reports:ce2ca02
Test executed on commit ce2ca0237e7ba13a0942afa7e8245a2138045913
Report generated on 28-Jun-2016 at 15:39:41
Environment
| Platform | Linux-3.16.0-70-generic-x86_64-with-debian-jessie-sid |
| Python | 2.7.11 |
Summary
0 tests ran in 27.64 seconds.
0 passed, 0 skipped, 0 failed, 18 errors.
0 expected failures, 0 unexpected passes.
Results
| Result | Test | Duration | Links | |
|---|---|---|---|---|
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_j_estimators[w7]::setup | 0.15 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz'> func = <function <lambda> at 0x7fae869e96e0>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_j_blue_estimators[w7]::setup | 0.00 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz'> func = <function <lambda> at 0x7fae7fd83aa0>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_last_line_interactions[w7]::setup | 0.00 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz'> func = <function <lambda> at 0x7fae7fd62578>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_nubar_estimators[w7]::setup | 0.00 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz'> func = <function <lambda> at 0x7fae7fa976e0>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_ws[w7]::setup | 0.01 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz'> func = <function <lambda> at 0x7fae7fa97668>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_luminosity_inner[w7]::setup | 0.00 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz'> func = <function <lambda> at 0x7fae7fabe848>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_spectrum[w7]::setup | 0.00 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz'> func = <function <lambda> at 0x7fae7fab3848>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_montecarlo_properties[w7]::setup | 0.00 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz'> func = <function <lambda> at 0x7fae7f97b8c0>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_shell_temperature[w7]::setup | 0.00 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz'> func = <function <lambda> at 0x7fae7f97b938>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/w7/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_j_estimators[at]::setup | 0.00 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz'> func = <function <lambda> at 0x7fae7f909848>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_j_blue_estimators[at]::setup | 0.01 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz'> func = <function <lambda> at 0x7fae7f8ec848>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_last_line_interactions[at]::setup | 0.00 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz'> func = <function <lambda> at 0x7fae7f85a848>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_nubar_estimators[at]::setup | 0.01 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz'> func = <function <lambda> at 0x7fae7f889848>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_ws[at]::setup | 0.00 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz'> func = <function <lambda> at 0x7fae7f7b77d0>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_luminosity_inner[at]::setup | 0.01 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz'> func = <function <lambda> at 0x7fae7f758848>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_spectrum[at]::setup | 0.00 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz'> func = <function <lambda> at 0x7fae7f7588c0>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_montecarlo_properties[at]::setup | 0.01 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz'> func = <function <lambda> at 0x7fae7f718848>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError | |
| Error | lib.linux-x86_64-2.7/tardis/tests/tests_slow/test_w7.py::TestW7::()::test_shell_temperature[at]::setup | 0.00 |
self = <CallInfo when='setup' exception: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz'> func = <function <lambda> at 0x7fae7fa53848>, when = 'setup' > ??? _pytest.runner:149: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _pytest.runner:137: in <lambda> ??? _pytest.core:521: in __call__ ??? _pytest.core:528: in _docall ??? _pytest.core:393: in execute ??? _pytest.core:113: in wrapped_call ??? _pytest.core:138: in get_result ??? _pytest.core:123: in __init__ ??? _pytest.core:394: in execute ??? _pytest.runner:86: in pytest_runtest_setup ??? _pytest.runner:403: in prepare ??? _pytest.python:1197: in setup ??? _pytest.python:702: in fillfixtures ??? _pytest.python:1345: in _fillfixtures ??? _pytest.python:1388: in getfuncargvalue ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1883: in execute ??? _pytest.python:1405: in _get_active_fixturedef ??? _pytest.python:1451: in _getfuncargvalue ??? _pytest.python:1896: in execute ??? _pytest.python:1921: in execute ??? _pytest.python:1842: in call_fixture_func ??? tardis/tests/tests_slow/conftest.py:102: in reference ndarrays = dict(np.load(os.path.join(reference_dirpath, "ndarrays.npz"))) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ file = '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz', mmap_mode = None, allow_pickle = True, fix_imports = True, encoding = 'ASCII' def load(file, mmap_mode=None, allow_pickle=True, fix_imports=True, encoding='ASCII'): """ Load arrays or pickled objects from ``.npy``, ``.npz`` or pickled files. Parameters ---------- file : file-like object or string The file to read. File-like objects must support the ``seek()`` and ``read()`` methods. Pickled files require that the file-like object support the ``readline()`` method as well. mmap_mode : {None, 'r+', 'r', 'w+', 'c'}, optional If not None, then memory-map the file, using the given mode (see `numpy.memmap` for a detailed description of the modes). A memory-mapped array is kept on disk. However, it can be accessed and sliced like any ndarray. Memory mapping is especially useful for accessing small fragments of large files without reading the entire file into memory. allow_pickle : bool, optional Allow loading pickled object arrays stored in npy files. Reasons for disallowing pickles include security, as loading pickled data can execute arbitrary code. If pickles are disallowed, loading object arrays will fail. Default: True fix_imports : bool, optional Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. If `fix_imports` is True, pickle will try to map the old Python 2 names to the new names used in Python 3. encoding : str, optional What encoding to use when reading Python 2 strings. Only useful when loading Python 2 generated pickled files on Python 3, which includes npy/npz files containing object arrays. Values other than 'latin1', 'ASCII', and 'bytes' are not allowed, as they can corrupt numerical data. Default: 'ASCII' Returns ------- result : array, tuple, dict, etc. Data stored in the file. For ``.npz`` files, the returned instance of NpzFile class must be closed to avoid leaking file descriptors. Raises ------ IOError If the input file does not exist or cannot be read. ValueError The file contains an object array, but allow_pickle=False given. See Also -------- save, savez, savez_compressed, loadtxt memmap : Create a memory-map to an array stored in a file on disk. Notes ----- - If the file contains pickle data, then whatever object is stored in the pickle is returned. - If the file is a ``.npy`` file, then a single array is returned. - If the file is a ``.npz`` file, then a dictionary-like object is returned, containing ``{filename: array}`` key-value pairs, one for each file in the archive. - If the file is a ``.npz`` file, the returned value supports the context manager protocol in a similar fashion to the open function:: with load('foo.npz') as data: a = data['a'] The underlying file descriptor is closed when exiting the 'with' block. Examples -------- Store data to disk, and load it again: >>> np.save('/tmp/123', np.array([[1, 2, 3], [4, 5, 6]])) >>> np.load('/tmp/123.npy') array([[1, 2, 3], [4, 5, 6]]) Store compressed data to disk, and load it again: >>> a=np.array([[1, 2, 3], [4, 5, 6]]) >>> b=np.array([1, 2]) >>> np.savez('/tmp/123.npz', a=a, b=b) >>> data = np.load('/tmp/123.npz') >>> data['a'] array([[1, 2, 3], [4, 5, 6]]) >>> data['b'] array([1, 2]) >>> data.close() Mem-map the stored array, and then access the second row directly from disk: >>> X = np.load('/tmp/123.npy', mmap_mode='r') >>> X[1, :] memmap([4, 5, 6]) """ import gzip own_fid = False if isinstance(file, basestring): > fid = open(file, "rb") E IOError: [Errno 2] No such file or directory: '/home/darth_sidious/Documents/TARDIS/slow/w7/at/ndarrays.npz' /home/darth_sidious/anaconda2/envs/tardis/lib/python2.7/site-packages/numpy/lib/npyio.py:362: IOError |
reports/ce2ca02.txt · Last modified: 2016/06/28 12:09 by karandesai96
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