Mercurial > hg > orthanc-tests
view PerfsDb/DbPopulator.py @ 753:a144d6289b92 find-refactoring
integration default->find-refactoring
author | Sebastien Jodogne <s.jodogne@gmail.com> |
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date | Mon, 16 Dec 2024 11:09:13 +0100 |
parents | 1ff0d830bb87 |
children |
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import typing import time import csv import os from orthancRestApi import OrthancClient from TestResult import TestResult from DbSize import DbSize class DbPopulator: def __init__(self, orthanc: OrthancClient, dbSize: DbSize): self._orthanc = orthanc self._dbSize = dbSize self._sourceInstanceId = None self._fileCounter = 0 def populate(self, label: str): self._sourceInstanceId = self._orthanc.uploadDicomFile("../Database/DummyCT.dcm") if self._dbSize == DbSize.Tiny: patientCount = 1 smallStudiesPerPatient = 2 largeStudiesPerPatient = 1 seriesPerSmallStudy = 1 seriesPerLargeStudy = 2 instancesPerSmallSeries = 1 instancesPerLargeSeries = 5 elif self._dbSize == DbSize.Small: patientCount = 100 smallStudiesPerPatient = 2 largeStudiesPerPatient = 1 seriesPerSmallStudy = 1 seriesPerLargeStudy = 2 instancesPerSmallSeries = 1 instancesPerLargeSeries = 30 elif self._dbSize == DbSize.Medium: patientCount = 1000 smallStudiesPerPatient = 2 largeStudiesPerPatient = 2 seriesPerSmallStudy = 1 seriesPerLargeStudy = 2 instancesPerSmallSeries = 1 instancesPerLargeSeries = 300 elif self._dbSize == DbSize.Large: patientCount = 10000 smallStudiesPerPatient = 2 largeStudiesPerPatient = 2 seriesPerSmallStudy = 1 seriesPerLargeStudy = 2 instancesPerSmallSeries = 1 instancesPerLargeSeries = 300 else: raise NotImplementedError print("Will generate data for (approximately):") print("{n:>12} patients".format(n=patientCount)) print("{n:>12} studies".format(n=patientCount * (smallStudiesPerPatient + largeStudiesPerPatient))) print("{n:>12} instances".format(n=patientCount * (smallStudiesPerPatient * seriesPerSmallStudy * instancesPerSmallSeries + largeStudiesPerPatient * seriesPerLargeStudy * instancesPerLargeSeries))) startTime = time.time() # first add data that are the same in small and large DBs (and that can be used in tests for comparing the same things !!) # used in TestFindStudyByPatientId100Results for i in range(100): self.createStudy(studyIndex=199000+i, patientIndex=99997, seriesCount=1, instancesPerSeries=1) # used in TestFindStudyByPatientId5Results self.createStudy(studyIndex=99994, patientIndex=99998, seriesCount=1, instancesPerSeries=1) self.createStudy(studyIndex=99995, patientIndex=99998, seriesCount=1, instancesPerSeries=1) self.createStudy(studyIndex=99996, patientIndex=99998, seriesCount=1, instancesPerSeries=1) self.createStudy(studyIndex=99997, patientIndex=99998, seriesCount=1, instancesPerSeries=1) self.createStudy(studyIndex=99998, patientIndex=99998, seriesCount=1, instancesPerSeries=1) # used in TestFindStudyByStudyDescription1Result # used in TestFindStudyByPatientId1Result # used in TestToolsFindStudyByStudyInstanceUID self.createStudy(studyIndex=99999, patientIndex=99999, seriesCount=1, instancesPerSeries=1) with open(os.path.join(os.path.dirname(os.path.abspath(__file__)), "Results/db-init-" + label + ".csv"), 'w', newline='') as resultFile: resultWriter = csv.writer(resultFile) resultWriter.writerow(["#patientCount", "filesCount", "files/sec"]) # then, add data to make the DB "large" or "small" for patientIndex in range(0, patientCount): studyIndex=0 print("Generating data for patient " + str(patientIndex)) fileCounterAtPatientStart = self._fileCounter startTimePatient = time.time() for i in range(0, smallStudiesPerPatient): print("Generating small study " + str(i)) self.createStudy(studyIndex=studyIndex, patientIndex=patientIndex, seriesCount=seriesPerSmallStudy, instancesPerSeries=instancesPerSmallSeries) studyIndex+=1 for i in range(0, largeStudiesPerPatient): print("Generating large study " + str(i)) self.createStudy(studyIndex=studyIndex, patientIndex=patientIndex, seriesCount=seriesPerLargeStudy, instancesPerSeries=instancesPerLargeSeries) studyIndex+=1 endTimePatient = time.time() print("STATS: uploaded {n} files in {s:.2f} seconds; {x:.2f} files/sec".format( n=self._fileCounter - fileCounterAtPatientStart, s=endTimePatient - startTimePatient, x=(self._fileCounter - fileCounterAtPatientStart)/(endTimePatient - startTimePatient) )) resultWriter.writerow([ patientIndex, self._fileCounter, (self._fileCounter - fileCounterAtPatientStart)/(endTimePatient - startTimePatient) ]) resultFile.flush() endTime = time.time() print("Generation completed. Elapsed time: {duration:.2f} sec".format(duration=endTime-startTime)) print("Uploaded {n} files -> {p:.2f} files/sec".format(n=self._fileCounter, p=self._fileCounter/(endTime-startTime))) def createStudy(self, studyIndex: int, patientIndex: int, seriesCount: int, instancesPerSeries: int): for seriesIndex in range(0, seriesCount): for instanceIndex in range(0, instancesPerSeries): dicomFile = self.createDicomFile(patientIndex=patientIndex, studyIndex=studyIndex, seriesIndex=seriesIndex, instanceIndex=instanceIndex) self._orthanc.uploadDicom(dicomFile) def createDicomFile(self, patientIndex: int, studyIndex: int, seriesIndex: int, instanceIndex: int) -> object: self._fileCounter += 1 return self._orthanc.instances.modify( instanceId=self._sourceInstanceId, replaceTags={ "PatientName": "Patient-" + str(patientIndex), "PatientID": str(patientIndex), "StudyDescription": str(patientIndex) + "-" + str(studyIndex), "SeriesDescription": str(patientIndex) + "-" + str(studyIndex) + "-" + str(seriesIndex), "SOPInstanceUID": str(patientIndex) + "." + str(studyIndex) + "." + str(seriesIndex) + "." + str(instanceIndex), "StudyInstanceUID": str(patientIndex) + "." + str(studyIndex), "SeriesInstanceUID": str(patientIndex) + "." + str(studyIndex) + "." + str(seriesIndex), "SeriesNumber": str(seriesIndex), "InstanceNumber": str(instanceIndex) }, deleteOriginal=False )