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Releases: AnyBody-Research-Group/AnyPyTools

AnyPyTools version 1.7.7

18 Jan 14:26
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Fixed:

  • Fix minor problem in repr for AnyPyProcessOutput.
  • Fix a problem where the pytest plugin would crash if AnyBody could not be found

AnyPyTools version 1.7.6

08 Dec 22:31
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Fixed:

  • Fix small issues in tutorials.
  • Fix issues when reading NaNs produced by AnyBody

AnyPyTools version 1.7.5

28 Sep 20:27
c7f986c
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Fixed:

  • Return code on linux is now correctly intercepted and reported.

AnyPyTools version 1.7.4

27 Sep 17:45
56588e8
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Fixed:

  • Fixed pytest deprecation warnings.
  • Remove a stray debug print

AnyPyTools version 1.7.3

27 Sep 13:31
bd28704
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Fixed:

  • Fixed a bug on linux when anybody was using it own internal Python hooks. Redirecting the output on the linux would cause
    python initialization to fail.

AnyPyTools version 1.7.2

14 Sep 09:20
f52f847
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Changed:

  • Add error message when no files are found with
    search_subdir arguments (fixes #69).
  • Update documentation to use markdown.

AnyPyTools version 1.7.1

13 Sep 08:50
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Fixed:

  • Fix deprecation warnings in pytest plugin.

AnyPyTools version 1.7.0

04 Sep 16:46
735bb55
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Added:

  • AnyPyTools can now be used on linux if the AnyBody Modeling System is installed using wine

AnyPyTools v.1.6.0

12 Aug 12:43
a220946
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Changed:

  • The to_dataframe() methods have been updated.
    They now return a dataframe without an index by default.

    They also now support interpolation of the data.

    app =  AnyPyProcess()
    results = app.start_marco(macro_list)

    df = results.to_dataframe(
      interp_var="Main.MyStudy.Output.Abscissa.t",
      interp_val=linspace(0,1,50)
    )

Added:

  • Documentation on how to use the to_dataframe() method has been added to the tutorials.

AnyPyTools version 1.5.0

10 Aug 13:30
20bde77
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Add methods for exporing simuation output as a pandas dataframe.

app =  AnyPyProcess()
results = app.start_marco(macro_list)

df = results.to_dataframe(index_var="Main.MyStudy.Output.Abscissa.t")

The data has too be consistent across all macros. That means that the index_var must be present in all simulations. Also note that since pandas dataframes are 2D any 3D data will be flattened. For example 3D vectors which will be saved into three columns in the dataframe. E.g. r[0], r[1], r[2].