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# This file is part of ctrl_mpexec. 

# 

# Developed for the LSST Data Management System. 

# This product includes software developed by the LSST Project 

# (https://www.lsst.org). 

# See the COPYRIGHT file at the top-level directory of this distribution 

# for details of code ownership. 

# 

# This program is free software: you can redistribute it and/or modify 

# it under the terms of the GNU General Public License as published by 

# the Free Software Foundation, either version 3 of the License, or 

# (at your option) any later version. 

# 

# This program is distributed in the hope that it will be useful, 

# but WITHOUT ANY WARRANTY; without even the implied warranty of 

# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 

# GNU General Public License for more details. 

# 

# You should have received a copy of the GNU General Public License 

# along with this program. If not, see <https://www.gnu.org/licenses/>. 

 

"""Simple unit test for Pipeline. 

""" 

 

import io 

import unittest 

 

from lsst.pipe.base import (PipelineTask, PipelineTaskConfig, 

InputDatasetField, OutputDatasetField, 

DatasetTypeDescriptor, Pipeline, TaskDef) 

from lsst.ctrl.mpexec.dotTools import pipeline2dot 

import lsst.utils.tests 

 

 

# This method is used by PipelineTask to instantiate DatasetType, normally this 

# should come from some other module but we have not defined that yet, so I 

# stick a trivial (mock) implementation here. 

def makeDatasetTypeDescr(dsConfig): 

return DatasetTypeDescriptor(name=dsConfig.name, dimensionNames=dsConfig.dimensions, 

storageClassName=dsConfig.storageClass, 

scalar=False, manualLoad=False) 

 

 

class ExamplePipelineTaskConfig(PipelineTaskConfig): 

input1 = InputDatasetField(name="", 

dimensions=[], 

storageClass="example", 

doc="Input for this task") 

input2 = InputDatasetField(name="", 

dimensions=[], 

storageClass="example", 

doc="Input for this task") 

output1 = OutputDatasetField(name="", 

dimensions=[], 

storageClass="example", 

doc="Output for this task") 

output2 = OutputDatasetField(name="", 

dimensions=[], 

storageClass="example", 

doc="Output for this task") 

 

 

def _makeConfig(inputName, outputName): 

"""Factory method for config instances 

 

inputName and outputName can be either string or tuple of strings 

with two items max. 

""" 

config = ExamplePipelineTaskConfig() 

if isinstance(inputName, tuple): 

config.input1.name = inputName[0] 

config.input2.name = inputName[1] if len(inputName) > 1 else "" 

else: 

config.input1.name = inputName 

 

if isinstance(outputName, tuple): 

config.output1.name = outputName[0] 

config.output2.name = outputName[1] if len(outputName) > 1 else "" 

else: 

config.output1.name = outputName 

 

dimensions = ["visit", "detector"] 

config.input1.dimensions = dimensions 

config.input2.dimensions = dimensions 

config.output1.dimensions = dimensions 

config.output2.dimensions = dimensions 

 

return config 

 

 

class ExamplePipelineTask(PipelineTask): 

ConfigClass = ExamplePipelineTaskConfig 

 

@classmethod 

def getInputDatasetTypes(cls, config): 

types = {"input1": makeDatasetTypeDescr(config.input1)} 

if config.input2.name: 

types["input2"] = makeDatasetTypeDescr(config.input2) 

return types 

 

@classmethod 

def getOutputDatasetTypes(cls, config): 

types = {"output1": makeDatasetTypeDescr(config.output1)} 

if config.output2.name: 

types["output2"] = makeDatasetTypeDescr(config.output2) 

return types 

 

 

def _makePipeline(tasks): 

"""Generate Pipeline instance. 

 

Parameters 

---------- 

tasks : list of tuples 

Each tuple in the list has 3 or 4 items: 

- input DatasetType name(s), string or tuple of strings 

- output DatasetType name(s), string or tuple of strings 

- task label, string 

- optional task class object, can be None 

 

Returns 

------- 

Pipeline instance 

""" 

pipe = Pipeline() 

for task in tasks: 

inputs = task[0] 

outputs = task[1] 

label = task[2] 

klass = task[3] if len(task) > 3 else ExamplePipelineTask 

config = _makeConfig(inputs, outputs) 

pipe.append(TaskDef("ExamplePipelineTask", config, klass, label)) 

return pipe 

 

 

class DotToolsTestCase(unittest.TestCase): 

"""A test case for dotTools 

""" 

 

def testPipeline2dot(self): 

"""Tests for dotTools.pipeline2dot method 

""" 

pipeline = _makePipeline([("A", ("B", "C"), "task1"), 

("C", "E", "task2"), 

("B", "D", "task3"), 

(("D", "E"), "F", "task4")]) 

file = io.StringIO() 

pipeline2dot(pipeline, file) 

 

# it's hard to validate complete output, just checking few basic things, 

# even that is not terribly stable 

lines = file.getvalue().strip().split('\n') 

ndatasets = 6 

ntasks = 4 

nedges = 10 

nextra = 2 # graph header and closing 

self.assertEqual(len(lines), ndatasets + ntasks + nedges + nextra) 

 

 

class MyMemoryTestCase(lsst.utils.tests.MemoryTestCase): 

pass 

 

 

def setup_module(module): 

lsst.utils.tests.init() 

 

 

168 ↛ 169line 168 didn't jump to line 169, because the condition on line 168 was never trueif __name__ == "__main__": 

lsst.utils.tests.init() 

unittest.main()