data_tamer repository

Repository Summary

Checkout URI https://github.com/PickNikRobotics/data_tamer.git
VCS Type git
VCS Version main
Last Updated 2024-02-02
Dev Status MAINTAINED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
data_tamer_cpp 0.9.4
data_tamer_msgs 0.9.4

README

Data Tamer

cmake Ubuntu ros2 codecov

DataTamer is a library to log/trace numerical variables over time and takes periodic "snapshots" of their values, to later visualize them as timeseries.

It works great with PlotJuggler, the timeseries visualization tool (note: you will need PlotJuggler 3.8.2 or later).

DataTamer is "fearless data logger" because you can record hundreds or thousands of variables: even 1 million points per second should have a fairly small CPU overhead.

Since all the values are aggregated in a single "snapshot", it is usually meant to record data in a periodic loop (a very frequent use case, in robotics applications).

Kudos to pal_statistics, for inspiring this project.

How it works

architecture

DataTamer can be used to monitor multiple variables in your applications.

Channels are used to take "snapshots" of a subset of variables at a given time. If you want to record at different frequencies, you can use different channels.

DataTamer will forward the collected data to 1 or multiple sinks; a sink may save the information immediately in a file (currently, we support MCAP) or publish it using an inter-process communication, for instance, a ROS2 publisher.

You can easily create your own, specialized sinks.

Use PlotJuggler to visualize your logs offline or in real-time.

Features

  • Serialization schema is created at run-time: no need to do code generation.
  • Suitable for real-time applications: very low latency (on the side of the callee).
  • Multi-sink architecture: recorded data can be forwarded to multiple "backends".
  • Very low serialization overhead, in the order of 1 bit per traced value.
  • The user can enable/disable traced variables at run-time.

Limitations

  • Traced variables can not be added (registered) once the recording starts (first takeSnapshot).
  • Focused on periodic recording. Not the best option for sporadic, asynchronous events.
  • If you use DataTamer::registerValue you must be careful about the lifetime of the object. If you prefer a safer RAII interface, use DataTamer::createLoggedValue instead.

Examples

Basic example

#include "data_tamer/data_tamer.hpp"
#include "data_tamer/sinks/mcap_sink.hpp"

int main()
{
  // Multiple channels can use this sink. Data will be saved in mylog.mcap
  auto mcap_sink = std::make_shared<DataTamer::MCAPSink>("mylog.mcap");

  // Create a channel and attach a sink. A channel can have multiple sinks
  auto channel = DataTamer::LogChannel::create("my_channel");
  channel->addDataSink(mcap_sink);

  // You can register any arithmetic value. You are responsible for their lifetime!
  double value_real = 3.14;
  int value_int = 42;
  auto id1 = channel->registerValue("value_real", &value_real);
  auto id2 = channel->registerValue("value_int", &value_int);

  // If you prefer to use RAII, use this method instead
  // logged_real will unregister itself when it goes out of scope.
  auto logged_real = channel->createLoggedValue<float>("my_real");

  // Store the current value of all the registered values
  channel->takeSnapshot();

  // You can disable (i.e., stop recording) a value like this
  channel->setEnabled(id1, false);
  // or, in the case of a LoggedValue
  logged_real->setEnabled(false);

  // The next snapshot will contain only [value_int], i.e. [id2],
  // since the other two were disabled
  channel->takeSnapshot();
}

How to register custom types

Containers such as std::vector and std::array are supported out of the box. You can also register a custom type, as shown in the example below.

#include "data_tamer/data_tamer.hpp"
#include "data_tamer/sinks/mcap_sink.hpp"
#include "data_tamer/custom_types.hpp"

// a custom type
struct Point3D
{
  double x;
  double y;
  double z;
};

namespace DataTamer
{
template <> struct TypeDefinition<Point3D>
{
  // Provide the name of the type
  std::string typeName() const { return "Point3D"; }
  // List all the member variables that you want to be saved (including their name)
  template <class Function> void typeDef(Function& addField)
  {
    addField("x", &Point3D::x);
    addField("y", &Point3D::y);
    addField("z", &Point3D::z);
  }
}
} // end namespace DataTamer

int main()
{
  auto channel = DataTamer::LogChannel::create("my_channel");
  channel->addDataSink(std::make_shared<DataTamer::MCAPSink>("mylog.mcap"));

  // Array/vectors are supported natively
  std::vector<double> values = {1, 2, 3, 4};
  channel->registerValue("values", &values);

  // Requires the implementation of DataTamer::TypeDefinition<Point3D>
  Point3D position = {0.1, -0.2, 0.3};
  channel->registerValue("position", &position);

  // save the data as usual ...
  channel->takeSnapshot();
}

Compilation

Compiling with ROS2

Just use colcon :)

Compiling with Conan (not ROS2 support)

Note that the ROS2 publisher will NOT be built when using this method.

Assuming conan 2.x installed. From the source directory.

Release:

conan install . -s compiler.cppstd=gnu17 --build=missing -s build_type=Release
cmake -S . -B build/Release -DCMAKE_BUILD_TYPE=Release \
      -DCMAKE_TOOLCHAIN_FILE="build/Release/generators/conan_toolchain.cmake"
cmake --build build/Release --parallel

Debug:

conan install . -s compiler.cppstd=gnu17 --build=missing -s build_type=Debug
cmake -S . -B build/Debug -DCMAKE_BUILD_TYPE=Debug \
      -DCMAKE_TOOLCHAIN_FILE="build/Debug/generators/conan_toolchain.cmake"
cmake --build build/Debug --parallel

How to deserialize data recorded with DataTamer

I will write more extensively about the serialization format used by DataTamer, but for the time being I created a single header file without external dependencies that you can just copy into your project: data_tamer_parser.hpp

You can see how it is used in this example: mcap_reader

CONTRIBUTING

No CONTRIBUTING.md found.

Repository Summary

Checkout URI https://github.com/PickNikRobotics/data_tamer.git
VCS Type git
VCS Version main
Last Updated 2024-02-02
Dev Status MAINTAINED
CI status No Continuous Integration
Released RELEASED
Tags No category tags.
Contributing Help Wanted (0)
Good First Issues (0)
Pull Requests to Review (0)

Packages

Name Version
data_tamer_cpp 0.9.4
data_tamer_msgs 0.9.4

README

Data Tamer

cmake Ubuntu ros2 codecov

DataTamer is a library to log/trace numerical variables over time and takes periodic "snapshots" of their values, to later visualize them as timeseries.

It works great with PlotJuggler, the timeseries visualization tool (note: you will need PlotJuggler 3.8.2 or later).

DataTamer is "fearless data logger" because you can record hundreds or thousands of variables: even 1 million points per second should have a fairly small CPU overhead.

Since all the values are aggregated in a single "snapshot", it is usually meant to record data in a periodic loop (a very frequent use case, in robotics applications).

Kudos to pal_statistics, for inspiring this project.

How it works

architecture

DataTamer can be used to monitor multiple variables in your applications.

Channels are used to take "snapshots" of a subset of variables at a given time. If you want to record at different frequencies, you can use different channels.

DataTamer will forward the collected data to 1 or multiple sinks; a sink may save the information immediately in a file (currently, we support MCAP) or publish it using an inter-process communication, for instance, a ROS2 publisher.

You can easily create your own, specialized sinks.

Use PlotJuggler to visualize your logs offline or in real-time.

Features

  • Serialization schema is created at run-time: no need to do code generation.
  • Suitable for real-time applications: very low latency (on the side of the callee).
  • Multi-sink architecture: recorded data can be forwarded to multiple "backends".
  • Very low serialization overhead, in the order of 1 bit per traced value.
  • The user can enable/disable traced variables at run-time.

Limitations

  • Traced variables can not be added (registered) once the recording starts (first takeSnapshot).
  • Focused on periodic recording. Not the best option for sporadic, asynchronous events.
  • If you use DataTamer::registerValue you must be careful about the lifetime of the object. If you prefer a safer RAII interface, use DataTamer::createLoggedValue instead.

Examples

Basic example

#include "data_tamer/data_tamer.hpp"
#include "data_tamer/sinks/mcap_sink.hpp"

int main()
{
  // Multiple channels can use this sink. Data will be saved in mylog.mcap
  auto mcap_sink = std::make_shared<DataTamer::MCAPSink>("mylog.mcap");

  // Create a channel and attach a sink. A channel can have multiple sinks
  auto channel = DataTamer::LogChannel::create("my_channel");
  channel->addDataSink(mcap_sink);

  // You can register any arithmetic value. You are responsible for their lifetime!
  double value_real = 3.14;
  int value_int = 42;
  auto id1 = channel->registerValue("value_real", &value_real);
  auto id2 = channel->registerValue("value_int", &value_int);

  // If you prefer to use RAII, use this method instead
  // logged_real will unregister itself when it goes out of scope.
  auto logged_real = channel->createLoggedValue<float>("my_real");

  // Store the current value of all the registered values
  channel->takeSnapshot();

  // You can disable (i.e., stop recording) a value like this
  channel->setEnabled(id1, false);
  // or, in the case of a LoggedValue
  logged_real->setEnabled(false);

  // The next snapshot will contain only [value_int], i.e. [id2],
  // since the other two were disabled
  channel->takeSnapshot();
}

How to register custom types

Containers such as std::vector and std::array are supported out of the box. You can also register a custom type, as shown in the example below.

#include "data_tamer/data_tamer.hpp"
#include "data_tamer/sinks/mcap_sink.hpp"
#include "data_tamer/custom_types.hpp"

// a custom type
struct Point3D
{
  double x;
  double y;
  double z;
};

namespace DataTamer
{
template <> struct TypeDefinition<Point3D>
{
  // Provide the name of the type
  std::string typeName() const { return "Point3D"; }
  // List all the member variables that you want to be saved (including their name)
  template <class Function> void typeDef(Function& addField)
  {
    addField("x", &Point3D::x);
    addField("y", &Point3D::y);
    addField("z", &Point3D::z);
  }
}
} // end namespace DataTamer

int main()
{
  auto channel = DataTamer::LogChannel::create("my_channel");
  channel->addDataSink(std::make_shared<DataTamer::MCAPSink>("mylog.mcap"));

  // Array/vectors are supported natively
  std::vector<double> values = {1, 2, 3, 4};
  channel->registerValue("values", &values);

  // Requires the implementation of DataTamer::TypeDefinition<Point3D>
  Point3D position = {0.1, -0.2, 0.3};
  channel->registerValue("position", &position);

  // save the data as usual ...
  channel->takeSnapshot();
}

Compilation

Compiling with ROS2

Just use colcon :)

Compiling with Conan (not ROS2 support)

Note that the ROS2 publisher will NOT be built when using this method.

Assuming conan 2.x installed. From the source directory.

Release:

conan install . -s compiler.cppstd=gnu17 --build=missing -s build_type=Release
cmake -S . -B build/Release -DCMAKE_BUILD_TYPE=Release \
      -DCMAKE_TOOLCHAIN_FILE="build/Release/generators/conan_toolchain.cmake"
cmake --build build/Release --parallel

Debug:

conan install . -s compiler.cppstd=gnu17 --build=missing -s build_type=Debug
cmake -S . -B build/Debug -DCMAKE_BUILD_TYPE=Debug \
      -DCMAKE_TOOLCHAIN_FILE="build/Debug/generators/conan_toolchain.cmake"
cmake --build build/Debug --parallel

How to deserialize data recorded with DataTamer

I will write more extensively about the serialization format used by DataTamer, but for the time being I created a single header file without external dependencies that you can just copy into your project: data_tamer_parser.hpp

You can see how it is used in this example: mcap_reader

CONTRIBUTING

No CONTRIBUTING.md found.