Indeed it does! I thought JIT compilation takes place prior to execution of the script. Thanks so much, this makes sense now!
Output: first call: 0.804573 seconds (1.18 M allocations: 53.183 MB, 1.43% gc time) repeated call: 0.000472 seconds (217 allocations: 402.938 KB) Thanks again, Cheers! On Monday, September 12, 2016 at 12:48:30 PM UTC+2, randm...@gmail.com wrote: > > The Julia code takes 0.000535 seconds for me on the second run -- during > the first run, Julia has to compile the method you're timing. Have a look > at the performance tips > <http://docs.julialang.org/en/latest/manual/performance-tips/#measure-performance-with-time-and-pay-attention-to-memory-allocation> > > for a more in depth explanation. > > Am Montag, 12. September 2016 11:53:01 UTC+2 schrieb MLicer: >> >> Dear all, >> >> i've written a low-pass filter in Julia and Python and the code in Julia >> seems to be much slower (*0.800 sec in Julia vs 0.000 sec in Python*). I >> *must* be coding ineffieciently, can anyone comment on the two codes >> below? >> >> *Julia:* >> >> >> <https://lh3.googleusercontent.com/-pEyZjPDcmP8/V9Z6hJdXKfI/AAAAAAAAKLc/iiefpFSzY88S333QndnbnnAnKUBQvzTkACLcB/s1600/filter_julia.png> >> using PyPlot, DSP >> >> # generate data: >> x = linspace(0,30,1e4) >> sin_noise(arr) = sin(arr) + rand(length(arr)) >> >> # create filter: >> designmethod = Butterworth(5) >> ff = digitalfilter(Lowpass(0.02),designmethod) >> @time yl = filtfilt(ff, sin_noise(x)) >> >> Python: >> >> from scipy import signal >> import numpy as np >> import cProfile, pstats >> >> def sin_noise(arr): >> return np.sin(arr) + np.random.rand(len(arr)) >> >> def filterSignal(b,a,x): >> return signal.filtfilt(b, a, x, axis=-1) >> >> def main(): >> # generate data: >> x = np.linspace(0,30,1e4) >> y = sin_noise(x) >> b, a = signal.butter(5, 0.02, "lowpass", analog=False) >> ff = filterSignal(b,a,y) >> >> cProfile.runctx('filterSignal(b,a,y)',globals(),{'b':b,'a':a,'y':y}, >> filename='profileStatistics') >> >> p = pstats.Stats('profileStatistics') >> printFirstN = 5 >> p.sort_stats('cumtime').print_stats(printFirstN) >> >> if __name__=="__main__": >> main() >> >> >> Thanks very much for any replies! >> >
