uncertainties.unumpy.core Namespace Reference

Classes
class	CallableStdDevs
	Matrix class. More...
class	matrix

Functions
def	unumpy_to_numpy_matrix
def	nominal_values
	Return the nominal values of the numbers in NumPy array arr. More...
def	std_devs
	Return the standard deviations of the numbers in NumPy array arr. More...
def	derivative
def	wrap_array_func
def	uarray
	Arrays. More...
def	array_derivative
def	func_with_deriv_to_uncert_func
def	inv_with_derivatives
	Matrix inverse. More...
def	pinv_with_derivatives
	Matrix pseudo-inverse. More...
def	pinv
def	umatrix
	Constructs a matrix that contains numbers with uncertainties. More...
def	define_vectorized_funcs
	Defines vectorized versions of functions from uncertainties.umath_core. More...

Variables
list	__all__
tuple	to_nominal_values
	Utilities: More...
tuple	to_std_devs
tuple	inv = func_with_deriv_to_uncert_func(inv_with_derivatives)
list	pinv_default = numpy.linalg.pinv.__defaults__[0]
tuple	pinv_with_uncert = func_with_deriv_to_uncert_func(pinv_with_derivatives)
tuple	pinv = uncert_core.set_doc(""" Version of numpy.linalg.pinv that works with array-like objects that contain numbers with uncertainties. The result is a unumpy.matrix if numpy.linalg.pinv would return a matrix for the array of nominal values. Analytical formulas are used. Original documentation: %s """ % numpy.linalg.pinv.__doc__)

Function Documentation

def uncertainties.unumpy.core.array_derivative	(		array_like,
			var
	)

def uncertainties.unumpy.core.define_vectorized_funcs

(

)

Defines vectorized versions of functions from uncertainties.umath_core.

Some functions have their name translated, so as to follow NumPy's convention math.acos -> numpy.arccos).

def uncertainties.unumpy.core.derivative	(		u,
			var
	)

def uncertainties.unumpy.core.func_with_deriv_to_uncert_func

(

func_with_derivatives

)

def uncertainties.unumpy.core.inv_with_derivatives	(		arr,
			input_type,
			derivatives
	)

Matrix inverse.

Defines the matrix inverse and its derivatives.

See the definition of func_with_deriv_to_uncert_func() for its
detailed semantics.

def uncertainties.unumpy.core.nominal_values

(

arr

)

Return the nominal values of the numbers in NumPy array arr.

Elements that are not numbers with uncertainties (derived from a class from this module) are passed through untouched (because a numpy.array can contain numbers with uncertainties and pure floats simultaneously).

If arr is of type unumpy.matrix, the returned array is a numpy.matrix, because the resulting matrix does not contain numbers with uncertainties.

def uncertainties.unumpy.core.pinv	(		array_like,
			rcond = pinv_default
	)

def uncertainties.unumpy.core.pinv_with_derivatives	(		arr,
			input_type,
			derivatives,
			rcond
	)

Matrix pseudo-inverse.

Defines the matrix pseudo-inverse and its derivatives.

Works with real or complex matrices.

See the definition of func_with_deriv_to_uncert_func() for its
detailed semantics.

def uncertainties.unumpy.core.std_devs

(

arr

)

Return the standard deviations of the numbers in NumPy array arr.

Elements that are not numbers with uncertainties (derived from a class from this module) are passed through untouched (because a numpy.array can contain numbers with uncertainties and pure floats simultaneously).

If arr is of type unumpy.matrix, the returned array is a numpy.matrix, because the resulting matrix does not contain numbers with uncertainties.

def uncertainties.unumpy.core.uarray	(		nominal_values,
			std_devs = None
	)

Arrays.

def uncertainties.unumpy.core.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.

def uncertainties.unumpy.core.unumpy_to_numpy_matrix

(

arr

)

def uncertainties.unumpy.core.wrap_array_func

(

func

)

Variable Documentation

list uncertainties.unumpy.core.__all__

Initial value:

= [
    # Factory functions:
    'uarray', 'umatrix',

    # Utilities:
    'nominal_values', 'std_devs',

    # Classes:
    'matrix'
    ]

tuple uncertainties.unumpy.core.inv = func_with_deriv_to_uncert_func(inv_with_derivatives)

tuple uncertainties.unumpy.core.pinv = uncert_core.set_doc(""" Version of numpy.linalg.pinv that works with array-like objects that contain numbers with uncertainties. The result is a unumpy.matrix if numpy.linalg.pinv would return a matrix for the array of nominal values. Analytical formulas are used. Original documentation: %s """ % numpy.linalg.pinv.__doc__)

list uncertainties.unumpy.core.pinv_default = numpy.linalg.pinv.__defaults__[0]

tuple uncertainties.unumpy.core.pinv_with_uncert = func_with_deriv_to_uncert_func(pinv_with_derivatives)

tuple uncertainties.unumpy.core.to_nominal_values

Initial value:

= numpy.vectorize(
    uncert_core.nominal_value,
    otypes=[float],  # Because vectorize() has side effects (dtype setting)
    doc=("Return the nominal value of the numbers with uncertainties contained"
         " in a NumPy (or unumpy) array (this includes matrices)."))

Utilities:

tuple uncertainties.unumpy.core.to_std_devs

Initial value:

= numpy.vectorize(
    uncert_core.std_dev,
    otypes=[float],  # Because vectorize() has side effects (dtype setting)
    doc=("Return the standard deviation of the numbers with uncertainties"
         " contained in a NumPy array, or zero for other objects."))