Re: I am now faster than trunk per spin calc. -- June 11, 2014

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 <tlinnet@xxxxxxxxxxxxx>:

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 <edward@xxxxxxxxxxxxx>:

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 <tlinnet@xxxxxxxxxxxxx> 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 <edward@xxxxxxxxxxxxx>:

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 <edward@xxxxxxxxxxxxx> wrote:

You wait until you see what happens with your multiple offset R1rho 
data ;)

On 11 June 2014 15:42, Troels Emtekær Linnet <tlinnet@xxxxxxxxxxxxx> 
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 
<tlinnet@xxxxxxxxxxxxx>:

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}


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Re: I am now faster than trunk per spin calc.

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