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flowmachine.features.subscriber.scores

Source: flowmachine/features/subscriber/scores.py

Calculates an event score for each event based on a scoring dictionary.

Class EventScore

EventScore(*, start: str, stop: str, spatial_unit: Union[flowmachine.core.spatial_unit.CellSpatialUnit, flowmachine.core.spatial_unit.GeomSpatialUnit, NoneType] = None, hours: Union[str, Tuple[int, int]] = 'all', table: Union[str, List[str]] = 'all', score_hour: List[float] = [-1, -1, -1, -1, -1, -1, -1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, -1, -1, -1], score_dow: Dict[str, float] = {'monday': 1, 'tuesday': 1, 'wednesday': 1, 'thursday': 0, 'friday': -1, 'saturday': -1, 'sunday': -1}, subscriber_identifier: str = 'msisdn', subscriber_subset=None)
Source: flowmachine/features/subscriber/scores.py

Represents an event score class. This class assigns a score to each event based on the hour of the day and the day of the week. The scores can be useful to cluster a set of events based on its signature. Such type of analysis reduces the dimensionality of the problem by projecting a given event pattern onto the real line. This class returns a table with scores averaged across the requested spatial unit per subscriber.

Attributes

Parameters

  • score_hour: typing.List[float], default [-1, -1, -1, -1, -1, -1, -1, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, -1, -1, -1]

    A length 24 list containing numerical scores between -1 and 1, where entry 0 is midnight.

  • score_dow: typing.Dict[str, float], default {'monday': 1, 'tuesday': 1, 'wednesday': 1, 'thursday': 0, 'friday': -1, 'saturday': -1, 'sunday': -1}

    A dictionary containing a key for every day of the week, and a numerical score between zero and 1. Keys should be the lowercase, full name of the day.

  • start: str

    iso format date range for the beginning of the time frame, e.g. 2016-01-01 or 2016-01-01 14:03:01

  • stop: str

    As above

  • spatial_unit: typing.Union[flowmachine.core.spatial_unit.CellSpatialUnit, flowmachine.core.spatial_unit.GeomSpatialUnit, NoneType], default None

    Spatial unit to which subscriber locations will be mapped. See the docstring of make_spatial_unit for more information.

  • hours: typing.Union[str, typing.Tuple[int, int]], default all

    Subset the result within certain hours, e.g. (4,17) This will subset the query only with these hours, but across all specified days. Or set to 'all' to include all hours.

  • table: typing.Union[str, typing.List[str]], default all

    schema qualified name of the table which the analysis is based upon.

  • subscriber_identifier: str, default msisdn

    Either msisdn, or imei, the column that identifies the subscriber.

  • subscriber_subset: flowmachine.core.Table, flowmachine.core.Query, list, str, default None

    If provided, string or list of string which are msisdn or imeis to limit results to; or, a query or table which has a column with a name matching subscriber_identifier (typically, msisdn), to limit results to.

Examples

es = EventScore(start='2016-01-01', stop='2016-01-05',
            spatial_unit=make_spatial_unit('versioned-site'))
es.head()
             subscriber location_id  version  score_hour  score_dow
3EgqzplqPYDyGRVK      DbWg4K        0         0.0       -1.0
G2DQzae1qOa48jK9      EyZykQ        0         1.0       -1.0
148ZaRZe54wPGQ9r      nWM8R3        0        -1.0       -1.0
QrAlXqDbXDkNJe3E      pdVVV4        0         1.0        0.0
kjGXLy9lWnZ4V6J7      r9KbQy        0         0.0        1.0
...

Methods

cache

cache
Source: flowmachine/core/query.py

Returns

  • bool

    True is caching is switched on.

column_names

column_names
Source: flowmachine/features/subscriber/scores.py

Returns the column names.

Returns

  • typing.List[str]

    List of the column names of this query.

column_names_as_string_list

column_names_as_string_list
Source: flowmachine/core/query.py

Get the column names as a comma separated list

Returns

  • str

    Comma separated list of column names

dependencies

dependencies
Source: flowmachine/core/query.py

Returns

  • set

    The set of queries which this one is directly dependent on.

fully_qualified_table_name

fully_qualified_table_name
Source: flowmachine/core/query.py

Returns a unique fully qualified name for the query to be stored as under the cache schema, based on a hash of the parameters, class, and subqueries.

Returns

  • str

    String form of the table's fqn

index_cols

index_cols
Source: flowmachine/core/query.py

A list of columns to use as indexes when storing this query.

Returns

  • ixen: list

    By default, returns the location columns if they are present and self.spatial_unit is defined, and the subscriber column.

Examples
daily_location("2016-01-01").index_cols
[['name'], '"subscriber"']

is_stored

is_stored
Source: flowmachine/core/query.py

Returns

  • bool

    True if the table is stored, and False otherwise.

query_id

query_id
Source: flowmachine/core/query.py

Generate a uniquely identifying hash of this query, based on the parameters of it and the subqueries it is composed of.

Returns

  • str

    query_id hash string

query_state

query_state
Source: flowmachine/core/query.py

Return the current query state.

Returns

  • QueryState

    The current query state

query_state_str

query_state_str
Source: flowmachine/core/query.py

Return the current query state as a string

Returns

  • str

    The current query state. The possible values are the ones defined in flowmachine.core.query_state.QueryState.

table_name

table_name
Source: flowmachine/core/query.py

Returns a uniquename for the query to be stored as, based on a hash of the parameters, class, and subqueries.

Returns

  • str

    String form of the table's fqn