From 252e1289d6fdb13ac02b88953881e694500e87ee Mon Sep 17 00:00:00 2001
From: Alan McIntyre <alan.mcintyre@local>
Date: Wed, 23 Jul 2008 13:51:45 +0000
Subject: Standardized NumPy import as "import numpy as np". Moved unique1d
 benchmarking code to new benchmarks directory.

---
 numpy/lib/benchmarks/bench_arraysetops.py | 65 +++++++++++++++++++++++++++++++
 1 file changed, 65 insertions(+)
 create mode 100644 numpy/lib/benchmarks/bench_arraysetops.py

(limited to 'numpy/lib/benchmarks/bench_arraysetops.py')

diff --git a/numpy/lib/benchmarks/bench_arraysetops.py b/numpy/lib/benchmarks/bench_arraysetops.py
new file mode 100644
index 000000000..2c77fb758
--- /dev/null
+++ b/numpy/lib/benchmarks/bench_arraysetops.py
@@ -0,0 +1,65 @@
+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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