from CCP4ReportParser import * import sys from lxml import etree import import_mosflm_report class mosflm_report(Report): # Specify which gui task and/or pluginscript this applies to TASKNAME = 'mosflm' RUNNING = True def __init__(self,xmlnode=None,jobInfo={},jobStatus=None,**kw): Report. __init__(self,xmlnode=xmlnode,jobInfo=jobInfo,**kw) if jobStatus.lower()=="nooutput": return integrationResultNode=self.makeIntegrationResult() #print etree.tostring(integrationResultNode,pretty_print=True) importMosflmReport = import_mosflm_report.import_mosflm_report(xmlnode=integrationResultNode,jobInfo=jobInfo, jobStatus="nooutput") detectorFold = self.addFold(label="Detector and beam", initiallyOpen=True) detectorDiv = detectorFold.addDiv(style="border:2px solid black;display:inline-block;") graphLineChooser = detectorDiv.addGraphLineChooser(tableWidth='220px',contentWidth='260px',height='270px') importMosflmReport.beamGraph(parent=graphLineChooser) importMosflmReport.centralSpotProfile(parent=detectorDiv) clearingDiv = self.addDiv(style="clear:both;") crystalFold = self.addFold(label="Crystal", initiallyOpen=True) crystalDiv = crystalFold.addDiv(style="border:2px solid black;display:inline-block;") otherGraphLineChooser = crystalDiv.addGraphLineChooser(tableWidth='220px',contentWidth='260px',height='270px') importMosflmReport.crystalGraph(parent=otherGraphLineChooser) importMosflmReport.blockProfiles(parent=crystalDiv) clearingDiv = self.addDiv(style="clear:both;") dataFold = self.addFold(label="Data", initiallyOpen=True) dataDiv = dataFold.addDiv(style="border:2px solid black;display:inline-block;") thirdGraphLineChooser = dataDiv.addGraphLineChooser(tableWidth='220px',contentWidth='260px',height='270px') importMosflmReport.dataGraph(parent=thirdGraphLineChooser) importMosflmReport.histograms(parent=dataDiv) def makeIntegrationResult(self): collectedData = {} integrationNodes = self.xmlnode.xpath('//integration_positional_refinement') integration_positional_refinement_tags = [] for integrationNode in integrationNodes: imageNameNodes = integrationNode.xpath('image_name') imageName = imageNameNodes[0].text if not imageName in collectedData: collectedData[imageName] = {} for child in integrationNode: if child.tag != 'image_name': if child.text is not None: collectedData[imageName][child.tag] = child.text.strip() if child.tag not in integration_positional_refinement_tags: integration_positional_refinement_tags.append (child.tag) integrationNodes = self.xmlnode.xpath('//integration_postrefinement') integration_post_refinement_tags = [] for integrationNode in integrationNodes: imageNameNodes = integrationNode.xpath('image_name') imageName = imageNameNodes[0].text if not imageName in collectedData: collectedData[imageName] = {} for child in integrationNode: if child.tag != 'image_name': if child.text is not None: collectedData[imageName][child.tag] = child.text.strip() if child.tag not in integration_post_refinement_tags: integration_post_refinement_tags.append (child.tag) spotProfiles = {} spotProfileNodes = self.xmlnode.xpath('//spot_profile') spot_profile_tags = [] for spotProfileNode in spotProfileNodes: imageNameNodes = spotProfileNode.xpath('image_name') imageName = imageNameNodes[0].text if not imageName in spotProfiles: spotProfiles[imageName] = {} for child in spotProfileNode: if child.text is not None: if child.tag == 'raw_data' or child.tag == 'mask': spotProfiles[imageName][child.tag] = " ".join(child.text.split()) else: spotProfiles[imageName][child.tag] = child.text.strip() if child.tag not in spot_profile_tags: spot_profile_tags.append (child.tag) regionalProfiles = [] regionalProfileNodes = self.xmlnode.xpath('//regional_spot_profile_response') for regionalProfileNode in regionalProfileNodes: regionalProfile = etree.Element('profile_grid') regionalProfiles += [regionalProfile] regionalProfile.set('block', str(len(regionalProfiles))) for child in regionalProfileNode: if child.tag == 'number_of_profiles_x': regionalProfile.set('num_x',child.text) elif child.tag == 'number_of_profiles_y': regionalProfile.set('num_y', child.text) elif child.tag == 'profile': subProfile = etree.SubElement(regionalProfile,'regional_profile') for grandChild in child: if grandChild.tag in ['box','width','height']: subProfile.set(grandChild.tag, grandChild.text) elif grandChild.tag == 'original': for greatGrandChild in grandChild: if greatGrandChild.tag == 'data': subProfile.set('raw_data', " ".join(greatGrandChild.text.split())) subProfile.set('max_data_value',str(max([int(value) for value in greatGrandChild.text.strip().split()]))) elif greatGrandChild.tag == 'mask': subProfile.set('mask', " ".join(greatGrandChild.text.split())) elif grandChild.tag == 'averaged': for greatGrandChild in grandChild: if greatGrandChild.tag == 'data': subProfile.set('alt_raw_data', " ".join(greatGrandChild.text.split())) elif greatGrandChild.tag == 'mask': subProfile.set('alt_mask', " ".join(greatGrandChild.text.split())) if 'alt_raw_data' in subProfile.attrib: if 'raw_data' in subProfile.attrib: subProfile.set('type','dual') else: subProfile.set('type','averaged_only') subProfile.set('raw_data','') subProfile.set('mask','') else: subProfile.set('type','original_only') subProfile.set('alt_raw_data','') subProfile.set('alt_mask','') # Need to add image by image data analyses and histograms. First off pass through and digest into the growing memory data structure integrationNodes = self.xmlnode.xpath('//integration_response') for iIntegrationNode in range(len(integrationNodes)): integrationNode = integrationNodes[iIntegrationNode] imageName = integrationNode.xpath('image_name')[0].text if not imageName in collectedData: print imageName collectedData[imageName] = {} for child in integrationNode: if child.tag == 'image_name': #no action pass elif child.tag == 'status': collectedData[imageName][child.tag] = {} for grandChild in child: collectedData[imageName][child.tag][grandChild.tag] = grandChild.text elif child.tag.startswith('bin'): if not 'bins' in collectedData[imageName]: collectedData[imageName]['bins'] = [] collectedData[imageName]['bins'].append({}) for grandChild in child: collectedData[imageName]['bins'][-1][grandChild.tag] = grandChild.text #And then turn this into additional XML #Get sorted list of image names imageNames = sorted([imageName for imageName in collectedData]) integrationResultNode = etree.Element('integration_result') integrationResultNode.set('image_files_being_processed',' '.join([imageName for imageName in imageNames])) for tag in integration_positional_refinement_tags: integrationResultNode.set(tag,' '.join([collectedData[imageName][tag] for imageName in imageNames])) for tag in integration_post_refinement_tags: dataArray = [] for imageName in imageNames: if tag in collectedData[imageName]: dataArray += [collectedData[imageName][tag]] else: dataArray += ['{}'] integrationResultNode.set(tag,' '.join(dataArray)) nameMappingTotal = {"profile_fitted_fulls":"mean_profile_fitted_fulls", "profile_fitted_partials":"mean_profile_fitted_partials", "summation_integration_fulls":"mean_summation_integration_fulls", "summation_integration_partials":"mean_summation_integration_partials", "spot_count_fulls":"total_spot_count_fulls", "spot_count_partials":"total_spot_count_partials"} for tag in nameMappingTotal: integrationResultNode.set(nameMappingTotal[tag],' '.join([collectedData[imageName]['bins'][-1][tag] for imageName in imageNames])) nameMappingOuter = {"profile_fitted_fulls":"outer_profile_fitted_fulls", "profile_fitted_partials":"outer_profile_fitted_partials", "summation_integration_fulls":"outer_summation_integration_fulls", "summation_integration_partials":"outer_summation_integration_partials", "spot_count_fulls":"outer_spot_count_fulls", "spot_count_partials":"outer_spot_count_partials"} for tag in nameMappingTotal: integrationResultNode.set(nameMappingOuter[tag],' '.join([collectedData[imageName]['bins'][-2][tag] for imageName in imageNames])) histogramText = '' for imageName in collectedData: nBins = len(collectedData[imageName]['bins']) resoHistogramText = imageName.strip()+u',bin_resolution_limits {\u221e'+" ".join([collectedData[imageName]['bins'][i]['upper_limit'].strip() for i in range(nBins)]).strip()+'} ' histogramText += resoHistogramText #print resoHistogramText for tag in nameMappingOuter: if tag in collectedData[imageName]['bins'][0]: thisHistogramText = imageName.strip()+','+tag.strip()+' '+'{'+" ".join([collectedData[imageName]['bins'][i][tag].strip() for i in range(nBins)]).strip()+'} ' #print thisHistogramText histogramText += thisHistogramText integrationResultNode.set('histograms', histogramText) #Get sorted list of spot profiles imageNames = sorted([imageName for imageName in spotProfiles]) profileTagLookup = {'width':'width','height':'height', 'profile':'raw_data', 'mask':'mask','image_name':'label'} for imageName in imageNames: newProfile = etree.SubElement(integrationResultNode,'profile') for tag in spot_profile_tags: newProfile.set(profileTagLookup[tag], spotProfiles[imageName][tag].strip()) newProfile.set('max_data_value',str(max([int(value) for value in newProfile.get('raw_data').strip().split()]))) #Append Block Profiles for regionalProfile in regionalProfiles: integrationResultNode.append(regionalProfile) return integrationResultNode