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Merge pull request datashield#618 from StuartWheater/v6.3.5-dev
General updates and reworkings
2 parents 78d3b4d + 816fc5d commit fe012e4

8 files changed

Lines changed: 60 additions & 143 deletions

azure-pipelines.yml

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@@ -3,11 +3,9 @@
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# Starts with a vanilla Opal docker composition, installs dsBase
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# and dsBaseClient (as well as dependencies - including a fully functional
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# Opal server).
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# Does checks and tests then saves results to testStatus repo.
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#
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# Inside the root directory $(Pipeline.Workspace) will be a file tree like:
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# /dsBaseClient <- Checked out version of datashield/dsBaseClient
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# /testStatus <- Checked out version of datashield/testStatus
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# /logs <- Where results of tests and lots are collated
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#
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# As of May 2020 this takes ~ 70 mins to run.
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_r_check_system_clock_: 0
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#########################################################################################
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# Need to define all the GH repos and their access tokens, see:
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# https://docs.microsoft.com/en-us/azure/devops/pipelines/library/service-endpoints?view=azure-devops&tabs=yaml
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resources:
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repositories:
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- repository: testStatusRepo
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type: github
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endpoint: datashield-testing
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name: datashield/testStatus
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ref: master
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#########################################################################################
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# When and under what condition to run the pipeline.
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schedules:
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- checkout: self
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path: 'dsBaseClient'
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- checkout: testStatusRepo
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path: 'testStatus'
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persistCredentials: true
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condition: and(eq(variables['Build.Repository.Name'], 'datashield/dsBaseClient'), ne(variables['Build.Reason'], 'PullRequest'))
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#####################################################################################
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# The MySQL install that comes with the VM doesn't seem compatable with our set up
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displayName: 'Down Opal Docker Composition'
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condition: succeeded()
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#####################################################################################
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# Windup phase
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#####################################################################################
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#####################################################################################
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# Output some important version numbers to file. This gets added to the testStatus
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# commit so it can be parsed and used on the status table.
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- bash: |
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echo 'branch:'$(branchName) >> $(datetime).txt
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echo 'os:'$(lsb_release -ds) >> $(datetime).txt
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echo 'R:'$(R --version | head -n 1) >> $(datetime).txt
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echo 'opal:'$(opal system --opal localhost:8443 --user administrator --password "datashield_test&" --version) >> $(datetime).txt
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workingDirectory: $(Pipeline.Workspace)/logs
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displayName: 'Write versions to file'
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condition: succeededOrFailed()
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#####################################################################################
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# Checkout the testStatus repo, add the results from here, push back to GH.
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# TODO: Automatically pull in better email/name info from somewhere.
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# TODO: More debug info in commit message
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- bash: |
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# Git needs some config set to be able to push to a repo.
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git config --global user.email "you@example.com"
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git config --global user.name "Azure pipeline"
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# This repo is checked out in detatched head state, so reconnect it here.
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git checkout master
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# It is possible that other commits have been made to the testStatus repo since it
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# was checked out. i.e. other pipeline runs might have finished.
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git pull
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# Make the directories if they dont already exist
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mkdir --parents logs/$(projectName)/$(branchName)
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mkdir --parents docs/$(projectName)/$(branchName)/latest
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cp $(Pipeline.Workspace)/logs/coveragelist.csv logs/$(projectName)/$(branchName)/
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cp $(Pipeline.Workspace)/logs/coveragelist.csv logs/$(projectName)/$(branchName)/$(datetime).csv
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cp $(Pipeline.Workspace)/logs/test_results.xml logs/$(projectName)/$(branchName)/
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cp $(Pipeline.Workspace)/logs/test_results.xml logs/$(projectName)/$(branchName)/$(datetime).xml
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cp $(Pipeline.Workspace)/logs/$(datetime).txt logs/$(projectName)/$(branchName)/
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# Run the script to parse the results and build the html pages.
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# status.py JUnit_file.xml coverage_file.csv output_file.html local_repo_path remote_repo_name branch
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source/status.py logs/$(projectName)/$(branchName)/$(datetime).xml logs/$(projectName)/$(branchName)/$(datetime).csv logs/$(projectName)/$(branchName)/$(datetime).txt status.html $(Pipeline.Workspace)/$(projectName) $(projectName) $(branchName)
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cp status.html docs/$(projectName)/$(branchName)/latest/index.html
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git add logs/$(projectName)/$(branchName)/coveragelist.csv
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git add logs/$(projectName)/$(branchName)/test_results.xml
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git add logs/$(projectName)/$(branchName)/$(datetime).xml
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git add logs/$(projectName)/$(branchName)/$(datetime).csv
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git add logs/$(projectName)/$(branchName)/$(datetime).txt
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git add docs/$(projectName)/$(branchName)/latest/index.html
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git commit -m "Azure auto test for $(projectName)/$(branchName) @ $(datetime)" -m "Debug info:\nProjectName:$(projectName)\nBranchName:$(branchName)\nDataTime:$(datetime)"
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git push
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exit 0
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workingDirectory: $(Pipeline.Workspace)/testStatus
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displayName: 'Parse test results'
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condition: and(eq(variables['Build.Repository.Name'], 'datashield/dsBaseClient'), ne(variables['Build.Reason'], 'PullRequest'))
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#####################################################################################
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# Output the environment information to the console. This is useful for debugging.
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# Always do this, even if some of the above has failed or the job has been cacelled.

docker-compose_armadillo.yml

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hostname: armadillo
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ports:
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- 8080:8080
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image: datashield/armadillo_citest:latest
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image: datashield/armadillo_citest:5.9.4
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environment:
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LOGGING_CONFIG: 'classpath:logback-file.xml'
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AUDIT_LOG_PATH: '/app/logs/audit.log'

docker-compose_opal.yml

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- MONGO_INITDB_ROOT_USERNAME=root
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- MONGO_INITDB_ROOT_PASSWORD=foobar
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rock:
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image: datashield/rock-omicron-karma-permissive:devel
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image: datashield/rock-lemon-donkey-permissive:draft
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environment:
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DEBUG: "FALSE"
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"refer_name","rate","lower_tolerance","upper_tolerance"
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"conndisconn::perf::simple0","0.1275","0.5","2"
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"ds.abs::perf::0","4.824","0.5","2"
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"ds.asInteger::perf:0","4.366","0.5","2"
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"ds.asList::perf:0","9.787","0.5","2"
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"ds.asNumeric::perf:0","4.316","0.5","2"
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"ds.assign::perf::0","8.055","0.5","2"
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"ds.class::perf::combine:0","9.847","0.5","2"
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"ds.colnames::perf:0","7.574","0.5","2"
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"ds.exists::perf::combine:0","19.84","0.5","2"
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"ds.length::perf::combine:0","19.58","0.5","2"
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"ds.mean::perf::combine:0","19.66","0.5","2"
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"ds.mean::perf::split:0","19.21","0.5","2"
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"void::perf::void::0","41810.0","0.5","2"
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"conndisconn::perf::simple0","0.1225","0.5","2"
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"ds.abs::perf::0","5.820","0.5","2"
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"ds.asInteger::perf:0","5.328","0.5","2"
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"ds.asList::perf:0","11.71","0.5","2"
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"ds.asNumeric::perf:0","5.268","0.5","2"
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"ds.assign::perf::0","9.229","0.5","2"
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"ds.class::perf::combine:0","10.84","0.5","2"
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"ds.colnames::perf:0","7.993","0.5","2"
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"ds.exists::perf::combine:0","21.68","0.5","2"
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"ds.length::perf::combine:0","21.84","0.5","2"
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"ds.mean::perf::combine:0","22.01","0.5","2"
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"ds.mean::perf::split:0","22.22","0.5","2"
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"void::perf::void::0","48520.0","0.5","2"
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"refer_name","rate","lower_tolerance","upper_tolerance"
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"conndisconn::perf::simple0","0.06225260028207","0.5","2"
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"ds.abs::perf::0","2.602332538044","0.5","2"
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"ds.asInteger::perf:0","2.16574645464856","0.5","2"
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"ds.asList::perf:0","5.125787987349","0.5","2"
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"ds.asNumeric::perf:0","2.02140793909654","0.5","2"
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"ds.assign::perf::0","4.25379741119624","0.5","2"
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"ds.class::perf::combine:0","5.03264832363257","0.5","2"
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"ds.colnames::perf:0","3.61308626946146","0.5","2"
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"ds.exists::perf::combine:0","8.47538336211864","0.5","2"
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"ds.length::perf::combine:0","9.49818979827918","0.5","2"
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"ds.mean::perf::combine:0","9.66558925664494","0.5","2"
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"ds.mean::perf::split:0","8.6304479562724","0.5","2"
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"void::perf::void::0","19351.7615914652","0.5","2"
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"conndisconn::perf::simple0","0.04918","0.5","2"
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"ds.abs::perf::0","1.184","0.5","2"
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"ds.asInteger::perf:0","1.297","0.5","2"
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"ds.asList::perf:0","2.884","0.5","2"
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"ds.asNumeric::perf:0","1.354","0.5","2"
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"ds.assign::perf::0","2.745","0.5","2"
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"ds.class::perf::combine:0","3.261","0.5","2"
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"ds.colnames::perf:0","2.404","0.5","2"
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"ds.exists::perf::combine:0","6.342","0.5","2"
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"ds.length::perf::combine:0","7.835","0.5","2"
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"ds.mean::perf::combine:0","8.127","0.5","2"
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"ds.mean::perf::split:0","8.109","0.5","2"
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"void::perf::void::0","20280.0","0.5","2"
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"refer_name","rate","lower_tolerance","upper_tolerance"
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"conndisconn::perf::simple0","0.2118","0.5","2"
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"ds.abs::perf::0","1.718","0.5","2"
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"ds.asInteger::perf:0","1.484","0.5","2"
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"ds.asList::perf:0","3.050","0.5","2"
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"ds.asNumeric::perf:0","1.508","0.5","2"
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"ds.assign::perf::0","3.547","0.5","2"
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"ds.class::perf::combine:0","3.061","0.5","2"
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"ds.colnames::perf:0","2.456","0.5","2"
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"ds.exists::perf::combine:0","6.904","0.5","2"
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"ds.length::perf::combine:0","6.058","0.5","2"
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"ds.mean::perf::combine:0","5.892","0.5","2"
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"ds.mean::perf::split:0","6.881","0.5","2"
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"void::perf::void::0","27070.0","0.5","2"
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"conndisconn::perf::simple0","0.2725","0.5","2"
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"ds.abs::perf::0","2.677","0.5","2"
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"ds.asInteger::perf:0","2.294","0.5","2"
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"ds.asList::perf:0","4.587","0.5","2"
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"ds.asNumeric::perf:0","2.185","0.5","2"
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"ds.assign::perf::0","5.490","0.5","2"
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"ds.class::perf::combine:0","4.760","0.5","2"
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"ds.colnames::perf:0","4.159","0.5","2"
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"ds.exists::perf::combine:0","11.09","0.5","2"
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"ds.length::perf::combine:0","9.479","0.5","2"
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"ds.mean::perf::combine:0","9.650","0.5","2"
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"ds.mean::perf::split:0","11.26","0.5","2"
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"void::perf::void::0","46250.0","0.5","2"
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"refer_name","rate","lower_tolerance","upper_tolerance"
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"conndisconn::perf::simple0","0.2118","0.5","2"
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"ds.abs::perf::0","1.718","0.5","2"
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"ds.asInteger::perf:0","1.484","0.5","2"
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"ds.asList::perf:0","3.050","0.5","2"
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"ds.asNumeric::perf:0","1.508","0.5","2"
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"ds.assign::perf::0","3.547","0.5","2"
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"ds.class::perf::combine:0","3.061","0.5","2"
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"ds.colnames::perf:0","2.456","0.5","2"
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"ds.exists::perf::combine:0","6.904","0.5","2"
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"ds.length::perf::combine:0","6.058","0.5","2"
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"ds.mean::perf::combine:0","5.892","0.5","2"
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"ds.mean::perf::split:0","6.881","0.5","2"
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"void::perf::void::0","27070.0","0.5","2"
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"conndisconn::perf::simple0","0.2725","0.5","2"
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"ds.abs::perf::0","2.677","0.5","2"
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"ds.asInteger::perf:0","2.294","0.5","2"
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"ds.asList::perf:0","4.587","0.5","2"
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"ds.asNumeric::perf:0","2.185","0.5","2"
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"ds.assign::perf::0","5.490","0.5","2"
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"ds.class::perf::combine:0","4.760","0.5","2"
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"ds.colnames::perf:0","4.159","0.5","2"
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"ds.exists::perf::combine:0","11.09","0.5","2"
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"ds.length::perf::combine:0","9.479","0.5","2"
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"ds.mean::perf::combine:0","9.650","0.5","2"
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"ds.mean::perf::split:0","11.26","0.5","2"
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"void::perf::void::0","46250.0","0.5","2"

tests/testthat/test-smk-ds.mice.R

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8282
expect_length(newImp$sim2, 3)
8383
expect_length(newImp$sim3, 3)
8484
expect_true("character" %in% class(newImp$sim1$method))
85-
expect_equal(as.character(newImp$sim1$method), c("pmm","norm","pmm","pmm","pmm","","","","","","polyreg"))
85+
if (ds.test_env$driver == "OpalDriver")
86+
expect_equal(as.character(newImp$sim1$method), c("pmm","norm","pmm","pmm","pmm","","","","","","polyreg"))
87+
else if (ds.test_env$driver == "ArmadilloDriver")
88+
expect_equal(as.character(newImp$sim1$method), c("pmm","norm","pmm","pmm","pmm","","","","","",""))
89+
else
90+
expect_equal(as.character(newImp$sim1$method), c("pmm","norm","pmm","pmm","pmm","","","","","","polyreg"))
8691
expect_true("matrix" %in% class(newImp$sim1$predictorMatrix))
8792
expect_true("array" %in% class(newImp$sim1$predictorMatrix))
8893
expect_equal(as.numeric(newImp$sim1$predictorMatrix[,1]), c(0,1,1,1,1,1,1,1,1,1,1))

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