def _updateImage(self):
selection = self._selector.selection()
auxSigIdx = self._auxSigSlider.value()
images = [img[selection] for img in self.__signals]
image = images[auxSigIdx]
x_axis = self.__x_axis
y_axis = self.__y_axis
if x_axis is None and y_axis is None:
xcalib = NoCalibration()
ycalib = NoCalibration()
else:
if x_axis is None:
# no calibration
x_axis = numpy.arange(image.shape[1])
elif numpy.isscalar(x_axis) or len(x_axis) == 1:
# constant axis
x_axis = x_axis * numpy.ones((image.shape[1], ))
elif len(x_axis) == 2:
# linear calibration
x_axis = x_axis[0] * numpy.arange(image.shape[1]) + x_axis[1]
if y_axis is None:
y_axis = numpy.arange(image.shape[0])
elif numpy.isscalar(y_axis) or len(y_axis) == 1:
y_axis = y_axis * numpy.ones((image.shape[0], ))
elif len(y_axis) == 2:
y_axis = y_axis[0] * numpy.arange(image.shape[0]) + y_axis[1]
xcalib = ArrayCalibration(x_axis)
ycalib = ArrayCalibration(y_axis)
self._plot.setData(image)
if xcalib.is_affine():
xorigin, xscale = xcalib(0), xcalib.get_slope()
else:
_logger.warning("Unsupported complex image X axis calibration")
xorigin, xscale = 0., 1.
if ycalib.is_affine():
yorigin, yscale = ycalib(0), ycalib.get_slope()
else:
_logger.warning("Unsupported complex image Y axis calibration")
yorigin, yscale = 0., 1.
self._plot.setOrigin((xorigin, yorigin))
self._plot.setScale((xscale, yscale))
if self.__title:
title = self.__title
if len(self.__signals_names) > 1:
# Append dataset name only when there is many datasets
title += '\n' + self.__signals_names[auxSigIdx]
else:
title = self.__signals_names[auxSigIdx]
self._plot.setGraphTitle(title)
self._plot.getXAxis().setLabel(self.__x_axis_name)
self._plot.getYAxis().setLabel(self.__y_axis_name)
def _updateImage(self):
legend = self.__signal_name + "["
for sl in self._selector.selection():
if sl == slice(None):
legend += ":, "
else:
legend += str(sl) + ", "
legend = legend[:-2] + "]"
self._legend.setText("Displayed data: " + legend)
img = self._selector.selectedData()
x_axis = self.__x_axis
y_axis = self.__y_axis
if x_axis is None and y_axis is None:
xcalib = NoCalibration()
ycalib = NoCalibration()
else:
if x_axis is None:
# no calibration
x_axis = numpy.arange(img.shape[-1])
elif numpy.isscalar(x_axis) or len(x_axis) == 1:
# constant axis
x_axis = x_axis * numpy.ones((img.shape[-1], ))
elif len(x_axis) == 2:
# linear calibration
x_axis = x_axis[0] * numpy.arange(img.shape[-1]) + x_axis[1]
if y_axis is None:
y_axis = numpy.arange(img.shape[-2])
elif numpy.isscalar(y_axis) or len(y_axis) == 1:
y_axis = y_axis * numpy.ones((img.shape[-2], ))
elif len(y_axis) == 2:
y_axis = y_axis[0] * numpy.arange(img.shape[-2]) + y_axis[1]
xcalib = ArrayCalibration(x_axis)
ycalib = ArrayCalibration(y_axis)
self._plot.remove(kind=("scatter", "image"))
if xcalib.is_affine() and ycalib.is_affine():
# regular image
xorigin, xscale = xcalib(0), xcalib.get_slope()
yorigin, yscale = ycalib(0), ycalib.get_slope()
origin = (xorigin, yorigin)
scale = (xscale, yscale)
self._plot.addImage(img, legend=legend,
origin=origin, scale=scale)
else:
scatterx, scattery = numpy.meshgrid(x_axis, y_axis)
self._plot.addScatter(numpy.ravel(scatterx),
numpy.ravel(scattery),
numpy.ravel(img),
legend=legend)
self._plot.getXAxis().setLabel(self.__x_axis_name)
self._plot.getYAxis().setLabel(self.__y_axis_name)
self._plot.resetZoom()
class TestNoCalibration(unittest.TestCase):
def setUp(self):
self.calib = NoCalibration()
def testIsAffine(self):
self.assertTrue(self.calib.is_affine())
def testSlope(self):
self.assertEqual(self.calib.get_slope(), 1.)
def testYIntercept(self):
self.assertEqual(self.calib(0.), 0.)
def testCall(self):
self.assertTrue(numpy.array_equal(self.calib(X), X))
class TestNoCalibration(unittest.TestCase):
def setUp(self):
self.calib = NoCalibration()
def testIsAffine(self):
self.assertTrue(self.calib.is_affine())
def testSlope(self):
self.assertEqual(self.calib.get_slope(), 1.)
def testYIntercept(self):
self.assertEqual(self.calib(0.),
0.)
def testCall(self):
self.assertTrue(numpy.array_equal(self.calib(X), X))
def _updateVolume(self):
"""Update displayed stack according to the current axes selector
data."""
x_axis = self.__x_axis
y_axis = self.__y_axis
z_axis = self.__z_axis
offset = []
scale = []
for axis in [x_axis, y_axis, z_axis]:
if axis is None:
calibration = NoCalibration()
elif len(axis) == 2:
calibration = LinearCalibration(y_intercept=axis[0],
slope=axis[1])
else:
calibration = ArrayCalibration(axis)
if not calibration.is_affine():
_logger.warning("Axis has not linear values, ignored")
offset.append(0.)
scale.append(1.)
else:
offset.append(calibration(0))
scale.append(calibration.get_slope())
legend = self.__signal_name + "["
for sl in self._selector.selection():
if sl == slice(None):
legend += ":, "
else:
legend += str(sl) + ", "
legend = legend[:-2] + "]"
self._legend.setText("Displayed data: " + legend)
# Update SceneWidget
data = self._selector.selectedData()
volumeView = self.getVolumeView()
volumeView.setData(data, offset=offset, scale=scale)
volumeView.setAxesLabels(self.__x_axis_name, self.__y_axis_name,
self.__z_axis_name)
def _updateImage(self):
selection = self._selector.selection()
auxSigIdx = self._auxSigSlider.value()
legend = self.__signals_names[auxSigIdx]
images = [img[selection] for img in self.__signals]
image = images[auxSigIdx]
x_axis = self.__x_axis
y_axis = self.__y_axis
if x_axis is None and y_axis is None:
xcalib = NoCalibration()
ycalib = NoCalibration()
else:
if x_axis is None:
# no calibration
x_axis = numpy.arange(image.shape[1])
elif numpy.isscalar(x_axis) or len(x_axis) == 1:
# constant axis
x_axis = x_axis * numpy.ones((image.shape[1], ))
elif len(x_axis) == 2:
# linear calibration
x_axis = x_axis[0] * numpy.arange(image.shape[1]) + x_axis[1]
if y_axis is None:
y_axis = numpy.arange(image.shape[0])
elif numpy.isscalar(y_axis) or len(y_axis) == 1:
y_axis = y_axis * numpy.ones((image.shape[0], ))
elif len(y_axis) == 2:
y_axis = y_axis[0] * numpy.arange(image.shape[0]) + y_axis[1]
xcalib = ArrayCalibration(x_axis)
ycalib = ArrayCalibration(y_axis)
self._plot.remove(kind=(
"scatter",
"image",
))
if xcalib.is_affine() and ycalib.is_affine():
# regular image
xorigin, xscale = xcalib(0), xcalib.get_slope()
yorigin, yscale = ycalib(0), ycalib.get_slope()
origin = (xorigin, yorigin)
scale = (xscale, yscale)
self._plot.getXAxis().setScale('linear')
self._plot.getYAxis().setScale('linear')
self._plot.addImage(image,
legend=legend,
origin=origin,
scale=scale,
replace=True,
resetzoom=False)
else:
xaxisscale, yaxisscale = self._axis_scales
if xaxisscale is not None:
self._plot.getXAxis().setScale('log' if xaxisscale ==
'log' else 'linear')
if yaxisscale is not None:
self._plot.getYAxis().setScale('log' if yaxisscale ==
'log' else 'linear')
scatterx, scattery = numpy.meshgrid(x_axis, y_axis)
# fixme: i don't think this can handle "irregular" RGBA images
self._plot.addScatter(numpy.ravel(scatterx),
numpy.ravel(scattery),
numpy.ravel(image),
legend=legend)
if self.__title:
title = self.__title
if len(self.__signals_names) > 1:
# Append dataset name only when there is many datasets
title += '\n' + self.__signals_names[auxSigIdx]
else:
title = self.__signals_names[auxSigIdx]
self._plot.setGraphTitle(title)
self._plot.getXAxis().setLabel(self.__x_axis_name)
self._plot.getYAxis().setLabel(self.__y_axis_name)
def _updateImage(self):
selection = self._selector.selection()
auxSigIdx = self._auxSigSlider.value()
legend = self.__signals_names[auxSigIdx]
images = [img[selection] for img in self.__signals]
image = images[auxSigIdx]
x_axis = self.__x_axis
y_axis = self.__y_axis
if x_axis is None and y_axis is None:
xcalib = NoCalibration()
ycalib = NoCalibration()
else:
if x_axis is None:
# no calibration
x_axis = numpy.arange(image.shape[1])
elif numpy.isscalar(x_axis) or len(x_axis) == 1:
# constant axis
x_axis = x_axis * numpy.ones((image.shape[1], ))
elif len(x_axis) == 2:
# linear calibration
x_axis = x_axis[0] * numpy.arange(image.shape[1]) + x_axis[1]
if y_axis is None:
y_axis = numpy.arange(image.shape[0])
elif numpy.isscalar(y_axis) or len(y_axis) == 1:
y_axis = y_axis * numpy.ones((image.shape[0], ))
elif len(y_axis) == 2:
y_axis = y_axis[0] * numpy.arange(image.shape[0]) + y_axis[1]
xcalib = ArrayCalibration(x_axis)
ycalib = ArrayCalibration(y_axis)
self._plot.remove(kind=("scatter", "image",))
if xcalib.is_affine() and ycalib.is_affine():
# regular image
xorigin, xscale = xcalib(0), xcalib.get_slope()
yorigin, yscale = ycalib(0), ycalib.get_slope()
origin = (xorigin, yorigin)
scale = (xscale, yscale)
self._plot.addImage(image, legend=legend,
origin=origin, scale=scale,
replace=True)
else:
scatterx, scattery = numpy.meshgrid(x_axis, y_axis)
# fixme: i don't think this can handle "irregular" RGBA images
self._plot.addScatter(numpy.ravel(scatterx),
numpy.ravel(scattery),
numpy.ravel(image),
legend=legend)
title = ""
if self.__title:
title += self.__title
if not title.strip().endswith(self.__signals_names[auxSigIdx]):
title += "\n" + self.__signals_names[auxSigIdx]
self._plot.setGraphTitle(title)
self._plot.getXAxis().setLabel(self.__x_axis_name)
self._plot.getYAxis().setLabel(self.__y_axis_name)
self._plot.resetZoom()
def _updateImage(self):
selection = self._selector.selection()
auxSigIdx = self._auxSigSlider.value()
legend = self.__signals_names[auxSigIdx]
images = [img[selection] for img in self.__signals]
image = images[auxSigIdx]
x_axis = self.__x_axis
y_axis = self.__y_axis
if x_axis is None and y_axis is None:
xcalib = NoCalibration()
ycalib = NoCalibration()
else:
if x_axis is None:
# no calibration
x_axis = numpy.arange(image.shape[1])
elif numpy.isscalar(x_axis) or len(x_axis) == 1:
# constant axis
x_axis = x_axis * numpy.ones((image.shape[1], ))
elif len(x_axis) == 2:
# linear calibration
x_axis = x_axis[0] * numpy.arange(image.shape[1]) + x_axis[1]
if y_axis is None:
y_axis = numpy.arange(image.shape[0])
elif numpy.isscalar(y_axis) or len(y_axis) == 1:
y_axis = y_axis * numpy.ones((image.shape[0], ))
elif len(y_axis) == 2:
y_axis = y_axis[0] * numpy.arange(image.shape[0]) + y_axis[1]
xcalib = ArrayCalibration(x_axis)
ycalib = ArrayCalibration(y_axis)
self._plot.remove(kind=(
"scatter",
"image",
))
if xcalib.is_affine() and ycalib.is_affine():
# regular image
xorigin, xscale = xcalib(0), xcalib.get_slope()
yorigin, yscale = ycalib(0), ycalib.get_slope()
origin = (xorigin, yorigin)
scale = (xscale, yscale)
self._plot.addImage(image,
legend=legend,
origin=origin,
scale=scale)
else:
scatterx, scattery = numpy.meshgrid(x_axis, y_axis)
# fixme: i don't think this can handle "irregular" RGBA images
self._plot.addScatter(numpy.ravel(scatterx),
numpy.ravel(scattery),
numpy.ravel(image),
legend=legend)
title = ""
if self.__title:
title += self.__title
if not title.strip().endswith(self.__signals_names[auxSigIdx]):
title += "\n" + self.__signals_names[auxSigIdx]
self._plot.setGraphTitle(title)
self._plot.getXAxis().setLabel(self.__x_axis_name)
self._plot.getYAxis().setLabel(self.__y_axis_name)
self._plot.resetZoom()
