Add LabelVariable

fipy/variables/__init__.py

@@ -12,6 +12,7 @@
 from fipy.variables.surfactantVariable import *
 from fipy.variables.surfactantConvectionVariable import *
 from fipy.variables.distanceVariable import *
+from fipy.variables.labelVariable import *
 
 __all__ = []
 __all__.extend(variable.__all__)
@@ -28,3 +29,4 @@
 __all__.extend(surfactantVariable.__all__)
 __all__.extend(surfactantConvectionVariable.__all__)
 __all__.extend(distanceVariable.__all__)
+__all__.extend(labelVariable.__all__)

fipy/variables/cellVariable.py

@@ -130,6 +130,43 @@ def globalValue(self):
         return self._getGlobalValue(self.mesh._localNonOverlappingCellIDs,
                                     self.mesh._globalNonOverlappingCellIDs)
 
+    @property
+    def ndimage(self):
+        """Global value as an `ndarray` suitable for `scipy.ndimage`
+
+        The cell values of a `CellVariable` are stored in a 1D `ndarray.
+        FiPy arranges its gridded cells in a right-handed Cartesian
+        fashion, with x increasing to the right, y increasing up, and z
+        increasing toward you.  Conversely, NumPy arrays, particularly
+        `scipy.ndimage` arrays, are arranged in stacks of increasing z,
+        each consisting of rows of increasing y, each element of which
+        increases in x.  As a result, we reverse FiPy's (x,y,z) shape to
+        NumPy's (z,y,x).
+
+        >>> import fipy as fp
+        >>> mesh = fp.Grid2D(nx=2, ny=3)
+        >>> var = fp.CellVariable(mesh=mesh, value=mesh.x * mesh.y)
+        >>> print(var.ndimage)
+        [[ 0.25  0.75]
+         [ 0.75  2.25]
+         [ 1.25  3.75]]
+
+        Returns
+        -------
+        ndarray
+            Shape of mesh grid
+
+        Note
+        ----
+        Only suitable for a `CellVariable` defined on a `Grid?D` mesh.
+        """
+        try:
+            shape = self.mesh.shape[::-1]
+        except AttributeError:
+            raise TypeError("Only CellVariables defined on a Grid mesh can "
+                            "be represented as an ndimage")
+        return self.globalValue.reshape(shape)
+
     def setValue(self, value, unit = None, where = None):
         _MeshVariable.setValue(self, value=self._globalToLocalValue(value), unit=unit, where=where)
 

fipy/variables/labelVariable.py

@@ -0,0 +1,238 @@
+from __future__ import unicode_literals
+__docformat__ = 'restructuredtext'
+
+from fipy.variables.cellVariable import CellVariable
+from fipy.tools import numerix
+
+__all__ = ["LabelVariable"]
+from future.utils import text_to_native_str
+__all__ = [text_to_native_str(n) for n in __all__]
+
+class LabelVariable(CellVariable):
+    """Label features in `var` using `scipy.ndimage.label`
+
+    >>> import fipy as fp
+
+    Create a 1D domain with two distinct non-zero regions.
+
+    >>> mesh = fp.Grid1D(nx=5)
+
+    >>> features = fp.CellVariable(mesh=mesh, name="features")
+    >>> features.setValue(1., where=(mesh.x > 1) & (mesh.x < 3))
+    >>> features.setValue(0.5, where=(mesh.x > 4) & (mesh.x < 5))
+    >>> print(features.ndimage)
+    [ 0.   1.   1.   0.   0.5]
+
+    Label the non-zero regions.
+
+    >>> labels = fp.LabelVariable(features, name="labels")
+    >>> print(labels.num_features)
+    2
+    >>> print(labels.ndimage)
+    [0 1 1 0 2]
+
+    To have no connectivity between cells, we can assign a structure with
+    no neighbors.
+
+    >>> labels = fp.LabelVariable(features,
+    ...                           structure=[0,1,0],
+    ...                           name="labels")
+    >>> print(labels.num_features)
+    3
+    >>> print(labels.ndimage)
+    [0 1 2 0 3]
+
+    Similarly, create a 2D domain with two distinct non-zero regions.
+
+    >>> mesh = fp.Grid2D(nx=5, ny=5)
+
+    >>> features = fp.CellVariable(mesh=mesh, name="features")
+    >>> features.setValue(1., where=((mesh.x > 1) & (mesh.x < 3)
+    ...                              & (mesh.y > 1) & (mesh.y < 3)))
+    >>> features.setValue(0.5, where=((mesh.x > 3) & (mesh.x < 4)
+    ...                               & (mesh.y > 3) & (mesh.y < 4)))
+
+    >>> print(features.ndimage)
+    [[ 0.   0.   0.   0.   0. ]
+     [ 0.   1.   1.   0.   0. ]
+     [ 0.   1.   1.   0.   0. ]
+     [ 0.   0.   0.   0.5  0. ]
+     [ 0.   0.   0.   0.   0. ]]
+
+    >>> labels = fp.LabelVariable(features, name="labels")
+    >>> print(labels.num_features)
+    2
+    >>> print(labels.ndimage)
+    [[0 0 0 0 0]
+     [0 1 1 0 0]
+     [0 1 1 0 0]
+     [0 0 0 2 0]
+     [0 0 0 0 0]]
+
+    By default, the two domains are seen as unconnected because there is no
+    overlap of cells along either the x or y axis.  The following structure
+    creates connectivity along one diagonal, but not the other.  Note that
+    the structure array follows NumPy (y, x) ordering, rather than FiPy (x,
+    y) ordering.
+
+    >>> labels = fp.LabelVariable(features,
+    ...                           structure=[[1,1,0],
+    ...                                      [1,1,1],
+    ...                                      [0,1,1]],
+    ...                           name="labels")
+    >>> print(labels.num_features)
+    1
+    >>> print(labels.ndimage)
+    [[0 0 0 0 0]
+     [0 1 1 0 0]
+     [0 1 1 0 0]
+     [0 0 0 1 0]
+     [0 0 0 0 0]]
+
+    Similarly, create a 3D domain with three distinct non-zero regions.
+
+    >>> mesh = fp.Grid3D(nx=3, ny=3, nz=3)
+
+    >>> features = fp.CellVariable(mesh=mesh, name="features")
+    >>> features.setValue(1., where=((mesh.x > 0) & (mesh.x < 2)
+    ...                              & (mesh.y > 0) & (mesh.y < 2)
+    ...                              & (mesh.z > 0) & (mesh.z < 2)))
+    >>> features.setValue(0.7, where=((mesh.x > 2) & (mesh.x < 3)
+    ...                               & (mesh.y > 2) & (mesh.y < 3)
+    ...                               & (mesh.z > 0) & (mesh.z < 1)))
+    >>> features.setValue(0.5, where=((mesh.x > 2) & (mesh.x < 3)
+    ...                               & (mesh.y > 2) & (mesh.y < 3)
+    ...                               & (mesh.z > 2) & (mesh.z < 3)))
+
+    >>> print(features.ndimage)
+    [[[ 1.   1.   0. ]
+      [ 1.   1.   0. ]
+      [ 0.   0.   0.7]]
+    <BLANKLINE>
+     [[ 1.   1.   0. ]
+      [ 1.   1.   0. ]
+      [ 0.   0.   0. ]]
+    <BLANKLINE>
+     [[ 0.   0.   0. ]
+      [ 0.   0.   0. ]
+      [ 0.   0.   0.5]]]
+
+    >>> labels = fp.LabelVariable(features, name="labels")
+    >>> print(labels.num_features)
+    3
+    >>> print(labels.ndimage)
+    [[[1 1 0]
+      [1 1 0]
+      [0 0 2]]
+    <BLANKLINE>
+     [[1 1 0]
+      [1 1 0]
+      [0 0 0]]
+    <BLANKLINE>
+     [[0 0 0]
+      [0 0 0]
+      [0 0 3]]]
+
+    By default, the three domains are seen as unconnected because there is
+    no overlap of cells along any of the x, y, or z axes.  The following
+    structure creates connectivity along one major diagonal, but not the
+    other two.  Note that the structure array follows NumPy (z, y, x)
+    ordering, rather than FiPy (x, y, z) ordering.
+
+    >>> labels = fp.LabelVariable(features,
+    ...                           structure=[[[1,0,0],
+    ...                                       [0,1,0],
+    ...                                       [0,0,0]],
+    ...                                      [[0,1,0],
+    ...                                       [1,1,1],
+    ...                                       [0,1,0]],
+    ...                                      [[0,0,0],
+    ...                                       [0,1,0],
+    ...                                       [0,0,1]]],
+    ...                           name="labels")
+    >>> print(labels.num_features)
+    2
+    >>> print(labels.ndimage)
+    [[[1 1 0]
+      [1 1 0]
+      [0 0 2]]
+    <BLANKLINE>
+     [[1 1 0]
+      [1 1 0]
+      [0 0 0]]
+    <BLANKLINE>
+     [[0 0 0]
+      [0 0 0]
+      [0 0 1]]]
+
+    Parameters
+    ----------
+    var : ~fipy.variables.cellVariable.CellVariable
+        Field to be labeled.  Any non-zero values in input are counted as
+        features and zero values are considered the background.
+
+        .. important:
+           Only sensible if `var` is defined on a `...Grid...` Mesh.
+    structure : array_like, optional
+        A structuring element that defines feature connections.
+        `structure` must be centrosymmetric
+        (see ```scipy.ndimage.label`` Notes
+        <https://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.label.html#scipy.ndimage.label>`_).
+        If no structuring element is provided,
+        one is automatically generated with a squared connectivity equal to
+        one.  That is, for a 2-D `input` array, the default structuring element
+        is::
+            [[0,1,0],
+             [1,1,1],
+             [0,1,0]]
+    dtype : date-type, optional
+        The desired data-type for the labels. Note that the type must be able
+        to store the largest label, or this Variable will raise an Exception.
+        Default: int.
+    """
+    def __init__(self, var, name="", structure=None, dtype=int):
+        # We want our value to hold dtype,
+        # but if we pass an array, the CellVariable
+        # will probably be wonky
+        value = numerix.array(0.).astype(dtype).item()
+        CellVariable.__init__(self,
+                              mesh=var.mesh,
+                              name=name,
+                              value=value,
+                              elementshape=var.shape[:-1])
+        self.var = self._requires(var)
+        self.structure = structure
+        self.dtype = dtype
+        self._num_features = None
+
+    def _calcValue(self):
+        """Label features of `var`
+
+        Side-effect: sets :attr:`self._num_features`.
+        """
+        from scipy import ndimage
+
+        feat = self.var.globalValue
+        feat = feat.reshape(self.var.mesh.shape[::-1])
+
+        arr = numerix.empty(self.var.mesh.shape[::-1], dtype=self.dtype)
+        self._num_features = ndimage.label(input=feat,
+                                           structure=self.structure,
+                                           output=arr)
+        return arr.flatten()
+
+    @property
+    def num_features(self):
+        """How many objects were found
+        """
+        if self.stale or not self._isCached() or self._num_features is None:
+            self._getValue()
+
+        return self._num_features
+
+def _test():
+    import fipy.tests.doctestPlus
+    return fipy.tests.doctestPlus.testmod()
+
+if __name__ == "__main__":
+    _test()

fipy/variables/test.py

@@ -31,7 +31,8 @@ def _suite():
             'fipy.variables.surfactantConvectionVariable',
             'fipy.variables.surfactantVariable',
             'fipy.variables.levelSetDiffusionVariable',
-            'fipy.variables.distanceVariable'
+            'fipy.variables.distanceVariable',
+            'fipy.variables.labelVariable'
         ))
 
 if __name__ == '__main__':