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# Source code for pyqtgraph.graphicsItems.PlotItem.PlotItem

    import collections.abc
    import os
    import warnings
    import weakref

    import numpy as np

    from ... import functions as fn
    from ... import icons
    from ...Qt import QtCore, QtWidgets
    from ...WidgetGroup import WidgetGroup
    from ...widgets.FileDialog import FileDialog
    from ..AxisItem import AxisItem
    from ..ButtonItem import ButtonItem
    from ..GraphicsWidget import GraphicsWidget
    from ..InfiniteLine import InfiniteLine
    from ..LabelItem import LabelItem
    from ..LegendItem import LegendItem
    from ..PlotCurveItem import PlotCurveItem
    from ..PlotDataItem import PlotDataItem
    from ..ScatterPlotItem import ScatterPlotItem
    from ..ViewBox import ViewBox

    translate = QtCore.QCoreApplication.translate

    from . import plotConfigTemplate_generic as ui_template

    __all__ = ['PlotItem']

    class PlotItem(GraphicsWidget):
        """GraphicsWidget implementing a standard 2D plotting area with axes.

        **Bases:** :class:`GraphicsWidget <pyqtgraph.GraphicsWidget>`

        This class provides the ViewBox-plus-axes that appear when using
        :func:`pg.plot() <pyqtgraph.plot>`, :class:`PlotWidget <pyqtgraph.PlotWidget>`,
        and :func:`GraphicsLayout.addPlot() <pyqtgraph.GraphicsLayout.addPlot>`.

        It's main functionality is:

          - Manage placement of ViewBox, AxisItems, and LabelItems
          - Create and manage a list of PlotDataItems displayed inside the ViewBox
          - Implement a context menu with commonly used display and analysis options

        Use :func:`plot() <pyqtgraph.PlotItem.plot>` to create a new PlotDataItem and
        add it to the view. Use :func:`addItem() <pyqtgraph.PlotItem.addItem>` to
        add any QGraphicsItem to the view.

        This class wraps several methods from its internal ViewBox:
          - :func:`setXRange <pyqtgraph.ViewBox.setXRange>`
          - :func:`setYRange <pyqtgraph.ViewBox.setYRange>`
          - :func:`setRange <pyqtgraph.ViewBox.setRange>`
          - :func:`autoRange <pyqtgraph.ViewBox.autoRange>`
          - :func:`setDefaultPadding <pyqtgraph.ViewBox.setDefaultPadding>`
          - :func:`setXLink <pyqtgraph.ViewBox.setXLink>`
          - :func:`setYLink <pyqtgraph.ViewBox.setYLink>`
          - :func:`setAutoPan <pyqtgraph.ViewBox.setAutoPan>`
          - :func:`setAutoVisible <pyqtgraph.ViewBox.setAutoVisible>`
          - :func:`setLimits <pyqtgraph.ViewBox.setLimits>`
          - :func:`viewRect <pyqtgraph.ViewBox.viewRect>`
          - :func:`viewRange <pyqtgraph.ViewBox.viewRange>`
          - :func:`setMouseEnabled <pyqtgraph.ViewBox.setMouseEnabled>`
          - :func:`enableAutoRange <pyqtgraph.ViewBox.enableAutoRange>`
          - :func:`disableAutoRange <pyqtgraph.ViewBox.disableAutoRange>`
          - :func:`setAspectLocked <pyqtgraph.ViewBox.setAspectLocked>`
          - :func:`invertY <pyqtgraph.ViewBox.invertY>`
          - :func:`invertX <pyqtgraph.ViewBox.invertX>`
          - :func:`register <pyqtgraph.ViewBox.register>`
          - :func:`unregister <pyqtgraph.ViewBox.unregister>`

        The ViewBox itself can be accessed by calling :func:`getViewBox() <pyqtgraph.PlotItem.getViewBox>`

        ==================== =======================================================================
        **Signals:**
        sigYRangeChanged     wrapped from :class:`ViewBox <pyqtgraph.ViewBox>`
        sigXRangeChanged     wrapped from :class:`ViewBox <pyqtgraph.ViewBox>`
        sigRangeChanged      wrapped from :class:`ViewBox <pyqtgraph.ViewBox>`
        ==================== =======================================================================
        """

        sigRangeChanged = QtCore.Signal(object, object)    ## Emitted when the ViewBox range has changed
        sigYRangeChanged = QtCore.Signal(object, object)   ## Emitted when the ViewBox Y range has changed
        sigXRangeChanged = QtCore.Signal(object, object)   ## Emitted when the ViewBox X range has changed

        lastFileDir = None

        def __init__(self, parent=None, name=None, labels=None, title=None, viewBox=None, axisItems=None, enableMenu=True, **kargs):
            """
            Create a new PlotItem. All arguments are optional.
            Any extra keyword arguments are passed to :func:`PlotItem.plot() <pyqtgraph.PlotItem.plot>`.

            ==============  ==========================================================================================
            **Arguments:**
            *title*         Title to display at the top of the item. Html is allowed.
            *labels*        A dictionary specifying the axis labels to display::

                                {'left': (args), 'bottom': (args), ...}

                            The name of each axis and the corresponding arguments are passed to
                            :func:`PlotItem.setLabel() <pyqtgraph.PlotItem.setLabel>`
                            Optionally, PlotItem my also be initialized with the keyword arguments left,
                            right, top, or bottom to achieve the same effect.
            *name*          Registers a name for this view so that others may link to it
            *viewBox*       If specified, the PlotItem will be constructed with this as its ViewBox.
            *axisItems*     Optional dictionary instructing the PlotItem to use pre-constructed items
                            for its axes. The dict keys must be axis names ('left', 'bottom', 'right', 'top')
                            and the values must be instances of AxisItem (or at least compatible with AxisItem).
            ==============  ==========================================================================================
            """

            GraphicsWidget.__init__(self, parent)

            self.setSizePolicy(QtWidgets.QSizePolicy.Policy.Expanding, QtWidgets.QSizePolicy.Policy.Expanding)

            ## Set up control buttons
            self.autoBtn = ButtonItem(icons.getGraphPixmap('auto'), 14, self)
            self.autoBtn.mode = 'auto'
            self.autoBtn.clicked.connect(self.autoBtnClicked)
            self.buttonsHidden = False ## whether the user has requested buttons to be hidden
            self.mouseHovering = False

            self.layout = QtWidgets.QGraphicsGridLayout()
            self.layout.setContentsMargins(1,1,1,1)
            self.setLayout(self.layout)
            self.layout.setHorizontalSpacing(0)
            self.layout.setVerticalSpacing(0)

            if viewBox is None:
                viewBox = ViewBox(parent=self, enableMenu=enableMenu)
            self.vb = viewBox
            self.vb.sigStateChanged.connect(self.viewStateChanged)

            # Enable or disable plotItem menu
            self.setMenuEnabled(enableMenu, None)

            if name is not None:
                self.vb.register(name)
            self.vb.sigRangeChanged.connect(self.sigRangeChanged)
            self.vb.sigXRangeChanged.connect(self.sigXRangeChanged)
            self.vb.sigYRangeChanged.connect(self.sigYRangeChanged)

            self.layout.addItem(self.vb, 2, 1)
            self.alpha = 1.0
            self.autoAlpha = True
            self.spectrumMode = False

            self.legend = None

            # Initialize axis items
            self.axes = {}
            self.setAxisItems(axisItems)

            self.titleLabel = LabelItem('', size='11pt', parent=self)
            self.layout.addItem(self.titleLabel, 0, 1)
            self.setTitle(None)  ## hide

            for i in range(4):
                self.layout.setRowPreferredHeight(i, 0)
                self.layout.setRowMinimumHeight(i, 0)
                self.layout.setRowSpacing(i, 0)
                self.layout.setRowStretchFactor(i, 1)

            for i in range(3):
                self.layout.setColumnPreferredWidth(i, 0)
                self.layout.setColumnMinimumWidth(i, 0)
                self.layout.setColumnSpacing(i, 0)
                self.layout.setColumnStretchFactor(i, 1)
            self.layout.setRowStretchFactor(2, 100)
            self.layout.setColumnStretchFactor(1, 100)

            self.items = []
            self.curves = []
            self.itemMeta = weakref.WeakKeyDictionary()
            self.dataItems = []
            self.paramList = {}
            self.avgCurves = {}
            # Change these properties to adjust the appearance of the averged curve:
            self.avgPen = fn.mkPen([0, 200, 0])
            self.avgShadowPen = fn.mkPen([0, 0, 0], width=4) # the previous default of [0,0,0,100] prevent fast drawing of the wide shadow line

            ### Set up context menu

            w = QtWidgets.QWidget()
            self.ctrl = c = ui_template.Ui_Form()
            c.setupUi(w)

            menuItems = [
                (translate("PlotItem", 'Transforms'), c.transformGroup),
                (translate("PlotItem", 'Downsample'), c.decimateGroup),
                (translate("PlotItem", 'Average'), c.averageGroup),
                (translate("PlotItem", 'Alpha'), c.alphaGroup),
                (translate("PlotItem", 'Grid'), c.gridGroup),
                (translate("PlotItem", 'Points'), c.pointsGroup),
            ]

            self.ctrlMenu = QtWidgets.QMenu(translate("PlotItem", 'Plot Options'))

            for name, grp in menuItems:
                sm = self.ctrlMenu.addMenu(name)
                act = QtWidgets.QWidgetAction(self)
                act.setDefaultWidget(grp)
                sm.addAction(act)

            self.stateGroup = WidgetGroup()
            for name, w in menuItems:
                self.stateGroup.autoAdd(w)

            self.fileDialog = None

            c.alphaGroup.toggled.connect(self.updateAlpha)
            c.alphaSlider.valueChanged.connect(self.updateAlpha)
            c.autoAlphaCheck.toggled.connect(self.updateAlpha)

            c.xGridCheck.toggled.connect(self.updateGrid)
            c.yGridCheck.toggled.connect(self.updateGrid)
            c.gridAlphaSlider.valueChanged.connect(self.updateGrid)

            c.fftCheck.toggled.connect(self.updateSpectrumMode)
            c.logXCheck.toggled.connect(self.updateLogMode)
            c.logYCheck.toggled.connect(self.updateLogMode)
            c.derivativeCheck.toggled.connect(self.updateDerivativeMode)
            c.phasemapCheck.toggled.connect(self.updatePhasemapMode)

            c.downsampleSpin.valueChanged.connect(self.updateDownsampling)
            c.downsampleCheck.toggled.connect(self.updateDownsampling)
            c.autoDownsampleCheck.toggled.connect(self.updateDownsampling)
            c.subsampleRadio.toggled.connect(self.updateDownsampling)
            c.meanRadio.toggled.connect(self.updateDownsampling)
            c.clipToViewCheck.toggled.connect(self.updateDownsampling)

            self.ctrl.avgParamList.itemClicked.connect(self.avgParamListClicked)
            self.ctrl.averageGroup.toggled.connect(self.avgToggled)

            self.ctrl.maxTracesCheck.toggled.connect(self._handle_max_traces_toggle)
            self.ctrl.forgetTracesCheck.toggled.connect(self.updateDecimation)
            self.ctrl.maxTracesSpin.valueChanged.connect(self.updateDecimation)

            if labels is None:
                labels = {}
            for label in list(self.axes.keys()):
                if label in kargs:
                    labels[label] = kargs[label]
                    del kargs[label]
            for k in labels:
                if isinstance(labels[k], str):
                    labels[k] = (labels[k],)
                self.setLabel(k, *labels[k])

            if title is not None:
                self.setTitle(title)

            if len(kargs) > 0:
                self.plot(**kargs)

        def implements(self, interface=None):
            return interface in ['ViewBoxWrapper']

        def getViewBox(self):
            """Return the :class:`ViewBox <pyqtgraph.ViewBox>` contained within."""
            return self.vb

        ## Wrap a few methods from viewBox.
        #Important: don't use a settattr(m, getattr(self.vb, m)) as we'd be leaving the viebox alive
        #because we had a reference to an instance method (creating wrapper methods at runtime instead).
        for m in ['setXRange', 'setYRange', 'setXLink', 'setYLink', 'setAutoPan',         # NOTE:
                  'setAutoVisible', 'setDefaultPadding', 'setRange', 'autoRange', 'viewRect', 'viewRange',     # If you update this list, please
                  'setMouseEnabled', 'setLimits', 'enableAutoRange', 'disableAutoRange',  # update the class docstring
                  'setAspectLocked', 'invertY', 'invertX', 'register', 'unregister']:                # as well.

            def _create_method(name):
                def method(self, *args, **kwargs):
                    return getattr(self.vb, name)(*args, **kwargs)
                method.__name__ = name
                return method

            locals()[m] = _create_method(m)

        del _create_method

        def setAxisItems(self, axisItems=None):
            """
            Place axis items as given by `axisItems`. Initializes non-existing axis items.

            ==============  ==========================================================================================
            **Arguments:**
            *axisItems*     Optional dictionary instructing the PlotItem to use pre-constructed items
                            for its axes. The dict keys must be axis names ('left', 'bottom', 'right', 'top')
                            and the values must be instances of AxisItem (or at least compatible with AxisItem).
            ==============  ==========================================================================================
            """

            if axisItems is None:
                axisItems = {}

            # Array containing visible axis items
            # Also containing potentially hidden axes, but they are not touched so it does not matter
            visibleAxes = ['left', 'bottom']
            visibleAxes.extend(axisItems.keys()) # Note that it does not matter that this adds
                                                 # some values to visibleAxes a second time

            for k, pos in (('top', (1,1)), ('bottom', (3,1)), ('left', (2,0)), ('right', (2,2))):
                if k in self.axes:
                    if k not in axisItems:
                        continue # Nothing to do here

                    # Remove old axis
                    oldAxis = self.axes[k]['item']
                    self.layout.removeItem(oldAxis)
                    oldAxis.scene().removeItem(oldAxis)
                    oldAxis.unlinkFromView()

                # Create new axis
                if k in axisItems:
                    axis = axisItems[k]
                    if axis.scene() is not None:
                        if k not in self.axes or axis != self.axes[k]["item"]:
                            raise RuntimeError(
                                "Can't add an axis to multiple plots. Shared axes"
                                " can be achieved with multiple AxisItem instances"
                                " and set[X/Y]Link.")
                else:
                    axis = AxisItem(orientation=k, parent=self)

                # Set up new axis
                axis.linkToView(self.vb)
                self.axes[k] = {'item': axis, 'pos': pos}
                self.layout.addItem(axis, *pos)
                # place axis above images at z=0, items that want to draw over the axes should be placed at z>=1:
                axis.setZValue(0.5)
                axis.setFlag(axis.GraphicsItemFlag.ItemNegativeZStacksBehindParent)
                axisVisible = k in visibleAxes
                self.showAxis(k, axisVisible)

        def setLogMode(self, x=None, y=None):
            """
            Set log scaling for `x` and/or `y` axes.
            This informs PlotDataItems to transform logarithmically and switches
            the axes to use log ticking.

            Note that *no other items* in the scene will be affected by
            this; there is (currently) no generic way to redisplay a GraphicsItem
            with log coordinates.

            """
            if x is not None:
                self.ctrl.logXCheck.setChecked(x)
            if y is not None:
                self.ctrl.logYCheck.setChecked(y)

        def showGrid(self, x=None, y=None, alpha=None):
            """
            Show or hide the grid for either axis.

            ==============  =====================================
            **Arguments:**
            x               (bool) Whether to show the X grid
            y               (bool) Whether to show the Y grid
            alpha           (0.0-1.0) Opacity of the grid
            ==============  =====================================
            """
            if x is None and y is None and alpha is None:
                raise Exception("Must specify at least one of x, y, or alpha.")  ## prevent people getting confused if they just call showGrid()

            if x is not None:
                self.ctrl.xGridCheck.setChecked(x)
            if y is not None:
                self.ctrl.yGridCheck.setChecked(y)
            if alpha is not None:
                v = fn.clip_scalar(alpha, 0, 1) * self.ctrl.gridAlphaSlider.maximum() # slider range 0 to 255
                self.ctrl.gridAlphaSlider.setValue( int(v) )

        def close(self):
            ## Most of this crap is needed to avoid PySide trouble.
            ## The problem seems to be whenever scene.clear() leads to deletion of widgets (either through proxies or qgraphicswidgets)
            ## the solution is to manually remove all widgets before scene.clear() is called
            if self.ctrlMenu is None: ## already shut down
                return
            self.ctrlMenu.setParent(None)
            self.ctrlMenu = None

            self.autoBtn.setParent(None)
            self.autoBtn = None

            for k in self.axes:
                i = self.axes[k]['item']
                i.close()

            self.axes = None
            self.scene().removeItem(self.vb)
            self.vb = None

        def registerPlot(self, name):   ## for backward compatibility
            self.vb.register(name)

        def updateGrid(self, *args):
            alpha = self.ctrl.gridAlphaSlider.value()
            x = alpha if self.ctrl.xGridCheck.isChecked() else False
            y = alpha if self.ctrl.yGridCheck.isChecked() else False
            self.getAxis('top').setGrid(x)
            self.getAxis('bottom').setGrid(x)
            self.getAxis('left').setGrid(y)
            self.getAxis('right').setGrid(y)

        def viewGeometry(self):
            """Return the screen geometry of the viewbox"""
            v = self.scene().views()[0]
            b = self.vb.mapRectToScene(self.vb.boundingRect())
            wr = v.mapFromScene(b).boundingRect()
            pos = v.mapToGlobal(v.pos())
            wr.adjust(pos.x(), pos.y(), pos.x(), pos.y())
            return wr

        def avgToggled(self, b):
            if b:
                self.recomputeAverages()
            for k in self.avgCurves:
                self.avgCurves[k][1].setVisible(b)

        def avgParamListClicked(self, item):
            name = str(item.text())
            self.paramList[name] = (item.checkState() == QtCore.Qt.CheckState.Checked)
            self.recomputeAverages()

        def recomputeAverages(self):
            if not self.ctrl.averageGroup.isChecked():
                return
            for k in self.avgCurves:
                self.removeItem(self.avgCurves[k][1])
            self.avgCurves = {}
            for c in self.curves:
                self.addAvgCurve(c)
            self.replot()

        def addAvgCurve(self, curve):
            ## Add a single curve into the pool of curves averaged together

            ## If there are plot parameters, then we need to determine which to average together.
            remKeys = []
            addKeys = []
            if self.ctrl.avgParamList.count() > 0:

                ### First determine the key of the curve to which this new data should be averaged
                for i in range(self.ctrl.avgParamList.count()):
                    item = self.ctrl.avgParamList.item(i)
                    if item.checkState() == QtCore.Qt.CheckState.Checked:
                        remKeys.append(str(item.text()))
                    else:
                        addKeys.append(str(item.text()))

                if len(remKeys) < 1:  ## In this case, there would be 1 average plot for each data plot; not useful.
                    return

            p = self.itemMeta.get(curve,{}).copy()
            for k in p:
                if type(k) is tuple:
                    p['.'.join(k)] = p[k]
                    del p[k]
            for rk in remKeys:
                if rk in p:
                    del p[rk]
            for ak in addKeys:
                if ak not in p:
                    p[ak] = None
            key = tuple(p.items())

            ### Create a new curve if needed
            if key not in self.avgCurves:
                plot = PlotDataItem()
                plot.setPen( self.avgPen )
                plot.setShadowPen(  self.avgShadowPen )
                plot.setAlpha(1.0, False)
                plot.setZValue(100)
                self.addItem(plot, skipAverage=True)
                self.avgCurves[key] = [0, plot]
            self.avgCurves[key][0] += 1
            (n, plot) = self.avgCurves[key]

            ### Average data together
            (x, y) = curve.getData()
            stepMode = curve.opts['stepMode']
            if plot.yData is not None and y.shape == plot.yData.shape:
                # note that if shapes do not match, then the average resets.
                newData = plot.yData * (n-1) / float(n) + y * 1.0 / float(n)
                plot.setData(plot.xData, newData, stepMode=stepMode)
            else:
                plot.setData(x, y, stepMode=stepMode)

        def autoBtnClicked(self):
            if self.autoBtn.mode == 'auto':
                self.enableAutoRange()
                self.autoBtn.hide()
            else:
                self.disableAutoRange()

        def viewStateChanged(self):
            self.updateButtons()

        def addItem(self, item, *args, **kargs):
            """
            Add a graphics item to the view box.
            If the item has plot data (:class:`PlotDataItem <pyqtgraph.PlotDataItem>` ,
            :class:`~pyqtgraph.PlotCurveItem` , :class:`~pyqtgraph.ScatterPlotItem` ),
            it may be included in analysis performed by the PlotItem.
            """
            if item in self.items:
                warnings.warn('Item already added to PlotItem, ignoring.')
                return
            self.items.append(item)
            vbargs = {}
            if 'ignoreBounds' in kargs:
                vbargs['ignoreBounds'] = kargs['ignoreBounds']
            self.vb.addItem(item, *args, **vbargs)
            name = None
            if hasattr(item, 'implements') and item.implements('plotData'):
                name = item.name()
                self.dataItems.append(item)
                #self.plotChanged()

                params = kargs.get('params', {})
                self.itemMeta[item] = params
                #item.setMeta(params)
                self.curves.append(item)
                #self.addItem(c)

            if hasattr(item, 'setLogMode'):
                item.setLogMode(self.ctrl.logXCheck.isChecked(), self.ctrl.logYCheck.isChecked())

            if isinstance(item, PlotDataItem):
                ## configure curve for this plot
                (alpha, auto) = self.alphaState()
                item.setAlpha(alpha, auto)
                item.setFftMode(self.ctrl.fftCheck.isChecked())
                item.setDownsampling(*self.downsampleMode())
                item.setClipToView(self.clipToViewMode())

                ## Hide older plots if needed
                self.updateDecimation()

                ## Add to average if needed
                self.updateParamList()
                if self.ctrl.averageGroup.isChecked() and 'skipAverage' not in kargs:
                    self.addAvgCurve(item)

                #c.connect(c, QtCore.SIGNAL('plotChanged'), self.plotChanged)
                #item.sigPlotChanged.connect(self.plotChanged)
                #self.plotChanged()
            #name = kargs.get('name', getattr(item, 'opts', {}).get('name', None))
            if name is not None and hasattr(self, 'legend') and self.legend is not None:
                self.legend.addItem(item, name=name)

        def listDataItems(self):
            """Return a list of all data items (:class:`PlotDataItem <pyqtgraph.PlotDataItem>`,
            :class:`~pyqtgraph.PlotCurveItem` , :class:`~pyqtgraph.ScatterPlotItem` , etc)
            contained in this PlotItem."""
            return self.dataItems[:]

        def addLine(self, x=None, y=None, z=None, **kwds):
            """
            Create an :class:`~pyqtgraph.InfiniteLine` and add to the plot.

            If `x` is specified,
            the line will be vertical. If `y` is specified, the line will be
            horizontal. All extra keyword arguments are passed to
            :func:`InfiniteLine.__init__() <pyqtgraph.InfiniteLine.__init__>`.
            Returns the item created.
            """
            kwds['pos'] = kwds.get('pos', x if x is not None else y)
            kwds['angle'] = kwds.get('angle', 0 if x is None else 90)
            line = InfiniteLine(**kwds)
            self.addItem(line)
            if z is not None:
                line.setZValue(z)
            return line

        def removeItem(self, item):
            """
            Remove an item from the PlotItem's :class:`~pyqtgraph.ViewBox`.
            """
            if not item in self.items:
                return
            self.items.remove(item)
            if item in self.dataItems:
                self.dataItems.remove(item)

            self.vb.removeItem(item)

            if item in self.curves:
                self.curves.remove(item)
                self.updateDecimation()
                self.updateParamList()

            if self.legend is not None:
                self.legend.removeItem(item)

        def clear(self):
            """
            Remove all items from the PlotItem's :class:`~pyqtgraph.ViewBox`.
            """
            for i in self.items[:]:
                self.removeItem(i)
            self.avgCurves = {}

        def clearPlots(self):
            for i in self.curves[:]:
                self.removeItem(i)
            self.avgCurves = {}

        def plot(self, *args, **kargs):
    #        **Additional arguments:**
            """
            Add and return a new plot.
            See :func:`PlotDataItem.__init__ <pyqtgraph.PlotDataItem.__init__>` for data arguments

            **Additional allowed arguments**

            ========= =================================================================
            `clear`   clears all plots before displaying new data
            `params`  sets meta-parameters to associate with this data
            ========= =================================================================
            """
            clear = kargs.get('clear', False)
            params = kargs.get('params', None)

            if clear:
                self.clear()

            item = PlotDataItem(*args, **kargs)

            if params is None:
                params = {}
            self.addItem(item, params=params)

            return item

        def addLegend(self, offset=(30, 30), **kwargs):
            """
            Create a new :class:`~pyqtgraph.LegendItem` and anchor it over the internal
            :class:`~pyqtgraph.ViewBox`. Plots added after this will be automatically
            displayed in the legend if they are created with a 'name' argument.

            If a :class:`~pyqtgraph.LegendItem` has already been created using this method,
            that item will be returned rather than creating a new one.

            Accepts the same arguments as :func:`~pyqtgraph.LegendItem.__init__`.
            """

            if self.legend is None:
                self.legend = LegendItem(offset=offset, **kwargs)
                self.legend.setParentItem(self.vb)
            return self.legend

        def addColorBar(self, image, **kargs):
            """
            Adds a color bar linked to the ImageItem specified by `image`.
            AAdditional parameters will be passed to the `pyqtgraph.ColorBarItem`.

            A call like `plot.addColorBar(img, colorMap='viridis')` is a convenient
            method to assign and show a color map.
            """
            from ..ColorBarItem import ColorBarItem  # avoid circular import
            bar = ColorBarItem(**kargs)
            bar.setImageItem( image, insert_in=self )
            return bar

        def multiDataPlot(self, *, x=None, y=None, constKwargs=None, **kwargs):
            """
            Allow plotting multiple curves on the same plot, changing some kwargs
            per curve.

            Parameters
            ----------
            x, y: array_like
                can be in the following formats:
                  - {x or y} = [n1, n2, n3, ...]: The named argument iterates through
                    ``n`` curves, while the unspecified argument is range(len(n)) for
                    each curve.
                  - x, [y1, y2, y3, ...]
                  - [x1, x2, x3, ...], [y1, y2, y3, ...]
                  - [x1, x2, x3, ...], y

                  where ``x_n`` and ``y_n`` are ``ndarray`` data for each curve. Since
                  ``x`` and ``y`` values are matched using ``zip``, unequal lengths mean
                  the longer array will be truncated. Note that 2D matrices for either x
                  or y are considered lists of curve
                  data.
            constKwargs: dict, optional
                A dict of {str: value} passed to each curve during ``plot()``.
            kwargs: dict, optional
                A dict of {str: iterable} where the str is the name of a kwarg and the
                iterable is a list of values, one for each plotted curve.
            """
            if (x is not None and not len(x)) or (y is not None and not len(y)):
                # Nothing to plot -- either x or y array will bail out early from
                # zip() below.
                return []
            def scalarOrNone(val):
                return val is None or (len(val) and np.isscalar(val[0]))

            if scalarOrNone(x) and scalarOrNone(y):
                raise ValueError(
                    "If both `x` and `y` represent single curves, use `plot` instead "
                    "of `multiPlot`."
                )
            curves = []
            constKwargs = constKwargs or {}
            xy: 'dict[str, list | None]' = dict(x=x, y=y)
            for key, oppositeVal in zip(('x', 'y'), [y, x]):
                oppositeVal: 'Iterable | None'
                val = xy[key]
                if val is None:
                    # Other curve has all data, make range that supports longest chain
                    val = range(max(len(curveN) for curveN in oppositeVal))
                if np.isscalar(val[0]):
                    # x, [y1, y2, y3, ...] or [x1, x2, x3, ...], y
                    # Repeat the single curve to match length of opposite list
                    val = [val] * len(oppositeVal)
                xy[key] = val
            for ii, (xi, yi) in enumerate(zip(xy['x'], xy['y'])):
                for kk in kwargs:
                    if len(kwargs[kk]) <= ii:
                        raise ValueError(
                            f"Not enough values for kwarg `{kk}`. "
                            f"Expected {ii + 1:d} (number of curves to plot), got"
                            f" {len(kwargs[kk]):d}"
                        )
                kwargsi = {kk: kwargs[kk][ii] for kk in kwargs}
                constKwargs.update(kwargsi)
                curves.append(self.plot(xi, yi, **constKwargs))
            return curves

        def scatterPlot(self, *args, **kargs):
            if 'pen' in kargs:
                kargs['symbolPen'] = kargs['pen']
            kargs['pen'] = None

            if 'brush' in kargs:
                kargs['symbolBrush'] = kargs['brush']
                del kargs['brush']

            if 'size' in kargs:
                kargs['symbolSize'] = kargs['size']
                del kargs['size']

            return self.plot(*args, **kargs)

        def replot(self):
            self.update()

        def updateParamList(self):
            self.ctrl.avgParamList.clear()
            ## Check to see that each parameter for each curve is present in the list
            for c in self.curves:
                for p in list(self.itemMeta.get(c, {}).keys()):
                    if type(p) is tuple:
                        p = '.'.join(p)

                    ## If the parameter is not in the list, add it.
                    matches = self.ctrl.avgParamList.findItems(p, QtCore.Qt.MatchFlag.MatchExactly)
                    if len(matches) == 0:
                        i = QtWidgets.QListWidgetItem(p)
                        if p in self.paramList and self.paramList[p] is True:
                            i.setCheckState(QtCore.Qt.CheckState.Checked)
                        else:
                            i.setCheckState(QtCore.Qt.CheckState.Unchecked)
                        self.ctrl.avgParamList.addItem(i)
                    else:
                        i = matches[0]

                    self.paramList[p] = (i.checkState() == QtCore.Qt.CheckState.Checked)

        def writeSvg(self, fileName=None):
            if fileName is None:
                self._chooseFilenameDialog(handler=self.writeSvg)
                return

            fileName = str(fileName)
            PlotItem.lastFileDir = os.path.dirname(fileName)

            from ...exporters import SVGExporter
            ex = SVGExporter(self)
            ex.export(fileName)

        def writeImage(self, fileName=None):
            if fileName is None:
                self._chooseFilenameDialog(handler=self.writeImage)
                return

            from ...exporters import ImageExporter
            ex = ImageExporter(self)
            ex.export(fileName)

        def writeCsv(self, fileName=None):
            if fileName is None:
                self._chooseFilenameDialog(handler=self.writeCsv)
                return

            fileName = str(fileName)
            PlotItem.lastFileDir = os.path.dirname(fileName)

            data = [c.getData() for c in self.curves]
            with open(fileName, 'w') as fd:
                i = 0
                while True:
                    done = True
                    for d in data:
                        if i < len(d[0]):
                            fd.write('%g,%g,' % (d[0][i], d[1][i]))
                            done = False
                        else:
                            fd.write(' , ,')
                    fd.write('\n')
                    if done:
                        break
                    i += 1

        def saveState(self):
            state = self.stateGroup.state()
            state['paramList'] = self.paramList.copy()
            state['view'] = self.vb.getState()
            return state

        def restoreState(self, state):
            if 'paramList' in state:
                self.paramList = state['paramList'].copy()

            self.stateGroup.setState(state)
            self.updateSpectrumMode()
            self.updateDownsampling()
            self.updateAlpha()
            self.updateDecimation()

            if 'powerSpectrumGroup' in state:
                state['fftCheck'] = state['powerSpectrumGroup']
            if 'gridGroup' in state:
                state['xGridCheck'] = state['gridGroup']
                state['yGridCheck'] = state['gridGroup']

            self.stateGroup.setState(state)
            self.updateParamList()

            if 'view' not in state:
                r = [[float(state['xMinText']), float(state['xMaxText'])], [float(state['yMinText']), float(state['yMaxText'])]]
                state['view'] = {
                    'autoRange': [state['xAutoRadio'], state['yAutoRadio']],
                    'linkedViews': [state['xLinkCombo'], state['yLinkCombo']],
                    'targetRange': r,
                    'viewRange': r,
                }
            self.vb.setState(state['view'])

        def widgetGroupInterface(self):
            return (None, PlotItem.saveState, PlotItem.restoreState)

        def updateSpectrumMode(self, b=None):
            if b is None:
                b = self.ctrl.fftCheck.isChecked()
            for c in self.curves:
                c.setFftMode(b)
            self.enableAutoRange()
            self.recomputeAverages()

        def updateLogMode(self):
            x = self.ctrl.logXCheck.isChecked()
            y = self.ctrl.logYCheck.isChecked()
            for i in self.items:
                if hasattr(i, 'setLogMode'):
                    i.setLogMode(x,y)
            self.getAxis('bottom').setLogMode(x, y)
            self.getAxis('top').setLogMode(x, y)
            self.getAxis('left').setLogMode(x, y)
            self.getAxis('right').setLogMode(x, y)
            self.enableAutoRange()
            self.recomputeAverages()

        def updateDerivativeMode(self):
            d = self.ctrl.derivativeCheck.isChecked()
            for i in self.items:
                if hasattr(i, 'setDerivativeMode'):
                    i.setDerivativeMode(d)
            self.enableAutoRange()
            self.recomputeAverages()

        def updatePhasemapMode(self):
            d = self.ctrl.phasemapCheck.isChecked()
            for i in self.items:
                if hasattr(i, 'setPhasemapMode'):
                    i.setPhasemapMode(d)
            self.enableAutoRange()
            self.recomputeAverages()

        def setDownsampling(self, ds=None, auto=None, mode=None):
            """
            Changes the default downsampling mode for all :class:`~pyqtgraph.PlotDataItem` managed by this plot.

            =============== ====================================================================
            **Arguments:**
            ds              (int) Reduce visible plot samples by this factor, or

                            (bool) To enable/disable downsampling without changing the value.

            auto            (bool) If `True`, automatically pick ``ds`` based on visible range

            mode            'subsample': Downsample by taking the first of N samples. This
                            method is fastest but least accurate.

                            'mean': Downsample by taking the mean of N samples.

                            'peak': Downsample by drawing a saw wave that follows the min and
                            max of the original data. This method produces the best visual
                            representation of the data but is slower.
            =============== ====================================================================
            """
            if ds is not None:
                if ds is False:
                    self.ctrl.downsampleCheck.setChecked(False)
                elif ds is True:
                    self.ctrl.downsampleCheck.setChecked(True)
                else:
                    self.ctrl.downsampleCheck.setChecked(True)
                    self.ctrl.downsampleSpin.setValue(ds)

            if auto is not None:
                if auto and ds is not False:
                    self.ctrl.downsampleCheck.setChecked(True)
                self.ctrl.autoDownsampleCheck.setChecked(auto)

            if mode is not None:
                if mode == 'subsample':
                    self.ctrl.subsampleRadio.setChecked(True)
                elif mode == 'mean':
                    self.ctrl.meanRadio.setChecked(True)
                elif mode == 'peak':
                    self.ctrl.peakRadio.setChecked(True)
                else:
                    raise ValueError("mode argument must be 'subsample', 'mean', or 'peak'.")

        def updateDownsampling(self):
            ds, auto, method = self.downsampleMode()
            clip = self.ctrl.clipToViewCheck.isChecked()
            for c in self.curves:
                c.setDownsampling(ds, auto, method)
                c.setClipToView(clip)
            self.recomputeAverages()

        def downsampleMode(self):
            if self.ctrl.downsampleCheck.isChecked():
                ds = self.ctrl.downsampleSpin.value()
            else:
                ds = 1

            auto = self.ctrl.downsampleCheck.isChecked() and self.ctrl.autoDownsampleCheck.isChecked()

            if self.ctrl.subsampleRadio.isChecked():
                method = 'subsample'
            elif self.ctrl.meanRadio.isChecked():
                method = 'mean'
            elif self.ctrl.peakRadio.isChecked():
                method = 'peak'
            else:
                raise ValueError("one of the method radios must be selected for: 'subsample', 'mean', or 'peak'.")

            return ds, auto, method

        def setClipToView(self, clip):
            """Set the default clip-to-view mode for all :class:`~pyqtgraph.PlotDataItem` s managed by this plot.
            If *clip* is `True`, then PlotDataItems will attempt to draw only points within the visible
            range of the ViewBox."""
            self.ctrl.clipToViewCheck.setChecked(clip)

        def clipToViewMode(self):
            return self.ctrl.clipToViewCheck.isChecked()

        def _handle_max_traces_toggle(self, check_state):
            if check_state:
                self.updateDecimation()
            else:
                for curve in self.curves:
                    curve.show()

        def updateDecimation(self):
            """
            Reduce or increase number of visible curves according to value set by the `Max Traces` spinner,
            if `Max Traces` is checked in the context menu. Destroy curves that are not visible if
            `forget traces` is checked. In most cases, this function is called automaticaly when the
            `Max Traces` GUI elements are triggered. It is also alled when the state of PlotItem is updated,
            its state is restored, or new items added added/removed.

            This can cause an unexpected or conflicting state of curve visibility (or destruction) if curve
            visibilities are controlled externally. In the case of external control it is advised to disable
            the `Max Traces` checkbox (or context menu) to prevent unexpected curve state changes.
            """
            if not self.ctrl.maxTracesCheck.isChecked():
                return
            else:
                numCurves = self.ctrl.maxTracesSpin.value()

            if self.ctrl.forgetTracesCheck.isChecked():
                for curve in self.curves[:-numCurves]:
                    curve.clear()
                    self.removeItem(curve)

            for i, curve in enumerate(reversed(self.curves)):
                if i < numCurves:
                    curve.show()
                else:
                    curve.hide()

        def updateAlpha(self, *args):
            (alpha, auto) = self.alphaState()
            for c in self.curves:
                c.setAlpha(alpha**2, auto)

        def alphaState(self):
            enabled = self.ctrl.alphaGroup.isChecked()
            auto = self.ctrl.autoAlphaCheck.isChecked()
            alpha = float(self.ctrl.alphaSlider.value()) / self.ctrl.alphaSlider.maximum()
            if auto:
                alpha = 1.0  ## should be 1/number of overlapping plots
            if not enabled:
                auto = False
                alpha = 1.0
            return (alpha, auto)

        def pointMode(self):
            if self.ctrl.pointsGroup.isChecked():
                if self.ctrl.autoPointsCheck.isChecked():
                    mode = None
                else:
                    mode = True
            else:
                mode = False
            return mode

        def resizeEvent(self, ev):
            if self.autoBtn is None:  ## already closed down
                return
            btnRect = self.mapRectFromItem(self.autoBtn, self.autoBtn.boundingRect())
            y = self.size().height() - btnRect.height()
            self.autoBtn.setPos(0, y)

        def getMenu(self):
            return self.ctrlMenu

        def getContextMenus(self, event):
            ## called when another item is displaying its context menu; we get to add extras to the end of the menu.
            if self.menuEnabled():
                return self.ctrlMenu
            else:
                return None

        def menuEnabled(self):
            return self._menuEnabled

        def hoverEvent(self, ev):
            if ev.enter:
                self.mouseHovering = True
            if ev.exit:
                self.mouseHovering = False

            self.updateButtons()

        def getLabel(self, key):
            pass

        def _checkScaleKey(self, key):
            if key not in self.axes:
                raise Exception("Scale '%s' not found. Scales are: %s" % (key, str(list(self.axes.keys()))))

        def getScale(self, key):
            return self.getAxis(key)

        def getAxis(self, name):
            """Return the specified AxisItem.
            *name* should be 'left', 'bottom', 'top', or 'right'."""
            self._checkScaleKey(name)
            return self.axes[name]['item']

        def setLabel(self, axis, text=None, units=None, unitPrefix=None, **args):
            """
            Sets the label for an axis. Basic HTML formatting is allowed.

            ==============  =================================================================
            **Arguments:**
            axis            must be one of 'left', 'bottom', 'right', or 'top'
            text            text to display along the axis. HTML allowed.
            units           units to display after the title. If units are given,
                            then an SI prefix will be automatically appended
                            and the axis values will be scaled accordingly.
                            (ie, use 'V' instead of 'mV'; 'm' will be added automatically)
            ==============  =================================================================
            """
            self.getAxis(axis).setLabel(text=text, units=units, **args)
            self.showAxis(axis)

        def setLabels(self, **kwds):
            """
            Convenience function allowing multiple labels and/or title to be set in one call.
            Keyword arguments can be 'title', 'left', 'bottom', 'right', or 'top'.
            Values may be strings or a tuple of arguments to pass to :func:`setLabel`.
            """
            for k,v in kwds.items():
                if k == 'title':
                    self.setTitle(v)
                else:
                    if isinstance(v, str):
                        v = (v,)
                    self.setLabel(k, *v)

        def showLabel(self, axis, show=True):
            """
            Show or hide one of the plot's axis labels (the axis itself will be unaffected).
            axis must be one of 'left', 'bottom', 'right', or 'top'
            """
            self.getScale(axis).showLabel(show)

        def setTitle(self, title=None, **args):
            """
            Set the title of the plot. Basic HTML formatting is allowed.
            If title is None, then the title will be hidden.
            """
            if title is None:
                self.titleLabel.setVisible(False)
                self.layout.setRowFixedHeight(0, 0)
                self.titleLabel.setMaximumHeight(0)
            else:
                self.titleLabel.setMaximumHeight(30)
                self.layout.setRowFixedHeight(0, 30)
                self.titleLabel.setVisible(True)
                self.titleLabel.setText(title, **args)

        def showAxis(self, axis, show=True):
            """
            Show or hide one of the plot's axes.
            axis must be one of 'left', 'bottom', 'right', or 'top'
            """
            s = self.getScale(axis)
            if show:
                s.show()
            else:
                s.hide()

        def hideAxis(self, axis):
            """Hide one of the PlotItem's axes. ('left', 'bottom', 'right', or 'top')"""
            self.showAxis(axis, False)

        def showAxes(self, selection, showValues=True, size=False):
            """
            Convenience method for quickly configuring axis settings.

            Parameters
            ----------
            selection: bool or tuple of bool
                Determines which AxisItems will be displayed.
                If in tuple form, order is (left, top, right, bottom)
                A single boolean value will set all axes,
                so that ``showAxes(True)`` configures the axes to draw a frame.
            showValues: bool or tuple of bool, optional
                Determines if values will be displayed for the ticks of each axis.
                True value shows values for left and bottom axis (default).
                False shows no values.
                If in tuple form, order is (left, top, right, bottom)
                None leaves settings unchanged.
                If not specified, left and bottom axes will be drawn with values.
            size: float or tuple of float, optional
                Reserves as fixed amount of space (width for vertical axis, height for horizontal axis)
                for each axis where tick values are enabled. If only a single float value is given, it
                will be applied for both width and height. If `None` is given instead of a float value,
                the axis reverts to automatic allocation of space.
                If in tuple form, order is (width, height)
            """
            if selection is True: # shortcut: enable all axes, creating a frame
                selection = (True, True, True, True)
            elif selection is False: # shortcut: disable all axes
                selection = (False, False, False, False)
            if showValues is True: # shortcut: defaults arrangement with labels at left and bottom
                showValues = (True, False, False, True)
            elif showValues is False: # shortcut: disable all labels
                showValues = (False, False, False, False)
            elif showValues is None: # leave labelling untouched
                showValues = (None, None, None, None)
            if size is not False and not isinstance(size, collections.abc.Sized):
                size = (size, size) # make sure that size is either False or a full set of (width, height)

            all_axes = ('left','top','right','bottom')
            for show_axis, show_value, axis_key in zip(selection, showValues, all_axes):
                if show_axis is None:
                    pass # leave axis display as it is.
                else:
                    if show_axis: self.showAxis(axis_key)
                    else        : self.hideAxis(axis_key)

                if show_value is None:
                    pass # leave value display as it is.
                else:
                    ax = self.getAxis(axis_key)
                    ax.setStyle(showValues=show_value)
                    if size is not False: # size adjustment is requested
                        if axis_key in ('left','right'):
                            if show_value: ax.setWidth(size[0])
                            else         : ax.setWidth( None )
                        elif axis_key in ('top', 'bottom'):
                            if show_value: ax.setHeight(size[1])
                            else         : ax.setHeight( None )

        def hideButtons(self):
            """Causes auto-scale button ('A' in lower-left corner) to be hidden for this PlotItem"""
            #self.ctrlBtn.hide()
            self.buttonsHidden = True
            self.updateButtons()

        def showButtons(self):
            """Causes auto-scale button ('A' in lower-left corner) to be visible for this PlotItem"""
            #self.ctrlBtn.hide()
            self.buttonsHidden = False
            self.updateButtons()

        def updateButtons(self):
            try:
                if self._exportOpts is False and self.mouseHovering and not self.buttonsHidden and not all(self.vb.autoRangeEnabled()):
                    self.autoBtn.show()
                else:
                    self.autoBtn.hide()
            except RuntimeError:
                pass  # this can happen if the plot has been deleted.

        def _plotArray(self, arr, x=None, **kargs):
            if arr.ndim != 1:
                raise Exception("Array must be 1D to plot (shape is %s)" % arr.shape)
            if x is None:
                x = np.arange(arr.shape[0])
            if x.ndim != 1:
                raise Exception("X array must be 1D to plot (shape is %s)" % x.shape)
            c = PlotCurveItem(arr, x=x, **kargs)
            return c

        def _plotMetaArray(self, arr, x=None, autoLabel=True, **kargs):
            if arr.ndim != 1:
                raise Exception('can only automatically plot 1 dimensional arrays.')
            ## create curve
            try:
                xv = arr.xvals(0)
            except:
                if x is None:
                    xv = np.arange(arr.shape[0])
                else:
                    xv = x
            c = PlotCurveItem(**kargs)
            c.setData(x=xv, y=arr.view(np.ndarray))

            if autoLabel:
                name = arr._info[0].get('name', None)
                units = arr._info[0].get('units', None)
                self.setLabel('bottom', text=name, units=units)

                name = arr._info[1].get('name', None)
                units = arr._info[1].get('units', None)
                self.setLabel('left', text=name, units=units)

            return c

        def setExportMode(self, export, opts=None):
            GraphicsWidget.setExportMode(self, export, opts)
            self.updateButtons()

        def _chooseFilenameDialog(self, handler):
            self.fileDialog = FileDialog()
            if PlotItem.lastFileDir is not None:
                self.fileDialog.setDirectory(PlotItem.lastFileDir)
            self.fileDialog.setFileMode(QtWidgets.QFileDialog.FileMode.AnyFile)
            self.fileDialog.setAcceptMode(QtWidgets.QFileDialog.AcceptMode.AcceptSave)
            self.fileDialog.show()
            self.fileDialog.fileSelected.connect(handler)