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"""
"""
from __future__ import absolute_import, print_function
# C:\home\ej\wrk\scipy\weave\examples>python vq.py
# vq with 1000 observation, 10 features and 30 codes fo 100 iterations
# speed in python: 0.150119999647
# [25 29] [ 2.49147266 3.83021032]
# speed in standard c: 0.00710999965668
# [25 29] [ 2.49147266 3.83021032]
# speed up: 21.11
# speed inline/blitz: 0.0186300003529
# [25 29] [ 2.49147272 3.83021021]
# speed up: 8.06
# speed inline/blitz2: 0.00461000084877
# [25 29] [ 2.49147272 3.83021021]
# speed up: 32.56
from numpy import *
import sys
sys.path.insert(0,'..')
import scipy.weave.inline_tools as inline_tools
import scipy.weave.converters as converters
blitz_type_converters = converters.blitz
import scipy.weave.c_spec as c_spec
def vq(obs,code_book):
# make sure we're looking at arrays.
obs = asarray(obs)
code_book = asarray(code_book)
# check for 2d arrays and compatible sizes.
obs_sh = shape(obs)
code_book_sh = shape(code_book)
assert(len(obs_sh) == 2 and len(code_book_sh) == 2)
assert(obs_sh[1] == code_book_sh[1])
type = c_spec.num_to_c_types[obs.typecode()]
# band aid for now.
ar_type = 'PyArray_FLOAT'
code = """
#line 37 "vq.py"
// Use tensor notation.
blitz::Array<%(type)s,2> dist_sq(Ncode_book[0],Nobs[0]);
blitz::firstIndex i;
blitz::secondIndex j;
blitz::thirdIndex k;
dist_sq = sum(pow2(obs(j,k) - code_book(i,k)),k);
// Surely there is a better way to do this...
PyArrayObject* py_code = (PyArrayObject*) PyArray_FromDims(1,&Nobs[0],PyArray_LONG);
blitz::Array<int,1> code((int*)(py_code->data),
blitz::shape(Nobs[0]), blitz::neverDeleteData);
code = minIndex(dist_sq(j,i),j);
PyArrayObject* py_min_dist = (PyArrayObject*) PyArray_FromDims(1,&Nobs[0],PyArray_FLOAT);
blitz::Array<float,1> min_dist((float*)(py_min_dist->data),
blitz::shape(Nobs[0]), blitz::neverDeleteData);
min_dist = sqrt(min(dist_sq(j,i),j));
py::tuple results(2);
results[0] = py_code;
results[1] = py_min_dist;
return_val = results;
""" % locals()
code, distortion = inline_tools.inline(code,['obs','code_book'],
type_converters=blitz_type_converters,
compiler='gcc',
verbose=1)
return code, distortion
def vq2(obs,code_book):
""" doesn't use blitz (except in conversion)
ALSO DOES NOT HANDLE STRIDED ARRAYS CORRECTLY
"""
# make sure we're looking at arrays.
obs = asarray(obs)
code_book = asarray(code_book)
# check for 2d arrays and compatible sizes.
obs_sh = shape(obs)
code_book_sh = shape(code_book)
assert(len(obs_sh) == 2 and len(code_book_sh) == 2)
assert(obs_sh[1] == code_book_sh[1])
assert(obs.typecode() == code_book.typecode())
type = c_spec.num_to_c_types[obs.typecode()]
# band aid for now.
ar_type = 'PyArray_FLOAT'
code = """
#line 83 "vq.py"
// THIS DOES NOT HANDLE STRIDED ARRAYS CORRECTLY
// Surely there is a better way to do this...
PyArrayObject* py_code = (PyArrayObject*) PyArray_FromDims(1,&Nobs[0],PyArray_LONG);
PyArrayObject* py_min_dist = (PyArrayObject*) PyArray_FromDims(1,&Nobs[0],PyArray_FLOAT);
int* raw_code = (int*)(py_code->data);
float* raw_min_dist = (float*)(py_min_dist->data);
%(type)s* raw_obs = obs.data();
%(type)s* raw_code_book = code_book.data();
%(type)s* this_obs = NULL;
%(type)s* this_code = NULL;
int Nfeatures = Nobs[1];
float diff,dist;
for(int i=0; i < Nobs[0]; i++)
{
this_obs = &raw_obs[i*Nfeatures];
raw_min_dist[i] = (%(type)s)10000000.; // big number
for(int j=0; j < Ncode_book[0]; j++)
{
this_code = &raw_code_book[j*Nfeatures];
dist = 0;
for(int k=0; k < Nfeatures; k++)
{
diff = this_obs[k] - this_code[k];
dist += diff*diff;
}
dist = dist;
if (dist < raw_min_dist[i])
{
raw_code[i] = j;
raw_min_dist[i] = dist;
}
}
raw_min_dist[i] = sqrt(raw_min_dist[i]);
}
py::tuple results(2);
results[0] = py_code;
results[1] = py_min_dist;
return_val = results;
""" % locals()
code, distortion = inline_tools.inline(code,['obs','code_book'],
type_converters=blitz_type_converters,
compiler='gcc',
verbose=1)
return code, distortion
def vq3(obs,code_book):
""" Uses standard array conversion completely bi-passing blitz.
THIS DOES NOT HANDLE STRIDED ARRAYS CORRECTLY
"""
# make sure we're looking at arrays.
obs = asarray(obs)
code_book = asarray(code_book)
# check for 2d arrays and compatible sizes.
obs_sh = shape(obs)
code_book_sh = shape(code_book)
assert(len(obs_sh) == 2 and len(code_book_sh) == 2)
assert(obs_sh[1] == code_book_sh[1])
assert(obs.typecode() == code_book.typecode())
type = c_spec.num_to_c_types[obs.typecode()]
code = """
#line 139 "vq.py"
// Surely there is a better way to do this...
PyArrayObject* py_code = (PyArrayObject*) PyArray_FromDims(1,&Nobs[0],PyArray_LONG);
PyArrayObject* py_min_dist = (PyArrayObject*) PyArray_FromDims(1,&Nobs[0],PyArray_FLOAT);
int* code_data = (int*)(py_code->data);
float* min_dist_data = (float*)(py_min_dist->data);
%(type)s* this_obs = NULL;
%(type)s* this_code = NULL;
int Nfeatures = Nobs[1];
float diff,dist;
for(int i=0; i < Nobs[0]; i++)
{
this_obs = &obs_data[i*Nfeatures];
min_dist_data[i] = (float)10000000.; // big number
for(int j=0; j < Ncode_book[0]; j++)
{
this_code = &code_book_data[j*Nfeatures];
dist = 0;
for(int k=0; k < Nfeatures; k++)
{
diff = this_obs[k] - this_code[k];
dist += diff*diff;
}
if (dist < min_dist_data[i])
{
code_data[i] = j;
min_dist_data[i] = dist;
}
}
min_dist_data[i] = sqrt(min_dist_data[i]);
}
py::tuple results(2);
results[0] = py_code;
results[1] = py_min_dist;
return_val = results;
""" % locals()
# this is an unpleasant way to specify type factories -- work on it.
import ext_tools
code, distortion = inline_tools.inline(code,['obs','code_book'])
return code, distortion
import time
import RandomArray
def compare(m,Nobs,Ncodes,Nfeatures):
obs = RandomArray.normal(0.,1.,(Nobs,Nfeatures))
codes = RandomArray.normal(0.,1.,(Ncodes,Nfeatures))
import scipy.cluster.vq
scipy.cluster.vq
print('vq with %d observation, %d features and %d codes for %d iterations' %
(Nobs,Nfeatures,Ncodes,m))
t1 = time.time()
for i in range(m):
code,dist = scipy.cluster.vq.py_vq(obs,codes)
t2 = time.time()
py = (t2-t1)
print(' speed in python:', (t2 - t1)/m)
print(code[:2],dist[:2])
t1 = time.time()
for i in range(m):
code,dist = scipy.cluster.vq.vq(obs,codes)
t2 = time.time()
print(' speed in standard c:', (t2 - t1)/m)
print(code[:2],dist[:2])
print(' speed up: %3.2f' % (py/(t2-t1)))
# load into cache
b = vq(obs,codes)
t1 = time.time()
for i in range(m):
code,dist = vq(obs,codes)
t2 = time.time()
print(' speed inline/blitz:',(t2 - t1) / m)
print(code[:2],dist[:2])
print(' speed up: %3.2f' % (py/(t2-t1)))
# load into cache
b = vq2(obs,codes)
t1 = time.time()
for i in range(m):
code,dist = vq2(obs,codes)
t2 = time.time()
print(' speed inline/blitz2:',(t2 - t1) / m)
print(code[:2],dist[:2])
print(' speed up: %3.2f' % (py/(t2-t1)))
# load into cache
b = vq3(obs,codes)
t1 = time.time()
for i in range(m):
code,dist = vq3(obs,codes)
t2 = time.time()
print(' speed using C arrays:',(t2 - t1) / m)
print(code[:2],dist[:2])
print(' speed up: %3.2f' % (py/(t2-t1)))
if __name__ == "__main__":
compare(100,1000,30,10)
#compare(1,10,2,10)
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