Merge pull request #620 from ANTsX/remove-labelimage

Add tests; Remove labelimage + invariant image similarity

ants/core/__init__.py

@@ -19,7 +19,6 @@
 
 from .ants_image import (
     ANTsImage,
-    LabelImage,
     copy_image_info,
     set_origin,
     get_origin,

ants/core/ants_image.py

@@ -1,7 +1,6 @@
 
 
 __all__ = ['ANTsImage',
-           'LabelImage',
            'copy_image_info',
            'set_origin',
            'get_origin',
@@ -45,7 +44,7 @@
 
 class ANTsImage(object):
 
-    def __init__(self, pixeltype='float', dimension=3, components=1, pointer=None, is_rgb=False, label_image=None):
+    def __init__(self, pixeltype='float', dimension=3, components=1, pointer=None, is_rgb=False):
         """
         Initialize an ANTsImage
 
@@ -63,9 +62,6 @@ def __init__(self, pixeltype='float', dimension=3, components=1, pointer=None, i
         pointer : py::capsule (optional)
             pybind11 capsule holding the pointer to the underlying ITK image object
 
-        label_image : LabelImage
-            a discrete label image for mapping locations to atlas regions
-
         """
         ## Attributes which cant change without creating a new ANTsImage object
         self.pointer = pointer
@@ -87,11 +83,6 @@ def __init__(self, pixeltype='float', dimension=3, components=1, pointer=None, i
         self.shape = utils.get_lib_fn('getShape%s'%self._libsuffix)(self.pointer)
         self.physical_shape = tuple([round(sh*sp,3) for sh,sp in zip(self.shape, self.spacing)])
 
-        if label_image is not None:
-            if not isinstance(label_image, LabelImage):
-                raise ValueError('label_image argument must be a LabelImage type')
-            self.label_image = label_image
-
         self._array = None
 
     @property
@@ -379,9 +370,6 @@ def apply(self, fn):
         new_array = fn(this_array)
         return self.new_image_like(new_array)
 
-    def as_label_image(self, label_info=None):
-        return LabelImage(image=self, label_info=label_info)
-
     ## NUMPY FUNCTIONS ##
     def abs(self, axis=None):
         """ Return absolute value of image """
@@ -641,189 +629,6 @@ def __setitem__(self, key, value):
             super(Dictlist, self).__setitem__(key, [])
         self[key].append(value)
 
-class LabelImage(ANTsImage):
-    """
-    A LabelImage is a special class of ANTsImage which has discrete values
-    and string labels or other metadata (e.g. another string label such as the
-    "lobe" of the region) associated with each of the discrete values.
-    A canonical example of a LabelImage is a brain label_image or parcellation.
-
-    This class provides convenient functionality for manipulating and visualizing
-    images where you have real values associated with aggregated image regions (e.g.
-    if you have cortical thickness values associated with brain regions)
-
-    Commonly-used functionality for LabelImage types:
-        - create publication-quality figures of an label_image
-
-    Nomenclature
-    ------------
-    - key : a string representing the name of the associated index in the atlas image
-        - e.g. if the index is 1001 and the key may be InferiorTemporalGyrus`
-    - value : an integer value in the atlas image
-    - metakey : a string representing one of the possible sets of label key
-        - e.g. 'Lobes' or 'Regions'
-    Notes
-    -----
-    - indexing works by creating a separate dict for each metakey, where
-    """
-    def __init__(self, label_image, label_info=None, template=None):
-        """
-        Initialize a LabelImage
-
-        ANTsR function: N/A
-
-        Arguments
-        ---------
-        label_image : ANTsImage
-            discrete (integer) image as label_image
-
-        label_info : dict or pandas.DataFrame
-            mapping between discrete values in `image` and string names
-            - if dict, the keys should be the discrete integer label values
-              and the values should be the label names or another dict with
-              any metadata
-            - if pd.DataFrame, the index (df.index) should be the discrete integer
-              label values and the other column(s) should be the label names and
-              any metadata
-
-        template : ANTsImage
-            default real-valued image to use for plotting or creating new images.
-            This image should be in the same space as the `label_image` image and the
-            two should be aligned.
-
-        Example
-        -------
-        >>> import ants
-        >>> square = np.zeros((20,20))
-        >>> square[:10,:10] = 0
-        >>> square[:10,10:] = 1
-        >>> square[10:,:10] = 2
-        >>> square[10:,10:] = 3
-        >>> img = ants.from_numpy(square).astype('uint8')
-        >>> label_image = ants.LabelImage(label_image=img, label_info=label_dict)
-        """
-        if label_image.pixeltype not in {'unsigned char', 'unsigned int'}:
-            raise ValueError('Label images must have discrete pixeltype - got %s' % label_image.pixeltype)
-        if label_image.components > 1:
-            raise ValueError('Label images must have only one component - got %i' % label_image.components)
-
-        if label_info is None:
-            label_info = {k:'Label%i'%k for k in range(len(label_image.unique()))}
-
-        if isinstance(label_info, pd.DataFrame):
-            pass
-        elif isinstance(label_info, dict):
-            if isinstance(label_info[list(label_info.keys())[0]], dict):
-                label_info = pd.DataFrame(label_info).T.to_dict()
-            else:
-                label_info = pd.DataFrame(label_info, index=np.arange(len(label_info))).T.to_dict()
-        else:
-            raise ValueError('label_label_info argument must be pd.DataFrame')
-
-        self.label_info = label_info
-        self.label_image = label_image
-        self.template = template
-        self.generate_data()
-
-        super(LabelImage, self).__init__(pixeltype=label_image.pixeltype, dimension=label_image.dimension,
-            components=label_image.components, pointer=label_image.pointer)
-
-    def generate_data(self):
-        self._metakeys = list(self.label_info.columns)
-        self._uniquekeys = {mk:list(np.unique(self.label_info[mk])) for mk in self._metakeys}
-        self._keys = {mk:list(self.label_info[mk]) for mk in self._metakeys}
-        self._values = list(self.label_info.index)
-        self._n_values = len(self._values)
-
-        items = {}
-        for mk in self._metakeys:
-            items[mk] = {}
-            for k, v in zip(self.keys(mk), self.values()):
-                if k in items[mk]:
-                    if isinstance(items[mk][k], list):
-                        items[mk][k].append(v)
-                    else:
-                        items[mk][k] = [items[mk][k]] + [v]
-                else:
-                    items[mk][k] = v
-        self._items = items
-
-    def uniquekeys(self, metakey=None):
-        """
-        Get keys for a given metakey
-        """
-        if metakey is None:
-            return self._uniquekeys
-        else:
-            if metakey not in self.metakeys():
-                raise ValueError('metakey %s does not exist' % metakey)
-            return self._uniquekeys[metakey]
-
-    def keys(self, metakey=None):
-        if metakey is None:
-            return self._keys
-        else:
-            if metakey not in self.metakeys():
-                raise ValueError('metakey %s does not exist' % metakey)
-            return self._keys[metakey]
-
-    def metakeys(self):
-        return self._metakeys
-
-    def parentkey(self, key):
-        parent = None
-        for mk in self.metakeys():
-            if key in self.keys(mk):
-                parent = mk
-        if parent is None:
-            raise ValueError('key does not have a parent')
-        return parent
-
-    def values(self):
-        return self._values
-
-    def items(self, metakey):
-        if metakey not in self.metakeys():
-            raise ValueError('metakey %s does not exist' % metakey)
-        return self._items[metakey]
-
-    def n_values(self):
-        return self._n_values
-
-    def __getitem__(self, key):
-        # get metakey of key
-        metakey = self.parentkey(key)
-        # get key,value pairs for metakey
-        items = self.items(metakey)
-        # return value at the given key
-        return items[key]
-
-    def __setitem__(self, key, value):
-        label_value = self.__getitem__(key)
-        if isinstance(label_value, list):
-            if isinstance(value, list):
-                if len(value) != len(label_value):
-                    raise ValueError('must give either single value or one value '+\
-                                     'for each index (got %i, expected %i)' % (len(value), len(label_value)))
-                    for old_val, new_val in zip(label_value, value):
-                        self.label_image[self.label_image==old_val] = new_val
-                else:
-                    for lv in label_value:
-                        self.label_image[self.label_image==lv] = value
-        else:
-            self.label_image[self.label_image==label_value] = value
-
-    def __repr__(self):
-        s = 'LabelImage\n' +\
-            '\t {:<10} : {} ({})\n'.format('Pixel Type', self.pixeltype, self.dtype)+\
-            '\t {:<10} : {}\n'.format('Components', self.components)+\
-            '\t {:<10} : {}\n'.format('Dimensions', self.shape)+\
-            '\t {:<10} : {}\n'.format('Spacing', self.spacing)+\
-            '\t {:<10} : {}\n'.format('Origin', self.origin)+\
-            '\t {:<10} : {}\n'.format('Direction', self.direction.flatten())+\
-            '\t {:<10} : {}\n'.format('Num Values', self.n_values())
-        return s
-
 
 def copy_image_info(reference, target):
     """

ants/lib/__init__.py

@@ -19,7 +19,6 @@
 from .hausdorffDistance import *
 from .histogramMatchImage import *
 from .invertDisplacementField import *
-# from .invariantImageSimilarity import *
 from .labelOverlapMeasures import *
 from .labelStats import *
 from .mergeChannels import *

ants/utils/__init__.py

@@ -51,8 +51,6 @@
            iMath_propagate_labels_through_mask)
 from .impute import impute
 from .integrate_velocity_field import integrate_velocity_field
-from .invariant_image_similarity import (invariant_image_similarity,
-           convolve_image)
 from .invert_displacement_field import invert_displacement_field
 from .label_clusters import label_clusters
 from .label_image_centroids import label_image_centroids