70 times faster is not bad at all! That's what different optimisation algorithms can give. Well the simplex to Newton change is a speed up of 6.97 (about one order of magnitude). You should also expect an order of difference in speed when changing algorithms for the relaxation dispersion models. However we do not have the gradients and Hessians derived and implemented for these yet. This would be a possible (distant) future target. However the Maple brute force expansion of numeric models would be far more time saving and may even be publishable as a note somewhere (again a distant future target).
Regards, Edward On 27 August 2014 11:49, <[email protected]> wrote: > Author: tlinnet > Date: Wed Aug 27 11:49:21 2014 > New Revision: 25331 > > URL: http://svn.gna.org/viewcvs/relax?rev=25331&view=rev > Log: > Modified profiling script to calculate timings. > > The timings for C-code are: > Simplex, with constraints = 2.192 > Simplex, without constraints = 0.216 > BFGS, without constraints = 0.079 > Newton, without constraints = 0.031 > > This is pretty pretty fast. > > To this profiling script, I would also now add some verification on > calculations. > > Profile, with constraints, C code, Simplex > Wed Aug 27 11:45:16 2014 > /var/folders/ww/1jkhkh315x57jglgxnr9g24w0000gp/T/tmpvJSNrB > > 724946 function calls (723444 primitive calls) in 2.192 seconds > > Ordered by: cumulative time > List reduced from 307 to 1 due to restriction <1> > > ncalls tottime percall cumtime percall filename:lineno(function) > 1 0.000 0.000 2.192 2.192 > profiling_relax_fit.py:314(verify) > > Verify, without constraints, C code, Simplex > Wed Aug 27 11:45:16 2014 > /var/folders/ww/1jkhkh315x57jglgxnr9g24w0000gp/T/tmphJ9GV3 > > 76042 function calls (74654 primitive calls) in 0.216 seconds > > Ordered by: cumulative time > List reduced from 132 to 1 due to restriction <1> > > ncalls tottime percall cumtime percall filename:lineno(function) > 1 0.000 0.000 0.216 0.216 > profiling_relax_fit.py:314(verify) > > Verify, without constraints, C code BFGS > Wed Aug 27 11:45:16 2014 > /var/folders/ww/1jkhkh315x57jglgxnr9g24w0000gp/T/tmp78MZjS > > 25618 function calls (24230 primitive calls) in 0.079 seconds > > Ordered by: cumulative time > List reduced from 153 to 1 due to restriction <1> > > ncalls tottime percall cumtime percall filename:lineno(function) > 1 0.000 0.000 0.079 0.079 > profiling_relax_fit.py:314(verify) > > Verify, without constraints, C code Newton > Wed Aug 27 11:45:16 2014 > /var/folders/ww/1jkhkh315x57jglgxnr9g24w0000gp/T/tmp2IPgFC > > 14572 function calls (13184 primitive calls) in 0.031 seconds > > Ordered by: cumulative time > List reduced from 169 to 1 due to restriction <1> > > ncalls tottime percall cumtime percall filename:lineno(function) > 1 0.000 0.000 0.031 0.031 > profiling_relax_fit.py:314(verify) > > Verify, with constraints, Python, Simplex > Wed Aug 27 11:45:20 2014 > /var/folders/ww/1jkhkh315x57jglgxnr9g24w0000gp/T/tmpQUUY4L > > 808444 function calls (806942 primitive calls) in 3.108 seconds > > Ordered by: cumulative time > List reduced from 141 to 1 due to restriction <1> > > ncalls tottime percall cumtime percall filename:lineno(function) > 1 0.000 0.000 3.108 3.108 > profiling_relax_fit.py:353(verify_pyt) > > Verify, without constraints, Python, Simplex > Wed Aug 27 11:45:20 2014 > /var/folders/ww/1jkhkh315x57jglgxnr9g24w0000gp/T/tmp3nFBTq > > 87492 function calls (86104 primitive calls) in 0.320 seconds > > Ordered by: cumulative time > List reduced from 131 to 1 due to restriction <1> > > ncalls tottime percall cumtime percall filename:lineno(function) > 1 0.000 0.000 0.320 0.320 > profiling_relax_fit.py:353(verify_pyt) > > Verify, without constraints, Python Scipy > Wed Aug 27 11:45:20 2014 > /var/folders/ww/1jkhkh315x57jglgxnr9g24w0000gp/T/tmpo1HoWn > > 6600 function calls (5212 primitive calls) in 0.020 seconds > > Ordered by: cumulative time > List reduced from 137 to 1 due to restriction <1> > > ncalls tottime percall cumtime percall filename:lineno(function) > 1 0.000 0.000 0.020 0.020 > profiling_relax_fit.py:388(verify_sci) > > task #7822(https://gna.org/task/index.php?7822): Implement user function to > estimate R2eff and associated errors for exponential curve fitting. > > Modified: > > trunk/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py > > Modified: > trunk/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py > URL: > http://svn.gna.org/viewcvs/relax/trunk/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py?rev=25331&r1=25330&r2=25331&view=diff > ============================================================================== > --- > trunk/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py > (original) > +++ > trunk/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py > Wed Aug 27 11:49:21 2014 > @@ -57,7 +57,8 @@ > # relax module imports. > from status import Status; status = Status() > from specific_analyses.relax_disp.estimate_r2eff import minimise_leastsq, Exp > -from target_functions.relax_fit import setup, func, dfunc, d2func, > back_calc_I > +from specific_analyses.relax_fit.optimisation import func_wrapper, > dfunc_wrapper, d2func_wrapper > +from target_functions.relax_fit import setup > from target_functions.chi2 import chi2_rankN > > ## Set the min_algor. > @@ -114,7 +115,7 @@ > print("C_cT=%1.1e C_cF=%1.1e P_cT=%1.1e P_cF=%1.1e" % > (chi_v_cT-chi_v_cT, chi_v_cF-chi_v_cT, chi_v_pyt_cT-chi_v_cT, > chi_v_pyt_cF-chi_v_cT) ) > > # Do verification for Python code, and difference between minfx and > Scipy optimisation without constraints. > - if True: > + if False: > # Calculate with Python code. > # Calculate without contraints. > v_pyt_cF_chi2_list = array(verify_pyt(constraints=False)) > @@ -132,10 +133,12 @@ > print("P_cF=%1.1e Sci_cF=%1.1e" % (chi_v_pyt_cF-chi_v_pyt_cF, > chi_v_pyt_cF-chi_v_sci_cF) ) > > # Do profiling. > - > if True: > - ################# > - print("Verify, with constraints, C code") > + print("\n################################# Profiling > #################################") > + > + > + ################# > + print("#####################\nProfile, with constraints, C code, > Simplex \n#####################") > constraints = True > > # Print statistics. > @@ -148,9 +151,8 @@ > > print_report(filename=filename, verbose=verbose) > > - if True: > - ################# > - print("Verify, without constraints, C code") > + ################# > + print("#####################\n Verify, without constraints, C code, > Simplex \n#####################") > constraints = False > > # Print statistics. > @@ -163,9 +165,8 @@ > > print_report(filename=filename, verbose=verbose) > > - if True: > - ################# > - print("Verify, without constraints, C code BFGS") > + ################# > + print("#####################\n Verify, without constraints, C code > BFGS \n#####################") > constraints = False > > # Print statistics. > @@ -178,9 +179,24 @@ > > print_report(filename=filename, verbose=verbose) > > - if False: > - ################# > - print("Verify, with constraints, Python") > + > + ################# > + print("#####################\n Verify, without constraints, C code > Newton \n#####################") > + constraints = False > + > + # Print statistics. > + verbose = True > + > + # Calc for verify with constraints. > + filename = tempfile.NamedTemporaryFile(delete=False).name > + # Profile for a single spin. > + cProfile.run('verify(min_algor="Newton", > constraints=%s)'%(constraints), filename) > + > + print_report(filename=filename, verbose=verbose) > + > + > + ################# > + print("#####################\n Verify, with constraints, Python, > Simplex \n#####################") > constraints = True > > # Print statistics. > @@ -193,9 +209,8 @@ > > print_report(filename=filename, verbose=verbose) > > - if False: > - ################# > - print("Verify, without constraints, Python") > + ################# > + print("#####################\n Verify, without constraints, Python, > Simplex \n#####################") > constraints = False > > # Print statistics. > @@ -208,9 +223,8 @@ > > print_report(filename=filename, verbose=verbose) > > - if True: > - ################# > - print("Verify, without constraints, Python Scipy") > + ################# > + print("#####################\n Verify, without constraints, Python > Scipy \n#####################") > > # Print statistics. > verbose = True > @@ -316,6 +330,11 @@ > > E.set_settings_minfx(min_algor=min_algor, constraints=constraints) > > + # Define func. > + func = func_wrapper > + dfunc = dfunc_wrapper > + d2func = d2func_wrapper > + > # Initialise the function to minimise. > scaling_list = [1.0, 1.0] > setup(num_params=len(x0), num_times=len(E.times), values=E.values, > sd=E.errors, relax_times=E.times, scaling_matrix=scaling_list) > @@ -353,6 +372,7 @@ > # Define func. > func = E.func_exp > dfunc = E.func_exp_grad > + d2func = None > > results = generic_minimise(func=func, dfunc=dfunc, d2func=d2func, > args=(), x0=x0, min_algor=E.min_algor, min_options=E.min_options, > func_tol=E.func_tol, grad_tol=E.grad_tol, maxiter=E.max_iterations, A=E.A, > b=E.b, full_output=True, print_flag=E.verbosity) > > > > _______________________________________________ > 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
