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from builtins import zip 

import matplotlib 

matplotlib.use("Agg") 

import numpy as np 

import unittest 

import lsst.sims.maf.metrics as metrics 

import lsst.sims.maf.slicers as slicers 

import lsst.sims.maf.metricBundles as metricBundle 

import lsst.utils.tests 

 

 

class Test2D(unittest.TestCase): 

 

def setUp(self): 

names = ['night', 'fieldId', 'fieldRA', 'fieldDec', 'fiveSigmaDepth', 'observationStartMJD'] 

types = [int, int, float, float, float, float] 

 

self.m5_1 = 25. 

self.m5_2 = 24. 

 

self.n1 = 50 

self.n2 = 49 

 

# Picking RA and Dec values that will hit nside=16 healpixels 

self.simData = np.zeros(self.n1+self.n2, dtype=list(zip(names, types))) 

self.simData['night'][0:self.n1] = 1 

self.simData['fieldId'][0:self.n1] = 1 

self.simData['fieldRA'][0:self.n1] = 10. 

self.simData['fieldDec'][0:self.n1] = 0. 

self.simData['fiveSigmaDepth'][0:self.n1] = self.m5_1 

 

self.simData['night'][self.n1:] = 2 

self.simData['fieldId'][self.n1:] = 2 

self.simData['fieldRA'][self.n1:] = 190. 

self.simData['fieldDec'][self.n1:] = -20. 

self.simData['fiveSigmaDepth'][self.n1:] = self.m5_2 

 

self.fieldData = np.zeros(2, dtype=list(zip(['fieldId', 'fieldRA', 'fieldDec'], [int, float, float]))) 

self.fieldData['fieldId'] = [1, 2] 

self.fieldData['fieldRA'] = np.radians([10., 190.]) 

self.fieldData['fieldDec'] = np.radians([0., -20.]) 

 

self.simData['observationStartMJD'] = self.simData['night'] 

 

def testOpsim2dSlicer(self): 

metric = metrics.AccumulateCountMetric(bins=[0.5, 1.5, 2.5]) 

slicer = slicers.OpsimFieldSlicer() 

sql = '' 

mb = metricBundle.MetricBundle(metric, slicer, sql) 

# Clobber the stacker that gets auto-added 

mb.stackerList = [] 

mbg = metricBundle.MetricBundleGroup({0: mb}, None, saveEarly=False) 

mbg.setCurrent('') 

mbg.fieldData = self.fieldData 

mbg.runCurrent('', simData=self.simData) 

expected = np.array([[self.n1, self.n1], 

[-666., self.n2]]) 

assert(np.array_equal(mb.metricValues.data, expected)) 

 

def testHealpix2dSlicer(self): 

metric = metrics.AccumulateCountMetric(bins=[0.5, 1.5, 2.5]) 

slicer = slicers.HealpixSlicer(nside=16) 

sql = '' 

mb = metricBundle.MetricBundle(metric, slicer, sql) 

# Clobber the stacker that gets auto-added 

mb.stackerList = [] 

mbg = metricBundle.MetricBundleGroup({0: mb}, None, saveEarly=False) 

mbg.setCurrent('') 

mbg.runCurrent('', simData=self.simData) 

 

good = np.where(mb.metricValues.mask[:, -1] == False)[0] 

expected = np.array([[self.n1, self.n1], 

[-666., self.n2]]) 

assert(np.array_equal(mb.metricValues.data[good, :], expected)) 

 

 

def testHistogramMetric(self): 

metric = metrics.HistogramMetric(bins=[0.5, 1.5, 2.5]) 

slicer = slicers.HealpixSlicer(nside=16) 

sql = '' 

mb = metricBundle.MetricBundle(metric, slicer, sql) 

# Clobber the stacker that gets auto-added 

mb.stackerList = [] 

mbg = metricBundle.MetricBundleGroup({0: mb}, None, saveEarly=False) 

mbg.setCurrent('') 

mbg.runCurrent('', simData=self.simData) 

 

good = np.where(mb.metricValues.mask[:, -1] == False)[0] 

expected = np.array([[self.n1, 0.], 

[0., self.n2]]) 

assert(np.array_equal(mb.metricValues.data[good, :], expected)) 

 

# Check that I can run a different statistic 

metric = metrics.HistogramMetric(col='fiveSigmaDepth', 

statistic='sum', 

bins=[0.5, 1.5, 2.5]) 

mb = metricBundle.MetricBundle(metric, slicer, sql) 

# Clobber the stacker that gets auto-added 

mb.stackerList = [] 

mbg = metricBundle.MetricBundleGroup({0: mb}, None, saveEarly=False) 

mbg.setCurrent('') 

mbg.runCurrent('', simData=self.simData) 

expected = np.array([[self.m5_1*self.n1, 0.], 

[0., self.m5_2*self.n2]]) 

assert(np.array_equal(mb.metricValues.data[good, :], expected)) 

 

def testAccumulateMetric(self): 

metric = metrics.AccumulateMetric(col='fiveSigmaDepth', bins=[0.5, 1.5, 2.5]) 

slicer = slicers.HealpixSlicer(nside=16) 

sql = '' 

mb = metricBundle.MetricBundle(metric, slicer, sql) 

# Clobber the stacker that gets auto-added 

mb.stackerList = [] 

mbg = metricBundle.MetricBundleGroup({0: mb}, None, saveEarly=False) 

mbg.setCurrent('') 

mbg.runCurrent('', simData=self.simData) 

good = np.where(mb.metricValues.mask[:, -1] == False)[0] 

expected = np.array([[self.n1*self.m5_1, self.n1*self.m5_1], 

[-666., self.n2 * self.m5_2]]) 

assert(np.array_equal(mb.metricValues.data[good, :], expected)) 

 

def testHistogramM5Metric(self): 

metric = metrics.HistogramM5Metric(bins=[0.5, 1.5, 2.5]) 

slicer = slicers.HealpixSlicer(nside=16) 

sql = '' 

mb = metricBundle.MetricBundle(metric, slicer, sql) 

# Clobber the stacker that gets auto-added 

mb.stackerList = [] 

mbg = metricBundle.MetricBundleGroup({0: mb}, None, saveEarly=False) 

mbg.setCurrent('') 

mbg.runCurrent('', simData=self.simData) 

good = np.where((mb.metricValues.mask[:, 0] == False) | 

(mb.metricValues.mask[:, 1] == False))[0] 

 

checkMetric = metrics.Coaddm5Metric() 

tempSlice = np.zeros(self.n1, dtype=list(zip(['fiveSigmaDepth'], [float]))) 

tempSlice['fiveSigmaDepth'] += self.m5_1 

val1 = checkMetric.run(tempSlice) 

tempSlice = np.zeros(self.n2, dtype=list(zip(['fiveSigmaDepth'], [float]))) 

tempSlice['fiveSigmaDepth'] += self.m5_2 

val2 = checkMetric.run(tempSlice) 

 

expected = np.array([[val1, -666.], 

[-666., val2]]) 

assert(np.array_equal(mb.metricValues.data[good, :], expected)) 

 

def testAccumulateM5Metric(self): 

metric = metrics.AccumulateM5Metric(bins=[0.5, 1.5, 2.5]) 

slicer = slicers.HealpixSlicer(nside=16) 

sql = '' 

mb = metricBundle.MetricBundle(metric, slicer, sql) 

# Clobber the stacker that gets auto-added 

mb.stackerList = [] 

mbg = metricBundle.MetricBundleGroup({0: mb}, None, saveEarly=False) 

mbg.setCurrent('') 

mbg.runCurrent('', simData=self.simData) 

good = np.where(mb.metricValues.mask[:, -1] == False)[0] 

 

checkMetric = metrics.Coaddm5Metric() 

tempSlice = np.zeros(self.n1, dtype=list(zip(['fiveSigmaDepth'], [float]))) 

tempSlice['fiveSigmaDepth'] += self.m5_1 

val1 = checkMetric.run(tempSlice) 

tempSlice = np.zeros(self.n2, dtype=list(zip(['fiveSigmaDepth'], [float]))) 

tempSlice['fiveSigmaDepth'] += self.m5_2 

val2 = checkMetric.run(tempSlice) 

 

expected = np.array([[val1, val1], 

[-666., val2]]) 

assert(np.array_equal(mb.metricValues.data[good, :], expected)) 

 

def testAccumulateUniformityMetric(self): 

names = ['night'] 

types = ['float'] 

dataSlice = np.zeros(3652, dtype=list(zip(names, types))) 

 

# Test that a uniform distribution is very close to zero 

dataSlice['night'] = np.arange(1, dataSlice.size+1) 

metric = metrics.AccumulateUniformityMetric() 

result = metric.run(dataSlice) 

assert(np.max(result) < 1./365.25) 

assert(np.min(result) >= 0) 

 

# Test that if everythin on night 1 or last night, then result is ~1 

dataSlice['night'] = 1 

result = metric.run(dataSlice) 

assert(np.max(result) >= 1.-1./365.25) 

dataSlice['night'] = 3652 

result = metric.run(dataSlice) 

assert(np.max(result) >= 1.-1./365.25) 

 

# Test if all taken in the middle, result ~0.5 

dataSlice['night'] = 3652/2 

result = metric.run(dataSlice) 

assert(np.max(result) >= 0.5-1./365.25) 

 

def testRunRegularToo(self): 

""" 

Test that a binned slicer and a regular slicer can run together 

""" 

bundleList = [] 

metric = metrics.AccumulateM5Metric(bins=[0.5, 1.5, 2.5]) 

slicer = slicers.HealpixSlicer(nside=16) 

sql = '' 

bundleList.append(metricBundle.MetricBundle(metric, slicer, sql)) 

metric = metrics.Coaddm5Metric() 

slicer = slicers.HealpixSlicer(nside=16) 

bundleList.append(metricBundle.MetricBundle(metric, slicer, sql)) 

for bundle in bundleList: 

bundle.stackerList = [] 

bd = metricBundle.makeBundlesDictFromList(bundleList) 

mbg = metricBundle.MetricBundleGroup(bd, None, saveEarly=False) 

mbg.setCurrent('') 

mbg.runCurrent('', simData=self.simData) 

 

assert(np.array_equal(bundleList[0].metricValues[:, 1].compressed(), 

bundleList[1].metricValues.compressed())) 

 

 

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

pass 

 

 

def setup_module(module): 

lsst.utils.tests.init() 

 

 

227 ↛ 228line 227 didn't jump to line 228, because the condition on line 227 was never trueif __name__ == "__main__": 

lsst.utils.tests.init() 

unittest.main()