Hi Edward. How about this script? Here I try to pass the back the r2eff values, and then set them in the back_calculated class object. Will this work ??
Or else I found this post about updating values. http://stackoverflow.com/questions/14916284/in-python-class-object-how-to-auto-update-attributes They talk about @property and setter, which I dont get yet. :-) Best Troels --------------- def loop_rep(x, nr): y = [98, 99] for i in range(nr): x[i] = y[i] def not_loop_rep(x, nr): y = [98, 99] x = y def not_loop_rep_new(x, nr): y = [98, 99] x = y return x class MyClass: def __init__(self, x): self.x = x self.nr = len(x) def printc(self): print self.x, self.nr def calc_loop_rep(self, x=None, nr=None): loop_rep(x=self.x, nr=self.nr) def calc_not_loop_rep(self, x=None, nr=None): not_loop_rep(x=self.x, nr=self.nr) def calc_not_loop_rep_new(self, x=None, nr=None): self.x = not_loop_rep_new(x=self.x, nr=self.nr) print("For class where we loop replace ") "Create object of class" t_rep = MyClass([0, 1]) "Print object of class" t_rep.printc() "Calc object of class" t_rep.calc_loop_rep() " Then print" t_rep.printc() print("\nFor class where we not loop replace ") " Now try with replace " t = MyClass([3, 4]) t.printc() t.calc_not_loop_rep() t.printc() print("\nFor class where we not loop replace ") t_new = MyClass([5, 6]) t_new.printc() t_new.calc_not_loop_rep_new() t_new.printc() 2014-05-05 19:07 GMT+02:00 Edward d'Auvergne <[email protected]>: > :) It does slow it down a little, but that's unavoidable. It's also > unavoidable in C, Fortran, Perl, etc. As long as the number of > operations in that loop is minimal, then it's the best you can do. If > it worries you, you could run a test where you call the target > function say 1e6 times, with and without the loop to see the timing > difference. Or simply running in Python 2: > > for i in xrange(1000000): > x = 1 > > Then try: > > for i in xrange(100000000): > x = 2 > > These two demonstrate the slowness of the Python loop. But the second > case is extreme and you won't encounter that much looping in these > functions. So while it is theoretically slower than C and Fortran > looping, you can probably see that no one would care :) Here is > another test, with Python 2 code: > > """ > import cProfile as profile > > def loop_1e6(): > for i in xrange(int(1e6)): > x = 1 > > def loop_1e8(): > for i in xrange(int(1e8)): > x = 1 > > def sum_conv(): > for i in xrange(100000000): > x = 2 + 2. > > def sum_normal(): > for i in xrange(100000000): > x = 2. + 2. > > def test(): > loop_1e6() > loop_1e8() > sum_normal() > sum_conv() > > profile.runctx('test()', globals(), locals()) > """ > > Running this on my system shows: > > """ > 7 function calls in 6.707 seconds > > Ordered by: standard name > > ncalls tottime percall cumtime percall filename:lineno(function) > 1 0.000 0.000 6.707 6.707 <string>:1(<module>) > 1 2.228 2.228 2.228 2.228 aaa.py:11(sum_conv) > 1 2.228 2.228 2.228 2.228 aaa.py:15(sum_normal) > 1 0.000 0.000 6.707 6.707 aaa.py:19(test) > 1 0.022 0.022 0.022 0.022 aaa.py:3(loop_1e6) > 1 2.228 2.228 2.228 2.228 aaa.py:7(loop_1e8) > 1 0.000 0.000 0.000 0.000 {method 'disable' of > '_lsprof.Profiler' objects} > """ > > That should be self explanatory. The better optimisation targets are > the repeated maths operations and the maths operations that can be > shifted into the target function or the target function > initialisation. Despite the numbers above which prove my int to float > speed argument as utter nonsense, it might still good to remove the > int to float conversions, if only to match the other functions. > > Regards, > > Edward > > > > > On 5 May 2014 18:45, Troels Emtekær Linnet <[email protected]> wrote: >> The reason why I ask, is that I am afraid that this for loop slows >> everything down. >> >> What do you think? >> >> 2014-05-05 18:41 GMT+02:00 Edward d'Auvergne <[email protected]>: >>> This is not Python specific though :) As far as I know, C uses >>> pass-by-value for arguments, unless they are arrays or other funky >>> objects/functions/etc.. This is the same behaviour as Python. >>> Pass-by-reference and pass-by-value is something that needs to be >>> mastered in all languages, whether or not you have pointers to play >>> with. >>> >>> Regards, >>> >>> Edward >>> >>> >>> >>> On 5 May 2014 18:30, Troels Emtekær Linnet <[email protected]> wrote: >>>> This reminds me: >>>> >>>> http://combichem.blogspot.dk/2013/08/you-know-what-really-grinds-my-gears-in.html >>>> >>>> 2014-05-05 17:52 GMT+02:00 Edward d'Auvergne <[email protected]>: >>>>> Hi, >>>>> >>>>> This is an important difference. In the first case (back_calc[i] = >>>>> Minty[i]), what is happening is that your are copying the data into a >>>>> pre-existing structure. In the second case (back_calc = Minty), the >>>>> existing back_calc structure will be overwritten. Therefore the >>>>> back_calc structure in the calling code will be modified in the first >>>>> case but not the second. Here is some demo code: >>>>> >>>>> def mod1(x): >>>>> x[0] = 1 >>>>> >>>>> def mod2(x): >>>>> x = [3, 2] >>>>> >>>>> x = [0, 2] >>>>> print(x) >>>>> mod1(x) >>>>> print(x) >>>>> mod2(x) >>>>> print(x) >>>>> >>>>> I don't know of a way around this. >>>>> >>>>> Regards, >>>>> >>>>> Edward >>>>> >>>>> >>>>> On 5 May 2014 17:42, Troels Emtekær Linnet <[email protected]> wrote: >>>>>> Hi Edward. >>>>>> >>>>>> In the library function of b14.py, i am looping over >>>>>> the dispersion points to put in the data. >>>>>> >>>>>> for i in range(num_points): >>>>>> >>>>>> # The full formula. >>>>>> back_calc[i] = Minty[i] >>>>>> >>>>>> Why can I not just set: >>>>>> back_calc = Minty >>>>>> >>>>>> _______________________________________________ >>>>>> 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
