Hi Paul (Bo?).
Which version of scikit-learn are you using and which version of numpy
and scipy? I guess scipy 0.16 numpy 1.10 and scikit-learn 0.16.2.
The errors for the newer versions of scipy and numpy are fixed in the
scikit-learn development version.
You shouldn't be concerned by these errors and your code will still be
correct.
If you are planning to use Gaussian Processes or PLS, you might want to
update to the development version of scikit-learn (or wait a week for a
release).
Best,
Andy
On 10/29/2015 05:28 PM, Bo Liu wrote:
> Hi, here is what I got when I tired to install the sklearn.
>
> Thanks
>
> Paul
>
>
> ERROR: sklearn.gaussian_process.tests.test_gaussian_process.test_2d
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/tests/test_gaussian_process.py",
> line 64, in test_2d
> gp.fit(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 338, in fit
> self._arg_max_reduced_likelihood_function()
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 730, in _arg_max_reduced_likelihood_function
> iprint=0)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/cobyla.py",
> line 177, in fmin_cobyla
> **opts)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/cobyla.py",
> line 244, in _minimize_cobyla
> f = c['fun'](x0, *c['args'])
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 707, in <lambda>
> log10t[i] - np.log10(self.thetaL[0, i]))
> IndexError: index 1 is out of bounds for axis 0 with size 1
>
> ======================================================================
> ERROR: sklearn.gaussian_process.tests.test_gaussian_process.test_2d_2d
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/tests/test_gaussian_process.py",
> line 94, in test_2d_2d
> gp.fit(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 338, in fit
> self._arg_max_reduced_likelihood_function()
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 730, in _arg_max_reduced_likelihood_function
> iprint=0)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/cobyla.py",
> line 177, in fmin_cobyla
> **opts)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/cobyla.py",
> line 244, in _minimize_cobyla
> f = c['fun'](x0, *c['args'])
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 707, in <lambda>
> log10t[i] - np.log10(self.thetaL[0, i]))
> IndexError: index 1 is out of bounds for axis 0 with size 1
>
> ======================================================================
> ERROR:
> sklearn.gaussian_process.tests.test_gaussian_process.test_more_builtin_correlation_models
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/tests/test_gaussian_process.py",
> line 114, in test_more_builtin_correlation_models
> test_2d(regr='constant', corr=corr, random_start=random_start)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/tests/test_gaussian_process.py",
> line 64, in test_2d
> gp.fit(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 338, in fit
> self._arg_max_reduced_likelihood_function()
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 730, in _arg_max_reduced_likelihood_function
> iprint=0)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/cobyla.py",
> line 177, in fmin_cobyla
> **opts)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/cobyla.py",
> line 244, in _minimize_cobyla
> f = c['fun'](x0, *c['args'])
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 707, in <lambda>
> log10t[i] - np.log10(self.thetaL[0, i]))
> IndexError: index 1 is out of bounds for axis 0 with size 1
>
> ======================================================================
> ERROR:
> sklearn.gaussian_process.tests.test_gaussian_process.test_ordinary_kriging
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/tests/test_gaussian_process.py",
> line 123, in test_ordinary_kriging
> test_2d(regr='linear', beta0=[0., 0.5, 0.5])
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/tests/test_gaussian_process.py",
> line 64, in test_2d
> gp.fit(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 338, in fit
> self._arg_max_reduced_likelihood_function()
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 730, in _arg_max_reduced_likelihood_function
> iprint=0)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/cobyla.py",
> line 177, in fmin_cobyla
> **opts)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/cobyla.py",
> line 244, in _minimize_cobyla
> f = c['fun'](x0, *c['args'])
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 707, in <lambda>
> log10t[i] - np.log10(self.thetaL[0, i]))
> IndexError: index 1 is out of bounds for axis 0 with size 1
>
> ======================================================================
> ERROR: sklearn.gaussian_process.tests.test_gaussian_process.test_random_starts
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/tests/test_gaussian_process.py",
> line 150, in test_random_starts
> verbose=False).fit(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 338, in fit
> self._arg_max_reduced_likelihood_function()
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 730, in _arg_max_reduced_likelihood_function
> iprint=0)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/cobyla.py",
> line 177, in fmin_cobyla
> **opts)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/scipy/optimize/cobyla.py",
> line 244, in _minimize_cobyla
> f = c['fun'](x0, *c['args'])
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/gaussian_process/gaussian_process.py",
> line 707, in <lambda>
> log10t[i] - np.log10(self.thetaL[0, i]))
> IndexError: index 1 is out of bounds for axis 0 with size 1
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_non_meta_estimators('CCA', <class
> 'sklearn.cross_decomposition.cca_.CCA'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/testing.py",
> line 300, in wrapper
> return fn(*args, **kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 350, in check_estimators_dtypes
> getattr(estimator, method)(X_train)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 414, in predict
> X -= self.x_mean_
> TypeError: Cannot cast ufunc subtract output from dtype('float64') to
> dtype('int64') with casting rule 'same_kind'
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_non_meta_estimators('CCA', <class
> 'sklearn.cross_decomposition.cca_.CCA'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/testing.py",
> line 300, in wrapper
> return fn(*args, **kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 326, in check_fit_score_takes_y
> func(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 440, in fit_transform
> return self.fit(X, y, **fit_params).transform(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 387, in transform
> Y -= self.y_mean_
> TypeError: Cannot cast ufunc subtract output from dtype('float64') to
> dtype('int64') with casting rule 'same_kind'
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_non_meta_estimators('FastICA', <class
> 'sklearn.decomposition.fastica_.FastICA'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/testing.py",
> line 300, in wrapper
> return fn(*args, **kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 345, in check_estimators_dtypes
> estimator.fit(X_train, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/decomposition/fastica_.py",
> line 519, in fit
> self._fit(X, compute_sources=False)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/decomposition/fastica_.py",
> line 475, in _fit
> compute_sources=compute_sources, return_n_iter=True)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/decomposition/fastica_.py",
> line 299, in fastica
> X -= X_mean[:, np.newaxis]
> TypeError: Cannot cast ufunc subtract output from dtype('float64') to
> dtype('int64') with casting rule 'same_kind'
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_non_meta_estimators('KernelRidge',
> <class 'sklearn.kernel_ridge.KernelRidge'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 174, in check_dtype_object
> estimator.fit(X, y.astype(object))
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/kernel_ridge.py",
> line 158, in fit
> copy)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/linear_model/ridge.py",
> line 145, in _solve_cholesky_kernel
> overwrite_a=False)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/scipy/linalg/basic.py",
> line 77, in solve
> b1 = _asarray_validated(b, check_finite=check_finite)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/scipy/_lib/_util.py",
> line 143, in _asarray_validated
> raise ValueError('object arrays are not supported')
> ValueError: object arrays are not supported
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_non_meta_estimators('LarsCV', <class
> 'sklearn.linear_model.least_angle.LarsCV'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/testing.py",
> line 300, in wrapper
> return fn(*args, **kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 345, in check_estimators_dtypes
> estimator.fit(X_train, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/linear_model/least_angle.py",
> line 999, in fit
> for train, test in cv)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.py",
> line 659, in __call__
> self.dispatch(function, args, kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.py",
> line 406, in dispatch
> job = ImmediateApply(func, args, kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.py",
> line 140, in __init__
> self.results = func(*args, **kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/linear_model/least_angle.py",
> line 853, in _lars_path_residues
> X_train -= X_mean
> TypeError: Cannot cast ufunc subtract output from dtype('float64') to
> dtype('int64') with casting rule 'same_kind'
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_non_meta_estimators('LassoLarsCV',
> <class 'sklearn.linear_model.least_angle.LassoLarsCV'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/testing.py",
> line 300, in wrapper
> return fn(*args, **kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 345, in check_estimators_dtypes
> estimator.fit(X_train, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/linear_model/least_angle.py",
> line 999, in fit
> for train, test in cv)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.py",
> line 659, in __call__
> self.dispatch(function, args, kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.py",
> line 406, in dispatch
> job = ImmediateApply(func, args, kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/externals/joblib/parallel.py",
> line 140, in __init__
> self.results = func(*args, **kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/linear_model/least_angle.py",
> line 853, in _lars_path_residues
> X_train -= X_mean
> TypeError: Cannot cast ufunc subtract output from dtype('float64') to
> dtype('int64') with casting rule 'same_kind'
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_non_meta_estimators('Normalizer',
> <class 'sklearn.preprocessing.data.Normalizer'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/testing.py",
> line 300, in wrapper
> return fn(*args, **kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 350, in check_estimators_dtypes
> getattr(estimator, method)(X_train)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/preprocessing/data.py",
> line 689, in transform
> return normalize(X, norm=self.norm, axis=1, copy=copy)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/preprocessing/data.py",
> line 617, in normalize
> norms = row_norms(X)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/extmath.py",
> line 71, in row_norms
> np.sqrt(norms, norms)
> TypeError: ufunc 'sqrt' output (typecode 'd') could not be coerced to
> provided output parameter (typecode 'l') according to the casting rule
> ''same_kind''
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_non_meta_estimators('PLSCanonical',
> <class 'sklearn.cross_decomposition.pls_.PLSCanonical'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/testing.py",
> line 300, in wrapper
> return fn(*args, **kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 350, in check_estimators_dtypes
> getattr(estimator, method)(X_train)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 414, in predict
> X -= self.x_mean_
> TypeError: Cannot cast ufunc subtract output from dtype('float64') to
> dtype('int64') with casting rule 'same_kind'
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_non_meta_estimators('PLSCanonical',
> <class 'sklearn.cross_decomposition.pls_.PLSCanonical'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/testing.py",
> line 300, in wrapper
> return fn(*args, **kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 326, in check_fit_score_takes_y
> func(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 440, in fit_transform
> return self.fit(X, y, **fit_params).transform(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 387, in transform
> Y -= self.y_mean_
> TypeError: Cannot cast ufunc subtract output from dtype('float64') to
> dtype('int64') with casting rule 'same_kind'
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_non_meta_estimators('PLSRegression',
> <class 'sklearn.cross_decomposition.pls_.PLSRegression'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/testing.py",
> line 300, in wrapper
> return fn(*args, **kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 350, in check_estimators_dtypes
> getattr(estimator, method)(X_train)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 414, in predict
> X -= self.x_mean_
> TypeError: Cannot cast ufunc subtract output from dtype('float64') to
> dtype('int64') with casting rule 'same_kind'
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_non_meta_estimators('PLSRegression',
> <class 'sklearn.cross_decomposition.pls_.PLSRegression'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/testing.py",
> line 300, in wrapper
> return fn(*args, **kwargs)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 326, in check_fit_score_takes_y
> func(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 440, in fit_transform
> return self.fit(X, y, **fit_params).transform(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 387, in transform
> Y -= self.y_mean_
> TypeError: Cannot cast ufunc subtract output from dtype('float64') to
> dtype('int64') with casting rule 'same_kind'
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_transformers('CCA', <class
> 'sklearn.cross_decomposition.cca_.CCA'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 188, in check_transformer
> _check_transformer(name, Transformer, X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 238, in _check_transformer
> X_pred = transformer.fit_transform(X, y=y_)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 440, in fit_transform
> return self.fit(X, y, **fit_params).transform(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 387, in transform
> Y -= self.y_mean_
> TypeError: Cannot cast ufunc subtract output from dtype('float64') to
> dtype('int64') with casting rule 'same_kind'
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_transformers('PLSCanonical', <class
> 'sklearn.cross_decomposition.pls_.PLSCanonical'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 188, in check_transformer
> _check_transformer(name, Transformer, X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 238, in _check_transformer
> X_pred = transformer.fit_transform(X, y=y_)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 440, in fit_transform
> return self.fit(X, y, **fit_params).transform(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 387, in transform
> Y -= self.y_mean_
> TypeError: Cannot cast ufunc subtract output from dtype('float64') to
> dtype('int64') with casting rule 'same_kind'
>
> ======================================================================
> ERROR: sklearn.tests.test_common.test_transformers('PLSRegression', <class
> 'sklearn.cross_decomposition.pls_.PLSRegression'>)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/nose/case.py",
> line 197, in runTest
> self.test(*self.arg)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 188, in check_transformer
> _check_transformer(name, Transformer, X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/utils/estimator_checks.py",
> line 238, in _check_transformer
> X_pred = transformer.fit_transform(X, y=y_)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 440, in fit_transform
> return self.fit(X, y, **fit_params).transform(X, y)
> File
> "/Users/paul/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/sklearn/cross_decomposition/pls_.py",
> line 387, in transform
> Y -= self.y_mean_
> TypeError: Cannot cast ufunc subtract output from dtype('float64') to
> dtype('int64') with casting rule 'same_kind'
>
> ----------------------------------------------------------------------
> Ran 4092 tests in 118.090s
>
> FAILED (SKIP=18, errors=19)
> PauldeMacBook-Pro:~ paul$
> ------------------------------------------------------------------------------
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