Python numpy.ndfromtxt() 使用实例

The following are code examples for showing how to use . They are extracted from open source Python projects. You can vote up the examples you like or vote down the exmaples you don’t like. You can also save this page to your account.

Example 1

def test_usecols(self):
        # Test the selection of columns
        # Select 1 column
        control = np.array([[1, 2], [3, 4]], float)
        data = TextIO()
        np.savetxt(data, control)
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=(1,))
        assert_equal(test, control[:, 1])
        #
        control = np.array([[1, 2, 3], [3, 4, 5]], float)
        data = TextIO()
        np.savetxt(data, control)
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=(1, 2))
        assert_equal(test, control[:, 1:])
        # Testing with arrays instead of tuples.
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=np.array([1, 2]))
        assert_equal(test, control[:, 1:]) 

Example 2

def test_invalid_raise(self):
        # Test invalid raise
        data = ["1, 1, 1, 1, 1"] * 50
        for i in range(5):
            data[10 * i] = "2, 2, 2, 2 2"
        data.insert(0, "a, b, c, d, e")
        mdata = TextIO("\n".join(data))
        #
        kwargs = dict(delimiter=",", dtype=None, names=True)
        # XXX: is there a better way to get the return value of the
        # callable in assert_warns ?
        ret = {}

        def f(_ret={}):
            _ret['mtest'] = np.ndfromtxt(mdata, invalid_raise=False, **kwargs)
        assert_warns(ConversionWarning, f, _ret=ret)
        mtest = ret['mtest']
        assert_equal(len(mtest), 45)
        assert_equal(mtest, np.ones(45, dtype=[(_, int) for _ in 'abcde']))
        #
        mdata.seek(0)
        assert_raises(ValueError, np.ndfromtxt, mdata,
                      delimiter=",", names=True) 

Example 3

def test_auto_dtype_largeint(self):
        # Regression test for numpy/numpy#5635 whereby large integers could
        # cause OverflowErrors.

        # Test the automatic definition of the output dtype
        #
        # 2**66 = 73786976294838206464 => should convert to float
        # 2**34 = 17179869184 => should convert to int64
        # 2**10 = 1024 => should convert to int (int32 on 32-bit systems,
        #                 int64 on 64-bit systems)

        data = TextIO('73786976294838206464 17179869184 1024')

        test = np.ndfromtxt(data, dtype=None)

        assert_equal(test.dtype.names, ['f0', 'f1', 'f2'])

        assert_(test.dtype['f0'] == np.float)
        assert_(test.dtype['f1'] == np.int64)
        assert_(test.dtype['f2'] == np.integer)

        assert_allclose(test['f0'], 73786976294838206464.)
        assert_equal(test['f1'], 17179869184)
        assert_equal(test['f2'], 1024) 

Example 4

def test_usecols(self):
        # Test the selection of columns
        # Select 1 column
        control = np.array([[1, 2], [3, 4]], float)
        data = TextIO()
        np.savetxt(data, control)
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=(1,))
        assert_equal(test, control[:, 1])
        #
        control = np.array([[1, 2, 3], [3, 4, 5]], float)
        data = TextIO()
        np.savetxt(data, control)
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=(1, 2))
        assert_equal(test, control[:, 1:])
        # Testing with arrays instead of tuples.
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=np.array([1, 2]))
        assert_equal(test, control[:, 1:]) 

Example 5

def test_invalid_raise(self):
        # Test invalid raise
        data = ["1, 1, 1, 1, 1"] * 50
        for i in range(5):
            data[10 * i] = "2, 2, 2, 2 2"
        data.insert(0, "a, b, c, d, e")
        mdata = TextIO("\n".join(data))
        #
        kwargs = dict(delimiter=",", dtype=None, names=True)
        # XXX: is there a better way to get the return value of the
        # callable in assert_warns ?
        ret = {}

        def f(_ret={}):
            _ret['mtest'] = np.ndfromtxt(mdata, invalid_raise=False, **kwargs)
        assert_warns(ConversionWarning, f, _ret=ret)
        mtest = ret['mtest']
        assert_equal(len(mtest), 45)
        assert_equal(mtest, np.ones(45, dtype=[(_, int) for _ in 'abcde']))
        #
        mdata.seek(0)
        assert_raises(ValueError, np.ndfromtxt, mdata,
                      delimiter=",", names=True) 

Example 6

def test_auto_dtype_largeint(self):
        # Regression test for numpy/numpy#5635 whereby large integers could
        # cause OverflowErrors.

        # Test the automatic definition of the output dtype
        #
        # 2**66 = 73786976294838206464 => should convert to float
        # 2**34 = 17179869184 => should convert to int64
        # 2**10 = 1024 => should convert to int (int32 on 32-bit systems,
        #                 int64 on 64-bit systems)

        data = TextIO('73786976294838206464 17179869184 1024')

        test = np.ndfromtxt(data, dtype=None)

        assert_equal(test.dtype.names, ['f0', 'f1', 'f2'])

        assert_(test.dtype['f0'] == np.float)
        assert_(test.dtype['f1'] == np.int64)
        assert_(test.dtype['f2'] == np.integer)

        assert_allclose(test['f0'], 73786976294838206464.)
        assert_equal(test['f1'], 17179869184)
        assert_equal(test['f2'], 1024) 

Example 7

def test_usecols(self):
        # Test the selection of columns
        # Select 1 column
        control = np.array([[1, 2], [3, 4]], float)
        data = TextIO()
        np.savetxt(data, control)
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=(1,))
        assert_equal(test, control[:, 1])
        #
        control = np.array([[1, 2, 3], [3, 4, 5]], float)
        data = TextIO()
        np.savetxt(data, control)
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=(1, 2))
        assert_equal(test, control[:, 1:])
        # Testing with arrays instead of tuples.
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=np.array([1, 2]))
        assert_equal(test, control[:, 1:]) 

Example 8

def test_invalid_raise(self):
        # Test invalid raise
        data = ["1, 1, 1, 1, 1"] * 50
        for i in range(5):
            data[10 * i] = "2, 2, 2, 2 2"
        data.insert(0, "a, b, c, d, e")
        mdata = TextIO("\n".join(data))
        #
        kwargs = dict(delimiter=",", dtype=None, names=True)
        # XXX: is there a better way to get the return value of the
        # callable in assert_warns ?
        ret = {}

        def f(_ret={}):
            _ret['mtest'] = np.ndfromtxt(mdata, invalid_raise=False, **kwargs)
        assert_warns(ConversionWarning, f, _ret=ret)
        mtest = ret['mtest']
        assert_equal(len(mtest), 45)
        assert_equal(mtest, np.ones(45, dtype=[(_, int) for _ in 'abcde']))
        #
        mdata.seek(0)
        assert_raises(ValueError, np.ndfromtxt, mdata,
                      delimiter=",", names=True) 

Example 9

def test_auto_dtype_largeint(self):
        # Regression test for numpy/numpy#5635 whereby large integers could
        # cause OverflowErrors.

        # Test the automatic definition of the output dtype
        #
        # 2**66 = 73786976294838206464 => should convert to float
        # 2**34 = 17179869184 => should convert to int64
        # 2**10 = 1024 => should convert to int (int32 on 32-bit systems,
        #                 int64 on 64-bit systems)

        data = TextIO('73786976294838206464 17179869184 1024')

        test = np.ndfromtxt(data, dtype=None)

        assert_equal(test.dtype.names, ['f0', 'f1', 'f2'])

        assert test.dtype['f0'] == np.float
        assert test.dtype['f1'] == np.int64
        assert test.dtype['f2'] == np.integer

        assert_allclose(test['f0'], 73786976294838206464.)
        assert_equal(test['f1'], 17179869184)
        assert_equal(test['f2'], 1024) 

Example 10

def test_usecols(self):
        # Test the selection of columns
        # Select 1 column
        control = np.array([[1, 2], [3, 4]], float)
        data = TextIO()
        np.savetxt(data, control)
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=(1,))
        assert_equal(test, control[:, 1])
        #
        control = np.array([[1, 2, 3], [3, 4, 5]], float)
        data = TextIO()
        np.savetxt(data, control)
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=(1, 2))
        assert_equal(test, control[:, 1:])
        # Testing with arrays instead of tuples.
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=np.array([1, 2]))
        assert_equal(test, control[:, 1:]) 

Example 11

def test_invalid_raise(self):
        # Test invalid raise
        data = ["1, 1, 1, 1, 1"] * 50
        for i in range(5):
            data[10 * i] = "2, 2, 2, 2 2"
        data.insert(0, "a, b, c, d, e")
        mdata = TextIO("\n".join(data))
        #
        kwargs = dict(delimiter=",", dtype=None, names=True)
        # XXX: is there a better way to get the return value of the
        # callable in assert_warns ?
        ret = {}

        def f(_ret={}):
            _ret['mtest'] = np.ndfromtxt(mdata, invalid_raise=False, **kwargs)
        assert_warns(ConversionWarning, f, _ret=ret)
        mtest = ret['mtest']
        assert_equal(len(mtest), 45)
        assert_equal(mtest, np.ones(45, dtype=[(_, int) for _ in 'abcde']))
        #
        mdata.seek(0)
        assert_raises(ValueError, np.ndfromtxt, mdata,
                      delimiter=",", names=True) 

Example 12

def test_auto_dtype_largeint(self):
        # Regression test for numpy/numpy#5635 whereby large integers could
        # cause OverflowErrors.

        # Test the automatic definition of the output dtype
        #
        # 2**66 = 73786976294838206464 => should convert to float
        # 2**34 = 17179869184 => should convert to int64
        # 2**10 = 1024 => should convert to int (int32 on 32-bit systems,
        #                 int64 on 64-bit systems)

        data = TextIO('73786976294838206464 17179869184 1024')

        test = np.ndfromtxt(data, dtype=None)

        assert_equal(test.dtype.names, ['f0', 'f1', 'f2'])

        assert_(test.dtype['f0'] == np.float)
        assert_(test.dtype['f1'] == np.int64)
        assert_(test.dtype['f2'] == np.integer)

        assert_allclose(test['f0'], 73786976294838206464.)
        assert_equal(test['f1'], 17179869184)
        assert_equal(test['f2'], 1024) 

Example 13

def test_usecols(self):
        # Test the selection of columns
        # Select 1 column
        control = np.array([[1, 2], [3, 4]], float)
        data = TextIO()
        np.savetxt(data, control)
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=(1,))
        assert_equal(test, control[:, 1])
        #
        control = np.array([[1, 2, 3], [3, 4, 5]], float)
        data = TextIO()
        np.savetxt(data, control)
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=(1, 2))
        assert_equal(test, control[:, 1:])
        # Testing with arrays instead of tuples.
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=np.array([1, 2]))
        assert_equal(test, control[:, 1:]) 

Example 14

def test_invalid_raise(self):
        # Test invalid raise
        data = ["1, 1, 1, 1, 1"] * 50
        for i in range(5):
            data[10 * i] = "2, 2, 2, 2 2"
        data.insert(0, "a, b, c, d, e")
        mdata = TextIO("\n".join(data))
        #
        kwargs = dict(delimiter=",", dtype=None, names=True)
        # XXX: is there a better way to get the return value of the
        # callable in assert_warns ?
        ret = {}

        def f(_ret={}):
            _ret['mtest'] = np.ndfromtxt(mdata, invalid_raise=False, **kwargs)
        assert_warns(ConversionWarning, f, _ret=ret)
        mtest = ret['mtest']
        assert_equal(len(mtest), 45)
        assert_equal(mtest, np.ones(45, dtype=[(_, int) for _ in 'abcde']))
        #
        mdata.seek(0)
        assert_raises(ValueError, np.ndfromtxt, mdata,
                      delimiter=",", names=True) 

Example 15

def test_auto_dtype_largeint(self):
        # Regression test for numpy/numpy#5635 whereby large integers could
        # cause OverflowErrors.

        # Test the automatic definition of the output dtype
        #
        # 2**66 = 73786976294838206464 => should convert to float
        # 2**34 = 17179869184 => should convert to int64
        # 2**10 = 1024 => should convert to int (int32 on 32-bit systems,
        #                 int64 on 64-bit systems)

        data = TextIO('73786976294838206464 17179869184 1024')

        test = np.ndfromtxt(data, dtype=None)

        assert_equal(test.dtype.names, ['f0', 'f1', 'f2'])

        assert_(test.dtype['f0'] == np.float)
        assert_(test.dtype['f1'] == np.int64)
        assert_(test.dtype['f2'] == np.integer)

        assert_allclose(test['f0'], 73786976294838206464.)
        assert_equal(test['f1'], 17179869184)
        assert_equal(test['f2'], 1024) 

Example 16

def test_usecols(self):
        # Test the selection of columns
        # Select 1 column
        control = np.array([[1, 2], [3, 4]], float)
        data = TextIO()
        np.savetxt(data, control)
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=(1,))
        assert_equal(test, control[:, 1])
        #
        control = np.array([[1, 2, 3], [3, 4, 5]], float)
        data = TextIO()
        np.savetxt(data, control)
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=(1, 2))
        assert_equal(test, control[:, 1:])
        # Testing with arrays instead of tuples.
        data.seek(0)
        test = np.ndfromtxt(data, dtype=float, usecols=np.array([1, 2]))
        assert_equal(test, control[:, 1:]) 

Example 17

def test_invalid_raise(self):
        # Test invalid raise
        data = ["1, 1, 1, 1, 1"] * 50
        for i in range(5):
            data[10 * i] = "2, 2, 2, 2 2"
        data.insert(0, "a, b, c, d, e")
        mdata = TextIO("\n".join(data))
        #
        kwargs = dict(delimiter=",", dtype=None, names=True)
        # XXX: is there a better way to get the return value of the
        # callable in assert_warns ?
        ret = {}

        def f(_ret={}):
            _ret['mtest'] = np.ndfromtxt(mdata, invalid_raise=False, **kwargs)
        assert_warns(ConversionWarning, f, _ret=ret)
        mtest = ret['mtest']
        assert_equal(len(mtest), 45)
        assert_equal(mtest, np.ones(45, dtype=[(_, int) for _ in 'abcde']))
        #
        mdata.seek(0)
        assert_raises(ValueError, np.ndfromtxt, mdata,
                      delimiter=",", names=True) 

Example 18

def test_auto_dtype_largeint(self):
        # Regression test for numpy/numpy#5635 whereby large integers could
        # cause OverflowErrors.

        # Test the automatic definition of the output dtype
        #
        # 2**66 = 73786976294838206464 => should convert to float
        # 2**34 = 17179869184 => should convert to int64
        # 2**10 = 1024 => should convert to int (int32 on 32-bit systems,
        #                 int64 on 64-bit systems)

        data = TextIO('73786976294838206464 17179869184 1024')

        test = np.ndfromtxt(data, dtype=None)

        assert_equal(test.dtype.names, ['f0', 'f1', 'f2'])

        assert_(test.dtype['f0'] == np.float)
        assert_(test.dtype['f1'] == np.int64)
        assert_(test.dtype['f2'] == np.integer)

        assert_allclose(test['f0'], 73786976294838206464.)
        assert_equal(test['f1'], 17179869184)
        assert_equal(test['f2'], 1024) 

Example 19

def test_record(self):
        # Test w/ explicit dtype
        data = TextIO('1 2\n3 4')
        test = np.ndfromtxt(data, dtype=[('x', np.int32), ('y', np.int32)])
        control = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
        assert_equal(test, control)
        #
        data = TextIO('M 64.0 75.0\nF 25.0 60.0')
        descriptor = {'names': ('gender', 'age', 'weight'),
                      'formats': ('S1', 'i4', 'f4')}
        control = np.array([('M', 64.0, 75.0), ('F', 25.0, 60.0)],
                           dtype=descriptor)
        test = np.ndfromtxt(data, dtype=descriptor)
        assert_equal(test, control) 

Example 20

def test_array(self):
        # Test outputing a standard ndarray
        data = TextIO('1 2\n3 4')
        control = np.array([[1, 2], [3, 4]], dtype=int)
        test = np.ndfromtxt(data, dtype=int)
        assert_array_equal(test, control)
        #
        data.seek(0)
        control = np.array([[1, 2], [3, 4]], dtype=float)
        test = np.loadtxt(data, dtype=float)
        assert_array_equal(test, control) 

Example 21

def test_1D(self):
        # Test squeezing to 1D
        control = np.array([1, 2, 3, 4], int)
        #
        data = TextIO('1\n2\n3\n4\n')
        test = np.ndfromtxt(data, dtype=int)
        assert_array_equal(test, control)
        #
        data = TextIO('1,2,3,4\n')
        test = np.ndfromtxt(data, dtype=int, delimiter=',')
        assert_array_equal(test, control) 

Example 22

def test_comments(self):
        # Test the stripping of comments
        control = np.array([1, 2, 3, 5], int)
        # Comment on its own line
        data = TextIO('# comment\n1,2,3,5\n')
        test = np.ndfromtxt(data, dtype=int, delimiter=',', comments='#')
        assert_equal(test, control)
        # Comment at the end of a line
        data = TextIO('1,2,3,5# comment\n')
        test = np.ndfromtxt(data, dtype=int, delimiter=',', comments='#')
        assert_equal(test, control) 

Example 23

def test_skiprows(self):
        # Test row skipping
        control = np.array([1, 2, 3, 5], int)
        kwargs = dict(dtype=int, delimiter=',')
        #
        data = TextIO('comment\n1,2,3,5\n')
        test = np.ndfromtxt(data, skip_header=1, **kwargs)
        assert_equal(test, control)
        #
        data = TextIO('# comment\n1,2,3,5\n')
        test = np.loadtxt(data, skiprows=1, **kwargs)
        assert_equal(test, control) 

Example 24

def test_auto_dtype(self):
        # Test the automatic definition of the output dtype
        data = TextIO('A 64 75.0 3+4j True\nBCD 25 60.0 5+6j False')
        test = np.ndfromtxt(data, dtype=None)
        control = [np.array([b'A', b'BCD']),
                   np.array([64, 25]),
                   np.array([75.0, 60.0]),
                   np.array([3 + 4j, 5 + 6j]),
                   np.array([True, False]), ]
        assert_equal(test.dtype.names, ['f0', 'f1', 'f2', 'f3', 'f4'])
        for (i, ctrl) in enumerate(control):
            assert_equal(test['f%i' % i], ctrl) 

Example 25

def test_auto_dtype_uniform(self):
        # Tests whether the output dtype can be uniformized
        data = TextIO('1 2 3 4\n5 6 7 8\n')
        test = np.ndfromtxt(data, dtype=None)
        control = np.array([[1, 2, 3, 4], [5, 6, 7, 8]])
        assert_equal(test, control) 

Example 26

def test_fancy_dtype(self):
        # Check that a nested dtype isn't MIA
        data = TextIO('1,2,3.0\n4,5,6.0\n')
        fancydtype = np.dtype([('x', int), ('y', [('t', int), ('s', float)])])
        test = np.ndfromtxt(data, dtype=fancydtype, delimiter=',')
        control = np.array([(1, (2, 3.0)), (4, (5, 6.0))], dtype=fancydtype)
        assert_equal(test, control) 

Example 27

def test_names_overwrite(self):
        # Test overwriting the names of the dtype
        descriptor = {'names': ('g', 'a', 'w'),
                      'formats': ('S1', 'i4', 'f4')}
        data = TextIO(b'M 64.0 75.0\nF 25.0 60.0')
        names = ('gender', 'age', 'weight')
        test = np.ndfromtxt(data, dtype=descriptor, names=names)
        descriptor['names'] = names
        control = np.array([('M', 64.0, 75.0),
                            ('F', 25.0, 60.0)], dtype=descriptor)
        assert_equal(test, control) 

Example 28

def test_autonames_and_usecols(self):
        # Tests names and usecols
        data = TextIO('A B C D\n aaaa 121 45 9.1')
        test = np.ndfromtxt(data, usecols=('A', 'C', 'D'),
                            names=True, dtype=None)
        control = np.array(('aaaa', 45, 9.1),
                           dtype=[('A', '|S4'), ('C', int), ('D', float)])
        assert_equal(test, control) 

Example 29

def test_converters_with_usecols_and_names(self):
        # Tests names and usecols
        data = TextIO('A B C D\n aaaa 121 45 9.1')
        test = np.ndfromtxt(data, usecols=('A', 'C', 'D'), names=True,
                            dtype=None, converters={'C': lambda s: 2 * int(s)})
        control = np.array(('aaaa', 90, 9.1),
                           dtype=[('A', '|S4'), ('C', int), ('D', float)])
        assert_equal(test, control) 

Example 30

def test_converters_cornercases(self):
        # Test the conversion to datetime.
        converter = {
            'date': lambda s: strptime(s, '%Y-%m-%d %H:%M:%SZ')}
        data = TextIO('2009-02-03 12:00:00Z, 72214.0')
        test = np.ndfromtxt(data, delimiter=',', dtype=None,
                            names=['date', 'stid'], converters=converter)
        control = np.array((datetime(2009, 2, 3), 72214.),
                           dtype=[('date', np.object_), ('stid', float)])
        assert_equal(test, control) 

Example 31

def test_converters_cornercases2(self):
        # Test the conversion to datetime64.
        converter = {
            'date': lambda s: np.datetime64(strptime(s, '%Y-%m-%d %H:%M:%SZ'))}
        data = TextIO('2009-02-03 12:00:00Z, 72214.0')
        test = np.ndfromtxt(data, delimiter=',', dtype=None,
                            names=['date', 'stid'], converters=converter)
        control = np.array((datetime(2009, 2, 3), 72214.),
                           dtype=[('date', 'datetime64[us]'), ('stid', float)])
        assert_equal(test, control) 

Example 32

def test_unused_converter(self):
        # Test whether unused converters are forgotten
        data = TextIO("1 21\n  3 42\n")
        test = np.ndfromtxt(data, usecols=(1,),
                            converters={0: lambda s: int(s, 16)})
        assert_equal(test, [21, 42])
        #
        data.seek(0)
        test = np.ndfromtxt(data, usecols=(1,),
                            converters={1: lambda s: int(s, 16)})
        assert_equal(test, [33, 66]) 

Example 33

def test_dtype_with_converters(self):
        dstr = "2009; 23; 46"
        test = np.ndfromtxt(TextIO(dstr,),
                            delimiter=";", dtype=float, converters={0: bytes})
        control = np.array([('2009', 23., 46)],
                           dtype=[('f0', '|S4'), ('f1', float), ('f2', float)])
        assert_equal(test, control)
        test = np.ndfromtxt(TextIO(dstr,),
                            delimiter=";", dtype=float, converters={0: float})
        control = np.array([2009., 23., 46],)
        assert_equal(test, control) 

Example 34

def test_missing(self):
        data = TextIO('1,2,3,,5\n')
        test = np.ndfromtxt(data, dtype=int, delimiter=',',
                            converters={3: lambda s: int(s or - 999)})
        control = np.array([1, 2, 3, -999, 5], int)
        assert_equal(test, control) 

Example 35

def test_usecols_with_structured_dtype(self):
        # Test usecols with an explicit structured dtype
        data = TextIO("JOE 70.1 25.3\nBOB 60.5 27.9")
        names = ['stid', 'temp']
        dtypes = ['S4', 'f8']
        test = np.ndfromtxt(
            data, usecols=(0, 2), dtype=list(zip(names, dtypes)))
        assert_equal(test['stid'], [b"JOE", b"BOB"])
        assert_equal(test['temp'], [25.3, 27.9]) 

Example 36

def test_shaped_dtype(self):
        c = TextIO("aaaa  1.0  8.0  1 2 3 4 5 6")
        dt = np.dtype([('name', 'S4'), ('x', float), ('y', float),
                       ('block', int, (2, 3))])
        x = np.ndfromtxt(c, dtype=dt)
        a = np.array([('aaaa', 1.0, 8.0, [[1, 2, 3], [4, 5, 6]])],
                     dtype=dt)
        assert_array_equal(x, a) 

Example 37

def test_default_field_format(self):
        # Test default format
        data = "0, 1, 2.3\n4, 5, 6.7"
        mtest = np.ndfromtxt(TextIO(data),
                             delimiter=",", dtype=None, defaultfmt="f%02i")
        ctrl = np.array([(0, 1, 2.3), (4, 5, 6.7)],
                        dtype=[("f00", int), ("f01", int), ("f02", float)])
        assert_equal(mtest, ctrl) 

Example 38

def test_single_dtype_wo_names(self):
        # Test single dtype w/o names
        data = "0, 1, 2.3\n4, 5, 6.7"
        mtest = np.ndfromtxt(TextIO(data),
                             delimiter=",", dtype=float, defaultfmt="f%02i")
        ctrl = np.array([[0., 1., 2.3], [4., 5., 6.7]], dtype=float)
        assert_equal(mtest, ctrl) 

Example 39

def test_single_dtype_w_explicit_names(self):
        # Test single dtype w explicit names
        data = "0, 1, 2.3\n4, 5, 6.7"
        mtest = np.ndfromtxt(TextIO(data),
                             delimiter=",", dtype=float, names="a, b, c")
        ctrl = np.array([(0., 1., 2.3), (4., 5., 6.7)],
                        dtype=[(_, float) for _ in "abc"])
        assert_equal(mtest, ctrl) 

Example 40

def test_single_dtype_w_implicit_names(self):
        # Test single dtype w implicit names
        data = "a, b, c\n0, 1, 2.3\n4, 5, 6.7"
        mtest = np.ndfromtxt(TextIO(data),
                             delimiter=",", dtype=float, names=True)
        ctrl = np.array([(0., 1., 2.3), (4., 5., 6.7)],
                        dtype=[(_, float) for _ in "abc"])
        assert_equal(mtest, ctrl) 

Example 41

def test_easy_structured_dtype(self):
        # Test easy structured dtype
        data = "0, 1, 2.3\n4, 5, 6.7"
        mtest = np.ndfromtxt(TextIO(data), delimiter=",",
                             dtype=(int, float, float), defaultfmt="f_%02i")
        ctrl = np.array([(0, 1., 2.3), (4, 5., 6.7)],
                        dtype=[("f_00", int), ("f_01", float), ("f_02", float)])
        assert_equal(mtest, ctrl) 

Example 42

def test_incomplete_names(self):
        # Test w/ incomplete names
        data = "A,,C\n0,1,2\n3,4,5"
        kwargs = dict(delimiter=",", names=True)
        # w/ dtype=None
        ctrl = np.array([(0, 1, 2), (3, 4, 5)],
                        dtype=[(_, int) for _ in ('A', 'f0', 'C')])
        test = np.ndfromtxt(TextIO(data), dtype=None, **kwargs)
        assert_equal(test, ctrl)
        # w/ default dtype
        ctrl = np.array([(0, 1, 2), (3, 4, 5)],
                        dtype=[(_, float) for _ in ('A', 'f0', 'C')])
        test = np.ndfromtxt(TextIO(data), **kwargs) 

Example 43

def test_fixed_width_names(self):
        # Test fix-width w/ names
        data = "    A    B   C\n    0    1 2.3\n   45   67   9."
        kwargs = dict(delimiter=(5, 5, 4), names=True, dtype=None)
        ctrl = np.array([(0, 1, 2.3), (45, 67, 9.)],
                        dtype=[('A', int), ('B', int), ('C', float)])
        test = np.ndfromtxt(TextIO(data), **kwargs)
        assert_equal(test, ctrl)
        #
        kwargs = dict(delimiter=5, names=True, dtype=None)
        ctrl = np.array([(0, 1, 2.3), (45, 67, 9.)],
                        dtype=[('A', int), ('B', int), ('C', float)])
        test = np.ndfromtxt(TextIO(data), **kwargs)
        assert_equal(test, ctrl) 

Example 44

def test_filling_values(self):
        # Test missing values
        data = b"1, 2, 3\n1, , 5\n0, 6, \n"
        kwargs = dict(delimiter=",", dtype=None, filling_values=-999)
        ctrl = np.array([[1, 2, 3], [1, -999, 5], [0, 6, -999]], dtype=int)
        test = np.ndfromtxt(TextIO(data), **kwargs)
        assert_equal(test, ctrl) 

Example 45

def test_record(self):
        # Test w/ explicit dtype
        data = TextIO('1 2\n3 4')
        test = np.ndfromtxt(data, dtype=[('x', np.int32), ('y', np.int32)])
        control = np.array([(1, 2), (3, 4)], dtype=[('x', 'i4'), ('y', 'i4')])
        assert_equal(test, control)
        #
        data = TextIO('M 64.0 75.0\nF 25.0 60.0')
        descriptor = {'names': ('gender', 'age', 'weight'),
                      'formats': ('S1', 'i4', 'f4')}
        control = np.array([('M', 64.0, 75.0), ('F', 25.0, 60.0)],
                           dtype=descriptor)
        test = np.ndfromtxt(data, dtype=descriptor)
        assert_equal(test, control) 

Example 46

def test_array(self):
        # Test outputing a standard ndarray
        data = TextIO('1 2\n3 4')
        control = np.array([[1, 2], [3, 4]], dtype=int)
        test = np.ndfromtxt(data, dtype=int)
        assert_array_equal(test, control)
        #
        data.seek(0)
        control = np.array([[1, 2], [3, 4]], dtype=float)
        test = np.loadtxt(data, dtype=float)
        assert_array_equal(test, control) 

Example 47

def test_1D(self):
        # Test squeezing to 1D
        control = np.array([1, 2, 3, 4], int)
        #
        data = TextIO('1\n2\n3\n4\n')
        test = np.ndfromtxt(data, dtype=int)
        assert_array_equal(test, control)
        #
        data = TextIO('1,2,3,4\n')
        test = np.ndfromtxt(data, dtype=int, delimiter=',')
        assert_array_equal(test, control) 

Example 48

def test_comments(self):
        # Test the stripping of comments
        control = np.array([1, 2, 3, 5], int)
        # Comment on its own line
        data = TextIO('# comment\n1,2,3,5\n')
        test = np.ndfromtxt(data, dtype=int, delimiter=',', comments='#')
        assert_equal(test, control)
        # Comment at the end of a line
        data = TextIO('1,2,3,5# comment\n')
        test = np.ndfromtxt(data, dtype=int, delimiter=',', comments='#')
        assert_equal(test, control) 

Example 49

def test_skiprows(self):
        # Test row skipping
        control = np.array([1, 2, 3, 5], int)
        kwargs = dict(dtype=int, delimiter=',')
        #
        data = TextIO('comment\n1,2,3,5\n')
        test = np.ndfromtxt(data, skip_header=1, **kwargs)
        assert_equal(test, control)
        #
        data = TextIO('# comment\n1,2,3,5\n')
        test = np.loadtxt(data, skiprows=1, **kwargs)
        assert_equal(test, control) 

Example 50

def test_auto_dtype(self):
        # Test the automatic definition of the output dtype
        data = TextIO('A 64 75.0 3+4j True\nBCD 25 60.0 5+6j False')
        test = np.ndfromtxt(data, dtype=None)
        control = [np.array([b'A', b'BCD']),
                   np.array([64, 25]),
                   np.array([75.0, 60.0]),
                   np.array([3 + 4j, 5 + 6j]),
                   np.array([True, False]), ]
        assert_equal(test.dtype.names, ['f0', 'f1', 'f2', 'f3', 'f4'])
        for (i, ctrl) in enumerate(control):
            assert_equal(test['f%i' % i], ctrl) 
点赞

发表评论

电子邮件地址不会被公开。 必填项已用*标注