Source code for PyMca5.tests.StackBaseTest

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__author__ = "V. Armando Sole - ESRF Data Analysis"
__contact__ = "sole@esrf.fr"
__license__ = "MIT"
__copyright__ = "European Synchrotron Radiation Facility, Grenoble, France"
import unittest
import numpy

[docs]class DummyArray(object): def __init__(self, data): """ This class forces ROI and spectra calculation to be performed as it is made for a dynamically loaded array. This allows detection of the PyMca bug track issue 3544665 """ self.data = numpy.array(data, copy=False) def __getitem__(self, *var): if len(var) == 1: return self.data[var[0]] elif len(var) == 2: return self.data[var[0], var[1]] elif len(var) == 3: return self.data[var[0], var[1], var[2]]
[docs] def getShape(self): return self.data.shape
[docs] def getDType(self): return self.data.dtype
[docs] def getSize(self): s = 1 for item in self.__shape: s *= item return s
shape = property(getShape) dtype = property(getDType) size = property(getSize)
[docs]class testStackBase(unittest.TestCase):
[docs] def testStackBaseImport(self): from PyMca5.PyMcaCore import StackBase
[docs] def testStackBaseStack1DDataHandling(self): from PyMca5.PyMcaCore import StackBase nrows = 50 ncolumns = 100 nchannels = 500 a = numpy.ones((nrows, ncolumns), numpy.float) referenceData = numpy.zeros((nrows, ncolumns, nchannels), numpy.float) for i in range(nchannels): referenceData[:, :, i] = a * i a = None mask = numpy.zeros((nrows, ncolumns), numpy.uint8) mask[20:30, 15:50] = 1 dummyArray = DummyArray(referenceData) defaultMca = referenceData.sum(axis=0, dtype=numpy.float64).sum(axis=0) maskedMca = referenceData[mask>0, :].sum(axis=0) for fileindex in [0, 1]: #usually only one file index case is used but #we test both to have a better coverage j = 0 for data in [referenceData, dummyArray]: if j == 0: dynamic = "" j = 1 else: dynamic = "dynamic " stackBase = StackBase.StackBase() stackBase.setStack(data, mcaindex=2, fileindex=fileindex) channels, counts = stackBase.getActiveCurve()[0:2] self.assertTrue(numpy.allclose(defaultMca, counts), "Incorrect %sdefault mca" % dynamic) # set mask stackBase.setSelectionMask(mask) self.assertTrue(numpy.allclose(stackBase.getSelectionMask(), mask), "Incorrect mask set and get") # get mca from mask mcaDataObject = stackBase.calculateMcaDataObject() self.assertTrue(numpy.allclose(mcaDataObject.y[0], maskedMca), "Incorrect %smca from mask calculation" % dynamic) #get image from roi i0 = 100 imiddle = 200 i1 = 400 # calculate imageDict = stackBase.calculateROIImages(i0, i1, imiddle=imiddle) self.assertTrue(numpy.allclose(imageDict['ROI'], data[:,:,i0:i1].sum(axis=-1)), "Incorrect ROI image from %sROI calculation" % dynamic) self.assertTrue(numpy.allclose(imageDict['Left'], data[:,:,i0]), "Incorrect Left image from %sROI calculation" % dynamic) self.assertTrue(numpy.allclose(imageDict['Right'], data[:,:,i1-1]), "Incorrect Right image from %sROI calculation" % dynamic) self.assertTrue(numpy.allclose(imageDict['Middle'], data[:,:,imiddle]), "Incorrect Middle image from %sROI calculation" % dynamic) stackBase = None data = None dummyArray = None referenceData = None
[docs] def testStackBaseStack2DDataHandling(self): from PyMca5.PyMcaCore import StackBase nrows = 50 ncolumns = 100 nchannels = 500 a = numpy.ones((nrows, ncolumns), numpy.float) referenceData = numpy.zeros((nchannels, nrows, ncolumns), numpy.float) for i in range(nchannels): referenceData[i] = a * i a = None mask = numpy.zeros((nrows, ncolumns), numpy.uint8) mask[20:30, 15:50] = 1 dummyArray = DummyArray(referenceData) defaultMca = referenceData.sum(axis=2, dtype=numpy.float64).sum(axis=1) maskedMca = referenceData[:,mask>0].sum(axis=1) for fileindex in [1, 2]: #usually only one file index case is used but #we test both to have a better coverage j = 0 for data in [referenceData, dummyArray]: if j == 0: dynamic = "" j = 1 else: dynamic = "dynamic " stackBase = StackBase.StackBase() stackBase.setStack(data, mcaindex=0, fileindex=fileindex) channels, counts = stackBase.getActiveCurve()[0:2] self.assertTrue(numpy.allclose(defaultMca, counts), "Incorrect %sdefault mca" % dynamic) # set mask stackBase.setSelectionMask(mask) self.assertTrue(numpy.allclose(stackBase.getSelectionMask(), mask), "Incorrect mask set and get") # get mca from mask mcaDataObject = stackBase.calculateMcaDataObject() self.assertTrue(numpy.allclose(mcaDataObject.y[0], maskedMca), "Incorrect %smca from mask calculation" % dynamic) #get image from roi i0 = 100 imiddle = 200 i1 = 400 # calculate imageDict = stackBase.calculateROIImages(i0, i1, imiddle=imiddle) self.assertTrue(numpy.allclose(imageDict['ROI'], data[i0:i1, :,:].sum(axis=0)), "Incorrect ROI image from %sROI calculation" % dynamic) self.assertTrue(numpy.allclose(imageDict['Left'], data[i0,:,:]), "Incorrect Left image from %sROI calculation" % dynamic) self.assertTrue(numpy.allclose(imageDict['Right'], data[i1-1,:,:]), "Incorrect Right image from %sROI calculation" % dynamic) self.assertTrue(numpy.allclose(imageDict['Middle'], data[imiddle,:,:]), "Incorrect Middle image from %sROI calculation" % dynamic) stackBase = None data = None dummyArray = None referenceData = None
[docs]def getSuite(auto=True): testSuite = unittest.TestSuite() if auto: testSuite.addTest(\ unittest.TestLoader().loadTestsFromTestCase(testStackBase)) else: # use a predefined order testSuite.addTest(testStackBase("testStackBaseImport")) testSuite.addTest(testStackBase("testStackBaseStack1DDataHandling")) testSuite.addTest(testStackBase("testStackBaseStack2DDataHandling")) return testSuite
[docs]def test(auto=False): unittest.TextTestRunner(verbosity=2).run(getSuite(auto=auto))
if __name__ == '__main__': test()