def computeProfile(self, item):
if not isinstance(item, items.ImageBase):
raise TypeError("Unexpected class %s" % type(item))
from silx.image.bilinear import BilinearImage
origin = item.getOrigin()
scale = item.getScale()
method = self.getProfileMethod()
lineWidth = self.getProfileLineWidth()
currentData = item.getValueData(copy=False)
roiInfo = self._getRoiInfo()
roiStart, roiEnd, _lineProjectionMode = roiInfo
startPt = ((roiStart[1] - origin[1]) / scale[1],
(roiStart[0] - origin[0]) / scale[0])
endPt = ((roiEnd[1] - origin[1]) / scale[1],
(roiEnd[0] - origin[0]) / scale[0])
if numpy.array_equal(startPt, endPt):
return None
bilinear = BilinearImage(currentData)
profile = bilinear.profile_line((startPt[0] - 0.5, startPt[1] - 0.5),
(endPt[0] - 0.5, endPt[1] - 0.5),
lineWidth,
method=method)
# Compute the line size
lineSize = numpy.sqrt((roiEnd[1] - roiStart[1])**2 +
(roiEnd[0] - roiStart[0])**2)
coords = numpy.linspace(0,
lineSize,
len(profile),
endpoint=True,
dtype=numpy.float32)
title = _lineProfileTitle(*roiStart, *roiEnd)
title = title + "; width = %d" % lineWidth
xLabel = "√({xlabel}²+{ylabel}²)"
yLabel = str(method).capitalize()
# Use the axis names from the original plot
profileManager = self.getProfileManager()
plot = profileManager.getPlotWidget()
xLabel = _relabelAxes(plot, xLabel)
title = _relabelAxes(plot, title)
data = core.CurveProfileData(
coords=coords,
profile=profile,
title=title,
xLabel=xLabel,
yLabel=yLabel,
)
return data
def resize_image(original_image, new_shape):
"""Return resized image
:param original_image:
:param tuple(int) new_shape: New image shape (rows, columns)
:return: New resized image, as a 2D numpy array
"""
bilinimg = BilinearImage(original_image)
row_array, column_array = numpy.meshgrid(
numpy.linspace(0, original_image.shape[0], new_shape[0]),
numpy.linspace(0, original_image.shape[1], new_shape[1]),
indexing="ij")
interpolated_values = bilinimg.map_coordinates((row_array, column_array))
interpolated_values.shape = new_shape
return interpolated_values
def resize_image(original_image, new_shape):
"""Return resized image
:param original_image:
:param tuple(int) new_shape: New image shape (rows, columns)
:return: New resized image, as a 2D numpy array
"""
bilinimg = BilinearImage(original_image)
row_array, column_array = numpy.meshgrid(
numpy.linspace(0, original_image.shape[0], new_shape[0]),
numpy.linspace(0, original_image.shape[1], new_shape[1]),
indexing="ij")
interpolated_values = bilinimg.map_coordinates((row_array, column_array))
interpolated_values.shape = new_shape
return interpolated_values
def createProfile(roiInfo, currentData, origin, scale, lineWidth, method):
"""Create the profile line for the the given image.
:param roiInfo: information about the ROI: start point, end point and
type ("X", "Y", "D")
:param numpy.ndarray currentData: the 2D image or the 3D stack of images
on which we compute the profile.
:param origin: (ox, oy) the offset from origin
:type origin: 2-tuple of float
:param scale: (sx, sy) the scale to use
:type scale: 2-tuple of float
:param int lineWidth: width of the profile line
:param str method: method to compute the profile. Can be 'mean' or 'sum'
:return: `coords, profile, area, profileName, xLabel`, where:
- coords is the X coordinate to use to display the profile
- profile is a 2D array of the profiles of the stack of images.
For a single image, the profile is a curve, so this parameter
has a shape *(1, len(curve))*
- area is a tuple of two 1D arrays with 4 values each. They represent
the effective ROI area corners in plot coords.
- profileName is a string describing the ROI, meant to be used as
title of the profile plot
- xLabel the label for X in the profile window
:rtype: tuple(ndarray,ndarray,(ndarray,ndarray),str)
"""
if currentData is None or roiInfo is None or lineWidth is None:
raise ValueError("createProfile called with invalide arguments")
# force 3D data (stack of images)
if len(currentData.shape) == 2:
currentData3D = currentData.reshape((1, ) + currentData.shape)
elif len(currentData.shape) == 3:
currentData3D = currentData
roiWidth = max(1, lineWidth)
roiStart, roiEnd, lineProjectionMode = roiInfo
if lineProjectionMode == 'X': # Horizontal profile on the whole image
profile, area = _alignedFullProfile(currentData3D,
origin,
scale,
roiStart[1],
roiWidth,
axis=0,
method=method)
coords = numpy.arange(len(profile[0]), dtype=numpy.float32)
coords = coords * scale[0] + origin[0]
yMin, yMax = min(area[1]), max(area[1]) - 1
if roiWidth <= 1:
profileName = 'Y = %g' % yMin
else:
profileName = 'Y = [%g, %g]' % (yMin, yMax)
xLabel = 'X'
elif lineProjectionMode == 'Y': # Vertical profile on the whole image
profile, area = _alignedFullProfile(currentData3D,
origin,
scale,
roiStart[0],
roiWidth,
axis=1,
method=method)
coords = numpy.arange(len(profile[0]), dtype=numpy.float32)
coords = coords * scale[1] + origin[1]
xMin, xMax = min(area[0]), max(area[0]) - 1
if roiWidth <= 1:
profileName = 'X = %g' % xMin
else:
profileName = 'X = [%g, %g]' % (xMin, xMax)
xLabel = 'Y'
else: # Free line profile
# Convert start and end points in image coords as (row, col)
startPt = ((roiStart[1] - origin[1]) / scale[1],
(roiStart[0] - origin[0]) / scale[0])
endPt = ((roiEnd[1] - origin[1]) / scale[1],
(roiEnd[0] - origin[0]) / scale[0])
if (int(startPt[0]) == int(endPt[0])
or int(startPt[1]) == int(endPt[1])):
# Profile is aligned with one of the axes
# Convert to int
startPt = int(startPt[0]), int(startPt[1])
endPt = int(endPt[0]), int(endPt[1])
# Ensure startPt <= endPt
if startPt[0] > endPt[0] or startPt[1] > endPt[1]:
startPt, endPt = endPt, startPt
if startPt[0] == endPt[0]: # Row aligned
rowRange = (int(startPt[0] + 0.5 - 0.5 * roiWidth),
int(startPt[0] + 0.5 + 0.5 * roiWidth))
colRange = startPt[1], endPt[1] + 1
profile = _alignedPartialProfile(currentData3D,
rowRange,
colRange,
axis=0,
method=method)
else: # Column aligned
rowRange = startPt[0], endPt[0] + 1
colRange = (int(startPt[1] + 0.5 - 0.5 * roiWidth),
int(startPt[1] + 0.5 + 0.5 * roiWidth))
profile = _alignedPartialProfile(currentData3D,
rowRange,
colRange,
axis=1,
method=method)
# Convert ranges to plot coords to draw ROI area
area = (numpy.array(
(colRange[0], colRange[1], colRange[1], colRange[0]),
dtype=numpy.float32) * scale[0] + origin[0],
numpy.array(
(rowRange[0], rowRange[0], rowRange[1], rowRange[1]),
dtype=numpy.float32) * scale[1] + origin[1])
else: # General case: use bilinear interpolation
# Ensure startPt <= endPt
if (startPt[1] > endPt[1]
or (startPt[1] == endPt[1] and startPt[0] > endPt[0])):
startPt, endPt = endPt, startPt
profile = []
for slice_idx in range(currentData3D.shape[0]):
bilinear = BilinearImage(currentData3D[slice_idx, :, :])
profile.append(
bilinear.profile_line((startPt[0] - 0.5, startPt[1] - 0.5),
(endPt[0] - 0.5, endPt[1] - 0.5),
roiWidth,
method=method))
profile = numpy.array(profile)
# Extend ROI with half a pixel on each end, and
# Convert back to plot coords (x, y)
length = numpy.sqrt((endPt[0] - startPt[0])**2 +
(endPt[1] - startPt[1])**2)
dRow = (endPt[0] - startPt[0]) / length
dCol = (endPt[1] - startPt[1]) / length
# Extend ROI with half a pixel on each end
roiStartPt = startPt[0] - 0.5 * dRow, startPt[1] - 0.5 * dCol
roiEndPt = endPt[0] + 0.5 * dRow, endPt[1] + 0.5 * dCol
# Rotate deltas by 90 degrees to apply line width
dRow, dCol = dCol, -dRow
area = (numpy.array(
(roiStartPt[1] - 0.5 * roiWidth * dCol, roiStartPt[1] +
0.5 * roiWidth * dCol, roiEndPt[1] + 0.5 * roiWidth * dCol,
roiEndPt[1] - 0.5 * roiWidth * dCol),
dtype=numpy.float32) * scale[0] + origin[0],
numpy.array(
(roiStartPt[0] - 0.5 * roiWidth * dRow, roiStartPt[0] +
0.5 * roiWidth * dRow, roiEndPt[0] + 0.5 * roiWidth *
dRow, roiEndPt[0] - 0.5 * roiWidth * dRow),
dtype=numpy.float32) * scale[1] + origin[1])
# Convert start and end points back to plot coords
y0 = startPt[0] * scale[1] + origin[1]
x0 = startPt[1] * scale[0] + origin[0]
y1 = endPt[0] * scale[1] + origin[1]
x1 = endPt[1] * scale[0] + origin[0]
if startPt[1] == endPt[1]:
profileName = 'X = %g; Y = [%g, %g]' % (x0, y0, y1)
coords = numpy.arange(len(profile[0]), dtype=numpy.float32)
coords = coords * scale[1] + y0
xLabel = 'Y'
elif startPt[0] == endPt[0]:
profileName = 'Y = %g; X = [%g, %g]' % (y0, x0, x1)
coords = numpy.arange(len(profile[0]), dtype=numpy.float32)
coords = coords * scale[0] + x0
xLabel = 'X'
else:
m = (y1 - y0) / (x1 - x0)
b = y0 - m * x0
profileName = 'y = %g * x %+g ; width=%d' % (m, b, roiWidth)
coords = numpy.linspace(x0,
x1,
len(profile[0]),
endpoint=True,
dtype=numpy.float32)
xLabel = 'X'
return coords, profile, area, profileName, xLabel
def createProfile(roiInfo, currentData, origin, scale, lineWidth, method):
"""Create the profile line for the the given image.
:param roiInfo: information about the ROI: start point, end point and
type ("X", "Y", "D")
:param numpy.ndarray currentData: the 2D image or the 3D stack of images
on which we compute the profile.
:param origin: (ox, oy) the offset from origin
:type origin: 2-tuple of float
:param scale: (sx, sy) the scale to use
:type scale: 2-tuple of float
:param int lineWidth: width of the profile line
:param str method: method to compute the profile. Can be 'mean' or 'sum'
:return: `coords, profile, area, profileName, xLabel`, where:
- coords is the X coordinate to use to display the profile
- profile is a 2D array of the profiles of the stack of images.
For a single image, the profile is a curve, so this parameter
has a shape *(1, len(curve))*
- area is a tuple of two 1D arrays with 4 values each. They represent
the effective ROI area corners in plot coords.
- profileName is a string describing the ROI, meant to be used as
title of the profile plot
- xLabel the label for X in the profile window
:rtype: tuple(ndarray,ndarray,(ndarray,ndarray),str)
"""
if currentData is None or roiInfo is None or lineWidth is None:
raise ValueError("createProfile called with invalide arguments")
# force 3D data (stack of images)
if len(currentData.shape) == 2:
currentData3D = currentData.reshape((1,) + currentData.shape)
elif len(currentData.shape) == 3:
currentData3D = currentData
roiWidth = max(1, lineWidth)
roiStart, roiEnd, lineProjectionMode = roiInfo
if lineProjectionMode == 'X': # Horizontal profile on the whole image
profile, area = _alignedFullProfile(currentData3D,
origin, scale,
roiStart[1], roiWidth,
axis=0,
method=method)
coords = numpy.arange(len(profile[0]), dtype=numpy.float32)
coords = coords * scale[0] + origin[0]
yMin, yMax = min(area[1]), max(area[1]) - 1
if roiWidth <= 1:
profileName = 'Y = %g' % yMin
else:
profileName = 'Y = [%g, %g]' % (yMin, yMax)
xLabel = 'X'
elif lineProjectionMode == 'Y': # Vertical profile on the whole image
profile, area = _alignedFullProfile(currentData3D,
origin, scale,
roiStart[0], roiWidth,
axis=1,
method=method)
coords = numpy.arange(len(profile[0]), dtype=numpy.float32)
coords = coords * scale[1] + origin[1]
xMin, xMax = min(area[0]), max(area[0]) - 1
if roiWidth <= 1:
profileName = 'X = %g' % xMin
else:
profileName = 'X = [%g, %g]' % (xMin, xMax)
xLabel = 'Y'
else: # Free line profile
# Convert start and end points in image coords as (row, col)
startPt = ((roiStart[1] - origin[1]) / scale[1],
(roiStart[0] - origin[0]) / scale[0])
endPt = ((roiEnd[1] - origin[1]) / scale[1],
(roiEnd[0] - origin[0]) / scale[0])
if (int(startPt[0]) == int(endPt[0]) or
int(startPt[1]) == int(endPt[1])):
# Profile is aligned with one of the axes
# Convert to int
startPt = int(startPt[0]), int(startPt[1])
endPt = int(endPt[0]), int(endPt[1])
# Ensure startPt <= endPt
if startPt[0] > endPt[0] or startPt[1] > endPt[1]:
startPt, endPt = endPt, startPt
if startPt[0] == endPt[0]: # Row aligned
rowRange = (int(startPt[0] + 0.5 - 0.5 * roiWidth),
int(startPt[0] + 0.5 + 0.5 * roiWidth))
colRange = startPt[1], endPt[1] + 1
profile = _alignedPartialProfile(currentData3D,
rowRange, colRange,
axis=0,
method=method)
else: # Column aligned
rowRange = startPt[0], endPt[0] + 1
colRange = (int(startPt[1] + 0.5 - 0.5 * roiWidth),
int(startPt[1] + 0.5 + 0.5 * roiWidth))
profile = _alignedPartialProfile(currentData3D,
rowRange, colRange,
axis=1,
method=method)
# Convert ranges to plot coords to draw ROI area
area = (
numpy.array(
(colRange[0], colRange[1], colRange[1], colRange[0]),
dtype=numpy.float32) * scale[0] + origin[0],
numpy.array(
(rowRange[0], rowRange[0], rowRange[1], rowRange[1]),
dtype=numpy.float32) * scale[1] + origin[1])
else: # General case: use bilinear interpolation
# Ensure startPt <= endPt
if (startPt[1] > endPt[1] or (
startPt[1] == endPt[1] and startPt[0] > endPt[0])):
startPt, endPt = endPt, startPt
profile = []
for slice_idx in range(currentData3D.shape[0]):
bilinear = BilinearImage(currentData3D[slice_idx, :, :])
profile.append(bilinear.profile_line(
(startPt[0] - 0.5, startPt[1] - 0.5),
(endPt[0] - 0.5, endPt[1] - 0.5),
roiWidth,
method=method))
profile = numpy.array(profile)
# Extend ROI with half a pixel on each end, and
# Convert back to plot coords (x, y)
length = numpy.sqrt((endPt[0] - startPt[0]) ** 2 +
(endPt[1] - startPt[1]) ** 2)
dRow = (endPt[0] - startPt[0]) / length
dCol = (endPt[1] - startPt[1]) / length
# Extend ROI with half a pixel on each end
roiStartPt = startPt[0] - 0.5 * dRow, startPt[1] - 0.5 * dCol
roiEndPt = endPt[0] + 0.5 * dRow, endPt[1] + 0.5 * dCol
# Rotate deltas by 90 degrees to apply line width
dRow, dCol = dCol, -dRow
area = (
numpy.array((roiStartPt[1] - 0.5 * roiWidth * dCol,
roiStartPt[1] + 0.5 * roiWidth * dCol,
roiEndPt[1] + 0.5 * roiWidth * dCol,
roiEndPt[1] - 0.5 * roiWidth * dCol),
dtype=numpy.float32) * scale[0] + origin[0],
numpy.array((roiStartPt[0] - 0.5 * roiWidth * dRow,
roiStartPt[0] + 0.5 * roiWidth * dRow,
roiEndPt[0] + 0.5 * roiWidth * dRow,
roiEndPt[0] - 0.5 * roiWidth * dRow),
dtype=numpy.float32) * scale[1] + origin[1])
# Convert start and end points back to plot coords
y0 = startPt[0] * scale[1] + origin[1]
x0 = startPt[1] * scale[0] + origin[0]
y1 = endPt[0] * scale[1] + origin[1]
x1 = endPt[1] * scale[0] + origin[0]
if startPt[1] == endPt[1]:
profileName = 'X = %g; Y = [%g, %g]' % (x0, y0, y1)
coords = numpy.arange(len(profile[0]), dtype=numpy.float32)
coords = coords * scale[1] + y0
xLabel = 'Y'
elif startPt[0] == endPt[0]:
profileName = 'Y = %g; X = [%g, %g]' % (y0, x0, x1)
coords = numpy.arange(len(profile[0]), dtype=numpy.float32)
coords = coords * scale[0] + x0
xLabel = 'X'
else:
m = (y1 - y0) / (x1 - x0)
b = y0 - m * x0
profileName = 'y = %g * x %+g ; width=%d' % (m, b, roiWidth)
coords = numpy.linspace(x0, x1, len(profile[0]),
endpoint=True,
dtype=numpy.float32)
xLabel = 'X'
return coords, profile, area, profileName, xLabel
def updateProfile(self):
"""Update the displayed profile and profile ROI.
This uses the current active image of the plot and the current ROI.
"""
# Clean previous profile area, and previous curve
self.plot.remove(self._POLYGON_LEGEND, kind='item')
self.profileWindow.clear()
self.profileWindow.setGraphTitle('')
self.profileWindow.setGraphXLabel('X')
self.profileWindow.setGraphYLabel('Y')
if self._roiInfo is None:
return
imageData = self.plot.getActiveImage()
if imageData is None:
return
data, params = imageData[0], imageData[4]
origin, scale = params['origin'], params['scale']
zActiveImage = params['z']
roiWidth = max(1, self.lineWidthSpinBox.value())
roiStart, roiEnd, lineProjectionMode = self._roiInfo
if lineProjectionMode == 'X': # Horizontal profile on the whole image
profile, area = self._alignedFullProfile(
data, origin, scale, roiStart[1], roiWidth, axis=0)
yMin, yMax = min(area[1]), max(area[1]) - 1
if roiWidth <= 1:
profileName = 'Y = %g' % yMin
else:
profileName = 'Y = [%g, %g]' % (yMin, yMax)
xLabel = 'Columns'
elif lineProjectionMode == 'Y': # Vertical profile on the whole image
profile, area = self._alignedFullProfile(
data, origin, scale, roiStart[0], roiWidth, axis=1)
xMin, xMax = min(area[0]), max(area[0]) - 1
if roiWidth <= 1:
profileName = 'X = %g' % xMin
else:
profileName = 'X = [%g, %g]' % (xMin, xMax)
xLabel = 'Rows'
else: # Free line profile
# Convert start and end points in image coords as (row, col)
startPt = ((roiStart[1] - origin[1]) / scale[1],
(roiStart[0] - origin[0]) / scale[0])
endPt = ((roiEnd[1] - origin[1]) / scale[1],
(roiEnd[0] - origin[0]) / scale[0])
if (int(startPt[0]) == int(endPt[0]) or
int(startPt[1]) == int(endPt[1])):
# Profile is aligned with one of the axes
# Convert to int
startPt = int(startPt[0]), int(startPt[1])
endPt = int(endPt[0]), int(endPt[1])
# Ensure startPt <= endPt
if startPt[0] > endPt[0] or startPt[1] > endPt[1]:
startPt, endPt = endPt, startPt
if startPt[0] == endPt[0]: # Row aligned
rowRange = (int(startPt[0] + 0.5 - 0.5 * roiWidth),
int(startPt[0] + 0.5 + 0.5 * roiWidth))
colRange = startPt[1], endPt[1] + 1
profile = self._alignedPartialProfile(
data, rowRange, colRange, axis=0)
else: # Column aligned
rowRange = startPt[0], endPt[0] + 1
colRange = (int(startPt[1] + 0.5 - 0.5 * roiWidth),
int(startPt[1] + 0.5 + 0.5 * roiWidth))
profile = self._alignedPartialProfile(
data, rowRange, colRange, axis=1)
# Convert ranges to plot coords to draw ROI area
area = (
numpy.array(
(colRange[0], colRange[1], colRange[1], colRange[0]),
dtype=numpy.float32) * scale[0] + origin[0],
numpy.array(
(rowRange[0], rowRange[0], rowRange[1], rowRange[1]),
dtype=numpy.float32) * scale[1] + origin[1])
else: # General case: use bilinear interpolation
# Ensure startPt <= endPt
if (startPt[1] > endPt[1] or (
startPt[1] == endPt[1] and startPt[0] > endPt[0])):
startPt, endPt = endPt, startPt
bilinear = BilinearImage(data)
# Offset start/end positions of 0.5 pixel to use pixel center
# rather than pixel lower left corner for interpolation
# This is only valid if image is displayed with nearest.
profile = bilinear.profile_line(
(startPt[0] - 0.5, startPt[1] - 0.5),
(endPt[0] - 0.5, endPt[1] - 0.5),
roiWidth)
# Extend ROI with half a pixel on each end, and
# Convert back to plot coords (x, y)
length = numpy.sqrt((endPt[0] - startPt[0]) ** 2 +
(endPt[1] - startPt[1]) ** 2)
dRow = (endPt[0] - startPt[0]) / length
dCol = (endPt[1] - startPt[1]) / length
# Extend ROI with half a pixel on each end
startPt = startPt[0] - 0.5 * dRow, startPt[1] - 0.5 * dCol
endPt = endPt[0] + 0.5 * dRow, endPt[1] + 0.5 * dCol
# Rotate deltas by 90 degrees to apply line width
dRow, dCol = dCol, -dRow
area = (
numpy.array((startPt[1] - 0.5 * roiWidth * dCol,
startPt[1] + 0.5 * roiWidth * dCol,
endPt[1] + 0.5 * roiWidth * dCol,
endPt[1] - 0.5 * roiWidth * dCol),
dtype=numpy.float32) * scale[0] + origin[0],
numpy.array((startPt[0] - 0.5 * roiWidth * dRow,
startPt[0] + 0.5 * roiWidth * dRow,
endPt[0] + 0.5 * roiWidth * dRow,
endPt[0] - 0.5 * roiWidth * dRow),
dtype=numpy.float32) * scale[1] + origin[1])
y0, x0 = startPt
y1, x1 = endPt
if x1 == x0 or y1 == y0:
profileName = 'From (%g, %g) to (%g, %g)' % (x0, y0, x1, y1)
else:
m = (y1 - y0) / (x1 - x0)
b = y0 - m * x0
profileName = 'y = %g * x %+g ; width=%d' % (m, b, roiWidth)
xLabel = 'Distance'
coords = numpy.arange(len(profile), dtype=numpy.float32)
# TODO coords in plot coords?
self.profileWindow.setGraphTitle(profileName)
self.profileWindow.addCurve(coords, profile,
legend=profileName,
xlabel=xLabel,
color=self.overlayColor)
self.plot.addItem(area[0], area[1],
legend=self._POLYGON_LEGEND,
color=self.overlayColor,
shape='polygon', fill=True,
replace=False, z=zActiveImage + 1)
if self._ownProfileWindow and not self.profileWindow.isVisible():
# If profile window was created in this widget,
# it tries to avoid overlapping this widget when shown
winGeom = self.window().frameGeometry()
qapp = qt.QApplication.instance()
screenGeom = qapp.desktop().availableGeometry(self)
spaceOnLeftSide = winGeom.left()
spaceOnRightSide = screenGeom.width() - winGeom.right()
profileWindowWidth = self.profileWindow.frameGeometry().width()
if (profileWindowWidth < spaceOnRightSide or
spaceOnRightSide > spaceOnLeftSide):
# Place profile on the right
self.profileWindow.move(winGeom.right(), winGeom.top())
else:
# Not enough place on the right, place profile on the left
self.profileWindow.move(
max(0, winGeom.left() - profileWindowWidth), winGeom.top())
self.profileWindow.show()