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import numpy as np
import time
from numpy.lib.arraysetops import *
def bench_unique1d( plot_results = False ):
exponents = np.linspace( 2, 7, 9 )
ratios = []
nItems = []
dt1s = []
dt2s = []
for ii in exponents:
nItem = 10 ** ii
print 'using %d items:' % nItem
a = np.fix( nItem / 10 * np.random.random( nItem ) )
print 'unique:'
tt = time.clock()
b = np.unique( a )
dt1 = time.clock() - tt
print dt1
print 'unique1d:'
tt = time.clock()
c = unique1d( a )
dt2 = time.clock() - tt
print dt2
if dt1 < 1e-8:
ratio = 'ND'
else:
ratio = dt2 / dt1
print 'ratio:', ratio
print 'nUnique: %d == %d\n' % (len( b ), len( c ))
nItems.append( nItem )
ratios.append( ratio )
dt1s.append( dt1 )
dt2s.append( dt2 )
assert np.alltrue( b == c )
print nItems
print dt1s
print dt2s
print ratios
if plot_results:
import pylab
def plotMe( fig, fun, nItems, dt1s, dt2s ):
pylab.figure( fig )
fun( nItems, dt1s, 'g-o', linewidth = 2, markersize = 8 )
fun( nItems, dt2s, 'b-x', linewidth = 2, markersize = 8 )
pylab.legend( ('unique', 'unique1d' ) )
pylab.xlabel( 'nItem' )
pylab.ylabel( 'time [s]' )
plotMe( 1, pylab.loglog, nItems, dt1s, dt2s )
plotMe( 2, pylab.plot, nItems, dt1s, dt2s )
pylab.show()
if __name__ == '__main__':
bench_unique1d( plot_results = True )
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