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import abc 

 

import numpy as np 

 

import unittest 

import lsst.utils.tests 

 

import lsst.afw.geom 

from lsst.jointcal import photometryTransfo 

 

 

12 ↛ exit,   12 ↛ exit,   12 ↛ exit,   12 ↛ exit,   12 ↛ exit,   12 ↛ exit6 missed branches: 1) line 18 didn't finish the lambda on line 18, 2) line 17 didn't finish the lambda on line 17, 3) line 16 didn't finish the lambda on line 16, 4) line 15 didn't finish the lambda on line 15, 5) line 14 didn't finish the lambda on line 14, 6) line 13 didn't finish the lambda on line 13CHEBYSHEV_T = [ 

lambda x: 1, 

lambda x: x, 

lambda x: 2*x**2 - 1, 

lambda x: (4*x**2 - 3)*x, 

lambda x: (8*x**2 - 8)*x**2 + 1, 

lambda x: ((16*x**2 - 20)*x**2 + 5)*x, 

] 

 

 

class PhotometryTransfoTestBase: 

def setUp(self): 

self.value = 5.0 

self.valueError = 0.3 

self.point = [1., 5.] 

 

 

class SpatiallyInvariantTestBase(PhotometryTransfoTestBase): 

"""Tests for PhotometryTransfoSpatiallyInvariant. 

Subclasses need to call setUp to define: 

self.transfo1 == a default initalized PhotometryTransfoSpatiallyInvariant. 

self.transfo2 == a transfo initialized with self.t2InitValue. 

""" 

def setUp(self): 

super().setUp() 

# initial values for self.transfo2 

self.t2InitValue = 1000.0 

self.t2InitError = 70.0 

 

def _test_transform(self, transfo, expect): 

result = transfo.transform(self.point[0], self.point[1], self.value) 

self.assertEqual(result, expect) # yes, I really mean exactly equal 

 

def _test_transformError(self, transfo, expect): 

result = transfo.transformError(self.point[0], self.point[1], self.value, self.valueError) 

self.assertFloatsAlmostEqual(result, expect) 

 

def _offsetParams(self, delta, value, expect): 

self.transfo1.offsetParams(delta) 

result = self.transfo1.transform(self.point[0], self.point[1], value) 

self.assertFloatsAlmostEqual(result, expect) 

 

def _test_offsetParams(self, expect): 

"""Test offsetting; note that offsetParams offsets by +1.""" 

# check that offset by 0 doesn't change anything. 

delta = np.zeros(1, dtype=float) 

self._offsetParams(delta, self.value, self.value) 

 

# offset by +1 should result in `expect` 

delta -= 1 

self._offsetParams(delta, self.value, expect) 

 

def test_clone(self): 

clone1 = self.transfo1.clone() 

self.assertEqual(self.transfo1.getParameters(), clone1.getParameters()) 

clone2 = self.transfo2.clone() 

self.assertEqual(self.transfo2.getParameters(), clone2.getParameters()) 

self.assertNotEqual(clone1.getParameters(), clone2.getParameters()) 

 

def _test_computeParameterDerivatives(self, expect): 

"""The derivative of a spatially invariant transform is always the same. 

Should be indepdendent of position 

""" 

result = self.transfo1.computeParameterDerivatives(1, 2, self.value) 

self.assertEqual(expect, result) 

result = self.transfo1.computeParameterDerivatives(-5, -100, self.value) 

self.assertEqual(expect, result) 

result = self.transfo2.computeParameterDerivatives(-1000, 150, self.value) 

self.assertEqual(expect, result) 

 

 

class FluxTransfoSpatiallyInvariantTestCase(SpatiallyInvariantTestBase, lsst.utils.tests.TestCase): 

def setUp(self): 

super().setUp() 

self.transfo1 = photometryTransfo.FluxTransfoSpatiallyInvariant() 

self.transfo2 = photometryTransfo.FluxTransfoSpatiallyInvariant(self.t2InitValue) 

 

def test_transform(self): 

self._test_transform(self.transfo1, self.value) 

self._test_transform(self.transfo2, self.value*self.t2InitValue) 

 

def test_transformError(self): 

expect = (self.valueError*1) 

self._test_transformError(self.transfo1, expect) 

expect = (self.valueError*self.t2InitValue) 

self._test_transformError(self.transfo2, expect) 

 

def test_offsetParams(self): 

"""Offset by +1 means transform by 2.""" 

self._test_offsetParams(self.value*2) 

 

def test_computeParameterDerivatives(self): 

"""Should be indepdendent of position, and equal to the flux.""" 

self._test_computeParameterDerivatives(self.value) 

 

 

class MagnitudeTransfoSpatiallyInvariantTestCase(SpatiallyInvariantTestBase, lsst.utils.tests.TestCase): 

def setUp(self): 

super().setUp() 

self.transfo1 = photometryTransfo.MagnitudeTransfoSpatiallyInvariant() 

self.transfo2 = photometryTransfo.MagnitudeTransfoSpatiallyInvariant(self.t2InitValue) 

 

def test_transform(self): 

self._test_transform(self.transfo1, self.value) 

self._test_transform(self.transfo2, self.value + self.t2InitValue) 

 

def test_transformError(self): 

expect = self.valueError 

self._test_transformError(self.transfo1, expect) 

expect = self.valueError 

self._test_transformError(self.transfo2, expect) 

 

def test_offsetParams(self): 

"""Offset by +1 means transform by +1.""" 

self._test_offsetParams(self.value + 1) 

 

def test_computeParameterDerivatives(self): 

"""Should always be identically 1.""" 

self._test_computeParameterDerivatives(1.0) 

 

 

class PhotometryTransfoChebyshevTestCase(PhotometryTransfoTestBase, abc.ABC): 

def setUp(self): 

"""Call this first, then construct self.transfo1 from self.order1, 

and self.transfo2 from self.coefficients. 

""" 

super().setUp() 

self.bbox = lsst.afw.geom.Box2D(lsst.afw.geom.Point2D(-5, -6), lsst.afw.geom.Point2D(7, 8)) 

self.order1 = 2 

self.coefficients = np.array([[5, 3], [4, 0]], dtype=float) 

 

# self.transfo1 will have 6 parameters, by construction 

self.delta = np.arange(6, dtype=float) 

# make one of them have opposite sign to check +/- consistency 

self.delta[0] = -self.delta[0] 

 

def test_getNpar(self): 

self.assertEqual(self.transfo1.getNpar(), 6) 

self.assertEqual(self.transfo2.getNpar(), 3) 

 

def _evaluate_chebyshev(self, x, y): 

"""Evaluate the chebyshev defined by self.coefficients at (x,y)""" 

# sx, sy: transform from self.bbox range to [-1, -1] 

cx = (self.bbox.getMinX() + self.bbox.getMaxX())/2.0 

cy = (self.bbox.getMinY() + self.bbox.getMaxY())/2.0 

sx = 2.0 / self.bbox.getWidth() 

sy = 2.0 / self.bbox.getHeight() 

result = 0 

order = len(self.coefficients) 

for j in range(order): 

for i in range(0, order-j): 

Tx = CHEBYSHEV_T[i](sx*(x - cx)) 

Ty = CHEBYSHEV_T[j](sy*(y - cy)) 

result += self.coefficients[j, i]*Tx*Ty 

return result 

 

def _test_offsetParams(self, expect): 

"""Test offsetting; note that offsetParams offsets by `-delta`. 

 

Parameters 

---------- 

expect1 : `numpy.ndarray`, (N,2) 

Expected coefficients from an offset by 0. 

expect2 : `numpy.ndarray`, (N,2) 

Expected coefficients from an offset by self.delta. 

""" 

# first offset by all zeros: nothing should change 

delta = np.zeros(self.transfo1.getNpar(), dtype=float) 

self.transfo1.offsetParams(delta) 

self.assertFloatsAlmostEqual(expect, self.transfo1.getCoefficients()) 

 

# now offset by self.delta 

expect[0, 0] -= self.delta[0] 

expect[0, 1] -= self.delta[1] 

expect[0, 2] -= self.delta[2] 

expect[1, 0] -= self.delta[3] 

expect[1, 1] -= self.delta[4] 

expect[2, 0] -= self.delta[5] 

self.transfo1.offsetParams(self.delta) 

self.assertFloatsAlmostEqual(expect, self.transfo1.getCoefficients()) 

 

def test_clone(self): 

clone1 = self.transfo1.clone() 

self.assertFloatsEqual(self.transfo1.getParameters(), clone1.getParameters()) 

self.assertEqual(self.transfo1.getOrder(), clone1.getOrder()) 

self.assertEqual(self.transfo1.getBBox(), clone1.getBBox()) 

clone2 = self.transfo2.clone() 

self.assertFloatsEqual(self.transfo2.getParameters(), clone2.getParameters()) 

self.assertEqual(self.transfo2.getOrder(), clone2.getOrder()) 

self.assertEqual(self.transfo2.getBBox(), clone2.getBBox()) 

 

@abc.abstractmethod 

def _computeChebyshevDerivative(self, Tx, Ty, value): 

"""Return the derivative of chebyshev component Tx, Ty.""" 

pass 

 

def test_computeParameterDerivatives(self): 

cx = (self.bbox.getMinX() + self.bbox.getMaxX())/2.0 

cy = (self.bbox.getMinY() + self.bbox.getMaxY())/2.0 

sx = 2.0 / self.bbox.getWidth() 

sy = 2.0 / self.bbox.getHeight() 

result = self.transfo1.computeParameterDerivatives(self.point[0], self.point[1], self.value) 

Tx = np.array([CHEBYSHEV_T[i](sx*(self.point[0] - cx)) for i in range(self.order1+1)], dtype=float) 

Ty = np.array([CHEBYSHEV_T[i](sy*(self.point[1] - cy)) for i in range(self.order1+1)], dtype=float) 

expect = [] 

for j in range(len(Ty)): 

for i in range(0, self.order1-j+1): 

expect.append(self._computeChebyshevDerivative(Ty[j], Tx[i], self.value)) 

self.assertFloatsAlmostEqual(np.array(expect), result) 

 

 

class FluxTransfoChebyshevTestCase(PhotometryTransfoChebyshevTestCase, lsst.utils.tests.TestCase): 

def setUp(self): 

super().setUp() 

self.transfo1 = photometryTransfo.FluxTransfoChebyshev(self.order1, self.bbox) 

self.transfo2 = photometryTransfo.FluxTransfoChebyshev(self.coefficients, self.bbox) 

 

def test_transform(self): 

result = self.transfo1.transform(self.point[0], self.point[1], self.value) 

self.assertEqual(result, self.value) # transfo1 is the identity 

 

result = self.transfo2.transform(self.point[0], self.point[1], self.value) 

expect = self.value*self._evaluate_chebyshev(self.point[0], self.point[1]) 

self.assertEqual(result, expect) 

 

def test_offsetParams(self): 

# an offset by 0 means we will still have 1 only in the 0th parameter 

expect = np.zeros((self.order1+1, self.order1+1), dtype=float) 

expect[0, 0] = 1 

self._test_offsetParams(expect) 

 

def _computeChebyshevDerivative(self, x, y, value): 

return x * y * value 

 

 

class MagnitudeTransfoChebyshevTestCase(PhotometryTransfoChebyshevTestCase, lsst.utils.tests.TestCase): 

def setUp(self): 

super().setUp() 

self.transfo1 = photometryTransfo.MagnitudeTransfoChebyshev(self.order1, self.bbox) 

self.transfo2 = photometryTransfo.MagnitudeTransfoChebyshev(self.coefficients, self.bbox) 

 

def test_transform(self): 

result = self.transfo1.transform(self.point[0], self.point[1], self.value) 

self.assertEqual(result, self.value) # transfo1 is the identity 

 

result = self.transfo2.transform(self.point[0], self.point[1], self.value) 

expect = self.value + self._evaluate_chebyshev(self.point[0], self.point[1]) 

self.assertEqual(result, expect) 

 

def test_offsetParams(self): 

# an offset by 0 means all parameters still 0 

expect = np.zeros((self.order1+1, self.order1+1), dtype=float) 

self._test_offsetParams(expect) 

 

def _computeChebyshevDerivative(self, x, y, value): 

return x * y 

 

 

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

pass 

 

 

def setup_module(module): 

lsst.utils.tests.init() 

 

 

278 ↛ 279line 278 didn't jump to line 279, because the condition on line 278 was never trueif __name__ == "__main__": 

lsst.utils.tests.init() 

unittest.main()