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# Source code for pyqtgraph.imageview.ImageView

    """
    ImageView.py -  Widget for basic image dispay and analysis
    Copyright 2010  Luke Campagnola
    Distributed under MIT/X11 license. See license.txt for more information.

    Widget used for displaying 2D or 3D data. Features:
      - float or int (including 16-bit int) image display via ImageItem
      - zoom/pan via GraphicsView
      - black/white level controls
      - time slider for 3D data sets
      - ROI plotting
      - Image normalization through a variety of methods
    """
    import os
    from math import log10
    from time import perf_counter

    import numpy as np

    from .. import debug as debug
    from .. import functions as fn
    from .. import getConfigOption
    from ..graphicsItems.GradientEditorItem import addGradientListToDocstring
    from ..graphicsItems.ImageItem import ImageItem
    from ..graphicsItems.InfiniteLine import InfiniteLine
    from ..graphicsItems.LinearRegionItem import LinearRegionItem
    from ..graphicsItems.ROI import ROI
    from ..graphicsItems.ViewBox import ViewBox
    from ..graphicsItems.VTickGroup import VTickGroup
    from ..Qt import QtCore, QtGui, QtWidgets
    from ..SignalProxy import SignalProxy
    from . import ImageViewTemplate_generic as ui_template

    try:
        from bottleneck import nanmax, nanmin
    except ImportError:
        from numpy import nanmax, nanmin

    translate = QtCore.QCoreApplication.translate

    class PlotROI(ROI):
        def __init__(self, size):
            ROI.__init__(self, pos=[0,0], size=size) #, scaleSnap=True, translateSnap=True)
            self.addScaleHandle([1, 1], [0, 0])
            self.addRotateHandle([0, 0], [0.5, 0.5])

    class ImageView(QtWidgets.QWidget):
        """
        Widget used for display and analysis of image data.
        Implements many features:

          * Displays 2D and 3D image data. For 3D data, a z-axis
            slider is displayed allowing the user to select which frame is displayed.
          * Displays histogram of image data with movable region defining the dark/light levels
          * Editable gradient provides a color lookup table
          * Frame slider may also be moved using left/right arrow keys as well as pgup, pgdn, home, and end.
          * Basic analysis features including:

              * ROI and embedded plot for measuring image values across frames
              * Image normalization / background subtraction

        Basic Usage::

            imv = pg.ImageView()
            imv.show()
            imv.setImage(data)

        **Keyboard interaction**

          * left/right arrows step forward/backward 1 frame when pressed,
            seek at 20fps when held.
          * up/down arrows seek at 100fps
          * pgup/pgdn seek at 1000fps
          * home/end seek immediately to the first/last frame
          * space begins playing frames. If time values (in seconds) are given
            for each frame, then playback is in realtime.
        """
        sigTimeChanged = QtCore.Signal(object, object)
        sigProcessingChanged = QtCore.Signal(object)

        def __init__(
                self,
                parent=None,
                name="ImageView",
                view=None,
                imageItem=None,
                levelMode='mono',
                discreteTimeLine=False,
                roi=None,
                normRoi=None,
                *args,
        ):
            """
            By default, this class creates an :class:`ImageItem <pyqtgraph.ImageItem>` to display image data
            and a :class:`ViewBox <pyqtgraph.ViewBox>` to contain the ImageItem.

            Parameters
            ----------
            parent : QWidget
                Specifies the parent widget to which this ImageView will belong. If None, then the ImageView is created with
                no parent.
            name : str
                The name used to register both the internal ViewBox and the PlotItem used to display ROI data. See the
                *name* argument to :func:`ViewBox.__init__() <pyqtgraph.ViewBox.__init__>`.
            view : ViewBox or PlotItem
                If specified, this will be used as the display area that contains the displayed image. Any
                :class:`ViewBox <pyqtgraph.ViewBox>`, :class:`PlotItem <pyqtgraph.PlotItem>`, or other compatible object is
                acceptable. Note: to display axis ticks inside the ImageView, instantiate it with a PlotItem instance as its
                view::

                    pg.ImageView(view=pg.PlotItem())
            imageItem : ImageItem
                If specified, this object will be used to display the image. Must be an instance of ImageItem or other
                compatible object.
            levelMode : str
                See the *levelMode* argument to :func:`HistogramLUTItem.__init__() <pyqtgraph.HistogramLUTItem.__init__>`
            discreteTimeLine : bool
                Whether to snap to xvals / frame numbers when interacting with the timeline position.
            roi : ROI
                If specified, this object is used as ROI for the plot feature. Must be an instance of ROI.
            normRoi : ROI
                If specified, this object is used as ROI for the normalization feature. Must be an instance of ROI.
            """
            QtWidgets.QWidget.__init__(self, parent, *args)
            self._imageLevels = None  # [(min, max), ...] per channel image metrics
            self.levelMin = None    # min / max levels across all channels
            self.levelMax = None

            self.name = name
            self.image = None
            self.axes = {}
            self.imageDisp = None
            self.ui = ui_template.Ui_Form()
            self.ui.setupUi(self)
            self.scene = self.ui.graphicsView.scene()
            self.discreteTimeLine = discreteTimeLine
            self.ui.histogram.setLevelMode(levelMode)
            self.ignoreTimeLine = False

            if view is None:
                self.view = ViewBox()
            else:
                self.view = view
            self.ui.graphicsView.setCentralItem(self.view)
            self.view.setAspectLocked(True)
            self.view.invertY()

            self.menu = None

            self.ui.normGroup.hide()

            if roi is None:
                self.roi = PlotROI(10)
            else:
                self.roi = roi
            self.roi.setZValue(20)
            self.view.addItem(self.roi)
            self.roi.hide()
            if normRoi is None:
                self.normRoi = PlotROI(10)
                self.normRoi.setPen('y')
            else:
                self.normRoi = normRoi
            self.normRoi.setZValue(20)
            self.view.addItem(self.normRoi)
            self.normRoi.hide()
            self.roiCurves = []
            self.timeLine = InfiniteLine(0, movable=True)
            if getConfigOption('background')=='w':
                self.timeLine.setPen((20, 80,80, 200))
            else:
                self.timeLine.setPen((255, 255, 0, 200))
            self.timeLine.setZValue(1)
            self.ui.roiPlot.addItem(self.timeLine)
            self.ui.splitter.setSizes([self.height()-35, 35])

            # init imageItem and histogram
            if imageItem is None:
                self.imageItem = ImageItem()
            else:
                self.imageItem = imageItem
                self.setImage(imageItem.image, autoRange=False, autoLevels=False, transform=imageItem.transform())
            self.view.addItem(self.imageItem)
            self.currentIndex = 0

            self.ui.histogram.setImageItem(self.imageItem)
            self.ui.histogram.setLevelMode(levelMode)

            # make splitter an unchangeable small grey line:
            s = self.ui.splitter
            s.handle(1).setEnabled(False)
            s.setStyleSheet("QSplitter::handle{background-color: grey}")
            s.setHandleWidth(2)

            self.ui.roiPlot.hideAxis('left')
            self.frameTicks = VTickGroup(yrange=[0.8, 1], pen=0.4)
            self.ui.roiPlot.addItem(self.frameTicks, ignoreBounds=True)

            self.keysPressed = {}
            self.playTimer = QtCore.QTimer()
            self.playRate = 0
            self._pausedPlayRate = None
            self.fps = 1  # 1 Hz by default
            self.lastPlayTime = 0

            self.normRgn = LinearRegionItem()
            self.normRgn.setZValue(0)
            self.ui.roiPlot.addItem(self.normRgn)
            self.normRgn.hide()

            ## wrap functions from view box
            for fn in ['addItem', 'removeItem']:
                setattr(self, fn, getattr(self.view, fn))

            ## wrap functions from histogram
            for fn in ['setHistogramRange', 'autoHistogramRange', 'getLookupTable', 'getLevels']:
                setattr(self, fn, getattr(self.ui.histogram, fn))

            self.timeLine.sigPositionChanged.connect(self.timeLineChanged)
            self.ui.roiBtn.clicked.connect(self.roiClicked)
            self.roi.sigRegionChanged.connect(self.roiChanged)
            #self.ui.normBtn.toggled.connect(self.normToggled)
            self.ui.menuBtn.clicked.connect(self.menuClicked)
            self.ui.normDivideRadio.clicked.connect(self.normRadioChanged)
            self.ui.normSubtractRadio.clicked.connect(self.normRadioChanged)
            self.ui.normOffRadio.clicked.connect(self.normRadioChanged)
            self.ui.normROICheck.clicked.connect(self.updateNorm)
            self.ui.normFrameCheck.clicked.connect(self.updateNorm)
            self.ui.normTimeRangeCheck.clicked.connect(self.updateNorm)
            self.playTimer.timeout.connect(self.timeout)

            self.normProxy = SignalProxy(
                self.normRgn.sigRegionChanged,
                slot=self.updateNorm,
                threadSafe=False,
            )
            self.normRoi.sigRegionChangeFinished.connect(self.updateNorm)

            self.ui.roiPlot.registerPlot(self.name + '_ROI')
            self.view.register(self.name)

            self.noRepeatKeys = [
                QtCore.Qt.Key.Key_Right,
                QtCore.Qt.Key.Key_Left,
                QtCore.Qt.Key.Key_Up,
                QtCore.Qt.Key.Key_Down,
                QtCore.Qt.Key.Key_PageUp,
                QtCore.Qt.Key.Key_PageDown,
            ]

            self.roiClicked() ## initialize roi plot to correct shape / visibility

        def setImage(
                self,
                img,
                autoRange=True,
                autoLevels=True,
                levels=None,
                axes=None,
                xvals=None,
                pos=None,
                scale=None,
                transform=None,
                autoHistogramRange=True,
                levelMode=None,
        ):
            """
            Set the image to be displayed in the widget.

            Parameters
            ----------
            img : np.ndarray
                The image to be displayed. See :func:`ImageItem.setImage` and *notes* below.
            autoRange : bool
                Whether to scale/pan the view to fit the image.
            autoLevels : bool
                Whether to update the white/black levels to fit the image.
            levels : tuple
                (min, max) white and black level values to use.
            axes : dict
                Dictionary indicating the interpretation for each axis. This is only needed to override the default guess.
                Format is::

                    {'t':0, 'x':1, 'y':2, 'c':3};
            xvals : np.ndarray
                1D array of values corresponding to the first axis in a 3D image. For video, this array should contain
                the time of each frame.
            pos
                Change the position of the displayed image
            scale
                Change the scale of the displayed image
            transform
                Set the transform of the displayed image. This option overrides *pos* and *scale*.
            autoHistogramRange : bool
                If True, the histogram y-range is automatically scaled to fit the image data.
            levelMode : str
                If specified, this sets the user interaction mode for setting image levels. Options are 'mono',
                which provides a single level control for all image channels, and 'rgb' or 'rgba', which provide
                individual controls for each channel.

            Notes
            -----
            For backward compatibility, image data is assumed to be in column-major order (column, row).
            However, most image data is stored in row-major order (row, column) and will need to be
            transposed before calling setImage()::

                imageview.setImage(imagedata.T)

            This requirement can be changed by the ``imageAxisOrder``
            :ref:`global configuration option <apiref_config>`.
            """
            profiler = debug.Profiler()

            if not isinstance(img, np.ndarray):
                required = ['dtype', 'max', 'min', 'ndim', 'shape', 'size']
                if not all(hasattr(img, attr) for attr in required):
                    raise TypeError("Image must be NumPy array or any object "
                                    "that provides compatible attributes/methods:\n"
                                    "  %s" % str(required))

            self.image = img
            self.imageDisp = None
            if levelMode is not None:
                self.ui.histogram.setLevelMode(levelMode)

            profiler()

            if axes is None:
                x,y = (0, 1) if self.imageItem.axisOrder == 'col-major' else (1, 0)

                if img.ndim == 2:
                    self.axes = {'t': None, 'x': x, 'y': y, 'c': None}
                elif img.ndim == 3:
                    # Ambiguous case; make a guess
                    if img.shape[2] <= 4:
                        self.axes = {'t': None, 'x': x, 'y': y, 'c': 2}
                    else:
                        self.axes = {'t': 0, 'x': x+1, 'y': y+1, 'c': None}
                elif img.ndim == 4:
                    # Even more ambiguous; just assume the default
                    self.axes = {'t': 0, 'x': x+1, 'y': y+1, 'c': 3}
                else:
                    raise Exception("Can not interpret image with dimensions %s" % (str(img.shape)))
            elif isinstance(axes, dict):
                self.axes = axes.copy()
            elif isinstance(axes, list) or isinstance(axes, tuple):
                self.axes = {}
                for i in range(len(axes)):
                    self.axes[axes[i]] = i
            else:
                raise Exception("Can not interpret axis specification %s. Must be like {'t': 2, 'x': 0, 'y': 1} or ('t', 'x', 'y', 'c')" % (str(axes)))

            for x in ['t', 'x', 'y', 'c']:
                self.axes[x] = self.axes.get(x, None)
            axes = self.axes

            if xvals is not None:
                self.tVals = xvals
            elif axes['t'] is not None:
                self.tVals = np.arange(img.shape[axes['t']])

            profiler()

            self.currentIndex = 0
            self.updateImage(autoHistogramRange=autoHistogramRange)
            if levels is None and autoLevels:
                self.autoLevels()
            if levels is not None:  ## this does nothing since getProcessedImage sets these values again.
                self.setLevels(*levels)

            if self.ui.roiBtn.isChecked():
                self.roiChanged()

            profiler()

            if self.axes['t'] is not None:
                self.ui.roiPlot.setXRange(self.tVals.min(), self.tVals.max())
                self.frameTicks.setXVals(self.tVals)
                self.timeLine.setValue(0)
                if len(self.tVals) > 1:
                    start = self.tVals.min()
                    stop = self.tVals.max() + abs(self.tVals[-1] - self.tVals[0]) * 0.02
                elif len(self.tVals) == 1:
                    start = self.tVals[0] - 0.5
                    stop = self.tVals[0] + 0.5
                else:
                    start = 0
                    stop = 1
                for s in [self.timeLine, self.normRgn]:
                    s.setBounds([start, stop])

            profiler()

            if transform is None:
                transform = QtGui.QTransform()
                # note that the order of transform is
                #   scale followed by translate
                if pos is not None:
                    transform.translate(*pos)
                if scale is not None:
                    transform.scale(*scale)
            self.imageItem.setTransform(transform)

            profiler()

            if autoRange:
                self.autoRange()
            self.roiClicked()

            profiler()

        def clear(self):
            self.image = None
            self.imageItem.clear()

        def play(self, rate=None):
            """Begin automatically stepping frames forward at the given rate (in fps).
            This can also be accessed by pressing the spacebar."""
            if rate is None:
                rate = self._pausedPlayRate or self.fps
            if rate == 0 and self.playRate not in (None, 0):
                self._pausedPlayRate = self.playRate
            self.playRate = rate

            if rate == 0:
                self.playTimer.stop()
                return

            self.lastPlayTime = perf_counter()
            if not self.playTimer.isActive():
                self.playTimer.start(abs(int(1000/rate)))

        def togglePause(self):
            if self.playTimer.isActive():
                self.play(0)
            elif self.playRate == 0:
                if self._pausedPlayRate is not None:
                    fps = self._pausedPlayRate
                else:
                    fps = (self.nframes() - 1) / (self.tVals[-1] - self.tVals[0])
                self.play(fps)
            else:
                self.play(self.playRate)

        def setHistogramLabel(self, text=None, **kwargs):
            """
            Set the label text of the histogram axis similar to
            :func:`AxisItem.setLabel() <pyqtgraph.AxisItem.setLabel>`
            """
            a = self.ui.histogram.axis
            a.setLabel(text, **kwargs)
            if text == '':
                a.showLabel(False)
            self.ui.histogram.setMinimumWidth(135)

        def nframes(self):
            """
            Returns
            -------
            int
                The number of frames in the image data.
            """
            if self.image is None:
                return 0
            elif self.axes['t'] is not None:
                return self.image.shape[self.axes['t']]
            return 1

        def autoLevels(self):
            """Set the min/max intensity levels automatically to match the image data."""
            self.setLevels(rgba=self._imageLevels)

        def setLevels(self, *args, **kwds):
            """Set the min/max (bright and dark) levels.

            See :func:`HistogramLUTItem.setLevels <pyqtgraph.HistogramLUTItem.setLevels>`.
            """
            self.ui.histogram.setLevels(*args, **kwds)

        def autoRange(self):
            """Auto scale and pan the view around the image such that the image fills the view."""
            self.getProcessedImage()
            self.view.autoRange()

        def getProcessedImage(self):
            """Returns the image data after it has been processed by any normalization options in use.
            """
            if self.imageDisp is None:
                image = self.normalize(self.image)
                self.imageDisp = image
                self._imageLevels = self.quickMinMax(self.imageDisp)
                self.levelMin = min([level[0] for level in self._imageLevels])
                self.levelMax = max([level[1] for level in self._imageLevels])

            return self.imageDisp

        def close(self):
            """Closes the widget nicely, making sure to clear the graphics scene and release memory."""
            self.clear()
            self.imageDisp = None
            self.imageItem.setParent(None)
            super(ImageView, self).close()
            self.setParent(None)

        def keyPressEvent(self, ev):
            if not self.hasTimeAxis():
                super().keyPressEvent(ev)
                return

            if ev.key() == QtCore.Qt.Key.Key_Space:
                self.togglePause()
                ev.accept()
            elif ev.key() == QtCore.Qt.Key.Key_Home:
                self.setCurrentIndex(0)
                self.play(0)
                ev.accept()
            elif ev.key() == QtCore.Qt.Key.Key_End:
                self.setCurrentIndex(self.nframes()-1)
                self.play(0)
                ev.accept()
            elif ev.key() in self.noRepeatKeys:
                ev.accept()
                if ev.isAutoRepeat():
                    return
                self.keysPressed[ev.key()] = 1
                self.evalKeyState()
            else:
                super().keyPressEvent(ev)

        def keyReleaseEvent(self, ev):
            if not self.hasTimeAxis():
                super().keyReleaseEvent(ev)
                return

            if ev.key() in [QtCore.Qt.Key.Key_Space, QtCore.Qt.Key.Key_Home, QtCore.Qt.Key.Key_End]:
                ev.accept()
            elif ev.key() in self.noRepeatKeys:
                ev.accept()
                if ev.isAutoRepeat():
                    return
                try:
                    del self.keysPressed[ev.key()]
                except:
                    self.keysPressed = {}
                self.evalKeyState()
            else:
                super().keyReleaseEvent(ev)

        def evalKeyState(self):
            if len(self.keysPressed) == 1:
                key = list(self.keysPressed.keys())[0]
                if key == QtCore.Qt.Key.Key_Right:
                    self.play(20)
                    self.jumpFrames(1)
                    # effectively pause playback for 0.2 s
                    self.lastPlayTime = perf_counter() + 0.2
                elif key == QtCore.Qt.Key.Key_Left:
                    self.play(-20)
                    self.jumpFrames(-1)
                    self.lastPlayTime = perf_counter() + 0.2
                elif key == QtCore.Qt.Key.Key_Up:
                    self.play(-100)
                elif key == QtCore.Qt.Key.Key_Down:
                    self.play(100)
                elif key == QtCore.Qt.Key.Key_PageUp:
                    self.play(-1000)
                elif key == QtCore.Qt.Key.Key_PageDown:
                    self.play(1000)
            else:
                self.play(0)

        @QtCore.Slot()
        def timeout(self):
            now = perf_counter()
            dt = now - self.lastPlayTime
            if dt < 0:
                return
            n = int(self.playRate * dt)
            if n != 0:
                self.lastPlayTime += (float(n)/self.playRate)
                if self.currentIndex+n > self.image.shape[self.axes['t']]:
                    self.play(0)
                self.jumpFrames(n)

        def setCurrentIndex(self, ind):
            """Set the currently displayed frame index."""
            index = fn.clip_scalar(ind, 0, self.nframes()-1)
            self.currentIndex = index
            self.updateImage()
            self.ignoreTimeLine = True
            # Implicitly call timeLineChanged
            self.timeLine.setValue(self.tVals[index])
            self.ignoreTimeLine = False

        def jumpFrames(self, n):
            """Move video frame ahead n frames (may be negative)"""
            if self.axes['t'] is not None:
                self.setCurrentIndex(self.currentIndex + n)

        @QtCore.Slot()
        def normRadioChanged(self):
            self.imageDisp = None
            self.updateImage()
            self.autoLevels()
            self.roiChanged()
            self.sigProcessingChanged.emit(self)

        @QtCore.Slot()
        def updateNorm(self):
            if self.ui.normTimeRangeCheck.isChecked():
                self.normRgn.show()
            else:
                self.normRgn.hide()

            if self.ui.normROICheck.isChecked():
                self.normRoi.show()
            else:
                self.normRoi.hide()

            if not self.ui.normOffRadio.isChecked():
                self.imageDisp = None
                self.updateImage()
                self.autoLevels()
                self.roiChanged()
                self.sigProcessingChanged.emit(self)

        @QtCore.Slot(bool)
        def normToggled(self, b):
            self.ui.normGroup.setVisible(b)
            self.normRoi.setVisible(b and self.ui.normROICheck.isChecked())
            self.normRgn.setVisible(b and self.ui.normTimeRangeCheck.isChecked())

        def hasTimeAxis(self):
            return 't' in self.axes and self.axes['t'] is not None

        @QtCore.Slot()
        def roiClicked(self):
            showRoiPlot = False
            if self.ui.roiBtn.isChecked():
                showRoiPlot = True
                self.roi.show()
                self.ui.roiPlot.setMouseEnabled(True, True)
                self.ui.splitter.setSizes([int(self.height()*0.6), int(self.height()*0.4)])
                self.ui.splitter.handle(1).setEnabled(True)
                self.roiChanged()
                for c in self.roiCurves:
                    c.show()
                self.ui.roiPlot.showAxis('left')
            else:
                self.roi.hide()
                self.ui.roiPlot.setMouseEnabled(False, False)
                for c in self.roiCurves:
                    c.hide()
                self.ui.roiPlot.hideAxis('left')

            if self.hasTimeAxis():
                showRoiPlot = True
                mn = self.tVals.min()
                mx = self.tVals.max()
                self.ui.roiPlot.setXRange(mn, mx, padding=0.01)
                self.timeLine.show()
                self.timeLine.setBounds([mn, mx])
                if not self.ui.roiBtn.isChecked():
                    self.ui.splitter.setSizes([self.height()-35, 35])
                    self.ui.splitter.handle(1).setEnabled(False)
            else:
                self.timeLine.hide()

            self.ui.roiPlot.setVisible(showRoiPlot)

        @QtCore.Slot()
        def roiChanged(self):
            # Extract image data from ROI
            if self.image is None:
                return

            image = self.getProcessedImage()

            # getArrayRegion axes should be (x, y) of data array for col-major,
            # (y, x) for row-major
            # can't just transpose input because ROI is axisOrder aware
            colmaj = self.imageItem.axisOrder == 'col-major'
            if colmaj:
                axes = (self.axes['x'], self.axes['y'])
            else:
                axes = (self.axes['y'], self.axes['x'])

            data, coords = self.roi.getArrayRegion(
                image.view(np.ndarray), img=self.imageItem, axes=axes,
                returnMappedCoords=True)

            if data is None:
                return

            # Convert extracted data into 1D plot data
            if self.axes['t'] is None:
                # Average across y-axis of ROI
                data = data.mean(axis=self.axes['y'])

                # get coordinates along x axis of ROI mapped to range (0, roiwidth)
                if colmaj:
                    coords = coords[:, :, 0] - coords[:, 0:1, 0]
                else:
                    coords = coords[:, 0, :] - coords[:, 0, 0:1]
                xvals = (coords**2).sum(axis=0) ** 0.5
            else:
                # Average data within entire ROI for each frame
                data = data.mean(axis=axes)
                xvals = self.tVals

            # Handle multi-channel data
            if data.ndim == 1:
                plots = [(xvals, data, 'w')]
            if data.ndim == 2:
                if data.shape[1] == 1:
                    colors = 'w'
                else:
                    colors = 'rgbw'
                plots = []
                for i in range(data.shape[1]):
                    d = data[:,i]
                    plots.append((xvals, d, colors[i]))

            # Update plot line(s)
            while len(plots) < len(self.roiCurves):
                c = self.roiCurves.pop()
                c.scene().removeItem(c)
            while len(plots) > len(self.roiCurves):
                self.roiCurves.append(self.ui.roiPlot.plot())
            for i in range(len(plots)):
                x, y, p = plots[i]
                self.roiCurves[i].setData(x, y, pen=p)

        def quickMinMax(self, data):
            """
            Estimate the min/max values of *data* by subsampling.
            Returns [(min, max), ...] with one item per channel
            """
            while data.size > 1e6:
                ax = np.argmax(data.shape)
                sl = [slice(None)] * data.ndim
                sl[ax] = slice(None, None, 2)
                data = data[tuple(sl)]

            cax = self.axes['c']
            if cax is None:
                if data.size == 0:
                    return [(0, 0)]
                return [(float(nanmin(data)), float(nanmax(data)))]
            else:
                if data.size == 0:
                    return [(0, 0)] * data.shape[-1]
                return [(float(nanmin(data.take(i, axis=cax))),
                         float(nanmax(data.take(i, axis=cax)))) for i in range(data.shape[-1])]

        def normalize(self, image):
            """
            Process *image* using the normalization options configured in the
            control panel.

            This can be repurposed to process any data through the same filter.
            """
            if self.ui.normOffRadio.isChecked():
                return image

            div = self.ui.normDivideRadio.isChecked()
            norm = image.view(np.ndarray).copy()
            #if div:
                #norm = ones(image.shape)
            #else:
                #norm = zeros(image.shape)
            if div:
                norm = norm.astype(np.float32)

            if self.ui.normTimeRangeCheck.isChecked() and image.ndim == 3:
                (sind, start) = self.timeIndex(self.normRgn.lines[0])
                (eind, end) = self.timeIndex(self.normRgn.lines[1])
                #print start, end, sind, eind
                n = image[sind:eind+1].mean(axis=0)
                n.shape = (1,) + n.shape
                if div:
                    norm /= n
                else:
                    norm -= n

            if self.ui.normFrameCheck.isChecked() and image.ndim == 3:
                n = image.mean(axis=1).mean(axis=1)
                n.shape = n.shape + (1, 1)
                if div:
                    norm /= n
                else:
                    norm -= n

            if self.ui.normROICheck.isChecked() and image.ndim == 3:
                n = self.normRoi.getArrayRegion(norm, self.imageItem, (1, 2)).mean(axis=1).mean(axis=1)
                n = n[:,np.newaxis,np.newaxis]
                #print start, end, sind, eind
                if div:
                    norm /= n
                else:
                    norm -= n

            return norm

        @QtCore.Slot()
        def timeLineChanged(self):
            if not self.ignoreTimeLine:
                self.play(0)

            (ind, time) = self.timeIndex(self.timeLine)
            if ind != self.currentIndex:
                self.currentIndex = ind
                self.updateImage()
            if self.discreteTimeLine:
                with fn.SignalBlock(self.timeLine.sigPositionChanged, self.timeLineChanged):
                    if self.tVals is not None:
                        self.timeLine.setPos(self.tVals[ind])
                    else:
                        self.timeLine.setPos(ind)

            self.sigTimeChanged.emit(ind, time)

        def updateImage(self, autoHistogramRange=True):
            ## Redraw image on screen
            if self.image is None:
                return

            image = self.getProcessedImage()
            if autoHistogramRange:
                self.ui.histogram.setHistogramRange(self.levelMin, self.levelMax)

            # Transpose image into order expected by ImageItem
            if self.imageItem.axisOrder == 'col-major':
                axorder = ['t', 'x', 'y', 'c']
            else:
                axorder = ['t', 'y', 'x', 'c']
            axorder = [self.axes[ax] for ax in axorder if self.axes[ax] is not None]
            image = image.transpose(axorder)

            # Select time index
            if self.axes['t'] is not None:
                self.ui.roiPlot.show()
                image = image[self.currentIndex]

            self.imageItem.updateImage(image)

        def timeIndex(self, slider):
            """
            Returns
            -------
            int
                The index of the frame closest to the timeline slider.
            float
                The time value of the slider.
            """
            if not self.hasTimeAxis():
                return 0, 0.0

            t = slider.value()

            xv = self.tVals
            if xv is None:
                ind = int(t)
            else:
                if len(xv) < 2:
                    return 0, 0.0
                inds = np.argwhere(xv <= t)
                if len(inds) < 1:
                    return 0, t
                ind = inds[-1, 0]
            return ind, t

        def getView(self):
            """Return the ViewBox (or other compatible object) which displays the ImageItem"""
            return self.view

        def getImageItem(self):
            """Return the ImageItem for this ImageView."""
            return self.imageItem

        def getRoiPlot(self):
            """Return the ROI PlotWidget for this ImageView"""
            return self.ui.roiPlot

        def getHistogramWidget(self):
            """Return the HistogramLUTWidget for this ImageView"""
            return self.ui.histogram

        def export(self, fileName):
            """
            Export data from the ImageView to a file, or to a stack of files if
            the data is 3D. Saving an image stack will result in index numbers
            being added to the file name. Images are saved as they would appear
            onscreen, with levels and lookup table applied.
            """
            img = self.getProcessedImage()
            if self.hasTimeAxis():
                base, ext = os.path.splitext(fileName)
                fmt = "%%s%%0%dd%%s" % int(log10(img.shape[0])+1)
                for i in range(img.shape[0]):
                    self.imageItem.setImage(img[i], autoLevels=False)
                    self.imageItem.save(fmt % (base, i, ext))
                self.updateImage()
            else:
                self.imageItem.save(fileName)

        @QtCore.Slot()
        def exportClicked(self):
            fileName, _ = QtWidgets.QFileDialog.getSaveFileName()
            if not fileName:
                return
            self.export(fileName)

        def buildMenu(self):
            self.menu = QtWidgets.QMenu()
            self.normAction = QtGui.QAction(translate("ImageView", "Normalization"), self.menu)
            self.normAction.setCheckable(True)
            self.normAction.toggled.connect(self.normToggled)
            self.menu.addAction(self.normAction)
            self.exportAction = QtGui.QAction(translate("ImageView", "Export"), self.menu)
            self.exportAction.triggered.connect(self.exportClicked)
            self.menu.addAction(self.exportAction)

        @QtCore.Slot()
        def menuClicked(self):
            if self.menu is None:
                self.buildMenu()
            self.menu.popup(QtGui.QCursor.pos())

        def setColorMap(self, colormap):
            """Set the color map.

            Parameters
            ----------
            colormap : ColorMap
                The ColorMap to use for coloring images.
            """
            self.ui.histogram.gradient.setColorMap(colormap)

        @addGradientListToDocstring()
        def setPredefinedGradient(self, name):
            """Set one of the gradients defined in :class:`GradientEditorItem`.
            Currently available gradients are:
            """
            self.ui.histogram.gradient.loadPreset(name)