PlasmaCalcs.dimensions.behavior.Behavior

class PlasmaCalcs.dimensions.behavior.Behavior(arg0=UNSET, dims=None, **kw)

Bases: dict

dict with ‘compatible’ method.

__getitem__ altered to include values from self.dims, and ‘dims’ itself.

e.g. self[‘dims’] == self.dims; self[‘fluid’] –> self.dims[‘fluid’], if possible.

__contains__ altered to include values from self.dims.

e.g. ‘fluid’ in self –> fluid in self.keys() or fluid in self.dims

arg0: object

first argument to pass to dict() constructor.

dims: None or dict

dict of dimension values for this behavior.

if None, use empty dict.

remaining **kw are passd to dict() constructor

__init__(arg0=UNSET, dims=None, **kw)

initialize Behavior.

Methods

__init__([arg0, dims])
assign_attrs(array)
assign_nondefault_attrs(array[, ql, include_xr])
clear()
compatible(other, *[, lenient, subdims])
copy(*[, keys])
default_keys([ql])
fromkeys([value])
get(key[, default])
items()
keys()
label_array(array, *[, skip])
nondefault([ql, include_xr])
nondefault_keys([ql, include_xr])
pop(k[,d])
popitem()
setdefault(key[, default])
update([E, ]**F)
values()

assign_attrs(array)

return copy of array with self keys & vals (but not dims) assigned as attrs.

if any were already attrs of array, crash if value mismatch.

See also: assign_nondefault_attrs

assign_nondefault_attrs(array, ql=None, *, include_xr=True)

return copy of array with self.nondefault() keys & vals (but not dims) assigned as attrs.

if any were already attrs of array, crash if value mismatch.

ql: None or BehaviorHaver

if provided, used to evaluate some defaults (anything defined with getdefault)

e.g. for stat_dims, getdefault = lambda ql: getattr(ql, ‘maindims’, []).

include_xr: bool

whether to include keys whose values are xarray objects (DataArray or Dataset).

See also: assign_attrs

clear() → None.  Remove all items from D.

compatible(other, *, lenient=False, subdims=False)

return whether self and other are compatible.

‘compatible’ when self[key] == other[key] for all keys in self (and self.dims).

only tests keys in self; other can have more keys than those in self.

lenient: bool

whether to only test keys which are in both self and other.

if False, and other is missing any keys in self, return False.

subdims: bool

whether to be compatible if dim from self is a value within dim from other.

when True, if only compatible due to subdims, return list of dims which are subdims.

E.g., self = dict(fluid=1, snap=0), other = dict(fluid=[0,1,2,3], snap=0) –>

subdims=True –> compatible; result will be [‘fluid’]

subdims=False –> not compatible.

To check whether other dim is a “list” of values, use is_iterable_dim(other_val)

copy(*, keys=None)

return a copy of self, including a copy of self.dims.

keys: None or iterable

if provided, the copy will include keys only from this list.

(either way, the copy will include a full copy of self.dims.)

default_keys(ql=None)

return list of keys in self with key.is_default(value, ql=ql)

Does not consider self.dims.

ql: None or BehaviorHaver

if provided, used to evaluate some defaults (anything defined with getdefault)

e.g. for stat_dims, getdefault = lambda ql: getattr(ql, ‘maindims’, []).

fromkeys(value=None, /)

Create a new dictionary with keys from iterable and values set to value.

get(key, default=None, /)

Return the value for key if key is in the dictionary, else default.

items() → a set-like object providing a view on D's items

keys() → a set-like object providing a view on D's keys

label_array(array, *, skip=UNSET)

label array with coords from self.dims, attrs from self.items().

Requires that values of self.dims are all non-iterable, according to is_iterable_dim().

skip: None, UNSET, or list of strs

skip these attrs, if provided.

UNSET –> skip DEFAULTS.SKIP_BEHAVIOR_ARRAY_LABELS

(default [])

None –> don’t skip anything.

nondefault(ql=None, *, include_xr=True)

returns Behavior like self but dropping all keys with key.is_default(value, ql=ql).

Note: these are the keys which MIGHT not have default values;

result includes keys where default was unknown and unchecked.

ql: None or BehaviorHaver

if provided, used to evaluate some defaults (anything defined with getdefault)

e.g. for stat_dims, getdefault = lambda ql: getattr(ql, ‘maindims’, []).

include_xr: bool

whether to include keys whose values are xarray objects (DataArray or Dataset).

‘only’ –> instead return a dict of only keys whose values are xarray objects (& not default).

nondefault_keys(ql=None, *, include_xr=True)

return list of keys in self with NOT key.is_default(value, ql=ql).

Does not consider self.dims.

ql: None or BehaviorHaver

if provided, used to evaluate some defaults (anything defined with getdefault)

e.g. for stat_dims, getdefault = lambda ql: getattr(ql, ‘maindims’, []).

include_xr: bool or ‘only’

whether to include keys whose values are xarray objects (DataArray or Dataset).

‘only’ –> instead return only keys whose values are xarray objects (& not default).

pop(k[, d]) → v, remove specified key and return the corresponding value.

If key is not found, default is returned if given, otherwise KeyError is raised

popitem()

Remove and return a (key, value) pair as a 2-tuple.

Pairs are returned in LIFO (last-in, first-out) order.

Raises KeyError if the dict is empty.

setdefault(key, default=None, /)

Insert key with a value of default if key is not in the dictionary.

Return the value for key if key is in the dictionary, else default.

update([E, ]**F) → None.  Update D from dict/iterable E and F.

If E is present and has a .keys() method, then does: for k in E: D[k] = E[k]

If E is present and lacks a .keys() method, then does: for k, v in E: D[k] = v

In either case, this is followed by: for k in F: D[k] = F[k]

values() → an object providing a view on D's values