2 Core information needed to inspect a runfolder.
15 from xml.etree import ElementTree
16 except ImportError, e:
17 from elementtree import ElementTree
19 EUROPEAN_STRPTIME = "%d-%m-%Y"
20 EUROPEAN_DATE_RE = "([0-9]{1,2}-[0-9]{1,2}-[0-9]{4,4})"
21 VERSION_RE = "([0-9\.]+)"
22 USER_RE = "([a-zA-Z0-9]+)"
23 LANES_PER_FLOWCELL = 8
25 from htsworkflow.util.alphanum import alphanum
26 from htsworkflow.util.ethelp import indent, flatten
28 class PipelineRun(object):
30 Capture "interesting" information about a pipeline run
33 PIPELINE_RUN = 'PipelineRun'
34 FLOWCELL_ID = 'FlowcellID'
36 def __init__(self, pathname=None, xml=None):
37 if pathname is not None:
38 self.pathname = os.path.normpath(pathname)
42 self._flowcell_id = None
43 self.image_analysis = None
48 self.set_elements(xml)
50 def _get_flowcell_id(self):
52 if self._flowcell_id is None:
53 config_dir = os.path.join(self.pathname, 'Config')
54 flowcell_id_path = os.path.join(config_dir, 'FlowcellId.xml')
55 if os.path.exists(flowcell_id_path):
56 flowcell_id_tree = ElementTree.parse(flowcell_id_path)
57 self._flowcell_id = flowcell_id_tree.findtext('Text')
59 path_fields = self.pathname.split('_')
60 if len(path_fields) > 0:
61 # guessing last element of filename
62 flowcell_id = path_fields[-1]
64 flowcell_id = 'unknown'
67 "Flowcell id was not found, guessing %s" % (
69 self._flowcell_id = flowcell_id
70 return self._flowcell_id
71 flowcell_id = property(_get_flowcell_id)
73 def get_elements(self):
75 make one master xml file from all of our sub-components.
77 root = ElementTree.Element(PipelineRun.PIPELINE_RUN)
78 flowcell = ElementTree.SubElement(root, PipelineRun.FLOWCELL_ID)
79 flowcell.text = self.flowcell_id
80 root.append(self.image_analysis.get_elements())
81 root.append(self.bustard.get_elements())
82 root.append(self.gerald.get_elements())
85 def set_elements(self, tree):
86 # this file gets imported by all the others,
87 # so we need to hide the imports to avoid a cyclic imports
88 from htsworkflow.pipelines import firecrest
89 from htsworkflow.pipelines import ipar
90 from htsworkflow.pipelines import bustard
91 from htsworkflow.pipelines import gerald
93 tag = tree.tag.lower()
94 if tag != PipelineRun.PIPELINE_RUN.lower():
95 raise ValueError('Pipeline Run Expecting %s got %s' % (
96 PipelineRun.PIPELINE_RUN, tag))
98 tag = element.tag.lower()
99 if tag == PipelineRun.FLOWCELL_ID.lower():
100 self._flowcell_id = element.text
101 #ok the xword.Xword.XWORD pattern for module.class.constant is lame
102 # you should only have Firecrest or IPAR, never both of them.
103 elif tag == firecrest.Firecrest.FIRECREST.lower():
104 self.image_analysis = firecrest.Firecrest(xml=element)
105 elif tag == ipar.IPAR.IPAR.lower():
106 self.image_analysis = ipar.IPAR(xml=element)
107 elif tag == bustard.Bustard.BUSTARD.lower():
108 self.bustard = bustard.Bustard(xml=element)
109 elif tag == gerald.Gerald.GERALD.lower():
110 self.gerald = gerald.Gerald(xml=element)
112 logging.warn('PipelineRun unrecognized tag %s' % (tag,))
114 def _get_run_name(self):
116 Given a run tuple, find the latest date and use that as our name
118 if self._name is None:
119 tmax = max(self.image_analysis.time, self.bustard.time, self.gerald.time)
120 timestamp = time.strftime('%Y-%m-%d', time.localtime(tmax))
121 self._name = 'run_'+self.flowcell_id+"_"+timestamp+'.xml'
123 name = property(_get_run_name)
125 def save(self, destdir=None):
128 logging.info("Saving run report "+ self.name)
129 xml = self.get_elements()
131 dest_pathname = os.path.join(destdir, self.name)
132 ElementTree.ElementTree(xml).write(dest_pathname)
134 def load(self, filename):
135 logging.info("Loading run report from " + filename)
136 tree = ElementTree.parse(filename).getroot()
137 self.set_elements(tree)
139 def load_pipeline_run_xml(pathname):
141 Load and instantiate a Pipeline run from a run xml file
144 - `pathname` : location of an run xml file
146 :Returns: initialized PipelineRun object
148 tree = ElementTree.parse(pathname).getroot()
149 run = PipelineRun(xml=tree)
152 def get_runs(runfolder):
154 Search through a run folder for all the various sub component runs
155 and then return a PipelineRun for each different combination.
157 For example if there are two different GERALD runs, this will
158 generate two different PipelineRun objects, that differ
159 in there gerald component.
161 from htsworkflow.pipelines import firecrest
162 from htsworkflow.pipelines import ipar
163 from htsworkflow.pipelines import bustard
164 from htsworkflow.pipelines import gerald
166 def scan_post_image_analysis(runs, runfolder, image_analysis, pathname):
167 logging.info("Looking for bustard directories in %s" % (pathname,))
168 bustard_glob = os.path.join(pathname, "Bustard*")
169 for bustard_pathname in glob(bustard_glob):
170 logging.info("Found bustard directory %s" % (bustard_pathname,))
171 b = bustard.bustard(bustard_pathname)
172 gerald_glob = os.path.join(bustard_pathname, 'GERALD*')
173 logging.info("Looking for gerald directories in %s" % (pathname,))
174 for gerald_pathname in glob(gerald_glob):
175 logging.info("Found gerald directory %s" % (gerald_pathname,))
177 g = gerald.gerald(gerald_pathname)
178 p = PipelineRun(runfolder)
179 p.image_analysis = image_analysis
184 logging.error("Ignoring " + str(e))
186 datadir = os.path.join(runfolder, 'Data')
188 logging.info('Searching for runs in ' + datadir)
190 # scan for firecrest directories
191 for firecrest_pathname in glob(os.path.join(datadir,"*Firecrest*")):
192 logging.info('Found firecrest in ' + datadir)
193 image_analysis = firecrest.firecrest(firecrest_pathname)
194 if image_analysis is None:
196 "%s is an empty or invalid firecrest directory" % (firecrest_pathname,)
199 scan_post_image_analysis(
200 runs, runfolder, image_analysis, firecrest_pathname
202 # scan for IPAR directories
203 for ipar_pathname in glob(os.path.join(datadir,"IPAR_*")):
204 logging.info('Found ipar directories in ' + datadir)
205 image_analysis = ipar.ipar(ipar_pathname)
206 if image_analysis is None:
208 "%s is an empty or invalid IPAR directory" %(ipar_pathname,)
211 scan_post_image_analysis(
212 runs, runfolder, image_analysis, ipar_pathname
217 def get_specific_run(gerald_dir):
219 Given a gerald directory, construct a PipelineRun out of its parents
221 Basically this allows specifying a particular run instead of the previous
222 get_runs which scans a runfolder for various combinations of
223 firecrest/ipar/bustard/gerald runs.
225 from htsworkflow.pipelines import firecrest
226 from htsworkflow.pipelines import ipar
227 from htsworkflow.pipelines import bustard
228 from htsworkflow.pipelines import gerald
230 bustard_dir = os.path.abspath(os.path.join(gerald_dir, '..'))
231 image_dir = os.path.abspath(os.path.join(gerald_dir, '..', '..'))
233 runfolder_dir = os.path.abspath(os.path.join(image_dir, '..','..'))
235 logging.info('--- use-run detected options ---')
236 logging.info('runfolder: %s' % (runfolder_dir,))
237 logging.info('image_dir: %s' % (image_dir,))
238 logging.info('bustard_dir: %s' % (bustard_dir,))
239 logging.info('gerald_dir: %s' % (gerald_dir,))
241 # find our processed image dir
243 # split into parent, and leaf directory
244 # leaf directory should be an IPAR or firecrest directory
245 data_dir, short_image_dir = os.path.split(image_dir)
246 logging.info('data_dir: %s' % (data_dir,))
247 logging.info('short_iamge_dir: %s' %(short_image_dir,))
249 # guess which type of image processing directory we have by looking
250 # in the leaf directory name
251 if re.search('Firecrest', short_image_dir, re.IGNORECASE) is not None:
252 image_run = firecrest.firecrest(image_dir)
253 elif re.search('IPAR', short_image_dir, re.IGNORECASE) is not None:
254 image_run = ipar.ipar(image_dir)
255 # if we din't find a run, report the error and return
256 if image_run is None:
257 msg = '%s does not contain an image processing step' % (image_dir,)
261 # find our base calling
262 base_calling_run = bustard.bustard(bustard_dir)
263 if base_calling_run is None:
264 logging.error('%s does not contain a bustard run' % (bustard_dir,))
268 gerald_run = gerald.gerald(gerald_dir)
269 if gerald_run is None:
270 logging.error('%s does not contain a gerald run' % (gerald_dir,))
273 p = PipelineRun(runfolder_dir)
274 p.image_analysis = image_run
275 p.bustard = base_calling_run
276 p.gerald = gerald_run
278 logging.info('Constructed PipelineRun from %s' % (gerald_dir,))
281 def extract_run_parameters(runs):
283 Search through runfolder_path for various runs and grab their parameters
288 def summarize_mapped_reads(genome_map, mapped_reads):
290 Summarize per chromosome reads into a genome count
291 But handle spike-in/contamination symlinks seperately.
293 summarized_reads = {}
296 for k, v in mapped_reads.items():
297 path, k = os.path.split(k)
298 if len(path) > 0 and not genome_map.has_key(path):
302 summarized_reads[k] = summarized_reads.setdefault(k, 0) + v
303 summarized_reads[genome] = genome_reads
304 return summarized_reads
306 def summarize_lane(gerald, lane_id):
308 summary_results = gerald.summary.lane_results
309 for end in range(len(summary_results)):
310 eland_result = gerald.eland_results.results[end][lane_id]
311 report.append("Sample name %s" % (eland_result.sample_name))
312 report.append("Lane id %s end %s" % (eland_result.lane_id, end))
313 cluster = summary_results[end][eland_result.lane_id].cluster
314 report.append("Clusters %d +/- %d" % (cluster[0], cluster[1]))
315 report.append("Total Reads: %d" % (eland_result.reads))
316 mc = eland_result._match_codes
318 nm_percent = float(nm)/eland_result.reads * 100
320 qc_percent = float(qc)/eland_result.reads * 100
322 report.append("No Match: %d (%2.2g %%)" % (nm, nm_percent))
323 report.append("QC Failed: %d (%2.2g %%)" % (qc, qc_percent))
324 report.append('Unique (0,1,2 mismatches) %d %d %d' % \
325 (mc['U0'], mc['U1'], mc['U2']))
326 report.append('Repeat (0,1,2 mismatches) %d %d %d' % \
327 (mc['R0'], mc['R1'], mc['R2']))
328 report.append("Mapped Reads")
329 mapped_reads = summarize_mapped_reads(eland_result.genome_map, eland_result.mapped_reads)
330 for name, counts in mapped_reads.items():
331 report.append(" %s: %d" % (name, counts))
335 def summary_report(runs):
337 Summarize cluster numbers and mapped read counts for a runfolder
342 report.append('Summary for %s' % (run.name,))
344 eland_keys = run.gerald.eland_results.results[0].keys()
345 eland_keys.sort(alphanum)
347 for lane_id in eland_keys:
348 report.extend(summarize_lane(run.gerald, lane_id))
351 return os.linesep.join(report)
353 def is_compressed(filename):
354 if os.path.splitext(filename)[1] == ".gz":
356 elif os.path.splitext(filename)[1] == '.bz2':
361 def extract_results(runs, output_base_dir=None):
362 if output_base_dir is None:
363 output_base_dir = os.getcwd()
366 result_dir = os.path.join(output_base_dir, r.flowcell_id)
367 logging.info("Using %s as result directory" % (result_dir,))
368 if not os.path.exists(result_dir):
372 cycle = "C%d-%d" % (r.image_analysis.start, r.image_analysis.stop)
373 logging.info("Filling in %s" % (cycle,))
374 cycle_dir = os.path.join(result_dir, cycle)
375 if os.path.exists(cycle_dir):
376 logging.error("%s already exists, not overwriting" % (cycle_dir,))
381 # copy stuff out of the main run
388 summary_path = os.path.join(r.gerald.pathname, 'Summary.htm')
389 if os.path.exists(summary_path):
390 logging.info('Copying %s to %s' % (summary_path, cycle_dir))
391 shutil.copy(summary_path, cycle_dir)
393 logging.info('Summary file %s was not found' % (summary_path,))
398 # check for g.pathname/Temp a new feature of 1.1rc1
399 scores_path = g.pathname
400 scores_path_temp = os.path.join(scores_path, 'Temp')
401 if os.path.isdir(scores_path_temp):
402 scores_path = scores_path_temp
404 # hopefully we have a directory that contains s_*_score files
405 for f in os.listdir(scores_path):
406 if re.match('.*_score.txt', f):
407 score_files.append(f)
409 tar_cmd = ['/bin/tar', 'c'] + score_files
410 bzip_cmd = [ 'bzip2', '-9', '-c' ]
411 tar_dest_name =os.path.join(cycle_dir, 'scores.tar.bz2')
412 tar_dest = open(tar_dest_name, 'w')
413 logging.info("Compressing score files from %s" % (scores_path,))
414 logging.info("Running tar: " + " ".join(tar_cmd[:10]))
415 logging.info("Running bzip2: " + " ".join(bzip_cmd))
416 logging.info("Writing to %s" %(tar_dest_name))
418 tar = subprocess.Popen(tar_cmd, stdout=subprocess.PIPE, shell=False,
420 bzip = subprocess.Popen(bzip_cmd, stdin=tar.stdout, stdout=tar_dest)
423 # copy & bzip eland files
424 for lanes_dictionary in g.eland_results.results:
425 for eland_lane in lanes_dictionary.values():
426 source_name = eland_lane.pathname
427 path, name = os.path.split(eland_lane.pathname)
428 dest_name = os.path.join(cycle_dir, name)
429 logging.info("Saving eland file %s to %s" % \
430 (source_name, dest_name))
432 if is_compressed(name):
433 logging.info('Already compressed, Saving to %s' % (dest_name, ))
434 shutil.copy(source_name, dest_name)
438 args = ['bzip2', '-9', '-c', source_name]
439 logging.info('Running: %s' % ( " ".join(args) ))
440 bzip_dest = open(dest_name, 'w')
441 bzip = subprocess.Popen(args, stdout=bzip_dest)
442 logging.info('Saving to %s' % (dest_name, ))
445 def rm_list(files, dry_run=True):
447 if os.path.exists(f):
448 logging.info('deleting %s' % (f,))
455 logging.warn("%s doesn't exist."% (f,))
457 def clean_runs(runs, dry_run=True):
459 Clean up run folders to optimize for compression.
462 logging.info('In dry-run mode')
465 logging.info('Cleaninging %s' % (run.pathname,))
467 runlogs = glob(os.path.join(run.pathname, 'RunLog*xml'))
468 rm_list(runlogs, dry_run)
470 pipeline_logs = glob(os.path.join(run.pathname, 'pipeline*.txt'))
471 rm_list(pipeline_logs, dry_run)
473 # rm NetCopy.log? Isn't this robocopy?
474 logs = glob(os.path.join(run.pathname, '*.log'))
475 rm_list(logs, dry_run)
478 calibration_dir = glob(os.path.join(run.pathname, 'Calibration_*'))
479 rm_list(calibration_dir, dry_run)
481 logging.info("Cleaning images")
482 image_dirs = glob(os.path.join(run.pathname, 'Images', 'L*'))
483 rm_list(image_dirs, dry_run)
484 # cd Data/C1-*_Firecrest*
485 logging.info("Cleaning intermediate files")
486 # make clean_intermediate
487 if os.path.exists(os.path.join(run.image_analysis.pathname, 'Makefile')):
488 clean_process = subprocess.Popen(['make', 'clean_intermediate'],
489 cwd=run.image_analysis.pathname,)