def __getPixmap(self):
if self.__pixmap is not None:
return self.__pixmap
calibrant = self.__getConfiguredCalibrant()
if calibrant is None:
return None
tths = numpy.array(calibrant.get_2th())
tth_min, tth_max = 0, numpy.pi
size = 360
agregation = numpy.zeros((1, size))
for tth in tths:
pos = int((tth - tth_min) / (tth_max - tth_min) * size)
if pos < 0:
continue
if pos >= size:
continue
agregation[0, pos] += 1
agregation = -agregation
colormap = Colormap()
rgbImage = colormap.applyToData(agregation)[:, :, :3]
qimage = imageutils.convertArrayToQImage(rgbImage)
qpixmap = qt.QPixmap.fromImage(qimage)
self.__pixmap = qpixmap
return self.__pixmap
def testAutoscaleFromDataReference(self):
colormap = Colormap(name='gray', normalization='linear')
data = numpy.array([50])
reference = numpy.array([0, 100])
value = colormap.applyToData(data, reference)
self.assertEqual(len(value), 1)
self.assertEqual(value[0, 0], 128)
def __getPixmap(self):
if self.__pixmap is not None:
return self.__pixmap
calibrant = self.__getConfiguredCalibrant()
if calibrant is None:
return None
tths = numpy.array(calibrant.get_2th())
tth_min, tth_max = 0, numpy.pi
size = 360
agregation = numpy.zeros((1, size))
for tth in tths:
pos = int((tth - tth_min) / (tth_max - tth_min) * size)
if pos < 0:
continue
if pos >= size:
continue
agregation[0, pos] += 1
agregation = -agregation
colormap = Colormap()
rgbImage = colormap.applyToData(agregation)[:, :, :3]
qimage = imageutils.convertArrayToQImage(rgbImage)
qpixmap = qt.QPixmap.fromImage(qimage)
self.__pixmap = qpixmap
return self.__pixmap
def testAutoscaleFromItemReference(self):
colormap = Colormap(name='gray', normalization='linear')
data = numpy.array([50])
image = items.ImageData()
image.setData(numpy.array([[0, 100]]))
value = colormap.applyToData(data, reference=image)
self.assertEqual(len(value), 1)
self.assertEqual(value[0, 0], 128)
def testNaNColor(self):
"""Test Colormap.applyToData with NaN values"""
colormap = Colormap(name='gray', normalization='linear')
colormap.setNaNColor('red')
self.assertEqual(colormap.getNaNColor(), qt.QColor(255, 0, 0))
data = numpy.array([50., numpy.nan])
image = items.ImageData()
image.setData(numpy.array([[0, 100]]))
value = colormap.applyToData(data, reference=image)
self.assertEqual(len(value), 2)
self.assertTrue(numpy.array_equal(value[0], (128, 128, 128, 255)))
self.assertTrue(numpy.array_equal(value[1], (255, 0, 0, 255)))
def testApplyColormapToData(self):
"""Simple test of applyColormapToData function"""
colormap = Colormap(name='gray', normalization='linear',
vmin=0, vmax=255)
size = 10
expected = numpy.empty((size, 4), dtype='uint8')
expected[:, 0] = numpy.arange(size, dtype='uint8')
expected[:, 1] = expected[:, 0]
expected[:, 2] = expected[:, 0]
expected[:, 3] = 255
for dtype in ('uint8', 'int32', 'float32', 'float64'):
with self.subTest(dtype=dtype):
array = numpy.arange(size, dtype=dtype)
result = colormap.applyToData(data=array)
self.assertTrue(numpy.all(numpy.equal(result, expected)))
def testApplyColormapToData(self):
"""Simple test of applyColormapToData function"""
colormap = Colormap(name='gray', normalization='linear',
vmin=0, vmax=255)
size = 10
expected = numpy.empty((size, 4), dtype='uint8')
expected[:, 0] = numpy.arange(size, dtype='uint8')
expected[:, 1] = expected[:, 0]
expected[:, 2] = expected[:, 0]
expected[:, 3] = 255
for dtype in ('uint8', 'int32', 'float32', 'float64'):
with self.subTest(dtype=dtype):
array = numpy.arange(size, dtype=dtype)
result = colormap.applyToData(data=array)
self.assertTrue(numpy.all(numpy.equal(result, expected)))
def __getPixmap(self, size=360):
if self.__pixmap is not None and self.__cachedSize == size:
return self.__pixmap
calibrant = self.__getConfiguredCalibrant()
if calibrant is None:
return None
tths = numpy.array(calibrant.get_2th())
tth_min, tth_max = 0, numpy.pi
histo = numpy.histogram(tths, bins=size, range=(tth_min, tth_max))
agregation = histo[0].reshape(1, -1)
colormap = Colormap(name="reversed gray",
vmin=agregation.min(),
vmax=agregation.max())
rgbImage = colormap.applyToData(agregation)[:, :, :3]
qimage = imageutils.convertArrayToQImage(rgbImage)
qpixmap = qt.QPixmap.fromImage(qimage)
self.__pixmap = qpixmap
self.__cachedSize = size
return self.__pixmap
def testApplyToData(self):
"""Test applyToData on different datasets"""
datasets = [
numpy.zeros((0, 0)), # Empty array
numpy.array((numpy.nan, numpy.inf)), # All non-finite
numpy.array((-numpy.inf, numpy.inf, 1.0, 2.0)), # Some infinite
]
for normalization in ('linear', 'log'):
colormap = Colormap(name='gray',
normalization=normalization,
vmin=None,
vmax=None)
for data in datasets:
with self.subTest(data=data):
image = colormap.applyToData(data)
self.assertEqual(image.dtype, numpy.uint8)
self.assertEqual(image.shape[-1], 4)
self.assertEqual(image.shape[:-1], data.shape)
def testApplyToData(self):
"""Test applyToData on different datasets"""
datasets = [
numpy.zeros((0, 0)), # Empty array
numpy.array((numpy.nan, numpy.inf)), # All non-finite
numpy.array((-numpy.inf, numpy.inf, 1.0, 2.0)), # Some infinite
]
for normalization in ('linear', 'log'):
colormap = Colormap(name='gray',
normalization=normalization,
vmin=None,
vmax=None)
for data in datasets:
with self.subTest(data=data):
image = colormap.applyToData(data)
self.assertEqual(image.dtype, numpy.uint8)
self.assertEqual(image.shape[-1], 4)
self.assertEqual(image.shape[:-1], data.shape)
