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""" Benchmark functions for linalg.decomp module
"""
from __future__ import division, print_function, absolute_import
import sys
from numpy import linalg as nl
from scipy import linalg as sl
from numpy.testing import measure, rand, assert_
def random(size):
return rand(*size)
def bench_eigvals():
numpy_eigvals = nl.eigvals
scipy_eigvals = sl.eigvals
print()
print(' Finding matrix eigenvalues')
print(' ==================================')
print(' | contiguous | non-contiguous ')
print('----------------------------------------------')
print(' size | scipy | numpy | scipy | numpy ')
for size,repeat in [(20,150),(100,7),(200,2)]:
repeat *= 1
print('%5s' % size, end=' ')
sys.stdout.flush()
a = random([size,size])
print('| %6.2f ' % measure('scipy_eigvals(a)',repeat), end=' ')
sys.stdout.flush()
print('| %6.2f ' % measure('numpy_eigvals(a)',repeat), end=' ')
sys.stdout.flush()
a = a[-1::-1,-1::-1] # turn into a non-contiguous array
assert_(not a.flags['CONTIGUOUS'])
print('| %6.2f ' % measure('scipy_eigvals(a)',repeat), end=' ')
sys.stdout.flush()
print('| %6.2f ' % measure('numpy_eigvals(a)',repeat), end=' ')
sys.stdout.flush()
print(' (secs for %s calls)' % (repeat))
def bench_svd():
numpy_svd = nl.svd
scipy_svd = sl.svd
print()
print(' Finding the SVD decomposition')
print(' ==================================')
print(' | contiguous | non-contiguous ')
print('----------------------------------------------')
print(' size | scipy | numpy | scipy | numpy ')
for size,repeat in [(20,150),(100,7),(200,2)]:
repeat *= 1
print('%5s' % size, end=' ')
sys.stdout.flush()
a = random([size,size])
print('| %6.2f ' % measure('scipy_svd(a)',repeat), end=' ')
sys.stdout.flush()
print('| %6.2f ' % measure('numpy_svd(a)',repeat), end=' ')
sys.stdout.flush()
a = a[-1::-1,-1::-1] # turn into a non-contiguous array
assert_(not a.flags['CONTIGUOUS'])
print('| %6.2f ' % measure('scipy_svd(a)',repeat), end=' ')
sys.stdout.flush()
print('| %6.2f ' % measure('numpy_svd(a)',repeat), end=' ')
sys.stdout.flush()
print(' (secs for %s calls)' % (repeat))
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