Removed redundend shape check functions. Fix #204

src/hdmf/backends/hdf5/h5tools.py

@@ -7,8 +7,8 @@
 import warnings
 from ...container import Container
 
-from ...utils import docval, getargs, popargs, call_docval_func
-from ...data_utils import AbstractDataChunkIterator, get_shape
+from ...utils import docval, getargs, popargs, call_docval_func, get_data_shape
+from ...data_utils import AbstractDataChunkIterator
 from ...build import Builder, GroupBuilder, DatasetBuilder, LinkBuilder, BuildManager,\
                      RegionBuilder, ReferenceBuilder, TypeMap, ObjectMapper
 from ...spec import RefSpec, DtypeSpec, NamespaceCatalog, GroupSpec
@@ -1028,7 +1028,7 @@ def __list_fill__(cls, parent, name, data, options=None):
         elif isinstance(dtype, np.dtype):
             data_shape = (len(data),)
         else:
-            data_shape = get_shape(data)
+            data_shape = get_data_shape(data)
         # Create the dataset
         try:
             dset = parent.create_dataset(name, shape=data_shape, dtype=dtype, **io_settings)

src/hdmf/container.py

@@ -2,8 +2,8 @@
 from abc import abstractmethod
 from uuid import uuid4
 from six import with_metaclass
-from .utils import docval, get_docval, call_docval_func, getargs, ExtenderMeta
-from .data_utils import DataIO, get_shape
+from .utils import docval, get_docval, call_docval_func, getargs, ExtenderMeta, get_data_shape
+from .data_utils import DataIO
 from warnings import warn
 import h5py
 
@@ -397,7 +397,7 @@ def shape(self):
         :return: Shape tuple
         :rtype: tuple of ints
         """
-        return get_shape(self.__data)
+        return get_data_shape(self.__data)
 
     @docval({'name': 'dataio', 'type': DataIO, 'doc': 'the DataIO to apply to the data held by this Data'})
     def set_dataio(self, **kwargs):

src/hdmf/data_utils.py

@@ -3,39 +3,12 @@
 
 import numpy as np
 from warnings import warn
-from six import with_metaclass, text_type, binary_type
+from six import with_metaclass
 import copy
 
 from .utils import docval, getargs, popargs, docval_macro, get_data_shape
 
 
-def __get_shape_helper(data):
-    """Helper function used by get_shape"""
-    shape = list()
-    if hasattr(data, '__len__'):
-        shape.append(len(data))
-        if len(data) and not isinstance(data[0], (text_type, binary_type)):
-            shape.extend(__get_shape_helper(data[0]))
-    return tuple(shape)
-
-
-def get_shape(data):
-    """
-    Determine the data shape for the given data
-    :param data: Array for which the data should be determined
-    :type data: list, ndarray, dict
-    :return: None in case shape is unknown and shape tuple otherwise
-    """
-    if isinstance(data, dict):
-        return None
-    elif hasattr(data, 'shape'):
-        return data.shape
-    elif hasattr(data, '__len__') and not isinstance(data, (text_type, binary_type)):
-        return __get_shape_helper(data)
-    else:
-        return None
-
-
 @docval_macro('array_data')
 class AbstractDataChunkIterator(with_metaclass(ABCMeta, object)):
     """

src/hdmf/utils.py

@@ -648,9 +648,11 @@ def __get_shape_helper(local_data):
         return tuple(shape)
     if hasattr(data, 'maxshape'):
         return data.maxshape
-    if hasattr(data, 'shape'):
+    elif hasattr(data, 'shape'):
         return data.shape
-    if hasattr(data, '__len__') and not isinstance(data, (text_type, binary_type)):
+    elif isinstance(data, dict):
+        return None
+    elif hasattr(data, '__len__') and not isinstance(data, (text_type, binary_type)):
         if not strict_no_data_load or (isinstance(data, list) or isinstance(data, tuple) or isinstance(data, set)):
             return __get_shape_helper(data)
         else:

src/hdmf/validate/validator.py

@@ -4,8 +4,7 @@
 import re
 from itertools import chain
 
-from ..utils import docval, getargs, call_docval_func, pystr
-from ..data_utils import get_shape
+from ..utils import docval, getargs, call_docval_func, pystr, get_data_shape
 
 from ..spec import Spec, AttributeSpec, GroupSpec, DatasetSpec, RefSpec
 from ..spec.spec import BaseStorageSpec, DtypeHelper
@@ -318,7 +317,7 @@ def validate(self, **kwargs):
                 dtype = get_type(value)
                 if not check_type(spec.dtype, dtype):
                     ret.append(DtypeError(self.get_spec_loc(spec), spec.dtype, dtype))
-            shape = get_shape(value)
+            shape = get_data_shape(value)
             if not check_shape(spec.shape, shape):
                 ret.append(ShapeError(self.get_spec_loc(spec), spec.shape, shape))
         return ret
@@ -374,7 +373,7 @@ def validate(self, **kwargs):
             if not check_type(self.spec.dtype, dtype):
                 ret.append(DtypeError(self.get_spec_loc(self.spec), self.spec.dtype, dtype,
                                       location=self.get_builder_loc(builder)))
-        shape = get_shape(data)
+        shape = get_data_shape(data)
         if not check_shape(self.spec.shape, shape):
             if shape is None:
                 ret.append(ExpectedArrayError(self.get_spec_loc(self.spec), self.spec.shape, str(data),

tests/unit/test_io_hdf5.py

@@ -5,7 +5,7 @@
 
 from hdmf.backends.hdf5 import HDF5IO
 from hdmf.build import GroupBuilder, DatasetBuilder, LinkBuilder
-from hdmf.data_utils import get_shape
+from hdmf.utils import get_data_shape
 
 from numbers import Number
 
@@ -239,5 +239,5 @@ def test_dataset_shape(self):
         io.write_builder(self.builder)
         builder = io.read_builder()
         dset = builder['test_bucket']['foo_holder']['foo1']['my_data'].data
-        self.assertEqual(get_shape(dset), (10,))
+        self.assertEqual(get_data_shape(dset), (10,))
         io.close()