sorry for so many questions. I am running Mac OSX 10.6 on Intel core 2 Duo. I am running some benchmarks for my research and I have run into another thing that baffles me.
If I run
python -mtimeit -s 'import numpy as np; a = np.random.randn(1e3,1e3)' 'np.dot(a,a)'
I get the following output: 10 loops, best of 3: 142 msec per loop
However, if I run
python -mtimeit -s 'import numpy as np; a = np.random.randint(10,size=1e6).reshape(1e3,1e3)' 'np.dot(a,a)'
I get the following output: 10 loops, best of 3: 7.57 sec per loop
Then I ran
python -mtimeit -s 'import numpy as np; a = np.random.randn(1e3,1e3)' 'a*a' And then
python -mtimeit -s 'import numpy as np; a = np.random.randint(10,size=1e6).reshape(1e3,1e3)' 'a*a'
Both ran at about 7.6 msec per loop so it is not the multiplication. Adding had similar speeds as well, so neither of these should be affecting the dot-product, right? So why is it over 50 times slower to calculate the dot product using ints than using floats?