tom package

Submodules

tom.cli module

Console script for TOM. Not yet functional!

tom.config module

tom.config.output_dir() → pathlib.Path

tom.config.output_file(filename: str, subdir: str = '.', suffix: str = '') → pathlib.Path

tom.plot module

tom.plot.annotate_train_run(ax: matplotlib.axes._axes.Axes, tr: tom.tom.TrainRun)

tom.plot.get_color_for_section(section)

tom.plot.plot_graph(g: networkx.classes.digraph.DiGraph)

tom.plot.plot_train(t: tom.tom.Train, no_of_runs=-1, plot_all=True, all_stations=None)

tom.tom module

This module defines the TOM domain model. The main classes are:

• A Train defines a set of planned TrainRuns which consist of a sequence of

• SectionRun. A SectionRun belongs to exactly one

• RouteSection, which has a planned calendar of days the SectionsRuns start. A RouteSection is managed by exactly one railway undertaking (RU) and one infrastructure manager (IM).

• Each ‘TrainRun` must run exactly once on each location (departure_station, arrival_station) of the train.

class tom.tom.LocationIdGenerator

Bases: object

location_last = 9999

location_name_to_code = {'A': 10000, 'AC': 10007, 'B': 10001, 'C': 10002, 'D': 10003, 'E': 10011, 'EEM': 10015, 'EMM': 10008, 'F': 10012, 'FF': 10009, 'G': 10013, 'H1': 10005, 'RXBA': 10016, 'S': 10004, 'T': 10006, 'Venlo': 10010, 'XNAC': 10014, 'XNU': 10018, 'XNVL': 10019, 'XSZH': 10017}

map_location_name_to_code(name: str) → str

class tom.tom.Route(sections: List[tom.tom.RouteSection])

Bases: object

A Route is a sequence of RouteSection where consecutive section must fit together:

If (prev, next) is a tuple in the sections, then

prev.arrival_station == next.departure_station

NOTE: The here proposed TOM model does not need routes! They are instead modeled as TrainRuns which are computed from RouteSection (see Train.train_run_iterator)

add_date(d: str)

calendar: pandas.core.indexes.datetimes.DatetimeIndex = DatetimeIndex([], dtype='datetime64[ns]', freq=None)

description(with_bitmap=True) → str

first_day()

journey_location_iter()

last_day()

route_key()

sections: List[RouteSection] = None

to_xml(parent: xml.etree.ElementTree.Element)

class tom.tom.RouteSection(departure_station: str, arrival_station: str, travel_time: datetime.timedelta, calendar: pandas.core.indexes.datetimes.DatetimeIndex, departure_daytime: pandas._libs.tslibs.timedeltas.Timedelta = None, stop_time: datetime.timedelta = Timedelta('0 days 00:00:00'))

Bases: object

Section of a route of a train which belongs to exactly one responsible IM and applicant RU.

The departure_times define the calendar of the SectionRuns of this RouteSection. The date part of these timestamps are the calender days of the train is running is this section.

adjust_calendar_to_timestamps()

arrival_station: str = None

arrival_time() → pandas._libs.tslibs.timestamps.Timestamp

Returns

Timestamp the first train run arrives at section station of arrival

arrival_time_offset() → int

Returns

Offset in days of arrival relativ to departure time (must be positiv)

arrival_times() → pandas.core.indexes.datetimes.DatetimeIndex

The arrival times are computed from section departure times + travel time.

calendar: pandas.core.indexes.datetimes.DatetimeIndex = None

can_connect_to(other) → bool

check_invariant()

color: str = None

complete_calender_from_predecessor(pred)

complete_calender_from_successor(succ)

complete_from_predecessor(pred)

complete_from_successor(succ)

departure_daytime: datetime.timedelta = None

departure_station: str = None

departure_stop_time: timedelta = None

departure_time() → pandas._libs.tslibs.timestamps.Timestamp

Returns

Timestamp the first train run departs from section departure_station

departure_times_from_predecessor(pred) → pandas.core.indexes.datetimes.DatetimeIndex

departure_timestamps: pandas.core.indexes.datetimes.DatetimeIndex = DatetimeIndex([], dtype='datetime64[ns]', freq=None)

departures_times_from_successor(succ)

description(with_bitmap=True) → str

first_day() → datetime.date

Returns

Calendar day of the first train run in this section.

is_complete()

is_construction_start: bool = False

is_section_complete: bool = False

last_day() → datetime.date

Returns

Calendar day of the last train run in this section.

route_id()

section_id: str = '00'

section_key()

A section of a train is uniquely identified by this quadruple:

((departure_station, departure time), (arrival_station, arrival time))

Returns

unique key among all sections of a train

successors: List[str] = []

to_dataframe() → pandas.core.frame.DataFrame

Returns

pandas dataframe with three columns for [section_id, departure_station, arrival_station] and one row for each section run.

to_xml(root: xml.etree.ElementTree.Element)

train = None

travel_time: timedelta = None

validity()

version: int = 1

version_info()

xml_add_id(parent: xml.etree.ElementTree.Element)

class tom.tom.SectionRun(section: tom.tom.RouteSection, time: datetime.datetime)

Bases: object

arrival_at_departure_station() → datetime.datetime

Returns

the timestamp when the train will arrive in the departure station

result = departure_time - departure_stop_time

arrival_column() → str

arrival_formatted() → str

arrival_station() → str

arrival_time() → datetime.datetime

block_timedelta() → datetime.timedelta

connects_to(other)

Checks if to two section self and other fit together`. This is only if

(self.arrival_station(), self.arrival_time())

= [other.departure_station(), other.arrival_at_departure_station())

Parameters

other – SectionRun

Returns

True if both section fit together.

departure_column() → str

departure_formatted() → str

departure_station() → str

departure_time: datetime = None

-1: < RCS 0: = RCS +1: > RCS

otr_at_arrival()

otr_at_departure()

section: RouteSection = None

section_id()

class tom.tom.SingleSource

Bases: object

Used as sentinel object in Train.extended_train_run_graph.

See also

https://www.revsys.com/tidbits/sentinel-values-python/

class tom.tom.SingleTarget

Bases: object

tom.tom.TSI_SCHEMA_VERSION = '2.3.0'

New Schema version proposed for change of element TrainInformation

exception tom.tom.TomError

Bases: ValueError

Constraint violation in the TOM Model are signalled using this error

class tom.tom.Train(core_id: str, sections: List[tom.tom.RouteSection])

Bases: object

all_stations() → List[str]

Returns

list of all stations of the train

basic_section_graph() → networkx.classes.digraph.DiGraph

calender()

core_id: str = None

extended_train_run_graph(use_sections=True) → networkx.classes.digraph.DiGraph

id()

id_to_sec: Dict[str, tom.tom.RouteSection] = {10: <tom.tom.RouteSection object>, 11: <tom.tom.RouteSection object>, 12: <tom.tom.RouteSection object>, 20: <tom.tom.RouteSection object>, 21: <tom.tom.RouteSection object>, 30: <tom.tom.RouteSection object>, 31: <tom.tom.RouteSection object>, 40: <tom.tom.RouteSection object>, 41: <tom.tom.RouteSection object>, 50: <tom.tom.RouteSection object>, 51: <tom.tom.RouteSection object>}

lead_ru: int = 8350

location_graph() → networkx.classes.digraph.DiGraph

routes() → ValuesView[tom.tom.Route]

routing_info_to_xml(schema: str) → xml.etree.ElementTree.Element

section_dataframes() → List[pandas.core.frame.DataFrame]

section_graph() → networkx.classes.digraph.DiGraph

section_run_iterator()

sections: List[tom.tom.RouteSection] = []

timetable_year() → int

Return type

year of departure_time of first section

to_dataframe(format_time=True) → pandas.core.frame.DataFrame

train_id(variant='00') → str

Attention:

in the ECM the variant part is only used to identify TrainRuns, not the train. the TimetableYear is only unique, when the start dates of all RouteSections belong to the TimetableYear. (This is currently not valid for the test examples used. Why? Because it is not necessary, that the TimetableYear should be part of the TrainID)

Returns

Unique ID of this train (LeadRU/CoreID/TimetableYear)

train_run_graph() → networkx.classes.digraph.DiGraph

train_run_iterator()

Iterate over all TrainRuns of this train.

Returns

Iterator[TrainRun]

version: int = None

class tom.tom.TrainRun(t: tom.tom.Train, section_runs: List[tom.tom.SectionRun])

Bases: object

first_run()

location_iterator()

route_key()

sections_runs: List[SectionRun] = None

start_date()

time_table(format_time=True) → Dict[str, str]

time_table_event_iterator()

time_table_event_iterator2()

time_table_events() → Tuple[List[str], List[datetime.datetime]]

train: Train = None

train_id()

tom.tom.compute_bitmap_days(calendar: pandas.core.indexes.datetimes.DatetimeIndex) → str

Parameters

calendar –

Returns

Bitmap string containing 1 and 0

tom.tom.day_offset(departure: datetime.datetime, arrival: datetime.datetime) → int

Return number of night shifts between two timestamps

tom.tom.make_train_from_yml(file: pathlib.PosixPath) → tom.tom.Train

tom.tom.xml_add_calendar(tom_object, parent: xml.etree.ElementTree.Element)

tom.tom.xml_add_journey_location(parent: xml.etree.ElementTree.Element, station: str, t: datetime.datetime, offset: int = 0, type_code=None)

Add XML Element PlannedJourneyLocation

Parameters

• parent – RouteSection

• station – name of destination or arrival

• t – timestamp

• offset – in days to departure

• type_code – JourneyLocationTypeCode (default ist Handover == 04)

tom.tom.xml_simple_element(parent: xml.etree.ElementTree.Element, name: str, text: str = None)

tom.util module

tom.util.dump_routing_info_as_xml(t: tom.tom.Train) → str

tom.util.example(data_dir, pattern)

tom.util.xml_to_string(xml: xml.etree.ElementTree.Element) → str

Module contents

Top-level package for Train Object Model.