mirror of
https://github.com/cmusphinx/sphinxtrain.git
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nshmyrev
b77932f224
git-svn-id: svn+ssh://svn.code.sf.net/p/cmusphinx/code/trunk/SphinxTrain@11367 94700074-3cef-4d97-a70e-9c8c206c02f5
67 lines
2.3 KiB
Cython
67 lines
2.3 KiB
Cython
import numpy
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cimport numpy
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def mixw_kmeans_iter(numpy.ndarray[numpy.float64_t, ndim=1] lmw not None,
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numpy.ndarray[numpy.float64_t, ndim=1] cb not None):
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cdef numpy.ndarray[numpy.float64_t, ndim=1] cbacc = numpy.zeros(len(cb))
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cdef numpy.ndarray[numpy.float64_t, ndim=1] cbcnt = numpy.zeros(len(cb))
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cdef numpy.ndarray[numpy.float64_t, ndim=1] dist = numpy.zeros(len(cb))
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cdef numpy.float64_t tdist = 0.0, m, mdist
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cdef Py_ssize_t i, k, cw
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for i in range(lmw.shape[0]):
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m = lmw[i]
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mdist = 1e+50
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cw = 0
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for k in range(dist.shape[0]):
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dist[k] = cb[k] - m
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dist[k] *= dist[k]
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if dist[k] < mdist:
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mdist = dist[k]
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cw = k
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tdist += mdist
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cbacc[cw] += m
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cbcnt[cw] += 1
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cb[:] = cbacc / cbcnt
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return tdist
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def map_mixw_cb(numpy.ndarray[numpy.float64_t, ndim=3] mixw not None,
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numpy.ndarray[numpy.float64_t, ndim=1] cb not None,
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numpy.float64_t zero=0.0):
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cdef numpy.ndarray[numpy.uint8_t, ndim=3] mwmap \
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= numpy.zeros((mixw.shape[0], mixw.shape[1], mixw.shape[2]), 'uint8')
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cdef numpy.ndarray[numpy.float64_t, ndim=3] lmw
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cdef Py_ssize_t s, f, g, i, cw
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cdef numpy.float64_t x, mdist, dist
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lmw = numpy.log(mixw)
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for s in range(lmw.shape[0]):
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for f in range(lmw.shape[1]):
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for g in range(lmw.shape[2]):
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x = mixw[s,f,g]
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if x <= zero:
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mwmap[s,f,g] = len(cb)
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else:
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cw = 0
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mdist = 1e+50
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for i in range(len(cb)):
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dist = cb[i] - lmw[s,f,g]
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dist *= dist
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if dist < mdist:
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mdist = dist
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cw = i
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mwmap[s,f,g] = cw
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return mwmap
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def mixw_freq(numpy.ndarray[numpy.uint8_t, ndim=3] mwmap):
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cdef numpy.ndarray[numpy.int32_t, ndim=1] hist \
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= numpy.zeros(mwmap.max() + 1, 'int32')
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cdef Py_ssize_t i, j, k, cw
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for i in range(mwmap.shape[0]):
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for j in range(mwmap.shape[1]):
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for k in range(mwmap.shape[2]):
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cw = mwmap[i,j,k]
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hist[cw] += 1
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return hist
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