sasdata.data_backing module¶

class sasdata.data_backing.DataType¶

Sasdata metadata tree

alias of TypeVar(‘DataType’)

class sasdata.data_backing.Dataset(name: str, data: DataType, attributes: dict[str, Self | str])¶

Bases: Generic

attributes: dict[str, Self | str]¶

data: DataType¶

name: str¶

summary(indent_amount: int = 0, indent: str = ' ') → str¶

class sasdata.data_backing.Function(abscissae: list[NamedQuantity], ordinate: NamedQuantity)¶

Bases: object

Representation of a (data driven) function, such as I vs Q

class sasdata.data_backing.FunctionType(*values)¶

Bases: Enum

What kind of function is this, should not be relied upon to be perfectly descriptive

The functions might be parametrised by more variables than the specification

CORRELATION_FUNCTION_1D = 32¶

CORRELATION_FUNCTION_2D = 33¶

CORRELATION_FUNCTION_3D = 34¶

INTERFACE_DISTRIBUTION_FUNCTION = 35¶

POLARISATION_EFFICIENCY = 22¶

PROBABILITY_DENSITY = 41¶

PROBABILITY_DISTRIBUTION = 40¶

SCATTERING_INTENSITY_VS_ANGLE = 4¶

SCATTERING_INTENSITY_VS_Q = 1¶

SCATTERING_INTENSITY_VS_Q_2D = 2¶

SCATTERING_INTENSITY_VS_Q_3D = 3¶

SESANS = 31¶

TRANSMISSION = 21¶

UNKNOWN = 0¶

UNKNOWN_METADATA = 20¶

UNKNOWN_REALSPACE = 30¶

class sasdata.data_backing.Group(name: str, children: dict[str, Self | sasdata.data_backing.Dataset])¶

Bases: object

children: dict[str, Self | Dataset]¶

name: str¶

summary(indent_amount: int = 0, indent=' ')¶

sasdata.data_backing.build_main_data(data: list[NamedQuantity]) → Function¶

sasdata.data_backing.function_type_identification_key(names)¶: Create a key from the names of data objects that can be used to assign a function type

sasdata.data_backing.key_tree(data: Group | Dataset, indent_amount=0, indent: str = ' ') → str¶: Show a metadata tree, showing the names of they keys used to access them

sasdata.data_backing.shorten_string(string)¶