Author: tlinnet
Date: Fri Aug 22 19:17:19 2014
New Revision: 25227
URL: http://svn.gna.org/viewcvs/relax?rev=25227&view=rev
Log:
Further extended the profiling script for curve fitting.
Now profiling is in place for the implemented C code method in relax.
A similar code should now be devised for numpy array for comparing.
But this profiling shows that when contraints=True, is slowing down this
procedure by a factor 10 X !
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=25227&r1=25226&r2=25227&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
Fri Aug 22 19:17:19 2014
@@ -24,10 +24,11 @@
# Python module imports.
import cProfile
from os import getcwd, path, sep
-from numpy import array, arange, int32, float64, pi, load
+from numpy import array, arange, int32, float64, pi, load, sqrt, sum
import pstats
import sys
import tempfile
+from minfx.generic import generic_minimise
# Python 3 support.
try:
@@ -52,46 +53,171 @@
# relax module imports.
from status import Status; status = Status()
+from target_functions.relax_fit import setup, func, dfunc, d2func,
back_calc_I
# Alter setup.
def main():
- param_key_list = [
- 'r1rho_799.77739910_118.078_431.000',
- 'r1rho_799.77739910_118.078_651.200',
- 'r1rho_799.77739910_118.078_800.500',
- 'r1rho_799.77739910_118.078_984.000',
- 'r1rho_799.77739910_118.078_1341.110',
- 'r1rho_799.77739910_118.078_1648.500',
- 'r1rho_799.77739910_124.247_1341.110',
- 'r1rho_799.77739910_130.416_800.500',
- 'r1rho_799.77739910_130.416_1341.110',
- 'r1rho_799.77739910_130.416_1648.500',
- 'r1rho_799.77739910_142.754_800.500',
- 'r1rho_799.77739910_142.754_1341.110',
- 'r1rho_799.77739910_179.768_1341.110',
- 'r1rho_799.77739910_241.459_1341.110'
- ]
-
- # Define maximum dimensions.
- NE, NS, NM, NO, ND, NT = 1, 1, 1, 6, 6, 5
-
- # Define path to data
- data_path = status.install_path +
sep+'test_suite'+sep+'shared_data'+sep+'curve_fitting'+sep+'profiling'+sep
-
- values_arr = load(data_path + "values_arr.npy")
- errors_arr = load(data_path + "errors_arr.npy")
- times_arr = load(data_path + "times_arr.npy")
- struct_arr = load(data_path + "struct_arr.npy")
+ v_cT_chi2_list = array(verify(constraints=True))
+ v_cF_chi2_list = array(verify(constraints=False))
+
+ sum_root_squared = sum( sqrt( (v_cT_chi2_list - v_cF_chi2_list)**2 ) )
+ print("The sum of the root squared differences are: %.3e" %
sum_root_squared)
+
+ lines_report = 15
+
+ if True:
+ #################
+ # Verify, with constraints
+ constraints = True
+
+ # Print statistics.
+ verbose = True
+
+ # Calc for verify with constraints.
+ v_cT_filename = tempfile.NamedTemporaryFile(delete=False).name
+ # Profile for a single spin.
+ cProfile.run('verify(constraints=%s)'%constraints, v_cT_filename)
+
+ # Read all stats files into a single object
+ v_cT_stats = pstats.Stats(v_cT_filename)
+
+ # Clean up filenames for the report
+ v_cT_stats.strip_dirs()
+
+ # Sort the statistics by the cumulative time spent in the
function. cumulative, time, calls
+ v_cT_stats.sort_stats('cumulative')
+
+ # Print report for single.
+ if verbose:
+ v_cT_stats.print_stats(lines_report)
+
+ if True:
+ #################
+ # Verify, without constraints
+ constraints = False
+
+ # Print statistics.
+ verbose = True
+
+ # Calc for verify with constraints.
+ v_cF_filename = tempfile.NamedTemporaryFile(delete=False).name
+ # Profile for a single spin.
+ cProfile.run('verify(constraints=%s)'%constraints, v_cF_filename)
+
+ # Read all stats files into a single object
+ v_cF_stats = pstats.Stats(v_cF_filename)
+
+ # Clean up filenames for the report
+ v_cF_stats.strip_dirs()
+
+ # Sort the statistics by the cumulative time spent in the
function. cumulative, time, calls
+ v_cF_stats.sort_stats('cumulative')
+
+ # Print report for single.
+ if verbose:
+ v_cF_stats.print_stats(lines_report)
+
+
+class Profile:
+ """
+ Class Profile inherits the Dispersion container class object.
+ """
+
+ def __init__(self):
+
+ # Define parameters
+ self.param_key_list = [
+ 'r1rho_799.77739910_118.078_431.000',
+ 'r1rho_799.77739910_118.078_651.200',
+ 'r1rho_799.77739910_118.078_800.500',
+ 'r1rho_799.77739910_118.078_984.000',
+ 'r1rho_799.77739910_118.078_1341.110',
+ 'r1rho_799.77739910_118.078_1648.500',
+ 'r1rho_799.77739910_124.247_1341.110',
+ 'r1rho_799.77739910_130.416_800.500',
+ 'r1rho_799.77739910_130.416_1341.110',
+ 'r1rho_799.77739910_130.416_1648.500',
+ 'r1rho_799.77739910_142.754_800.500',
+ 'r1rho_799.77739910_142.754_1341.110',
+ 'r1rho_799.77739910_179.768_1341.110',
+ 'r1rho_799.77739910_241.459_1341.110'
+ ]
+
+ # Define maximum dimensions.
+ self.NE, self.NS, self.NM, self.NO, self.ND, self.NT = 1, 1, 1, 6,
6, 5
+
+ # Define path to data
+ self.data_path = status.install_path +
sep+'test_suite'+sep+'shared_data'+sep+'curve_fitting'+sep+'profiling'+sep
+
+ self.values_arr = load(self.data_path + "values_arr.npy")
+ self.errors_arr = load(self.data_path + "errors_arr.npy")
+ self.times_arr = load(self.data_path + "times_arr.npy")
+ self.struct_arr = load(self.data_path + "struct_arr.npy")
+
+ #param_vector = array([ 0., 0.])
+ self.param_vector = array([ 8.800000000000001e+00,
2.000000000800000e+05])
+ self.scaling_list = [1.0, 1.0]
+ self.func_tol = 1e-25
+ self.grad_tol = None
+ self.max_iterations = 10000000
+ self.verbosity = 0
+
+ def set_options(self, constraints=None):
+ # Define which constraints should be used.
+ self.constraints = constraints
+
+ if self.constraints:
+ self.min_algor = 'Log barrier'
+ self.min_options = ('simplex',)
+ self.A = array([ [ 1., 0.],
+ [-1., 0.],
+ [ 0., 1.]] )
+ self.b = array([ 0., -200., 0.])
+
+ else:
+ self.min_algor = 'simplex'
+ self.min_options = ()
+ self.A = None
+ self.b = None
+
+
+def verify(constraints=None):
+ # Instantiate class.
+ C = Profile()
+
+ # Set the minimising options.
+ C.set_options(constraints=constraints)
+
+ chi2_list = []
# Print arrays.
- for ei in range(NE):
- for si in range(NS):
- for mi in range(NM):
- for oi in range(NO):
- for di in range(ND):
- print(ei, si, mi, oi, di, values_arr[ei, si, mi,
oi, di], struct_arr[ei, si, mi, oi, di])
-
+ for ei in range(C.NE):
+ for si in range(C.NS):
+ for mi in range(C.NM):
+ for oi in range(C.NO):
+ for di in range(C.ND):
+ # Extract values
+ values = C.values_arr[ei, si, mi, oi, di]
+ errors = C.errors_arr[ei, si, mi, oi, di]
+ times = C.times_arr[ei, si, mi, oi, di]
+ struct = C.struct_arr[ei, si, mi, oi, di]
+ num_times = int( sum(struct) )
+
+ if num_times == 0:
+ continue
+
+ # Initialise the function to minimise.
+ setup(num_params=len(C.param_vector),
num_times=num_times, values=values, sd=errors, relax_times=times,
scaling_matrix=C.scaling_list)
+
+ results = generic_minimise(func=func, dfunc=dfunc,
d2func=d2func, args=(), x0=C.param_vector, min_algor=C.min_algor,
min_options=C.min_options, func_tol=C.func_tol, grad_tol=C.grad_tol,
maxiter=C.max_iterations, A=C.A, b=C.b, full_output=True,
print_flag=C.verbosity)
+
+ # Unpack
+ param_vector, chi2, iter_count, f_count, g_count,
h_count, warning = results
+
+ chi2_list.append(chi2)
+
+ return chi2_list
# Execute main function.
if __name__ == "__main__":
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Re: r25227 - /trunk/test_suite/shared_data/curve_fitting/profiling/profiling_relax_fit.py