MatLogger2

Library for logging of numeric data to HDF5 MAT-files, which is RT-safe and multithreaded.

Building MatLogger2 from source

Standard cmake workflow:

• git clone the repo to SOURCE_DIR
• create a build folder BUILD_DIR
• cd BUILD_DIR && cmake SOURCE_DIR
• make
• make install

Installing the binary release

• go to GitHub release page and download the latest binary
• sudo dpkg -i matlogger2-X.Y.Z-Linux.deb

The binary release has been tested only with Ubuntu 16.04

Linking against MatLogger2

find_package(matlogger2 REQUIRED)
target_link_libraries(mytarget matlogger2::matlogger2)

Quick start

Circular-buffer mode

#include <matlogger2/matlogger2.h>

int main()
{
   auto logger = XBot::MatLogger2::MakeLogger("/tmp/my_log"); // date-time automatically appended
   logger->set_buffer_mode(XBot::VariableBuffer::Mode::circular_buffer);
   
   for(int i = 0; i < 1e5; i++)
   {
       Eigen::VectorXd vec(10);
       Eigen::MatrixXd mat(6,8);
       
       logger->add("my_vec_var", vec);
       logger->add("my_scalar_var", M_PI);
       logger->add("my_mat_var", mat);
   }
   
} // destructor flushes to disk

Producer-consumer mode (default)

#include <matlogger2/matlogger2.h>
#include <matlogger2/utils/mat_appender.h>

int main()
{
   auto logger = XBot::MatLogger2::MakeLogger("/tmp/my_log.mat"); // extension provided -> date-time NOT appended
   auto appender = XBot::MatAppender::MakeInstance();
   appender->add_logger(logger);
   appender->start_flush_thread();
   
   for(int i = 0; i < 1e5; i++)
   {
       Eigen::VectorXd vec(10);
       Eigen::MatrixXd mat(6,8);
       
       logger->add("my_vec_var", vec);
       logger->add("my_scalar_var", M_PI);
       logger->add("my_mat_var", mat);
       
       usleep(1000);
   }
   
}

Custom buffer size and compression

#include <matlogger2/matlogger2.h>

int main()
{
   XBot::MatLogger2::Options opt;
   opt.default_buffer_size = 1e4; // set default buffer size
   opt.enable_compression = true; // enable ZLIB compression
                                  // this can be computationally expensive
   auto logger = XBot::MatLogger2::MakeLogger("/tmp/my_log", opt);
   
   logger->create("my_vec_var", 10); // this pre-allocates the buffer with default buffer size
   
   logger->create("my_mat_var", 6, 8, 1e3); // custom buffer size can be set variable-wise
   
   for(int i = 0; i < 1e5; i++)
   {
       Eigen::VectorXd vec(10);
       Eigen::MatrixXd mat(6,8);
       
       logger->add("my_vec_var", vec);
       logger->add("my_scalar_var", M_PI);
       logger->add("my_mat_var", mat);
       
       usleep(1000);
   }
   
   logger.reset(); // manually destroy the logger in order to flush to disk
   
} 

Python bindings

If pybind11 can be found on your system, python2.7 bindings will be generated and installed. It'll then be possible to log numpy arrays and python lists in the same way as the C++ API works with Eigen3 types and STL classes.

Python API vs C++

Main differences are:

• factories are replaced by simple constructors

Example

import matlogger2.matlogger as ml

logger = ml.MatLogger2(file='/tmp/my_log', 
                     enable_compression=True,# default value is False
                     default_buffer_size=int(1e5)) # default value is 1e4
             
logger.setBufferMode(ml.BufferMode.ProducerConsumer) # this is already the default choice

ap = ml.MatAppender()
ap.add_logger(logger)
ap.start_flush_thread()

logger.create('myvar', 5, 1, buffer_size=1000) # 5x1 variable
logger.add('myvar', [0, 1, 2, 3, 4])

del(logger) # destroy to force flushing

Documentation

Header files are documented with doxygen! An online version is also available.