CHANGES.rst

Change Log

3.2.5 2026-January-21

• change warnings about deprecation of error_components() and derivates to PendingDeprecationWarning
• Drop support for Python 3.8

3.2.4 2026-January-9

Adds:

• Adds a section in the documentation advertising the forthcoming 4.0.0 release.

• Add github action CI to automatically publish a new package version to pypi when

  a github release of a new version is published.

• Increases the stacklevel of the warning about std_dev==0 so that it blames the caller rather than blaming the ufloat() function.
• Adjusts the Sphinx configuration to allow for reproducible builds using SOURCE_DATE_EPOCH.
• Mark Python 3.13 and 3.14 as officially supported.

Deprecates:

• The AffineScalarFunc.derivatives property has been marked as deprecated. This

  property will be removed in a future release.

• The AffineScalarFunc.error_components() method has been marked as deprecated. This

  method will be replaced by a property of the same name in a future release.

• Support for interoperability between uncertainties AffineScalarFunc scalar objects

  and np.matrix objects is now marked as deprecated. According to the numpy documentation usage of the np.matrix class is no longer recommended.

3.2.3 2025-April-18

Changes

• Changes how numpy is handled as an optional dependency. Previously,

  importing a numpy-dependent function, like correlated_values, without numpy installed would result in an ImportError at import time. Now such a function can be imported but if the user attempts to execute it, a NotImplementedError is raised indicating that the function can't be used because numpy couldn't be imported.

• Refactors the implementation for the calculation of the derivatives of

  the power function and improves the corresponding testing.

Adds:

• Adds a small benchmarking suite to CI to guard against absolute

  performance regressions and accidental breakage of the lazy expansion algorithm whichs ensures O(N), rather than O(N^2), scaling complexity for operations involving many numbers with uncertainty. Established connectivity with `codspeed.io<codspeed.io>`_ to track benchmarking results. (#274)

Fixes:

• Adds documentation for ufloat_fromstr behavior for strings which do

  not contain uncertainty. (#287)

• Fixes typos in ufloat_fromstr docstring examples (#285)
• Fixes readthedocs configuration so that the build passes (#254)
• Fixes all doctests (#281)

• Adjusts codecov.io configuration so that minor code coverage changes

  will not result in indications that tests are failing. Rather code coverage reports will be purely informational for code reviewers. Also fix other minor configuration issues. (#270)

• Fixes a bug that resulted in a ZeroDivisionError while formatting

  very small numbers with uncertainty (#135)

Deprecates:

• Certain umath functions and AffineScalarFunc/UFloat methods will

  be removed in a future release. A deprecation warning has been added to these functions and methods. The following umath functions are marked as deprecated: ceil, copysign, fabs, factorial, floor, fmod, frexp, ldexp, modf, trunc. The following AffineScalarFunc/UFloat methods are marked as deprecated: __floordiv__, __mod__, __abs__, __trunc__, __lt__, __le__, __gt__, __ge__, __bool__.

3.2.2 2024-July-08

Fixes:

• fix support for Numpy 2.0 (#245). Note: uncertainties.unumpy still

  provides umatrix based on numpy.matrix. With numpy.matrix discouraged, umatrix is too, and will be dropped in a future release.

• fix automated running and reporting of code coverage with tests (#246)
• use setuptools-scm for setting version number from git tag (#247)

3.2.1 2024-June-08

---

Fixes for build, deployment, and docs

• Use explicit package list to make sure unumpy is included (#232)
• Use setuptools-scm to make sure all files are in the source distribution (#235)
• updates to configuration for and links to readthedocs documentation. (#239)
• use double backticks more uniformly in docs. (#240)
• fixes to README.rst to allow it to render (needed for PyPI upload) (#243)

3.2.0 2024-June-02

Version 3.2.0 is the first release of Uncertainties in nearly two years and the first minor release in over five years. It marks the beginning of an effort to refresh and update the project with a new and expanded team of maintainers.

• Main Changes
  • Moved code development to lmfit organization, with 4 maintainers.
  • Update documentation.

  • Drop future dependency. Uncertainties now has no external dependencies when

    not using Numpy integration (Drop official support for Python versions before 3.8 #200).

  • Drop support for Python versions before 3.8, including Python 2 (Drop official support for Python versions before 3.8 #200)
  • remove 1to2 and deprecations (remove 1to2 and depreciations #214)
• Developer related changes
  • Moved from setup.py to pyproject.toml (Transition from setup.py to pyproject.toml #199)
  • Move tests to tests folder (Move tests to tests folder #216)
  • Update unumpy test to be compatible with numpy 2
  • Mark docstrings with backslashes as raw strings in tests (Mark docstrings with backslashes as raw strings #226)

Older Version history

Main changes: - 3.1.6: The pretty-print and LaTeX format can now be customized. - 3.1.5: Added a "p" formatting option, that makes sure that there are always

parentheses around the … ± … part of printed numbers.

• 3.1.4: Python 2.7+ is now required.
• 3.1.2: Fix for NumPy 1.17 and unumpy.ulinalg.pinv().
• 3.1: Variables built through a correlation or covariance matrix, and that have uncertainties that span many orders of magnitude are now calculated more accurately (improved correlated_values() and correlated_values_norm() functions).
• 3.0: Massive speedup for some operations involving large numbers of numbers with uncertainty, like sum(ufloat(1, 1) for _ in xrange(100000)) (this is about 5,000 times faster than before).
• 2.4.8: Friendlier completions in Python shells, etc.: internal functions should not appear anymore (for the user modules: uncertainties, uncertainties.umath and uncertainties.unumpy). Parsing the shorthand notation (e.g. 3.1(2)) now works with infinite values (e.g. -inf(inf)); this mirrors the ability to print such numbers with uncertainty. The Particle Data Group rounding rule is applied in more cases (e.g. printing 724.2±26.2 now gives 724±26). The shorthand+LaTeX formatting of numbers with an infinite nominal value is fixed. uncertainties.unumpy.matrix now uses .std_devs instead of .std_devs(), for consistency with floats with uncertainty (automatic conversion of code added to uncertainties.1to2).
• 2.4.7: String formatting now works for (-)inf+/-... numbers.
• 2.4.5: String formatting now works for NaN+/-... numbers.
• 2.4.4: The documentation license now allows its commercial use.
• 2.4.2: NumPy 1.8 compatibility.
• 2.4.1: In uncertainties.umath, functions ceil(), floor(), isinf(), isnan() and trunc() now return values of the same type as the corresponding math module function (instead of generally returning a value with a zero uncertainty ...+/-0).
• 2.4: Extensive support for the formatting of numbers with uncertainties. A zero uncertainty is now explicitly displayed as the integer 0. The new formats are generally understood by ufloat_fromstr(). Abbreviations for the nominal value (n) and the standard deviation (s) are now available.
• 2.3.6: Full support for limit cases of the power operator umath.pow().
• 2.3.5: Uncertainties and derivatives can now be NaN (not-a-number). Full support for numbers with a zero uncertainty (sqrt(ufloat(0, 0)) now works). Full support for limit cases of the power operator (x**y).
• 2.3: Functions wrapped so that they accept numbers with uncertainties instead of floats now have full keyword arguments support (improved wrap() function). Incompatible change: wrap(..., None) should be replaced by wrap(...) or wrap(..., []).
• 2.2: Creating arrays and matrices of numbers with uncertainties with uarray() and umatrix() now requires two simple arguments (nominal values and standard deviations) instead of a tuple argument. This is consistent with the new, simpler ufloat() interface. The previous usage will be supported for some time. Users are encouraged to update their code, for instance through the newly provided code updater, which in addition now automatically converts .set_std_dev(v) to .std_dev = v.
• 2.1: Numbers with uncertainties are now created more directly like ufloat(3, 0.1), ufloat(3, 0.1, "pi"), ufloat_fromstr("3.0(1)"), or ufloat_fromstr("3.0(1)", "pi"). The previous ufloat((3, 0.1)) and ufloat("3.0(1)") forms will be supported for some time. Users are encouraged to update their code, for instance through the newly provided code updater.
• 2.0: The standard deviation is now obtained more directly without an explicit call (x.std_dev instead of x.std_dev()). x.std_dev() will be supported for some time. Users are encouraged to update their code. The standard deviation of a variable can now be directly updated with x.std_dev = 0.1. As a consequence, x.set_std_dev() is deprecated.
• 1.9.1: Support added for pickling subclasses of UFloat (= Variable).
• 1.9: Added functions for handling correlation matrices: correlation_matrix() and correlated_values_norm(). (These new functions mirror the covariance-matrix based covariance_matrix() and correlated_values().) UFloat.position_in_sigmas() is now named UFloat.std_score(), so as to follow the common naming convention (standard score). Obsolete functions were removed (from the main module: NumberWithUncert, num_with_uncert, array_u, nominal_values, std_devs).
• 1.8: Compatibility with Python 3.2 added.
• 1.7.2: Compatibility with Python 2.3, Python 2.4, Jython 2.5.1 and Jython 2.5.2 added.
• 1.7.1: New semantics: ufloat("12.3(78)") now represents 12.3+/-7.8 instead of 12.3+/-78.
• 1.7: ufloat() now raises ValueError instead of a generic Exception, when given an incorrect string representation, like float() does.
• 1.6: Testing whether an object is a number with uncertainty should now be done with isinstance(..., UFloat). AffineScalarFunc is not imported by from uncertainties import * anymore, but its new alias UFloat is.
• 1.5.5: The first possible license is now the Revised BSD License instead of GPLv2, which makes it easier to include this package in other projects.
• 1.5.4.2: Added umath.modf() and umath.frexp().
• 1.5.4: ufloat does not accept a single number (nominal value) anymore. This removes some potential confusion about ufloat(1.1) (zero uncertainty) being different from ufloat("1.1") (uncertainty of 1 on the last digit).
• 1.5.2: float_u, array_u and matrix_u renamed ufloat, uarray and umatrix, for ease of typing.
• 1.5: Added functions nominal_value and std_dev, and modules unumpy (additional support for NumPy arrays and matrices) and unumpy.ulinalg (generalization of some functions from numpy.linalg). Memory footprint of arrays of numbers with uncertainties divided by 3. Function array_u is 5 times faster. Main function num_with_uncert renamed float_u, for consistency with unumpy.array_u and unumpy.matrix_u, with the added benefit of a shorter name.
• 1.4.5: Added support for the standard pickle module.
• 1.4.2: Added support for the standard copy module.
• 1.4: Added utilities for manipulating NumPy arrays of numbers with uncertainties (array_u, nominal_values and std_devs).
• 1.3: Numbers with uncertainties are now constructed with num_with_uncert(), which replaces NumberWithUncert(). This simplifies the class hierarchy by removing the NumberWithUncert class.
• 1.2.5: Numbers with uncertainties can now be entered as NumberWithUncert("1.23+/-0.45") too.
• 1.2.3: log(x, base) is now supported by umath.log(), in addition to log(x).
• 1.2.2: Values with uncertainties are now output like 3+/-1, in order to avoid confusing 3+-1 with 3+(-1).
• 1.2: A new function, wrap(), is exposed, which allows non-Python functions (e.g. Fortran or C used through a module such as SciPy) to handle numbers with uncertainties.
• 1.1: Mathematical functions (such as cosine, etc.) are in a new uncertainties.umath module; they do not override functions from the math module anymore.
• 1.0.12: Main class (Number_with_uncert) renamed NumberWithUncert so as to follow PEP 8.
• 1.0.11: origin_value renamed more appropriately as nominal_value.
• 1.0.9: correlations() renamed more appropriately as covariance_matrix().