Package madgraph :: Package madevent :: Module sum_html
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Source Code for Module madgraph.madevent.sum_html

  1  ################################################################################ 
  2  # 
  3  # Copyright (c) 2011 The MadGraph5_aMC@NLO Development team and Contributors 
  4  # 
  5  # This file is a part of the MadGraph5_aMC@NLO project, an application which  
  6  # automatically generates Feynman diagrams and matrix elements for arbitrary 
  7  # high-energy processes in the Standard Model and beyond. 
  8  # 
  9  # It is subject to the MadGraph5_aMC@NLO license which should accompany this  
 10  # distribution. 
 11  # 
 12  # For more information, visit madgraph.phys.ucl.ac.be and amcatnlo.web.cern.ch 
 13  # 
 14  ################################################################################ 
 15  from __future__ import division 
 16  import os 
 17  import math 
 18  import logging 
 19  import re 
 20  import xml.dom.minidom as minidom 
 21   
 22  logger = logging.getLogger('madevent.stdout') # -> stdout 
 23   
 24  pjoin = os.path.join 
 25  try: 
 26      import madgraph 
 27  except ImportError: 
 28      import internal.cluster as cluster 
 29      import internal.misc as misc 
 30      from internal import MadGraph5Error 
 31  else: 
 32      import madgraph.various.cluster as cluster 
 33      import madgraph.various.misc as misc 
 34      from madgraph import MadGraph5Error 
 35   
36 -class RunStatistics(dict):
37 """ A class to store statistics about a MadEvent run. """ 38
39 - def __init__(self, *args, **opts):
40 """ Initialize the run dictionary. For now, the same as a regular 41 dictionary, except that we specify some default statistics. """ 42 43 madloop_statistics = { 44 'unknown_stability' : 0, 45 'stable_points' : 0, 46 'unstable_points' : 0, 47 'exceptional_points' : 0, 48 'DP_usage' : 0, 49 'QP_usage' : 0, 50 'DP_init_usage' : 0, 51 'QP_init_usage' : 0, 52 'CutTools_DP_usage' : 0, 53 'CutTools_QP_usage' : 0, 54 'PJFry_usage' : 0, 55 'Golem_usage' : 0, 56 'IREGI_usage' : 0, 57 'Samurai_usage' : 0, 58 'Ninja_usage' : 0, 59 'Ninja_QP_usage' : 0, 60 'max_precision' : 1.0e99, 61 'min_precision' : 0.0, 62 'averaged_timing' : 0.0, 63 'n_madloop_calls' : 0, 64 'cumulative_timing' : 0.0, 65 'skipped_subchannel' : 0 # number of times that a computation have been 66 # discarded due to abnormal weight. 67 } 68 69 for key, value in madloop_statistics.items(): 70 self[key] = value 71 72 super(dict,self).__init__(*args, **opts)
73
74 - def aggregate_statistics(self, new_stats):
75 """ Update the current statitistics with the new_stats specified.""" 76 77 if isinstance(new_stats,RunStatistics): 78 new_stats = [new_stats, ] 79 elif isinstance(new_stats,list): 80 if any(not isinstance(_,RunStatistics) for _ in new_stats): 81 raise MadGraph5Error, "The 'new_stats' argument of the function "+\ 82 "'updtate_statistics' must be a (possibly list of) "+\ 83 "RunStatistics instance." 84 85 keys = set([]) 86 for stat in [self,]+new_stats: 87 keys |= set(stat.keys()) 88 89 new_stats = new_stats+[self,] 90 for key in keys: 91 # Define special rules 92 if key=='max_precision': 93 # The minimal precision corresponds to the maximal value for PREC 94 self[key] = min( _[key] for _ in new_stats if key in _) 95 elif key=='min_precision': 96 # The maximal precision corresponds to the minimal value for PREC 97 self[key] = max( _[key] for _ in new_stats if key in _) 98 elif key=='averaged_timing': 99 n_madloop_calls = sum(_['n_madloop_calls'] for _ in new_stats if 100 'n_madloop_calls' in _) 101 if n_madloop_calls > 0 : 102 self[key] = sum(_[key]*_['n_madloop_calls'] for _ in 103 new_stats if (key in _ and 'n_madloop_calls' in _) )/n_madloop_calls 104 else: 105 # Now assume all other quantities are cumulative 106 self[key] = sum(_[key] for _ in new_stats if key in _)
107
108 - def load_statistics(self, xml_node):
109 """ Load the statistics from an xml node. """ 110 111 def getData(Node): 112 return Node.childNodes[0].data
113 114 u_return_code = xml_node.getElementsByTagName('u_return_code') 115 u_codes = [int(_) for _ in getData(u_return_code[0]).split(',')] 116 self['CutTools_DP_usage'] = u_codes[1] 117 self['PJFry_usage'] = u_codes[2] 118 self['IREGI_usage'] = u_codes[3] 119 self['Golem_usage'] = u_codes[4] 120 self['Samurai_usage'] = u_codes[5] 121 self['Ninja_usage'] = u_codes[6] 122 self['Ninja_QP_usage'] = u_codes[8] 123 self['CutTools_QP_usage'] = u_codes[9] 124 t_return_code = xml_node.getElementsByTagName('t_return_code') 125 t_codes = [int(_) for _ in getData(t_return_code[0]).split(',')] 126 self['DP_usage'] = t_codes[1] 127 self['QP_usage'] = t_codes[2] 128 self['DP_init_usage'] = t_codes[3] 129 self['DP_init_usage'] = t_codes[4] 130 h_return_code = xml_node.getElementsByTagName('h_return_code') 131 h_codes = [int(_) for _ in getData(h_return_code[0]).split(',')] 132 self['unknown_stability'] = h_codes[1] 133 self['stable_points'] = h_codes[2] 134 self['unstable_points'] = h_codes[3] 135 self['exceptional_points'] = h_codes[4] 136 average_time = xml_node.getElementsByTagName('average_time') 137 avg_time = float(getData(average_time[0])) 138 self['averaged_timing'] = avg_time 139 cumulated_time = xml_node.getElementsByTagName('cumulated_time') 140 cumul_time = float(getData(cumulated_time[0])) 141 self['cumulative_timing'] = cumul_time 142 max_prec = xml_node.getElementsByTagName('max_prec') 143 max_prec = float(getData(max_prec[0])) 144 # The minimal precision corresponds to the maximal value for PREC 145 self['min_precision'] = max_prec 146 min_prec = xml_node.getElementsByTagName('min_prec') 147 min_prec = float(getData(min_prec[0])) 148 # The maximal precision corresponds to the minimal value for PREC 149 self['max_precision'] = min_prec 150 n_evals = xml_node.getElementsByTagName('n_evals') 151 n_evals = int(getData(n_evals[0])) 152 self['n_madloop_calls'] = n_evals
153
154 - def nice_output(self,G, no_warning=False):
155 """Returns a one-line string summarizing the run statistics 156 gathered for the channel G.""" 157 158 # Do not return anythign for now if there is no madloop calls. This can 159 # change of course if more statistics are gathered, unrelated to MadLoop. 160 if self['n_madloop_calls']==0: 161 return '' 162 163 stability = [ 164 ('tot#',self['n_madloop_calls']), 165 ('unkwn#',self['unknown_stability']), 166 ('UPS%',float(self['unstable_points'])/self['n_madloop_calls']), 167 ('EPS#',self['exceptional_points'])] 168 169 stability = [_ for _ in stability if _[1] > 0 or _[0] in ['UPS%','EPS#']] 170 stability = [(_[0],'%i'%_[1]) if isinstance(_[1], int) else 171 (_[0],'%.3g'%(100.0*_[1])) for _ in stability] 172 173 tools_used = [ 174 ('CT_DP',float(self['CutTools_DP_usage'])/self['n_madloop_calls']), 175 ('CT_QP',float(self['CutTools_QP_usage'])/self['n_madloop_calls']), 176 ('PJFry',float(self['PJFry_usage'])/self['n_madloop_calls']), 177 ('Golem',float(self['Golem_usage'])/self['n_madloop_calls']), 178 ('IREGI',float(self['IREGI_usage'])/self['n_madloop_calls']), 179 ('Samurai',float(self['Samurai_usage'])/self['n_madloop_calls']), 180 ('Ninja_DP',float(self['Ninja_usage'])/self['n_madloop_calls']), 181 ('Ninja_QP',float(self['Ninja_QP_usage'])/self['n_madloop_calls'])] 182 183 tools_used = [(_[0],'%.3g'%(100.0*_[1])) for _ in tools_used if _[1] > 0.0 ] 184 185 to_print = [('%s statistics:'%(G if isinstance(G,str) else 186 str(os.path.join(list(G))))\ 187 +(' %s,'%misc.format_time(int(self['cumulative_timing'])) if 188 int(self['cumulative_timing']) > 0 else '') 189 +((' Avg. ML timing = %i ms'%int(1.0e3*self['averaged_timing'])) if 190 self['averaged_timing'] > 0.001 else 191 (' Avg. ML timing = %i mus'%int(1.0e6*self['averaged_timing']))) \ 192 +', Min precision = %.2e'%self['min_precision']) 193 ,' -> Stability %s'%dict(stability) 194 ,' -> Red. tools usage in %% %s'%dict(tools_used) 195 # I like the display above better after all 196 # ,'Stability %s'%(str([_[0] for _ in stability]), 197 # str([_[1] for _ in stability])) 198 # ,'Red. tools usage in %% %s'%(str([_[0] for _ in tools_used]), 199 # str([_[1] for _ in tools_used])) 200 ] 201 202 if self['skipped_subchannel'] > 0 and not no_warning: 203 to_print.append("WARNING: Some event with large weight have been "+\ 204 "discarded. This happened %s times." % self['skipped_subchannel']) 205 206 return ('\n'.join(to_print)).replace("'"," ")
207
208 - def has_warning(self):
209 """return if any stat needs to be reported as a warning 210 When this is True, the print_warning doit retourner un warning 211 """ 212 213 if self['n_madloop_calls'] > 0: 214 fraction = self['exceptional_points']/float(self['n_madloop_calls']) 215 else: 216 fraction = 0.0 217 218 if self['skipped_subchannel'] > 0: 219 return True 220 elif fraction > 1.0e-4: 221 return True 222 else: 223 return False
224
225 - def get_warning_text(self):
226 """get a string with all the identified warning""" 227 228 to_print = [] 229 if self['skipped_subchannel'] > 0: 230 to_print.append("Some event with large weight have been discarded."+\ 231 " This happens %s times." % self['skipped_subchannel']) 232 if self['n_madloop_calls'] > 0: 233 fraction = self['exceptional_points']/float(self['n_madloop_calls']) 234 if fraction > 1.0e-4: 235 to_print.append("Some PS with numerical instability have been set "+\ 236 "to a zero matrix-element (%.3g%%)" % (100.0*fraction)) 237 238 return ('\n'.join(to_print)).replace("'"," ")
239
240 -class OneResult(object):
241
242 - def __init__(self, name):
243 """Initialize all data """ 244 245 self.run_statistics = RunStatistics() 246 self.name = name 247 self.parent_name = '' 248 self.axsec = 0 # Absolute cross section = Sum(abs(wgt)) 249 self.xsec = 0 # Real cross section = Sum(wgt) 250 self.xerru = 0 # uncorrelated error 251 self.xerrc = 0 # correlated error 252 self.nevents = 0 253 self.nw = 0 # number of events after the primary unweighting 254 self.maxit = 0 # 255 self.nunwgt = 0 # number of unweighted events 256 self.luminosity = 0 257 self.mfactor = 1 # number of times that this channel occur (due to symmetry) 258 self.ysec_iter = [] 259 self.yerr_iter = [] 260 self.yasec_iter = [] 261 self.eff_iter = [] 262 self.maxwgt_iter = [] 263 self.maxwgt = 0 # weight used for the secondary unweighting. 264 self.th_maxwgt= 0 # weight that should have been use for secondary unweighting 265 # this can happen if we force maxweight 266 self.th_nunwgt = 0 # associated number of event with th_maxwgt 267 #(this is theoretical do not correspond to a number of written event) 268 269 return
270 271 #@cluster.multiple_try(nb_try=5,sleep=20)
272 - def read_results(self, filepath):
273 """read results.dat and fullfill information""" 274 275 if isinstance(filepath, str): 276 finput = open(filepath) 277 elif isinstance(filepath, file): 278 finput = filepath 279 else: 280 raise Exception, "filepath should be a path or a file descriptor" 281 282 i=0 283 found_xsec_line = False 284 for line in finput: 285 # Exit as soon as we hit the xml part. Not elegant, but the part 286 # below should eventually be xml anyway. 287 if '<' in line: 288 break 289 i+=1 290 if i == 1: 291 def secure_float(d): 292 try: 293 return float(d) 294 except ValueError: 295 m=re.search(r'''([+-]?[\d.]*)([+-]\d*)''', d) 296 if m: 297 return float(m.group(1))*10**(float(m.group(2))) 298 return
299 300 data = [secure_float(d) for d in line.split()] 301 self.axsec, self.xerru, self.xerrc, self.nevents, self.nw,\ 302 self.maxit, self.nunwgt, self.luminosity, self.wgt, \ 303 self.xsec = data[:10] 304 if len(data) > 10: 305 self.maxwgt = data[10] 306 if len(data) >12: 307 self.th_maxwgt, self.th_nunwgt = data[11:13] 308 if self.mfactor > 1: 309 self.luminosity /= self.mfactor 310 continue 311 try: 312 l, sec, err, eff, maxwgt, asec = line.split() 313 found_xsec_line = True 314 except: 315 break 316 self.ysec_iter.append(secure_float(sec)) 317 self.yerr_iter.append(secure_float(err)) 318 self.yasec_iter.append(secure_float(asec)) 319 self.eff_iter.append(secure_float(eff)) 320 self.maxwgt_iter.append(secure_float(maxwgt)) 321 322 finput.seek(0) 323 xml = [] 324 for line in finput: 325 if re.match('^.*<.*>',line): 326 xml.append(line) 327 break 328 for line in finput: 329 xml.append(line) 330 331 if xml: 332 self.parse_xml_results('\n'.join(xml)) 333 334 # this is for amcatnlo: the number of events has to be read from another file 335 if self.nevents == 0 and self.nunwgt == 0 and isinstance(filepath, str) and \ 336 os.path.exists(pjoin(os.path.split(filepath)[0], 'nevts')): 337 nevts = int(open(pjoin(os.path.split(filepath)[0], 'nevts')).read()) 338 self.nevents = nevts 339 self.nunwgt = nevts
340
341 - def parse_xml_results(self, xml):
342 """ Parse the xml part of the results.dat file.""" 343 344 dom = minidom.parseString(xml) 345 346 statistics_node = dom.getElementsByTagName("run_statistics") 347 348 if statistics_node: 349 try: 350 self.run_statistics.load_statistics(statistics_node[0]) 351 except ValueError, IndexError: 352 logger.warning('Fail to read run statistics from results.dat')
353
354 - def set_mfactor(self, value):
355 self.mfactor = int(value)
356
357 - def change_iterations_number(self, nb_iter):
358 """Change the number of iterations for this process""" 359 360 if len(self.ysec_iter) <= nb_iter: 361 return 362 363 # Combine the first iterations into a single bin 364 nb_to_rm = len(self.ysec_iter) - nb_iter 365 ysec = [0] 366 yerr = [0] 367 for i in range(nb_to_rm): 368 ysec[0] += self.ysec_iter[i] 369 yerr[0] += self.yerr_iter[i]**2 370 ysec[0] /= (nb_to_rm+1) 371 yerr[0] = math.sqrt(yerr[0]) / (nb_to_rm + 1) 372 373 for i in range(1, nb_iter): 374 ysec[i] = self.ysec_iter[nb_to_rm + i] 375 yerr[i] = self.yerr_iter[nb_to_rm + i] 376 377 self.ysec_iter = ysec 378 self.yerr_iter = yerr
379
380 - def get(self, name):
381 382 if name in ['xsec', 'xerru','xerrc']: 383 return getattr(self, name) * self.mfactor 384 elif name in ['luminosity']: 385 #misc.sprint("use unsafe luminosity definition") 386 #raise Exception 387 return getattr(self, name) #/ self.mfactor 388 elif (name == 'eff'): 389 return self.xerr*math.sqrt(self.nevents/(self.xsec+1e-99)) 390 elif name == 'xerr': 391 return math.sqrt(self.xerru**2+self.xerrc**2) 392 elif name == 'name': 393 return pjoin(self.parent_name, self.name) 394 else: 395 return getattr(self, name)
396
397 -class Combine_results(list, OneResult):
398
399 - def __init__(self, name):
400 401 list.__init__(self) 402 OneResult.__init__(self, name)
403
404 - def add_results(self, name, filepath, mfactor=1):
405 """read the data in the file""" 406 try: 407 oneresult = OneResult(name) 408 oneresult.set_mfactor(mfactor) 409 oneresult.read_results(filepath) 410 oneresult.parent_name = self.name 411 self.append(oneresult) 412 return oneresult 413 except Exception: 414 logger.critical("Error when reading %s" % filepath) 415 raise
416 417
418 - def compute_values(self, update_statistics=False):
419 """compute the value associate to this combination""" 420 421 self.compute_iterations() 422 self.axsec = sum([one.axsec for one in self]) 423 self.xsec = sum([one.xsec for one in self]) 424 self.xerrc = sum([one.xerrc for one in self]) 425 self.xerru = math.sqrt(sum([one.xerru**2 for one in self])) 426 427 self.nevents = sum([one.nevents for one in self]) 428 self.nw = sum([one.nw for one in self]) 429 self.maxit = len(self.yerr_iter) # 430 self.nunwgt = sum([one.nunwgt for one in self]) 431 self.wgt = 0 432 self.luminosity = min([0]+[one.luminosity for one in self]) 433 if update_statistics: 434 self.run_statistics.aggregate_statistics([_.run_statistics for _ in self])
435
436 - def compute_average(self):
437 """compute the value associate to this combination""" 438 439 nbjobs = len(self) 440 if not nbjobs: 441 return 442 self.axsec = sum([one.axsec for one in self]) / nbjobs 443 self.xsec = sum([one.xsec for one in self]) /nbjobs 444 self.xerrc = sum([one.xerrc for one in self]) /nbjobs 445 self.xerru = math.sqrt(sum([one.xerru**2 for one in self])) /nbjobs 446 447 self.nevents = sum([one.nevents for one in self]) 448 self.nw = 0#sum([one.nw for one in self]) 449 self.maxit = 0#len(self.yerr_iter) # 450 self.nunwgt = sum([one.nunwgt for one in self]) 451 self.wgt = 0 452 self.luminosity = sum([one.luminosity for one in self]) 453 self.ysec_iter = [] 454 self.yerr_iter = [] 455 self.th_maxwgt = 0.0 456 self.th_nunwgt = 0 457 for result in self: 458 self.ysec_iter+=result.ysec_iter 459 self.yerr_iter+=result.yerr_iter 460 self.yasec_iter += result.yasec_iter 461 self.eff_iter += result.eff_iter 462 self.maxwgt_iter += result.maxwgt_iter
463 464 465
466 - def compute_iterations(self):
467 """Compute iterations to have a chi-square on the stability of the 468 integral""" 469 470 nb_iter = min([len(a.ysec_iter) for a in self], 0) 471 # syncronize all iterations to a single one 472 for oneresult in self: 473 oneresult.change_iterations_number(nb_iter) 474 475 # compute value error for each iteration 476 for i in range(nb_iter): 477 value = [one.ysec_iter[i] for one in self] 478 error = [one.yerr_iter[i]**2 for one in self] 479 480 # store the value for the iteration 481 self.ysec_iter.append(sum(value)) 482 self.yerr_iter.append(math.sqrt(sum(error)))
483 484 485 template_file = \ 486 """ 487 %(diagram_link)s 488 <BR> 489 &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<b>s= %(cross).5g &#177 %(error).3g (%(unit)s)</b><br><br> 490 <table class="sortable" id='tablesort'> 491 <tr><th>Graph</th> 492 <th> %(result_type)s</th> 493 <th>Error</th> 494 <th>Events (K)</th> 495 <th>Unwgt</th> 496 <th>Luminosity</th> 497 </tr> 498 %(table_lines)s 499 </table> 500 </center> 501 <br><br><br> 502 """ 503 table_line_template = \ 504 """ 505 <tr><td align=right>%(P_title)s</td> 506 <td align=right><a id="%(P_link)s" href=%(P_link)s onClick="check_link('%(P_link)s','%(mod_P_link)s','%(P_link)s')"> %(cross)s </a> </td> 507 <td align=right> %(error)s</td> 508 <td align=right> %(events)s</td> 509 <td align=right> %(unweighted)s</td> 510 <td align=right> %(luminosity)s</td> 511 </tr> 512 """ 513
514 - def get_html(self,run, unit, me_dir = []):
515 """write html output""" 516 517 # store value for global cross-section 518 P_grouping = {} 519 520 tables_line = '' 521 for oneresult in self: 522 if oneresult.name.startswith('P'): 523 title = '<a href=../../SubProcesses/%(P)s/diagrams.html>%(P)s</a>' \ 524 % {'P':oneresult.name} 525 P = oneresult.name.split('_',1)[0] 526 if P in P_grouping: 527 P_grouping[P] += float(oneresult.xsec) 528 else: 529 P_grouping[P] = float(oneresult.xsec) 530 else: 531 title = oneresult.name 532 533 if not isinstance(oneresult, Combine_results): 534 # this is for the (aMC@)NLO logs 535 if os.path.exists(pjoin(me_dir, 'Events', run, 'alllogs_1.html')): 536 link = '../../Events/%(R)s/alllogs_1.html#/%(P)s/%(G)s' % \ 537 {'P': self.name, 538 'G': oneresult.name, 539 'R': run} 540 mod_link = link 541 elif os.path.exists(pjoin(me_dir, 'Events', run, 'alllogs_0.html')): 542 link = '../../Events/%(R)s/alllogs_0.html#/%(P)s/%(G)s' % \ 543 {'P': self.name, 544 'G': oneresult.name, 545 'R': run} 546 mod_link = link 547 else: 548 # this is for madevent runs 549 link = '../../SubProcesses/%(P)s/%(G)s/%(R)s_log.txt' % \ 550 {'P': self.name, 551 'G': oneresult.name, 552 'R': run} 553 mod_link = '../../SubProcesses/%(P)s/%(G)s/log.txt' % \ 554 {'P': self.name, 555 'G': oneresult.name} 556 else: 557 link = '#%s' % oneresult.name 558 mod_link = link 559 560 dico = {'P_title': title, 561 'P_link': link, 562 'mod_P_link': mod_link, 563 'cross': '%.4g' % oneresult.xsec, 564 'error': '%.3g' % oneresult.xerru, 565 'events': oneresult.nevents/1000.0, 566 'unweighted': oneresult.nunwgt, 567 'luminosity': '%.3g' % oneresult.luminosity 568 } 569 570 tables_line += self.table_line_template % dico 571 572 for P_name, cross in P_grouping.items(): 573 dico = {'P_title': '%s sum' % P_name, 574 'P_link': './results.html', 575 'mod_P_link':'', 576 'cross': cross, 577 'error': '', 578 'events': '', 579 'unweighted': '', 580 'luminosity': '' 581 } 582 tables_line += self.table_line_template % dico 583 584 if self.name.startswith('P'): 585 title = '<dt><a name=%(P)s href=../../SubProcesses/%(P)s/diagrams.html>%(P)s</a></dt><dd>' \ 586 % {'P':self.name} 587 else: 588 title = '' 589 590 dico = {'cross': self.xsec, 591 'abscross': self.axsec, 592 'error': self.xerru, 593 'unit': unit, 594 'result_type': 'Cross-Section', 595 'table_lines': tables_line, 596 'diagram_link': title 597 } 598 599 html_text = self.template_file % dico 600 return html_text
601
602 - def write_results_dat(self, output_path):
603 """write a correctly formatted results.dat""" 604 605 def fstr(nb): 606 data = '%E' % nb 607 if data == 'NAN': 608 nb, power = 0,0 609 else: 610 nb, power = data.split('E') 611 nb = float(nb) /10 612 power = int(power) + 1 613 return '%.5fE%+03i' %(nb,power)
614 615 line = '%s %s %s %i %i %i %i %s %s %s %s %s %i\n' % (fstr(self.axsec), fstr(self.xerru), 616 fstr(self.xerrc), self.nevents, self.nw, self.maxit, self.nunwgt, 617 fstr(self.luminosity), fstr(self.wgt), fstr(self.xsec), fstr(self.maxwgt), 618 fstr(self.th_maxwgt), self.th_nunwgt) 619 fsock = open(output_path,'w') 620 fsock.writelines(line) 621 for i in range(len(self.ysec_iter)): 622 line = '%s %s %s %s %s %s\n' % (i+1, self.ysec_iter[i], self.yerr_iter[i], 623 self.eff_iter[i], self.maxwgt_iter[i], self.yasec_iter[i]) 624 fsock.writelines(line)
625 626 627 628 results_header = """ 629 <head> 630 <title>Process results</title> 631 <script type="text/javascript" src="../sortable.js"></script> 632 <link rel=stylesheet href="../mgstyle.css" type="text/css"> 633 </head> 634 <body> 635 <script type="text/javascript"> 636 function UrlExists(url) { 637 var http = new XMLHttpRequest(); 638 http.open('HEAD', url, false); 639 try{ 640 http.send() 641 } 642 catch(err){ 643 return 1==2; 644 } 645 return http.status!=404; 646 } 647 function check_link(url,alt, id){ 648 var obj = document.getElementById(id); 649 if ( ! UrlExists(url)){ 650 if ( ! UrlExists(alt)){ 651 obj.href = alt; 652 return true; 653 } 654 obj.href = alt; 655 return false; 656 } 657 obj.href = url; 658 return 1==1; 659 } 660 </script> 661 """ 662
663 -def collect_result(cmd, folder_names):
664 """ """ 665 666 run = cmd.results.current['run_name'] 667 all = Combine_results(run) 668 669 for Pdir in open(pjoin(cmd.me_dir, 'SubProcesses','subproc.mg')): 670 Pdir = Pdir.strip() 671 P_comb = Combine_results(Pdir) 672 673 P_path = pjoin(cmd.me_dir, 'SubProcesses', Pdir) 674 G_dir = [G for G in os.listdir(P_path) if G.startswith('G') and 675 os.path.isdir(pjoin(P_path,G))] 676 677 try: 678 for line in open(pjoin(P_path, 'symfact.dat')): 679 name, mfactor = line.split() 680 if float(mfactor) < 0: 681 continue 682 if os.path.exists(pjoin(P_path, 'ajob.no_ps.log')): 683 continue 684 685 if not folder_names: 686 name = 'G' + name 687 P_comb.add_results(name, pjoin(P_path,name,'results.dat'), mfactor) 688 else: 689 for folder in folder_names: 690 if 'G' in folder: 691 dir = folder.replace('*', name) 692 else: 693 dir = folder.replace('*', '_G' + name) 694 P_comb.add_results(dir, pjoin(P_path,dir,'results.dat'), mfactor) 695 except IOError: 696 continue 697 P_comb.compute_values() 698 all.append(P_comb) 699 all.compute_values() 700 return all
701 702
703 -def make_all_html_results(cmd, folder_names = []):
704 """ folder_names has been added for the amcatnlo runs """ 705 run = cmd.results.current['run_name'] 706 if not os.path.exists(pjoin(cmd.me_dir, 'HTML', run)): 707 os.mkdir(pjoin(cmd.me_dir, 'HTML', run)) 708 709 unit = cmd.results.unit 710 P_text = "" 711 Presults = collect_result(cmd, folder_names=folder_names) 712 713 714 for P_comb in Presults: 715 P_text += P_comb.get_html(run, unit, cmd.me_dir) 716 P_comb.compute_values() 717 P_comb.write_results_dat(pjoin(cmd.me_dir, 'SubProcesses', P_comb.name, 718 '%s_results.dat' % run)) 719 720 721 Presults.write_results_dat(pjoin(cmd.me_dir,'SubProcesses', 'results.dat')) 722 723 fsock = open(pjoin(cmd.me_dir, 'HTML', run, 'results.html'),'w') 724 fsock.write(results_header) 725 fsock.write('%s <dl>' % Presults.get_html(run, unit, cmd.me_dir)) 726 fsock.write('%s </dl></body>' % P_text) 727 728 return Presults.xsec, Presults.xerru
729