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"""QWidget displaying a 2D image with histograms on its sides.
The :class:`ImageView` implements this widget, and
:class:`ImageViewMainWindow` provides a main window with additional toolbar
and status bar.
Basic usage of :class:`ImageView` is through the following methods:
- :meth:`ImageView.getColormap`, :meth:`ImageView.setColormap` to update the
default colormap to use and update the currently displayed image.
- :meth:`ImageView.setImage` to update the displayed image.
For an example of use, see `imageview.py` in :ref:`sample-code`.
"""
__authors__ = ["T. Vincent"]
__license__ = "MIT"
__date__ = "26/04/2018"
import logging
import numpy
import collections
from typing import Union
import silx
from .. import qt
from .. import colors
from .. import icons
from . import items, PlotWindow, PlotWidget, actions
from ..colors import Colormap
from ..colors import cursorColorForColormap
from .tools import LimitsToolBar
from .Profile import ProfileToolBar
from ...utils.proxy import docstring
from ...utils.deprecation import deprecated
from ...utils.enum import Enum
from .tools.RadarView import RadarView
from .utils.axis import SyncAxes
from ..utils import blockSignals
from . import _utils
from .tools.profile import rois
from .actions import PlotAction
from .actions.image import AggregationModeAction
from silx._utils import NP_OPTIONAL_COPY
_logger = logging.getLogger(__name__)
ProfileSumResult = collections.namedtuple(
"ProfileResult",
[
"dataXRange",
"dataYRange",
"histoH",
"histoHRange",
"histoV",
"histoVRange",
"xCoords",
"xData",
"yCoords",
"yData",
],
)
def computeProfileSumOnRange(imageItem, xRange, yRange, cache=None):
"""
Compute a full vertical and horizontal profile on an image item using a
a range in the plot referential.
Optionally takes a previous computed result to be able to skip the
computation.
:rtype: ProfileSumResult
"""
data = imageItem.getValueData(copy=False)
origin = imageItem.getOrigin()
scale = imageItem.getScale()
height, width = data.shape
xMin, xMax = xRange
yMin, yMax = yRange
# Convert plot area limits to image coordinates
# and work in image coordinates (i.e., in pixels)
xMin = int((xMin - origin[0]) / scale[0])
xMax = int((xMax - origin[0]) / scale[0])
yMin = int((yMin - origin[1]) / scale[1])
yMax = int((yMax - origin[1]) / scale[1])
if xMin >= width or xMax < 0 or yMin >= height or yMax < 0:
return None
# The image is at least partly in the plot area
# Get the visible bounds in image coords (i.e., in pixels)
subsetXMin = 0 if xMin < 0 else xMin
subsetXMax = (width if xMax >= width else xMax) + 1
subsetYMin = 0 if yMin < 0 else yMin
subsetYMax = (height if yMax >= height else yMax) + 1
if cache is not None:
if (subsetXMin, subsetXMax) == cache.dataXRange and (
subsetYMin,
subsetYMax,
) == cache.dataYRange:
# The visible area of data is the same
return cache
# Rebuild histograms for visible area
visibleData = data[subsetYMin:subsetYMax, subsetXMin:subsetXMax]
histoHVisibleData = numpy.nansum(visibleData, axis=0)
histoVVisibleData = numpy.nansum(visibleData, axis=1)
histoHMin = numpy.nanmin(histoHVisibleData)
histoHMax = numpy.nanmax(histoHVisibleData)
histoVMin = numpy.nanmin(histoVVisibleData)
histoVMax = numpy.nanmax(histoVVisibleData)
# Convert to histogram curve and update plots
# Taking into account origin and scale
coords = numpy.arange(2 * histoHVisibleData.size)
xCoords = (coords + 1) // 2 + subsetXMin
xCoords = origin[0] + scale[0] * xCoords
xData = numpy.take(histoHVisibleData, coords // 2)
coords = numpy.arange(2 * histoVVisibleData.size)
yCoords = (coords + 1) // 2 + subsetYMin
yCoords = origin[1] + scale[1] * yCoords
yData = numpy.take(histoVVisibleData, coords // 2)
result = ProfileSumResult(
dataXRange=(subsetXMin, subsetXMax),
dataYRange=(subsetYMin, subsetYMax),
histoH=histoHVisibleData,
histoHRange=(histoHMin, histoHMax),
histoV=histoVVisibleData,
histoVRange=(histoVMin, histoVMax),
xCoords=xCoords,
xData=xData,
yCoords=yCoords,
yData=yData,
)
return result
class _SideHistogram(PlotWidget):
"""
Widget displaying one of the side profile of the ImageView.
Implement ProfileWindow
"""
sigClose = qt.Signal()
sigMouseMoved = qt.Signal(float, float)
def __init__(self, parent=None, backend=None, direction=qt.Qt.Horizontal):
super(_SideHistogram, self).__init__(parent=parent, backend=backend)
self._direction = direction
self.sigPlotSignal.connect(self._plotEvents)
self._color = "blue"
self.__profile = None
self.__profileSum = None
def _plotEvents(self, eventDict):
"""Callback for horizontal histogram plot events."""
if eventDict["event"] == "mouseMoved":
self.sigMouseMoved.emit(eventDict["x"], eventDict["y"])
def setProfileColor(self, color):
self._color = color
def setProfileSum(self, result):
self.__profileSum = result
if self.__profile is None:
self.__drawProfileSum()
def prepareWidget(self, roi):
"""Implements `ProfileWindow`"""
pass
def setRoiProfile(self, roi):
"""Implements `ProfileWindow`"""
if roi is None:
return
self._roiColor = colors.rgba(roi.getColor())
def getProfile(self):
"""Implements `ProfileWindow`"""
return self.__profile
def setProfile(self, data):
"""Implements `ProfileWindow`"""
self.__profile = data
if data is None:
self.__drawProfileSum()
else:
self.__drawProfile()
def __drawProfileSum(self):
"""Only draw the profile sum on the plot.
Other elements are removed
"""
profileSum = self.__profileSum
try:
self.removeCurve("profile")
except Exception:
pass
if profileSum is None:
try:
self.removeCurve("profilesum")
except Exception:
pass
return
if self._direction == qt.Qt.Horizontal:
xx, yy = profileSum.xCoords, profileSum.xData
elif self._direction == qt.Qt.Vertical:
xx, yy = profileSum.yData, profileSum.yCoords
else:
assert False
self.addCurve(
xx,
yy,
xlabel="",
ylabel="",
legend="profilesum",
color=self._color,
linestyle="-",
selectable=False,
resetzoom=False,
)
self.__updateLimits()
def __drawProfile(self):
"""Only draw the profile on the plot.
Other elements are removed
"""
profile = self.__profile
try:
self.removeCurve("profilesum")
except Exception:
pass
if profile is None:
try:
self.removeCurve("profile")
except Exception:
pass
self.setProfileSum(self.__profileSum)
return
if self._direction == qt.Qt.Horizontal:
xx, yy = profile.coords, profile.profile
elif self._direction == qt.Qt.Vertical:
xx, yy = profile.profile, profile.coords
else:
assert False
self.addCurve(xx, yy, legend="profile", color=self._roiColor, resetzoom=False)
self.__updateLimits()
def __updateLimits(self):
if self.__profile:
data = self.__profile.profile
vMin = numpy.nanmin(data)
vMax = numpy.nanmax(data)
elif self.__profileSum is not None:
if self._direction == qt.Qt.Horizontal:
vMin, vMax = self.__profileSum.histoHRange
elif self._direction == qt.Qt.Vertical:
vMin, vMax = self.__profileSum.histoVRange
else:
assert False
else:
vMin, vMax = 0, 0
# Tune the result using the data margins
margins = self.getDataMargins()
if self._direction == qt.Qt.Horizontal:
_, _, vMin, vMax = _utils.addMarginsToLimits(
margins, False, False, 0, 0, vMin, vMax
)
elif self._direction == qt.Qt.Vertical:
vMin, vMax, _, _ = _utils.addMarginsToLimits(
margins, False, False, vMin, vMax, 0, 0
)
else:
assert False
if self._direction == qt.Qt.Horizontal:
dataAxis = self.getYAxis()
elif self._direction == qt.Qt.Vertical:
dataAxis = self.getXAxis()
else:
assert False
with blockSignals(dataAxis):
dataAxis.setLimits(vMin, vMax)
class ShowSideHistogramsAction(PlotAction):
"""QAction to change visibility of side histogram of a :class:`.ImageView`.
:param plot: :class:`.ImageView` instance on which to operate
:param parent: See :class:`QAction`
"""
def __init__(self, plot, parent=None):
super(ShowSideHistogramsAction, self).__init__(
plot,
icon="side-histograms",
text="Show/hide side histograms",
tooltip="Show/hide side histogram",
triggered=self._actionTriggered,
checkable=True,
parent=parent,
)
def _actionTriggered(self, checked=False):
if self.plot.isSideHistogramDisplayed() != checked:
self.plot.setSideHistogramDisplayed(checked)
[docs]
class ImageView(PlotWindow):
"""Display a single image with horizontal and vertical histograms.
Use :meth:`setImage` to control the displayed image.
This class also provides the :class:`silx.gui.plot.Plot` API.
The :class:`ImageView` inherits from :class:`.PlotWindow` (which provides
the toolbars) and also exposes :class:`.PlotWidget` API for further
plot control (plot title, axes labels, aspect ratio, ...).
:param parent: The parent of this widget or None.
:param backend: The backend to use for the plot (default: matplotlib).
See :class:`.PlotWidget` for the list of supported backend.
:type backend: str or :class:`BackendBase.BackendBase`
"""
HISTOGRAMS_COLOR = "blue"
"""Color to use for the side histograms."""
HISTOGRAMS_HEIGHT = 200
"""Height in pixels of the side histograms."""
IMAGE_MIN_SIZE = 200
"""Minimum size in pixels of the image area."""
# Qt signals
valueChanged = qt.Signal(float, float, object)
"""Signals that the data value under the cursor has changed.
It provides: row, column, data value.
When the cursor is over an histogram, either row or column is Nan
and the provided data value is the histogram value
(i.e., the sum along the corresponding row/column).
Row and columns are either Nan or integer values.
"""
class ProfileWindowBehavior(Enum):
"""ImageView's profile window behavior options"""
POPUP = "popup"
"""All profiles are displayed in pop-up windows"""
EMBEDDED = "embedded"
"""Horizontal, vertical and cross profiles are displayed in
sides widgets, others are displayed in pop-up windows.
"""
def __init__(self, parent=None, backend=None):
self._imageLegend = "__ImageView__image" + str(id(self))
self._cache = None # Store currently visible data information
super(ImageView, self).__init__(
parent=parent,
backend=backend,
resetzoom=True,
autoScale=False,
logScale=False,
grid=False,
curveStyle=False,
colormap=True,
aspectRatio=True,
yInverted=True,
copy=True,
save=True,
print_=True,
control=False,
position=False,
roi=False,
mask=True,
)
# Enable mask synchronisation to use it in profiles
maskToolsWidget = self.getMaskToolsDockWidget().widget()
maskToolsWidget.setItemMaskUpdated(True)
self.__showSideHistogramsAction = ShowSideHistogramsAction(self, self)
self.__showSideHistogramsAction.setChecked(True)
self.__aggregationModeAction = AggregationModeAction(self)
self.__aggregationModeAction.sigAggregationModeChanged.connect(
self._aggregationModeChanged
)
if parent is None:
self.setWindowTitle("ImageView")
if silx.config.DEFAULT_PLOT_IMAGE_Y_AXIS_ORIENTATION == "downward":
self.getYAxis().setInverted(True)
self._initWidgets(backend)
toolBar = self.toolBar()
toolBar.addAction(self.__showSideHistogramsAction)
toolBar.addAction(self.__aggregationModeAction)
self.__profileWindowBehavior = self.ProfileWindowBehavior.POPUP
self.__profile = ProfileToolBar(plot=self)
self.addToolBar(self.__profile)
def _initWidgets(self, backend):
"""Set-up layout and plots."""
self._histoHPlot = _SideHistogram(
backend=backend, parent=self, direction=qt.Qt.Horizontal
)
widgetHandle = self._histoHPlot.getWidgetHandle()
widgetHandle.setMinimumHeight(self.HISTOGRAMS_HEIGHT)
widgetHandle.setMaximumHeight(self.HISTOGRAMS_HEIGHT)
self._histoHPlot.setInteractiveMode("zoom")
self._histoHPlot.setDataMargins(0.0, 0.0, 0.1, 0.1)
self._histoHPlot.sigMouseMoved.connect(self._mouseMovedOnHistoH)
self._histoHPlot.setProfileColor(self.HISTOGRAMS_COLOR)
self._histoVPlot = _SideHistogram(
backend=backend, parent=self, direction=qt.Qt.Vertical
)
widgetHandle = self._histoVPlot.getWidgetHandle()
widgetHandle.setMinimumWidth(self.HISTOGRAMS_HEIGHT)
widgetHandle.setMaximumWidth(self.HISTOGRAMS_HEIGHT)
# Trick to align the histogram to the main plot
self._histoVPlot.setGraphTitle(" ")
self._histoVPlot.setInteractiveMode("zoom")
self._histoVPlot.setDataMargins(0.1, 0.1, 0.0, 0.0)
self._histoVPlot.sigMouseMoved.connect(self._mouseMovedOnHistoV)
self._histoVPlot.setProfileColor(self.HISTOGRAMS_COLOR)
self.setPanWithArrowKeys(True)
self.setInteractiveMode("zoom") # Color set in setColormap
self.sigPlotSignal.connect(self._imagePlotCB)
self.sigActiveImageChanged.connect(self._activeImageChangedSlot)
self._radarView = RadarView(parent=self)
self._radarView.setPlotWidget(self)
self.__syncXAxis = SyncAxes([self.getXAxis(), self._histoHPlot.getXAxis()])
self.__syncYAxis = SyncAxes([self.getYAxis(), self._histoVPlot.getYAxis()])
self.__setCentralWidget()
def __setCentralWidget(self):
"""Set central widget with all its content"""
layout = qt.QGridLayout()
layout.addWidget(self.getWidgetHandle(), 0, 0)
layout.addWidget(self._histoVPlot, 0, 1)
layout.addWidget(self._histoHPlot, 1, 0)
layout.addWidget(self._radarView, 1, 1, 1, 2)
layout.addWidget(self.getColorBarWidget(), 0, 2)
self._radarView.setMinimumWidth(self.IMAGE_MIN_SIZE)
self._radarView.setMinimumHeight(self.HISTOGRAMS_HEIGHT)
self._histoHPlot.setMinimumWidth(self.IMAGE_MIN_SIZE)
self._histoVPlot.setMinimumHeight(self.HISTOGRAMS_HEIGHT)
layout.setColumnStretch(0, 1)
layout.setColumnStretch(1, 0)
layout.setRowStretch(0, 1)
layout.setRowStretch(1, 0)
layout.setSpacing(0)
layout.setContentsMargins(0, 0, 0, 0)
centralWidget = qt.QWidget(self)
centralWidget.setLayout(layout)
self.setCentralWidget(centralWidget)
@docstring(PlotWidget)
def setBackend(self, backend):
# Use PlotWidget here since we override PlotWindow behavior
PlotWidget.setBackend(self, backend)
self.__setCentralWidget()
def _dirtyCache(self):
self._cache = None
def getAggregationModeAction(self):
return self.__aggregationModeAction
def _aggregationModeChanged(self):
item = self._getItem("image", self._imageLegend)
if item is None:
return
aggregationMode = self.__aggregationModeAction.getAggregationMode()
if aggregationMode is not None and isinstance(item, items.ImageDataAggregated):
item.setAggregationMode(aggregationMode)
else:
# It means the item type have to be changed
self.removeImage(self._imageLegend)
image = item.getData(copy=False)
if image is None:
return
origin = item.getOrigin()
scale = item.getScale()
self.setImage(image, origin, scale, copy=False, resetzoom=False)
def getShowSideHistogramsAction(self):
return self.__showSideHistogramsAction
def setSideHistogramDisplayed(self, show):
"""Display or not the side histograms"""
if self.isSideHistogramDisplayed() == show:
return
self._histoHPlot.setVisible(show)
self._histoVPlot.setVisible(show)
self._radarView.setVisible(show)
self.__showSideHistogramsAction.setChecked(show)
if show:
# Probably have to be computed
self._updateHistograms()
def isSideHistogramDisplayed(self):
"""True if the side histograms are displayed"""
return self._histoHPlot.isVisibleTo(self)
def _updateHistograms(self):
"""Update histograms content using current active image."""
if not self.isSideHistogramDisplayed():
# The histogram computation can be skipped
return
activeImage = self.getActiveImage()
if activeImage is not None:
xRange = self.getXAxis().getLimits()
yRange = self.getYAxis().getLimits()
result = computeProfileSumOnRange(activeImage, xRange, yRange, self._cache)
self._cache = result
self._histoHPlot.setProfileSum(result)
self._histoVPlot.setProfileSum(result)
# Plots event listeners
def _imagePlotCB(self, eventDict):
"""Callback for imageView plot events."""
if eventDict["event"] == "mouseMoved":
activeImage = self.getActiveImage()
if activeImage is not None:
data = activeImage.getData(copy=False)
height, width = data.shape[0:2]
# Get corresponding coordinate in image
origin = activeImage.getOrigin()
scale = activeImage.getScale()
if eventDict["x"] >= origin[0] and eventDict["y"] >= origin[1]:
x = int((eventDict["x"] - origin[0]) / scale[0])
y = int((eventDict["y"] - origin[1]) / scale[1])
if x >= 0 and x < width and y >= 0 and y < height:
self.valueChanged.emit(float(x), float(y), data[y][x])
elif eventDict["event"] == "limitsChanged":
self._updateHistograms()
def _mouseMovedOnHistoH(self, x, y):
if self._cache is None:
return
activeImage = self.getActiveImage()
if activeImage is None:
return
xOrigin = activeImage.getOrigin()[0]
xScale = activeImage.getScale()[0]
minValue = xOrigin + xScale * self._cache.dataXRange[0]
if x >= minValue:
data = self._cache.histoH
column = int((x - minValue) / xScale)
if column >= 0 and column < data.shape[0]:
self.valueChanged.emit(
float("nan"),
float(column + self._cache.dataXRange[0]),
data[column],
)
def _mouseMovedOnHistoV(self, x, y):
if self._cache is None:
return
activeImage = self.getActiveImage()
if activeImage is None:
return
yOrigin = activeImage.getOrigin()[1]
yScale = activeImage.getScale()[1]
minValue = yOrigin + yScale * self._cache.dataYRange[0]
if y >= minValue:
data = self._cache.histoV
row = int((y - minValue) / yScale)
if row >= 0 and row < data.shape[0]:
self.valueChanged.emit(
float(row + self._cache.dataYRange[0]), float("nan"), data[row]
)
def _activeImageChangedSlot(self, previous, legend):
"""Handle Plot active image change.
Resets side histograms cache
"""
self._dirtyCache()
self._updateHistograms()
def setProfileWindowBehavior(self, behavior: Union[str, ProfileWindowBehavior]):
"""Set where profile widgets are displayed.
:param ProfileWindowBehavior behavior:
- 'popup': All profiles are displayed in pop-up windows
- 'embedded': Horizontal, vertical and cross profiles are displayed in
sides widgets, others are displayed in pop-up windows.
"""
behavior = self.ProfileWindowBehavior(behavior)
if behavior is not self.getProfileWindowBehavior():
manager = self.__profile.getProfileManager()
manager.clearProfile()
manager.requestUpdateAllProfile()
if behavior is self.ProfileWindowBehavior.EMBEDDED:
horizontalProfileWindow = self._histoHPlot
verticalProfileWindow = self._histoVPlot
else:
horizontalProfileWindow = None
verticalProfileWindow = None
manager.setSpecializedProfileWindow(
rois.ProfileImageHorizontalLineROI, horizontalProfileWindow
)
manager.setSpecializedProfileWindow(
rois.ProfileImageVerticalLineROI, verticalProfileWindow
)
self.__profileWindowBehavior = behavior
def getProfileWindowBehavior(self) -> ProfileWindowBehavior:
"""Returns current profile display behavior.
See :meth:`setProfileWindowBehavior` and :class:`ProfileWindowBehavior`
"""
return self.__profileWindowBehavior
def getProfileToolBar(self):
"""Returns profile tools attached to this plot.
:rtype: silx.gui.plot.PlotTools.ProfileToolBar
"""
return self.__profile
@property
@deprecated(replacement="getProfileToolBar()")
def profile(self):
return self.getProfileToolBar()
[docs]
def getHistogram(self, axis):
"""Return the histogram and corresponding row or column extent.
The returned value when an histogram is available is a dict with keys:
- 'data': numpy array of the histogram values.
- 'extent': (start, end) row or column index.
end index is not included in the histogram.
:param str axis: 'x' for horizontal, 'y' for vertical
:return: The histogram and its extent as a dict or None.
:rtype: dict
"""
assert axis in ("x", "y")
if self._cache is None:
return None
else:
if axis == "x":
return dict(
data=numpy.array(self._cache.histoH, copy=True),
extent=self._cache.dataXRange,
)
else:
return dict(
data=numpy.array(self._cache.histoV, copy=True),
extent=(self._cache.dataYRange),
)
def radarView(self):
"""Get the lower right radarView widget."""
return self._radarView
def setRadarView(self, radarView):
"""Change the lower right radarView widget.
:param RadarView radarView: Widget subclassing RadarView to replace
the lower right corner widget.
"""
self._radarView = radarView
self._radarView.setPlotWidget(self)
self.centralWidget().layout().addWidget(self._radarView, 1, 1)
# High-level API
[docs]
def getColormap(self):
"""Get the default colormap description.
:return: A description of the current colormap.
See :meth:`setColormap` for details.
:rtype: dict
"""
return self.getDefaultColormap()
[docs]
def setColormap(
self,
colormap=None,
normalization=None,
autoscale=None,
vmin=None,
vmax=None,
colors=None,
):
"""Set the default colormap and update active image.
Parameters that are not provided are taken from the current colormap.
The colormap parameter can also be a dict with the following keys:
- *name*: string. The colormap to use:
'gray', 'reversed gray', 'temperature', 'red', 'green', 'blue'.
- *normalization*: string. The mapping to use for the colormap:
either 'linear' or 'log'.
- *autoscale*: bool. Whether to use autoscale (True)
or range provided by keys 'vmin' and 'vmax' (False).
- *vmin*: float. The minimum value of the range to use if 'autoscale'
is False.
- *vmax*: float. The maximum value of the range to use if 'autoscale'
is False.
- *colors*: optional. Nx3 or Nx4 array of float in [0, 1] or uint8.
List of RGB or RGBA colors to use (only if name is None)
:param colormap: Name of the colormap in
'gray', 'reversed gray', 'temperature', 'red', 'green', 'blue'.
Or the description of the colormap as a dict.
:type colormap: dict or str.
:param str normalization: Colormap mapping: 'linear' or 'log'.
:param bool autoscale: Whether to use autoscale (True)
or [vmin, vmax] range (False).
:param float vmin: The minimum value of the range to use if
'autoscale' is False.
:param float vmax: The maximum value of the range to use if
'autoscale' is False.
:param numpy.ndarray colors: Only used if name is None.
Custom colormap colors as Nx3 or Nx4 RGB or RGBA arrays
"""
cmap = self.getDefaultColormap()
if isinstance(colormap, Colormap):
# Replace colormap
cmap = colormap
self.setDefaultColormap(cmap)
# Update active image colormap
activeImage = self.getActiveImage()
if isinstance(activeImage, items.ColormapMixIn):
activeImage.setColormap(cmap)
elif isinstance(colormap, dict):
# Support colormap parameter as a dict
assert normalization is None
assert autoscale is None
assert vmin is None
assert vmax is None
assert colors is None
cmap._setFromDict(colormap)
else:
if colormap is not None:
cmap.setName(colormap)
if normalization is not None:
cmap.setNormalization(normalization)
if autoscale:
cmap.setVRange(None, None)
else:
if vmin is not None:
cmap.setVMin(vmin)
if vmax is not None:
cmap.setVMax(vmax)
if colors is not None:
cmap.setColormapLUT(colors)
cursorColor = cursorColorForColormap(cmap.getName())
self.setInteractiveMode("zoom", color=cursorColor)
[docs]
def setImage(
self,
image,
origin=(0, 0),
scale=(1.0, 1.0),
copy=True,
reset=None,
resetzoom=True,
):
"""Set the image to display.
:param image: A 2D array representing the image or None to empty plot.
:type image: numpy.ndarray-like with 2 dimensions or None.
:param origin: The (x, y) position of the origin of the image.
Default: (0, 0).
The origin is the lower left corner of the image when
the Y axis is not inverted.
:type origin: Tuple of 2 floats: (origin x, origin y).
:param scale: The scale factor to apply to the image on X and Y axes.
Default: (1, 1).
It is the size of a pixel in the coordinates of the axes.
Scales must be positive numbers.
:type scale: Tuple of 2 floats: (scale x, scale y).
:param bool copy: Whether to copy image data (default) or not.
:param bool reset: Deprecated. Alias for `resetzoom`.
:param bool resetzoom: Whether to reset zoom and ROI (default) or not.
"""
self._dirtyCache()
if reset is not None:
resetzoom = reset
assert len(origin) == 2
assert len(scale) == 2
assert scale[0] > 0
assert scale[1] > 0
if image is None:
self.remove(self._imageLegend, kind="image")
return
data = numpy.array(image, order="C", copy=copy or NP_OPTIONAL_COPY)
if data.size == 0:
self.remove(self._imageLegend, kind="image")
return
assert data.ndim == 2 or (data.ndim == 3 and data.shape[2] in (3, 4))
aggregation = self.getAggregationModeAction().getAggregationMode()
if data.ndim != 2 and aggregation is not None:
# RGB/A with aggregation is not supported
aggregation = items.ImageDataAggregated.Aggregation.NONE
if aggregation is items.ImageDataAggregated.Aggregation.NONE:
self.addImage(
data,
legend=self._imageLegend,
origin=origin,
scale=scale,
colormap=self.getColormap(),
resetzoom=False,
)
else:
item = self._getItem("image", self._imageLegend)
if isinstance(item, items.ImageDataAggregated):
item.setData(data)
item.setOrigin(origin)
item.setScale(scale)
else:
if isinstance(item, items.ImageDataAggregated):
imageItem = item
wasCreated = False
else:
if item is not None:
self.removeImage(self._imageLegend)
imageItem = items.ImageDataAggregated()
imageItem.setName(self._imageLegend)
imageItem.setColormap(self.getColormap())
wasCreated = True
imageItem.setData(data)
imageItem.setOrigin(origin)
imageItem.setScale(scale)
imageItem.setAggregationMode(aggregation)
if wasCreated:
self.addItem(imageItem)
self.setActiveImage(self._imageLegend)
self._updateHistograms()
if resetzoom:
self.resetZoom()
# ImageViewMainWindow #########################################################
class ImageViewMainWindow(ImageView):
""":class:`ImageView` with additional toolbars
Adds extra toolbar and a status bar to :class:`ImageView`.
"""
def __init__(self, parent=None, backend=None):
self._dataInfo = None
super(ImageViewMainWindow, self).__init__(parent, backend)
self.setWindowFlags(qt.Qt.Window)
self.getXAxis().setLabel("X")
self.getYAxis().setLabel("Y")
self.setGraphTitle("Image")
# Add toolbars and status bar
self.addToolBar(qt.Qt.BottomToolBarArea, LimitsToolBar(plot=self))
menu = self.menuBar().addMenu("File")
menu.addAction(self.getOutputToolBar().getSaveAction())
menu.addAction(self.getOutputToolBar().getPrintAction())
menu.addSeparator()
action = menu.addAction("Quit")
action.triggered[bool].connect(qt.QApplication.instance().quit)
menu = self.menuBar().addMenu("Edit")
menu.addAction(self.getOutputToolBar().getCopyAction())
menu.addSeparator()
menu.addAction(self.getResetZoomAction())
menu.addAction(self.getColormapAction())
menu.addAction(actions.control.KeepAspectRatioAction(self, self))
menu.addAction(actions.control.YAxisInvertedAction(self, self))
menu.addAction(self.getShowSideHistogramsAction())
self.__profileMenu = self.menuBar().addMenu("Profile")
self.__updateProfileMenu()
# Connect to ImageView's signal
self.valueChanged.connect(self._statusBarSlot)
def __updateProfileMenu(self):
"""Update actions available in 'Profile' menu"""
profile = self.getProfileToolBar()
self.__profileMenu.clear()
self.__profileMenu.addAction(profile.hLineAction)
self.__profileMenu.addAction(profile.vLineAction)
self.__profileMenu.addAction(profile.crossAction)
self.__profileMenu.addAction(profile.lineAction)
self.__profileMenu.addAction(profile.clearAction)
def _formatValueToString(self, value):
try:
if isinstance(value, numpy.ndarray):
if len(value) == 4:
return "RGBA: %.3g, %.3g, %.3g, %.3g" % (
value[0],
value[1],
value[2],
value[3],
)
elif len(value) == 3:
return "RGB: %.3g, %.3g, %.3g" % (value[0], value[1], value[2])
else:
return "Value: %g" % value
except Exception:
_logger.error("Error while formatting pixel value", exc_info=True)
pass
return "Value: %s" % value
def _statusBarSlot(self, row, column, value):
"""Update status bar with coordinates/value from plots."""
if numpy.isnan(row):
msg = "Column: %d, Sum: %g" % (int(column), value)
elif numpy.isnan(column):
msg = "Row: %d, Sum: %g" % (int(row), value)
else:
msg_value = self._formatValueToString(value)
msg = "Position: (%d, %d), %s" % (int(row), int(column), msg_value)
if self._dataInfo is not None:
msg = self._dataInfo + ", " + msg
self.statusBar().showMessage(msg)
@docstring(ImageView)
def setProfileWindowBehavior(self, behavior: str):
super().setProfileWindowBehavior(behavior)
self.__updateProfileMenu()
@docstring(ImageView)
def setImage(self, image, *args, **kwargs):
if hasattr(image, "dtype") and hasattr(image, "shape"):
assert image.ndim == 2 or (image.ndim == 3 and image.shape[2] in (3, 4))
height, width = image.shape[0:2]
dataInfo = "Data: %dx%d (%s)" % (width, height, str(image.dtype))
else:
dataInfo = None
if self._dataInfo != dataInfo:
self._dataInfo = dataInfo
self.statusBar().showMessage(self._dataInfo)
# Set the new image in ImageView widget
super(ImageViewMainWindow, self).setImage(image, *args, **kwargs)
