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  • v0.12.1
    Changelog in the Sphinx Documenatation
    
    From this release on, a changelog generated from git version tags is
    available in the Sphinx documentation.
  • v0.12.0
    Keyboard Shortcut for Pretty Xaxis Date Format
    
    This release adds a keyboard shortcut 'x' to the `TimeLinesAnimator` to
    run autofmt_xdate.
  • v0.11.1
    Fix automated PyPI upload
    
    This release fixes the automated package upload to PyPI. pyOpenSSL was
    not installed in the runner.
  • v0.11.0
    Tight Layout Keyboard Shurtcut
    
    This release adds a keyboard shortcut 't' to run
    matplotlib.pyplot.tight_layout() manually.
  • v0.10.0
    Introduce Filters
    
    This release introduces the concept of Filters for modifying incoming
    data. With custom Filters it is possible to adjust (e.g. smooth) data or
    even to add new derived data (e.g.  the maximum, a derivative, an
    integral, etc...).
    
    A slight speedup of the SpectrumAnimator was achieved by using scipy's
    FFT implementation, not numpy's. Furthermore, displaying the current FPS
    is now possible for some Animators.
  • v0.9.0
    Structural Improvements
    
    This release reduces duplicate code and improves the overall code
    structure. Furthermore, CI tests are now performed for Python versions
    back to 3.4.
  • v0.8.0
    Live Histograms and Spectra and Data Generation
    
    This release adds a lot of useful new features:
    
    - Live Histograms
    - Live FFTs (spectra)
    - Data Generation Tool
  • v0.7.0
    Pausing, Custom Animators, Rate Limiting and More Documentation
    
    This release introduces some structural changes that allow for using
    custom Animators (#14), which can now be specified similar to the custom
    parsers.
    
    Furthermore, the incoming data rate can now be limited per streamer (#27)
    which can be handy when the plotting can't catch up the the input.
    
    Also, the animation can now be paused (and resumed) by hitting the
    spacebar. During pause, the graph can be moved, zoomed and modified with
    the standard Matplotlib toolbar without further data updates.
    
    The documentation has recieved a big update with a clearer structure and
    more information on various topics.
  • v0.6.0
    Prettier Subplots Arrangement
    
    Bugs Fixed:
    
    - #44: Repeated values were deleted when using --extrapolate
    
    New Features:
    
    - #45: Option for automatic tight_layout(), i.e. less whitespace
    - #37: Column blacklist for CsvParser
  • v0.5.0
    Improved Timeseries Plotting
    
    New Features:
    
    - #4: make the temporal time frame configurable
    - #41: clear the buffer at each frame, better preventing indefinite
      buffer growth
    - #23: enable sharing time axis between subplots
    - #26: use autofmt_xdate to display time axis more readable
    - #30, #31: proper documentation (deployed to GitLab Pages)
  • v0.4.0
    Multiple Improvements
    
    Fixed issues:
    
    - #35: add-source command failed due to importlib not being imported
    - #36: csv parsing failed when using a command as input
    
    New Features:
    
    - #34: setuptools' entry_points can now be used to add parsers do polt
    - #32: the csv delimiter used by CsvParser can now be specified via cli and the
           configuration
    - #36, #39: an --encoding option exists now for the add-source command to
                specify the input encoding for parsers
    
    Improvements:
    
    - #40: the left-free subplot area is now minimized more aggressively
    
    Code style:
    
    - #33: parsers now reside in separate modules
  • v0.3.0
    Improved Command-Line Interface
    
    - use click as command-line parser
    - use console_scripts entry point to make cli available via a simple `polt`
  • v0.2.0
    Improve Parsers
    
    This release improves the available parsers for numbers and CSV input.
    Several bugs were also fixed.
  • v0.1.0
    Initial Version
    
    This is the initial release with a basic set of features:
    
    - reading numbers from multiple sources
    - rudimentary timeseries plotting