savu.data.data_structures.data.Data.__check_dims() - Code Metrics - Inspection of "scrutinizer config" - DiamondLightSource/Savu - Measure and Improve Code Quality continuously with Scrutinizer

Test Failed

Retried Inspection

Pull Request — master (#708)

by Daniil

created 2021-02-25 17:47 UTC

savu.data.data_structures.data.Data.__check_dims() A

↳ Parent: savu.data.data_structures.data

Complexity

Conditions

Size

Total Lines	12
Code Lines	8

Duplication

Lines	0
Ratio	0 %

Importance

Changes

Metric	Value
cc	3
eloc	8
nop	1
dl	0
loc	12
rs	10
c	0
b	0
f	0

# Copyright 2014 Diamond Light Source Ltd.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

"""
.. module:: data
   :platform: Unix
   :synopsis: The Data class dynamically inherits from transport specific data\
   class and holds the data array, along with associated information.

.. moduleauthor:: Nicola Wadeson <[email protected]>

"""

import savu.core.utils as cu
from savu.data.meta_data import MetaData
import savu.data.data_structures.utils as dsu
from savu.data.data_structures.preview import Preview
from savu.data.data_structures.data_create import DataCreate


class Data(DataCreate):
    """The Data class dynamically inherits from transport specific data class
    and holds the data array, along with associated information.
    """

    def __init__(self, name, exp):
        super(Data, self).__init__(name)
        self.meta_data = MetaData()
        self.related = {}
        self.pattern_list = self.__get_available_pattern_list()
        self.data_info = MetaData()
        self.__initialise_data_info(name)
        self._preview = Preview(self)
        self.exp = exp
        self.group_name = None
        self.group = None
        self._plugin_data_obj = None
        self.raw = None
        self.backing_file = None
        self.data = None
        self.next_shape = None
        self.orig_shape = None
        self.previous_pattern = None
        self.transport_data = None

#    def get_data(self, related):
#        return self.related[related].data

    def __initialise_data_info(self, name):
        """ Initialise entries in the data_info meta data.
        """
        self.data_info.set('name', name)
        self.data_info.set('data_patterns', {})
        self.data_info.set('shape', None)
        self.data_info.set('nDims', None)

    def _set_plugin_data(self, plugin_data_obj):
        """ Encapsulate a PluginData object.
        """
        self._plugin_data_obj = plugin_data_obj

    def _clear_plugin_data(self):
        """ Set encapsulated PluginData object to None.
        """
        self._plugin_data_obj = None

    def _get_plugin_data(self):
        """ Get encapsulated PluginData object.
        """
        if self._plugin_data_obj is not None:
            return self._plugin_data_obj
        else:
            raise Exception("There is no PluginData object associated with "
                            "the Data object.")

    def get_preview(self):
        """ Get the Preview instance associated with the data object
        """
        return self._preview

    def _set_transport_data(self, transport):
        """ Import the data transport mechanism

        :returns: instance of data transport
        :rtype: transport_data
        """
        transport_data = "savu.data.transport_data." + transport + \
                         "_transport_data"
        transport_data = cu.import_class(transport_data)
        self.transport_data = transport_data(self)
        self.data_info.set('transport', transport)

    def _get_transport_data(self):
        return self.transport_data

    def __deepcopy__(self, memo):
        """ Copy the data object.
        """
        name = self.data_info.get('name')
        return dsu._deepcopy_data_object(self, Data(name, self.exp))

    def get_data_patterns(self):
        """ Get data patterns associated with this data object.

        :returns: A dictionary of associated patterns.
        :rtype: dict
        """
        return self.data_info.get('data_patterns')

    def _set_previous_pattern(self, pattern):
        self.previous_pattern = pattern

    def get_previous_pattern(self):
        return self.previous_pattern

    def set_shape(self, shape):
        """ Set the dataset shape.
        """
        self.data_info.set('shape', shape)
        self.__check_dims()

    def set_original_shape(self, shape):
        """ Set the original data shape before previewing
        """
        self.orig_shape = shape
        self.set_shape(shape)

    def get_original_shape(self):
        """
        Returns the original shape of the data before previewing
        
        Returns
        -------
        tuple
            Original data shape.
        """
        return self.orig_shape

    def get_shape(self):
        """ Get the dataset shape

        :returns: data shape
        :rtype: tuple
        """
        shape = self.data_info.get('shape')
        return shape

    def __check_dims(self):
        """ Check the ``shape`` and ``nDims`` entries in the data_info
        meta_data dictionary are equal.
        """
        nDims = self.data_info.get("nDims")
        shape = self.data_info.get('shape')
        if nDims:
            if len(shape) != nDims:
                error_msg = ("The number of axis labels, %d, does not "
                             "coincide with the number of data "
                             "dimensions %d." % (nDims, len(shape)))
                raise Exception(error_msg)

    def _set_name(self, name):
        self.data_info.set('name', name)

    def get_name(self, orig=False):
        """ Get data name.

        :keyword bool orig: Set this flag to true to return the original cloned
            dataset name if this dataset is a clone
        :returns: the name associated with the dataset
        :rtype: str
        """
        if orig:
            dinfo = self.data_info.get_dictionary()
            return dinfo['clone'] if 'clone' in dinfo.keys() else dinfo['name']
        return self.data_info.get('name')

    def __get_available_pattern_list(self):
        """ Get a list of ALL pattern names that are currently allowed in the
        framework.
        """
        pattern_list = dsu.get_available_pattern_types()
        return pattern_list

    def add_pattern(self, dtype, **kwargs):
        """ Add a pattern.

        :params str dtype: The *type* of pattern to add, which can be anything
            from the :const:`savu.data.data_structures.utils.pattern_list`
            :const:`pattern_list`
            :data:`savu.data.data_structures.utils.pattern_list`
            :data:`pattern_list`:
        :keyword tuple core_dims: Dimension indices of core dimensions
        :keyword tuple slice_dims: Dimension indices of slice dimensions
        """
        if dtype in self.pattern_list:
            nDims = 0
            for args in kwargs:
                dlen = len(kwargs[args])
                if not dlen:
                    raise Exception("Pattern Error: Pattern %s must have at"
                                    " least one %s" % (dtype, args))
                nDims += len(kwargs[args])
                self.data_info.set(['data_patterns', dtype, args],
                                   kwargs[args])

            self.__convert_pattern_dimensions(dtype)
            if self.get_shape():
                diff = len(self.get_shape()) - nDims
                if diff:
                    pattern = {dtype: self.get_data_patterns()[dtype]}
                    self._set_data_patterns(pattern)
                    nDims += diff
            try:
                if nDims != self.data_info.get("nDims"):
                    actualDims = self.data_info.get('nDims')
                    err_msg = ("The pattern %s has an incorrect number of "
                               "dimensions: %d required but %d specified."
                               % (dtype, actualDims, nDims))
                    raise Exception(err_msg)
            except KeyError:
                self.data_info.set('nDims', nDims)
        else:
            raise Exception("The data pattern '%s'does not exist. Please "
                            "choose from the following list: \n'%s'",
                            dtype, str(self.pattern_list))

    def add_volume_patterns(self, x, y, z):
        """ Adds volume patterns

        :params int x: dimension to be associated with x-axis
        :params int y: dimension to be associated with y-axis
        :params int z: dimension to be associated with z-axis
        """
        self.add_pattern("VOLUME_XZ", **self.__get_dirs_for_volume(x, z, y))

        if y:
            self.add_pattern(
                "VOLUME_YZ", **self.__get_dirs_for_volume(y, z, x))
            self.add_pattern(
                "VOLUME_XY", **self.__get_dirs_for_volume(x, y, z))

        if self.data_info.get("nDims") > 3 and y:
            self.add_pattern("VOLUME_3D", **self.__get_dirs_for_volume_3D())

    def __get_dirs_for_volume(self, dim1, dim2, sdir, dim3=None):
        """ Calculate core_dir and slice_dir for a volume pattern.
        """
        all_dims = range(self.data_info.get("nDims"))
        vol_dict = {}
        vol_dict['core_dims'] = (dim1, dim2)
        slice_dir = [sdir] if type(sdir) is int else []
        for ddir in all_dims:
            if ddir not in [dim1, dim2, sdir]:
                slice_dir.append(ddir)                
        vol_dict['slice_dims'] = tuple(slice_dir)
        return vol_dict

    def __get_dirs_for_volume_3D(self):
        # create volume 3D pattern here
        patterns = self.get_data_patterns()
        cdim = []
        for v in ['VOLUME_YZ', 'VOLUME_XY', 'VOLUME_XZ']:
            cdim += (patterns[v]['core_dims'])
            
        cdim = set(cdim)
        sdim = tuple(set(range(self.data_info.get("nDims"))).difference(cdim))
        return {"core_dims": tuple(cdim), "slice_dims": sdim}

    def set_axis_labels(self, *args):
        """ Set the axis labels associated with each data dimension.

        :arg str: Each arg should be of the form ``name.unit``. If ``name`` is\
        a data_obj.meta_data entry, it will be output to the final .nxs file.
        """
        self.data_info.set('nDims', len(args))
        axis_labels = []
        for arg in args:
            if isinstance(arg, dict):
                axis_labels.append(arg)
            else:
                try:
                    axis = arg.split('.')
                    axis_labels.append({axis[0]: axis[1]})
                except:
                    # data arrives here, but that may be an error
                    pass
        self.data_info.set('axis_labels', axis_labels)

    def get_axis_labels(self):
        """ Get axis labels.

        :returns: Axis labels
        :rtype: list(dict)
        """
        return self.data_info.get('axis_labels')

    def get_data_dimension_by_axis_label(self, name, contains=False, exists=False):
        """ Get the dimension of the data associated with a particular
        axis_label.

        :param str name: The name of the axis_label
        :keyword bool contains: Set this flag to true if the name is only part
            of the axis_label name
        :keyword bool exists: Set to True to return False rather than Exception
        :returns: The associated axis number
        :rtype: int
        """
        axis_labels = self.data_info.get('axis_labels')
        for i in range(len(axis_labels)):
            if contains is True:
                for names in list(axis_labels[i].keys()):
                    if name in names:
                        return i
            else:
                if name in list(axis_labels[i].keys()):
                    return i
        if exists:
            return False
        raise Exception("Cannot find the specifed axis label.")

    def _finalise_patterns(self):
        """ Adds a main axis (fastest changing) to SINOGRAM and PROJECTON
        patterns.
        """
        check = 0        
        check += self.__check_pattern('SINOGRAM')
        check += self.__check_pattern('PROJECTION')

        if check == 2 and len(self.get_shape()) > 2:
            self.__set_main_axis('SINOGRAM')
            self.__set_main_axis('PROJECTION')

    def __check_pattern(self, pattern_name):
        """ Check if a pattern exists.
        """
        patterns = self.get_data_patterns()
        try:
            patterns[pattern_name]
        except KeyError:
            return 0
        return 1

    def __convert_pattern_dimensions(self, dtype):
        """ Replace negative indices in pattern kwargs.
        """
        pattern = self.get_data_patterns()[dtype]
        if 'main_dir' in list(pattern.keys()):
            del pattern['main_dir']

        nDims = sum([len(i) for i in list(pattern.values())])
        for p in pattern:
            ddirs = pattern[p]
            pattern[p] = self._non_negative_directions(ddirs, nDims)

    def _non_negative_directions(self, ddirs, nDims):
        """ Replace negative indexing values with positive counterparts.

        :params tuple(int) ddirs: data dimension indices
        :params int nDims: The number of data dimensions
        :returns: non-negative data dimension indices
        :rtype: tuple(int)
        """
        index = [i for i in range(len(ddirs)) if ddirs[i] < 0]
        list_ddirs = list(ddirs)
        for i in index:
            list_ddirs[i] = nDims + ddirs[i]
        return tuple(list_ddirs)

    def __set_main_axis(self, pname):
        """ Set the ``main_dir`` pattern kwarg to the fastest changing
        dimension
        """
        patterns = self.get_data_patterns()
        n1 = 'PROJECTION' if pname == 'SINOGRAM' else 'SINOGRAM'
        d1 = patterns[n1]['core_dims']
        d2 = patterns[pname]['slice_dims']
        tdir = set(d1).intersection(set(d2))

        # this is required when a single sinogram exists in the mm case, and a
        # dimension is added via parameter tuning.
        if not tdir:
            tdir = [d2[0]]

        self.data_info.set(['data_patterns', pname, 'main_dir'], list(tdir)[0])

    def get_axis_label_keys(self):
        """ Get axis_label names

        :returns: A list containing associated axis names for each dimension
        :rtype: list(str)
        """
        axis_labels = self.data_info.get('axis_labels')
        axis_label_keys = []
        for labels in axis_labels:
            for key in list(labels.keys()):
                axis_label_keys.append(key)
        return axis_label_keys

    def amend_axis_label_values(self, slice_list):
        """ Amend all axis label values based on the slice_list parameter.\
        This is required if the data is reduced.
        """
        axis_labels = self.get_axis_labels()
        for i in range(len(slice_list)):
            label = list(axis_labels[i].keys())[0]
            if label in list(self.meta_data.get_dictionary().keys()):
                values = self.meta_data.get(label)
                preview_sl = [slice(None)]*len(values.shape)
                preview_sl[0] = slice_list[i]
                self.meta_data.set(label, values[tuple(preview_sl)])

    def get_core_dimensions(self):
        """ Get the core data dimensions associated with the current pattern.

        :returns: value associated with pattern key ``core_dims``
        :rtype: tuple
        """
        return list(self._get_plugin_data().get_pattern().values())[0]['core_dims']

    def get_slice_dimensions(self):
        """ Get the slice data dimensions associated with the current pattern.

        :returns: value associated with pattern key ``slice_dims``
        :rtype: tuple
        """
        return list(self._get_plugin_data().get_pattern().values())[0]['slice_dims']

    def get_itemsize(self):
        """ Returns bytes per entry """
        dtype = self.get_dtype()
        if not dtype:
            self.set_dtype(None)
            dtype = self.get_dtype()
        return self.get_dtype().itemsize


1			# Copyright 2014 Diamond Light Source Ltd.
2			#
3			# Licensed under the Apache License, Version 2.0 (the "License");
4			# you may not use this file except in compliance with the License.
5			# You may obtain a copy of the License at
6			#
7			# http://www.apache.org/licenses/LICENSE-2.0
8			#
9			# Unless required by applicable law or agreed to in writing, software
10			# distributed under the License is distributed on an "AS IS" BASIS,
11			# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
12			# See the License for the specific language governing permissions and
13			# limitations under the License.
14
15			"""
16			.. module:: data
17			:platform: Unix
18			:synopsis: The Data class dynamically inherits from transport specific data\
19			class and holds the data array, along with associated information.
20
21			.. moduleauthor:: Nicola Wadeson <[email protected]>
22
23			"""
24
25			import savu.core.utils as cu
26			from savu.data.meta_data import MetaData
27			import savu.data.data_structures.utils as dsu
28			from savu.data.data_structures.preview import Preview
29			from savu.data.data_structures.data_create import DataCreate
30
31
32			class Data(DataCreate):
33			"""The Data class dynamically inherits from transport specific data class
34			and holds the data array, along with associated information.
35			"""
36
37			def __init__(self, name, exp):
38			super(Data, self).__init__(name)
39			self.meta_data = MetaData()
40			self.related = {}
41			self.pattern_list = self.__get_available_pattern_list()
42			self.data_info = MetaData()
43			self.__initialise_data_info(name)
44			self._preview = Preview(self)
45			self.exp = exp
46			self.group_name = None
47			self.group = None
48			self._plugin_data_obj = None
49			self.raw = None
50			self.backing_file = None
51			self.data = None
52			self.next_shape = None
53			self.orig_shape = None
54			self.previous_pattern = None
55			self.transport_data = None
56
57			# def get_data(self, related):
58			# return self.related[related].data
59
60			def __initialise_data_info(self, name):
61			""" Initialise entries in the data_info meta data.
62			"""
63			self.data_info.set('name', name)
64			self.data_info.set('data_patterns', {})
65			self.data_info.set('shape', None)
66			self.data_info.set('nDims', None)
67
68			def _set_plugin_data(self, plugin_data_obj):
69			""" Encapsulate a PluginData object.
70			"""
71			self._plugin_data_obj = plugin_data_obj
72
73			def _clear_plugin_data(self):
74			""" Set encapsulated PluginData object to None.
75			"""
76			self._plugin_data_obj = None
77
78			def _get_plugin_data(self):
79			""" Get encapsulated PluginData object.
80			"""
81			if self._plugin_data_obj is not None:
82			return self._plugin_data_obj
83			else:
84			raise Exception("There is no PluginData object associated with "
85			"the Data object.")
86
87			def get_preview(self):
88			""" Get the Preview instance associated with the data object
89			"""
90			return self._preview
91
92			def _set_transport_data(self, transport):
93			""" Import the data transport mechanism
94
95			:returns: instance of data transport
96			:rtype: transport_data
97			"""
98			transport_data = "savu.data.transport_data." + transport + \
99			"_transport_data"
100			transport_data = cu.import_class(transport_data)
101			self.transport_data = transport_data(self)
102			self.data_info.set('transport', transport)
103
104			def _get_transport_data(self):
105			return self.transport_data
106
107			def __deepcopy__(self, memo):
108			""" Copy the data object.
109			"""
110			name = self.data_info.get('name')
111			return dsu._deepcopy_data_object(self, Data(name, self.exp))
112
113			def get_data_patterns(self):
114			""" Get data patterns associated with this data object.
115
116			:returns: A dictionary of associated patterns.
117			:rtype: dict
118			"""
119			return self.data_info.get('data_patterns')
120
121			def _set_previous_pattern(self, pattern):
122			self.previous_pattern = pattern
123
124			def get_previous_pattern(self):
125			return self.previous_pattern
126
127			def set_shape(self, shape):
128			""" Set the dataset shape.
129			"""
130			self.data_info.set('shape', shape)
131			self.__check_dims()
132
133			def set_original_shape(self, shape):
134			""" Set the original data shape before previewing
135			"""
136			self.orig_shape = shape
137			self.set_shape(shape)
138
139			def get_original_shape(self):
140			"""
141			Returns the original shape of the data before previewing
142
143			Returns
144			-------
145			tuple
146			Original data shape.
147			"""
148			return self.orig_shape
149
150			def get_shape(self):
151			""" Get the dataset shape
152
153			:returns: data shape
154			:rtype: tuple
155			"""
156			shape = self.data_info.get('shape')
157			return shape
158
159			def __check_dims(self):
160			""" Check the ``shape`` and ``nDims`` entries in the data_info
161			meta_data dictionary are equal.
162			"""
163			nDims = self.data_info.get("nDims")
164			shape = self.data_info.get('shape')
165			if nDims:
166			if len(shape) != nDims:
167			error_msg = ("The number of axis labels, %d, does not "
168			"coincide with the number of data "
169			"dimensions %d." % (nDims, len(shape)))
170			raise Exception(error_msg)
171
172			def _set_name(self, name):
173			self.data_info.set('name', name)
174
175			def get_name(self, orig=False):
176			""" Get data name.
177
178			:keyword bool orig: Set this flag to true to return the original cloned
179			dataset name if this dataset is a clone
180			:returns: the name associated with the dataset
181			:rtype: str
182			"""
183			if orig:
184			dinfo = self.data_info.get_dictionary()
185			return dinfo['clone'] if 'clone' in dinfo.keys() else dinfo['name']
186			return self.data_info.get('name')
187
188			def __get_available_pattern_list(self):
189			""" Get a list of ALL pattern names that are currently allowed in the
190			framework.
191			"""
192			pattern_list = dsu.get_available_pattern_types()
193			return pattern_list
194
195			def add_pattern(self, dtype, **kwargs):
196			""" Add a pattern.
197
198			:params str dtype: The type of pattern to add, which can be anything
199			from the :const:`savu.data.data_structures.utils.pattern_list`
200			:const:`pattern_list`
201			:data:`savu.data.data_structures.utils.pattern_list`
202			:data:`pattern_list`:
203			:keyword tuple core_dims: Dimension indices of core dimensions
204			:keyword tuple slice_dims: Dimension indices of slice dimensions
205			"""
206			if dtype in self.pattern_list:
207			nDims = 0
208			for args in kwargs:
209			dlen = len(kwargs[args])
210			if not dlen:
211			raise Exception("Pattern Error: Pattern %s must have at"
212			" least one %s" % (dtype, args))
213			nDims += len(kwargs[args])
214			self.data_info.set(['data_patterns', dtype, args],
215			kwargs[args])
216
217			self.__convert_pattern_dimensions(dtype)
218			if self.get_shape():
219			diff = len(self.get_shape()) - nDims
220			if diff:
221			pattern = {dtype: self.get_data_patterns()[dtype]}
222			self._set_data_patterns(pattern)
223			nDims += diff
224			try:
225			if nDims != self.data_info.get("nDims"):
226			actualDims = self.data_info.get('nDims')
227			err_msg = ("The pattern %s has an incorrect number of "
228			"dimensions: %d required but %d specified."
229			% (dtype, actualDims, nDims))
230			raise Exception(err_msg)
231			except KeyError:
232			self.data_info.set('nDims', nDims)
233			else:
234			raise Exception("The data pattern '%s'does not exist. Please "
235			"choose from the following list: \n'%s'",
236			dtype, str(self.pattern_list))
237
238			def add_volume_patterns(self, x, y, z):
239			""" Adds volume patterns
240
241			:params int x: dimension to be associated with x-axis
242			:params int y: dimension to be associated with y-axis
243			:params int z: dimension to be associated with z-axis
244			"""
245			self.add_pattern("VOLUME_XZ", **self.__get_dirs_for_volume(x, z, y))
246
247			if y:
248			self.add_pattern(
249			"VOLUME_YZ", **self.__get_dirs_for_volume(y, z, x))
250			self.add_pattern(
251			"VOLUME_XY", **self.__get_dirs_for_volume(x, y, z))
252
253			if self.data_info.get("nDims") > 3 and y:
254			self.add_pattern("VOLUME_3D", **self.__get_dirs_for_volume_3D())
255
256			def __get_dirs_for_volume(self, dim1, dim2, sdir, dim3=None):
257			""" Calculate core_dir and slice_dir for a volume pattern.
258			"""
259			all_dims = range(self.data_info.get("nDims"))
260			vol_dict = {}
261			vol_dict['core_dims'] = (dim1, dim2)
262			slice_dir = [sdir] if type(sdir) is int else []
263			for ddir in all_dims:
264			if ddir not in [dim1, dim2, sdir]:
265			slice_dir.append(ddir)
266			vol_dict['slice_dims'] = tuple(slice_dir)
267			return vol_dict
268
269			def __get_dirs_for_volume_3D(self):
270			# create volume 3D pattern here
271			patterns = self.get_data_patterns()
272			cdim = []
273			for v in ['VOLUME_YZ', 'VOLUME_XY', 'VOLUME_XZ']:
274			cdim += (patterns[v]['core_dims'])
275
276			cdim = set(cdim)
277			sdim = tuple(set(range(self.data_info.get("nDims"))).difference(cdim))
278			return {"core_dims": tuple(cdim), "slice_dims": sdim}
279
280			def set_axis_labels(self, *args):
281			""" Set the axis labels associated with each data dimension.
282
283			:arg str: Each arg should be of the form ``name.unit``. If ``name`` is\
284			a data_obj.meta_data entry, it will be output to the final .nxs file.
285			"""
286			self.data_info.set('nDims', len(args))
287			axis_labels = []
288			for arg in args:
289			if isinstance(arg, dict):
290			axis_labels.append(arg)
291			else:
292			try:
293			axis = arg.split('.')
294			axis_labels.append({axis[0]: axis[1]})
295			except:
296			# data arrives here, but that may be an error
297			pass
298			self.data_info.set('axis_labels', axis_labels)
299
300			def get_axis_labels(self):
301			""" Get axis labels.
302
303			:returns: Axis labels
304			:rtype: list(dict)
305			"""
306			return self.data_info.get('axis_labels')
307
308			def get_data_dimension_by_axis_label(self, name, contains=False, exists=False):
309			""" Get the dimension of the data associated with a particular
310			axis_label.
311
312			:param str name: The name of the axis_label
313			:keyword bool contains: Set this flag to true if the name is only part
314			of the axis_label name
315			:keyword bool exists: Set to True to return False rather than Exception
316			:returns: The associated axis number
317			:rtype: int
318			"""
319			axis_labels = self.data_info.get('axis_labels')
320			for i in range(len(axis_labels)):
321			if contains is True:
322			for names in list(axis_labels[i].keys()):
323			if name in names:
324			return i
325			else:
326			if name in list(axis_labels[i].keys()):
327			return i
328			if exists:
329			return False
330			raise Exception("Cannot find the specifed axis label.")
331
332			def _finalise_patterns(self):
333			""" Adds a main axis (fastest changing) to SINOGRAM and PROJECTON
334			patterns.
335			"""
336			check = 0
337			check += self.__check_pattern('SINOGRAM')
338			check += self.__check_pattern('PROJECTION')
339
340			if check == 2 and len(self.get_shape()) > 2:
341			self.__set_main_axis('SINOGRAM')
342			self.__set_main_axis('PROJECTION')
343
344			def __check_pattern(self, pattern_name):
345			""" Check if a pattern exists.
346			"""
347			patterns = self.get_data_patterns()
348			try:
349			patterns[pattern_name]
350			except KeyError:
351			return 0
352			return 1
353
354			def __convert_pattern_dimensions(self, dtype):
355			""" Replace negative indices in pattern kwargs.
356			"""
357			pattern = self.get_data_patterns()[dtype]
358			if 'main_dir' in list(pattern.keys()):
359			del pattern['main_dir']
360
361			nDims = sum([len(i) for i in list(pattern.values())])
362			for p in pattern:
363			ddirs = pattern[p]
364			pattern[p] = self._non_negative_directions(ddirs, nDims)
365
366			def _non_negative_directions(self, ddirs, nDims):
367			""" Replace negative indexing values with positive counterparts.
368
369			:params tuple(int) ddirs: data dimension indices
370			:params int nDims: The number of data dimensions
371			:returns: non-negative data dimension indices
372			:rtype: tuple(int)
373			"""
374			index = [i for i in range(len(ddirs)) if ddirs[i] < 0]
375			list_ddirs = list(ddirs)
376			for i in index:
377			list_ddirs[i] = nDims + ddirs[i]
378			return tuple(list_ddirs)
379
380			def __set_main_axis(self, pname):
381			""" Set the ``main_dir`` pattern kwarg to the fastest changing
382			dimension
383			"""
384			patterns = self.get_data_patterns()
385			n1 = 'PROJECTION' if pname == 'SINOGRAM' else 'SINOGRAM'
386			d1 = patterns[n1]['core_dims']
387			d2 = patterns[pname]['slice_dims']
388			tdir = set(d1).intersection(set(d2))
389
390			# this is required when a single sinogram exists in the mm case, and a
391			# dimension is added via parameter tuning.
392			if not tdir:
393			tdir = [d2[0]]
394
395			self.data_info.set(['data_patterns', pname, 'main_dir'], list(tdir)[0])
396
397			def get_axis_label_keys(self):
398			""" Get axis_label names
399
400			:returns: A list containing associated axis names for each dimension
401			:rtype: list(str)
402			"""
403			axis_labels = self.data_info.get('axis_labels')
404			axis_label_keys = []
405			for labels in axis_labels:
406			for key in list(labels.keys()):
407			axis_label_keys.append(key)
408			return axis_label_keys
409
410			def amend_axis_label_values(self, slice_list):
411			""" Amend all axis label values based on the slice_list parameter.\
412			This is required if the data is reduced.
413			"""
414			axis_labels = self.get_axis_labels()
415			for i in range(len(slice_list)):
416			label = list(axis_labels[i].keys())[0]
417			if label in list(self.meta_data.get_dictionary().keys()):
418			values = self.meta_data.get(label)
419			preview_sl = [slice(None)]*len(values.shape)
420			preview_sl[0] = slice_list[i]
421			self.meta_data.set(label, values[tuple(preview_sl)])
422
423			def get_core_dimensions(self):
424			""" Get the core data dimensions associated with the current pattern.
425
426			:returns: value associated with pattern key ``core_dims``
427			:rtype: tuple
428			"""
429			return list(self._get_plugin_data().get_pattern().values())[0]['core_dims']
430
431			def get_slice_dimensions(self):
432			""" Get the slice data dimensions associated with the current pattern.
433
434			:returns: value associated with pattern key ``slice_dims``
435			:rtype: tuple
436			"""
437			return list(self._get_plugin_data().get_pattern().values())[0]['slice_dims']
438
439			def get_itemsize(self):
440			""" Returns bytes per entry """
441			dtype = self.get_dtype()
442			if not dtype:
443			self.set_dtype(None)
444			dtype = self.get_dtype()
445			return self.get_dtype().itemsize
446

DiamondLightSource / Savu

Pull Request — master (#708)

savu.data.data_structures.data.Data.__check_dims() A

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