Exemple #1
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def uarray(nominal_values, std_devs=None):
    """
    Return a NumPy array of numbers with uncertainties
    initialized with the given nominal values and standard
    deviations.

    nominal_values, std_devs -- valid arguments for numpy.array, with
    identical shapes (list of numbers, list of lists, numpy.ndarray,
    etc.).

    std_devs=None is only used for supporting legacy code, where
    nominal_values can be the tuple of nominal values and standard
    deviations.
    """

    if std_devs is None:  # Obsolete, single tuple argument call
        deprecation('uarray() should now be called with two arguments.')
        (nominal_values, std_devs) = nominal_values

    return (numpy.vectorize(
        # ! Looking up uncert_core.Variable beforehand through
        # '_Variable = uncert_core.Variable' does not result in a
        # significant speed up:
        lambda v, s: uncert_core.Variable(v, s),
        otypes=[object])(nominal_values, std_devs))
Exemple #2
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def uarray(nominal_values, std_devs=None):
    """
    Return a NumPy array of numbers with uncertainties
    initialized with the given nominal values and standard
    deviations.

    nominal_values, std_devs -- valid arguments for numpy.array, with
    identical shapes (list of numbers, list of lists, numpy.ndarray,
    etc.).

    std_devs=None is only used for supporting legacy code, where
    nominal_values can be the tuple of nominal values and standard
    deviations.
    """

    if std_devs is None:  # Obsolete, single tuple argument call
        deprecation('uarray() should now be called with two arguments.')
        (nominal_values, std_devs) = nominal_values

    return (numpy.vectorize(
        # ! Looking up uncert_core.Variable beforehand through
        # '_Variable = uncert_core.Variable' does not result in a
        # significant speed up:
        lambda v, s: uncert_core.Variable(v, s), otypes=[object])
        (nominal_values, std_devs))
Exemple #3
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def umatrix(nominal_values, std_devs=None):
    """
    Constructs a matrix that contains numbers with uncertainties.

    The arguments are the same as for uarray(...): nominal values, and
    standard deviations.

    The returned matrix can be inverted, thanks to the fact that it is
    a unumpy.matrix object instead of a numpy.matrix one.
    """

    if std_devs is None:  # Obsolete, single tuple argument call
        deprecation('umatrix() should now be called with two arguments.')
        (nominal_values, std_devs) = nominal_values

    return uarray(nominal_values, std_devs).view(matrix)
Exemple #4
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def umatrix(nominal_values, std_devs=None):
    """
    Constructs a matrix that contains numbers with uncertainties.

    The arguments are the same as for uarray(...): nominal values, and
    standard deviations.

    The returned matrix can be inverted, thanks to the fact that it is
    a unumpy.matrix object instead of a numpy.matrix one.
    """

    if std_devs is None:  # Obsolete, single tuple argument call
        deprecation('umatrix() should now be called with two arguments.')
        (nominal_values, std_devs) = nominal_values

    return uarray(nominal_values, std_devs).view(matrix)
Exemple #5
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 def __call__(self):
     deprecation('the std_devs attribute should not be called'
                 ' anymore: use .std_devs instead of .std_devs().')
     return self
Exemple #6
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 def __call__ (self):
     deprecation('the std_devs attribute should not be called'
                 ' anymore: use .std_devs instead of .std_devs().')
     return self