonal_eval.TestPolys.test_legendre ... ok
- test_orthogonal_eval.TestPolys.test_sh_chebyt ... Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- ok
- test_orthogonal_eval.TestPolys.test_sh_chebyu ... ok
- test_orthogonal_eval.TestPolys.test_sh_jacobi ... ok
- test_orthogonal_eval.TestPolys.test_sh_legendre ... Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- Warning: invalid value encountered in divide
- ok
- test_orthogonal_eval.test_eval_chebyt ... ok
- test1 (test_spfun_stats.TestMultiGammaLn) ... ok
- test_ararg (test_spfun_stats.TestMultiGammaLn) ... ok
- test_bararg (test_spfun_stats.TestMultiGammaLn) ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x9f4986c>, (3.5704770516650459,), array(inf), array(inf), 0.31772708039386738, 0.021186836778540892, 1000, 'alphasample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x9f4986c>, (3.5704770516650459,), array(inf), array(inf), 'alpha') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x9f4986c>, (3.5704770516650459,), 'alpha') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x9f4986c>, (3.5704770516650459,), 'alpha') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x9f4986c>, (3.5704770516650459,), 'alpha') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x9f4986c>, (3.5704770516650459,), 'alpha') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x9f4986c>, (3.5704770516650459,), 'alpha') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.alpha_gen object at 0x9f4986c>, (3.5704770516650459,), 'alpha') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x9f4996c>, (), array(0.0), array(0.11685027506808487), 0.019485173966289543, 0.11461131582481676, 1000, 'anglitsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x9f4996c>, (), array(0.0), array(0.11685027506808487), 'anglit') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x9f4996c>, (), 'anglit') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x9f4996c>, (), 'anglit') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x9f4996c>, (), 'anglit') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x9f4996c>, (), 'anglit') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x9f4996c>, (), 'anglit') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.anglit_gen object at 0x9f4996c>, (), 'anglit') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x9f49a2c>, (), array(0.5), array(0.125), 0.51691545030819286, 0.12586663168201145, 1000, 'arcsinesample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x9f49a2c>, (), array(0.5), array(0.125), 'arcsine') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x9f49a2c>, (), 'arcsine') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x9f49a2c>, (), 'arcsine') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x9f49a2c>, (), 'arcsine') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x9f49a2c>, (), 'arcsine') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x9f49a2c>, (), 'arcsine') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.arcsine_gen object at 0x9f49a2c>, (), 'arcsine') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x9f49acc>, (2.3098496451481823, 0.62687954300963677), array(0.78653818488354665), array(0.04264856955583702), 0.78396526766379815, 0.045854302817001986, 1000, 'betasample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x9f49acc>, (2.3098496451481823, 0.62687954300963677), array(0.78653818488354665), array(0.04264856955583702), 'beta') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x9f49acc>, (2.3098496451481823, 0.62687954300963677), 'beta') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x9f49acc>, (2.3098496451481823, 0.62687954300963677), 'beta') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x9f49acc>, (2.3098496451481823, 0.62687954300963677), 'beta') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x9f49acc>, (2.3098496451481823, 0.62687954300963677), 'beta') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x9f49acc>, (2.3098496451481823, 0.62687954300963677), 'beta') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.beta_gen object at 0x9f49acc>, (2.3098496451481823, 0.62687954300963677), 'beta') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x9f49c4c>, (5, 6), array(1.0), array(0.5), 0.96080765058071127, 0.47274240606696388, 1000, 'betaprimesample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x9f49c4c>, (5, 6), array(1.0), array(0.5), 'betaprime') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x9f49c4c>, (5, 6), 'betaprime') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x9f49c4c>, (5, 6), 'betaprime') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x9f49c4c>, (5, 6), 'betaprime') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x9f49c4c>, (5, 6), 'betaprime') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x9f49c4c>, (5, 6), 'betaprime') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.betaprime_gen object at 0x9f49c4c>, (5, 6), 'betaprime') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x9f49d0c>, (0.29891359763170633,), array(0.47823078529291196), array(0.083238491922311225), 0.49336924420907019, 0.083341918695194112, 1000, 'bradfordsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x9f49d0c>, (0.29891359763170633,), array(0.47823078529291196), array(0.083238491922311225), 'bradford') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x9f49d0c>, (0.29891359763170633,), 'bradford') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x9f49d0c>, (0.29891359763170633,), 'bradford') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x9f49d0c>, (0.29891359763170633,), 'bradford') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x9f49d0c>, (0.29891359763170633,), 'bradford') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x9f49d0c>, (0.29891359763170633,), 'bradford') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.bradford_gen object at 0x9f49d0c>, (0.29891359763170633,), 'bradford') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x9f49e6c>, (10.5, 4.2999999999999998), array(1.2109372989617824), array(0.02914827276568499), 1.2204374750635179, 0.030007409783013299, 1000, 'burrsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x9f49e6c>, (10.5, 4.2999999999999998), array(1.2109372989617824), array(0.02914827276568499), 'burr') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x9f49e6c>, (10.5, 4.2999999999999998), 'burr') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x9f49e6c>, (10.5, 4.2999999999999998), 'burr') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x9f49e6c>, (10.5, 4.2999999999999998), 'burr') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x9f49e6c>, (10.5, 4.2999999999999998), 'burr') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x9f49e6c>, (10.5, 4.2999999999999998), 'burr') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.burr_gen object at 0x9f49e6c>, (10.5, 4.2999999999999998), 'burr') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x9f510ac>, (), array(inf), array(inf), 1.5526458878695526, 327.63988189221948, 1000, 'cauchysample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x9f510ac>, (), array(inf), array(inf), 'cauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x9f510ac>, (), 'cauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x9f510ac>, (), 'cauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x9f510ac>, (), 'cauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x9f510ac>, (), 'cauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x9f510ac>, (), 'cauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.cauchy_gen object at 0x9f510ac>, (), 'cauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x9f511ac>, (78,), array(8.8035000285242742), array(0.49838724777310972), 8.7666853364107968, 0.46130946026199121, 1000, 'chisample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x9f511ac>, (78,), array(8.8035000285242742), array(0.49838724777310972), 'chi') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x9f511ac>, (78,), 'chi') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x9f511ac>, (78,), 'chi') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x9f511ac>, (78,), 'chi') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x9f511ac>, (78,), 'chi') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x9f511ac>, (78,), 'chi') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi_gen object at 0x9f511ac>, (78,), 'chi') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x9f512ac>, (55,), array(55.0), array(110.0), 54.443237765581792, 99.925909007064973, 1000, 'chi2sample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x9f512ac>, (55,), array(55.0), array(110.0), 'chi2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x9f512ac>, (55,), 'chi2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x9f512ac>, (55,), 'chi2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x9f512ac>, (55,), 'chi2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x9f512ac>, (55,), 'chi2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x9f512ac>, (55,), 'chi2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.chi2_gen object at 0x9f512ac>, (55,), 'chi2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x9f514ac>, (1.1023326088288166,), array(0.0), array(2.3174697893161609), 0.058649521093078805, 2.2265558396676184, 1000, 'dgammasample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x9f514ac>, (1.1023326088288166,), array(0.0), array(2.3174697893161609), 'dgamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x9f514ac>, (1.1023326088288166,), 'dgamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x9f514ac>, (1.1023326088288166,), 'dgamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x9f514ac>, (1.1023326088288166,), 'dgamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x9f514ac>, (1.1023326088288166,), 'dgamma') ... Warning: divide by zero encountered in log
- ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x9f514ac>, (1.1023326088288166,), 'dgamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dgamma_gen object at 0x9f514ac>, (1.1023326088288166,), 'dgamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x9f5152c>, (2.0685080649914673,), array(0.0), array(0.98644644671326842), 0.03640005212926381, 0.9580928500389827, 1000, 'dweibullsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x9f5152c>, (2.0685080649914673,), array(0.0), array(0.98644644671326842), 'dweibull') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x9f5152c>, (2.0685080649914673,), 'dweibull') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x9f5152c>, (2.0685080649914673,), 'dweibull') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x9f5152c>, (2.0685080649914673,), 'dweibull') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x9f5152c>, (2.0685080649914673,), 'dweibull') ... Warning: divide by zero encountered in log
- ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x9f5152c>, (2.0685080649914673,), 'dweibull') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.dweibull_gen object at 0x9f5152c>, (2.0685080649914673,), 'dweibull') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x9f516ac>, (20,), array(20.0), array(20.0), 19.759095772201878, 18.118858828066088, 1000, 'erlangsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x9f516ac>, (20,), array(20.0), array(20.0), 'erlang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x9f516ac>, (20,), 'erlang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x9f516ac>, (20,), 'erlang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x9f516ac>, (20,), 'erlang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x9f516ac>, (20,), 'erlang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x9f516ac>, (20,), 'erlang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.erlang_gen object at 0x9f516ac>, (20,), 'erlang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x9f517ac>, (), array(1.0), array(1.0), 1.0489197735650717, 1.0635814072598191, 1000, 'exponsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x9f517ac>, (), array(1.0), array(1.0), 'expon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x9f517ac>, (), 'expon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x9f517ac>, (), 'expon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x9f517ac>, (), 'expon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x9f517ac>, (), 'expon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x9f517ac>, (), 'expon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.expon_gen object at 0x9f517ac>, (), 'expon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x9f4908c>, (2.697119160358469,), array(0.76622330667382488), array(0.05900404926303171), 0.78088147091689719, 0.055982343857351263, 1000, 'exponpowsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x9f4908c>, (2.697119160358469,), array(0.76622330667382488), array(0.05900404926303171), 'exponpow') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x9f4908c>, (2.697119160358469,), 'exponpow') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x9f4908c>, (2.697119160358469,), 'exponpow') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x9f4908c>, (2.697119160358469,), 'exponpow') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x9f4908c>, (2.697119160358469,), 'exponpow') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x9f4908c>, (2.697119160358469,), 'exponpow') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponpow_gen object at 0x9f4908c>, (2.697119160358469,), 'exponpow') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x9f518ac>, (2.8923945291034436, 1.9505288745913174), array(1.2873418037984079), array(0.18119174498960655), 1.3122933415946192, 0.18047748963723559, 1000, 'exponweibsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x9f518ac>, (2.8923945291034436, 1.9505288745913174), array(1.2873418037984079), array(0.18119174498960655), 'exponweib') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x9f518ac>, (2.8923945291034436, 1.9505288745913174), 'exponweib') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x9f518ac>, (2.8923945291034436, 1.9505288745913174), 'exponweib') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x9f518ac>, (2.8923945291034436, 1.9505288745913174), 'exponweib') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x9f518ac>, (2.8923945291034436, 1.9505288745913174), 'exponweib') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x9f518ac>, (2.8923945291034436, 1.9505288745913174), 'exponweib') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.exponweib_gen object at 0x9f518ac>, (2.8923945291034436, 1.9505288745913174), 'exponweib') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x9f51c8c>, (29, 18), array(1.125), array(0.2805572660098522), 1.1043635143445394, 0.26689745386425451, 1000, 'fsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x9f51c8c>, (29, 18), array(1.125), array(0.2805572660098522), 'f') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x9f51c8c>, (29, 18), 'f') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x9f51c8c>, (29, 18), 'f') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x9f51c8c>, (29, 18), 'f') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x9f51c8c>, (29, 18), 'f') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x9f51c8c>, (29, 18), 'f') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.f_gen object at 0x9f51c8c>, (29, 18), 'f') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x9f51a6c>, (29,), array(421.5), array(884942.25), 381.5231692182968, 659709.81429483288, 1000, 'fatiguelifesample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x9f51a6c>, (29,), array(421.5), array(884942.25), 'fatiguelife') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x9f51a6c>, (29,), 'fatiguelife') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x9f51a6c>, (29,), 'fatiguelife') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x9f51a6c>, (29,), 'fatiguelife') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x9f51a6c>, (29,), 'fatiguelife') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x9f51a6c>, (29,), 'fatiguelife') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fatiguelife_gen object at 0x9f51a6c>, (29,), 'fatiguelife') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x9f49f8c>, (3.0857548622253179,), array(1.1961976340331102), array(0.84763509403100734), 1.2366804437236738, 0.81012589838120341, 1000, 'fisksample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x9f49f8c>, (3.0857548622253179,), array(1.1961976340331102), array(0.84763509403100734), 'fisk') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x9f49f8c>, (3.0857548622253179,), 'fisk') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x9f49f8c>, (3.0857548622253179,), 'fisk') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x9f49f8c>, (3.0857548622253179,), 'fisk') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x9f49f8c>, (3.0857548622253179,), 'fisk') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x9f49f8c>, (3.0857548622253179,), 'fisk') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.fisk_gen object at 0x9f49f8c>, (3.0857548622253179,), 'fisk') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x9f51b8c>, (4.7164673455831894,), array(inf), array(inf), 7.1128596673275517, 316.34888997897679, 1000, 'foldcauchysample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x9f51b8c>, (4.7164673455831894,), array(inf), array(inf), 'foldcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x9f51b8c>, (4.7164673455831894,), 'foldcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x9f51b8c>, (4.7164673455831894,), 'foldcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x9f51b8c>, (4.7164673455831894,), 'foldcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x9f51b8c>, (4.7164673455831894,), 'foldcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x9f51b8c>, (4.7164673455831894,), 'foldcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldcauchy_gen object at 0x9f51b8c>, (4.7164673455831894,), 'foldcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x9f51d8c>, (1.9521253373555869,), array(1.97141281966251), array(0.92432482721597609), 1.9485668609369065, 0.89445098899947073, 1000, 'foldnormsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x9f51d8c>, (1.9521253373555869,), array(1.97141281966251), array(0.92432482721597609), 'foldnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x9f51d8c>, (1.9521253373555869,), 'foldnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x9f51d8c>, (1.9521253373555869,), 'foldnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x9f51d8c>, (1.9521253373555869,), 'foldnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x9f51d8c>, (1.9521253373555869,), 'foldnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x9f51d8c>, (1.9521253373555869,), 'foldnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.foldnorm_gen object at 0x9f51d8c>, (1.9521253373555869,), 'foldnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5608c>, (3.6279911255583239,), array(-0.9014841669765834), array(0.076288054283962903), -0.88452420295607126, 0.07344496156832396, 1000, 'frechet_lsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5608c>, (3.6279911255583239,), array(-0.9014841669765834), array(0.076288054283962903), 'frechet_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5608c>, (3.6279911255583239,), 'frechet_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5608c>, (3.6279911255583239,), 'frechet_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5608c>, (3.6279911255583239,), 'frechet_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5608c>, (3.6279911255583239,), 'frechet_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5608c>, (3.6279911255583239,), 'frechet_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5608c>, (3.6279911255583239,), 'frechet_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51e8c>, (1.8928171603534227,), array(0.88747270666698841), array(0.23766896745884458), 0.91443119143867402, 0.24138404811476447, 1000, 'frechet_rsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51e8c>, (1.8928171603534227,), array(0.88747270666698841), array(0.23766896745884458), 'frechet_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51e8c>, (1.8928171603534227,), 'frechet_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51e8c>, (1.8928171603534227,), 'frechet_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51e8c>, (1.8928171603534227,), 'frechet_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51e8c>, (1.8928171603534227,), 'frechet_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51e8c>, (1.8928171603534227,), 'frechet_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51e8c>, (1.8928171603534227,), 'frechet_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x9f5666c>, (1.9932305483800778,), array(1.9932305483800778), array(1.9932305483800778), 1.9049475453784122, 1.6832872321787387, 1000, 'gammasample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x9f5666c>, (1.9932305483800778,), array(1.9932305483800778), array(1.9932305483800778), 'gamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x9f5666c>, (1.9932305483800778,), 'gamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x9f5666c>, (1.9932305483800778,), 'gamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x9f5666c>, (1.9932305483800778,), 'gamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x9f5666c>, (1.9932305483800778,), 'gamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x9f5666c>, (1.9932305483800778,), 'gamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gamma_gen object at 0x9f5666c>, (1.9932305483800778,), 'gamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x9f5656c>, (-0.10000000000000001,), array(0.68628702119319185), array(2.2262410732082651), 0.76598002574841639, 2.3195034224827271, 1000, 'genextremesample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x9f5656c>, (-0.10000000000000001,), array(0.68628702119319185), array(2.2262410732082651), 'genextreme') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x9f5656c>, (-0.10000000000000001,), 'genextreme') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x9f5656c>, (-0.10000000000000001,), 'genextreme') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x9f5656c>, (-0.10000000000000001,), 'genextreme') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x9f5656c>, (-0.10000000000000001,), 'genextreme') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x9f5656c>, (-0.10000000000000001,), 'genextreme') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genextreme_gen object at 0x9f5656c>, (-0.10000000000000001,), 'genextreme') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x9f5668c>, (4.4162385429431925, 3.1193091679242761), array(1.5702162249275609), array(0.060317549758582167), 1.5854913681198328, 0.057829220024230743, 1000, 'gengammasample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x9f5668c>, (4.4162385429431925, 3.1193091679242761), array(1.5702162249275609), array(0.060317549758582167), 'gengamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x9f5668c>, (4.4162385429431925, 3.1193091679242761), 'gengamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x9f5668c>, (4.4162385429431925, 3.1193091679242761), 'gengamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x9f5668c>, (4.4162385429431925, 3.1193091679242761), 'gengamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x9f5668c>, (4.4162385429431925, 3.1193091679242761), 'gengamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x9f5668c>, (4.4162385429431925, 3.1193091679242761), 'gengamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gengamma_gen object at 0x9f5668c>, (4.4162385429431925, 3.1193091679242761), 'gengamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x9f567cc>, (0.77274727809929322,), array(0.70597656450848112), array(0.12459765121103794), 0.72486157273526908, 0.1219347345196404, 1000, 'genhalflogisticsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x9f567cc>, (0.77274727809929322,), array(0.70597656450848112), array(0.12459765121103794), 'genhalflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x9f567cc>, (0.77274727809929322,), 'genhalflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x9f567cc>, (0.77274727809929322,), 'genhalflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x9f567cc>, (0.77274727809929322,), 'genhalflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x9f567cc>, (0.77274727809929322,), 'genhalflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x9f567cc>, (0.77274727809929322,), 'genhalflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genhalflogistic_gen object at 0x9f567cc>, (0.77274727809929322,), 'genhalflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x9f5624c>, (0.41192440799679475,), array(-1.8996417990533176), array(8.5520107632574316), -1.6915023776411082, 7.2701839656308893, 1000, 'genlogisticsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x9f5624c>, (0.41192440799679475,), array(-1.8996417990533176), array(8.5520107632574316), 'genlogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x9f5624c>, (0.41192440799679475,), 'genlogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x9f5624c>, (0.41192440799679475,), 'genlogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x9f5624c>, (0.41192440799679475,), 'genlogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x9f5624c>, (0.41192440799679475,), 'genlogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x9f5624c>, (0.41192440799679475,), 'genlogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genlogistic_gen object at 0x9f5624c>, (0.41192440799679475,), 'genlogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x9f5636c>, (0.10000000000000001,), array(1.1111111111111116), array(1.543209876543199), 1.1693857515263724, 1.6532801760783784, 1000, 'genparetosample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x9f5636c>, (0.10000000000000001,), array(1.1111111111111116), array(1.543209876543199), 'genpareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x9f5636c>, (0.10000000000000001,), 'genpareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x9f5636c>, (0.10000000000000001,), 'genpareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x9f5636c>, (0.10000000000000001,), 'genpareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x9f5636c>, (0.10000000000000001,), 'genpareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x9f5636c>, (0.10000000000000001,), 'genpareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.genpareto_gen object at 0x9f5636c>, (0.10000000000000001,), 'genpareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x9f5f8ec>, (), array(1.6487212707001282), array(4.670774270471604), 1.5542857947354745, 3.0177319205419812, 1000, 'gilbratsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x9f5f8ec>, (), array(1.6487212707001282), array(4.670774270471604), 'gilbrat') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x9f5f8ec>, (), 'gilbrat') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x9f5f8ec>, (), 'gilbrat') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x9f5f8ec>, (), 'gilbrat') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x9f5f8ec>, (), 'gilbrat') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x9f5f8ec>, (), 'gilbrat') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gilbrat_gen object at 0x9f5f8ec>, (), 'gilbrat') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x9f568ec>, (0.94743713075105251,), array(0.61842381762891141), array(0.18616258957403664), 0.64114216641328881, 0.19073684302906715, 1000, 'gompertzsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x9f568ec>, (0.94743713075105251,), array(0.61842381762891141), array(0.18616258957403664), 'gompertz') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x9f568ec>, (0.94743713075105251,), 'gompertz') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x9f568ec>, (0.94743713075105251,), 'gompertz') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x9f568ec>, (0.94743713075105251,), 'gompertz') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x9f568ec>, (0.94743713075105251,), 'gompertz') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x9f568ec>, (0.94743713075105251,), 'gompertz') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gompertz_gen object at 0x9f568ec>, (0.94743713075105251,), 'gompertz') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x9f56a0c>, (), array(-0.57721566490153287), array(1.6449340668482264), -0.48770832402349995, 1.4031452475835418, 1000, 'gumbel_lsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x9f56a0c>, (), array(-0.57721566490153287), array(1.6449340668482264), 'gumbel_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x9f56a0c>, (), 'gumbel_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x9f56a0c>, (), 'gumbel_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x9f56a0c>, (), 'gumbel_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x9f56a0c>, (), 'gumbel_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x9f56a0c>, (), 'gumbel_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_l_gen object at 0x9f56a0c>, (), 'gumbel_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x9f569cc>, (), array(0.57721566490153287), array(1.6449340668482264), 0.64936088543269987, 1.6827982006295097, 1000, 'gumbel_rsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x9f569cc>, (), array(0.57721566490153287), array(1.6449340668482264), 'gumbel_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x9f569cc>, (), 'gumbel_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x9f569cc>, (), 'gumbel_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x9f569cc>, (), 'gumbel_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x9f569cc>, (), 'gumbel_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x9f569cc>, (), 'gumbel_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.gumbel_r_gen object at 0x9f569cc>, (), 'gumbel_r') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x9f56b0c>, (), array(inf), array(inf), 5.8851391398051529, 1194.9588343167102, 1000, 'halfcauchysample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x9f56b0c>, (), array(inf), array(inf), 'halfcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x9f56b0c>, (), 'halfcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x9f56b0c>, (), 'halfcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x9f56b0c>, (), 'halfcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x9f56b0c>, (), 'halfcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x9f56b0c>, (), 'halfcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfcauchy_gen object at 0x9f56b0c>, (), 'halfcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x9f56bcc>, (), array(1.3862943611198906), array(1.3680560780236473), 1.445669360439183, 1.4370223442716132, 1000, 'halflogisticsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x9f56bcc>, (), array(1.3862943611198906), array(1.3680560780236473), 'halflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x9f56bcc>, (), 'halflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x9f56bcc>, (), 'halflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x9f56bcc>, (), 'halflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x9f56bcc>, (), 'halflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x9f56bcc>, (), 'halflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halflogistic_gen object at 0x9f56bcc>, (), 'halflogistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x9f56c8c>, (), array(0.79788456080286541), array(0.36338022763241862), 0.7895392823931896, 0.34253579133614614, 1000, 'halfnormsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x9f56c8c>, (), array(0.79788456080286541), array(0.36338022763241862), 'halfnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x9f56c8c>, (), 'halfnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x9f56c8c>, (), 'halfnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x9f56c8c>, (), 'halfnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x9f56c8c>, (), 'halfnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x9f56c8c>, (), 'halfnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.halfnorm_gen object at 0x9f56c8c>, (), 'halfnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x9f56d4c>, (), array(0.0), array(2.4674011002723395), 0.10651732466849632, 2.2821454925062783, 1000, 'hypsecantsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x9f56d4c>, (), array(0.0), array(2.4674011002723395), 'hypsecant') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x9f56d4c>, (), 'hypsecant') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x9f56d4c>, (), 'hypsecant') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x9f56d4c>, (), 'hypsecant') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x9f56d4c>, (), 'hypsecant') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x9f56d4c>, (), 'hypsecant') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.hypsecant_gen object at 0x9f56d4c>, (), 'hypsecant') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x9f56ecc>, (2.0668996136993067,), array(0.93729530609975309), array(13.131951625091871), 0.98003361245261911, 2.2163927217803856, 1000, 'invgammasample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x9f56ecc>, (2.0668996136993067,), array(0.93729530609975309), array(13.131951625091871), 'invgamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x9f56ecc>, (2.0668996136993067,), 'invgamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x9f56ecc>, (2.0668996136993067,), 'invgamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x9f56ecc>, (2.0668996136993067,), 'invgamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x9f56ecc>, (2.0668996136993067,), 'invgamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x9f56ecc>, (2.0668996136993067,), 'invgamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invgamma_gen object at 0x9f56ecc>, (2.0668996136993067,), 'invgamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invnorm_gen object at 0x9f56fcc>, (0.14546264555347513,), array(0.14546264555347513), array(0.0030778995751055637), 0.14654162671350618, 0.002904205822954576, 1000, 'invnormsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invnorm_gen object at 0x9f56fcc>, (0.14546264555347513,), array(0.14546264555347513), array(0.0030778995751055637), 'invnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invnorm_gen object at 0x9f56fcc>, (0.14546264555347513,), 'invnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invnorm_gen object at 0x9f56fcc>, (0.14546264555347513,), 'invnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invnorm_gen object at 0x9f56fcc>, (0.14546264555347513,), 'invnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invnorm_gen object at 0x9f56fcc>, (0.14546264555347513,), 'invnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invnorm_gen object at 0x9f56fcc>, (0.14546264555347513,), 'invnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.invnorm_gen object at 0x9f56fcc>, (0.14546264555347513,), 'invnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x9f5f14c>, (4.3172675099141058, 3.1837781130785063), array(0.20952073643389141), array(0.0026608544463240791), 0.21254860453459296, 0.002650284972435924, 1000, 'johnsonsbsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x9f5f14c>, (4.3172675099141058, 3.1837781130785063), array(0.20952073643389141), array(0.0026608544463240791), 'johnsonsb') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x9f5f14c>, (4.3172675099141058, 3.1837781130785063), 'johnsonsb') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x9f5f14c>, (4.3172675099141058, 3.1837781130785063), 'johnsonsb') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x9f5f14c>, (4.3172675099141058, 3.1837781130785063), 'johnsonsb') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x9f5f14c>, (4.3172675099141058, 3.1837781130785063), 'johnsonsb') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x9f5f14c>, (4.3172675099141058, 3.1837781130785063), 'johnsonsb') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.johnsonsb_gen object at 0x9f5f14c>, (4.3172675099141058, 3.1837781130785063), 'johnsonsb') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x9f5f2cc>, (), array(0.0), array(2.0), 0.098100813619853122, 1.8262500606297387, 1000, 'laplacesample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x9f5f2cc>, (), array(0.0), array(2.0), 'laplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x9f5f2cc>, (), 'laplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x9f5f2cc>, (), 'laplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x9f5f2cc>, (), 'laplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x9f5f2cc>, (), 'laplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x9f5f2cc>, (), 'laplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.laplace_gen object at 0x9f5f2cc>, (), 'laplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x9f5f30c>, (), array(inf), array(inf), 1932.0205477129177, 578434680.15985334, 1000, 'levysample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x9f5f30c>, (), array(inf), array(inf), 'levy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x9f5f30c>, (), 'levy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x9f5f30c>, (), 'levy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x9f5f30c>, (), 'levy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x9f5f30c>, (), 'levy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x9f5f30c>, (), 'levy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_gen object at 0x9f5f30c>, (), 'levy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x9f5f42c>, (), array(inf), array(inf), -146.03264446610149, 5369822.6715052985, 1000, 'levy_lsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x9f5f42c>, (), array(inf), array(inf), 'levy_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x9f5f42c>, (), 'levy_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x9f5f42c>, (), 'levy_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x9f5f42c>, (), 'levy_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x9f5f42c>, (), 'levy_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x9f5f42c>, (), 'levy_l') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.levy_l_gen object at 0x9f5f42c>, (), 'levy_l') ... ok
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x9f5f6ac>, (0.41411931826052117,), array(-2.4617679388246936), array(6.8426502245961025), -2.4057296757832169, 5.9831621683265697, 1000, 'loggammasample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x9f5f6ac>, (0.41411931826052117,), array(-2.4617679388246936), array(6.8426502245961025), 'loggamma') ... Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x9f5f6ac>, (0.41411931826052117,), 'loggamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x9f5f6ac>, (0.41411931826052117,), 'loggamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x9f5f6ac>, (0.41411931826052117,), 'loggamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x9f5f6ac>, (0.41411931826052117,), 'loggamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x9f5f6ac>, (0.41411931826052117,), 'loggamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loggamma_gen object at 0x9f5f6ac>, (0.41411931826052117,), 'loggamma') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x9f5f5ac>, (), array(0.0), array(3.2898681336964528), 0.12005549995830977, 3.0789850583848901, 1000, 'logisticsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x9f5f5ac>, (), array(0.0), array(3.2898681336964528), 'logistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x9f5f5ac>, (), 'logistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x9f5f5ac>, (), 'logistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x9f5f5ac>, (), 'logistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x9f5f5ac>, (), 'logistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x9f5f5ac>, (), 'logistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.logistic_gen object at 0x9f5f5ac>, (), 'logistic') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x9f5f72c>, (3.2505926592051435,), array(1.1045330480739952), array(0.38917293304417666), 1.1334773520725607, 0.37349384621458176, 1000, 'loglaplacesample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x9f5f72c>, (3.2505926592051435,), array(1.1045330480739952), array(0.38917293304417666), 'loglaplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x9f5f72c>, (3.2505926592051435,), 'loglaplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x9f5f72c>, (3.2505926592051435,), 'loglaplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x9f5f72c>, (3.2505926592051435,), 'loglaplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x9f5f72c>, (3.2505926592051435,), 'loglaplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x9f5f72c>, (3.2505926592051435,), 'loglaplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.loglaplace_gen object at 0x9f5f72c>, (3.2505926592051435,), 'loglaplace') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x9f5f7ec>, (0.95368226960575331,), array(1.5757871665018548), array(3.6827062109137709), 1.493598084343392, 2.4720855647743405, 1000, 'lognormsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x9f5f7ec>, (0.95368226960575331,), array(1.5757871665018548), array(3.6827062109137709), 'lognorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x9f5f7ec>, (0.95368226960575331,), 'lognorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x9f5f7ec>, (0.95368226960575331,), 'lognorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x9f5f7ec>, (0.95368226960575331,), 'lognorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x9f5f7ec>, (0.95368226960575331,), 'lognorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x9f5f7ec>, (0.95368226960575331,), 'lognorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lognorm_gen object at 0x9f5f7ec>, (0.95368226960575331,), 'lognorm') ... ok
- Warning: invalid value encountered in sqrt
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x9f5ff8c>, (1.8771398388773268,), array(1.1400690695795155), array(inf), 1.2046982570012685, 8.1205985026367316, 1000, 'lomaxsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x9f5ff8c>, (1.8771398388773268,), array(1.1400690695795155), array(inf), 'lomax') ... Warning: invalid value encountered in sqrt
- Warning: invalid value encountered in sqrt
- ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x9f5ff8c>, (1.8771398388773268,), 'lomax') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x9f5ff8c>, (1.8771398388773268,), 'lomax') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x9f5ff8c>, (1.8771398388773268,), 'lomax') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x9f5ff8c>, (1.8771398388773268,), 'lomax') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x9f5ff8c>, (1.8771398388773268,), 'lomax') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.lomax_gen object at 0x9f5ff8c>, (1.8771398388773268,), 'lomax') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x9f5f92c>, (), array(1.5957691216057308), array(0.45352091052967447), 1.5580947217508436, 0.41026340192631594, 1000, 'maxwellsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x9f5f92c>, (), array(1.5957691216057308), array(0.45352091052967447), 'maxwell') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x9f5f92c>, (), 'maxwell') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x9f5f92c>, (), 'maxwell') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x9f5f92c>, (), 'maxwell') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x9f5f92c>, (), 'maxwell') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x9f5f92c>, (), 'maxwell') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.maxwell_gen object at 0x9f5f92c>, (), 'maxwell') ... ok
- /usr/lib/python2.6/site-packages/scipy/stats/distributions.py:3628: SpecialFunctionWarning: gammaincinv: failed to converge at (a, y) = (4.9673794866666236558, 0.22373737420826877997): got 3.1975 +- 3.99724e-07, code 3
- return sqrt(1.0/nu*special.gammaincinv(nu,q))
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x9f5faac>, (4.9673794866666237,), array(0.97519075370169728), array(0.04900299389471563), nan, nan, 1000, 'nakagamisample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x9f5faac>, (4.9673794866666237,), array(0.97519075370169728), array(0.04900299389471563), 'nakagami') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x9f5faac>, (4.9673794866666237,), 'nakagami') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x9f5faac>, (4.9673794866666237,), 'nakagami') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x9f5faac>, (4.9673794866666237,), 'nakagami') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x9f5faac>, (4.9673794866666237,), 'nakagami') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x9f5faac>, (4.9673794866666237,), 'nakagami') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nakagami_gen object at 0x9f5faac>, (4.9673794866666237,), 'nakagami') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x9f5fcac>, (27, 27, 0.41578441799226107), array(1.0966313767196905), array(0.19835325341303081), 1.0759414510260821, 0.18247641865181691, 1000, 'ncfsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x9f5fcac>, (27, 27, 0.41578441799226107), array(1.0966313767196905), array(0.19835325341303081), 'ncf') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x9f5fcac>, (27, 27, 0.41578441799226107), 'ncf') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x9f5fcac>, (27, 27, 0.41578441799226107), 'ncf') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x9f5fcac>, (27, 27, 0.41578441799226107), 'ncf') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x9f5fcac>, (27, 27, 0.41578441799226107), 'ncf') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x9f5fcac>, (27, 27, 0.41578441799226107), 'ncf') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncf_gen object at 0x9f5fcac>, (27, 27, 0.41578441799226107), 'ncf') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x9f5fdcc>, (14, 0.24045031331198066), array(0.25436732738327772), array(1.1694163414603562), 0.2391750701345105, 1.0714795483341117, 1000, 'nctsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x9f5fdcc>, (14, 0.24045031331198066), array(0.25436732738327772), array(1.1694163414603562), 'nct') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x9f5fdcc>, (14, 0.24045031331198066), 'nct') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x9f5fdcc>, (14, 0.24045031331198066), 'nct') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x9f5fdcc>, (14, 0.24045031331198066), 'nct') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x9f5fdcc>, (14, 0.24045031331198066), 'nct') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x9f5fdcc>, (14, 0.24045031331198066), 'nct') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.nct_gen object at 0x9f5fdcc>, (14, 0.24045031331198066), 'nct') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x9f5fbac>, (21, 1.0560465975116415), array(22.056046597511642), array(46.224186390046569), 22.092814053046375, 48.38458031593926, 1000, 'ncx2sample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x9f5fbac>, (21, 1.0560465975116415), array(22.056046597511642), array(46.224186390046569), 'ncx2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x9f5fbac>, (21, 1.0560465975116415), 'ncx2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x9f5fbac>, (21, 1.0560465975116415), 'ncx2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x9f5fbac>, (21, 1.0560465975116415), 'ncx2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x9f5fbac>, (21, 1.0560465975116415), 'ncx2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x9f5fbac>, (21, 1.0560465975116415), 'ncx2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.ncx2_gen object at 0x9f5fbac>, (21, 1.0560465975116415), 'ncx2') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x9f4974c>, (), array(0.0), array(1.0), -0.021857613430289077, 0.96543031451323102, 1000, 'normsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x9f4974c>, (), array(0.0), array(1.0), 'norm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x9f4974c>, (), 'norm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x9f4974c>, (), 'norm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x9f4974c>, (), 'norm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x9f4974c>, (), 'norm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x9f4974c>, (), 'norm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.norm_gen object at 0x9f4974c>, (), 'norm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x9f5ff0c>, (2.621716532144454,), array(1.6166305764162521), array(1.6034057205287133), 1.6550137301062535, 1.2674974417903762, 1000, 'paretosample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x9f5ff0c>, (2.621716532144454,), array(1.6166305764162521), array(1.6034057205287133), 'pareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x9f5ff0c>, (2.621716532144454,), 'pareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x9f5ff0c>, (2.621716532144454,), 'pareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x9f5ff0c>, (2.621716532144454,), 'pareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x9f5ff0c>, (2.621716532144454,), 'pareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x9f5ff0c>, (2.621716532144454,), 'pareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.pareto_gen object at 0x9f5ff0c>, (2.621716532144454,), 'pareto') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x9f5ffac>, (1.6591133289905851,), array(0.62393479469353574), array(0.85857496135780687), 0.6381234170824458, 0.061503031152340959, 1000, 'powerlawsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x9f5ffac>, (1.6591133289905851,), array(0.62393479469353574), array(0.85857496135780687), 'powerlaw') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x9f5ffac>, (1.6591133289905851,), 'powerlaw') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x9f5ffac>, (1.6591133289905851,), 'powerlaw') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x9f5ffac>, (1.6591133289905851,), 'powerlaw') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x9f5ffac>, (1.6591133289905851,), 'powerlaw') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x9f5ffac>, (1.6591133289905851,), 'powerlaw') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powerlaw_gen object at 0x9f5ffac>, (1.6591133289905851,), 'powerlaw') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x9f661ec>, (4.4453652254590779,), array(-1.0934378551735171), array(0.46999722851193337), -1.0492605411034246, 0.43875052024467159, 1000, 'powernormsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x9f661ec>, (4.4453652254590779,), array(-1.0934378551735171), array(0.46999722851193337), 'powernorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x9f661ec>, (4.4453652254590779,), 'powernorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x9f661ec>, (4.4453652254590779,), 'powernorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x9f661ec>, (4.4453652254590779,), 'powernorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x9f661ec>, (4.4453652254590779,), 'powernorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x9f661ec>, (4.4453652254590779,), 'powernorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.powernorm_gen object at 0x9f661ec>, (4.4453652254590779,), 'powernorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x9f663ec>, (), array(1.2533141373155001), array(0.42920367320510344), 1.2898620140336596, 0.43409553188317462, 1000, 'rayleighsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x9f663ec>, (), array(1.2533141373155001), array(0.42920367320510344), 'rayleigh') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x9f663ec>, (), 'rayleigh') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x9f663ec>, (), 'rayleigh') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x9f663ec>, (), 'rayleigh') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x9f663ec>, (), 'rayleigh') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x9f663ec>, (), 'rayleigh') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.rayleigh_gen object at 0x9f663ec>, (), 'rayleigh') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x9f6642c>, (0.0062309367010521255, 1.0062309367010522), array(0.19667848552072986), array(0.060882307287375481), 0.2086064427595101, 0.06412533451045889, 1000, 'reciprocalsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x9f6642c>, (0.0062309367010521255, 1.0062309367010522), array(0.19667848552072986), array(0.060882307287375481), 'reciprocal') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x9f6642c>, (0.0062309367010521255, 1.0062309367010522), 'reciprocal') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x9f6642c>, (0.0062309367010521255, 1.0062309367010522), 'reciprocal') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x9f6642c>, (0.0062309367010521255, 1.0062309367010522), 'reciprocal') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x9f6642c>, (0.0062309367010521255, 1.0062309367010522), 'reciprocal') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x9f6642c>, (0.0062309367010521255, 1.0062309367010522), 'reciprocal') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.reciprocal_gen object at 0x9f6642c>, (0.0062309367010521255, 1.0062309367010522), 'reciprocal') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x9f5fd6c>, (2.7433514990818093,), array(0.0), array(3.6905172081719186), -0.027973201793274054, 3.534440759001078, 1000, 'tsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x9f5fd6c>, (2.7433514990818093,), array(0.0), array(3.6905172081719186), 't') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x9f5fd6c>, (2.7433514990818093,), 't') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x9f5fd6c>, (2.7433514990818093,), 't') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x9f5fd6c>, (2.7433514990818093,), 't') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x9f5fd6c>, (2.7433514990818093,), 't') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x9f5fd6c>, (2.7433514990818093,), 't') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.t_gen object at 0x9f5fd6c>, (2.7433514990818093,), 't') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x9f6670c>, (0.15785029824528218,), array(0.38595009941509401), array(0.048170356578380126), 0.3979467137648407, 0.048758189137974771, 1000, 'triangsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x9f6670c>, (0.15785029824528218,), array(0.38595009941509401), array(0.048170356578380126), 'triang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x9f6670c>, (0.15785029824528218,), 'triang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x9f6670c>, (0.15785029824528218,), 'triang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x9f6670c>, (0.15785029824528218,), 'triang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x9f6670c>, (0.15785029824528218,), 'triang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x9f6670c>, (0.15785029824528218,), 'triang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.triang_gen object at 0x9f6670c>, (0.15785029824528218,), 'triang') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x9f6682c>, (4.6907725456810478,), array(0.95654169346841034), array(0.79425834443323384), 1.0006988174499494, 0.83089849698746743, 1000, 'truncexponsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x9f6682c>, (4.6907725456810478,), array(0.95654169346841034), array(0.79425834443323384), 'truncexpon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x9f6682c>, (4.6907725456810478,), 'truncexpon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x9f6682c>, (4.6907725456810478,), 'truncexpon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x9f6682c>, (4.6907725456810478,), 'truncexpon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x9f6682c>, (4.6907725456810478,), 'truncexpon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x9f6682c>, (4.6907725456810478,), 'truncexpon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncexpon_gen object at 0x9f6682c>, (4.6907725456810478,), 'truncexpon') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x9f668ac>, (-1.0978730080013919, 2.7306754109031979), array(0.24256013977032281), array(0.63221524437974919), 0.28565694330796615, 0.63826177893087399, 1000, 'truncnormsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x9f668ac>, (-1.0978730080013919, 2.7306754109031979), array(0.24256013977032281), array(0.63221524437974919), 'truncnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x9f668ac>, (-1.0978730080013919, 2.7306754109031979), 'truncnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x9f668ac>, (-1.0978730080013919, 2.7306754109031979), 'truncnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x9f668ac>, (-1.0978730080013919, 2.7306754109031979), 'truncnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x9f668ac>, (-1.0978730080013919, 2.7306754109031979), 'truncnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x9f668ac>, (-1.0978730080013919, 2.7306754109031979), 'truncnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.truncnorm_gen object at 0x9f668ac>, (-1.0978730080013919, 2.7306754109031979), 'truncnorm') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x9f669ec>, (3.1321477856738267,), array(0.0), array(0.30476472279111871), 0.0090800061342219546, 0.026536393118696603, 1000, 'tukeylambdasample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x9f669ec>, (3.1321477856738267,), array(0.0), array(0.30476472279111871), 'tukeylambda') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x9f669ec>, (3.1321477856738267,), 'tukeylambda') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x9f669ec>, (3.1321477856738267,), 'tukeylambda') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x9f669ec>, (3.1321477856738267,), 'tukeylambda') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x9f669ec>, (3.1321477856738267,), 'tukeylambda') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x9f669ec>, (3.1321477856738267,), 'tukeylambda') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.tukeylambda_gen object at 0x9f669ec>, (3.1321477856738267,), 'tukeylambda') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x9f66a0c>, (), array(0.5), array(0.083333333333333329), 0.51516123993082608, 0.083002600178291683, 1000, 'uniformsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x9f66a0c>, (), array(0.5), array(0.083333333333333329), 'uniform') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x9f66a0c>, (), 'uniform') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x9f66a0c>, (), 'uniform') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x9f66a0c>, (), 'uniform') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x9f66a0c>, (), 'uniform') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x9f66a0c>, (), 'uniform') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.uniform_gen object at 0x9f66a0c>, (), 'uniform') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wald_gen object at 0x9f66bec>, (), array(1.0), array(1.0), 1.0190852081914161, 1.0256627129688465, 1000, 'waldsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wald_gen object at 0x9f66bec>, (), array(1.0), array(1.0), 'wald') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wald_gen object at 0x9f66bec>, (), 'wald') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wald_gen object at 0x9f66bec>, (), 'wald') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wald_gen object at 0x9f66bec>, (), 'wald') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5618c>, (2.8687961709100187,), array(-0.89129676887660936), array(0.11369305518071726), -0.87022627496962035, 0.10761318131749302, 1000, 'weibull_maxsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5618c>, (2.8687961709100187,), array(-0.89129676887660936), array(0.11369305518071726), 'weibull_max') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5618c>, (2.8687961709100187,), 'weibull_max') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5618c>, (2.8687961709100187,), 'weibull_max') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5618c>, (2.8687961709100187,), 'weibull_max') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5618c>, (2.8687961709100187,), 'weibull_max') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5618c>, (2.8687961709100187,), 'weibull_max') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_l_gen object at 0x9f5618c>, (2.8687961709100187,), 'weibull_max') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51f8c>, (1.7866166930421596,), array(0.8896162979747505), array(0.26510662289002973), 0.91782113279650301, 0.27042300220730836, 1000, 'weibull_minsample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51f8c>, (1.7866166930421596,), array(0.8896162979747505), array(0.26510662289002973), 'weibull_min') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51f8c>, (1.7866166930421596,), 'weibull_min') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51f8c>, (1.7866166930421596,), 'weibull_min') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51f8c>, (1.7866166930421596,), 'weibull_min') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51f8c>, (1.7866166930421596,), 'weibull_min') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51f8c>, (1.7866166930421596,), 'weibull_min') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.frechet_r_gen object at 0x9f51f8c>, (1.7866166930421596,), 'weibull_min') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x9f66c6c>, (0.031071279018614728,), array(3.1415926535897931), array(3.4151322438845), 3.2377370605003604, 3.4056398320138883, 1000, 'wrapcauchysample mean test') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x9f66c6c>, (0.031071279018614728,), array(3.1415926535897931), array(3.4151322438845), 'wrapcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x9f66c6c>, (0.031071279018614728,), 'wrapcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x9f66c6c>, (0.031071279018614728,), 'wrapcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x9f66c6c>, (0.031071279018614728,), 'wrapcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x9f66c6c>, (0.031071279018614728,), 'wrapcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x9f66c6c>, (0.031071279018614728,), 'wrapcauchy') ... ok
- test_continuous_basic.test_cont_basic(<scipy.stats.distributions.wrapcauchy_gen object at 0x9f66c6c>, (0.031071279018614728,), 'wrapcauchy') ... ok
- test_continuous_extra.test_540_567 ... ok
- test_discrete_basic.test_discrete_basic(0.29999999999999999, array(0.29999999999999999), 'bernoulli sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(0.20999999999999996, array(0.20999999999999999), 'bernoulli sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x9f66dec>, (0.29999999999999999,), 'bernoulli cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x9f66dec>, (0.29999999999999999,), array([0, 1]), 'bernoulli cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x9f66dec>, (0.29999999999999999,), 'bernoulli pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x9f66dec>, (0.29999999999999999,), 'bernoulli oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x9f66dec>, (0.29999999999999999,), -1.2380952380952377, 0.87287156094396945, 'bernoulli skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.bernoulli_gen object at 0x9f66dec>, (0.29999999999999999,), array([0, 0, 0, ..., 1, 0, 0]), 0.01, 'bernoulli chisquare') ... ok
- test_discrete_basic.test_discrete_basic(2.0015000000000001, array(2.0), 'binom sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(1.1854977500000001, array(1.2), 'binom sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x9f66d2c>, (5, 0.40000000000000002), 'binom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x9f66d2c>, (5, 0.40000000000000002), array([0, 1, 2, 3, 4, 5]), 'binom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x9f66d2c>, (5, 0.40000000000000002), 'binom pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x9f66d2c>, (5, 0.40000000000000002), 'binom oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x9f66d2c>, (5, 0.40000000000000002), -0.26248929225028617, 0.28057933666557583, 'binom skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.binom_gen object at 0x9f66d2c>, (5, 0.40000000000000002), array([2, 2, 2, ..., 4, 1, 3]), 0.01, 'binom chisquare') ... ok
- test_discrete_basic.test_discrete_basic(0.32900000000000001, array(0.32731081784804011), 'boltzmann sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(0.43975900000000001, array(0.4344431884043245), 'boltzmann sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x9f6f4ac>, (1.3999999999999999, 19), 'boltzmann cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x9f6f4ac>, (1.3999999999999999, 19), array([0, 1, 2, 3, 4]), 'boltzmann cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x9f6f4ac>, (1.3999999999999999, 19), 'boltzmann pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x9f6f4ac>, (1.3999999999999999, 19), 'boltzmann oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x9f6f4ac>, (1.3999999999999999, 19), 6.7133652484345081, 2.4186913927972746, 'boltzmann skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.boltzmann_gen object at 0x9f6f4ac>, (1.3999999999999999, 19), array([0, 0, 0, ..., 2, 0, 0]), 0.01, 'boltzmann chisquare') ... ok
- test_discrete_basic.test_discrete_basic(0.0070000000000000001, array(7.9181711188056743e-17), 'dlaplace sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(2.9319510000000002, array(2.9635341891843714), 'dlaplace sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.dlaplace_gen object at 0x9f6f70c>, (0.80000000000000004,), 'dlaplace cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.dlaplace_gen object at 0x9f6f70c>, (0.80000000000000004,), array([-8, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7]), 'dlaplace cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.dlaplace_gen object at 0x9f6f70c>, (0.80000000000000004,), 'dlaplace pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.dlaplace_gen object at 0x9f6f70c>, (0.80000000000000004,), 'dlaplace oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.dlaplace_gen object at 0x9f6f70c>, (0.80000000000000004,), 3.0660776822074851, 0.021996158609061872, 'dlaplace skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.dlaplace_gen object at 0x9f6f70c>, (0.80000000000000004,), array([ 0, 0, 0, ..., 4, -1, 0]), 0.01, 'dlaplace chisquare') ... Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- Warning: overflow encountered in exp
- ok
- test_discrete_basic.test_discrete_basic(1.9870000000000001, array(2.0), 'geom sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(2.0098310000000001, array(2.0), 'geom sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x9f6f08c>, (0.5,), 'geom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x9f6f08c>, (0.5,), array([ 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]), 'geom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x9f6f08c>, (0.5,), 'geom pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x9f6f08c>, (0.5,), 'geom oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x9f6f08c>, (0.5,), 5.1935883716660154, 2.0476504362661965, 'geom skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.geom_gen object at 0x9f6f08c>, (0.5,), array([1, 1, 2, ..., 6, 1, 2]), 0.01, 'geom chisquare') ... ok
- test_discrete_basic.test_discrete_basic(2.3860000000000001, array(2.4000000000000004), 'hypergeom sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(1.150004, array(1.1917241379310344), 'hypergeom sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (30, 12, 6), 'hypergeom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (30, 12, 6), array([0, 1, 2, 3, 4, 5, 6]), 'hypergeom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (30, 12, 6), 'hypergeom pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (30, 12, 6), 'hypergeom oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (30, 12, 6), -0.29686916362566595, 0.020906577365968099, 'hypergeom skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (30, 12, 6), array([1, 1, 4, ..., 3, 2, 2]), 0.01, 'hypergeom chisquare') ... ok
- test_discrete_basic.test_discrete_basic(1.724, array(1.7142857142857142), 'hypergeom sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(0.65282399999999996, array(0.66122448979591841), 'hypergeom sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (21, 3, 12), 'hypergeom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (21, 3, 12), array([0, 1, 2, 3]), 'hypergeom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (21, 3, 12), 'hypergeom pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (21, 3, 12), 'hypergeom oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (21, 3, 12), -0.46243472564584698, -0.18093529905212996, 'hypergeom skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (21, 3, 12), array([2, 3, 2, ..., 2, 2, 1]), 0.01, 'hypergeom chisquare') ... ok
- test_discrete_basic.test_discrete_basic(9.4184999999999999, array(9.4285714285714288), 'hypergeom sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(0.68435774999999999, array(0.67346938775510201), 'hypergeom sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (21, 18, 11), 'hypergeom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (21, 18, 11), array([ 8, 9, 10, 11]), 'hypergeom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (21, 18, 11), 'hypergeom pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (21, 18, 11), 'hypergeom oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (21, 18, 11), -0.53396352457629082, 0.093601755841812559, 'hypergeom skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.hypergeom_gen object at 0x9f6f22c>, (21, 18, 11), array([ 9, 8, 9, ..., 10, 10, 10]), 0.01, 'hypergeom chisquare') ... ok
- test_discrete_basic.test_discrete_basic(1.635, array(1.637035001905937), 'logser sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(1.3257750000000001, array(1.4127039072996714), 'logser sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x9f6f24c>, (0.59999999999999998,), 'logser cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x9f6f24c>, (0.59999999999999998,), array([1, 2, 3, 4, 5, 6, 7, 8, 9]), 'logser cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x9f6f24c>, (0.59999999999999998,), 'logser pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x9f6f24c>, (0.59999999999999998,), 'logser oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x9f6f24c>, (0.59999999999999998,), 7.5591983779780421, 2.4947797038221462, 'logser skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.logser_gen object at 0x9f6f24c>, (0.59999999999999998,), array([1, 1, 1, ..., 1, 1, 4]), 0.01, 'logser chisquare') ... ok
- test_discrete_basic.test_discrete_basic(4.9210000000000003, array(5.0), 'nbinom sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(9.4787590000000002, array(10.0), 'nbinom sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x9f66eec>, (5, 0.5), 'nbinom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x9f66eec>, (5, 0.5), array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 21]), 'nbinom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x9f66eec>, (5, 0.5), 'nbinom pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x9f66eec>, (5, 0.5), 'nbinom oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x9f66eec>, (5, 0.5), 1.5000586959708722, 0.97358518373019654, 'nbinom skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x9f66eec>, (5, 0.5), array([0, 2, 6, ..., 3, 3, 3]), 0.01, 'nbinom chisquare') ... ok
- test_discrete_basic.test_discrete_basic(0.58399999999999996, array(0.60000000000000009), 'nbinom sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(1.472944, array(1.5000000000000002), 'nbinom sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x9f66eec>, (0.40000000000000002, 0.40000000000000002), 'nbinom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x9f66eec>, (0.40000000000000002, 0.40000000000000002), array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12]), 'nbinom cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x9f66eec>, (0.40000000000000002, 0.40000000000000002), 'nbinom pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x9f66eec>, (0.40000000000000002, 0.40000000000000002), 'nbinom oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x9f66eec>, (0.40000000000000002, 0.40000000000000002), 13.929082276072258, 3.2071528858782039, 'nbinom skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.nbinom_gen object at 0x9f66eec>, (0.40000000000000002, 0.40000000000000002), array([0, 0, 0, ..., 0, 0, 0]), 0.01, 'nbinom chisquare') ... ok
- test_discrete_basic.test_discrete_basic(1.496, array(1.5031012098113492), 'planck sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(3.8119839999999998, array(3.7624144567476914), 'planck sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x9f6f3ec>, (0.51000000000000001,), 'planck cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x9f6f3ec>, (0.51000000000000001,), array([ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12]), 'planck cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x9f6f3ec>, (0.51000000000000001,), 'planck pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x9f6f3ec>, (0.51000000000000001,), 'planck oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x9f6f3ec>, (0.51000000000000001,), 5.0921201134829879, 1.9924056300477018, 'planck skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.planck_gen object at 0x9f6f3ec>, (0.51000000000000001,), array([1, 1, 1, ..., 7, 0, 2]), 0.01, 'planck chisquare') ... ok
- test_discrete_basic.test_discrete_basic(0.58550000000000002, array(0.59999999999999998), 'poisson sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(0.59768975000000002, array(0.59999999999999998), 'poisson sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x9f6f18c>, (0.59999999999999998,), 'poisson cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x9f6f18c>, (0.59999999999999998,), array([0, 1, 2, 3, 4, 5]), 'poisson cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x9f6f18c>, (0.59999999999999998,), 'poisson pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x9f6f18c>, (0.59999999999999998,), 'poisson oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x9f6f18c>, (0.59999999999999998,), 1.9406814436779811, 1.3589585241917084, 'poisson skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.poisson_gen object at 0x9f6f18c>, (0.59999999999999998,), array([0, 0, 0, ..., 1, 0, 0]), 0.01, 'poisson chisquare') ... ok
- test_discrete_basic.test_discrete_basic(18.4725, array(18.5), 'randint sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(48.80024375, array(47.916666666666664), 'randint sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x9f6f56c>, (7, 31), 'randint cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x9f6f56c>, (7, 31), array([ 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x9f6f56c>, (7, 31), 'randint pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x9f6f56c>, (7, 31), 'randint oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x9f6f56c>, (7, 31), -1.2115060412211864, -0.025412774105826163, 'randint skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.randint_gen object at 0x9f6f56c>, (7, 31), array([27, 10, 15, ..., 16, 9, 17]), 0.01, 'randint chisquare') ... ok
- test_discrete_basic.test_discrete_basic(7.0019999999999998, array(7.0), 'skellam sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(22.550996000000001, array(23.0), 'skellam sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.skellam_gen object at 0x9f6f6ac>, (15, 8), 'skellam cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.skellam_gen object at 0x9f6f6ac>, (15, 8), array([-10, -7, -6, -5, -4, -3, -2, -1, 0, 1, 2, 3, 4, 5, 6, 7, ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.skellam_gen object at 0x9f6f6ac>, (15, 8), 'skellam pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.skellam_gen object at 0x9f6f6ac>, (15, 8), 'skellam oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.skellam_gen object at 0x9f6f6ac>, (15, 8), 0.11554402415314646, 0.10806520422790719, 'skellam skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.skellam_gen object at 0x9f6f6ac>, (15, 8), array([ 4, 6, 10, ..., 5, 14, 15]), 0.01, 'skellam chisquare') ... ok
- test_discrete_basic.test_discrete_basic(1.1194999999999999, array(1.1106265353261477), 'zipf sample mean test') ... ok
- test_discrete_basic.test_discrete_basic(0.30921974999999996, array(0.2863264536645036), 'zipf sample var test') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.zipf_gen object at 0x9f6f52c>, (4,), 'zipf cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.zipf_gen object at 0x9f6f52c>, (4,), array([ 1, 2, 3, 4, 5, 6, 14]), 'zipf cdf_ppf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.zipf_gen object at 0x9f6f52c>, (4,), 'zipf pmf_cdf') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.zipf_gen object at 0x9f6f52c>, (4,), 'zipf oth') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.zipf_gen object at 0x9f6f52c>, (4,), 167.01888834706017, 10.00257952205159, 'zipf skew_kurt') ... ok
- test_discrete_basic.test_discrete_basic(<scipy.stats.distributions.zipf_gen object at 0x9f6f52c>, (4,), array([1, 1, 1, ..., 1, 1, 1]), 0.01, 'zipf chisquare') ... ok
- Failure: SkipTest (Skipping test: test_discrete_privateTest skipped due to test condition) ... SKIP: Skipping test: test_discrete_privateTest skipped due to test condition
- test_noexception (test_distributions.TestArrayArgument) ... ok
- test_rvs (test_distributions.TestBernoulli) ... ok
- test_rvs (test_distributions.TestBinom) ... ok
- test_precision (test_distributions.TestChi2) ... ok
- test_rvs (test_distributions.TestDLaplace) ... ok
- See ticket #761 ... ok
- See ticket #497 ... ok
- test_tail (test_distributions.TestExpon) ... ok
- test_zero (test_distributions.TestExpon) ... ok
- test_tail (test_distributions.TestExponpow) ... ok
- test_cdf_bounds (test_distributions.TestGenExpon) ... ok
- test_pdf_unity_area (test_distributions.TestGenExpon) ... ok
- test_cdf_sf (test_distributions.TestGeom) ... ok
- test_pmf (test_distributions.TestGeom) ... ok
- test_rvs (test_distributions.TestGeom) ... ok
- test_precision (test_distributions.TestHypergeom) ... ok
- test_rvs (test_distributions.TestLogser) ... ok
- test_rvs (test_distributions.TestNBinom) ... ok
- test_rvs (test_distributions.TestPoisson) ... ok
- test_cdf (test_distributions.TestRandInt) ... ok
- test_pdf (test_distributions.TestRandInt) ... ok
- test_rvs (test_distributions.TestRandInt) ... ok
- test_rvs (test_distributions.TestRvDiscrete) ... ok
- test_cdf (test_distributions.TestSkellam) ... ok
- test_pmf (test_distributions.TestSkellam) ... ok
- test_rvs (test_distributions.TestZipf) ... ok
- test_distributions.test_all_distributions('uniform', (), 0.01) ... ok
- test_distributions.test_all_distributions('norm', (), 0.01) ... ok
- test_distributions.test_all_distributions('lognorm', (1.5876170641754364,), 0.01) ... ok
- test_distributions.test_all_distributions('expon', (), 0.01) ... ok
- test_distributions.test_all_distributions('beta', (1.4449890262755161, 1.5962868615831063), 0.01) ... ok
- test_distributions.test_all_distributions('powerlaw', (1.3849011459726603,), 0.01) ... ok
- test_distributions.test_all_distributions('bradford', (1.5756510141648885,), 0.01) ... ok
- test_distributions.test_all_distributions('burr', (1.2903295024027579, 1.1893913285543563), 0.01) ... ok
- test_distributions.test_all_distributions('fisk', (1.186729528255555,), 0.01) ... ok
- test_distributions.test_all_distributions('cauchy', (), 0.01) ... ok
- test_distributions.test_all_distributions('halfcauchy', (), 0.01) ... ok
- test_distributions.test_all_distributions('foldcauchy', (1.6127731798686067,), 0.01) ... ok
- test_distributions.test_all_distributions('gamma', (1.6566593889896288,), 0.01) ... ok
- test_distributions.test_all_distributions('gengamma', (1.4765309920093808, 1.0898243611955936), 0.01) ... /usr/lib/python2.6/site-packages/scipy/stats/distributions.py:2910: SpecialFunctionWarning: gammaincinv: failed to converge at (a, y) = (1.4765309920093807605, 0.18873438190412772375): got 0.465447 +- 1.51437e-07, code 3
- val1 = special.gammaincinv(a,q)
- /usr/lib/python2.6/site-packages/scipy/stats/distributions.py:2911: SpecialFunctionWarning: gammaincinv: failed to converge at (a, y) = (1.4765309920093807605, 0.15245287958853148691): got 0.391536 +- 1.55137e-07, code 3
- val2 = special.gammaincinv(a,1.0-q)
- /usr/lib/python2.6/site-packages/scipy/stats/distributions.py:2911: SpecialFunctionWarning: gammaincinv: failed to converge at (a, y) = (1.4765309920093807605, 0.22978667246545214642): got 0.548935 +- 1.44517e-07, code 3
- val2 = special.gammaincinv(a,1.0-q)
- /usr/lib/python2.6/site-packages/scipy/stats/distributions.py:2911: SpecialFunctionWarning: gammaincinv: failed to converge at (a, y) = (1.4765309920093807605, 0.23084145297124092355): got 0.551088 +- 2.1022e-07, code 3
- val2 = special.gammaincinv(a,1.0-q)
- ok
- test_distributions.test_all_distributions('loggamma', (1.7576039219664368,), 0.01) ... ok
- test_distributions.test_all_distributions('alpha', (1.8767703708227748,), 0.01) ... ok
- test_distributions.test_all_distributions('anglit', (), 0.01) ... ok
- test_distributions.test_all_distributions('arcsine', (), 0.01) ... ok
- test_distributions.test_all_distributions('betaprime', (1.9233810159462807, 1.8424602231401823), 0.01) ... ok
- test_distributions.test_all_distributions('erlang', (4, 0.89817312135787897, 0.92308243982017679), 0.01) ... ok
- test_distributions.test_all_distributions('dgamma', (1.5405999249480544,), 0.01) ... ok
- test_distributions.test_all_distributions('exponweib', (1.391296050234625, 1.7052833998544061), 0.01) ... ok
- test_distributions.test_all_distributions('exponpow', (1.2756341213121272,), 0.01) ... ok
- test_distributions.test_all_distributions('frechet_l', (1.8116287085078784,), 0.01) ... ok
- test_distributions.test_all_distributions('frechet_r', (1.8494859651863671,), 0.01) ... ok
- test_distributions.test_all_distributions('gilbrat', (), 0.01) ... ok
- test_distributions.test_all_distributions('f', (1.8950389674266752, 1.5898011835311598), 0.01) ... ok
- test_distributions.test_all_distributions('ncf', (1.9497648732321204, 1.5796950107456058, 1.4505631066311553), 0.01) ... ok
- test_distributions.test_all_distributions('chi2', (1.660245378622389,), 0.01) ... ok
- test_distributions.test_all_distributions('chi', (1.9962578393535728,), 0.01) ... ok
- test_distributions.test_all_distributions('nakagami', (1.9169412179474561,), 0.01) ... /usr/lib/python2.6/site-packages/scipy/stats/distributions.py:3628: SpecialFunctionWarning: gammaincinv: failed to converge at (a, y) = (1.9169412179474560887, 0.1897430039039509353): got 0.741565 +- 1.29151e-07, code 3
- return sqrt(1.0/nu*special.gammaincinv(nu,q))
- /usr/lib/python2.6/site-packages/scipy/stats/distributions.py:3628: SpecialFunctionWarning: gammaincinv: failed to converge at (a, y) = (1.9169412179474560887, 0.20721623628659302518): got 0.788026 +- 4.28984e-07, code 3
- return sqrt(1.0/nu*special.gammaincinv(nu,q))
- /usr/lib/python2.6/site-packages/scipy/stats/distributions.py:3628: SpecialFunctionWarning: gammaincinv: failed to converge at (a, y) = (1.9169412179474560887, 0.24276250406510935242): got 0.881607 +- 1.4972e-07, code 3
- return sqrt(1.0/nu*special.gammaincinv(nu,q))
- /usr/lib/python2.6/site-packages/scipy/stats/distributions.py:3628: SpecialFunctionWarning: gammaincinv: failed to converge at (a, y) = (1.9169412179474560887, 0.20921997868657327135): got 0.793329 +- 2.67161e-07, code 3
- return sqrt(1.0/nu*special.gammaincinv(nu,q))
- /usr/lib/python2.6/site-packages/scipy/stats/distributions.py:3628: SpecialFunctionWarning: gammaincinv: failed to converge at (a, y) = (1.9169412179474560887, 0.20832379908957909809): got 0.790958 +- 3.3952e-07, code 3
- return sqrt(1.0/nu*special.gammaincinv(nu,q))
- FAIL
- test_distributions.test_all_distributions('genpareto', (1.7933250841302242,), 0.01) ... ok
- test_distributions.test_all_distributions('genextreme', (1.0823729881966475,), 0.01) ... ok
- test_distributions.test_all_distributions('genhalflogistic', (1.6127831050407122,), 0.01) ... ok
- test_distributions.test_all_distributions('pareto', (1.4864442019691668,), 0.01) ... ok
- test_distributions.test_all_distributions('lomax', (1.6301473404114728,), 0.01) ... ok
- test_distributions.test_all_distributions('halfnorm', (), 0.01) ... ok
- test_distributions.test_all_distributions('halflogistic', (), 0.01) ... ok
- test_distributions.test_all_distributions('fatiguelife', (1.8450775756715152,), 0.001) ... ok
- test_distributions.test_all_distributions('foldnorm', (1.2430356220618561,), 0.01) ... ok
- test_distributions.test_all_distributions('ncx2', (1.7314892207908477, 1.117134293208518), 0.01) ... ok
- test_distributions.test_all_distributions('t', (1.2204605368678285,), 0.01) ... ok
- test_distributions.test_all_distributions('nct', (1.7945829717105759, 1.3325361492196555), 0.01) ... ok
- test_distributions.test_all_distributions('weibull_min', (1.8159130965336594,), 0.01) ... ok
- test_distributions.test_all_distributions('weibull_max', (1.1006075202160961,), 0.01) ... ok
- test_distributions.test_all_distributions('dweibull', (1.1463584889123037,), 0.01) ... ok
- test_distributions.test_all_distributions('maxwell', (), 0.01) ... ok
- test_distributions.test_all_distributions('rayleigh', (), 0.01) ... ok
- test_distributions.test_all_distributions('genlogistic', (1.6976706401912387,), 0.01) ... ok
- test_distributions.test_all_distributions('logistic', (), 0.01) ... ok
- test_distributions.test_all_distributions('gumbel_l', (), 0.01) ... ok
- test_distributions.test_all_distributions('gumbel_r', (), 0.01) ... ok
- test_distributions.test_all_distributions('gompertz', (1.0452340678656125,), 0.01) ... ok
- test_distributions.test_all_distributions('hypsecant', (), 0.01) ... ok
- test_distributions.test_all_distributions('laplace', (), 0.01) ... ok
- test_distributions.test_all_distributions('reciprocal', (0.57386603678916692, 1.573866036789167), 0.01) ... ok
- test_distributions.test_all_distributions('triang', (0.53419796826072397,), 0.01) ... ok
- test_distributions.test_all_distributions('tukeylambda', (1.6805891325622566,), 0.01) ... ok
- test_distributions.test_all_distributions('vonmises', (10,), 0.01) ... ok
- test_distributions.test_all_distributions('vonmises', (101,), 0.01) ... ok
- test_distributions.test_all_distributions('vonmises', (1.0266967946622052,), 0.01) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 1, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 1, 1, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 10, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 1, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 1, 1, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 10, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 1, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 1, 1, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 10, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 1, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 1, 1, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 10, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 1, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 1, 1, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 10, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 1, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 1, 1, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 10, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 1, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 1, 1, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 10, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 1, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 1, 1, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 10, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 1, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 1, 1, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 10, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 1, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 1, 1, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(0.10000000000000001, 0, 10, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 1, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 1, 1, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 10, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 1, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 1, 1, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 10, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 1, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 1, 1, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 10, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 1, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 1, 1, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 10, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 1, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 1, 1, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 10, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 1, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 1, 1, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 10, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 1, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 1, 1, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 10, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 1, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 1, 1, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 10, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 1, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 1, 1, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 10, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 1, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 1, 1, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(1, 0, 10, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 1, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 1, 1, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 10, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 1, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 1, 1, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 10, 0) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 1, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 1, 1, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 10, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 1, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 1, 1, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 10, 1) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 1, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 1, 1, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 10, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 1, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 1, 1, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 10, 3.1415926535897931) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 1, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 1, 1, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 10, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 1, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 1, 1, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 10, 10) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 1, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 1, 1, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 10, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 1, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 1, 1, 100) ... ok
- test_distributions.test_vonmises_pdf_periodic(101, 0, 10, 100) ... ok
- test_distributions.TestArgsreduce ... ok
- test_kdeoth.test_kde_1d ... ok
- test_expon (test_morestats.TestAnderson) ... Warning: divide by zero encountered in log
- Warning: divide by zero encountered in log
- ok
- test_normal (test_morestats.TestAnderson) ... ok
- test_approx (test_morestats.TestAnsari) ... /usr/lib/python2.6/site-packages/scipy/stats/morestats.py:736: UserWarning: Ties preclude use of exact statistic.
- warnings.warn("Ties preclude use of exact statistic.")
- ok
- test_exact (test_morestats.TestAnsari) ... ok
- test_small (test_morestats.TestAnsari) ... ok
- test_data (test_morestats.TestBartlett) ... ok
- test_data (test_morestats.TestBinomP) ... ok
- test_basic (test_morestats.TestFindRepeats) ... ok
- test_data (test_morestats.TestLevene) ... ok
- test_basic (test_morestats.TestShapiro) ... ok
- test_morestats.test_fligner ... ok
- test_morestats.test_mood ... ok
- Tests the cov function. ... ok
- Tests some computations of Kendall's tau ... ok
- Tests the seasonal Kendall tau. ... ok
- Tests some computations of Pearson's r ... Warning: divide by zero encountered in divide
- Warning: divide by zero encountered in divide
- ok
- Tests point biserial ... ok
- Tests some computations of Spearman's rho ... ok
- test_1D (test_mstats_basic.TestGMean) ... ok
- test_2D (test_mstats_basic.TestGMean) ... ok
- test_1D (test_mstats_basic.TestHMean) ... ok
- test_2D (test_mstats_basic.TestHMean) ... ok
- Tests the Friedman Chi-square test ... ok
- Tests the Kolmogorov-Smirnov 2 samples test ... ok
- Tests Obrien transform ... ok
- sum((testcase-mean(testcase,axis=0))**4,axis=0)/((sqrt(var(testcase)*3/4))**4)/4 ... ok
- Tests the mode ... ok
- mean((testcase-mean(testcase))**power,axis=0),axis=0))**power)) ... ok
- sum((testmathworks-mean(testmathworks,axis=0))**3,axis=0)/((sqrt(var(testmathworks)*4/5))**3)/5 ... ok
- variation = samplestd/mean ... ok
- Ticket #867 ... ok
- test_2D (test_mstats_basic.TestPercentile) ... ok
- test_percentile (test_mstats_basic.TestPercentile) ... ok
- test_ranking (test_mstats_basic.TestRanking) ... ok
- Tests trimming ... ok
- Tests trimming. ... ok
- Tests the trimmed mean standard error. ... ok
- Tests the trimmed mean. ... ok
- Tests the Winsorization of the data. ... ok
- test_samplestd (test_mstats_basic.TestVariability) ... ok
- R does not have 'samplevar' so the following was used ... ok
- this is not in R, so used ... ok
- this is not in R, so used ... ok
- test_std (test_mstats_basic.TestVariability) ... ok
- this is not in R, so used ... ok
- var(testcase) = 1.666666667 ... ok
- not in R, so used ... ok
- not in R, so tested by using ... ok
- Tests ideal-fourths ... ok
- Tests the Marits-Jarrett estimator ... ok
- Tests the confidence intervals of the trimmed mean. ... ok
- test_hdquantiles (test_mstats_extras.TestQuantiles) ... ok
- test_meanBIG (test_stats.TestBasicStats) ... ok
- test_meanHUGE (test_stats.TestBasicStats) ... ok
- test_meanLITTLE (test_stats.TestBasicStats) ... ok
- test_meanROUND (test_stats.TestBasicStats) ... ok
- test_meanTINY (test_stats.TestBasicStats) ... ok
- test_meanX (test_stats.TestBasicStats) ... ok
- test_meanZERO (test_stats.TestBasicStats) ... ok
- test_stdBIG (test_stats.TestBasicStats) ... ok
- test_stdHUGE (test_stats.TestBasicStats) ... ok
- test_stdLITTLE (test_stats.TestBasicStats) ... ok
- test_stdROUND (test_stats.TestBasicStats) ... ok
- test_stdTINY (test_stats.TestBasicStats) ... ok
- test_stdX (test_stats.TestBasicStats) ... ok
- test_stdZERO (test_stats.TestBasicStats) ... ok
- test_tmeanX (test_stats.TestBasicStats) ... ok
- test_tstdX (test_stats.TestBasicStats) ... ok
- test_tvarX (test_stats.TestBasicStats) ... ok
- test_basic (test_stats.TestCMedian) ... ok
- test_pBIGBIG (test_stats.TestCorr) ... ok
- test_pBIGHUGE (test_stats.TestCorr) ... ok
- test_pBIGLITTLE (test_stats.TestCorr) ... ok
- test_pBIGROUND (test_stats.TestCorr) ... ok
- test_pBIGTINY (test_stats.TestCorr) ... ok
- test_pHUGEHUGE (test_stats.TestCorr) ... ok
- test_pHUGEROUND (test_stats.TestCorr) ... ok
- test_pHUGETINY (test_stats.TestCorr) ... ok
- test_pLITTLEHUGE (test_stats.TestCorr) ... ok
- test_pLITTLELITTLE (test_stats.TestCorr) ... ok
- test_pLITTLEROUND (test_stats.TestCorr) ... ok
- test_pLITTLETINY (test_stats.TestCorr) ... ok
- test_pROUNDROUND (test_stats.TestCorr) ... ok
- test_pTINYROUND (test_stats.TestCorr) ... ok
- test_pTINYTINY (test_stats.TestCorr) ... ok
- test_pXBIG (test_stats.TestCorr) ... ok
- test_pXHUGE (test_stats.TestCorr) ... ok
- test_pXLITTLE (test_stats.TestCorr) ... ok
- test_pXROUND (test_stats.TestCorr) ... ok
- test_pXTINY (test_stats.TestCorr) ... ok
- test_pXX (test_stats.TestCorr) ... ok
- test_sBIGBIG (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sBIGHUGE (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sBIGLITTLE (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sBIGROUND (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sBIGTINY (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sHUGEHUGE (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sHUGEROUND (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sHUGETINY (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sLITTLEHUGE (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sLITTLELITTLE (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sLITTLEROUND (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sLITTLETINY (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sROUNDROUND (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sTINYROUND (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sTINYTINY (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sXBIG (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sXHUGE (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sXLITTLE (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sXROUND (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sXTINY (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- test_sXX (test_stats.TestCorr) ... Warning: divide by zero encountered in divide
- ok
- A test of stats.f_oneway, with F=2. ... ok
- A trivial test of stats.f_oneway, with F=0. ... ok
- test_1D_array (test_stats.TestGMean) ... ok
- test_1D_list (test_stats.TestGMean) ... ok
- test_2D_array_default (test_stats.TestGMean) ... ok
- test_2D_array_dim1 (test_stats.TestGMean) ... ok
- test_large_values (test_stats.TestGMean) ... ok
- Test a 1d array ... ok
- Test a 1d array with zero element ... Warning: divide by zero encountered in log
- ok
- Test a 1d list ... ok
- Test a 1d list with zero element ... Warning: divide by zero encountered in log
- ok
- Test a 1d masked array ... ok
- Test a 1d masked array with zero element ... Warning: divide by zero encountered in log
- ok
- Test a 1d masked array with negative element ... Warning: invalid value encountered in log
- ok
- Test a 1d masked array with a masked value ... ok
- Test a 2d array ... ok
- Test a 2d list with axis=0 ... ok
- Test a 2d list with axis=1 ... ok
- Test a 2d list ... ok
- Test a 2d masked array ... ok
- Test a 2d list with axis=1 ... ok
- Test a 2d list with axis=0 ... ok
- test_1D_array (test_stats.TestHMean) ... ok
- test_1D_list (test_stats.TestHMean) ... ok
- test_2D_array_default (test_stats.TestHMean) ... ok
- test_2D_array_dim1 (test_stats.TestHMean) ... ok
- Test a 1d array ... ok
- Test a 1d list ... ok
- Test a 1d masked array ... ok
- Test a 1d masked array with a masked value ... ok
- Test a 2d array ... ok
- Test a 2d list with axis=0 ... ok
- Test a 2d list with axis=1 ... ok
- Test a 2d list ... ok
- Test a 2d masked array ... ok
- Test a 2d list with axis=1 ... ok
- Test a 2d list with axis=0 ... ok
- Tests that increasing the number of bins produces expected results ... ok
- Tests that reducing the number of bins produces expected results ... ok
- Tests that each of the tests works as expected with default params ... ok
- Tests that weights give expected histograms ... ok
- test_2d (test_stats.TestMean) ... ok
- test_basic (test_stats.TestMean) ... ok
- test_ravel (test_stats.TestMean) ... ok
- Regression test for #760. ... ok
- test_basic (test_stats.TestMedian) ... ok
- test_basic2 (test_stats.TestMedian) ... ok
- test_basic (test_stats.TestMode) ... ok
- sum((testcase-mean(testcase,axis=0))**4,axis=0)/((sqrt(var(testcase)*3/4))**4)/4 ... ok
- test_kurtosis_array_scalar (test_stats.TestMoments) ... ok
- mean((testcase-mean(testcase))**power,axis=0),axis=0))**power)) ... ok
- sum((testmathworks-mean(testmathworks,axis=0))**3,axis=0)/ ... ok
- `skew` must return a scalar for 1-dim input ... ok
- variation = samplestd/mean ... ok
- Check nanmean when all values are nan. ... ok
- Check nanmean when no values are nan. ... ok
- Check nanmean when some values only are nan. ... ok
- Check nanmedian when all values are nan. ... ok
- Check nanmedian when no values are nan. ... ok
- Check nanmedian when some values only are nan. ... ok
- Check nanstd when all values are nan. ... ok
- test_nanstd_negative_axis (test_stats.TestNanFunc) ... ok
- Check nanstd when no values are nan. ... ok
- Check nanstd when some values only are nan. ... ok
- test_2D (test_stats.TestPercentile) ... ok
- test_median (test_stats.TestPercentile) ... ok
- test_percentile (test_stats.TestPercentile) ... ok
- compared with multivariate ols with pinv ... ok
- W.II.F. Regress BIG on X. ... ok
- W.IV.B. Regress X on X. ... ok
- W.IV.D. Regress ZERO on X. ... ok
- Check that a single input argument to linregress with wrong shape ... ok
- Regress a line with sinusoidal noise. ... ok
- Regress a line with sinusoidal noise, with a single input of shape ... ok
- Regress a line with sinusoidal noise, with a single input of shape ... ok
- W.II.A.0. Print ROUND with only one digit. ... ok
- W.II.A.1. Y = INT(2.6*7 -0.2) (Y should be 18) ... ok
- W.II.A.2. Y = 2-INT(EXP(LOG(SQR(2)*SQR(2)))) (Y should be 0) ... ok
- W.II.A.3. Y = INT(3-EXP(LOG(SQR(2)*SQR(2)))) (Y should be 1) ... ok
- test_stats.TestSigamClip.test_sigmaclip1 ... ok
- test_stats.TestSigamClip.test_sigmaclip2 ... ok
- test_stats.TestSigamClip.test_sigmaclip3 ... ok
- test_2d (test_stats.TestStd) ... ok
- test_basic (test_stats.TestStd) ... ok
- test_onesample (test_stats.TestStudentTest) ... ok
- test_basic (test_stats.TestThreshold) ... ok
- test_samplestd (test_stats.TestVariability) ... ok
- R does not have 'samplevar' so the following was used ... ok
- this is not in R, so used ... ok
- this is not in R, so used ... ok
- test_std (test_stats.TestVariability) ... ok
- this is not in R, so used ... ok
- var(testcase) = 1.666666667 ... ok
- not in R, so used ... ok
- not in R, so tested by using ... ok
- not in R, so tested by using ... ok
- not in R, so tested by using ... ok
- test_stats.Test_Trim.test_trim1 ... ok
- test_stats.Test_Trim.test_trim_mean ... ok
- test_stats.Test_Trim.test_trimboth ... ok
- test_stats.test_scoreatpercentile ... ok
- test_stats.test_percentileofscore(35.0, 35.0) ... ok
- test_stats.test_percentileofscore(30.0, 30.0) ... ok
- test_stats.test_percentileofscore(40.0, 40.0) ... ok
- test_stats.test_percentileofscore(45.0, 45.0) ... ok
- test_stats.test_percentileofscore(30.0, 30.0) ... ok
- test_stats.test_percentileofscore(50.0, 50.0) ... ok
- test_stats.test_percentileofscore(40.0, 40.0) ... ok
- test_stats.test_percentileofscore(50.0, 50.0) ... ok
- test_stats.test_percentileofscore(45.0, 45.0) ... ok
- test_stats.test_percentileofscore(30.0, 30.0) ... ok
- test_stats.test_percentileofscore(60.0, 60.0) ... ok
- test_stats.test_percentileofscore(30.0, 30) ... ok
- test_stats.test_percentileofscore(30.0, 30) ... ok
- test_stats.test_percentileofscore(30.0, 30) ... ok
- test_stats.test_percentileofscore(30.0, 30) ... ok
- test_stats.test_percentileofscore(35.0, 35.0) ... ok
- test_stats.test_percentileofscore(30.0, 30.0) ... ok
- test_stats.test_percentileofscore(40.0, 40.0) ... ok
- test_stats.test_percentileofscore(45.0, 45.0) ... ok
- test_stats.test_percentileofscore(30.0, 30.0) ... ok
- test_stats.test_percentileofscore(60.0, 60.0) ... ok
- test_stats.test_percentileofscore(30.0, 30.0) ... ok
- test_stats.test_percentileofscore(30.0, 30.0) ... ok
- test_stats.test_percentileofscore(30.0, 30.0) ... ok
- test_stats.test_percentileofscore(30.0, 30.0) ... ok
- test_stats.test_percentileofscore(10.0, 10.0) ... ok
- test_stats.test_percentileofscore(5.0, 5.0) ... ok
- test_stats.test_percentileofscore(0.0, 0.0) ... ok
- test_stats.test_percentileofscore(10.0, 10.0) ... ok
- test_stats.test_percentileofscore(100.0, 100.0) ... ok
- test_stats.test_percentileofscore(95.0, 95.0) ... ok
- test_stats.test_percentileofscore(90.0, 90.0) ... ok
- test_stats.test_percentileofscore(100.0, 100.0) ... ok
- test_stats.test_percentileofscore(100.0, 100.0) ... ok
- test_stats.test_percentileofscore(100.0, 100.0) ... ok
- test_stats.test_percentileofscore(0.0, 0.0) ... ok
- test_stats.test_friedmanchisquare ... ok
- test_stats.test_kstest ... ok
- test_stats.test_ks_2samp ... ok
- test_stats.test_ttest_rel ... ok
- test_stats.test_ttest_ind ... ok
- test_stats.test_ttest_1samp_new ... ok
- test_stats.test_describe ... ok
- test_stats.test_normalitytests((3.9237191815818493, 0.14059672529747547), (3.92371918, 0.14059673)) ... ok
- test_stats.test_normalitytests((1.9807882609087573, 0.04761502382843226), (1.98078826, 0.047615020000000001)) ... ok
- test_stats.test_normalitytests((-0.014037344047599392, 0.98880018772590395), (-0.014037340000000001, 0.98880018999999997)) ... ok
- test_stats.test_pointbiserial ... ok
- test_stats.test_obrientransform ... ok
- test_stats.test_binomtest ... ok
- convert simple expr to blitz ... ok
- convert fdtd equation to blitz. ... ok
- convert simple expr to blitz ... ok
- bad path should return same as default (and warn) ... ok
- make sure it handles relative values. ... ok
- default behavior is to return current directory ... ok
- make sure it handles relative values ... ok
- test_simple (test_build_tools.TestConfigureSysArgv) ... ok
- bad path should return same as default (and warn) ... ok
- make sure it handles relative values. ... ok
- default behavior returns tempdir ... ok
- make sure it handles relative values ... ok
- There should always be a writable file -- even if it is in temp ... ok
- test_add_function_ordered (test_catalog.TestCatalog) ... ok
- Test persisting a function in the default catalog ... ok
- MODULE in search path should be replaced by module_dir. ... ok
- MODULE in search path should be removed if module_dir==None. ... ok
- If MODULE is absent, module_dir shouldn't be in search path. ... ok
- Make sure environment variable is getting used. ... ok
- Be sure we get at least one file even without specifying the path. ... ok
- Ignore bad paths in the path. ... ok
- test_clear_module_directory (test_catalog.TestCatalog) ... ok
- test_get_environ_path (test_catalog.TestCatalog) ... ok
- Shouldn't get any files when temp doesn't exist and no path set. ... ok
- Shouldn't get a single file from the temp dir. ... ok
- test_set_module_directory (test_catalog.TestCatalog) ... ok
- Check that we can create a file in the writable directory ... ok
- Check that we can create a file in the writable directory ... ok
- There should always be a writable file -- even if search paths contain ... ok
- test_bad_path (test_catalog.TestCatalogPath) ... ok
- test_current (test_catalog.TestCatalogPath) ... ok
- test_default (test_catalog.TestCatalogPath) ... ok
- test_module (test_catalog.TestCatalogPath) ... ok
- test_path (test_catalog.TestCatalogPath) ... ok
- test_user (test_catalog.TestCatalogPath) ... ok
- test_is_writable (test_catalog.TestDefaultDir) ... ok
- get_test_dir (test_catalog.TestGetCatalog) ... ok
- test_create_catalog (test_catalog.TestGetCatalog) ... ok
- test_nonexistent_catalog_is_none (test_catalog.TestGetCatalog) ... ok
- test_assign_variable_types (test_ext_tools.TestAssignVariableTypes) ... ok
- test_numpy_scalar_spec.setup_test_location ... ok
- test_numpy_scalar_spec.teardown_test_location ... ok
- test_error1 (test_size_check.TestBinaryOpSize) ... ok
- test_error2 (test_size_check.TestBinaryOpSize) ... ok
- test_scalar (test_size_check.TestBinaryOpSize) ... ok
- test_x1 (test_size_check.TestBinaryOpSize) ... ok
- test_x_y (test_size_check.TestBinaryOpSize) ... ok
- test_x_y2 (test_size_check.TestBinaryOpSize) ... ok
- test_x_y3 (test_size_check.TestBinaryOpSize) ... ok
- test_x_y4 (test_size_check.TestBinaryOpSize) ... ok
- test_x_y5 (test_size_check.TestBinaryOpSize) ... ok
- test_x_y6 (test_size_check.TestBinaryOpSize) ... ok
- test_x_y7 (test_size_check.TestBinaryOpSize) ... ok
- test_y1 (test_size_check.TestBinaryOpSize) ... ok
- test_error1 (test_size_check.TestDummyArray) ... ok
- test_error2 (test_size_check.TestDummyArray) ... ok
- test_scalar (test_size_check.TestDummyArray) ... ok
- test_x1 (test_size_check.TestDummyArray) ... ok
- test_x_y (test_size_check.TestDummyArray) ... ok
- test_x_y2 (test_size_check.TestDummyArray) ... ok
- test_x_y3 (test_size_check.TestDummyArray) ... ok
- test_x_y4 (test_size_check.TestDummyArray) ... ok
- test_x_y5 (test_size_check.TestDummyArray) ... ok
- test_x_y6 (test_size_check.TestDummyArray) ... ok
- test_x_y7 (test_size_check.TestDummyArray) ... ok
- test_y1 (test_size_check.TestDummyArray) ... ok
- test_1d_0 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_1 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_10 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_2 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_3 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_4 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_5 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_6 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_7 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_8 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_9 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_index_0 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_index_1 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_index_2 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_index_3 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_index_calculated (test_size_check.TestDummyArrayIndexing) ... ok
- through a bunch of different indexes at it for good measure. ... ok
- test_1d_stride_0 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_stride_1 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_stride_10 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_stride_11 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_stride_12 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_stride_2 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_stride_3 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_stride_4 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_stride_5 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_stride_6 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_stride_7 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_stride_8 (test_size_check.TestDummyArrayIndexing) ... ok
- test_1d_stride_9 (test_size_check.TestDummyArrayIndexing) ... ok
- test_2d_0 (test_size_check.TestDummyArrayIndexing) ... ok
- test_2d_1 (test_size_check.TestDummyArrayIndexing) ... ok
- test_2d_2 (test_size_check.TestDummyArrayIndexing) ... ok
- through a bunch of different indexes at it for good measure. ... ok
- through a bunch of different indexes at it for good measure. ... ok
- test_calculated_index (test_size_check.TestExpressions) ... ok
- test_calculated_index2 (test_size_check.TestExpressions) ... ok
- test_generic_1d (test_size_check.TestExpressions) ... ok
- test_single_index (test_size_check.TestExpressions) ... ok
- test_scalar (test_size_check.TestMakeSameLength) ... ok
- test_x_scalar (test_size_check.TestMakeSameLength) ... ok
- test_x_short (test_size_check.TestMakeSameLength) ... ok
- test_y_scalar (test_size_check.TestMakeSameLength) ... ok
- test_y_short (test_size_check.TestMakeSameLength) ... ok
- test_1d_0 (test_size_check.TestReduction) ... ok
- test_2d_0 (test_size_check.TestReduction) ... ok
- test_2d_1 (test_size_check.TestReduction) ... ok
- test_3d_0 (test_size_check.TestReduction) ... ok
- test_error0 (test_size_check.TestReduction) ... ok
- test_error1 (test_size_check.TestReduction) ... ok
- test_exclusive_end (test_slice_handler.TestBuildSliceAtom) ... ok
- match slice from a[1:] ... ok
- match slice from a[1::] ... ok
- match slice from a[1:2] ... ok
- match slice from a[1:2:] ... ok
- match slice from a[1:2:3] ... ok
- match slice from a[1::3] ... ok
- match slice from a[:] ... ok
- match slice from a[::] ... ok
- match slice from a[:2] ... ok
- match slice from a[:2:] ... ok
- match slice from a[:2:3] ... ok
- match slice from a[:1+i+2:] ... ok
- match slice from a[0] ... ok
- match slice from a[::3] ... ok
- transform a[:,:] = b[:,1:1+2:3] *(c[1-2+i:,:] - c[:,:]) ... ok
- test_type_match_array (test_standard_array_spec.TestArrayConverter) ... ok
- test_type_match_int (test_standard_array_spec.TestArrayConverter) ... ok
- test_type_match_string (test_standard_array_spec.TestArrayConverter) ... ok
- ======================================================================
- FAIL: line-search Newton conjugate gradient optimization routine
- ----------------------------------------------------------------------
- Traceback (most recent call last):
- File "/usr/lib/python2.6/site-packages/scipy/optimize/tests/test_optimize.py", line 192, in test_ncg
- atol=1e-14, rtol=1e-7), self.trace[3:5]
- AssertionError: [array([ -4.35700753e-07, -5.24869435e-01, 4.87527480e-01]), array([ -4.35700753e-07, -5.24869358e-01, 4.87527751e-01])]
- ======================================================================
- FAIL: test_distributions.test_all_distributions('nakagami', (1.9169412179474561,), 0.01)
- ----------------------------------------------------------------------
- Traceback (most recent call last):
- File "/usr/lib/python2.6/site-packages/nose/case.py", line 186, in runTest
- self.test(*self.arg)
- File "/usr/lib/python2.6/site-packages/scipy/stats/tests/test_distributions.py", line 51, in check_distribution
- "; alpha = " + str(alpha) + "\nargs = " + str(args)
- AssertionError: D = 1.0; pval = 0.0; alpha = 0.01
- args = (1.9169412179474561,)
- 1.0,0.0 = <module 'scipy.stats' from '/usr/lib/python2.6/site-packages/scipy/stats/__init__.pyc'>.kstest('nakagami','',(1.9169412179474561,)=(1.9169412179474561,), N=1000)
- #if (pval < alpha):
- # D,pval = stats.kstest(dist,'',args=args, N=1000)
- >> assert (0.0 > 0.01), "D = " + str(1.0) + "; pval = " + str(0.0) + \
- "; alpha = " + str(0.01) + "\nargs = " + str((1.9169412179474561,))
- ----------------------------------------------------------------------
- Ran 4668 tests in 211.153s
- FAILED (KNOWNFAIL=12, SKIP=34, failures=2)
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