Base classes

class thermoextrap.core._attrs_utils.MyAttrsMixin

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().
set_params(**kws)	Set parameters of self, and return self (for chaining).

asdict()

Convert object to dictionary.

new_like(**kws)

Create a new object with optional parameters.

Parameters:

**kws – attribute, value pairs.

assign(**kws)

Alias to new_like().

set_params(**kws)

Set parameters of self, and return self (for chaining).

class thermoextrap.models.PiecewiseMixin

Bases: object

Provide methods for Piecewise state collection.

class thermoextrap.models.SymDerivBase(func, args=None, expand=True, post_func=None)

Bases: object

Base class for working with recursive derivatives in expansions.

Parameters:

• func (Function) – Function to differentiate. This should (most likely) be an instance of thermoextrap.models.SymFuncBase

• args (sequence of Symbol) – Arguments to func

• expand (bool) – If True, apply expand()

• post_func (str or callable()) – Transformation of base function. For example, post_fuc = -sympy.log is equivalent to passing minus_log=True If a string, then apply the following standard functions

  • minus_log : post_func = -sympy.log

  • pow_i : post_func = lambda f: pow(f, i). E.g., pow_2 => pow(f, 2)

class thermoextrap.models.SymFuncBase(beta)

Bases: Function

Base class to define a sympy function for user defined deriatives.

See also

thermoextrap.models.SymDerivBase

Methods:

deriv_args()	Symbol arguments of function.
fdiff([argindex])	Derivative of function.
eval(beta)	Evaluate function.

classmethod deriv_args()

Symbol arguments of function.

This is used by Data class to create a ‘lambdfied’ callable function.

See also

sympy.utilities.lambdify.lambdify

fdiff(argindex=1)

Derivative of function. This will be used by thermoextrap.models.SymDerivBase.

classmethod eval(beta)

Evaluate function.

We use the convention of passing in beta=’None’ to evaluate the function to an indexed variable.

class thermoextrap.data.AbstractData(*, meta)

Bases: MyAttrsMixin

Abstract class for data.

Attributes:

meta	Callback
central	Whether central (True) or raw (False) moments are used.
derivs_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.
set_params(**kws)	Set parameters of self, and return self (for chaining).

meta

Callback

abstract property central

Whether central (True) or raw (False) moments are used.

abstract property derivs_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()

Convert object to dictionary.

assign(**kws)

Alias to new_like().

new_like(**kws)

Create a new object with optional parameters.

Parameters:

**kws – attribute, value pairs.

set_params(**kws)

Set parameters of self, and return self (for chaining).

class thermoextrap.data.DataCentralMomentsBase(dxduave, *, meta, umom_dim='umom', xmom_dim='xmom', rec_dim='rec', deriv_dim=None, central=False, x_is_u=None)

Bases: AbstractData

Data object based on central co-moments array.

Parameters:

• dxduave (xCentralMoments) – Central moments object.

• rec_dim (hashable, optional) – 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 derivs_args. Values passed through method resample_meta

• x_is_u (bool, default False) – if True, treat xv = uv and do adjust u/du accordingly

Attributes:

dxduave	cmomy.xCentralMoments object
umom_dim	Energy moment dimension
xmom_dim	Overvable moment dimension
rec_dim	Records dimension
deriv_dim	Derivative with respect to alpha dimension
central	Whether central or raw moments are used
x_is_u	Whether observable x is same as energy u
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.
derivs_args	Arguments to be passed to derivative function.
meta	Callback
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.
set_params(**kws)	Set parameters of self, and return self (for chaining).

dxduave

cmomy.xCentralMoments object

umom_dim

Energy moment dimension

xmom_dim

Overvable moment dimension

rec_dim

Records dimension

deriv_dim

Derivative with respect to alpha dimension

central

Whether central or raw moments are used

x_is_u

Whether observable x is same as energy u

property order

Order of expansion.

property values

Data underlying dxduave.

See also

cmomy.xCentralMoments.values

rmom()

Raw co-moments.

cmom()

Central co-moments.

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.

property derivs_args

Arguments to be passed to derivative function.

For example, derivs(*self.derivs_args).

asdict()

Convert object to dictionary.

assign(**kws)

Alias to new_like().

meta

Callback

new_like(**kws)

Create a new object with optional parameters.

Parameters:

**kws – attribute, value pairs.

set_params(**kws)

Set parameters of self, and return self (for chaining).

property xalpha

Whether X has explicit dependence on alpha.

That is, if self.deriv_dim is not None

class thermoextrap.data.DataValuesBase(uv, xv, order, *, meta, rec_dim='rec', umom_dim='umom', deriv_dim=None, skipna=False, chunk=None, compute=None, build_aves_kws=None, x_is_u=False)

Bases: AbstractData

Base class to work with data based on values (non-cmomy).

Parameters:

• uv (xarray.DataArray) – raw values of u (energy)

• xv (xarray.DataArray) – raw values of x (observable)

• order (int) – maximum order of moments/expansion to calculate

• rec_dim (hashable, optional) – Name of dimension for ‘records’, i.e., multiple observations.

• umom_dim (str, default 'umom') – Name of dimension for moment of energy u.

• 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

• skipna (bool, default False) – if True, skip nan values

• chunk (bool, optional) – chunking of xarray objects

• compute (bool, optional) – whether to perform compute step on xarray outputs

• 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 derivs_args. Values passed through method resample_meta

• x_is_u (bool, default False) – if True, treat xv = uv and do adjust u/du accordingly

Attributes:

uv	Energy values
xv	Obervable values
order	Expansion order
rec_dim	Records dimension
umom_dim	Energy moments dimension
deriv_dim	Derivative dimension
skipna	Whether to skip NAN values
chunk	Whether to chunk the xarray objects
compute	Whether to compute the chunked data
build_aves_kws	Arguments to building the averages
x_is_u	Whether the observable x is the same as energy u
central	Whether central (True) or raw (False) moments are used.
derivs_args	Sequence of arguments to derivative calculation function.
meta	Callback
xalpha	Whether X has explicit dependence on alpha.

Methods:

from_vals(xv, uv, order[, rec_dim, ...])	Constructor from arrays.
resample([indices, nrep, rep_dim, chunk, ...])	Resample object.
asdict()	Convert object to dictionary.
assign(**kws)	Alias to new_like().
new_like(**kws)	Create a new object with optional parameters.
set_params(**kws)	Set parameters of self, and return self (for chaining).

uv

Energy values

xv

Obervable values

order

Expansion order

rec_dim

Records dimension

umom_dim

Energy moments dimension

deriv_dim

Derivative dimension

skipna

Whether to skip NAN values

chunk

Whether to chunk the xarray objects

compute

Whether to compute the chunked data

build_aves_kws

Arguments to building the averages

x_is_u

Whether the observable x is the same as energy u

classmethod from_vals(xv, uv, order, rec_dim='rec', umom_dim='umom', rep_dim='rep', deriv_dim=None, val_dims='val', skipna=False, chunk=None, compute=None, build_aves_kws=None, meta=None, x_is_u=False)

Constructor from arrays.

Parameters:

• uv (array-like) – raw values of u (energy) if not DataArray, wrap with xrwrap_uv

• xv (xarray.DataArray) – raw values of x (observable) if not DataArray, wrap with xrwrap_xv

• order (int) – maximum order of moments/expansion to calculate

• rec_dim (hashable, optional) – Name of dimension for ‘records’, i.e., multiple observations.

• umom_dim (str, default 'umom') – Name of dimension for moment of energy u.

• val_dims (str or sequence of str) – Names of extra dimensions

• 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

• skipna (bool, default False) – if True, skip nan values

• chunk (bool, optional) – chunking of xarray objects

• 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 derivs_args. Values passed through method resample_meta

• x_is_u (bool, default False) – if True, treat xv = uv and do adjust u/du accordingly

property central

Whether central (True) or raw (False) moments are used.

resample(indices=None, nrep=None, rep_dim='rep', chunk=None, compute='None', meta_kws=None, rng=None)

Resample object.

Parameters:

• indices (array of int, optional) – Array of shape (nrep, size). If passed, create freq from indices. See randsamp_freq().

• nrep (int, optional) – Number of replicates. Create freq with this many replicates. See randsamp_freq()

• rep_dim (hashable, optional) – Name of new ‘replicated’ dimension:

• chunk (bool, optional) – chunking of xarray objects

• compute (bool, optional) – whether to perform compute step on xarray outputs

• meta_kws (mapping, optional) – Optional parameters for meta.

• rng (Generator, optional) – Random number generator object. Defaults to result of cmomy.random.default_rng().

asdict()

Convert object to dictionary.

assign(**kws)

Alias to new_like().

abstract property derivs_args

Sequence of arguments to derivative calculation function.

meta

Callback

new_like(**kws)

Create a new object with optional parameters.

Parameters:

**kws – attribute, value pairs.

set_params(**kws)

Set parameters of self, and return self (for chaining).

property xalpha

Whether X has explicit dependence on alpha.

That is, if self.deriv_dim is not None