0.2.2

Release notes for sbmlsim 0.2.2

• bugfix release

0.2.0

Release notes for sbmlsim 0.2.0

• breaking changes in units handling
• bugfix plotting dimensionless units in labels
• remove deprecated distrib and sampling functionality.
• fixed typo in sensitivity

parameter fitting

• refactoring parameter fitting
• improved weight and options handling
• documentation
• reports for parameter fitting (fit mapping contribution, #79)
• storing and combination of parameter fitting results (#73)
• better cost plots (#72)
• improved parameter fitting results plots (#96)
• loss functions implemented (#99)
  • ‘linear’ (default) : rho(z) = z. Gives a standard least-squares problem.
  • ‘soft_l1’ : rho(z) = 2 * ((1 + z)**0.5 - 1). The smooth approximation of l1 (absolute value) loss. Usually a good choice for robust least squares.
  • ‘cauchy’ : rho(z) = ln(1 + z). Severely weakens outliers influence, but may cause difficulties in optimization process.
  • ‘arctan’ : rho(z) = arctan(z). Limits a maximum loss on a single residual, has properties similar to ‘cauchy’.
• figures closing in reports (#88)
• improved parameter fitting plots and results (#32)
• bugfix all NaN errors (#101)

0.1.14

Release notes for sbmlsim 0.1.14

• Fix #81, feature timecourse concatenation and reuse in timecoursesim

This allows simplified creation of multiple dosing timecourse simulations and reuse
of timecourse definitions in multiple simulations. E.g. repeated timecourse [tc]*3

    simulator = Simulator(MODEL_REPRESSILATOR)
    tc = Timecourse(
                    start=0,
                    end=50,
                    steps=100,
                    changes={"X": 10})

    s = simulator._timecourse(
        simulation=TimecourseSim(
            [tc]*3
        )
    )

• Fix #82, bugfix; remove time shift from discarded simulations
• Fix #83, allow empty timecourses in timecoursesim
• Fix #86, dependency update ray>=1.2.0
• Fix #87, weighting by counts in parameter fitting
• Fix #88, bugfix figure closing in parameter fitting
• adding mypy configuration and initial mypy fixes
• many flake8 fixes and type annotations
• Fix #91, support hex colors in plot
• Fix #94, update xarray>=0.17.0

0.1.13

Release notes for sbmlsim 0.1.13

• Fix #51, feature discarding pre-simulation
• Fix #76, Package templates in pip packages
• dependency update

	python-libsbml-experimental>=5.19.0
	python-libsedml>=2.0.15
	python-libcombine>=0.2.7
	python-libnuml>=1.1.3
	libroadrunner>=2.0.4
    ray>=1.1.0

• Fix #77, updated github actions
• Fix #78, contributing information and depinfo

0.1.12

Release notes for sbmlsim 0.1.12

• Fix #51, feature discarding pre-simulation
• Fix #76, Package templates in pip packages
• dependency update

	python-libsbml-experimental>=5.19.0
	python-libsedml>=2.0.15
	python-libcombine>=0.2.7
	python-libnuml>=1.1.3
	libroadrunner>=2.0.4
    ray>=1.1.0

0.1.11

Release notes for sbmlsim 0.1.11

• update to ray ray>=1.0
• working on
• minor bugfixes
• support for model changes with initial assignments

0.1.10

Release notes for sbmlsim 0.1.10

• better handling of model changes and model manipulations
• working on
• Minor bugfixes

0.1.9

Release notes for sbmlsim 0.1.9

• Fixed regression in unit serialization
• Minor bugfixes

0.1.8

Release notes for sbmlsim 0.1.8

• Fix #64 support of model changes (with unit normalization)
• minor bugfixes

0.1.7

Release notes for sbmlsim 0.1.7

• fixed packaging of data
• support for count from DataSets (#50)
• improved plotting serialization, adding order on curves
• plotting bugfixes (better handling of labels and legends, default colors serialized, #56)