Deploy

.travis.yml

@@ -1,3 +1,5 @@
+dist: trusty
+
 branches:
   only:
   - master
@@ -6,7 +8,6 @@ branches:
 language: python - "2.7"
 
 before_install:
-    - echo "54.230.142.136 apt.dockerproject.org" | sudo tee -a /etc/hosts
     - wget http://repo.continuum.io/miniconda/Miniconda-latest-Linux-x86_64.sh -O miniconda.sh
     - chmod +x miniconda.sh
     - "./miniconda.sh -b"

install.sh

@@ -0,0 +1,71 @@
+#!/bin/bash
+# This script is meant to be called by the "install" step defined in
+# .travis.yml. See http://docs.travis-ci.com/ for more details.
+# The behavior of the script is controlled by environment variabled defined
+# in the .travis.yml in the top level folder of the project.
+
+# License: 3-clause BSD
+
+set -e
+
+# Fix the compilers to workaround avoid having the Python 3.4 build
+# lookup for g++44 unexpectedly.
+export CC=gcc
+export CXX=g++
+
+
+if [[ "$DISTRIB" == "conda" ]]; then
+    # Deactivate the travis-provided virtual environment and setup a
+    # conda-based environment instead
+    deactivate
+
+    # Use the miniconda installer for faster download / install of conda
+    # itself
+    wget http://repo.continuum.io/miniconda/Miniconda-3.6.0-Linux-x86_64.sh \
+        -O miniconda.sh
+    chmod +x miniconda.sh && ./miniconda.sh -b
+    export PATH=/home/travis/miniconda/bin:$PATH
+    conda update --yes conda
+
+    # Configure the conda environment and put it in the path using the
+    # provided versions
+    if [[ "$INSTALL_MKL" == "true" ]]; then
+        conda create -n testenv --yes python=$PYTHON_VERSION pip nose \
+            numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION numpy scipy \
+            libgfortran mkl
+    else
+        conda create -n testenv --yes python=$PYTHON_VERSION pip nose \
+            numpy=$NUMPY_VERSION scipy=$SCIPY_VERSION libgfortran
+    fi
+    source activate testenv
+
+
+elif [[ "$DISTRIB" == "ubuntu" ]]; then
+    # At the time of writing numpy 1.9.1 is included in the travis
+    # virtualenv but we want to used numpy installed through apt-get
+    # install.
+    deactivate
+    # Create a new virtualenv using system site packages for numpy and scipy
+    virtualenv --system-site-packages testvenv
+    source testvenv/bin/activate
+    pip install nose
+fi
+
+if [[ "$COVERAGE" == "true" ]]; then
+    pip install coverage coveralls
+fi
+
+pip install --user travis-sphinx
+
+# Build scikit-learn in the install.sh script to collapse the verbose
+# build output in the travis output when it succeeds.
+python --version
+python -c "import numpy; print('numpy %s' % numpy.__version__)"
+python -c "import scipy; print('scipy %s' % scipy.__version__)"
+
+cp -r translate/* doc
+cd doc
+travis-sphinx --source=. --nowarn build
+cd target/doc/build
+echo "sklearn.lzjqsdd.com" > CNAME
+cd ../../..

sklearn/__check_build/__init__.py

@@ -0,0 +1,46 @@
+""" Module to give helpful messages to the user that did not
+compile the scikit properly.
+"""
+import os
+
+INPLACE_MSG = """
+It appears that you are importing a local scikit-learn source tree. For
+this, you need to have an inplace install. Maybe you are in the source
+directory and you need to try from another location."""
+
+STANDARD_MSG = """
+If you have used an installer, please check that it is suited for your
+Python version, your operating system and your platform."""
+
+
+def raise_build_error(e):
+    # Raise a comprehensible error and list the contents of the
+    # directory to help debugging on the mailing list.
+    local_dir = os.path.split(__file__)[0]
+    msg = STANDARD_MSG
+    if local_dir == "sklearn/__check_build":
+        # Picking up the local install: this will work only if the
+        # install is an 'inplace build'
+        msg = INPLACE_MSG
+    dir_content = list()
+    for i, filename in enumerate(os.listdir(local_dir)):
+        if ((i + 1) % 3):
+            dir_content.append(filename.ljust(26))
+        else:
+            dir_content.append(filename + '\n')
+    raise ImportError("""%s
+___________________________________________________________________________
+Contents of %s:
+%s
+___________________________________________________________________________
+It seems that scikit-learn has not been built correctly.
+
+If you have installed scikit-learn from source, please do not forget
+to build the package before using it: run `python setup.py install` or
+`make` in the source directory.
+%s""" % (e, local_dir, ''.join(dir_content).strip(), msg))
+
+try:
+    from ._check_build import check_build
+except ImportError as e:
+    raise_build_error(e)

sklearn/__check_build/_check_build.pyx

@@ -0,0 +1,2 @@
+def check_build():
+    return

sklearn/__check_build/setup.py

@@ -0,0 +1,18 @@
+# Author: Virgile Fritsch <virgile.fritsch@inria.fr>
+# License: BSD 3 clause
+
+import numpy
+
+
+def configuration(parent_package='', top_path=None):
+    from numpy.distutils.misc_util import Configuration
+    config = Configuration('__check_build', parent_package, top_path)
+    config.add_extension('_check_build',
+                         sources=['_check_build.pyx'],
+                         include_dirs=[numpy.get_include()])
+
+    return config
+
+if __name__ == '__main__':
+    from numpy.distutils.core import setup
+    setup(**configuration(top_path='').todict())

sklearn/__init__.py

@@ -0,0 +1,87 @@
+"""
+Machine learning module for Python
+==================================
+
+sklearn is a Python module integrating classical machine
+learning algorithms in the tightly-knit world of scientific Python
+packages (numpy, scipy, matplotlib).
+
+It aims to provide simple and efficient solutions to learning problems
+that are accessible to everybody and reusable in various contexts:
+machine-learning as a versatile tool for science and engineering.
+
+See http://scikit-learn.org for complete documentation.
+"""
+import sys
+import re
+import warnings
+
+
+# Make sure that DeprecationWarning within this package always gets printed
+warnings.filterwarnings('always', category=DeprecationWarning,
+                        module='^{0}\.'.format(re.escape(__name__)))
+
+# PEP0440 compatible formatted version, see:
+# https://www.python.org/dev/peps/pep-0440/
+#
+# Generic release markers:
+#   X.Y
+#   X.Y.Z   # For bugfix releases
+#
+# Admissible pre-release markers:
+#   X.YaN   # Alpha release
+#   X.YbN   # Beta release
+#   X.YrcN  # Release Candidate
+#   X.Y     # Final release
+#
+# Dev branch marker is: 'X.Y.dev' or 'X.Y.devN' where N is an integer.
+# 'X.Y.dev0' is the canonical version of 'X.Y.dev'
+#
+__version__ = '0.19.dev0'
+
+
+try:
+    # This variable is injected in the __builtins__ by the build
+    # process. It used to enable importing subpackages of sklearn when
+    # the binaries are not built
+    __SKLEARN_SETUP__
+except NameError:
+    __SKLEARN_SETUP__ = False
+
+if __SKLEARN_SETUP__:
+    sys.stderr.write('Partial import of sklearn during the build process.\n')
+    # We are not importing the rest of the scikit during the build
+    # process, as it may not be compiled yet
+else:
+    from . import __check_build
+    from .base import clone
+    __check_build  # avoid flakes unused variable error
+
+    __all__ = ['calibration', 'cluster', 'covariance', 'cross_decomposition',
+               'cross_validation', 'datasets', 'decomposition', 'dummy',
+               'ensemble', 'exceptions', 'externals', 'feature_extraction',
+               'feature_selection', 'gaussian_process', 'grid_search',
+               'isotonic', 'kernel_approximation', 'kernel_ridge',
+               'learning_curve', 'linear_model', 'manifold', 'metrics',
+               'mixture', 'model_selection', 'multiclass', 'multioutput',
+               'naive_bayes', 'neighbors', 'neural_network', 'pipeline',
+               'preprocessing', 'random_projection', 'semi_supervised',
+               'svm', 'tree', 'discriminant_analysis',
+               # Non-modules:
+               'clone']
+
+
+def setup_module(module):
+    """Fixture for the tests to assure globally controllable seeding of RNGs"""
+    import os
+    import numpy as np
+    import random
+
+    # It could have been provided in the environment
+    _random_seed = os.environ.get('SKLEARN_SEED', None)
+    if _random_seed is None:
+        _random_seed = np.random.uniform() * (2 ** 31 - 1)
+    _random_seed = int(_random_seed)
+    print("I: Seeding RNGs with %r" % _random_seed)
+    np.random.seed(_random_seed)
+    random.seed(_random_seed)

sklearn/_build_utils/__init__.py

@@ -0,0 +1,84 @@
+"""
+Utilities useful during the build.
+"""
+# author: Andy Mueller, Gael Varoquaux
+# license: BSD
+
+from __future__ import division, print_function, absolute_import
+
+import os
+
+from distutils.version import LooseVersion
+
+from numpy.distutils.system_info import get_info
+
+DEFAULT_ROOT = 'sklearn'
+CYTHON_MIN_VERSION = '0.23'
+
+
+def get_blas_info():
+    def atlas_not_found(blas_info_):
+        def_macros = blas_info.get('define_macros', [])
+        for x in def_macros:
+            if x[0] == "NO_ATLAS_INFO":
+                # if x[1] != 1 we should have lapack
+                # how do we do that now?
+                return True
+            if x[0] == "ATLAS_INFO":
+                if "None" in x[1]:
+                    # this one turned up on FreeBSD
+                    return True
+        return False
+
+    blas_info = get_info('blas_opt', 0)
+    if (not blas_info) or atlas_not_found(blas_info):
+        cblas_libs = ['cblas']
+        blas_info.pop('libraries', None)
+    else:
+        cblas_libs = blas_info.pop('libraries', [])
+
+    return cblas_libs, blas_info
+
+
+def build_from_c_and_cpp_files(extensions):
+    """Modify the extensions to build from the .c and .cpp files.
+
+    This is useful for releases, this way cython is not required to
+    run python setup.py install.
+    """
+    for extension in extensions:
+        sources = []
+        for sfile in extension.sources:
+            path, ext = os.path.splitext(sfile)
+            if ext in ('.pyx', '.py'):
+                if extension.language == 'c++':
+                    ext = '.cpp'
+                else:
+                    ext = '.c'
+                sfile = path + ext
+            sources.append(sfile)
+        extension.sources = sources
+
+
+def maybe_cythonize_extensions(top_path, config):
+    """Tweaks for building extensions between release and development mode."""
+    is_release = os.path.exists(os.path.join(top_path, 'PKG-INFO'))
+
+    if is_release:
+        build_from_c_and_cpp_files(config.ext_modules)
+    else:
+        message = ('Please install cython with a version >= {0} in order '
+                   'to build a scikit-learn development version.').format(
+                       CYTHON_MIN_VERSION)
+        try:
+            import Cython
+            if LooseVersion(Cython.__version__) < CYTHON_MIN_VERSION:
+                message += ' Your version of Cython was {0}.'.format(
+                    Cython.__version__)
+                raise ValueError(message)
+            from Cython.Build import cythonize
+        except ImportError as exc:
+            exc.args += (message,)
+            raise
+
+        config.ext_modules = cythonize(config.ext_modules)