Python numpy.setbufsize() Examples

The following are 30 code examples of numpy.setbufsize(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module numpy , or try the search function .
Example #1
Source File: test_regression.py    From pySINDy with MIT License 5 votes vote down vote up 
def test_reduce_big_object_array(self):
        # Ticket #713
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #2
Source File: test_regression.py    From keras-lambda with MIT License 5 votes vote down vote up 
def test_reduce_big_object_array(self, level=rlevel):
        # Ticket #713
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #3
Source File: test_umath.py    From keras-lambda with MIT License 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #4
Source File: test_regression.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_reduce_big_object_array(self):
        # Ticket #713
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #5
Source File: test_umath.py    From twitter-stock-recommendation with MIT License 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #6
Source File: test_regression.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 5 votes vote down vote up 
def test_reduce_big_object_array(self):
        # Ticket #713
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #7
Source File: test_umath.py    From Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda with MIT License 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #8
Source File: test_regression.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_reduce_big_object_array(self):
        # Ticket #713
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #9
Source File: test_umath.py    From coffeegrindsize with MIT License 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #10
Source File: test_regression.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_reduce_big_object_array(self, level=rlevel):
        # Ticket #713
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #11
Source File: test_umath.py    From elasticintel with GNU General Public License v3.0 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #12
Source File: test_regression.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_reduce_big_object_array(self, level=rlevel):
        """Ticket #713"""
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #13
Source File: test_umath.py    From ImageFusion with MIT License 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    res = np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #14
Source File: test_regression.py    From mxnet-lambda with Apache License 2.0 5 votes vote down vote up 
def test_reduce_big_object_array(self, level=rlevel):
        # Ticket #713
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #15
Source File: test_umath.py    From mxnet-lambda with Apache License 2.0 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #16
Source File: test_umath.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #17
Source File: test_umath.py    From pySINDy with MIT License 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #18
Source File: test_regression.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_reduce_big_object_array(self):
        # Ticket #713
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #19
Source File: test_umath.py    From predictive-maintenance-using-machine-learning with Apache License 2.0 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #20
Source File: test_regression.py    From GraphicDesignPatternByPython with MIT License 5 votes vote down vote up 
def test_reduce_big_object_array(self):
        # Ticket #713
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #21
Source File: test_umath.py    From GraphicDesignPatternByPython with MIT License 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #22
Source File: test_regression.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up 
def test_reduce_big_object_array(self):
        # Ticket #713
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #23
Source File: test_umath.py    From Mastering-Elasticsearch-7.0 with MIT License 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #24
Source File: test_regression.py    From Computable with MIT License 5 votes vote down vote up 
def test_reduce_big_object_array(self, level=rlevel):
        """Ticket #713"""
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #25
Source File: test_umath.py    From Computable with MIT License 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    res = np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #26
Source File: test_regression.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_reduce_big_object_array(self):
        # Ticket #713
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #27
Source File: test_umath.py    From vnpy_crypto with MIT License 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #28
Source File: test_regression.py    From auto-alt-text-lambda-api with MIT License 5 votes vote down vote up 
def test_reduce_big_object_array(self, level=rlevel):
        # Ticket #713
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)
Example #29
Source File: test_umath.py    From auto-alt-text-lambda-api with MIT License 5 votes vote down vote up 
def test_reduceat():
    """Test bug in reduceat when structured arrays are not copied."""
    db = np.dtype([('name', 'S11'), ('time', np.int64), ('value', np.float32)])
    a = np.empty([100], dtype=db)
    a['name'] = 'Simple'
    a['time'] = 10
    a['value'] = 100
    indx = [0, 7, 15, 25]

    h2 = []
    val1 = indx[0]
    for val2 in indx[1:]:
        h2.append(np.add.reduce(a['value'][val1:val2]))
        val1 = val2
    h2.append(np.add.reduce(a['value'][val1:]))
    h2 = np.array(h2)

    # test buffered -- this should work
    h1 = np.add.reduceat(a['value'], indx)
    assert_array_almost_equal(h1, h2)

    # This is when the error occurs.
    # test no buffer
    np.setbufsize(32)
    h1 = np.add.reduceat(a['value'], indx)
    np.setbufsize(np.UFUNC_BUFSIZE_DEFAULT)
    assert_array_almost_equal(h1, h2)
Example #30
Source File: test_regression.py    From recruit with Apache License 2.0 5 votes vote down vote up 
def test_reduce_big_object_array(self):
        # Ticket #713
        oldsize = np.setbufsize(10*16)
        a = np.array([None]*161, object)
        assert_(not np.any(a))
        np.setbufsize(oldsize)