44 lines
1.4 KiB
Cython
44 lines
1.4 KiB
Cython
# Fast inner loop for DBSCAN.
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# Author: Lars Buitinck
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# License: 3-clause BSD
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cimport cython
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from libcpp.vector cimport vector
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cimport numpy as np
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import numpy as np
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np.import_array()
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def dbscan_inner(np.ndarray[np.uint8_t, ndim=1, mode='c'] is_core,
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np.ndarray[object, ndim=1] neighborhoods,
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np.ndarray[np.npy_intp, ndim=1, mode='c'] labels):
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cdef np.npy_intp i, label_num = 0, v
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cdef np.ndarray[np.npy_intp, ndim=1] neighb
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cdef vector[np.npy_intp] stack
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for i in range(labels.shape[0]):
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if labels[i] != -1 or not is_core[i]:
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continue
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# Depth-first search starting from i, ending at the non-core points.
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# This is very similar to the classic algorithm for computing connected
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# components, the difference being that we label non-core points as
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# part of a cluster (component), but don't expand their neighborhoods.
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while True:
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if labels[i] == -1:
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labels[i] = label_num
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if is_core[i]:
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neighb = neighborhoods[i]
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for i in range(neighb.shape[0]):
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v = neighb[i]
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if labels[v] == -1:
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stack.push_back(v)
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if stack.size() == 0:
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break
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i = stack.back()
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stack.pop_back()
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label_num += 1
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