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Histogram2 Properties

Histogram2 appearance and behavior

Histogram2 properties control the appearance and behavior of the histogram. By changing property values, you can modify aspects of the histogram. Use dot notation to refer to a particular object and property:

h = histogram2(randn(10,1),randn(10,1));
c = h.NumBins;
h.NumBins = [4 7];

Bins

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Number of bins in each dimension, specified as a two-element vector of positive integers, [nX nY]. If you do not specify NumBins, then histogram2 automatically calculates how many bins to use based on the values in X and Y.

Example: histogram2(X,Y,[10 20])

Example: h.NumBins = [10 20]

Width of bins in each dimension, specified as a two-element vector. The first element in the vector gives the width of the bins in the x-dimension, and the second element gives the width of the bins in the y-dimension.

When you specify BinWidth, then histogram2 can use a maximum of 1024 bins (210) along each dimension. If instead the specified bin width requires more bins, then histogram2 uses a larger bin width corresponding to the maximum number of bins.

Example: histogram2(X,Y,'BinWidth',[5 10]) uses bins with size 5 in the x-dimension and size 10 in the y-dimension.

Bin edges in x-dimension, specified as a vector. Xedges(1) is the first edge of the first bin in the x-dimension, and Xedges(end) is the outer edge of the last bin.

The value [X(k),Y(k)] is in the (i,j)th bin if Xedges(i)X(k) < Xedges(i+1) and Yedges(j)Y(k) < Yedges(j+1). The last bins in each dimension also include the last (outer) edge. For example, [X(k),Y(k)] falls into the ith bin in the last row if Xedges(end-1)X(k)Xedges(end) and Yedges(i)Y(k) < Yedges(i+1).

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical

Bin edges in y-dimension, specified as a vector. Yedges(1) is the first edge of the first bin in the y-dimension, and Yedges(end) is the outer edge of the last bin.

The value [X(k),Y(k)] is in the (i,j)th bin if Xedges(i)X(k) < Xedges(i+1) and Yedges(j)Y(k) < Yedges(j+1). The last bins in each dimension also include the last (outer) edge. For example, [X(k),Y(k)] falls into the ith bin in the last row if Xedges(end-1)X(k)Xedges(end) and Yedges(i)Y(k) < Yedges(i+1).

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical

Bin limits in x-dimension, specified as a two-element vector, [xbmin,xbmax]. The vector indicates the first and last bin edges in the x-dimension.

histogram2 only plots data that falls within the bin limits inclusively, Data(Data(:,1)>=xbmin & Data(:,1)<=xbmax).

Selection mode for bin limits in x-dimension, specified as 'auto' or 'manual'. The default value is 'auto', so that the bin limits automatically adjust to the data along the x-axis.

If you explicitly specify either XBinLimits or XBinEdges, then XBinLimitsMode is set automatically to 'manual'. In that case, specify XBinLimitsMode as 'auto' to rescale the bin limits to the data.

Bin limits in y-dimension, specified as a two-element vector, [ybmin,ybmax]. The vector indicates the first and last bin edges in the y-dimension.

histogram2 only plots data that falls within the bin limits inclusively, Data(Data(:,2)>=ybmin & Data(:,2)<=ybmax).

Selection mode for bin limits in y-dimension, specified as 'auto' or 'manual'. The default value is 'auto', so that the bin limits automatically adjust to the data along the y-axis.

If you explicitly specify either YBinLimits or YBinEdges, then YBinLimitsMode is set automatically to 'manual'. In that case, specify YBinLimitsMode as 'auto' to rescale the bin limits to the data.

Binning algorithm, specified as one of the values in this table.

ValueDescription
'auto'The default 'auto' algorithm chooses a bin width to cover the data range and reveal the shape of the underlying distribution.
'scott'Scott’s rule is optimal if the data is close to being jointly normally distributed. This rule is appropriate for most other distributions, as well. It uses a bin size of [3.5*std(X(:))*numel(X)^(-1/4), 3.5*std(Y(:))*numel(Y)^(-1/4)].
'fd'The Freedman-Diaconis rule is less sensitive to outliers in the data, and might be more suitable for data with heavy-tailed distributions. It uses a bin size of [2*IQR(X(:))*numel(X)^(-1/4), 2*IQR(Y(:))*numel(Y)^(-1/4)], where IQR is the interquartile range.
'integers'The integer rule is useful with integer data, as it creates a bin for each pair of integers X and Y. It uses a bin width of 1 for each dimension and places bin edges halfway between integers. To avoid accidentally creating too many bins, you can use this rule to create a limit of 1024 bins (210). If the data range for either dimension is greater than 1024, then the integer rule uses wider bins instead.

Note

If you set the NumBins, XBinEdges, YBinEdges, BinWidth, or BinLimits property, then the BinMethod property is set to 'manual'.

Example: histogram2(X,Y,'BinMethod','integers') creates a bivariate histogram with the bins centered on integers.

Toggle display of empty bins, specified as either 'off' or 'on'. The default value is 'off'.

Example: histogram2(X,Y,'ShowEmptyBins','on') turns on the display of empty bins.

Data

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Data to distribute among bins, specified as a matrix of size m-by-2. The X and Y inputs to histogram2 correspond to the columns in Data, that is, Data(:,1) is X(:) and Data(:,2) is Y(:).

histogram2 ignores all NaN values. Similarly,histogram2 ignores Inf and -Inf values, unless the bin edges explicitly specify Inf or -Inf as a bin edge. Although NaN, Inf, and -Inf values are typically not plotted, they are still included in normalization calculations that include the total number of data elements, such as 'probability'.

If you change the values in the Data property of a histogram2 object, then the bin edges are not automatically updated. To recompute the bins, adjust a bin-related property such as BinMethod or NumBins.

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64 | logical

This property is read-only.

Bin values, returned as a numeric matrix. If Normalization is 'count', then the (i,j)th entry in Values specifies the bin count for the bin whose x edges are [Xedges(i), Xedges(i+1)] and whose y edges are [Yedges(j), Yedges(j+1)].

Depending on the value of Normalization, the Values property instead can contain a normalized variant of the bin counts.

The bin inclusion scheme for the different numbered bins in Values, as well as their relative orientation to the x-axis and y-axis, is

For example, the (1,1) bin includes values that fall on the first edge in each dimension, and the last bin in the bottom right includes values that fall on any of its edges.

Type of normalization, specified as one of the values in the table.

ValueDescription
'count'

Default normalization scheme. The height of each bar is the number of observations in each bin. The sum of the bar heights is equal to numel(X) and numel(Y).

'probability'

The height of each bar is the relative number of observations, (Number of observations in bin / Total number of observations). The sum of the bar heights is 1.

'countdensity'

The height of each bar is (Number of observations in bin) / (Area of bin). The volume (Height * Area) of each bar is the number of observations in the bin. The sum of the bar volumes is equal to numel(X) and numel(Y).

'pdf'

Probability density function estimate. The height of each bar is, (Number of observations in the bin) / (Total number of observations * Area of bin). The volume of each bar is the relative number of observations. The sum of the bar volumes is 1.

'cumcount'

The height of each bar is the cumulative number of observations in each bin and all previous bins in both the x and y dimensions. The height of the last bar is equal to numel(X) and numel(Y).

'cdf'

Cumulative density function estimate. The height of each bar is equal to the cumulative relative number of observations in each bin and all previous bins in both the x and y dimensions. The height of the last bar is 1.

Example: histogram2(X,Y,'Normalization','pdf') plots an estimate of the probability density function for X and Y.

Bin counts, specified as a matrix. Use this input to pass bin counts to histogram2 when the bin counts calculation is performed separately and you do not want histogram2 to do any data binning.

counts must be a matrix of size [nbinsX nbinsY] so that it specifies a bin count for each bin.

The number of bins in the x-dimension is length(XBinEdges)-1, and the number of bins in the y-dimension is length(YBinEdges)-1.

Compared to the Values property, BinCounts is not normalized. If Normalization is 'count', then Values and BinCounts are equivalent.

Example: histogram2('XBinEdges',-1:1,'YBinEdges',-2:2,'BinCounts',[1 2 3 4; 5 6 7 8])

Selection mode for bin counts, specified as 'auto' or 'manual'. The default value is 'auto', so that the bin counts are automatically computed from Data, XBinEdges, and YBinEdges.

If you specify BinCounts, then BinCountsMode is automatically set to 'manual'. Similarly, if you specify Data, then BinCountsMode is automatically set to 'auto'.

Color and Styling

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Histogram display style, specified as either 'bar3' or 'tile'. Specify 'tile' to display the histogram as a rectangular array of tiles with colors indicating the bin values.

The default value of 'bar3' displays the histogram using 3-D bars.

Example: histogram2(X,Y,'DisplayStyle','tile') plots the histogram as a rectangular array of tiles.

Histogram bar color, specified as one of these values:

  • 'none' — Bars are not filled.

  • 'flat' — Bar colors vary with height. Bars with different height have different colors. The colors are selected from the figure or axes colormap.

  • 'auto' — Bar color is chosen automatically (default).

  • RGB triplet, hexadecimal color code, or color name — Bars are filled with the specified color.

    RGB triplets and hexadecimal color codes are useful for specifying custom colors.

    • An RGB triplet is a three-element row vector whose elements specify the intensities of the red, green, and blue components of the color. The intensities must be in the range [0,1]; for example, [0.4 0.6 0.7].

    • A hexadecimal color code is a character vector or a string scalar that starts with a hash symbol (#) followed by three or six hexadecimal digits, which can range from 0 to F. The values are not case sensitive. Thus, the color codes '#FF8800', '#ff8800', '#F80', and '#f80' are equivalent.

    Alternatively, you can specify some common colors by name. This table lists the named color options, the equivalent RGB triplets, and hexadecimal color codes.

    Color NameShort NameRGB TripletHexadecimal Color CodeAppearance
    'red''r'[1 0 0]'#FF0000'

    'green''g'[0 1 0]'#00FF00'

    'blue''b'[0 0 1]'#0000FF'

    'cyan' 'c'[0 1 1]'#00FFFF'

    'magenta''m'[1 0 1]'#FF00FF'

    'yellow''y'[1 1 0]'#FFFF00'

    'black''k'[0 0 0]'#000000'

    'white''w'[1 1 1]'#FFFFFF'

    Here are the RGB triplets and hexadecimal color codes for the default colors MATLAB® uses in many types of plots.

    RGB TripletHexadecimal Color CodeAppearance
    [0 0.4470 0.7410]'#0072BD'

    [0.8500 0.3250 0.0980]'#D95319'

    [0.9290 0.6940 0.1250]'#EDB120'

    [0.4940 0.1840 0.5560]'#7E2F8E'

    [0.4660 0.6740 0.1880]'#77AC30'

    [0.3010 0.7450 0.9330]'#4DBEEE'

    [0.6350 0.0780 0.1840]'#A2142F'

If you specify DisplayStyle as 'stairs', then histogram2 does not use the FaceColor property.

Example: histogram2(X,Y,'FaceColor','g') creates a histogram plot with green bars.

Histogram edge color, specified as one of these values:

  • 'none' — Edges are not drawn.

  • 'auto' — Color of each edge is chosen automatically.

  • RGB triplet, hexadecimal color code, or color name — Edges use the specified color.

    RGB triplets and hexadecimal color codes are useful for specifying custom colors.

    • An RGB triplet is a three-element row vector whose elements specify the intensities of the red, green, and blue components of the color. The intensities must be in the range [0,1]; for example, [0.4 0.6 0.7].

    • A hexadecimal color code is a character vector or a string scalar that starts with a hash symbol (#) followed by three or six hexadecimal digits, which can range from 0 to F. The values are not case sensitive. Thus, the color codes '#FF8800', '#ff8800', '#F80', and '#f80' are equivalent.

    Alternatively, you can specify some common colors by name. This table lists the named color options, the equivalent RGB triplets, and hexadecimal color codes.

    Color NameShort NameRGB TripletHexadecimal Color CodeAppearance
    'red''r'[1 0 0]'#FF0000'

    'green''g'[0 1 0]'#00FF00'

    'blue''b'[0 0 1]'#0000FF'

    'cyan' 'c'[0 1 1]'#00FFFF'

    'magenta''m'[1 0 1]'#FF00FF'

    'yellow''y'[1 1 0]'#FFFF00'

    'black''k'[0 0 0]'#000000'

    'white''w'[1 1 1]'#FFFFFF'

    Here are the RGB triplets and hexadecimal color codes for the default colors MATLAB uses in many types of plots.

    RGB TripletHexadecimal Color CodeAppearance
    [0 0.4470 0.7410]'#0072BD'

    [0.8500 0.3250 0.0980]'#D95319'

    [0.9290 0.6940 0.1250]'#EDB120'

    [0.4940 0.1840 0.5560]'#7E2F8E'

    [0.4660 0.6740 0.1880]'#77AC30'

    [0.3010 0.7450 0.9330]'#4DBEEE'

    [0.6350 0.0780 0.1840]'#A2142F'

Example: histogram2(X,Y,'EdgeColor','r') creates a histogram plot with red bar edges.

Transparency of histogram bars, specified as a scalar value between 0 and 1 inclusive. histogram2 uses the same transparency for all the bars of the histogram. A value of 1 means fully opaque and 0 means completely transparent (invisible).

Example: histogram2(X,Y,'FaceAlpha',0.5) creates a bivariate histogram plot with semi-transparent bars.

Transparency of histogram bar edges, specified as a scalar value between 0 and 1 inclusive. A value of 1 means fully opaque and 0 means completely transparent (invisible).

Example: histogram2(X,Y,'EdgeAlpha',0.5) creates a bivariate histogram plot with semi-transparent bar edges.

Lighting effect on histogram bars, specified as one of the values in the table.

ValueDescription
'lit'

Histogram bars display a pseudo-lighting effect, where the sides of the bars use darker colors relative to the tops. The bars are unaffected by other light sources in the axes.

This is the default value when DisplayStyle is 'bar3'.

'flat'

Histogram bars are not lit automatically. In the presence of other light objects, the lighting effect is uniform across the bar faces.

'none'

Histogram bars are not lit automatically, and lights do not affect the histogram bars.

FaceLighting can only be 'none' when DisplayStyle is 'tile'.

Example: histogram2(X,Y,'FaceLighting','none') turns off the lighting of the histogram bars.

Line style, specified as one of the options listed in this table.

Line StyleDescriptionResulting Line
'-'Solid line

'--'Dashed line

':'Dotted line

'-.'Dash-dotted line

'none'No lineNo line

Width of bar outlines, specified as a positive value in point units. One point equals 1/72 inch.

Example: 1.5

Data Types: single | double | int8 | int16 | int32 | int64 | uint8 | uint16 | uint32 | uint64

Legend

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Text used by the legend, specified as a character vector. The text appears next to an icon of the histogram2.

Example: 'Text Description'

For multiline text, create the character vector using sprintf with the new line character \n.

Example: sprintf('line one\nline two')

Alternatively, you can specify the legend text using the legend function.

  • If you specify the text as an input argument to the legend function, then the legend uses the specified text and sets the DisplayName property to the same value.

  • If you do not specify the text as an input argument to the legend function, then the legend uses the text in the DisplayName property. By default, DisplayName is a character vector representing the variable names of the x and y input data used to construct the histogram. If one or both of the inputs do not have variable names, then DisplayName is empty, ''.

If the DisplayName property does not contain any text, then the legend generates a character vector. The character vector has the form 'dataN', where N is the number assigned to the histogram2 object based on its location in the list of legend entries.

If you edit interactively the character vector in an existing legend, then MATLAB updates the DisplayName property to the edited character vector.

This property is read-only.

Control for including or excluding the object from a legend, returned as an Annotation object. Set the underlying IconDisplayStyle property to one of these values:

  • 'on' — Include the object in the legend (default).

  • 'off' — Do not include the object in the legend.

For example, to exclude a graphics object, go, from the legend set the IconDisplayStyle property to 'off'.

go.Annotation.LegendInformation.IconDisplayStyle = 'off';

Alternatively, you can control the items in a legend using the legend function. Specify the first input argument as a vector of the graphics objects to include. If you do not specify an existing graphics object in the first input argument, then it does not appear in the legend. However, graphics objects added to the axes after the legend is created do appear in the legend. Consider creating the legend after creating all the plots to avoid extra items.

Interactivity

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State of visibility, specified as one of these values:

  • 'on' — Display the object.

  • 'off' — Hide the object without deleting it. You still can access the properties of an invisible object.

Context menu, specified as a ContextMenu object. Use this property to display a context menu when you right-click the object. Create the context menu using the uicontextmenu function.

Note

If the PickableParts property is set to 'none' or if the HitTest property is set to 'off', then the context menu does not appear.

Selection state, specified as one of these values:

  • 'on' — Selected. If you click the object when in plot edit mode, then MATLAB sets its Selected property to 'on'. If the SelectionHighlight property also is set to 'on', then MATLAB displays selection handles around the object.

  • 'off' — Not selected.

Display of selection handles when selected, specified as one of these values:

  • 'on' — Display selection handles when the Selected property is set to 'on'.

  • 'off' — Never display selection handles, even when the Selected property is set to 'on'.

Callbacks

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Mouse-click callback, specified as one of these values:

  • Function handle

  • Cell array containing a function handle and additional arguments

  • Character vector that is a valid MATLAB command or function, which is evaluated in the base workspace (not recommended)

Use this property to execute code when you click the object. If you specify this property using a function handle, then MATLAB passes two arguments to the callback function when executing the callback:

  • Clicked object — Access properties of the clicked object from within the callback function.

  • Event data — Empty argument. Replace it with the tilde character (~) in the function definition to indicate that this argument is not used.

For more information on how to use function handles to define callback functions, see Callback Definition.

Note

If the PickableParts property is set to 'none' or if the HitTest property is set to 'off', then this callback does not execute.

Creation callback, specified as one of these values:

  • Function handle

  • Cell array containing a function handle and additional arguments

  • Character vector that is a valid MATLAB command or function, which is evaluated in the base workspace (not recommended)

Use this property to execute code when you create the object. MATLAB executes the callback after creating the object and setting all of its properties. Setting the CreateFcn property on an existing object has no effect. To have an effect, you must specify the CreateFcn property during object creation. One way to specify the property during object creation is to set the default property value for the object. See Default Property Values for more information.

If you specify this callback using a function handle, then MATLAB passes two arguments to the callback function when executing the callback:

  • Created object — Access properties of the object from within the callback function. You also can access the object through the CallbackObject property of the graphics root object, which can be queried using the gcbo function.

  • Event data — Empty argument. Replace it with the tilde character (~) in the function definition to indicate that this argument is not used.

For more information on how to use function handles to define callback functions, see Callback Definition.

Deletion callback, specified as one of these values:

  • Function handle

  • Cell array containing a function handle and additional arguments

  • Character vector that is a valid MATLAB command or function, which is evaluated in the base workspace (not recommended)

Use this property to execute code when you delete the object. MATLAB executes the callback before destroying the object so that the callback can access its property values.

If you specify this callback using a function handle, then MATLAB passes two arguments to the callback function when executing the callback:

  • Deleted object — Access properties of the object from within the callback function. You also can access the object through the CallbackObject property of the graphics root object, which can be queried using the gcbo function.

  • Event data — Empty argument. Replace it with the tilde character (~) in the function definition to indicate that this argument is not used.

For more information on how to use function handles to define callback functions, see Callback Definition.

Callback Execution Control

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Callback interruption, specified as 'on' or 'off'. The Interruptible property determines if a running callback can be interrupted.

Note

Consider these callback states where:

  • The running callback is the currently executing callback.

  • The interrupting callback is a callback that tries to interrupt the running callback.

Whenever MATLAB invokes a callback, that callback attempts to interrupt a running callback. The Interruptible property of the object owning the running callback determines if interruption is permitted. If interruption is not permitted, then the BusyAction property of the object owning the interrupting callback determines if it is discarded or put in the queue.

The Interruptible property determines if another callback can interrupt the ButtonDownFcn callback of the Histogram2 object. The Interruptible property has two values:

  • 'on' — Interruptible. Interruption occurs at the next point where MATLAB processes the queue. For example, queues are processed by commands such as drawnow, figure, getframe, waitfor, pause, and waitbar.

    • If the running callback contains one of these commands, then MATLAB stops the execution of the callback at this point and executes the interrupting callback. MATLAB resumes executing the running callback when the interrupting callback completes. For more information, see Interrupt Callback Execution.

    • If the running callback does not contain one of these commands, then MATLAB finishes executing the callback without interruption.

  • 'off' — Not interruptible. MATLAB finishes executing the running callback without any interruptions.

Callback queuing specified as 'queue' or 'cancel'. The BusyAction property determines how MATLAB handles the execution of interrupting callbacks.

Consider these callback states where:

  • The running callback is the currently executing callback.

  • The interrupting callback is a callback that tries to interrupt the running callback.

Whenever MATLAB invokes a callback, that callback attempts to interrupt a running callback. The Interruptible property of the object owning the running callback determines if interruption is permitted. If interruption is not permitted, then the BusyAction property of the object owning the interrupting callback determines if it is discarded or put in the queue.

If a callback of the Histogram2 object tries to interrupt a running callback that cannot be interrupted, then the BusyAction property determines if it is discarded or put in the queue. Specify the BusyAction property as one of these values:

  • 'queue' — Put the interrupting callback in a queue to be processed after the running callback finishes execution. (default behavior)

  • 'cancel' — Discard the interrupting callback.

Ability to capture mouse clicks, specified as one of these values:

  • 'visible' — Capture mouse clicks only when visible. The Visible property must be set to 'on'. The HitTest property determines if the Histogram2 object responds to the click or if an ancestor does.

  • 'none' — Cannot capture mouse clicks. Clicking the Histogram2 object passes the click to the object behind it in the current view of the figure window. The HitTest property of the Histogram2 object has no effect.

Response to captured mouse clicks, specified as one of these values:

  • 'on' — Trigger the ButtonDownFcn callback of the Histogram2 object. If you have defined the UIContextMenu property, then invoke the context menu.

  • 'off' — Trigger the callbacks for the nearest ancestor of the Histogram2 object that has one of these:

    • HitTest property set to 'on'

    • PickableParts property set to a value that enables the ancestor to capture mouse clicks

Note

The PickableParts property determines if the Histogram2 object can capture mouse clicks. If it cannot, then the HitTest property has no effect.

This property is read-only.

Deletion status, returned as 'off' or 'on'. MATLAB sets the BeingDeleted property to 'on' when the delete function of the object begins execution (see the DeleteFcn property). The BeingDeleted property remains set to 'on' until the object no longer exists.

Check the value of the BeingDeleted property if you need to verify that the object is not about to be deleted before querying or modifying it.

Parent/Child

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Parent, specified as an Axes, Group, or Transform object.

The object has no children. You cannot set this property.

Visibility of the object handle in the Children property of the parent, specified as one of these values:

  • 'on' — Object handle is always visible.

  • 'off' — Object handle is invisible at all times. This option is useful for preventing unintended changes to the UI by another function. Set the HandleVisibility to 'off' to temporarily hide the handle during the execution of that function.

  • 'callback' — Object handle is visible from within callbacks or functions invoked by callbacks, but not from within functions invoked from the command line. This option blocks access to the object at the command line, but permits callback functions to access it.

If the object is not listed in the Children property of the parent, then functions that obtain object handles by searching the object hierarchy or querying handle properties cannot return it. Examples of such functions include the get, findobj, gca, gcf, gco, newplot, cla, clf, and close functions.

Hidden object handles are still valid. Set the root ShowHiddenHandles property to 'on' to list all object handles regardless of their HandleVisibility property setting.

Identifiers

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This property is read-only.

Type of graphics object, returned as 'histogram2'. Use this property to find all objects of a given type within a plotting hierarchy, such as searching for the type using findobj.

Tag to associate with the histogram2 object, specified as a character vector or string scalar.

Use this property to find histogram2 objects in a hierarchy. For example, you can use the findobj function to find histogram2 objects that have a specific Tag property value.

Example: 'January Data'

Data Types: char

User data to associate with the histogram2 object, specified as any MATLAB data, for example, a scalar, vector, matrix, cell array, character array, table, or structure. MATLAB does not use this data.

To associate multiple sets of data or to attach a field name to the data, use the getappdata and setappdata functions.

Example: 1:100

Introduced in R2015b