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#!/usr/bin/env python 

 

# 

# LSST Data Management System 

# 

# Copyright 2008-2017 AURA/LSST. 

# 

# This product includes software developed by the 

# LSST Project (http://www.lsst.org/). 

# 

# 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 LSST License Statement and 

# the GNU General Public License along with this program. If not, 

# see <https://www.lsstcorp.org/LegalNotices/>. 

# 

"""Test cases for cp_pipe.""" 

 

from __future__ import absolute_import, division, print_function 

import unittest 

import numpy as np 

import copy 

 

import lsst.utils 

import lsst.utils.tests 

 

import lsst.cp.pipe as cpPipe 

import lsst.ip.isr.isrMock as isrMock 

 

 

class MeasurePhotonTransferCurveTaskTestCase(lsst.utils.tests.TestCase): 

"""A test case for the PTC task.""" 

 

def setUp(self): 

self.defaultConfig = cpPipe.ptc.MeasurePhotonTransferCurveTask.ConfigClass() 

self.defaultConfig.isr.doFlat = False 

self.defaultConfig.isr.doFringe = False 

self.defaultConfig.isr.doCrosstalk = False 

self.defaultConfig.isr.doAddDistortionModel = False 

self.defaultConfig.isr.doUseOpticsTransmission = False 

self.defaultConfig.isr.doUseFilterTransmission = False 

self.defaultConfig.isr.doUseSensorTransmission = False 

self.defaultConfig.isr.doUseAtmosphereTransmission = False 

self.defaultConfig.isr.doAttachTransmissionCurve = False 

 

self.defaultTask = cpPipe.ptc.MeasurePhotonTransferCurveTask(config=self.defaultConfig) 

 

self.flatMean = 2000 

self.readNoiseAdu = 10 

mockImageConfig = isrMock.IsrMock.ConfigClass() 

 

# flatDrop is not really relevant as we replace the data 

# but good to note it in case we change how this image is made 

mockImageConfig.flatDrop = 0.99999 

mockImageConfig.isTrimmed = True 

 

self.flatExp1 = isrMock.FlatMock(config=mockImageConfig).run() 

self.flatExp2 = self.flatExp1.clone() 

(shapeY, shapeX) = self.flatExp1.getDimensions() 

 

self.flatWidth = np.sqrt(self.flatMean) + self.readNoiseAdu 

 

self.rng1 = np.random.RandomState(1984) 

flatData1 = self.rng1.normal(self.flatMean, self.flatWidth, (shapeX, shapeY)) 

self.rng2 = np.random.RandomState(666) 

flatData2 = self.rng2.normal(self.flatMean, self.flatWidth, (shapeX, shapeY)) 

 

self.flatExp1.image.array[:] = flatData1 

self.flatExp2.image.array[:] = flatData2 

 

# create fake PTC data to see if fit works, for one amp ('amp') 

flux = 1000 # ADU/sec 

timeVec = np.arange(0., 201.) 

muVec = flux*timeVec # implies that signal-chain non-linearity is zero 

self.gain = 1.5 # e-/ADU 

c1 = 1./self.gain 

self.noiseSq = 5*self.gain # 7.5 (e-)^2 

a00 = -1.2e-6 

c2 = -1.5e-6 

c3 = 1.7e-11 

 

self.fitVectorsQuadDict = {'amp': ([], [], [])} 

self.fitVectorsCubicDict = {'amp': ([], [], [])} 

self.fitVectorsAstierDict = {'amp': ([], [], [])} 

 

for (t, mu) in zip(timeVec, muVec): 

varQuad = self.noiseSq + c1*mu + c2*mu**2 

varCubic = self.noiseSq + c1*mu + c2*mu**2 + c3*mu**3 

varAstier = (0.5/(a00*self.gain*self.gain)*(np.exp(2*a00*mu*self.gain)-1) + 

self.noiseSq/(self.gain*self.gain)) 

 

self.fitVectorsQuadDict['amp'][0].append(t) 

self.fitVectorsQuadDict['amp'][1].append(mu) 

self.fitVectorsQuadDict['amp'][2].append(varQuad) 

 

self.fitVectorsCubicDict['amp'][0].append(t) 

self.fitVectorsCubicDict['amp'][1].append(mu) 

self.fitVectorsCubicDict['amp'][2].append(varCubic) 

 

self.fitVectorsAstierDict['amp'][0].append(t) 

self.fitVectorsAstierDict['amp'][1].append(mu) 

self.fitVectorsAstierDict['amp'][2].append(varAstier) 

 

def test_ptcFitQuad(self): 

config = copy.copy(self.defaultConfig) 

config.polynomialFitDegree = 2 

task = cpPipe.ptc.MeasurePhotonTransferCurveTask(config=config) 

 

_, nlDict, gainDict, noiseDict = task.fitPtcAndNl(self.fitVectorsQuadDict, 

ptcFitType='POLYNOMIAL') 

 

self.assertAlmostEqual(self.gain, gainDict['amp'][0]) 

self.assertAlmostEqual(np.sqrt(self.noiseSq)*self.gain, noiseDict['amp'][0]) 

# Linearity residual should be zero 

# nlDict[amp] = (timeVecFinal, meanVecFinal, linResidual, parsFit, parsFitErr) 

self.assertTrue(nlDict['amp'][2].all() == 0) 

 

def test_ptcFitCubic(self): 

config = copy.copy(self.defaultConfig) 

config.polynomialFitDegree = 3 

task = cpPipe.ptc.MeasurePhotonTransferCurveTask(config=config) 

_, nlDict, gainDict, noiseDict = task.fitPtcAndNl(self.fitVectorsCubicDict, 

ptcFitType='POLYNOMIAL') 

self.assertAlmostEqual(self.gain, gainDict['amp'][0]) 

self.assertAlmostEqual(np.sqrt(self.noiseSq)*self.gain, noiseDict['amp'][0]) 

self.assertTrue(nlDict['amp'][2].all() == 0) 

 

def test_ptcFitAstier(self): 

task = self.defaultTask 

 

_, nlDict, gainDict, noiseDict = task.fitPtcAndNl(self.fitVectorsAstierDict, 

ptcFitType='ASTIERAPPROXIMATION') 

 

self.assertAlmostEqual(self.gain, gainDict['amp'][0]) 

# noise already comes out of the fit in electrons 

self.assertAlmostEqual(np.sqrt(self.noiseSq), noiseDict['amp'][0]) 

self.assertTrue(nlDict['amp'][2].all() == 0) 

 

def test_meanVarMeasurement(self): 

task = self.defaultTask 

mu, varDiff = task.measureMeanVarPair(self.flatExp1, self.flatExp2) 

 

self.assertLess(self.flatWidth - np.sqrt(varDiff), 1) 

self.assertLess(self.flatMean - mu, 1) 

 

 

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

pass 

 

 

def setup_module(module): 

lsst.utils.tests.init() 

 

 

163 ↛ 164line 163 didn't jump to line 164, because the condition on line 163 was never trueif __name__ == "__main__": 

lsst.utils.tests.init() 

unittest.main()