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ENH: Cleanups as suggested by Tony.
This commit is contained in:
Stefan van der Walt
@@ -16,63 +16,64 @@ See also:
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Paper LBNL-56864, 2005,
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Lawrence Berkeley National Laboratory
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(University of California),
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http://repositories.cdlib.org/lbnl/LBNL-56864.
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http://repositories.cdlib.org/lbnl/LBNL-56864
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"""
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# Tree operations implemented by an array as described in Wu et al.
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# The term "forest" is used to indicate an array that stores one or more trees
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DTYPE = np.int
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ctypedef np.int_t DTYPE_t
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cdef DTYPE_t find_root(np.int_t *work, np.int_t n):
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cdef DTYPE_t find_root(np.int_t *forest, np.int_t n):
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"""Find the root of node n.
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"""
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cdef np.int_t root = n
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while (work[root] < root):
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root = work[root]
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while (forest[root] < root):
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root = forest[root]
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return root
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cdef set_root(np.int_t *work, np.int_t n, np.int_t root):
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cdef set_root(np.int_t *forest, np.int_t n, np.int_t root):
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"""
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Set all nodes on a path to point to new_root.
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"""
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cdef np.int_t j
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while (work[n] < n):
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j = work[n]
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work[n] = root
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while (forest[n] < n):
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j = forest[n]
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forest[n] = root
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n = j
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work[n] = root
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forest[n] = root
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cdef join_trees(np.int_t *work, np.int_t n, np.int_t m):
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cdef join_trees(np.int_t *forest, np.int_t n, np.int_t m):
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"""Join two trees containing nodes n and m.
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"""
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cdef np.int_t root = find_root(work, n)
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cdef np.int_t root = find_root(forest, n)
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cdef np.int_t root_m
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if (n != m):
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root_m = find_root(work, m)
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root_m = find_root(forest, m)
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if (root > root_m):
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root = root_m
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set_root(work, n, root)
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set_root(work, m, root)
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set_root(forest, n, root)
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set_root(forest, m, root)
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cdef link_bg(np.int_t *work, np.int_t n, np.int_t *background_node):
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cdef link_bg(np.int_t *forest, np.int_t n, np.int_t *background_node):
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"""
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Link a node to the background node.
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"""
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if background_node[0] == -1:
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if background_node[0] == -999:
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background_node[0] = n
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join_trees(work, n, background_node[0])
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join_trees(forest, n, background_node[0])
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# Connected components search as described in Fiorio et al.
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@@ -139,16 +140,16 @@ def label(np.ndarray[DTYPE_t, ndim=2] input,
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cdef np.int_t cols = input.shape[1]
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cdef np.ndarray[DTYPE_t, ndim=2] data = input.copy()
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cdef np.ndarray[DTYPE_t, ndim=2] work
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cdef np.ndarray[DTYPE_t, ndim=2] forest
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work = np.arange(data.size, dtype=DTYPE).reshape((rows, cols))
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forest = np.arange(data.size, dtype=DTYPE).reshape((rows, cols))
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cdef np.int_t *work_p = <np.int_t*>work.data
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cdef np.int_t *forest_p = <np.int_t*>forest.data
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cdef np.int_t *data_p = <np.int_t*>data.data
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cdef np.int_t i, j
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cdef np.int_t background_node = -1
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cdef np.int_t background_node = -999
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if neighbors != 4 and neighbors != 8:
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raise ValueError('Neighbors must be either 4 or 8.')
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@@ -156,41 +157,41 @@ def label(np.ndarray[DTYPE_t, ndim=2] input,
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# Initialize the first row
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for j in range(1, cols):
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if data[0, j] == background:
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link_bg(work_p, j, &background_node)
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link_bg(forest_p, j, &background_node)
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if data[0, j] == data[0, j-1]:
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join_trees(work_p, j, j-1)
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join_trees(forest_p, j, j-1)
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for i in range(1, rows):
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# Handle the first column
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if data[i, 0] == background:
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link_bg(work_p, i * cols, &background_node)
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link_bg(forest_p, i * cols, &background_node)
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if data[i, 0] == data[i-1, 0]:
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join_trees(work_p, i*cols, (i-1)*cols)
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join_trees(forest_p, i*cols, (i-1)*cols)
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if neighbors == 8:
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if data[i, 0] == data[i-1, 1]:
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join_trees(work_p, i*cols, (i-1)*cols + 1)
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join_trees(forest_p, i*cols, (i-1)*cols + 1)
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for j in range(1, cols):
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if data[i, j] == background:
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link_bg(work_p, i * cols + j, &background_node)
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link_bg(forest_p, i * cols + j, &background_node)
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if neighbors == 8:
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if data[i, j] == data[i-1, j-1]:
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join_trees(work_p, i*cols + j, (i-1)*cols + j - 1)
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join_trees(forest_p, i*cols + j, (i-1)*cols + j - 1)
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if data[i, j] == data[i-1, j]:
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join_trees(work_p, i*cols + j, (i-1)*cols + j)
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join_trees(forest_p, i*cols + j, (i-1)*cols + j)
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if neighbors == 8:
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if j < cols - 1:
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if data[i, j] == data[i - 1, j + 1]:
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join_trees(work_p, i*cols + j, (i-1)*cols + j + 1)
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join_trees(forest_p, i*cols + j, (i-1)*cols + j + 1)
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if data[i, j] == data[i, j-1]:
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join_trees(work_p, i*cols + j, i*cols + j - 1)
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join_trees(forest_p, i*cols + j, i*cols + j - 1)
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# Label output
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@@ -199,10 +200,10 @@ def label(np.ndarray[DTYPE_t, ndim=2] input,
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for j in range(cols):
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if (i*cols + j) == background_node:
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data[i, j] = -1
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elif (i*cols + j) == work[i, j]:
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elif (i*cols + j) == forest[i, j]:
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data[i, j] = ctr
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ctr = ctr + 1
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else:
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data[i, j] = data_p[work[i, j]]
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data[i, j] = data_p[forest[i, j]]
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return data
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