pySPACE is a Signal Processing And Classification Environment (SPACE)
written in Python interfacing to the user
with YAML configuration files and enabling parallel process
execution (for all of these reasons we put a small py in front).
pySPACE allows rapid specification, execution,
and analysis of empirical investigations (short: benchmarking)
in signal processing and machine learning.
Besides the benchmarking way of executing pySPACE where you can evaluate your
data with your own configuration of algorithms,
the software also provides a launch_live mode
where you can directly execute signal processing as soon as you have the data
in an online fashion.
If you take a look at the Main Software Structure of pySPACE you should be able to
directly see how you can interact with the software.
Besides this, user data (input, output and processing definitions)
are stored in your pySPACEcenter (until configured otherwise). You can
see more when looking at the Getting started page.
In pySPACE the parallelization part is not restricted to signal processing and
machine learning, though these are the only use cases currently supported.
By defining your own operations,
you can interface any library with pySPACE, using different
parallelization modes. pySPACE already provides interfaces to popular toolkit
libraries like the Weka framework,
and the MMLF but
also comes with a lot of own algorithms,
though some algorithms are just wrapper to methods from other libraries like
the Modular toolkit for Data Processing
This software can be used to analyze and compare the performance
(e.g. classification accuracy) of different methods and parameter settings, respectively.
It allows to estimate these quantities based on different validation schemes
(including crossvalidation) and several
independent runs. Furthermore, it allows to make use of the fact that most of
these problems can be handled independently and allows to process subtasks in parallel on different
backends. For instance the
allows to run as
many tasks in parallel as cores are present in the respective machine.
pySPACE supports the massive parallel execution of benchmarking experiment on grids
like systems using
sharing a common data access.
This software has an object-oriented design,
providing classes for important entities like:
which define the structure of the data, how it is changed and which
parallelization mode is used.
!! IMPORTANT INFORMATION !!
This software including all extensions and accessories is neither designed nor
suitable for medical or diagnostic purposes.
This software must not be used as a medical product according
to appendixes 1 and 2 of the medical product operator regulation
!! WICHTIGER HINWEIS !!
Die vorliegende Software einschließlich aller Erweiterungen und Zubehör ist
für medizinische oder diagnostische Zwecke nicht bestimmt oder geeignet.
Sie darf nich mit Zweckbestimmung eines Medizinproduktes
im Sinne der Anlagen 1 und 2 der Medizinprodukte-Betreiberverordnung