dispel.data.raw module#

A module containing models for raw data sets.

dispel.data.raw.ACCELEROMETER_COLUMNS = ['userAccelerationX', 'userAccelerationY', 'userAccelerationZ']#: Column ids of the accelerometer sensor

dispel.data.raw.DEFAULT_COLUMNS = ['x', 'y', 'z']#: Default columns ids for sensors

exception dispel.data.raw.EmptyDataError[source]#

Bases: ValueError

Exception raised when a pandas dataframe is empty.

Parameters:: message – An optional message.

__init__(message=None)[source]#

Parameters:: message (str | None) –

dispel.data.raw.GRAVITY_COLUMNS = ['gravityX', 'gravityY', 'gravityZ']#: Column ids of the gravity sensor

exception dispel.data.raw.MissingColumnError[source]#

Bases: ValueError

Exception raised when a pandas dataframe is missing required column(s).

Parameters:

columns – The set of the missing column names.
message – An optional message.

__init__(columns, message=None)[source]#

Parameters:

columns (Iterable[str]) –
message (str | None) –

dispel.data.raw.PRESSURE_MAX = 6.666666666666667#: Max pressure in screen measurements

dispel.data.raw.PRESSURE_VALIDATOR = <RangeValidator: [0, 6.666666666666667]>#

A validator for pressure in screen measurements

Parameters:: value (Any) –

class dispel.data.raw.RawDataSet[source]#

Bases: FlagMixIn

A raw data set.

Parameters:

definition – The definition of the raw data set
data – The data set

__init__(definition, data)[source]#

Parameters:

definition (RawDataSetDefinition) –
data (DataFrame) –

concat(other)[source]#

Concatenate two raw data sets.

Parameters:: other (RawDataSet) –
Return type:: RawDataSet

property id: str#: Get the identifier from the definition of the raw data set.

class dispel.data.raw.RawDataSetDefinition[source]#

Bases: object

The definition of a raw data set.

__init__(id, source, value_definitions_list, is_computed=False)#

Parameters:

id (str) –
source (RawDataSetSource) –
value_definitions_list (dataclasses.InitVar[Iterable[dispel.data.raw.RawDataValueDefinition]]) –
is_computed (bool) –

Return type:

None

get_value_definition(id_)[source]#

Get a value definition.

Parameters:: id_ (DefinitionId) –

id: str#: The identifier of the raw data set definition

is_computed: bool = False#: True if the raw data source is computed. False if it is a measured source without transformation, e.g. acceleration recorded from the low level APIs.

source: RawDataSetSource#: The source of the raw data set

property value_definitions#: Get the value definitions of the raw data set.

value_definitions_list: dataclasses.InitVar[Iterable[dispel.data.raw.RawDataValueDefinition]]#

class dispel.data.raw.RawDataSetSource[source]#

Bases: object

The source of a raw data set.

__init__(manufacturer)#

Parameters:: manufacturer (str) –
Return type:: None

manufacturer: str#: The manufacturer producing the raw data set source

class dispel.data.raw.RawDataValueDefinition[source]#

Bases: ValueDefinition

The definition of raw data set values.

is_index#: True if the values are part of the raw data set index. Otherwise, False.

__init__(id_, name, unit=None, description=None, data_type=None, precision=None, is_index=False)[source]#

Parameters:

id_ (str) –
name (str) –
unit (str | None) –
description (str | None) –
data_type (str | None) –
precision (int | None) –
is_index (bool) –

class dispel.data.raw.SensorType[source]#

Bases: str, Enum

Abstract class for sensor type.

dispel.data.raw.USER_ACC_MAP = {'ts': 'ts', 'userAccelerationX': 'x', 'userAccelerationY': 'y', 'userAccelerationZ': 'z'}#: Map user acceleration columns