Last Modified: March 31, 2017

Finds the discrete histogram of a signal.

Representation for the output.

Name | Description |
---|---|

sample count | Represents the value of each bin as the number of samples in that bin. |

percent of total | Represents the value of each bin as a percentage of the total. |

**Default: **sample count

Number of bins in the histogram.

**Default: **10

Maximum value to include in the histogram.

**Default: **0

Minimum value to include in the histogram.

**Default: **0

Error conditions that occur before this node runs.

The node responds to this input according to standard error behavior.

Standard Error Behavior

Many nodes provide an **error in** input and an **error out** output so that the node can respond to and communicate errors that occur while code is running. The value of **error in** specifies whether an error occurred before the node runs. Most nodes respond to values of **error in** in a standard, predictable way.

**Default: **No error

The boundary of each bin to handle.

If bin specifications are provided in **bins**, this node uses the inclusion in **bins** instead.

Name | Description |
---|---|

lower | Includes the lower boundary. |

upper | Includes the upper boundary. |

Determining the Bin Widths When inclusion Is lower

If **inclusion** is set to lower, the bin widths are determined according to the following equations.

${\mathrm{\Delta}}_{0}=[\mathrm{min},\text{\hspace{0.17em}}\mathrm{min}+\mathrm{\Delta}x)$

${\mathrm{\Delta}}_{1}=[\mathrm{min}+\mathrm{\Delta}x,\text{\hspace{0.17em}}\mathrm{min}+2\mathrm{\Delta}x)$

$\vdots $

${\mathrm{\Delta}}_{i}=[\mathrm{min}+i\mathrm{\Delta}x,\text{\hspace{0.17em}}\mathrm{min}+(i+1)\mathrm{\Delta}x)$

$\vdots $

${\mathrm{\Delta}}_{k-1}=[\mathrm{min}+(k-1)\mathrm{\Delta}x,\text{\hspace{0.17em}}\mathrm{max}]$

where

- $\mathrm{\Delta}x=\frac{\mathrm{max}-\mathrm{min}}{m}$
*max*is the**maximum***min*is the**minimum***m*is the**number of bins**

Determining the Bin Widths When inclusion Is upper

If **inclusion** is set to upper, the bin widths are determined according to the following equations.

${\mathrm{\Delta}}_{0}=[\mathrm{min},\text{\hspace{0.17em}}\mathrm{min}+\mathrm{\Delta}x]$

${\mathrm{\Delta}}_{1}=(\mathrm{min}+\mathrm{\Delta}x,\text{\hspace{0.17em}}\mathrm{min}+2\mathrm{\Delta}x]$

$\vdots $

${\mathrm{\Delta}}_{i}=(\mathrm{min}+i\mathrm{\Delta}x,\text{\hspace{0.17em}}\mathrm{min}+(i+1)\mathrm{\Delta}x]$

$\vdots $

${\mathrm{\Delta}}_{k-1}=(\mathrm{min}+(k-1)\mathrm{\Delta}x,\text{\hspace{0.17em}}\mathrm{max}]$

where

- $\mathrm{\Delta}x=\frac{\mathrm{max}-\mathrm{min}}{m}$
*max*is the**maximum***min*is the**minimum***m*is the**number of bins**

**Default: **lower

The histogram of the input signal.

This input accepts a cluster or a 1D array of clusters.

An array of the center values of the bins of the histogram.

Discrete histogram of the input signal.

Actual number of bins in the histogram.

This output can return a 32-bit signed integer number or a 1D array of 32-bit signed integer numbers.

Actual maximum value in the histogram.

This output can return a double-precision, floating-point number or a 1D array of double-precision, floating-point numbers.

Actual minimum value to include in the histogram.

This output can return a double-precision, floating-point number or a 1D array of double-precision, floating-point numbers.

Error information.

The node produces this output according to standard error behavior.

Standard Error Behavior

**error in** input and an **error out** output so that the node can respond to and communicate errors that occur while code is running. The value of **error in** specifies whether an error occurred before the node runs. Most nodes respond to values of **error in** in a standard, predictable way.

Information about points that do not fall in any bin upon successful execution of the node.

Total number of values in **signal** that do not fall in any bin upon successful execution.

Number of values in **signal** below the first bin on the lower boundary.

Number of values in **signal** above the last bin on the upper boundary.

The histogram is a frequency count of the number of times that a specified frequency bin occurs in the input sequence. The node constructs **histogram** as follows.

The following equation calculates the width of the frequency bin Δ*x*.

where *max* is the **maximum**, *min* is the **minimum**, and *m* is the **number of bins**.

The node calculates the center of each frequency bin according to the following equation.

The node defines the range of the *i*^{th} frequency bin according to the following definition.

${\mathrm{\Delta}}_{i}\in (\mathrm{center}\left[i\right]-0.5\mathrm{\Delta}x,\mathrm{center}\left[i\right]+0.5\mathrm{\Delta}x)$

The node scans the input sequence, calculates the number of samples in each frequency bin from 0 to *m* - 1, and returns the **histogram**.

The following illustration shows the waveform of an input signal.

This example configures the node using the following input values:

For the previous input values, the following illustration shows the output histogram for the input signal.

**Where This Node Can Run: **

Desktop OS: Windows

FPGA: This product does not support FPGA devices