Revision: 6766
http://matplotlib.svn.sourceforge.net/matplotlib/?rev=6766&view=rev
Author: jdh2358
Date: 2009-01-08 19:42:15 +0000 (Thu, 08 Jan 2009)
Log Message:
-----------
enhanced tests and moved numpy method into pyx module
Modified Paths:
--------------
trunk/py4science/examples/pyrex/nnbf/nnbf.pyx
trunk/py4science/examples/pyrex/nnbf/test_nnbf.py
Modified: trunk/py4science/examples/pyrex/nnbf/nnbf.pyx
===================================================================
--- trunk/py4science/examples/pyrex/nnbf/nnbf.pyx 2009-01-08 19:17:15 UTC
(rev 6765)
+++ trunk/py4science/examples/pyrex/nnbf/nnbf.pyx 2009-01-08 19:42:15 UTC
(rev 6766)
@@ -38,8 +38,8 @@
self.n = n
- self.numrows = 100
- # XXX how to create mepty as contiguous w/o copy?
+ self.numrows = 10000
+ # XXX how to create empty as contiguous w/o copy?
data = np.empty((self.numrows, self.n), dtype=np.float)
self.data = np.ascontiguousarray(data, dtype=np.float)
inner_data = self.data
@@ -53,7 +53,7 @@
"""
cdef np.ndarray[double, ndim=2] inner_data
cdef np.ndarray[double, ndim=1] pp
- pp = np.asarray(point).astype(np.float)
+ pp = np.array(point).astype(np.float)
self.data[self.numpoints] = pp
@@ -67,8 +67,8 @@
self.data = np.ascontiguousarray(newdata, dtype=np.float)
inner_data = self.data
self.raw_data = <double*>inner_data.data
- #self.raw_data = <double*>inner_data.data
+
def get_data(NNBF self):
"""
return a copy of data added so far as a numpoints x n array
@@ -99,16 +99,11 @@
# don't do a python lookup inside the loop
n = self.n
-
+
for i in range(self.numpoints):
- # XXX : is there a more efficient way to access the row
- # data? Can/should we be using raw_data here?
- #row = self.data[i]
neighbor = is_neighbor(
n,
- #(<double*>self.data.data)+i*n,
self.raw_data + i*n,
- #dataptr + i*n,
<double*>pp.data,
d2max)
@@ -119,4 +114,19 @@
return neighbors
+ def find_neighbors_numpy(self, point, radius):
+ """
+ do a plain ol numpy lookup to compare performance and output
+ *data* is a numpoints x numdims array
+ *point* is a numdims length vector
+ radius is the max distance distance
+
+ return an array of indices into data which are within radius
+ """
+ data = self.get_data()
+ distance = data - point
+ r = np.sqrt((distance*distance).sum(axis=1))
+ return np.nonzero(r<=radius)[0]
+
+
Modified: trunk/py4science/examples/pyrex/nnbf/test_nnbf.py
===================================================================
--- trunk/py4science/examples/pyrex/nnbf/test_nnbf.py 2009-01-08 19:17:15 UTC
(rev 6765)
+++ trunk/py4science/examples/pyrex/nnbf/test_nnbf.py 2009-01-08 19:42:15 UTC
(rev 6766)
@@ -4,18 +4,10 @@
import numpy.testing as nptest
-from nnbf_proto import find_neighbors_numpy
-# the pure python prototype
-
-
-#import nnbf_proto as nnbf
-
-# the cython extension
import nnbf
-
-def jdh_add_data():
+def test_add_data():
nn = nnbf.NNBF(6)
for i in range(202):
@@ -38,14 +30,13 @@
ind = nn.find_neighbors(x, radius)
data = nn.get_data()
- indnumpy = find_neighbors_numpy(data, x, radius)
+ indnumpy = nn.find_neighbors_numpy(x, radius)
nptest.assert_equal((ind==indnumpy), True)
-if 1:
-#def test_performance():
+def test_performance():
NUMDIM = 6
nn = nnbf.NNBF(NUMDIM)
@@ -61,27 +52,32 @@
print 'testing nnbf...'
times = np.zeros(10)
- for i in range(len(times)):
+ for i in range(len(times)):
start = time.clock()
ind = nn.find_neighbors(x, radius)
end = time.clock()
times[i] = end-start
- print ' 10 trials: mean=%1.4f, min=%1.4f'%(times.mean(), times.min())
+ munn = times.mean()
+ print ' 10 trials: mean=%1.4f, min=%1.4f'%(munn, times.min())
+
print 'testing numpy...'
- for i in range(len(times)):
+ for i in range(len(times)):
start = time.clock()
- ind = find_neighbors_numpy(data, x, radius)
- end = time.clock()
+ ind = nn.find_neighbors_numpy(x, radius)
+ end = time.clock()
times[i] = end-start
- print ' 10 trials: mean=%1.4f, min=%1.4f'%(times.mean(), times.min())
+ munumpy = times.mean()
+ print ' 10 trials: mean=%1.4f, min=%1.4f'%(munumpy, times.min())
+ # nn should be at least 3 times faster
+ nptest.assert_equal((3*munn < munumpy), True)
if __name__=='__main__':
- #nose.runmodule(argv=['-s','--with-doctest'], exit=False)
+ nose.runmodule(argv=['-s','--with-doctest'], exit=False)
pass
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