Python numpy.bytes_() 使用实例

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Example 1

def test_iter_buffering_string():
    # Safe casting disallows shrinking strings
    a = np.array(['abc', 'a', 'abcd'], dtype=np.bytes_)
    assert_equal(a.dtype, np.dtype('S4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                  op_dtypes='S2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='S6')
    assert_equal(i[0], asbytes('abc'))
    assert_equal(i[0].dtype, np.dtype('S6'))

    a = np.array(['abc', 'a', 'abcd'], dtype=np.unicode)
    assert_equal(a.dtype, np.dtype('U4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                    op_dtypes='U2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='U6')
    assert_equal(i[0], sixu('abc'))
    assert_equal(i[0].dtype, np.dtype('U6')) 

Example 2

def read_atlas_annot(atlas_dir, hemi_list=None):
    " Returns atlas annotations "

    if hemi_list is None:
        hemi_list = ['lh', 'rh']

    annot = dict()
    for hemi in hemi_list:
        annot[hemi] = dict()
        annot_path = pjoin(atlas_dir, 'label', '{}.aparc.annot'.format(hemi))
        annot[hemi]['labels'], annot[hemi]['ctab'], annot[hemi]['names'] = nib.freesurfer.io.read_annot(annot_path,
                                                                                                        orig_ids=True)

        # ensuring names are plainstring
        if isinstance(annot[hemi]['names'][0], np.bytes_):
            annot[hemi]['names'] = [bytestr.decode('UTF-8') for bytestr in annot[hemi]['names']]

    return annot 

Example 3

def test_iter_buffering_string():
    # Safe casting disallows shrinking strings
    a = np.array(['abc', 'a', 'abcd'], dtype=np.bytes_)
    assert_equal(a.dtype, np.dtype('S4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                  op_dtypes='S2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='S6')
    assert_equal(i[0], asbytes('abc'))
    assert_equal(i[0].dtype, np.dtype('S6'))

    a = np.array(['abc', 'a', 'abcd'], dtype=np.unicode)
    assert_equal(a.dtype, np.dtype('U4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                    op_dtypes='U2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='U6')
    assert_equal(i[0], sixu('abc'))
    assert_equal(i[0].dtype, np.dtype('U6')) 

Example 4

def hdf_attr_to_dict(attr):
    """
    Convert from HDF attributes to valid dict
    """

    try:
        output_dict = dict(attr)
    except:
        output_dict = {}
        for count in attr:
            try:
                output_dict[count] = attr[count]
            except:
                print('Fail: {}'.format(count))
    
    # String in HDF are treated as numpy bytes_ literals
    # We want out instance in memeory to have Python Strings
    # This does a simple conversion
    for k in output_dict:
        if isinstance(output_dict[k], _np.bytes_):
            output_dict[k] = output_dict[k].decode('UTF-8')
    return output_dict 

Example 5

def test_iter_buffering_string():
    # Safe casting disallows shrinking strings
    a = np.array(['abc', 'a', 'abcd'], dtype=np.bytes_)
    assert_equal(a.dtype, np.dtype('S4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                  op_dtypes='S2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='S6')
    assert_equal(i[0], asbytes('abc'))
    assert_equal(i[0].dtype, np.dtype('S6'))

    a = np.array(['abc', 'a', 'abcd'], dtype=np.unicode)
    assert_equal(a.dtype, np.dtype('U4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                    op_dtypes='U2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='U6')
    assert_equal(i[0], sixu('abc'))
    assert_equal(i[0].dtype, np.dtype('U6')) 

Example 6

def test_iter_buffering_string():
    # Safe casting disallows shrinking strings
    a = np.array(['abc', 'a', 'abcd'], dtype=np.bytes_)
    assert_equal(a.dtype, np.dtype('S4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                  op_dtypes='S2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='S6')
    assert_equal(i[0], asbytes('abc'))
    assert_equal(i[0].dtype, np.dtype('S6'))

    a = np.array(['abc', 'a', 'abcd'], dtype=np.unicode)
    assert_equal(a.dtype, np.dtype('U4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                    op_dtypes='U2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='U6')
    assert_equal(i[0], sixu('abc'))
    assert_equal(i[0].dtype, np.dtype('U6')) 

Example 7

def test_iter_buffering_string():
    # Safe casting disallows shrinking strings
    a = np.array(['abc', 'a', 'abcd'], dtype=np.bytes_)
    assert_equal(a.dtype, np.dtype('S4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                  op_dtypes='S2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='S6')
    assert_equal(i[0], asbytes('abc'))
    assert_equal(i[0].dtype, np.dtype('S6'))

    a = np.array(['abc', 'a', 'abcd'], dtype=np.unicode)
    assert_equal(a.dtype, np.dtype('U4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                    op_dtypes='U2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='U6')
    assert_equal(i[0], sixu('abc'))
    assert_equal(i[0].dtype, np.dtype('U6')) 

Example 8

def test_iter_buffering_string():
    # Safe casting disallows shrinking strings
    a = np.array(['abc', 'a', 'abcd'], dtype=np.bytes_)
    assert_equal(a.dtype, np.dtype('S4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                  op_dtypes='S2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='S6')
    assert_equal(i[0], asbytes('abc'))
    assert_equal(i[0].dtype, np.dtype('S6'))

    a = np.array(['abc', 'a', 'abcd'], dtype=np.unicode)
    assert_equal(a.dtype, np.dtype('U4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                    op_dtypes='U2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='U6')
    assert_equal(i[0], sixu('abc'))
    assert_equal(i[0].dtype, np.dtype('U6')) 

Example 9

def _extract_edge_value(tree, edge):
    ft_idx = edge.calc_record.feature_idx
    split_type = edge.calc_record.split_type
    val = edge.value_encoded
    pivot = edge.calc_record.pivot
    if split_type is CalcRecord.NUM:
        if val == SplitRecord.GREATER:
            return ">{0:.2f}".format(pivot)
        else:
            return "<={0:.2f}".format(pivot)
    elif tree.X_encoders is not None:
        value = tree.X_encoders[ft_idx].single_inv_transform(val)
        if isinstance(value, np.bytes_):
            return value.decode('UTF-8')
        else:
            return value
    else:
        return val 

Example 10

def normalize_attr_strings(a: np.ndarray) -> np.ndarray:
	"""
	Take an np.ndarray of all kinds of string-like elements, and return an array of ascii (np.string_) objects
	"""
	if np.issubdtype(a.dtype, np.object_):
		if np.all([type(x) is str for x in a]) or np.all([type(x) is np.str_ for x in a]) or np.all([type(x) is np.unicode_ for x in a]):
			return np.array([x.encode('ascii', 'xmlcharrefreplace') for x in a])
		elif np.all([type(x) is np.string_ for x in a]) or np.all([type(x) is np.bytes_ for x in a]):
			return a.astype("string_")
		else:
			print(type(a[0]))
			raise ValueError("Arbitrary numpy object arrays not supported (all elements must be string objects).")
	elif np.issubdtype(a.dtype, np.string_) or np.issubdtype(a.dtype, np.object_):
		return a
	elif np.issubdtype(a.dtype, np.str_) or np.issubdtype(a.dtype, np.unicode_):
		return np.array([x.encode('ascii', 'xmlcharrefreplace') for x in a])
	else:
		raise ValueError("String values must be object, ascii or unicode.") 

Example 11

def h5py_dataset_iterator(self,g, prefix=''):
        for key in g.keys():
            item = g[key]
            path = '{}/{}'.format(prefix, key)
            keys = [i for i in item.keys()]
            if isinstance(item[keys[0]], h5py.Dataset): # test for dataset
                data = {'path':path}
                for k in keys:
                    if not isinstance(item[k], h5py.Group):
                        dataset = np.array(item[k].value)

                        if type(dataset) is np.ndarray:
                            if dataset.size != 0:
                                if type(dataset[0]) is np.bytes_:
                                    dataset = [a.decode('ascii') for a in dataset]

                        data.update({k:dataset})

                yield data
            else: # test for group (go down)
                yield from self.h5py_dataset_iterator(item, path) 

Example 12

def get_data(self, path, prefix=''):
        item = self.store[path]
        path = '{}/{}'.format(prefix, path)
        keys = [i for i in item.keys()]
        data = {'path': path}
        # print(path)
        for k in keys:
            if not isinstance(item[k], h5py.Group):
                dataset = np.array(item[k].value)

                if type(dataset) is np.ndarray:
                    if dataset.size != 0:
                        if type(dataset[0]) is np.bytes_:
                            dataset = [a.decode('ascii') for a in dataset]

                data.update({k: dataset})
        return data 

Example 13

def test_iter_buffering_string():
    # Safe casting disallows shrinking strings
    a = np.array(['abc', 'a', 'abcd'], dtype=np.bytes_)
    assert_equal(a.dtype, np.dtype('S4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                  op_dtypes='S2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='S6')
    assert_equal(i[0], asbytes('abc'))
    assert_equal(i[0].dtype, np.dtype('S6'))

    a = np.array(['abc', 'a', 'abcd'], dtype=np.unicode)
    assert_equal(a.dtype, np.dtype('U4'))
    assert_raises(TypeError, nditer, a, ['buffered'], ['readonly'],
                    op_dtypes='U2')
    i = nditer(a, ['buffered'], ['readonly'], op_dtypes='U6')
    assert_equal(i[0], sixu('abc'))
    assert_equal(i[0].dtype, np.dtype('U6')) 

Example 14

def _getconv(dtype):
    """ Find the correct dtype converter. Adapted from matplotlib """

    def floatconv(x):
        x.lower()
        if b'0x' in x:
            return float.fromhex(asstr(x))
        return float(x)

    typ = dtype.type
    if issubclass(typ, np.bool_):
        return lambda x: bool(int(x))
    if issubclass(typ, np.uint64):
        return np.uint64
    if issubclass(typ, np.int64):
        return np.int64
    if issubclass(typ, np.integer):
        return lambda x: int(float(x))
    elif issubclass(typ, np.longdouble):
        return np.longdouble
    elif issubclass(typ, np.floating):
        return floatconv
    elif issubclass(typ, np.complex):
        return lambda x: complex(asstr(x))
    elif issubclass(typ, np.bytes_):
        return bytes
    else:
        return str 

Example 15

def decode_qtypes(cls, value):
        """
        Decode all the QCollection items to normal python types
        """
        if isinstance(value, numpy.bytes_):
            return value.decode("utf-8")
        elif isinstance(value, list):
            return value
        else:
            return value.item() 

Example 16

def _getconv(dtype):
    """ Find the correct dtype converter. Adapted from matplotlib """

    def floatconv(x):
        x.lower()
        if b'0x' in x:
            return float.fromhex(asstr(x))
        return float(x)

    typ = dtype.type
    if issubclass(typ, np.bool_):
        return lambda x: bool(int(x))
    if issubclass(typ, np.uint64):
        return np.uint64
    if issubclass(typ, np.int64):
        return np.int64
    if issubclass(typ, np.integer):
        return lambda x: int(float(x))
    elif issubclass(typ, np.longdouble):
        return np.longdouble
    elif issubclass(typ, np.floating):
        return floatconv
    elif issubclass(typ, np.complex):
        return lambda x: complex(asstr(x))
    elif issubclass(typ, np.bytes_):
        return bytes
    else:
        return str 

Example 17

def encode_ascii(s):
        if isinstance(s, str):
            return s.encode('ascii')
        elif isinstance(s, numpy.ndarray) and \
                issubclass(s.dtype.type, numpy.str_):
            ns = numpy.char.encode(s, 'ascii').view(type(s))
            if ns.dtype.itemsize != s.dtype.itemsize / 4:
                ns = ns.astype((numpy.bytes_, s.dtype.itemsize / 4))
            return ns
        return s 

Example 18

def decode_ascii(s):
        if isinstance(s, bytes):
            return s.decode('ascii')
        elif (isinstance(s, numpy.ndarray) and
              issubclass(s.dtype.type, numpy.bytes_)):
            # np.char.encode/decode annoyingly don't preserve the type of the
            # array, hence the view() call
            # It also doesn't necessarily preserve widths of the strings,
            # hence the astype()
            ns = numpy.char.decode(s, 'ascii').view(type(s))
            if ns.dtype.itemsize / 4 != s.dtype.itemsize:
                ns = ns.astype((numpy.str_, s.dtype.itemsize))
            return ns
        return s 

Example 19

def _ensure_decoded(s):
    """ if we have bytes, decode them to unicode """
    if isinstance(s, (np.bytes_, bytes)):
        s = s.decode(pd.get_option('display.encoding'))
    return s 

Example 20

def test_isscalar_numpy_array_scalars(self):
        self.assertTrue(lib.isscalar(np.int64(1)))
        self.assertTrue(lib.isscalar(np.float64(1.)))
        self.assertTrue(lib.isscalar(np.int32(1)))
        self.assertTrue(lib.isscalar(np.object_('foobar')))
        self.assertTrue(lib.isscalar(np.str_('foobar')))
        self.assertTrue(lib.isscalar(np.unicode_(u('foobar'))))
        self.assertTrue(lib.isscalar(np.bytes_(b'foobar')))
        self.assertTrue(lib.isscalar(np.datetime64('2014-01-01')))
        self.assertTrue(lib.isscalar(np.timedelta64(1, 'h'))) 

Example 21

def _ensure_decoded(s):
    """ if we have bytes, decode them to unicode """
    if isinstance(s, np.bytes_):
        s = s.decode('UTF-8')
    return s 

Example 22

def _getconv(dtype):
    """ Find the correct dtype converter. Adapted from matplotlib """

    def floatconv(x):
        x.lower()
        if b'0x' in x:
            return float.fromhex(asstr(x))
        return float(x)

    typ = dtype.type
    if issubclass(typ, np.bool_):
        return lambda x: bool(int(x))
    if issubclass(typ, np.uint64):
        return np.uint64
    if issubclass(typ, np.int64):
        return np.int64
    if issubclass(typ, np.integer):
        return lambda x: int(float(x))
    elif issubclass(typ, np.floating):
        return floatconv
    elif issubclass(typ, np.complex):
        return lambda x: complex(asstr(x))
    elif issubclass(typ, np.bytes_):
        return bytes
    else:
        return str 

Example 23

def _getconv(dtype):
    """ Find the correct dtype converter. Adapted from matplotlib """

    def floatconv(x):
        x.lower()
        if b'0x' in x:
            return float.fromhex(asstr(x))
        return float(x)

    typ = dtype.type
    if issubclass(typ, np.bool_):
        return lambda x: bool(int(x))
    if issubclass(typ, np.uint64):
        return np.uint64
    if issubclass(typ, np.int64):
        return np.int64
    if issubclass(typ, np.integer):
        return lambda x: int(float(x))
    elif issubclass(typ, np.longdouble):
        return np.longdouble
    elif issubclass(typ, np.floating):
        return floatconv
    elif issubclass(typ, np.complex):
        return lambda x: complex(asstr(x))
    elif issubclass(typ, np.bytes_):
        return bytes
    else:
        return str 

Example 24

def _getconv(dtype):
    """ Find the correct dtype converter. Adapted from matplotlib """

    def floatconv(x):
        x.lower()
        if b'0x' in x:
            return float.fromhex(asstr(x))
        return float(x)

    typ = dtype.type
    if issubclass(typ, np.bool_):
        return lambda x: bool(int(x))
    if issubclass(typ, np.uint64):
        return np.uint64
    if issubclass(typ, np.int64):
        return np.int64
    if issubclass(typ, np.integer):
        return lambda x: int(float(x))
    elif issubclass(typ, np.longdouble):
        return np.longdouble
    elif issubclass(typ, np.floating):
        return floatconv
    elif issubclass(typ, np.complex):
        return lambda x: complex(asstr(x))
    elif issubclass(typ, np.bytes_):
        return bytes
    else:
        return str 

Example 25

def export_text(decision_tree, feature_names=None):
    """Export a decision tree in WEKA like string format.
    Parameters
    ----------
    decision_tree : decision tree classifier
    feature_names : list of strings, optional (default=None)
        Names of each of the features.
    Returns
    -------
    ret : string
    """
    max_depth = 500

    def build_string(node, indent, depth):
        ret = ''
        if node is None or depth > max_depth:
            return ''
        if node.is_feature:
            ret += '\n'
            template = '|   ' * indent
            if feature_names is None:
                template += str(node.details.feature_idx)
            else:
                template += feature_names[node.details.feature_idx]
            template += ' {}'
            for child in node.children:
                edge_value = _extract_edge_value(decision_tree, child[1])
                ret += template.format(edge_value)
                ret += build_string(child[0], indent + 1, depth + 1)
        else:
            value = decision_tree.y_encoder.single_inv_transform(node.value)
            if isinstance(value, np.bytes_):
                value = value.decode('UTF-8')
            ret += ': {} {} \n'.format(value, _extract_class_count(node))
        return ret
    return build_string(decision_tree.root, 0, 0) 

Example 26

def _getconv(dtype):
    """ Find the correct dtype converter. Adapted from matplotlib """

    def floatconv(x):
        x.lower()
        if b'0x' in x:
            return float.fromhex(asstr(x))
        return float(x)

    typ = dtype.type
    if issubclass(typ, np.bool_):
        return lambda x: bool(int(x))
    if issubclass(typ, np.uint64):
        return np.uint64
    if issubclass(typ, np.int64):
        return np.int64
    if issubclass(typ, np.integer):
        return lambda x: int(float(x))
    elif issubclass(typ, np.longdouble):
        return np.longdouble
    elif issubclass(typ, np.floating):
        return floatconv
    elif issubclass(typ, np.complex):
        return lambda x: complex(asstr(x))
    elif issubclass(typ, np.bytes_):
        return bytes
    else:
        return str 

Example 27

def test_pickle_py2_scalar_latin1_hack(self):
        # Check that scalar unpickling hack in Py3 that supports
        # encoding='latin1' work correctly.

        # Python2 output for pickle.dumps(...)
        datas = [
            # (original, python2_pickle, koi8r_validity)
            (np.unicode_('\u6bd2'),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n"
                     "(S'U1'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI4\nI4\nI0\n"
                     "tp6\nbS'\\xd2k\\x00\\x00'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.float64(9e123),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'f8'\n"
                     "p2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI-1\nI-1\nI0\ntp6\n"
                     "bS'O\\x81\\xb7Z\\xaa:\\xabY'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.bytes_(asbytes('\x9c')),  # different 8-bit code point in KOI8-R vs latin1
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'S1'\np2\n"
                     "I0\nI1\ntp3\nRp4\n(I3\nS'|'\np5\nNNNI1\nI1\nI0\ntp6\nbS'\\x9c'\np7\n"
                     "tp8\nRp9\n."),
             'different'),
        ]
        if sys.version_info[0] >= 3:
            for original, data, koi8r_validity in datas:
                result = pickle.loads(data, encoding='latin1')
                assert_equal(result, original)

                # Decoding under non-latin1 encoding (e.g.) KOI8-R can
                # produce bad results, but should not segfault.
                if koi8r_validity == 'different':
                    # Unicode code points happen to lie within latin1,
                    # but are different in koi8-r, resulting to silent
                    # bogus results
                    result = pickle.loads(data, encoding='koi8-r')
                    assert_(result != original)
                elif koi8r_validity == 'invalid':
                    # Unicode code points outside latin1, so results
                    # to an encoding exception
                    assert_raises(ValueError, pickle.loads, data, encoding='koi8-r')
                else:
                    raise ValueError(koi8r_validity) 

Example 28

def test_pickle_py2_scalar_latin1_hack(self):
        # Check that scalar unpickling hack in Py3 that supports
        # encoding='latin1' work correctly.

        # Python2 output for pickle.dumps(...)
        datas = [
            # (original, python2_pickle, koi8r_validity)
            (np.unicode_('\u6bd2'),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n"
                     "(S'U1'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI4\nI4\nI0\n"
                     "tp6\nbS'\\xd2k\\x00\\x00'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.float64(9e123),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'f8'\n"
                     "p2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI-1\nI-1\nI0\ntp6\n"
                     "bS'O\\x81\\xb7Z\\xaa:\\xabY'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.bytes_(asbytes('\x9c')),  # different 8-bit code point in KOI8-R vs latin1
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'S1'\np2\n"
                     "I0\nI1\ntp3\nRp4\n(I3\nS'|'\np5\nNNNI1\nI1\nI0\ntp6\nbS'\\x9c'\np7\n"
                     "tp8\nRp9\n."),
             'different'),
        ]
        if sys.version_info[0] >= 3:
            for original, data, koi8r_validity in datas:
                result = pickle.loads(data, encoding='latin1')
                assert_equal(result, original)

                # Decoding under non-latin1 encoding (e.g.) KOI8-R can
                # produce bad results, but should not segfault.
                if koi8r_validity == 'different':
                    # Unicode code points happen to lie within latin1,
                    # but are different in koi8-r, resulting to silent
                    # bogus results
                    result = pickle.loads(data, encoding='koi8-r')
                    assert_(result != original)
                elif koi8r_validity == 'invalid':
                    # Unicode code points outside latin1, so results
                    # to an encoding exception
                    assert_raises(ValueError, pickle.loads, data, encoding='koi8-r')
                else:
                    raise ValueError(koi8r_validity) 

Example 29

def datasetselected(self):
        """ Action : One or more DataSets were selected from the list """

        #print('Selection changed')
        self.currentdset = self.ui.dataGroupSelect.currentText() + '/' + \
            self.ui.dataSetList.currentItem().text()

#        print('Current Selection : {}'.format(self.currentdset))
        self.allselect = ['/' + str(self.ui.dataGroupSelect.currentText() +\
            '/' + i.text()) for i in self.ui.dataSetList.selectedItems()]


        if len(self.allselect) == 0:
            self.allselect = None
            self.ui.currentDatasetText.setText('')
            attrs = {}
            self.ui.dataSetAttribs.setRowCount(0)
            self.ui.dataSetMemo.setText('')
        else:
            if len(self.allselect) == 1:
                self.ui.currentDatasetText.setText(self.currentdset)
            else:
                self.ui.currentDatasetText.setText(self.currentdset + ' ( + ' +\
                    str(len(self.allselect)-1) + ' others)' )

            self.ui.dataSetAttribs.setSortingEnabled(False)
            self.ui.dataSetAttribs.setRowCount(0)
            self.ui.dataSetAttribs.setColumnCount(2)

            attrs = _h5utils.retrieve_dataset_attribute_dict(self.path + self.filename,self.currentdset)

            for count, key in enumerate(attrs.keys()):
                self.ui.dataSetAttribs.insertRow(self.ui.dataSetAttribs.rowCount())
                self.ui.dataSetAttribs.setItem(count,0,_QTableWidgetItem(str(key)))
                temp = attrs[key]
                if isinstance(temp,_np.bytes_):
                    self.ui.dataSetAttribs.setItem(count,1,_QTableWidgetItem(temp.decode()))
                else:
                    self.ui.dataSetAttribs.setItem(count,1,_QTableWidgetItem(str(temp)))

            self.ui.dataSetAttribs.setSortingEnabled(True)
            self.ui.dataSetAttribs.sortItems(0)

            try:
                self.ui.dataSetMemo.setText(attrs['Memo'].decode())
            except:
                pass 

Example 30

def test_pickle_py2_scalar_latin1_hack(self):
        # Check that scalar unpickling hack in Py3 that supports
        # encoding='latin1' work correctly.

        # Python2 output for pickle.dumps(...)
        datas = [
            # (original, python2_pickle, koi8r_validity)
            (np.unicode_('\u6bd2'),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n"
                     "(S'U1'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI4\nI4\nI0\n"
                     "tp6\nbS'\\xd2k\\x00\\x00'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.float64(9e123),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'f8'\n"
                     "p2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI-1\nI-1\nI0\ntp6\n"
                     "bS'O\\x81\\xb7Z\\xaa:\\xabY'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.bytes_(asbytes('\x9c')),  # different 8-bit code point in KOI8-R vs latin1
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'S1'\np2\n"
                     "I0\nI1\ntp3\nRp4\n(I3\nS'|'\np5\nNNNI1\nI1\nI0\ntp6\nbS'\\x9c'\np7\n"
                     "tp8\nRp9\n."),
             'different'),
        ]
        if sys.version_info[0] >= 3:
            for original, data, koi8r_validity in datas:
                result = pickle.loads(data, encoding='latin1')
                assert_equal(result, original)

                # Decoding under non-latin1 encoding (e.g.) KOI8-R can
                # produce bad results, but should not segfault.
                if koi8r_validity == 'different':
                    # Unicode code points happen to lie within latin1,
                    # but are different in koi8-r, resulting to silent
                    # bogus results
                    result = pickle.loads(data, encoding='koi8-r')
                    assert_(result != original)
                elif koi8r_validity == 'invalid':
                    # Unicode code points outside latin1, so results
                    # to an encoding exception
                    assert_raises(ValueError, pickle.loads, data, encoding='koi8-r')
                else:
                    raise ValueError(koi8r_validity) 

Example 31

def test_pickle_py2_scalar_latin1_hack(self):
        # Check that scalar unpickling hack in Py3 that supports
        # encoding='latin1' work correctly.

        # Python2 output for pickle.dumps(...)
        datas = [
            # (original, python2_pickle, koi8r_validity)
            (np.unicode_('\u6bd2'),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n"
                     "(S'U1'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI4\nI4\nI0\n"
                     "tp6\nbS'\\xd2k\\x00\\x00'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.float64(9e123),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'f8'\n"
                     "p2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI-1\nI-1\nI0\ntp6\n"
                     "bS'O\\x81\\xb7Z\\xaa:\\xabY'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.bytes_(asbytes('\x9c')),  # different 8-bit code point in KOI8-R vs latin1
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'S1'\np2\n"
                     "I0\nI1\ntp3\nRp4\n(I3\nS'|'\np5\nNNNI1\nI1\nI0\ntp6\nbS'\\x9c'\np7\n"
                     "tp8\nRp9\n."),
             'different'),
        ]
        if sys.version_info[0] >= 3:
            for original, data, koi8r_validity in datas:
                result = pickle.loads(data, encoding='latin1')
                assert_equal(result, original)

                # Decoding under non-latin1 encoding (e.g.) KOI8-R can
                # produce bad results, but should not segfault.
                if koi8r_validity == 'different':
                    # Unicode code points happen to lie within latin1,
                    # but are different in koi8-r, resulting to silent
                    # bogus results
                    result = pickle.loads(data, encoding='koi8-r')
                    assert_(result != original)
                elif koi8r_validity == 'invalid':
                    # Unicode code points outside latin1, so results
                    # to an encoding exception
                    assert_raises(ValueError, pickle.loads, data, encoding='koi8-r')
                else:
                    raise ValueError(koi8r_validity) 

Example 32

def test_pickle_py2_scalar_latin1_hack(self):
        # Check that scalar unpickling hack in Py3 that supports
        # encoding='latin1' work correctly.

        # Python2 output for pickle.dumps(...)
        datas = [
            # (original, python2_pickle, koi8r_validity)
            (np.unicode_('\u6bd2'),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n"
                     "(S'U1'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI4\nI4\nI0\n"
                     "tp6\nbS'\\xd2k\\x00\\x00'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.float64(9e123),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'f8'\n"
                     "p2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI-1\nI-1\nI0\ntp6\n"
                     "bS'O\\x81\\xb7Z\\xaa:\\xabY'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.bytes_(asbytes('\x9c')),  # different 8-bit code point in KOI8-R vs latin1
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'S1'\np2\n"
                     "I0\nI1\ntp3\nRp4\n(I3\nS'|'\np5\nNNNI1\nI1\nI0\ntp6\nbS'\\x9c'\np7\n"
                     "tp8\nRp9\n."),
             'different'),
        ]
        if sys.version_info[0] >= 3:
            for original, data, koi8r_validity in datas:
                result = pickle.loads(data, encoding='latin1')
                assert_equal(result, original)

                # Decoding under non-latin1 encoding (e.g.) KOI8-R can
                # produce bad results, but should not segfault.
                if koi8r_validity == 'different':
                    # Unicode code points happen to lie within latin1,
                    # but are different in koi8-r, resulting to silent
                    # bogus results
                    result = pickle.loads(data, encoding='koi8-r')
                    assert_(result != original)
                elif koi8r_validity == 'invalid':
                    # Unicode code points outside latin1, so results
                    # to an encoding exception
                    assert_raises(ValueError, pickle.loads, data, encoding='koi8-r')
                else:
                    raise ValueError(koi8r_validity) 

Example 33

def test_pickle_py2_scalar_latin1_hack(self):
        # Check that scalar unpickling hack in Py3 that supports
        # encoding='latin1' work correctly.

        # Python2 output for pickle.dumps(...)
        datas = [
            # (original, python2_pickle, koi8r_validity)
            (np.unicode_('\u6bd2'),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n"
                     "(S'U1'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI4\nI4\nI0\n"
                     "tp6\nbS'\\xd2k\\x00\\x00'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.float64(9e123),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'f8'\n"
                     "p2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI-1\nI-1\nI0\ntp6\n"
                     "bS'O\\x81\\xb7Z\\xaa:\\xabY'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.bytes_(asbytes('\x9c')),  # different 8-bit code point in KOI8-R vs latin1
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'S1'\np2\n"
                     "I0\nI1\ntp3\nRp4\n(I3\nS'|'\np5\nNNNI1\nI1\nI0\ntp6\nbS'\\x9c'\np7\n"
                     "tp8\nRp9\n."),
             'different'),
        ]
        if sys.version_info[0] >= 3:
            for original, data, koi8r_validity in datas:
                result = pickle.loads(data, encoding='latin1')
                assert_equal(result, original)

                # Decoding under non-latin1 encoding (e.g.) KOI8-R can
                # produce bad results, but should not segfault.
                if koi8r_validity == 'different':
                    # Unicode code points happen to lie within latin1,
                    # but are different in koi8-r, resulting to silent
                    # bogus results
                    result = pickle.loads(data, encoding='koi8-r')
                    assert_(result != original)
                elif koi8r_validity == 'invalid':
                    # Unicode code points outside latin1, so results
                    # to an encoding exception
                    assert_raises(ValueError, pickle.loads, data, encoding='koi8-r')
                else:
                    raise ValueError(koi8r_validity) 

Example 34

def test_pickle_py2_scalar_latin1_hack(self):
        # Check that scalar unpickling hack in Py3 that supports
        # encoding='latin1' work correctly.

        # Python2 output for pickle.dumps(...)
        datas = [
            # (original, python2_pickle, koi8r_validity)
            (np.unicode_('\u6bd2'),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n"
                     "(S'U1'\np2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI4\nI4\nI0\n"
                     "tp6\nbS'\\xd2k\\x00\\x00'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.float64(9e123),
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'f8'\n"
                     "p2\nI0\nI1\ntp3\nRp4\n(I3\nS'<'\np5\nNNNI-1\nI-1\nI0\ntp6\n"
                     "bS'O\\x81\\xb7Z\\xaa:\\xabY'\np7\ntp8\nRp9\n."),
             'invalid'),

            (np.bytes_(asbytes('\x9c')),  # different 8-bit code point in KOI8-R vs latin1
             asbytes("cnumpy.core.multiarray\nscalar\np0\n(cnumpy\ndtype\np1\n(S'S1'\np2\n"
                     "I0\nI1\ntp3\nRp4\n(I3\nS'|'\np5\nNNNI1\nI1\nI0\ntp6\nbS'\\x9c'\np7\n"
                     "tp8\nRp9\n."),
             'different'),
        ]
        if sys.version_info[0] >= 3:
            for original, data, koi8r_validity in datas:
                result = pickle.loads(data, encoding='latin1')
                assert_equal(result, original)

                # Decoding under non-latin1 encoding (e.g.) KOI8-R can
                # produce bad results, but should not segfault.
                if koi8r_validity == 'different':
                    # Unicode code points happen to lie within latin1,
                    # but are different in koi8-r, resulting to silent
                    # bogus results
                    result = pickle.loads(data, encoding='koi8-r')
                    assert_(result != original)
                elif koi8r_validity == 'invalid':
                    # Unicode code points outside latin1, so results
                    # to an encoding exception
                    assert_raises(ValueError, pickle.loads, data, encoding='koi8-r')
                else:
                    raise ValueError(koi8r_validity) 
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