nifty8.utilities module#

class NiftyMeta(name, bases, clsdict)[source]#: Bases: _DocStringInheritor

check_MPI_equality(obj, comm, hash=False)[source]#

Check that object is the same on all MPI tasks associated to a given communicator.

Raises a RuntimeError if it differs.

Parameters:

obj – Any Python object that implements __eq__.
comm (MPI communicator or None) – If comm is None, no check will be performed

check_MPI_synced_random_state(comm)[source]#

Check that random state is the same on all MPI tasks associated to a given communicator.

Raises a RuntimeError if it differs.

Parameters:: comm (MPI communicator or None) – If comm is None, no check will be performed

check_object_identity(obj0, obj1)[source]#: Check if two objects are the same and throw ValueError if not.

class frozendict(*args, **kwargs)[source]#

Bases: Mapping

An immutable wrapper around dictionaries that implements the complete collections.Mapping interface. It can be used as a drop-in replacement for dictionaries where immutability is desired.

__init__(*args, **kwargs)[source]#

copy(**add_or_replace)[source]#

dict_cls#: alias of dict

get_slice_list(shape, axes)[source]#

Helper function which generates slice list(s) to traverse over all combinations of axes, other than the selected axes.

Parameters:

shape (tuple) – Shape of the data array to traverse over.
axes (tuple) – Axes which should not be iterated over.

Yields:

list – The next list of indices and/or slice objects for each dimension.

Raises:

ValueError – If shape is empty. If axes(axis) does not match shape.

indent(inp)[source]#

infer_space(domain, space)[source]#

iscomplextype(dtype)[source]#

issingleprec(dtype)[source]#

lognormal_moments(mean, sigma, N=0)[source]#

Calculates the parameters for a normal distribution n(x) such that exp(n)(x) has the mean and standard deviation given.

Used in LognormalTransform().

memo(f)[source]#

my_lincomb(terms, factors)[source]#

my_lincomb_simple(terms, factors)[source]#

my_product(iterable)[source]#

my_sum(iterable)[source]#

parse_spaces(spaces, nspc)[source]#

safe_cast(tfunc, val)[source]#

special_add_at(a, axis, index, b)[source]#

value_reshaper(x, N)[source]#: Produce arrays of shape (N,). If x is a scalar or array of length one, fill the target array with it. If x is an array, check if it has the right shape.