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
