Main Content

Histogram Properties

Histogram appearance and behavior

expand all in page

Histogram 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 = histogram(randn(10,1));
c = h.BinWidth;
h.BinWidth = 2;

Bins

expand all

Number of bins, specified as a positive integer. If you do not specify NumBins, then histogram automatically calculates how many bins to use based on the input data.

  • If you specify NumBins with BinMethod, BinWidth or BinEdges, histogram only honors the last parameter.

  • This option does not apply to categorical data.

Width of bins, specified as a positive scalar. If you specify BinWidth, then Histogram can use a maximum of 65,536 bins (or 216). If the specified bin width requires more bins, then histogram uses a larger bin width corresponding to the maximum number of bins.

  • For datetime and duration data, BinWidth can be a scalar duration or calendar duration.

  • If you specify BinWidth with BinMethod, NumBins, or BinEdges, histogram only honors the last parameter.

  • This option does not apply to categorical data.

Example: histogram(X,'BinWidth',5) uses bins with a width of 5.

Edges of bins, specified as a numeric vector. The first element specifies the leading edge of the first bin. The last element specifies the trailing edge of the last bin. The trailing edge is only included for the last bin.

If you do not specify the bin edges, then histogram automatically determines the bin edges.

If BinCountsMode is "manual", then BinEdges must be a row vector.

  • If you specify BinEdges with BinMethod, BinWidth, NumBins, or BinLimits, histogram only honors BinEdges and BinEdges must be specified last.

  • This option does not apply to categorical data.

Bin limits, specified as a two-element vector, [bmin,bmax]. The first element indicates the first bin edge. The second element indicates the last bin edge.

This option computes using only the data that falls within the bin limits inclusively, X>=bmin & X<=bmax.

This option does not apply to categorical data.

Example: histogram(X,'BinLimits',[1,10]) bins only the values in X that are between 1 and 10 inclusive.

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

  • If you specify BinLimits or BinEdges, then BinLimitsMode is set to 'manual'. Specify BinLimitsMode as 'auto' to rescale the bin limits to the data.

  • This option does not apply to histograms of categorical data.

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

Value

Description

'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 normally distributed. This rule is appropriate for most other distributions, as well. It uses a bin width of 3.5*std(X(:))*numel(X)^(-1/3).

'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 width of 2*iqr(X(:))*numel(X)^(-1/3).

'integers'

The integer rule is useful with integer data, as it creates a bin for each integer. It uses a bin width of 1 and places bin edges halfway between integers.

To avoid accidentally creating too many bins, you can use this rule to create a limit of 65536 bins (216). If the data range is greater than 65536, then the integer rule uses wider bins instead.

'integers' does not support datetime or duration data.

'sturges'

Sturges’ rule is popular due to its simplicity. It chooses the number of bins to be ceil(1 + log2(numel(X))).

'sqrt'

The Square Root rule is widely used in other software packages. It chooses the number of bins to be ceil(sqrt(numel(X))).

histogram adjusts the number of bins slightly so that the bin edges fall on "nice" numbers, rather than using these exact formulas.

For datetime or duration data, specify the binning algorithm as one of these units of time.

ValueDescriptionData Type
"second"

Each bin is 1 second.

datetime and duration
"minute"

Each bin is 1 minute.

datetime and duration
"hour"

Each bin is 1 hour.

datetime and duration
"day"

Each bin is 1 calendar day. This value accounts for daylight saving time shifts.

datetime and duration
"week"Each bin is 1 calendar week.datetime only
"month"Each bin is 1 calendar month.datetime only
"quarter"Each bin is 1 calendar quarter.datetime only
"year"

Each bin is 1 calendar year. This value accounts for leap days.

datetime and duration
"decade"Each bin is 1 decade (10 calendar years).datetime only
"century"Each bin is 1 century (100 calendar years).datetime only

  • If you specify BinMethod for datetime or duration data, then histogram can use a maximum of 65,536 bins (or 216). If the specified bin duration requires more bins, then histogram uses a larger bin width corresponding to the maximum number of bins.

  • If you specify BinLimits, NumBins, BinEdges, or BinWidth, then BinMethod is set to 'manual'.

  • If you specify BinMethod with BinWidth, NumBins or BinEdges, histogram only honors the last parameter.

  • This option does not apply to categorical data.

Example: histogram(X,'BinMethod','integers') centers the bins on integers.

Categories

expand all

Note

This option only applies to categorical histograms.

Categories included in histogram, specified as a cell array of character vectors, categorical array, string array, or pattern scalar.

  • If you specify an input categorical array C, then by default, histogram plots a bar for each category in C. In that case, use Categories to specify a unique subset of the categories instead.

  • If you specify bin counts, then Categories specifies the associated category names for the histogram.

Example: h = histogram(C,{'Large','Small'}) plots only the categorical data in the categories 'Large' and 'Small'.

Example: histogram(C,"Y" + wildcardPattern) plots data in the categories whose names begin with the letter Y.

Example: histogram('Categories',{'Yes','No','Maybe'},'BinCounts',[22 18 3]) plots a histogram that has three categories with the associated bin counts.

Example: h.Categories queries the categories that are in histogram object h.

Data Types: cell | categorical | string | pattern

Category display order, specified as 'data', 'ascend', or 'descend'.

  • 'data' — Use the category order in the input data C.

  • 'ascend' — Display the histogram with increasing bar heights.

  • 'descend' — Display the histogram with decreasing bar heights.

This option only works with categorical data.

Number of categories to display, specified as a scalar. You can change the ordering of categories displayed in the histogram using the 'DisplayOrder' option.

This option only works with categorical data.

Toggle summary display of data belonging to undisplayed categories, specified as 'on' or 'off', or as numeric or logical 1 (true) or 0 (false). A value of 'on' is equivalent to true, and 'off' is equivalent to false. Thus, you can use the value of this property as a logical value. The value is stored as an on/off logical value of type matlab.lang.OnOffSwitchState.

  • Set this option to 'on' to display an additional bar in the histogram with the name 'Others'. This extra bar counts all elements that do not belong to categories displayed in the histogram.

  • You can change the number of categories displayed in the histogram, as well as their order, using the 'NumDisplayBins' and 'DisplayOrder' options.

  • This option only works with categorical data.

Data

expand all

Data to distribute among bins, specified as a vector, matrix, multidimensional array, or categorical array. If Data is not a vector, then histogram treats it as a single column vector, Data(:), and plots a single histogram.

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

You can only specify categorical values for Data if the histogram object was originally created using categoricals.

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

This property is read-only.

Bin values, returned as a numeric vector. If Normalization is 'count' (the default), then the kth element in Values specifies how many elements of Data fall in the kth bin interval (bin counts). The last bin includes values that are on either bin edge, but all other bins only include values that fall on the leading edge.

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

Type of normalization, specified as one of the values in this table. For each bin i:

  • vi is the bin value.

  • ci is the number of elements in the bin.

  • wi is the width of the bin.

  • N is the number of elements in the input data. This value can be greater than the binned data if the data contains missing values, such as NaN, or if some of the data lies outside the bin limits.

ValueBin ValuesNotes
'count' (default)

vi=ci

  • Count or frequency of observations.

  • Sum of bin values is at most numel(X), or sum(ismember(X(:),'Categories')) for categorical data. The sum is less than this only when some of the input data is not included in the bins.

'probability'

vi=ciN

  • Relative probability.

  • The number of elements in each bin relative to the total number of elements in the input data is at most 1.

'percentage'

vi=100*ciN

  • Relative percentage.

  • The percentage of elements in each bin is at most 100.

'countdensity'

vi=ciwi

  • Count or frequency scaled by width of bin.

  • For categorical data, this is the same as 'count'.

  • 'countdensity' does not support datetime or duration data.

  • The sum of the bin areas is at most numel(X).

'cumcount'

vi=∑j=1icj

  • Cumulative count, or the number of observations in each bin and all previous bins.

  • N(end) is at most numel(X), or sum(ismember(X(:),'Categories')) for categorical data.

'pdf'

vi=ciN  ⋅   wi

  • Probability density function estimate.

  • For categorical data, this is the same as 'probability'.

  • 'pdf' does not support datetime or duration data.

  • The sum of the bin areas is at most 1.

'cdf'

vi=∑j=1i cjN

  • Cumulative distribution function estimate.

  • The count of each bin is equal to the cumulative relative number of observations in the bin and all previous bins.

  • N(end) is at most 1.

Example: histogram(X,'Normalization','pdf') bins the data using an estimate of the probability density function.

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

The length of counts must be equal to the number of bins.

  • For numeric histograms, the number of bins is length(edges)-1.

  • For categorical histograms, the number of bins is equal to the number of categories.

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

Example: histogram('BinEdges',-2:2,'BinCounts',[5 8 15 9])

Example: histogram('Categories',{'Yes','No','Maybe'},'BinCounts',[22 18 3])

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 and BinEdges.

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

expand all

Histogram display style, specified as either 'bar' or 'stairs'.

  • 'bar' — Display a histogram bar plot over each window of A. This method is useful for reducing periodic trends in data.

  • 'stairs' — Display a stairstep plot, which displays the outline of the histogram without filling the interior.

Example: histogram(X,'DisplayStyle','stairs') plots the outline of the histogram.

Orientation of bars, specified as 'vertical' or 'horizontal'.

Example: histogram(X,'Orientation','horizontal') creates a histogram plot with horizontal bars.

Relative width of categorical bars, specified as a scalar value in the range [0,1]. Use this property to control the separation of categorical bars within the histogram. The default value is 0.9, which means that the bar width is 90% of the space from the previous bar to the next bar, with 5% of that space on each side.

If BarWidth is 1, then adjacent bars touch.

This option only works with categorical data.

Example: 0.5

Histogram bar color, specified as one of these values:

  • 'none' — Bars are not filled.

  • 'auto' — Histogram 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"

    Sample of the color red

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

    Sample of the color green

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

    Sample of the color blue

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

    Sample of the color cyan

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

    Sample of the color magenta

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

    Sample of the color yellow

    "black""k"[0 0 0]"#000000"

    Sample of the color black

    "white""w"[1 1 1]"#FFFFFF"

    Sample of the color white

    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"

    Sample of RGB triplet [0 0.4470 0.7410], which appears as dark blue

    [0.8500 0.3250 0.0980]"#D95319"

    Sample of RGB triplet [0.8500 0.3250 0.0980], which appears as dark orange

    [0.9290 0.6940 0.1250]"#EDB120"

    Sample of RGB triplet [0.9290 0.6940 0.1250], which appears as dark yellow

    [0.4940 0.1840 0.5560]"#7E2F8E"

    Sample of RGB triplet [0.4940 0.1840 0.5560], which appears as dark purple

    [0.4660 0.6740 0.1880]"#77AC30"

    Sample of RGB triplet [0.4660 0.6740 0.1880], which appears as medium green

    [0.3010 0.7450 0.9330]"#4DBEEE"

    Sample of RGB triplet [0.3010 0.7450 0.9330], which appears as light blue

    [0.6350 0.0780 0.1840]"#A2142F"

    Sample of RGB triplet [0.6350 0.0780 0.1840], which appears as dark red

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

Example: histogram(X,'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"

    Sample of the color red

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

    Sample of the color green

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

    Sample of the color blue

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

    Sample of the color cyan

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

    Sample of the color magenta

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

    Sample of the color yellow

    "black""k"[0 0 0]"#000000"

    Sample of the color black

    "white""w"[1 1 1]"#FFFFFF"

    Sample of the color white

    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"

    Sample of RGB triplet [0 0.4470 0.7410], which appears as dark blue

    [0.8500 0.3250 0.0980]"#D95319"

    Sample of RGB triplet [0.8500 0.3250 0.0980], which appears as dark orange

    [0.9290 0.6940 0.1250]"#EDB120"

    Sample of RGB triplet [0.9290 0.6940 0.1250], which appears as dark yellow

    [0.4940 0.1840 0.5560]"#7E2F8E"

    Sample of RGB triplet [0.4940 0.1840 0.5560], which appears as dark purple

    [0.4660 0.6740 0.1880]"#77AC30"

    Sample of RGB triplet [0.4660 0.6740 0.1880], which appears as medium green

    [0.3010 0.7450 0.9330]"#4DBEEE"

    Sample of RGB triplet [0.3010 0.7450 0.9330], which appears as light blue

    [0.6350 0.0780 0.1840]"#A2142F"

    Sample of RGB triplet [0.6350 0.0780 0.1840], which appears as dark red

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

Transparency of histogram bars, specified as a scalar value in range [0,1]. histogram 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: histogram(X,'FaceAlpha',1) creates a histogram plot with fully opaque bars.

Transparency of histogram bar edges, specified as a scalar value in the range [0,1]. A value of 1 means fully opaque and 0 means completely transparent (invisible).

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

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

Line StyleDescriptionResulting Line
"-"Solid line

Sample of solid line

"--"Dashed line

Sample of dashed line

":"Dotted line

Sample of dotted line

"-."Dash-dotted line

Sample of dash-dotted line, with alternating dashes and dots

"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

Series index, specified as a positive integer or "none". This property is useful for reassigning the face colors of Histogram objects so that they match the colors of other objects.

By default, the SeriesIndex property of a Histogram object is a number that corresponds to its order of creation, starting at 1. MATLAB uses the number to calculate indices for assigning colors when you call plotting functions. The indices refer to the rows of the arrays stored in the ColorOrder property of the axes. Any objects in the axes that have the same SeriesIndex number will have the same color.

A SeriesIndex value of "none" corresponds to a neutral color that does not participate in the indexing scheme.

How Manual Color Assignment Overrides SeriesIndex Behavior

To manually control face color, set the FaceColor property of the Histogram object to a color value, such as a color name or an RGB triplet.

When you manually set the face color of a Histogram object, MATLAB disables automatic color selection for that object and allows your color to persist, regardless of the value of the SeriesIndex property.

To enable automatic selection again, set the SeriesIndex property to positive integer, and set the FaceColor property to "auto".

In some cases, MATLAB sets the SeriesIndex value to 0, which also disables automatic color selection.

Legend

expand all

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

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. The default value of DisplayName is one of these values.

    • For numeric inputs, DisplayName is a character vector representing the variable name of the input data used to construct the histogram. If the input data does not have a variable name, then DisplayName is empty, ''.

    • For categorical array inputs, 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 histogram 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.

Include the object in the legend, specified as an Annotation object. Set the underlying IconDisplayStyle property of the Annotation object 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 the Histogram object named obj from the legend, set the IconDisplayStyle property to "off".

obj.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

expand all

State of visibility, specified as "on" or "off", or as numeric or logical 1 (true) or 0 (false). A value of "on" is equivalent to true, and "off" is equivalent to false. Thus, you can use the value of this property as a logical value. The value is stored as an on/off logical value of type matlab.lang.OnOffSwitchState.

  • "on" — Display the object.

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

Data tip content, specified as a DataTipTemplate object. You can control the content that appears in a data tip by modifying the properties of the underlying DataTipTemplate object. For a list of properties, see DataTipTemplate Properties.

For an example of modifying data tips, see Create Custom Data Tips.

Note

The DataTipTemplate object is not returned by findobj or findall, and it is not copied by copyobj.

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 'on' or 'off', or as numeric or logical 1 (true) or 0 (false). A value of 'on' is equivalent to true, and 'off' is equivalent to false. Thus, you can use the value of this property as a logical value. The value is stored as an on/off logical value of type matlab.lang.OnOffSwitchState.

  • '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 'on' or 'off', or as numeric or logical 1 (true) or 0 (false). A value of 'on' is equivalent to true, and 'off' is equivalent to false. Thus, you can use the value of this property as a logical value. The value is stored as an on/off logical value of type matlab.lang.OnOffSwitchState.

  • '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

expand all

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 Create Callbacks for Graphics Objects.

Note

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

Object creation function, specified as one of these values:

  • Function handle.

  • Cell array in which the first element is a function handle. Subsequent elements in the cell array are the arguments to pass to the callback function.

  • Character vector containing a valid MATLAB expression (not recommended). MATLAB evaluates this expression in the base workspace.

For more information about specifying a callback as a function handle, cell array, or character vector, see Create Callbacks for Graphics Objects.

This property specifies a callback function to execute when MATLAB creates the object. MATLAB initializes all property values before executing the CreateFcn callback. If you do not specify the CreateFcn property, then MATLAB executes a default creation function.

Setting the CreateFcn property on an existing component has no effect.

If you specify this property as a function handle or cell array, you can access the object that is being created using the first argument of the callback function. Otherwise, use the gcbo function to access the object.

Object deletion function, specified as one of these values:

  • Function handle.

  • Cell array in which the first element is a function handle. Subsequent elements in the cell array are the arguments to pass to the callback function.

  • Character vector containing a valid MATLAB expression (not recommended). MATLAB evaluates this expression in the base workspace.

For more information about specifying a callback as a function handle, cell array, or character vector, see Create Callbacks for Graphics Objects.

This property specifies a callback function to execute when MATLAB deletes the object. MATLAB executes the DeleteFcn callback before destroying the properties of the object. If you do not specify the DeleteFcn property, then MATLAB executes a default deletion function.

If you specify this property as a function handle or cell array, you can access the object that is being deleted using the first argument of the callback function. Otherwise, use the gcbo function to access the object.

Callback Execution Control

expand all

Callback interruption, specified as 'on' or 'off', or as numeric or logical 1 (true) or 0 (false). A value of 'on' is equivalent to true, and 'off' is equivalent to false. Thus, you can use the value of this property as a logical value. The value is stored as an on/off logical value of type matlab.lang.OnOffSwitchState.

This property determines if a running callback can be interrupted. There are two callback states to consider:

  • The running callback is the currently executing callback.

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

MATLAB determines callback interruption behavior whenever it executes a command that processes the callback queue. These commands include drawnow, figure, uifigure, getframe, waitfor, and pause.

If the running callback does not contain one of these commands, then no interruption occurs. MATLAB first finishes executing the running callback, and later executes the interrupting callback.

If the running callback does contain one of these commands, then the Interruptible property of the object that owns the running callback determines if the interruption occurs:

  • If the value of Interruptible is 'off', then no interruption occurs. Instead, the BusyAction property of the object that owns the interrupting callback determines if the interrupting callback is discarded or added to the callback queue.

  • If the value of Interruptible is 'on', then the interruption occurs. The next time MATLAB processes the callback queue, it stops the execution of the running callback and executes the interrupting callback. After the interrupting callback completes, MATLAB then resumes executing the running callback.

Note

Callback interruption and execution behave differently in these situations:

  • If the interrupting callback is a DeleteFcn, CloseRequestFcn, or SizeChangedFcn callback, then the interruption occurs regardless of the Interruptible property value.

  • If the running callback is currently executing the waitfor function, then the interruption occurs regardless of the Interruptible property value.

  • If the interrupting callback is owned by a Timer object, then the callback executes according to schedule regardless of the Interruptible property value.

Note

When an interruption occurs, MATLAB does not save the state of properties or the display. For example, the object returned by the gca or gcf command might change when another callback executes.

Callback queuing, specified as 'queue' or 'cancel'. The BusyAction property determines how MATLAB handles the execution of interrupting callbacks. There are two callback states to consider:

  • The running callback is the currently executing callback.

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

The BusyAction property determines callback queuing behavior only when both of these conditions are met:

  • The running callback contains a command that processes the callback queue, such as drawnow, figure, uifigure, getframe, waitfor, or pause.

  • The value of the Interruptible property of the object that owns the running callback is 'off'.

Under these conditions, the BusyAction property of the object that owns the interrupting callback determines how MATLAB handles the interrupting callback. These are possible values of the BusyAction property:

  • 'queue' — Puts the interrupting callback in a queue to be processed after the running callback finishes execution.

  • 'cancel' — Does not execute 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 Histogram object responds to the click or if an ancestor does.

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

Response to captured mouse clicks, specified as 'on' or 'off', or as numeric or logical 1 (true) or 0 (false). A value of 'on' is equivalent to true, and 'off' is equivalent to false. Thus, you can use the value of this property as a logical value. The value is stored as an on/off logical value of type matlab.lang.OnOffSwitchState.

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

  • 'off' — Trigger the callbacks for the nearest ancestor of the Histogram object that meets one of these conditions:

    • HitTest property is set to 'on'.

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

Note

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

This property is read-only.

Deletion status, returned as an on/off logical value of type matlab.lang.OnOffSwitchState.

MATLAB sets the BeingDeleted property to 'on' when the DeleteFcn callback begins execution. The BeingDeleted property remains set to 'on' until the component object no longer exists.

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

Parent/Child

expand all

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

Children, returned as an empty GraphicsPlaceholder array or a DataTip object array. Use this property to view a list of data tips that are plotted on the chart.

You cannot add or remove children using the Children property. To add a child to this list, set the Parent property of the DataTip object to the chart object.

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 by another function. Set 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

expand all

This property is read-only.

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

Object identifier, specified as a character vector or string scalar. You can specify a unique Tag value to serve as an identifier for an object. When you need access to the object elsewhere in your code, you can use the findobj function to search for the object based on the Tag value.

User data, specified as any MATLAB array. For example, you can specify a scalar, vector, matrix, cell array, character array, table, or structure. Use this property to store arbitrary data on an object.

If you are working in App Designer, create public or private properties in the app to share data instead of using the UserData property. For more information, see Share Data Within App Designer Apps.

Version History

Introduced in R2014b

expand all

See Also

Topics