Most data will be from 2 or more magnetic fields, as that is rather essential. But the change will not be significant.
Regards, Edward On 11 June 2014 16:42, Troels Emtekær Linnet <[email protected]> wrote: > Hi Ed. > > I will keep the flag: has_missing. > > I guess, that most data will be one field ? > > So, that check is faster than computing for spins missings. > > Best > Troels > > 2014-06-11 16:20 GMT+02:00 Troels Emtekær Linnet <[email protected]>: >> Welllll..... >> >> Argghhh... >> >> Okay! >> >> But only because of global warming, and saving energy and computation >> costs... >> >> Best >> Troels >> >> 2014-06-11 16:19 GMT+02:00 Edward d'Auvergne <[email protected]>: >>> Pity, I just tested and for the single spin case I see a 33% speed up >>> with this change (nr_iter = 10000, cumtime 2.41 seconds verses 1.80 >>> seconds for the change). Are you really, really sure this idea should >>> not be used and is not worth such a speed up? >>> >>> Regards, >>> >>> Edward >>> >>> >>> >>> On 11 June 2014 16:05, Troels Emtekær Linnet <[email protected]> wrote: >>>> Hi Edward. >>>> >>>> I wont make that change. >>>> >>>> I will keep the clean implementation as it is. >>>> >>>> Best >>>> Troels >>>> >>>> 2014-06-11 15:52 GMT+02:00 Edward d'Auvergne <[email protected]>: >>>>> By the way, I just obtained a ~10% speed up using your profiling >>>>> script test_suite/shared_data/dispersion/profiling/profiling_cr72.py >>>>> if I send in the original parameter vector R20A, R20B, and dw arrays >>>>> and check these values instead of the full structures. See the diff >>>>> below for ideas. With a little more polish and more numpy ufunc >>>>> usage, you should be able to squeeze more speed out of the CR72 model >>>>> still. >>>>> >>>>> Regards, >>>>> >>>>> Edward >>>>> >>>>> >>>>> P. S. Here is the diff: >>>>> >>>>> """ >>>>> Index: lib/dispersion/cr72.py >>>>> =================================================================== >>>>> --- lib/dispersion/cr72.py (revision 23841) >>>>> +++ lib/dispersion/cr72.py (working copy) >>>>> @@ -92,13 +92,13 @@ >>>>> """ >>>>> >>>>> # Python module imports. >>>>> -from numpy import arccosh, array, cos, cosh, isfinite, fabs, min, >>>>> max, sqrt, subtract, sum >>>>> +from numpy import arccosh, array, cos, cosh, isfinite, fabs, min, >>>>> max, sqrt, subtract, sum, multiply >>>>> from numpy.ma import fix_invalid, masked_greater_equal, masked_less, >>>>> masked_where >>>>> >>>>> # Repetitive calculations (to speed up calculations). >>>>> eta_scale = 2.0**(-3.0/2.0) >>>>> >>>>> -def r2eff_CR72(r20a=None, r20b=None, pA=None, dw=None, kex=None, >>>>> cpmg_frqs=None, back_calc=None, num_points=None): >>>>> +def r2eff_CR72(r20a_orig=None, r20b_orig=None, r20a=None, r20b=None, >>>>> pA=None, dw_orig=None, dw=None, kex=None, cpmg_frqs=None, >>>>> back_calc=None, num_points=None): >>>>> """Calculate the R2eff values for the CR72 model. >>>>> >>>>> See the module docstring for details. >>>>> @@ -133,7 +133,7 @@ >>>>> return >>>>> >>>>> # Test if dw is zero. Wait for replacement, since this is spin >>>>> specific. >>>>> - if min(fabs(dw)) == 0.0: >>>>> + if min(fabs(dw_orig)) == 0.0: >>>>> t_dw_zero = True >>>>> mask_dw_zero = masked_where(dw == 0.0, dw) >>>>> >>>>> @@ -147,7 +147,7 @@ >>>>> k_AB = pB * kex >>>>> >>>>> # The Psi and zeta values. >>>>> - if sum(r20a - r20b) != 0.0: >>>>> + if sum(r20a_orig - r20b_orig) != 0.0: >>>>> fact = r20a - r20b - k_BA + k_AB >>>>> Psi = fact**2 - dw2 + 4.0*pA*pB*kex**2 >>>>> zeta = 2.0*dw * fact >>>>> @@ -182,7 +182,8 @@ >>>>> return >>>>> >>>>> # Calculate R2eff. This uses the temporary buffer and fill >>>>> directly to back_calc. >>>>> - subtract(r20_kex, cpmg_frqs * arccosh( fact ), out=back_calc) >>>>> + multiply(cpmg_frqs, arccosh(fact), out=back_calc) >>>>> + subtract(r20_kex, back_calc, out=back_calc) >>>>> >>>>> # Replace data in array. >>>>> # If dw is zero. >>>>> Index: target_functions/relax_disp.py >>>>> =================================================================== >>>>> --- target_functions/relax_disp.py (revision 23841) >>>>> +++ target_functions/relax_disp.py (working copy) >>>>> @@ -567,7 +567,7 @@ >>>>> self.r20b_struct[:] = multiply.outer( >>>>> asarray(R20B).reshape(self.NE, self.NS, self.NM), self.no_nd_struct ) >>>>> >>>>> ## Back calculate the R2eff values. >>>>> - r2eff_CR72(r20a=self.r20a_struct, r20b=self.r20b_struct, >>>>> pA=pA, dw=self.dw_struct, kex=kex, cpmg_frqs=self.cpmg_frqs_a, >>>>> back_calc=self.back_calc_a, num_points=self.num_disp_points_a) >>>>> + r2eff_CR72(r20a_orig=R20A, r20b_orig=R20B, >>>>> r20a=self.r20a_struct, r20b=self.r20b_struct, pA=pA, dw_orig=dw, >>>>> dw=self.dw_struct, kex=kex, cpmg_frqs=self.cpmg_frqs_a, >>>>> back_calc=self.back_calc_a, num_points=self.num_disp_points_a) >>>>> >>>>> # Clean the data for all values, which is left over at the >>>>> end of arrays. >>>>> self.back_calc_a = self.back_calc_a*self.disp_struct >>>>> Index: test_suite/shared_data/dispersion/profiling/profiling_cr72.py >>>>> =================================================================== >>>>> --- test_suite/shared_data/dispersion/profiling/profiling_cr72.py >>>>> (revision 23841) >>>>> +++ test_suite/shared_data/dispersion/profiling/profiling_cr72.py >>>>> (working copy) >>>>> @@ -55,7 +55,7 @@ >>>>> def main(): >>>>> if True: >>>>> # Nr of iterations. >>>>> - nr_iter = 1 >>>>> + nr_iter = 10000 >>>>> >>>>> # Print statistics. >>>>> verbose = True >>>>> @@ -275,7 +275,7 @@ >>>>> back_calc = array([0.0]*len(cpmg_frqs[ei][mi][oi])) >>>>> >>>>> # Initialise call to function. >>>>> - r2eff_CR72(r20a=r20a, r20b=r20b, pA=pA, >>>>> dw=dw_frq, kex=kex, cpmg_frqs=array(cpmg_frqs[ei][mi][oi]), >>>>> back_calc=back_calc, num_points=len(back_calc)) >>>>> + r2eff_CR72(r20a_orig=R20A, r20b_orig=R20B, >>>>> r20a=r20a, r20b=r20b, pA=pA, dw_orig=dw_frq, dw=dw_frq, kex=kex, >>>>> cpmg_frqs=array(cpmg_frqs[ei][mi][oi]), back_calc=back_calc, >>>>> num_points=len(back_calc)) >>>>> >>>>> for oi in range(len(self.offset)): >>>>> for di in range(len(self.points[mi])): >>>>> @@ -505,4 +505,4 @@ >>>>> model = C1.calc(params) >>>>> print(model) >>>>> >>>>> -#test_reshape() >>>>> \ No newline at end of file >>>>> +#test_reshape() >>>>> """ >>>>> >>>>> >>>>> >>>>> On 11 June 2014 15:45, Edward d'Auvergne <[email protected]> wrote: >>>>>> You wait until you see what happens with your multiple offset R1rho data >>>>>> ;) >>>>>> >>>>>> On 11 June 2014 15:42, Troels Emtekær Linnet <[email protected]> >>>>>> wrote: >>>>>>> The progress is EXTREME. >>>>>>> >>>>>>> Per spin, I am now 1.5 X faster per spin calculation. >>>>>>> Per cluster of 100, I am now 33X faster. >>>>>>> >>>>>>> Go one more version up, and it is 64 X faster. >>>>>>> >>>>>>> WOW! >>>>>>> >>>>>>> >>>>>>> >>>>>>> ---- >>>>>>> Checked on MacBook Pro >>>>>>> 2.4 GHz Intel Core i5 >>>>>>> 8 GB 1067 Mhz DDR3 RAM. >>>>>>> >>>>>>> Timing for: >>>>>>> 3 fields >>>>>>> ('sfrq: ', 600000000.0, 'number of cpmg frq', 15, array([ 2., 6., 10., >>>>>>> 14., 18., 22., 26., 30., 34., 38., 42., 46., 50., 54., 58.])) >>>>>>> ('sfrq: ', 800000000.0, 'number of cpmg frq', 20, array([ 2., 6., 10., >>>>>>> 14., 18., 22., 26., 30., 34., 38., 42., 46., 50., 54., 58., 62., 66., >>>>>>> 70., 74., 78.])) >>>>>>> ('sfrq: ', 900000000.0, 'number of cpmg frq', 22, array([ 2., 6., 10., >>>>>>> 14., 18., 22., 26., 30., 34., 38., 42., 46., 50., 54., 58., 62., 66., >>>>>>> 70., 74., 78., 82., 86.])) >>>>>>> >>>>>>> iterations of function call: 1000 >>>>>>> >>>>>>> Timed for simulating 1 or 100 clustered spins. >>>>>>> >>>>>>> Find tags: >>>>>>> svn ls "^/tags" >>>>>>> svn switch ^/tags/3.2.2 >>>>>>> >>>>>>> ############################################################################################## >>>>>>> ncalls tottime percall cumtime percall filename:lineno(function) >>>>>>> >>>>>>> ############################ >>>>>>> For disp_spin_speed r23841 # >>>>>>> ############################ >>>>>>> 1 spin: >>>>>>> 1 0.000 0.000 0.373 0.373 <string>:1(<module>) >>>>>>> 1 0.001 0.001 0.373 0.373 pf:427(single) >>>>>>> 1000 0.002 0.000 0.366 0.000 pf:413(calc) >>>>>>> 1000 0.012 0.000 0.363 0.000 >>>>>>> relax_disp.py:994(func_CR72_full) >>>>>>> 1000 0.027 0.000 0.345 0.000 >>>>>>> relax_disp.py:545(calc_CR72_chi2) >>>>>>> 1003 0.148 0.000 0.260 0.000 cr72.py:101(r2eff_CR72) >>>>>>> 7043 0.059 0.000 0.059 0.000 {method 'reduce' of >>>>>>> 'numpy.ufunc' objects} >>>>>>> 1000 0.004 0.000 0.052 0.000 core.py:1701(masked_where) >>>>>>> 3006 0.006 0.000 0.036 0.000 fromnumeric.py:1621(sum) >>>>>>> 3006 0.004 0.000 0.028 0.000 _methods.py:23(_sum) >>>>>>> 3000 0.024 0.000 0.024 0.000 {method 'outer' of >>>>>>> 'numpy.ufunc' objects} >>>>>>> 1000 0.013 0.000 0.024 0.000 chi2.py:72(chi2_rankN) >>>>>>> 1000 0.002 0.000 0.024 0.000 {method 'view' of >>>>>>> 'numpy.ndarray' objects} >>>>>>> 2006 0.003 0.000 0.023 0.000 fromnumeric.py:2132(amin) >>>>>>> 1000 0.003 0.000 0.021 0.000 >>>>>>> core.py:2774(__array_finalize__) >>>>>>> >>>>>>> 100 spins: >>>>>>> 1 0.000 0.000 1.630 1.630 <string>:1(<module>) >>>>>>> 1 0.003 0.003 1.630 1.630 pf:449(cluster) >>>>>>> 1000 0.004 0.000 1.532 0.002 pf:413(calc) >>>>>>> 1000 0.020 0.000 1.528 0.002 >>>>>>> relax_disp.py:994(func_CR72_full) >>>>>>> 1000 0.073 0.000 1.495 0.001 >>>>>>> relax_disp.py:545(calc_CR72_chi2) >>>>>>> 1300 1.071 0.001 1.285 0.001 cr72.py:101(r2eff_CR72) >>>>>>> 8528 0.131 0.000 0.131 0.000 {method 'reduce' of >>>>>>> 'numpy.ufunc' objects} >>>>>>> 1 0.000 0.000 0.094 0.094 pf:106(__init__) >>>>>>> 3000 0.083 0.000 0.083 0.000 {method 'outer' of >>>>>>> 'numpy.ufunc' objects} >>>>>>> 3600 0.009 0.000 0.082 0.000 fromnumeric.py:1621(sum) >>>>>>> 1000 0.055 0.000 0.079 0.000 chi2.py:72(chi2_rankN) >>>>>>> 1000 0.006 0.000 0.078 0.000 core.py:1701(masked_where) >>>>>>> 1 0.019 0.019 0.069 0.069 >>>>>>> pf:173(return_r2eff_arrays) >>>>>>> 3600 0.006 0.000 0.067 0.000 _methods.py:23(_sum) >>>>>>> 2600 0.006 0.000 0.049 0.000 fromnumeric.py:2132(amin) >>>>>>> 2600 0.005 0.000 0.042 0.000 _methods.py:19(_amin) >>>>>>> 1000 0.004 0.000 0.032 0.000 {method 'view' of >>>>>>> 'numpy.ndarray' objects} >>>>>>> >>>>>>> >>>>>>> ############################ >>>>>>> For disp_spin_speed r23806 # >>>>>>> ############################ >>>>>>> 1 spin: >>>>>>> 1 0.000 0.000 0.546 0.546 <string>:1(<module>) >>>>>>> 1 0.002 0.002 0.546 0.546 pf:427(single) >>>>>>> 1000 0.003 0.000 0.538 0.001 pf:413(calc) >>>>>>> 1000 0.015 0.000 0.535 0.001 >>>>>>> relax_disp.py:989(func_CR72_full) >>>>>>> 1000 0.042 0.000 0.513 0.001 >>>>>>> relax_disp.py:523(calc_CR72_chi2) >>>>>>> 1003 0.142 0.000 0.365 0.000 cr72.py:101(r2eff_CR72) >>>>>>> 2003 0.055 0.000 0.181 0.000 numeric.py:2056(allclose) >>>>>>> 10046 0.083 0.000 0.083 0.000 {method 'reduce' of >>>>>>> 'numpy.ufunc' objects} >>>>>>> 3000 0.045 0.000 0.076 0.000 shape_base.py:761(tile) >>>>>>> 4015 0.006 0.000 0.053 0.000 fromnumeric.py:1762(any) >>>>>>> 4015 0.004 0.000 0.039 0.000 {method 'any' of >>>>>>> 'numpy.ndarray' objects} >>>>>>> 4015 0.005 0.000 0.035 0.000 _methods.py:31(_any) >>>>>>> 2003 0.003 0.000 0.028 0.000 fromnumeric.py:1842(all) >>>>>>> 1000 0.014 0.000 0.026 0.000 chi2.py:72(chi2_rankN) >>>>>>> 2003 0.004 0.000 0.026 0.000 fromnumeric.py:1621(sum) >>>>>>> 4138 0.012 0.000 0.025 0.000 numeric.py:2320(seterr) >>>>>>> 2003 0.002 0.000 0.020 0.000 {method 'all' of >>>>>>> 'numpy.ndarray' objects} >>>>>>> 2003 0.003 0.000 0.019 0.000 _methods.py:23(_sum) >>>>>>> 2003 0.003 0.000 0.018 0.000 _methods.py:35(_all) >>>>>>> 14046 0.016 0.000 0.016 0.000 >>>>>>> {numpy.core.multiarray.array} >>>>>>> >>>>>>> 100 spins: >>>>>>> 1 0.000 0.000 2.036 2.036 <string>:1(<module>) >>>>>>> 1 0.003 0.003 2.036 2.036 pf:449(cluster) >>>>>>> 1000 0.004 0.000 1.905 0.002 pf:413(calc) >>>>>>> 1000 0.022 0.000 1.901 0.002 >>>>>>> relax_disp.py:989(func_CR72_full) >>>>>>> 1000 0.098 0.000 1.865 0.002 >>>>>>> relax_disp.py:523(calc_CR72_chi2) >>>>>>> 1300 0.986 0.001 1.511 0.001 cr72.py:101(r2eff_CR72) >>>>>>> 2300 0.238 0.000 0.434 0.000 numeric.py:2056(allclose) >>>>>>> 3000 0.058 0.000 0.238 0.000 shape_base.py:761(tile) >>>>>>> 4000 0.154 0.000 0.154 0.000 {method 'repeat' of >>>>>>> 'numpy.ndarray' objects} >>>>>>> 11828 0.147 0.000 0.147 0.000 {method 'reduce' of >>>>>>> 'numpy.ufunc' objects} >>>>>>> 1 0.000 0.000 0.129 0.129 pf:106(__init__) >>>>>>> 1 0.021 0.021 0.098 0.098 >>>>>>> pf:173(return_r2eff_arrays) >>>>>>> 1000 0.054 0.000 0.078 0.000 chi2.py:72(chi2_rankN) >>>>>>> 4609 0.008 0.000 0.073 0.000 fromnumeric.py:1762(any) >>>>>>> 2300 0.007 0.000 0.055 0.000 fromnumeric.py:1621(sum) >>>>>>> 4609 0.005 0.000 0.054 0.000 {method 'any' of >>>>>>> 'numpy.ndarray' objects} >>>>>>> 4609 0.006 0.000 0.049 0.000 _methods.py:31(_any) >>>>>>> 2300 0.004 0.000 0.044 0.000 _methods.py:23(_sum) >>>>>>> 2300 0.005 0.000 0.039 0.000 fromnumeric.py:1842(all) >>>>>>> 4732 0.016 0.000 0.035 0.000 numeric.py:2320(seterr) >>>>>>> 4600 0.032 0.000 0.032 0.000 {abs} >>>>>>> 1301 0.004 0.000 0.030 0.000 fromnumeric.py:2048(amax) >>>>>>> 17016 0.028 0.000 0.028 0.000 >>>>>>> {numpy.core.multiarray.array} >>>>>>> >>>>>>> ############################ >>>>>>> For trunk r23785 # >>>>>>> ############################ >>>>>>> 1 spin: >>>>>>> 1 0.000 0.000 0.572 0.572 <string>:1(<module>) >>>>>>> 1 0.002 0.002 0.572 0.572 pf:427(single) >>>>>>> 1000 0.002 0.000 0.565 0.001 pf:413(calc) >>>>>>> 1000 0.013 0.000 0.563 0.001 >>>>>>> relax_disp.py:908(func_CR72_full) >>>>>>> 1000 0.061 0.000 0.543 0.001 >>>>>>> relax_disp.py:456(calc_CR72_chi2) >>>>>>> 3003 0.294 0.000 0.400 0.000 cr72.py:100(r2eff_CR72) >>>>>>> 12036 0.100 0.000 0.100 0.000 {method 'reduce' of >>>>>>> 'numpy.ufunc' objects} >>>>>>> 3000 0.042 0.000 0.078 0.000 chi2.py:32(chi2) >>>>>>> 6003 0.011 0.000 0.072 0.000 fromnumeric.py:1621(sum) >>>>>>> 6003 0.008 0.000 0.055 0.000 _methods.py:23(_sum) >>>>>>> 3003 0.005 0.000 0.037 0.000 fromnumeric.py:2048(amax) >>>>>>> 3003 0.004 0.000 0.033 0.000 fromnumeric.py:2132(amin) >>>>>>> 3003 0.004 0.000 0.032 0.000 _methods.py:15(_amax) >>>>>>> 3003 0.004 0.000 0.029 0.000 _methods.py:19(_amin) >>>>>>> 6003 0.006 0.000 0.006 0.000 {isinstance} >>>>>>> >>>>>>> 100 spins: >>>>>>> 1 0.000 0.000 53.864 53.864 <string>:1(<module>) >>>>>>> 1 0.004 0.004 53.864 53.864 pf:449(cluster) >>>>>>> 1000 0.005 0.000 53.777 0.054 pf:413(calc) >>>>>>> 1000 0.022 0.000 53.772 0.054 >>>>>>> relax_disp.py:908(func_CR72_full) >>>>>>> 1000 6.340 0.006 53.735 0.054 >>>>>>> relax_disp.py:456(calc_CR72_chi2) >>>>>>> 300300 28.936 0.000 39.278 0.000 cr72.py:100(r2eff_CR72) >>>>>>> 1200927 9.811 0.000 9.811 0.000 {method 'reduce' of >>>>>>> 'numpy.ufunc' objects} >>>>>>> 300000 4.227 0.000 7.738 0.000 chi2.py:32(chi2) >>>>>>> 600300 1.047 0.000 7.051 0.000 fromnumeric.py:1621(sum) >>>>>>> 600300 0.752 0.000 5.434 0.000 _methods.py:23(_sum) >>>>>>> 300300 0.445 0.000 3.580 0.000 fromnumeric.py:2048(amax) >>>>>>> 300300 0.413 0.000 3.221 0.000 fromnumeric.py:2132(amin) >>>>>>> 300300 0.431 0.000 3.134 0.000 _methods.py:15(_amax) >>>>>>> 300300 0.383 0.000 2.808 0.000 _methods.py:19(_amin) >>>>>>> 600300 0.570 0.000 0.570 0.000 {isinstance} >>>>>>> >>>>>>> >>>>>>> ############################ >>>>>>> For tag 3.2.2 # >>>>>>> svn switch ^/tags/3.2.2 # >>>>>>> ############################ >>>>>>> >>>>>>> 1 spin: >>>>>>> 1 0.000 0.000 0.569 0.569 <string>:1(<module>) >>>>>>> 1 0.002 0.002 0.569 0.569 pf:427(single) >>>>>>> 1000 0.002 0.000 0.562 0.001 pf:413(calc) >>>>>>> 1000 0.005 0.000 0.560 0.001 >>>>>>> relax_disp.py:907(func_CR72_full) >>>>>>> 1000 0.062 0.000 0.555 0.001 >>>>>>> relax_disp.py:456(calc_CR72_chi2) >>>>>>> 3003 0.299 0.000 0.407 0.000 cr72.py:100(r2eff_CR72) >>>>>>> 12036 0.103 0.000 0.103 0.000 {method 'reduce' of >>>>>>> 'numpy.ufunc' objects} >>>>>>> 3000 0.044 0.000 0.082 0.000 chi2.py:32(chi2) >>>>>>> 6003 0.011 0.000 0.074 0.000 fromnumeric.py:1621(sum) >>>>>>> 6003 0.008 0.000 0.057 0.000 _methods.py:23(_sum) >>>>>>> 3003 0.005 0.000 0.037 0.000 fromnumeric.py:2048(amax) >>>>>>> 3003 0.004 0.000 0.034 0.000 fromnumeric.py:2132(amin) >>>>>>> 3003 0.004 0.000 0.033 0.000 _methods.py:15(_amax) >>>>>>> 3003 0.004 0.000 0.029 0.000 _methods.py:19(_amin) >>>>>>> 6003 0.006 0.000 0.006 0.000 {isinstance} >>>>>>> >>>>>>> 100 spins: >>>>>>> 1 0.000 0.000 53.987 53.987 <string>:1(<module>) >>>>>>> 1 0.004 0.004 53.987 53.987 pf:449(cluster) >>>>>>> 1000 0.004 0.000 53.907 0.054 pf:413(calc) >>>>>>> 1000 0.008 0.000 53.903 0.054 >>>>>>> relax_disp.py:907(func_CR72_full) >>>>>>> 1000 6.367 0.006 53.895 0.054 >>>>>>> relax_disp.py:456(calc_CR72_chi2) >>>>>>> 300300 28.870 0.000 39.278 0.000 cr72.py:100(r2eff_CR72) >>>>>>> 1200927 9.917 0.000 9.917 0.000 {method 'reduce' of >>>>>>> 'numpy.ufunc' objects} >>>>>>> 300000 4.283 0.000 7.853 0.000 chi2.py:32(chi2) >>>>>>> 600300 1.066 0.000 7.154 0.000 fromnumeric.py:1621(sum) >>>>>>> 600300 0.745 0.000 5.516 0.000 _methods.py:23(_sum) >>>>>>> 300300 0.447 0.000 3.565 0.000 fromnumeric.py:2048(amax) >>>>>>> 300300 0.417 0.000 3.259 0.000 fromnumeric.py:2132(amin) >>>>>>> 300300 0.422 0.000 3.118 0.000 _methods.py:15(_amax) >>>>>>> 300300 0.392 0.000 2.841 0.000 _methods.py:19(_amin) >>>>>>> 600300 0.572 0.000 0.572 0.000 {isinstance} >>>>>>> >>>>>>> ############################ >>>>>>> For tag 3.2.1 # >>>>>>> svn switch ^/tags/3.2.1 # >>>>>>> ############################ >>>>>>> 1 spin: >>>>>>> 1 0.000 0.000 1.021 1.021 <string>:1(<module>) >>>>>>> 1 0.002 0.002 1.021 1.021 pf:427(single) >>>>>>> 1000 0.002 0.000 1.014 0.001 pf:413(calc) >>>>>>> 1000 0.005 0.000 1.012 0.001 >>>>>>> relax_disp.py:907(func_CR72_full) >>>>>>> 1000 0.055 0.000 1.007 0.001 >>>>>>> relax_disp.py:456(calc_CR72_chi2) >>>>>>> 3003 0.861 0.000 0.864 0.000 cr72.py:98(r2eff_CR72) >>>>>>> 3000 0.043 0.000 0.084 0.000 chi2.py:32(chi2) >>>>>>> 3000 0.006 0.000 0.042 0.000 fromnumeric.py:1621(sum) >>>>>>> 3000 0.004 0.000 0.032 0.000 _methods.py:23(_sum) >>>>>>> 3027 0.028 0.000 0.028 0.000 {method 'reduce' of >>>>>>> 'numpy.ufunc' objects} >>>>>>> 8049 0.007 0.000 0.007 0.000 {range} >>>>>>> 1 0.000 0.000 0.006 0.006 pf:106(__init__) >>>>>>> 3 0.000 0.000 0.004 0.001 >>>>>>> numeric.py:1509(array_repr) >>>>>>> 3 0.000 0.000 0.004 0.001 >>>>>>> arrayprint.py:343(array2string) >>>>>>> 3 0.000 0.000 0.004 0.001 >>>>>>> arrayprint.py:233(_array2string) >>>>>>> 3000 0.004 0.000 0.004 0.000 {isinstance} >>>>>>> >>>>>>> 100 spins: >>>>>>> 1 0.000 0.000 104.086 104.086 <string>:1(<module>) >>>>>>> 1 0.004 0.004 104.086 104.086 pf:449(cluster) >>>>>>> 1000 0.004 0.000 103.944 0.104 pf:413(calc) >>>>>>> 1000 0.009 0.000 103.940 0.104 >>>>>>> relax_disp.py:907(func_CR72_full) >>>>>>> 1000 6.057 0.006 103.931 0.104 >>>>>>> relax_disp.py:456(calc_CR72_chi2) >>>>>>> 300300 88.604 0.000 88.888 0.000 cr72.py:98(r2eff_CR72) >>>>>>> 300000 4.408 0.000 8.695 0.000 chi2.py:32(chi2) >>>>>>> 300000 0.627 0.000 4.287 0.000 fromnumeric.py:1621(sum) >>>>>>> 300000 0.458 0.000 3.296 0.000 _methods.py:23(_sum) >>>>>>> 300027 2.839 0.000 2.839 0.000 {method 'reduce' of >>>>>>> 'numpy.ufunc' objects} >>>>>>> 703722 0.672 0.000 0.672 0.000 {range} >>>>>>> 300000 0.364 0.000 0.364 0.000 {isinstance} >>>>>>> 1 0.000 0.000 0.139 0.139 pf:106(__init__) >>>>>>> >>>>>>> >>>>>>> ################# System information ###################### >>>>>>> Processor fabric: Uni-processor. >>>>>>> >>>>>>> >>>>>>> Hardware information: >>>>>>> Machine: x86_64 >>>>>>> Processor: i386 >>>>>>> Processor name: Intel(R) Core(TM) i5-2435M CPU @ 2.40GHz >>>>>>> Endianness: little >>>>>>> Total RAM size: 2048.0 Mb >>>>>>> Total swap size: 6144.0 Mb >>>>>>> >>>>>>> Operating system information: >>>>>>> System: Darwin >>>>>>> Release: 13.2.0 >>>>>>> Version: Darwin Kernel Version 13.2.0: Thu Apr 17 >>>>>>> 23:03:13 PDT 2014; root:xnu-2422.100.13~1/RELEASE_X86_64 >>>>>>> Mac version: 10.9.3 (, , ) x86_64 >>>>>>> Distribution: >>>>>>> Full platform string: Darwin-13.2.0-x86_64-i386-64bit >>>>>>> >>>>>>> Python information: >>>>>>> Architecture: 64bit >>>>>>> Python version: 2.7.6 >>>>>>> Python branch: >>>>>>> Python build: default, Apr 11 2014 11:55:30 >>>>>>> Python compiler: GCC 4.2.1 (Apple Inc. build 5666) (dot 3) >>>>>>> Libc version: >>>>>>> Python implementation: CPython >>>>>>> Python revision: >>>>>>> Python executable: >>>>>>> /Users/tlinnet/Library/Enthought/Canopy_64bit/User/bin/python >>>>>>> Python flags: sys.flags(debug=0, py3k_warning=0, >>>>>>> division_warning=0, division_new=0, inspect=0, interactive=0, >>>>>>> optimize=0, dont_write_bytecode=0, no_user_site=0, no_site=0, >>>>>>> ignore_environment=0, tabcheck=0, verbose=0, unicode=0, >>>>>>> bytes_warning=0, hash_randomization=0) >>>>>>> Python float info: >>>>>>> sys.float_info(max=1.7976931348623157e+308, max_exp=1024, >>>>>>> max_10_exp=308, min=2.2250738585072014e-308, min_exp=-1021, >>>>>>> min_10_exp=-307, dig=15, mant_dig=53, epsilon=2.220446049250313e-16, >>>>>>> radix=2, rounds=1) >>>>>>> Python module path: ['/Users/tlinnet/software/relax_trunk', >>>>>>> '/Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python27.zip', >>>>>>> '/Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7', >>>>>>> '/Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/plat-darwin', >>>>>>> '/Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/plat-mac', >>>>>>> '/Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/plat-mac/lib-scriptpackages', >>>>>>> '/Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/lib-tk', >>>>>>> '/Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/lib-old', >>>>>>> '/Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/lib-dynload', >>>>>>> '/Users/tlinnet/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages', >>>>>>> '/Users/tlinnet/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/PIL', >>>>>>> '/Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/site-packages'] >>>>>>> >>>>>>> Python packages and modules (most are optional): >>>>>>> >>>>>>> Name Installed Version Path >>>>>>> minfx True 1.0.6 >>>>>>> /Users/tlinnet/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/minfx >>>>>>> bmrblib True 1.0.3 >>>>>>> /Users/tlinnet/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/bmrblib >>>>>>> numpy True 1.8.0 >>>>>>> /Users/tlinnet/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/numpy >>>>>>> scipy True 0.13.3 >>>>>>> /Users/tlinnet/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/scipy >>>>>>> wxPython True 2.9.2.4 osx-cocoa (classic) >>>>>>> /Users/tlinnet/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/wx >>>>>>> matplotlib True 1.3.1 >>>>>>> /Users/tlinnet/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/matplotlib >>>>>>> mpi4py False >>>>>>> epydoc True 3.0.1 >>>>>>> /Users/tlinnet/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/epydoc >>>>>>> optparse True 1.5.3 >>>>>>> /Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/optparse.pyc >>>>>>> readline True >>>>>>> /Users/tlinnet/Library/Enthought/Canopy_64bit/User/lib/python2.7/site-packages/readline.so >>>>>>> profile True >>>>>>> /Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/profile.pyc >>>>>>> bz2 True >>>>>>> /Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/lib-dynload/bz2.so >>>>>>> gzip True >>>>>>> /Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/gzip.pyc >>>>>>> io True >>>>>>> /Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/io.pyc >>>>>>> xml True 0.8.4 (internal) >>>>>>> /Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/xml/__init__.pyc >>>>>>> xml.dom.minidom True >>>>>>> /Applications/Canopy.app/appdata/canopy-1.4.0.1938.macosx-x86_64/Canopy.app/Contents/lib/python2.7/xml/dom/minidom.pyc >>>>>>> >>>>>>> relax information: >>>>>>> Version: repository checkout r23785 >>>>>>> svn+ssh://svn.gna.org/svn/relax/trunk >>>>>>> Processor fabric: Uni-processor. >>>>>>> >>>>>>> relax C modules: >>>>>>> >>>>>>> Module Compiled File type >>>>>>> Path >>>>>>> target_functions.relax_fit True 2-way ['Mach-O 64-bit bundle >>>>>>> x86_64', 'Mach-O bundle i386'] >>>>>>> /Users/tlinnet/software/relax_trunk/target_functions/relax_fit.so >>>>>>> >>>>>>> 2014-06-11 15:38 GMT+02:00 Troels Emtekær Linnet >>>>>>> <[email protected]>: >>>>>>>> Hi Ed. >>>>>>>> >>>>>>>> I am now faster than trunk per spin, even if I replaces the cr72.py >>>>>>>> file. >>>>>>>> >>>>>>>> 10000 iterations: >>>>>>>> >>>>>>>> BRANCH: >>>>>>>> 1 0.000 0.000 4.060 4.060 <string>:1(<module>) >>>>>>>> 1 0.016 0.016 4.060 4.060 pf:427(single) >>>>>>>> 10000 0.028 0.000 4.038 0.000 pf:413(calc) >>>>>>>> 10000 0.133 0.000 4.010 0.000 >>>>>>>> relax_disp.py:994(func_CR72_full) >>>>>>>> 10000 0.301 0.000 3.803 0.000 >>>>>>>> relax_disp.py:545(calc_CR72_chi2) >>>>>>>> 10003 1.629 0.000 2.862 0.000 cr72.py:101(r2eff_CR72) >>>>>>>> 70043 0.647 0.000 0.647 0.000 {method 'reduce' of >>>>>>>> 'numpy.ufunc' objects} >>>>>>>> 10000 0.042 0.000 0.572 0.000 >>>>>>>> core.py:1701(masked_where) >>>>>>>> 30006 0.061 0.000 0.395 0.000 fromnumeric.py:1621(sum) >>>>>>>> 30006 0.040 0.000 0.305 0.000 _methods.py:23(_sum) >>>>>>>> 10000 0.142 0.000 0.269 0.000 chi2.py:72(chi2_rankN) >>>>>>>> 30000 0.267 0.000 0.267 0.000 {method 'outer' of >>>>>>>> 'numpy.ufunc' objects} >>>>>>>> 10000 0.026 0.000 0.262 0.000 {method 'view' of >>>>>>>> 'numpy.ndarray' objects} >>>>>>>> 20006 0.032 0.000 0.250 0.000 fromnumeric.py:2132(amin) >>>>>>>> >>>>>>>> TRUNK, with new CR72. >>>>>>>> 1 0.000 0.000 6.585 6.585 <string>:1(<module>) >>>>>>>> 1 0.016 0.016 6.585 6.585 pf:427(single) >>>>>>>> 10000 0.026 0.000 6.562 0.001 pf:413(calc) >>>>>>>> 10000 0.133 0.000 6.536 0.001 >>>>>>>> relax_disp.py:908(func_CR72_full) >>>>>>>> 10000 0.601 0.000 6.327 0.001 >>>>>>>> relax_disp.py:456(calc_CR72_chi2) >>>>>>>> 30003 3.153 0.000 4.907 0.000 cr72.py:101(r2eff_CR72) >>>>>>>> 180042 1.356 0.000 1.356 0.000 {method 'reduce' of >>>>>>>> 'numpy.ufunc' objects} >>>>>>>> 90006 0.165 0.000 1.108 0.000 fromnumeric.py:1621(sum) >>>>>>>> 90006 0.109 0.000 0.792 0.000 _methods.py:23(_sum) >>>>>>>> 30000 0.423 0.000 0.775 0.000 chi2.py:32(chi2) >>>>>>>> 60006 0.096 0.000 0.647 0.000 fromnumeric.py:2132(amin) >>>>>>>> 60006 0.074 0.000 0.483 0.000 _methods.py:19(_amin) >>>>>>>> 30003 0.044 0.000 0.350 0.000 fromnumeric.py:2048(amax) >>>>>>>> >>>>>>>> TRUNK, with original CR72. >>>>>>>> 1 0.000 0.000 5.994 5.994 <string>:1(<module>) >>>>>>>> 1 0.018 0.018 5.994 5.994 pf:427(single) >>>>>>>> 10000 0.027 0.000 5.971 0.001 pf:413(calc) >>>>>>>> 10000 0.142 0.000 5.944 0.001 >>>>>>>> relax_disp.py:908(func_CR72_full) >>>>>>>> 10000 0.639 0.000 5.722 0.001 >>>>>>>> relax_disp.py:456(calc_CR72_chi2) >>>>>>>> 30003 3.093 0.000 4.205 0.000 cr72.py:100(r2eff_CR72) >>>>>>>> 120036 1.051 0.000 1.051 0.000 {method 'reduce' of >>>>>>>> 'numpy.ufunc' objects} >>>>>>>> 30000 0.455 0.000 0.830 0.000 chi2.py:32(chi2) >>>>>>>> 60003 0.113 0.000 0.755 0.000 fromnumeric.py:1621(sum) >>>>>>>> 60003 0.078 0.000 0.580 0.000 _methods.py:23(_sum) >>>>>>>> 30003 0.049 0.000 0.382 0.000 fromnumeric.py:2048(amax) >>>>>>>> 30003 0.048 0.000 0.350 0.000 fromnumeric.py:2132(amin) >>>>>>>> 30003 0.045 0.000 0.333 0.000 _methods.py:15(_amax) >>>>>>>> 30003 0.041 0.000 0.302 0.000 _methods.py:19(_amin) >>>>>>>> 60003 0.061 0.000 0.061 0.000 {isinstance} >>>>>>>> 20002 0.061 0.000 0.061 0.000 {method 'flatten' of >>>>>>>> 'numpy.ndarray' objects} >>>>>>>> 50046 0.048 0.000 0.048 0.000 {range} >>>>>>> >>>>>>> _______________________________________________ >>>>>>> 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
