8.1. Charts Panel

In this panel, the different Chartboxes with the different series the user creates will be displayed.

8.1.1. Chart series

A DataPoint in a Chart Series in the Fast DDS Monitor refers to a specific data type of the DDS network monitoring. Each DataPoint consists in a timestamp and a real value. The timestamp is the moment the data has been created, reported, received, etc. depending on the DataKind. The value refers to the real value of this DataPoint for this DataKind at the moment of the timestamp value.

For example, each DataPoint of the DataKind DATA_COUNT has a timestamp and an integer value. This value is the number of Data packets a DataWriter sent since the last time that same data was reported.

8.1.2. Chart view

Every DataKind is represented similarly inside a Chartbox. None, one or multiple lines of different colors will represent the different data series that are being displayed in the chart with the following format:

  • The X axis is the timestamp value of the data.

  • The Y axis is the real value that is stored in the data.

These real values could consist of integers, doubles or times, but any given DataKind will always present the same value type. Every point in the chart represents an accumulated value of DataPoints of a specific data kind in a given time range.

8.1.3. Chartbox kinds

There are two kinds of Chartbox that could be created, historic and dynamic.

  • The historic Chartbox represents static data that has been accumulated along the monitor execution. The data shown is not updated with new data or refreshed in case there has been any change. See the details of this Chartbox kind in section Historic Data.

  • The dynamic or real-time Chartbox represents the new data that is being collected in real time by the monitor. These series will update over time with the new data received from a DDS network, and so the new data will be displayed in pseudo-real-time. See the details of this Chartbox kind in section Real-Time Data.

8.1.4. Common Series parameters

Some parameters for creating a Chartbox depend on the specific kind of Chartbox being created. Below, we present the parameters common to both kinds of Chartbox.

8.1.4.1. Data kind

The DataKind refers to the specific data that the Chartbox will represent. There are several DataKinds that represent each of the data kinds that a Fast DDS network can report. (Be aware that by default a DDS network will not report most of this data, and in case of Fast DDS it must be configured beforehand in order to report it periodically).

8.1.4.2. Series label

Name of the new series in the Chartbox. If not set, the default series name is formed according to the following rule: <cumulative_function>_<source_entity_kind>-<source_entity_id>_<target_entity_kind>-<target_entity_id>.

8.1.4.3. Source Entity Id

This is the name and entity Id of the entity from which the data will be collected in the format <name>:\<<id>\>. This field has an entity kind to encapsulate the Ids of the entities with the same kind, to make it easier for users to locate the required Id.

Each DataKind is related with one entity kind, normally a DataWriter or a DataReader, which are the producers of that DataKind. However, every entity kind is available to choose the data to represent. When an entity without this type of data is selected, the monitor will look for any entities contained within that do report this specific DataKind. For example, in case the user wants to represent the number of packets (DATA_COUNT) transmitted by a Host, the monitor will look for all the DataWriters contained in that Host and report the total number of packets.

Continuing with the DATA_COUNT DataKind example, the monitor will find every DataWriter in this Host by finding every User in this Host, then finding every Process in these Users, finding every DomainParticipant in these Processes and finding every DataWriter in these DomainParticipants. Hence, the data displayed will be all the data that all those DataWriters have stored, accumulated by the cumulative function. Please refer to Entities section for more information on the monitor entities connections.

It is recommended to check some examples (see Example of usage) in order to better understand this functionality.

8.1.4.4. Target Entity Id

Note

Not every DataKind has a target entity, so the dialog will only show this field when the DataKind selected requires it.

This is the name and entity Id of the entity the data refers to. This field works in a similar fashion to the Source Entity Id. Some DataKinds have a target entity to which the data refers, and this target must belong to an specific entity kind. Choosing an entity of a different kind than the one this data requires will be solved by using the mechanism explained in Source Entity Id. That is, searching for the correct entity kind by following the connections between entities.

i.e. To show the DataKind FASTDDS_LATENCY, that is reported by a DataWriter, and targeted to a DataReader, from an entity Host_1 to an entity Host_2, both of kind Host, the data displayed would be collected following the steps described below:

  • Get all the DataWriters of Host_1 by searching for its Users, their Processes, their DomainParticipants and their respective DataWriters.

  • Get all the DataReaders of Host_2 by searching for its Users, their Processes, their DomainParticipants and their respective DataReaders.

  • Get all the data from the DataWriters found that refer to the DataReaders found inside the interval set.

  • Accumulate the data using the cumulative function.

It is recommended to check some examples (Example of usage) in order to better understand this functionality.

8.1.4.5. Statistics kind

When there are several data points to show in a single time frame, these data points are transformed into one by a cumulative function. This function is the one set in Statistics kind.

The available methods to accumulate some data points into one are:

  • MEAN: calculate the mean value of all the data points.

  • STANDARD_DEVIATION: calculate the standard deviation of all the data points.

  • MAX: returns the DataPoint with the maximum value.

  • MIN: returns the DataPoint with the minimum value.

  • MEDIAN: calculate the median of all the data points.

  • SUM: calculate the sum of all the data points.

  • RAW_DATA: returns the data points without any operation performed on them.

In case the Number of bins is 0 the Statistics kind is not used as the data is not going to be accumulated.