Base classes

Base classes#

class thermoextrap.core._attrs_utils.MyAttrsMixin[source]#

Bases: object

Baseclass for adding some sugar to attrs.derived classes.

Methods:

`asdict`()	Convert object to dictionary.
`new_like`(**kws)	Create a new object with optional parameters.
`assign`(**kws)	Alias to `new_like()`.

asdict()[source]#: Convert object to dictionary.

new_like(**kws)[source]#

Create a new object with optional parameters.

Parameters:: **kws – attribute, value pairs.

assign(**kws)[source]#: Alias to new_like().

class thermoextrap.data.AbstractData(*, meta=None, umom_dim='umom', deriv_dim=None, x_is_u=False)[source]#

Bases: MyAttrsMixin

Abstract class for data.

Attributes:

`meta`	Callback
`umom_dim`	Energy moments dimension
`deriv_dim`	Derivative dimension
`x_is_u`	Whether the observable x is the same as energy u
`order`	Expansion order.
`central`	Whether central (True) or raw (False) moments are used.
`deriv_args`	Sequence of arguments to derivative calculation function.
`xalpha`	Whether X has explicit dependence on alpha.

Methods:

`asdict`()	Convert object to dictionary.
`assign`(**kws)	Alias to `new_like()`.
`new_like`(**kws)	Create a new object with optional parameters.

meta#: Callback

umom_dim#: Energy moments dimension

deriv_dim#: Derivative dimension

x_is_u#: Whether the observable x is the same as energy u

abstract property order#: Expansion order.

abstract property central#: Whether central (True) or raw (False) moments are used.

abstract property deriv_args#: Sequence of arguments to derivative calculation function.

property xalpha#

Whether X has explicit dependence on alpha.

That is, if self.deriv_dim is not None

asdict()[source]#: Convert object to dictionary.

assign(**kws)[source]#: Alias to new_like().

new_like(**kws)[source]#

Create a new object with optional parameters.

Parameters:: **kws – attribute, value pairs.

class thermoextrap.data.DataCentralMomentsBase(*, meta=None, umom_dim='umom', deriv_dim=None, xmom_dim='xmom', rec_dim='rec', central=False, x_is_u=None, use_cache=True)[source]#

Bases: AbstractData, Generic[DataT]

Data object based on central co-moments array.

Parameters:

dxduave (CentralMomentsData) – Central moments object.
rec_dim (hashable) – Name of dimension for ‘records’, i.e., multiple observations.
umom_dim (str, default 'umom') – Name of dimension for moment of energy u.
xmom_dim (str, default 'xmom') – Name of dimension for moments of observable x.
deriv_dim (str, default None) – if deriv_dim is a string, then this is the name of the derivative dimension and xarray objects will have a derivative
central (bool) – If True, Use central moments. Otherwise, use raw moments.
meta (dict, optional) – extra meta data/parameters to be carried along with object and child objects. if ‘checker’ in meta, then perform a callback of the form meta[‘checker](self, meta) this can also be used to override things like deriv_args. Values passed through method resample_meta
x_is_u (bool, default False) – if True, treat xv = uv and do adjust u/du accordingly
use_cache (bool) – If True (default), cache intermediate result. Speeds up calculations, but can lead to large objects.

Attributes:

`xmom_dim`	Overvable moment dimension
`rec_dim`	Records dimension
`central`	Whether central or raw moments are used
`x_is_u`	Whether observable x is same as energy u
`dxduave`	Wrapped `cmomy.CentralMomentsData` object.
`order`	Order of expansion.
`values`	Data underlying `dxduave`.
`xu`	Averages of form `x * u ** n`.
`u`	Averages of form `u ** n`.
`xave`	Averages of form observable `x`.
`dxdu`	Averages of form `dx * dx ** n`.
`du`	Averages of `du ** n`.
`u_selector`	Indexer for `u_selector[n] = u ** n`.
`xu_selector`	Indexer for `xu_select[n] = x * u ** n`.
`xave_selector`	Selector for `xave`.
`du_selector`	Selector for `du_selector[n] = du ** n`.
`dxdu_selector`	Selector for `dxdu_selector[n] = dx * du ** n`.
`deriv_args`	Arguments to be passed to derivative function.
`deriv_dim`	Derivative dimension
`meta`	Callback
`umom_dim`	Energy moments dimension
`xalpha`	Whether X has explicit dependence on alpha.

Methods:

`rmom`()	Raw co-moments.
`cmom`()	Central co-moments.
`asdict`()	Convert object to dictionary.
`assign`(**kws)	Alias to `new_like()`.
`new_like`(**kws)	Create a new object with optional parameters.

xmom_dim#: Overvable moment dimension

rec_dim#: Records dimension

central#: Whether central or raw moments are used

x_is_u#: Whether observable x is same as energy u

property dxduave#: Wrapped cmomy.CentralMomentsData object.

property order#: Order of expansion.

property values#: Data underlying dxduave.

See also

cmomy.CentralMomentsData.obj

rmom()[source]#: Raw co-moments.

cmom()[source]#: Central co-moments.

xu[source]#: Averages of form x * u ** n.

u[source]#: Averages of form u ** n.

xave[source]#: Averages of form observable x.

dxdu[source]#: Averages of form dx * dx ** n.

du[source]#: Averages of du ** n.

u_selector[source]#: Indexer for u_selector[n] = u ** n.

xu_selector[source]#: Indexer for xu_select[n] = x * u ** n.

xave_selector[source]#: Selector for xave.

du_selector[source]#: Selector for du_selector[n] = du ** n.

dxdu_selector[source]#: Selector for dxdu_selector[n] = dx * du ** n.

property deriv_args#

Arguments to be passed to derivative function.

For example, derivs(*self.deriv_args).

asdict()[source]#: Convert object to dictionary.

assign(**kws)[source]#: Alias to new_like().

deriv_dim#: Derivative dimension

meta#: Callback

new_like(**kws)[source]#

Create a new object with optional parameters.

Parameters:: **kws – attribute, value pairs.

umom_dim#: Energy moments dimension

property xalpha#

Whether X has explicit dependence on alpha.

That is, if self.deriv_dim is not None

Base classes

Contents

Base classes#