From 0c8b7afa9201a6b6438c4ae287302c3351b461fb Mon Sep 17 00:00:00 2001
From: "John (EBo) David" <John.L.David@NASA.gov>
Date: Wed, 30 Jan 2019 15:01:48 -0500
Subject: [PATCH] Added a port of scipy.ndimage.measurement.watershed.

dask.array.atop was depricated and moved to dask.array.blockwise.
---
 dask_image/ndmeasure/__init__.py | 94 ++++++++++++++++++++++++++++++++
 dask_image/ndmeasure/_utils.py   |  2 +-
 2 files changed, 95 insertions(+), 1 deletion(-)

diff --git a/dask_image/ndmeasure/__init__.py b/dask_image/ndmeasure/__init__.py
index e383a378..c87b201e 100644
--- a/dask_image/ndmeasure/__init__.py
+++ b/dask_image/ndmeasure/__init__.py
@@ -649,3 +649,97 @@ def variance(input, labels=None, index=None):
     )
 
     return var_lbl
+
+# this version of a watershed alg. is adapted from scipy.ndimage.measurement
+def watershed_ift(input, markers, structure=None, output=None):
+    """
+    Apply watershed from markers using image foresting transform algorithm.
+
+    Parameters
+    ----------
+    input : array_like
+        Input.
+    markers : array_like
+        Markers are points within each watershed that form the beginning
+        of the process.  Negative markers are considered background markers
+        which are processed after the other markers.
+    structure : structure element, optional
+        A structuring element defining the connectivity of the object can be
+        provided. If None, an element is generated with a squared
+        connectivity equal to one.
+    output : ndarray, optional
+        An output array can optionally be provided.  The same shape as input.
+
+    Returns
+    -------
+    watershed_ift : ndarray
+        Output.  Same shape as `input`.
+
+    References
+    ----------
+    .. [1] A.X. Falcao, J. Stolfi and R. de Alencar Lotufo, "The image
+           foresting transform: theory, algorithms, and applications",
+           Pattern Analysis and Machine Intelligence, vol. 26, pp. 19-29, 2004.
+
+    """
+    print("Warning: watershed is a stub")
+    warn("Warning: watershed is a stub", RuntimeWarning)
+
+    input = dask.array.asarray(input)
+
+    if input.dtype.type not in [numpy.uint8, numpy.uint16]:
+        raise TypeError('only 8 and 16 unsigned inputs are supported')
+
+    if not all([len(c) == 1 for c in input.chunks]):
+        warn("``input`` does not have 1 chunk in all dimensions; it will be consolidated first", RuntimeWarning)
+
+    if structure is None:
+        structure = scipy.ndimage.generate_binary_structure(input.ndim, 1)
+    structure = dask.array.asarray(structure, dtype=bool)
+    if structure.ndim != input.ndim:
+        raise RuntimeError('structure and input must have equal rank')
+    for ii in structure.shape:
+        if ii != 3:
+            raise RuntimeError('structure dimensions must be equal to 3')
+
+    return None # 
+    #input = numpy.asarray(input)
+    #if input.dtype.type not in [numpy.uint8, numpy.uint16]:
+    #    raise TypeError('only 8 and 16 unsigned inputs are supported')
+
+    if structure is None:
+        structure = scipy.ndimage.generate_binary_structure(input.ndim, 1)
+    structure = numpy.asarray(structure, dtype=bool)
+    if structure.ndim != input.ndim:
+        raise RuntimeError('structure and input must have equal rank')
+    for ii in structure.shape:
+        if ii != 3:
+            raise RuntimeError('structure dimensions must be equal to 3')
+
+    if not structure.flags.contiguous:
+        structure = structure.copy()
+    markers = numpy.asarray(markers)
+    if input.shape != markers.shape:
+        raise RuntimeError('input and markers must have equal shape')
+
+    integral_types = [numpy.int0,
+                      numpy.int8,
+                      numpy.int16,
+                      numpy.int32,
+                      numpy.int_,
+                      numpy.int64,
+                      numpy.intc,
+                      numpy.intp]
+
+    if markers.dtype.type not in integral_types:
+        raise RuntimeError('marker should be of integer type')
+
+    if isinstance(output, numpy.ndarray):
+        if output.dtype.type not in integral_types:
+            raise RuntimeError('output should be of integer type')
+    else:
+        output = markers.dtype
+
+    output = _ni_support._get_output(output, input)
+    _nd_image.watershed_ift(input, markers, structure, output)
+    return output
diff --git a/dask_image/ndmeasure/_utils.py b/dask_image/ndmeasure/_utils.py
index 6817ac7e..14f92d3e 100644
--- a/dask_image/ndmeasure/_utils.py
+++ b/dask_image/ndmeasure/_utils.py
@@ -33,7 +33,7 @@ def _norm_input_labels_index(input, labels=None, index=None):
 
     if index.ndim > 1:
         warnings.warn(
-            "Having index with dimensionality greater than 1 is undefined.",
+            "Having index with dimensionality (%d) greater than 1 is undefined."%index.ndim,
             FutureWarning
         )