The 32 to 2 second speed up is quite impressive! But I want to help you advance this even more so that your current 2 seconds drops down to a millisecond scale!
Regards, Edward On 10 June 2014 15:05, Edward d'Auvergne <[email protected]> wrote: > Removing the pA_arr and kex_arr structures will make this even faster: > > $ python -m timeit -n 100000 'import numpy as np; X = np.ones(100, > np.float64); pA = 0.9; pA*X' > 100000 loops, best of 3: 6.39 usec per loop > $ python -m timeit -n 100000 'import numpy as np; X = np.ones(100, > np.float64); pA = 0.9; pA_arr = np.array([pA]*100, np.float64); pA*X' > 100000 loops, best of 3: 14.2 usec per loop > $ python -m timeit -n 100000 'import numpy as np; X = np.ones(100, > np.float64); pA = 0.9; pA_arr = np.array([pA]*100, np.float64); > pA_arr*X' > 100000 loops, best of 3: 13.9 usec per loop > > So the first one where pA_arr is not created is more than half the > speed of the others. This will remove some of the overhead that makes > the single spin calculations slower. I'm getting close to the end of > the list of your changes now :) > > Regards, > > Edward > > On 10 June 2014 14:37, Troels Emtekær Linnet <[email protected]> wrote: >> Hi Edward. >> >> When you have digged your way through, you will see that I end up with: >> https://gna.org/task/?7807#comment56 >> >> Going from 32.247 seconds to 2 second for a 100 clustered calculation. >> >> ! BUM! >> >> 2014-06-10 14:33 GMT+02:00 Edward d'Auvergne <[email protected]>: >>> Hi, >>> >>> Maybe self.spins_a could be renamed as self.ones_array? And >>> self.not_spins_a could be self.zeros_array? Or maybe self.ones_struct >>> and self.zeros_struct? The spin part is only one dimension of 5, so >>> the name is confusing. The name needs to have something to do with >>> the ones and zeros, as well as the entire [ei][si][mi][oi][di] >>> structure. >>> >>> Anyway, I can now see that pA_arr is most definitely not needed ;) >>> Its removal will make the code much faster. Try and see what happens! >>> >>> Regards, >>> >>> Edward >>> >>> On 10 June 2014 14:25, Troels Emtekær Linnet <[email protected]> wrote: >>>> Hi Edward. >>>> >>>> spins_a is the multi dimensional numpy array >>>> Of dimension [ei][si][mi][oi][di]. >>>> It consists of 1.0 on all places, where there are dispersion points. >>>> >>>> pA is just the float. >>>> >>>> So, I think we agree? >>>> >>>> The pA values has to end up in a multi dimensional array. >>>> >>>> All multiplications in the target functions has to broadcast to the same >>>> size. >>>> >>>> Numpy multiplication is elements vise. >>>> In all dimensions. >>>> >>>> >>>> >>>> 2014-06-10 13:45 GMT+02:00 Edward d'Auvergne <[email protected]>: >>>>> Hi, >>>>> >>>>> I don't think you even need the pA array. What is the variable >>>>> self.spins_a? Simply try using pA directly. Here is a demo: >>>>> >>>>> """ >>>>> from numpy import array, float64, ones >>>>> >>>>> a = ones(3) >>>>> pA = 0.9 >>>>> pA_array = pA * a >>>>> >>>>> b = array([1, 2, 3], float64) >>>>> >>>>> print("\nFloat times array:") >>>>> print(repr(pA * b)) >>>>> print("\nArray times array:") >>>>> print(repr(pA_array * b)) >>>>> """ >>>>> >>>>> If you run this, you will obtain the same result for both operations. >>>>> Is there a good reason, that I cannot see, why the second option is >>>>> required in the target functions? >>>>> >>>>> Cheers, >>>>> >>>>> Edward >>>>> >>>>> >>>>> >>>>> >>>>> >>>>> On 10 June 2014 12:09, Troels Emtekær Linnet <[email protected]> >>>>> wrote: >>>>>> You are Correct !!! >>>>>> >>>>>> The final version is: >>>>>> pA_arr = pA*self.spins_a >>>>>> >>>>>> The "trick" was to make a numpy multi dimensional spin array in the >>>>>> __init__ function of the class. >>>>>> >>>>>> That is filled with 1.0 where there are dispersion points. >>>>>> >>>>>> This array essential replace the spin looping! >>>>>> >>>>>> Best >>>>>> Troels >>>>>> >>>>>> >>>>>> >>>>>> >>>>>> 2014-06-10 11:56 GMT+02:00 Edward d'Auvergne <[email protected]>: >>>>>>> Hi Troels, >>>>>>> >>>>>>> From the dispersion equations, to me it looks like that you can keep >>>>>>> pA as a single value. Why have you converted it to an array >>>>>>> structure? You will have no problems as you can multiply any numpy >>>>>>> array with a single float. This should be the same for all model >>>>>>> parameters, excluding dw and R20. If you can use single values, that >>>>>>> should be much quicker for the target functions. >>>>>>> >>>>>>> Regards, >>>>>>> >>>>>>> Edward >>>>>>> >>>>>>> >>>>>>> >>>>>>> On 8 June 2014 19:48, <[email protected]> wrote: >>>>>>>> Author: tlinnet >>>>>>>> Date: Sun Jun 8 19:48:31 2014 >>>>>>>> New Revision: 23735 >>>>>>>> >>>>>>>> URL: http://svn.gna.org/viewcvs/relax?rev=23735&view=rev >>>>>>>> Log: >>>>>>>> Important fix for the creation of the multi dimensional pA numpy array. >>>>>>>> >>>>>>>> It should be created as numpy.zeros([ei][si][mi][oi]) instead of >>>>>>>> numpy.ones([ei][si][mi][oi]). >>>>>>>> >>>>>>>> This allows for rapid testing of all dimensions with np.allclose(pA, >>>>>>>> numpy.ones(dw.shape)). >>>>>>>> pA can have missing filled out values, when the number of dispersion >>>>>>>> points are different >>>>>>>> per spectrometer frequency. >>>>>>>> >>>>>>>> Task #7807 (https://gna.org/task/index.php?7807): Speed-up of >>>>>>>> dispersion models for Clustered analysis. >>>>>>>> >>>>>>>> Modified: >>>>>>>> branches/disp_spin_speed/target_functions/relax_disp.py >>>>>>>> >>>>>>>> Modified: branches/disp_spin_speed/target_functions/relax_disp.py >>>>>>>> URL: >>>>>>>> http://svn.gna.org/viewcvs/relax/branches/disp_spin_speed/target_functions/relax_disp.py?rev=23735&r1=23734&r2=23735&view=diff >>>>>>>> ============================================================================== >>>>>>>> --- branches/disp_spin_speed/target_functions/relax_disp.py >>>>>>>> (original) >>>>>>>> +++ branches/disp_spin_speed/target_functions/relax_disp.py Sun >>>>>>>> Jun 8 19:48:31 2014 >>>>>>>> @@ -411,7 +411,7 @@ >>>>>>>> # The number of disp point can change per spectrometer, >>>>>>>> so we make the maximum size. >>>>>>>> self.R20A_a = np.ones(back_calc_shape + >>>>>>>> [self.max_num_disp_points]) >>>>>>>> self.R20B_a = np.ones(back_calc_shape + >>>>>>>> [self.max_num_disp_points]) >>>>>>>> - self.pA_a = np.ones(back_calc_shape + >>>>>>>> [self.max_num_disp_points]) >>>>>>>> + self.pA_a = np.zeros(back_calc_shape + >>>>>>>> [self.max_num_disp_points]) >>>>>>>> self.dw_frq_a = np.ones(back_calc_shape + >>>>>>>> [self.max_num_disp_points]) >>>>>>>> self.kex_a = np.ones(back_calc_shape + >>>>>>>> [self.max_num_disp_points]) >>>>>>>> self.cpmg_frqs_a = np.ones(back_calc_shape + >>>>>>>> [self.max_num_disp_points]) >>>>>>>> >>>>>>>> >>>>>>>> _______________________________________________ >>>>>>>> relax (http://www.nmr-relax.com) >>>>>>>> >>>>>>>> This is the relax-commits mailing list >>>>>>>> [email protected] >>>>>>>> >>>>>>>> To unsubscribe from this list, get a password >>>>>>>> reminder, or change your subscription options, >>>>>>>> visit the list information page at >>>>>>>> https://mail.gna.org/listinfo/relax-commits >>>>>>> >>>>>>> _______________________________________________ >>>>>>> relax (http://www.nmr-relax.com) >>>>>>> >>>>>>> This is the relax-devel mailing list >>>>>>> [email protected] >>>>>>> >>>>>>> To unsubscribe from this list, get a password >>>>>>> reminder, or change your subscription options, >>>>>>> visit the list information page at >>>>>>> https://mail.gna.org/listinfo/relax-devel _______________________________________________ relax (http://www.nmr-relax.com) This is the relax-devel mailing list [email protected] To unsubscribe from this list, get a password reminder, or change your subscription options, visit the list information page at https://mail.gna.org/listinfo/relax-devel
