Python numpy.setbufsize() Examples

The following are 30 code examples for showing how to use numpy.setbufsize(). These examples are extracted from open source projects. 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.

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Example 1
Project: recruit   Author: Frank-qlu   File: test_umath.py    License: 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 2
Project: recruit   Author: Frank-qlu   File: test_regression.py    License: 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 3
Project: auto-alt-text-lambda-api   Author: abhisuri97   File: test_umath.py    License: 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
Project: auto-alt-text-lambda-api   Author: abhisuri97   File: test_regression.py    License: 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 5
Project: vnpy_crypto   Author: birforce   File: test_umath.py    License: 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
Project: vnpy_crypto   Author: birforce   File: test_regression.py    License: 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
Project: Computable   Author: ktraunmueller   File: test_umath.py    License: 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 8
Project: Computable   Author: ktraunmueller   File: test_regression.py    License: 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 9
Project: Mastering-Elasticsearch-7.0   Author: PacktPublishing   File: test_umath.py    License: 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
Project: Mastering-Elasticsearch-7.0   Author: PacktPublishing   File: test_regression.py    License: 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 11
Project: GraphicDesignPatternByPython   Author: Relph1119   File: test_umath.py    License: 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 12
Project: GraphicDesignPatternByPython   Author: Relph1119   File: test_regression.py    License: 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 13
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 14
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 15
Project: pySINDy   Author: luckystarufo   File: test_umath.py    License: 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 16
Project: pySINDy   Author: luckystarufo   File: test_regression.py    License: 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 17
Project: mxnet-lambda   Author: awslabs   File: test_umath.py    License: 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 18
Project: mxnet-lambda   Author: awslabs   File: test_regression.py    License: 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 19
Project: ImageFusion   Author: pfchai   File: test_umath.py    License: 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 20
Project: ImageFusion   Author: pfchai   File: test_regression.py    License: 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 21
Project: elasticintel   Author: securityclippy   File: test_umath.py    License: 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 22
Project: elasticintel   Author: securityclippy   File: test_regression.py    License: 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 23
Project: coffeegrindsize   Author: jgagneastro   File: test_umath.py    License: 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
Project: coffeegrindsize   Author: jgagneastro   File: test_regression.py    License: 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 25
Project: Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda   Author: PacktPublishing   File: test_umath.py    License: 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 26
Project: Serverless-Deep-Learning-with-TensorFlow-and-AWS-Lambda   Author: PacktPublishing   File: test_regression.py    License: 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
Project: twitter-stock-recommendation   Author: alvarobartt   File: test_umath.py    License: 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
Project: twitter-stock-recommendation   Author: alvarobartt   File: test_regression.py    License: 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 29
Project: keras-lambda   Author: sunilmallya   File: test_umath.py    License: 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
Project: keras-lambda   Author: sunilmallya   File: test_regression.py    License: 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)