~madteam/mg5amcnlo/series2.0 : revision 289

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#

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################################################################################

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from __future__ import division

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from __future__ import absolute_import

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import os

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import math

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import logging

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import re

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import xml.dom.minidom as minidom

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from six.moves import range

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logger = logging.getLogger('madevent.stdout') # -> stdout

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new_stats = [new_stats, ]

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elif isinstance(new_stats,list):

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if any(not isinstance(_,RunStatistics) for _ in new_stats):

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raise MadGraph5Error, "The 'new_stats' argument of the function "+\

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raise MadGraph5Error("The 'new_stats' argument of the function "+\

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"'updtate_statistics' must be a (possibly list of) "+\

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"RunStatistics instance."

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"RunStatistics instance.")

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keys = set([])

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for stat in [self,]+new_stats:

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elif isinstance(filepath, file):

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finput = filepath

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else:

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raise Exception, "filepath should be a path or a file descriptor"

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raise Exception("filepath should be a path or a file descriptor")

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i=0

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found_xsec_line = False

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if 'end code not correct' in line:

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error_code = data[4]

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log = pjoin(os.path.dirname(filepath), 'log.txt')

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raise Exception, "Reported error: End code %s \n Full associated log: \n%s"\

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% (error_code, open(log).read())

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raise Exception("Reported error: End code %s \n Full associated log: \n%s"\

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% (error_code, open(log).read()))

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else:

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log = pjoin(os.path.dirname(filepath), 'log.txt')

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raise Exception, "Wrong formatting in results.dat: %s \n Full associated log: \n%s"\

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% (line, open(log).read())

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raise Exception("Wrong formatting in results.dat: %s \n Full associated log: \n%s"\

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% (line, open(log).read()))

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if len(data) > 10:

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self.maxwgt = data[10]

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if len(data) >12:

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if statistics_node:

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try:

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self.run_statistics.load_statistics(statistics_node[0])

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except ValueError, IndexError:

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except ValueError as IndexError:

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logger.warning('Fail to read run statistics from results.dat')

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def set_mfactor(self, value):

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"""Compute iterations to have a chi-square on the stability of the

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integral"""

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nb_iter = min([len(a.ysec_iter) for a in self], 0)

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#iter = [len(a.ysec_iter) for a in self]

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#if iter:

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# nb_iter = min(iter)

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#else:

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# nb_iter = 0

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#nb_iter = misc.mmin([len(a.ysec_iter) for a in self], 0)

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#misc.sprint(nb_iter)

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# syncronize all iterations to a single one

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for oneresult in self:

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oneresult.change_iterations_number(nb_iter)

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oneresult.change_iterations_number(0)

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# compute value error for each iteration

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for i in range(nb_iter):

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value = [one.ysec_iter[i] for one in self]

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error = [one.yerr_iter[i]**2 for one in self]

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# store the value for the iteration

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self.ysec_iter.append(sum(value))

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self.yerr_iter.append(math.sqrt(sum(error)))

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#for i in range(nb_iter):

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# value = [one.ysec_iter[i] for one in self]

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# error = [one.yerr_iter[i]**2 for one in self]

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#

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# # store the value for the iteration

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# raise Exception

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# self.ysec_iter.append(sum(value))

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# self.yerr_iter.append(math.sqrt(sum(error)))

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template_file = \

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P_comb = Combine_results(Pdir)

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if jobs:

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for job in filter(lambda j: j['p_dir'] in Pdir, jobs):

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for job in [j for j in jobs if j['p_dir'] in Pdir]:

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P_comb.add_results(os.path.basename(job['dirname']),\

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pjoin(job['dirname'],'results.dat'))

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elif folder_names:

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dir = folder.replace('*', '_G' + name)

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P_comb.add_results(dir, pjoin(Pdir,dir,'results.dat'), mfactor)

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if jobs:

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for job in filter(lambda j: j['p_dir'] == Pdir, jobs):

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for job in [j for j in jobs if j['p_dir'] == Pdir]:

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P_comb.add_results(os.path.basename(job['dirname']),\

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pjoin(job['dirname'],'results.dat'))

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except IOError:

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else:

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path = pjoin(G,'results.dat')

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P_comb.add_results(os.path.basename(G), path, mfactors[G])

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P_comb.compute_values()

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all.append(P_comb)

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all.compute_values()