pDESy.model package

Submodules

pDESy.model.base_component module

base_component.

class pDESy.model.base_component.BaseComponent(name=None, ID=None, child_component_id_set=None, targeted_task_id_set=None, space_size=None, parent_product_id=None, state=BaseComponentState.NONE, state_record_list=None, placed_workplace_id=None, placed_workplace_id_record_list=None, error_tolerance=None, error=None)

Bases: object

BaseComponent.

BaseComponent class for expressing target product. This class can be used as template.

add_child_component(child_component: BaseComponent) → None

Add child component to child_component_id_set.

Parameters:

child_component (BaseComponent) – BaseComponent which is child of this component.

add_targeted_task(targeted_task: BaseTask) → None

Add targeted task to targeted_task_list.

Parameters:

targeted_task (BaseTask) – Targeted task of this component.

append_child_component(child_component: BaseComponent) → None

Append child component to child_component_id_set.

Deprecated since version Use: add_child_component instead.

Parameters:

child_component (BaseComponent) – BaseComponent which is child of this component.

append_targeted_task(targeted_task: BaseTask) → None

Append targeted task to targeted_task_list.

Deprecated since version Use: add_targeted_task instead.

Parameters:

targeted_task (BaseTask) – Targeted task of this component.

create_task(name=None, ID=None, default_work_amount=None, work_amount_progress_of_unit_step_time=None, input_task_id_dependency_set=None, allocated_team_id_set=None, allocated_workplace_id_set=None, parent_workflow_id=None, workplace_priority_rule=WorkplacePriorityRuleMode.FSS, worker_priority_rule=ResourcePriorityRuleMode.MW, facility_priority_rule=ResourcePriorityRuleMode.SSP, need_facility=False, default_progress=None, due_time=None, auto_task=False, fixing_allocating_worker_id_set=None, fixing_allocating_facility_id_set=None, est=0.0, eft=0.0, lst=-1.0, lft=-1.0, remaining_work_amount=None, remaining_work_amount_record_list=None, state=BaseTaskState.NONE, state_record_list=None, allocated_worker_facility_id_tuple_set=None, allocated_worker_facility_id_tuple_set_record_list=None, additional_work_amount=None, additional_task_flag=False, actual_work_amount=None)

Create a new BaseTask instance and add it to the targeted tasks.

Parameters:

• name (str, optional) – Name of this task. Defaults to None -> “New Task”.

• ID (str, optional) – ID will be defined automatically. Defaults to None -> str(uuid.uuid4()).

• default_work_amount (float, optional) – Default workamount of this BaseTask. Defaults to None -> 10.0.

• work_amount_progress_of_unit_step_time (float, optional) – Baseline of work amount progress of unit step time. Default to None -> 1.0.

• input_task_id_dependency_set (set(tuple(str, BaseTaskDependency)), optional) – Set of input BaseTask id and type of dependency(FS, SS, SF, F/F) tuple. Defaults to None -> set().

• allocated_team_id_set (set[str], optional) – Set of allocated BaseTeam id. Defaults to None -> set().

• allocated_workplace_id_set (set[str], optional) – Set of allocated BaseWorkplace id. Defaults to None -> set().

• parent_workflow_id (str, optional) – Parent workflow id. Defaults to None.

• workplace_priority_rule (WorkplacePriorityRuleMode, optional) – Workplace priority rule for simulation. Defaults to WorkplacePriorityRuleMode.FSS.

• worker_priority_rule (ResourcePriorityRule, optional) – Worker priority rule for simulation. Defaults to ResourcePriorityRule.SSP.

• facility_priority_rule (ResourcePriorityRule, optional) – Task priority rule for simulation. Defaults to TaskPriorityRule.TSLACK.

• need_facility (bool, optional) – Whether one facility is needed for performing this task or not. Defaults to False.

• default_progress (float, optional) – Progress before starting simulation (0.0 ~ 1.0). Defaults to None -> 0.0.

• due_time (int, optional) – Defaults to None -> int(-1).

• auto_task (bool, optional) – If True, this task is performed automatically even if there are no allocated workers. Defaults to False.

• fixing_allocating_worker_id_set (set[str], optional) – Allocating worker ID set for fixing allocation in simulation. Defaults to None.

• fixing_allocating_facility_id_set (set[str], optional) – Allocating facility ID set for fixing allocation in simulation. Defaults to None.

• est (float, optional) – Earliest start time of CPM. This will be updated step by step. Defaults to 0.0.

• eft (float, optional) – Earliest finish time of CPM. This will be updated step by step. Defaults to 0.0.

• lst (float, optional) – Latest start time of CPM. This will be updated step by step. Defaults to -1.0.

• lft (float, optional) – Latest finish time of CPM. This will be updated step by step. Defaults to -1.0.

• remaining_work_amount (float, optional) – Remaining workamount in simulation. Defaults to None -> default_work_amount * (1.0 - default_progress).

• remaining_work_amount_record_list (List[float], optional) – Record of remaining workamount in simulation. Defaults to None -> [].

• state (BaseTaskState, optional) – State of this task in simulation. Defaults to BaseTaskState.NONE.

• state_record_list (List[BaseTaskState], optional) – Record list of state. Defaults to None -> [].

• allocated_worker_facility_id_tuple_set (set(tuple(str, str)), optional) – State of allocating worker and facility id tuple set in simulation. Defaults to None -> set().

• allocated_worker_facility_id_tuple_set_record_list (List[set[tuple(str, str)]], optional) – State of allocating worker and facility id tuple set in simulation. Defaults to None -> [].

• additional_work_amount (float, optional) – Advanced parameter. Defaults to None.

• additional_task_flag (bool, optional) – Advanced variable. Defaults to False.

• actual_work_amount (float, optional) – Advanced variable. Default to None -> default_work_amount*(1.0-default_progress)

Returns:

Created BaseTask instance.

Return type:

BaseTask

export_dict_json_data()

Export the information of this component to JSON data.

Returns:

JSON format data.

Return type:

dict

extend_child_component_list(child_component_list: list[BaseComponent]) → None

Extend the list of child components.

Deprecated since version Use: update_child_component_set instead.

Parameters:

child_component_list (List[BaseComponent]) – List of BaseComponents which are children of this component.

extend_targeted_task_list(targeted_task_list: list[BaseTask]) → None

Extend the list of targeted tasks to targeted_task_list.

Deprecated since version Use: update_targeted_task_set instead.

Parameters:

targeted_task_list (List[BaseTask]) – List of targeted tasks.

get_gantt_mermaid_data(range_time: tuple[int, int] = (0, 9223372036854775807), view_ready: bool = False, detailed_info: bool = False, id_name_dict: dict[str, str] = None) → list[str]

Get gantt mermaid data of this component.

Parameters:

• range_time (tuple[int, int], optional) – Range time of gantt chart. Defaults to (0, sys.maxsize).

• view_ready (bool, optional) – If True, ready tasks are included in gantt chart. Defaults to False.

• detailed_info (bool, optional) – If True, detailed information is included in gantt chart. Defaults to False.

• id_name_dict (dict[str, str], optional) – Dictionary of ID and name for detailed information. Defaults to None.

Returns:

List of lines for gantt mermaid diagram.

Return type:

list[str]

get_mermaid_diagram(shape: str = 'odd', subgraph: bool = False, subgraph_name: str = 'Component', subgraph_direction: str = 'LR') → list[str]

Get mermaid diagram of this component.

Parameters:

• shape (str, optional) – Shape of mermaid diagram. Defaults to “odd”.

• subgraph (bool, optional) – Subgraph or not. Defaults to False.

• subgraph_name (str, optional) – Subgraph name. Defaults to “Component”.

• subgraph_direction (str, optional) – Direction of subgraph. Defaults to “LR”.

Returns:

List of lines for mermaid diagram.

Return type:

list[str]

get_time_list_for_gantt_chart(finish_margin: float = 1.0) → tuple[list[tuple[int, int]], list[tuple[int, int]]]

Get ready/working time_list for drawing Gantt chart.

Parameters:

finish_margin (float, optional) – Margin of finish time in Gantt chart. Defaults to 1.0.

Returns:

(ready_time_list, working_time_list)

• ready_time_list (List[tuple(int, int)]): ready_time_list including start_time, length

• working_time_list (List[tuple(int, int)]): working_time_list including start_time, length

Return type:

tuple

initialize(state_info: bool = True, log_info: bool = True) → None

Initialize the following changeable basic variables of BaseComponent.

If state_info is True, the following attributes are initialized:

• state

• placed_workplace

• error

If log_info is True, the following attributes are initialized:

• state_record_list

• placed_workplace_id_record_list

Parameters:

• state_info (bool, optional) – State information are initialized or not. Defaults to True.

• log_info (bool, optional) – Log information are initialized or not. Defaults to True.

insert_absence_time_list(absence_time_list: list[int]) → None

Insert record information on absence_time_list.

Parameters:

absence_time_list (List[int]) – List of absence step time in simulation.

print_all_log_in_chronological_order(backward: bool = False) → None

Print all log in chronological order.

Parameters:

backward (bool, optional) – If True, print in reverse order. Defaults to False.

print_log(target_step_time: int) → None

Print log in target_step_time.

Prints:

• ID

• name

• state_record_list[target_step_time]

• placed_workplace_id_record_list[target_step_time]

Parameters:

target_step_time (int) – Target step time of printing log.

print_mermaid_diagram(orientations: str = 'LR', shape: str = 'odd', subgraph: bool = False, subgraph_name: str = 'Component', subgraph_direction: str = 'LR') → None

Print mermaid diagram of this component.

Parameters:

• orientations (str, optional) – Orientation of mermaid diagram. See: https://mermaid.js.org/syntax/flowchart.html#direction. Defaults to “LR”.

• shape (str, optional) – Shape of mermaid diagram. Defaults to “odd”.

• subgraph (bool, optional) – Subgraph or not. Defaults to False.

• subgraph_name (str, optional) – Subgraph name. Defaults to “Component”.

• subgraph_direction (str, optional) – Direction of subgraph. Defaults to “LR”.

record_placed_workplace_id() → None

Record workplace id in this time to placed_workplace_id_record_list.

record_state(working: bool = True) → None

Record current state in state_record_list.

Parameters:

working (bool, optional) – If False and state is WORKING, record READY instead. Defaults to True.

remove_absence_time_list(absence_time_list: list[int]) → None

Remove record information on absence_time_list.

Parameters:

absence_time_list (List[int]) – List of absence step time in simulation.

reverse_log_information() → None

Reverse log information of all.

update_child_component_set(child_component_set: set[BaseComponent]) → None

Update the set of child components.

Parameters:

child_component_set (set[BaseComponent]) – Set of BaseComponents which are children of this component.

update_error_value(no_error_prob: float, error_increment: float, seed=None) → None

Update error value randomly.

If no_error_prob >=1.0, error = error + error_increment.

Parameters:

• no_error_prob (float) – Probability of no error (0.0~1.0).

• error_increment (float) – Increment of error variables if error has occurred.

• seed (int, optional) – Seed of creating random.rand(). Defaults to None.

Note

This method is developed for customized simulation.

update_targeted_task_set(targeted_task_set: set[BaseTask]) → None

Extend the list of targeted tasks to targeted_task_id_set.

Parameters:

targeted_task_set (set(BaseTask)) – Targeted tasks set.

class pDESy.model.base_component.BaseComponentState(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: IntEnum

BaseComponentState.

NONE

No state.

Type:

int

READY

Ready state.

Type:

int

WORKING

Working state.

Type:

int

FINISHED

Finished state.

Type:

int

REMOVED

Removed state.

Type:

int

FINISHED = -1

NONE = 0

READY = 1

REMOVED = -2

WORKING = 2

pDESy.model.base_facility module

pDESy.model.base_priority_rule module

base_priority_rule.

This module defines enums and functions for sorting workplaces, workers, facilities, and tasks according to various priority rules.

class pDESy.model.base_priority_rule.ResourcePriorityRuleMode(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: IntEnum

Enum for resource (worker/facility) priority rule modes.

MW

A worker whose main workplace is equal to target has high priority.

Type:

int

SSP

A worker/facility with lower skill point sum has high priority.

Type:

int

VC

A worker/facility with lower cost has high priority.

Type:

int

HSV

A worker/facility with higher target skill point has high priority.

Type:

int

HSV = 2

MW = -1

SSP = 0

VC = 1

class pDESy.model.base_priority_rule.TaskPriorityRuleMode(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: IntEnum

Enum for task priority rule modes.

TSLACK

Task with lower slack time has high priority.

Type:

int

EST

Earliest Start Time.

Type:

int

SPT

Shortest Processing Time.

Type:

int

LPT

Longest Processing Time.

Type:

int

FIFO

First in First Out.

Type:

int

LRPT

Longest Remaining Process Time.

Type:

int

SRPT

Shortest Remaining Process Time.

Type:

int

EST = 1

FIFO = 4

LPT = 3

LRPT = 5

SPT = 2

SRPT = 6

TSLACK = 0

class pDESy.model.base_priority_rule.WorkplacePriorityRuleMode(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: IntEnum

Enum for workplace priority rule modes.

FSS

Free Space Size.

Type:

int

SSP

Sum Skill Points of targeted task.

Type:

int

FSS = 0

SSP = 1

pDESy.model.base_priority_rule.sort_facility_list(facility_list: list, priority_rule_mode=ResourcePriorityRuleMode.SSP, **kwargs)

Sort facility_list as priority_rule_mode.

Parameters:

• facility_list (List[BaseFacility]) – Target facility list of sorting.

• priority_rule_mode (ResourcePriorityRuleMode, optional) – Mode of priority rule for sorting. Defaults to ResourcePriorityRuleMode.SSP.

• **kwargs – Other information of each rule.

Returns:

facility_list after sorted.

Return type:

List[BaseFacility]

pDESy.model.base_priority_rule.sort_task_list(task_list: list, priority_rule_mode=TaskPriorityRuleMode.TSLACK)

Sort task_list as priority_rule_mode.

Parameters:

• task_list (List[BaseTask]) – Target task list of sorting.

• priority_rule_mode (TaskPriorityRuleMode, optional) – Mode of priority rule for sorting. Defaults to TaskPriorityRuleMode.TSLACK.

Returns:

task_list after sorted.

Return type:

List[BaseTask]

pDESy.model.base_priority_rule.sort_worker_list(worker_list: list, priority_rule_mode=ResourcePriorityRuleMode.SSP, **kwargs)

Sort worker_list as priority_rule_mode.

Parameters:

• worker_list (List[BaseWorker]) – Target worker list of sorting.

• priority_rule_mode (ResourcePriorityRuleMode, optional) – Mode of priority rule for sorting. Defaults to ResourcePriorityRuleMode.SSP.

• **kwargs – Other information of each rule.

Returns:

worker_list after sorted.

Return type:

List[BaseWorker]

pDESy.model.base_priority_rule.sort_workplace_list(workplace_list: list, priority_rule_mode=WorkplacePriorityRuleMode.FSS, **kwargs)

Sort workplace_list as priority_rule_mode.

Parameters:

• workplace_list (List[BaseWorkplace]) – Target workplace list of sorting.

• priority_rule_mode (WorkplacePriorityRuleMode, optional) – Mode of priority rule for sorting. Defaults to WorkplacePriorityRuleMode.FSS.

• **kwargs – Other information of each rule.

Returns:

workplace_list after sorted.

Return type:

List[BaseWorkplace]

pDESy.model.base_product module

base_product.

class pDESy.model.base_product.BaseProduct(name: str = None, ID: str = None, component_set: set[BaseComponent] = None)

Bases: object

BaseProduct.

BaseProduct class for expressing target product in a project. BaseProduct consists of multiple BaseComponents. This class will be used as a template.

Parameters:

• name (str, optional) – Name of this product. Defaults to None -> “Product”.

• ID (str, optional) – ID will be defined automatically. Defaults to None -> str(uuid.uuid4()).

• component_set (set[BaseComponent], optional) – Set of BaseComponents.

add_component(component: BaseComponent)

Add target component to this workflow.

Parameters:

component (BaseComponent) – Target component.

append_component(component: BaseComponent)

Append target component to this workflow.

Deprecated since version Use: add_component instead.

Parameters:

component (BaseComponent) – Target component.

create_component(name: str = None, ID: str = None, child_component_id_set: set[str] = None, targeted_task_id_set: set[str] = None, space_size: float = None, state: BaseComponentState = BaseComponentState.NONE, state_record_list: list[BaseComponentState] = None, placed_workplace_id: str = None, placed_workplace_id_record_list: list[str] = None, error_tolerance: float = None, error: float = None)

Create BaseComponent instance and add it to this product.

Parameters:

• name (str, optional) – Name of this component. Defaults to None -> “New Component”.

• ID (str, optional) – ID will be defined automatically.

• child_component_id_set (set[str], optional) – Child BaseComponents id set. Defaults to None -> set().

• targeted_task_id_set (set[str], optional) – Targeted tasks id set. Defaults to None -> set().

• space_size (float, optional) – Space size related to base_workplace’s max_space_size. Default to None -> 1.0.

• state (BaseComponentState, optional) – State of this task in simulation. Defaults to BaseComponentState.NONE.

• state_record_list (List[BaseComponentState], optional) – Record list of state. Defaults to None -> [].

• placed_workplace_id (str, optional) – A workplace which this component is placed in simulation. Defaults to None.

• placed_workplace_id_record_list (List[str], optional) – Record of placed workplace ID in simulation. Defaults to None -> [].

• error_tolerance (float, optional) – Advanced parameter.

• error (float, optional) – Advanced variables.

Returns:

The created component.

Return type:

BaseComponent

create_data_for_gantt_plotly(init_datetime: datetime, unit_timedelta: timedelta, target_id_order_list: list[str] = None, finish_margin: float = 1.0, print_product_name: bool = True, view_ready: bool = False)

Create data for gantt plotly from component_set.

Parameters:

• init_datetime (datetime.datetime) – Start datetime of project.

• unit_timedelta (datetime.timedelta) – Unit time of simulation.

• target_id_order_list (list[str], optional) – Target ID order list. Defaults to None.

• finish_margin (float, optional) – Margin of finish time in Gantt chart. Defaults to 1.0.

• print_product_name (bool, optional) – Print product name or not. Defaults to True.

• view_ready (bool, optional) – View READY time or not. Defaults to False.

Returns:

Gantt plotly information of this BaseProduct.

Return type:

List[dict]

create_gantt_plotly(init_datetime: datetime, unit_timedelta: timedelta, target_id_order_list: list[str] = None, title: str = 'Gantt Chart', colors: dict[str, str] = None, index_col: str = None, showgrid_x: bool = True, showgrid_y: bool = True, group_tasks: bool = True, show_colorbar: bool = True, finish_margin: float = 1.0, print_product_name: bool = True, view_ready: bool = False, save_fig_path: str = None)

Create Gantt chart by plotly.

This method will be used after simulation.

Parameters:

• init_datetime (datetime.datetime) – Start datetime of project.

• unit_timedelta (datetime.timedelta) – Unit time of simulation.

• target_id_order_list (list[str], optional) – Target ID order list. Defaults to None.

• title (str, optional) – Title of Gantt chart. Defaults to “Gantt Chart”.

• colors (Dict[str, str], optional) – Color setting of plotly Gantt chart. Defaults to None -> dict(Component=”rgb(246, 37, 105)”, READY=”rgb(107, 127, 135)”).

• index_col (str, optional) – index_col of plotly Gantt chart. Defaults to None -> “State”.

• showgrid_x (bool, optional) – showgrid_x of plotly Gantt chart. Defaults to True.

• showgrid_y (bool, optional) – showgrid_y of plotly Gantt chart. Defaults to True.

• group_tasks (bool, optional) – group_tasks of plotly Gantt chart. Defaults to True.

• show_colorbar (bool, optional) – show_colorbar of plotly Gantt chart. Defaults to True.

• finish_margin (float, optional) – Margin of finish time in Gantt chart. Defaults to 1.0.

• print_product_name (bool, optional) – Print product name or not. Defaults to True.

• view_ready (bool, optional) – View READY time or not. Defaults to False.

• save_fig_path (str, optional) – Path of saving figure. Defaults to None.

Returns:

Figure for a gantt chart.

Return type:

figure

create_simple_gantt(target_id_order_list: list[str] = None, finish_margin: float = 1.0, print_product_name: bool = True, view_ready: bool = True, component_color: str = '#FF6600', ready_color: str = '#C0C0C0', figsize: tuple[float, float] = None, dpi: float = 100.0, save_fig_path: str = None)

Create Gantt chart by matplotlib.

In this Gantt chart, datetime information is not included. This method will be used after simulation.

Parameters:

• target_id_order_list (list[str], optional) – Target ID order list. Defaults to None.

• finish_margin (float, optional) – Margin of finish time in Gantt chart. Defaults to 1.0.

• view_ready (bool, optional) – View READY time or not. Defaults to True.

• print_product_name (bool, optional) – Print product name or not. Defaults to True.

• component_color (str, optional) – Component color setting information. Defaults to “#FF6600”.

• ready_color (str, optional) – Ready color setting information. Defaults to “#C0C0C0”.

• figsize ((float, float), optional) – Width, height in inches. Default to None -> [6.4, 4.8].

• dpi (float, optional) – The resolution of the figure in dots-per-inch. Default to 100.0.

• save_fig_path (str, optional) – Path of saving figure. Defaults to None.

Returns:

Figure in plt.subplots(). gnt: Axes in plt.subplots().

Return type:

fig

draw_networkx(g: DiGraph = None, pos: dict = None, arrows: bool = True, component_node_color: str = '#FF6600', figsize: tuple[float, float] = None, dpi: float = 100.0, save_fig_path: str = None, **kwargs)

Draw networkx.

Parameters:

• g (networkx.Digraph, optional) – The information of networkx graph. Defaults to None -> self.get_networkx_graph().

• pos (networkx.layout, optional) – Layout of networkx. Defaults to None -> networkx.spring_layout(g).

• arrows (bool, optional) – Digraph or Graph(no arrows). Defaults to True.

• component_node_color (str, optional) – Node color setting information. Defaults to “#FF6600”.

• figsize ((float, float), optional) – Width, height in inches. Default to None -> [6.4, 4.8].

• dpi (float, optional) – The resolution of the figure in dots-per-inch. Default to 100.0.

• save_fig_path (str, optional) – Path of saving figure. Defaults to None.

• **kwargs – Other networkx settings.

Returns:

Figure for a network.

Return type:

figure

draw_plotly_network(g: DiGraph = None, pos: dict = None, title: str = 'Product', node_size: int = 20, component_node_color: str = '#FF6600', save_fig_path: str = None)

Draw plotly network.

Parameters:

• g (networkx.Digraph, optional) – The information of networkx graph. Defaults to None -> self.get_networkx_graph().

• pos (networkx.layout, optional) – Layout of networkx. Defaults to None -> networkx.spring_layout(g).

• title (str, optional) – Figure title of this network. Defaults to “Product”.

• node_size (int, optional) – Node size setting information. Defaults to 20.

• component_node_color (str, optional) – Node color setting information. Defaults to “#FF6600”.

• save_fig_path (str, optional) – Path of saving figure. Defaults to None.

Returns:

Figure for a network.

Return type:

figure

export_dict_json_data()

Export the information of this product to JSON data.

Returns:

JSON format data.

Return type:

dict

extend_component_list(component_set: set[BaseComponent])

Extend target component_set to this product.

Deprecated since version Use: update_component_set instead.

Parameters:

component_set (set[BaseComponent]) – Target component set.

extract_finished_component_set(target_time_list: list[int])

Extract FINISHED component set from simulation result.

Parameters:

target_time_list (List[int]) – Target time list. If you want to extract finished component from time 2 to time 4, you must set [2, 3, 4] to this argument.

Returns:

List of BaseComponent.

Return type:

List[BaseComponent]

extract_none_component_set(target_time_list: list[int])

Extract NONE component set from simulation result.

Parameters:

target_time_list (List[int]) – Target time list. If you want to extract none component from time 2 to time 4, you must set [2, 3, 4] to this argument.

Returns:

List of BaseComponent.

Return type:

List[BaseComponent]

extract_ready_component_set(target_time_list: list[int])

Extract READY component set from simulation result.

Parameters:

target_time_list (List[int]) – Target time list. If you want to extract ready component from time 2 to time 4, you must set [2, 3, 4] to this argument.

Returns:

List of BaseComponent.

Return type:

List[BaseComponent]

extract_working_component_set(target_time_list: list[int])

Extract WORKING component set from simulation result.

Parameters:

target_time_list (List[int]) – Target time list. If you want to extract working component from time 2 to time 4, you must set [2, 3, 4] to this argument.

Returns:

List of BaseComponent.

Return type:

List[BaseComponent]

get_gantt_mermaid(target_id_order_list: list[str] = None, section: bool = True, range_time: tuple[int, int] = (0, 9223372036854775807), view_ready: bool = False, detailed_info: bool = False, id_name_dict: dict[str, str] = None)

Get mermaid diagram of Gantt chart.

Parameters:

• target_id_order_list (list[str], optional) – Target ID order list. Defaults to None.

• section (bool, optional) – Section or not. Defaults to True.

• range_time (tuple[int, int], optional) – Range of Gantt chart. Defaults to (0, sys.maxsize).

• view_ready (bool, optional) – If True, ready tasks are included in gantt chart. Defaults to False.

• detailed_info (bool, optional) – If True, detailed information is included in gantt chart. Defaults to False.

• id_name_dict (dict[str, str], optional) – Dictionary of ID and name for detailed information. Defaults to None.

Returns:

List of lines for mermaid diagram.

Return type:

list[str]

get_mermaid_diagram(shape_component: str = 'odd', link_type_str: str = '-->', subgraph: bool = True, subgraph_direction: str = 'LR')

Get mermaid diagram of this product.

Parameters:

• shape_component (str, optional) – Shape of mermaid diagram. Defaults to “odd”.

• link_type_str (str, optional) – Link type of mermaid diagram. Defaults to “–>”.

• subgraph (bool, optional) – Subgraph or not. Defaults to True.

• subgraph_direction (str, optional) – Direction of subgraph. Defaults to “LR”.

Returns:

List of lines for mermaid diagram.

Return type:

list[str]

get_networkx_graph()

Get the information of networkx graph.

Returns:

Directed graph of the product.

Return type:

networkx.DiGraph

get_node_and_edge_trace_for_plotly_network(g: DiGraph = None, pos: dict = None, node_size: int = 20, component_node_color: str = '#FF6600')

Get nodes and edges information of plotly network.

Parameters:

• g (networkx.Digraph, optional) – The information of networkx graph. Defaults to None -> self.get_networkx_graph().

• pos (networkx.layout, optional) – Layout of networkx. Defaults to None -> networkx.spring_layout(g).

• node_size (int, optional) – Node size setting information. Defaults to 20.

• component_node_color (str, optional) – Node color setting information. Defaults to “#FF6600”.

Returns:

Node information of plotly network. edge_trace: Edge information of plotly network.

Return type:

node_trace

get_target_component_mermaid_diagram(target_component_set: set[BaseComponent], shape_component: str = 'odd', link_type_str: str = '-->', subgraph: bool = True, subgraph_direction: str = 'LR')

Get mermaid diagram of target component.

Parameters:

• target_component_set (set[BaseComponent]) – Target component set.

• shape_component (str, optional) – Shape of mermaid diagram. Defaults to “odd”.

• link_type_str (str, optional) – Link type of mermaid diagram. Defaults to “–>”.

• subgraph (bool, optional) – Subgraph or not. Defaults to True.

• subgraph_direction (str, optional) – Direction of subgraph. Defaults to “LR”.

Returns:

List of lines for mermaid diagram.

Return type:

list[str]

initialize(state_info: bool = True, log_info: bool = True)

Initialize the changeable variables of BaseProduct.

BaseComponent in component_set are also initialized by this function.

Parameters:

• state_info (bool, optional) – Whether to initialize state information. Defaults to True.

• log_info (bool, optional) – Whether to initialize log information. Defaults to True.

insert_absence_time_list(absence_time_list: list[int])

Insert record information on absence_time_list.

Parameters:

absence_time_list (List[int]) – List of absence step time in simulation.

plot_simple_gantt(target_id_order_list: list[str] = None, finish_margin: float = 1.0, print_product_name: bool = True, view_ready: bool = True, component_color: str = '#FF6600', ready_color: str = '#C0C0C0', figsize: tuple[float, float] = None, dpi: float = 100.0, save_fig_path: str = None)

Plot Gantt chart by matplotlib.

In this Gantt chart, datetime information is not included. This method will be used after simulation.

Parameters:

• target_id_order_list (list[str], optional) – Target ID order list. Defaults to None.

• finish_margin (float, optional) – Margin of finish time in Gantt chart. Defaults to 1.0.

• print_product_name (bool, optional) – Print product name or not. Defaults to True.

• view_ready (bool, optional) – View READY time or not. Defaults to True.

• component_color (str, optional) – Component color setting information. Defaults to “#FF6600”.

• ready_color (str, optional) – Ready color setting information. Defaults to “#C0C0C0”.

• figsize ((float, float), optional) – Width, height in inches. Default to None -> [6.4, 4.8].

• dpi (float, optional) – The resolution of the figure in dots-per-inch. Default to 100.0.

• save_fig_path (str, optional) – Path of saving figure. Defaults to None.

Returns:

Figure in plt.subplots().

Return type:

fig

print_all_log_in_chronological_order(backward: bool = False)

Print all log in chronological order.

Parameters:

backward (bool, optional) – If True, print logs in reverse order. Defaults to False.

print_gantt_mermaid(target_id_order_list: list[str] = None, date_format: str = 'X', axis_format: str = '%s', section: bool = True, range_time: tuple[int, int] = (0, 9223372036854775807), view_ready: bool = False, detailed_info: bool = False, id_name_dict: dict[str, str] = None)

Print mermaid diagram of Gantt chart.

Parameters:

• target_id_order_list (list[str], optional) – Target ID order list. Defaults to None.

• date_format (str, optional) – Date format of mermaid diagram. Defaults to “X”.

• axis_format (str, optional) – Axis format of mermaid diagram. Defaults to “%s”.

• section (bool, optional) – Section or not. Defaults to True.

• range_time (tuple[int, int], optional) – Range of Gantt chart. Defaults to (0, sys.maxsize).

• view_ready (bool, optional) – If True, ready tasks are included in gantt chart. Defaults to False.

• detailed_info (bool, optional) – If True, detailed information is included in gantt chart. Defaults to False.

• id_name_dict (dict[str, str], optional) – Dictionary of ID and name for detailed information. Defaults to None.

print_log(target_step_time: int)

Print log in target_step_time.

Parameters:

target_step_time (int) – Target step time of printing log.

print_mermaid_diagram(orientations: str = 'LR', shape_component: str = 'odd', link_type_str: str = '-->', subgraph: bool = True, subgraph_direction: str = 'LR')

Print mermaid diagram of this product.

Parameters:

• orientations (str, optional) – Orientation of mermaid diagram. See: https://mermaid.js.org/syntax/flowchart.html#direction. Defaults to “LR”.

• shape_component (str, optional) – Shape of mermaid diagram. Defaults to “odd”.

• link_type_str (str, optional) – Link type of mermaid diagram. Defaults to “–>”.

• subgraph (bool, optional) – Subgraph or not. Defaults to True.

• subgraph_direction (str, optional) – Direction of subgraph. Defaults to “LR”.

print_target_component_mermaid_diagram(target_component_set: set[BaseComponent], orientations: str = 'LR', shape_component: str = 'odd', link_type_str: str = '-->', subgraph: bool = True, subgraph_direction: str = 'LR')

Print mermaid diagram of target component.

Parameters:

• target_component_set (set[BaseComponent]) – Target component set.

• orientations (str, optional) – Orientation of mermaid diagram. See: https://mermaid.js.org/syntax/flowchart.html#direction. Defaults to “LR”.

• shape_component (str, optional) – Shape of mermaid diagram. Defaults to “odd”.

• link_type_str (str, optional) – Link type of mermaid diagram. Defaults to “–>”.

• subgraph (bool, optional) – Subgraph or not. Defaults to True.

• subgraph_direction (str, optional) – Direction of subgraph. Defaults to “LR”.

read_json_data(json_data: dict)

Read the JSON data for creating BaseProduct instance.

Parameters:

json_data (dict) – JSON data.

record(working=True)

Record placed workplace id in this time.

Parameters:

working (bool, optional) – Whether to record as working. Defaults to True.

remove_absence_time_list(absence_time_list: list[int])

Remove record information on absence_time_list.

Parameters:

absence_time_list (List[int]) – List of absence step time in simulation.

reverse_log_information()

Reverse log information of all.

update_component_set(component_set: set[BaseComponent])

Update target component_set to this product.

Parameters:

component_set (set[BaseComponent]) – Target component set.

pDESy.model.base_project module

pDESy.model.base_subproject_task module

BaseSubProjectTask module.

This module provides the BaseSubProjectTask class for expressing target sub projects.

Classes:

BaseSubProjectTask: A class representing a sub project task, inheriting from BaseTask.

class pDESy.model.base_subproject_task.BaseSubProjectTask(file_path: str = None, unit_timedelta: timedelta = None, read_json_file: bool = False, remove_absence_time_list: bool = False, name: str = None, ID: str = None, default_work_amount: float = None, work_amount_progress_of_unit_step_time: float = None, input_task_id_dependency_set: set = None, allocated_team_id_set: set = None, allocated_workplace_id_set: set = None, parent_workflow_id: str = None, workplace_priority_rule: WorkplacePriorityRuleMode = WorkplacePriorityRuleMode.FSS, worker_priority_rule: ResourcePriorityRuleMode = ResourcePriorityRuleMode.SSP, facility_priority_rule: ResourcePriorityRuleMode = ResourcePriorityRuleMode.SSP, need_facility: bool = False, target_component_id: str = None, default_progress: float = None, due_time: float = None, auto_task: bool = True, fixing_allocating_worker_id_set: set = None, fixing_allocating_facility_id_set: set = None, est: float = 0.0, eft: float = 0.0, lst: float = -1.0, lft: float = -1.0, remaining_work_amount: float = None, remaining_work_amount_record_list: list = None, state: BaseTaskState = BaseTaskState.NONE, state_record_list: list = None, allocated_worker_facility_id_tuple_set: set = None, allocated_worker_facility_id_tuple_set_record_list: list = None, additional_work_amount: float = None, additional_task_flag: bool = False, actual_work_amount: float = None)

Bases: BaseTask

A class representing a sub project task.

This class is used for expressing a target sub project within the simulation.

export_dict_json_data()

Exports the information of this task to a JSON-serializable dictionary.

Returns:

JSON format data.

Return type:

dict

set_all_attributes_from_json(file_path: str = None, remove_absence_time_list: bool = True)

Reads attributes from a JSON file created by BaseProject.write_simple_json().

Parameters:

• file_path (str, optional) – JSON file path for reading sub project data. Defaults to None, which uses self.file_path.

• remove_absence_time_list (bool, optional) – Whether to remove absence_time_list information from the JSON file. Defaults to True.

Returns:

Duration step time of the target project. datetime.timedelta: Unit time of the target project.

Return type:

int

set_work_amount_progress_of_unit_step_time(project_unit_timedelta: timedelta)

Sets the work amount progress of unit step time.

Parameters:

project_unit_timedelta (datetime.timedelta) – The unit time of the project.

pDESy.model.base_task module

base_task.

class pDESy.model.base_task.BaseTask(name: str = None, ID: str = None, default_work_amount: float = 10.0, work_amount_progress_of_unit_step_time: float = 1.0, input_task_id_dependency_set: set[tuple[str, BaseTaskDependency]] = None, allocated_team_id_set: set[str] = None, allocated_workplace_id_set: set[str] = None, parent_workflow_id: str = None, workplace_priority_rule: WorkplacePriorityRuleMode = WorkplacePriorityRuleMode.FSS, worker_priority_rule: ResourcePriorityRuleMode = ResourcePriorityRuleMode.MW, facility_priority_rule: ResourcePriorityRuleMode = ResourcePriorityRuleMode.SSP, need_facility: bool = False, target_component_id: str = None, default_progress: float = 0.0, due_time: int = -1, auto_task: bool = False, fixing_allocating_worker_id_set: set[str] = None, fixing_allocating_facility_id_set: set[str] = None, est: float = 0.0, eft: float = 0.0, lst: float = -1.0, lft: float = -1.0, remaining_work_amount: float = None, remaining_work_amount_record_list: list[float] = None, state: BaseTaskState = BaseTaskState.NONE, state_record_list: list[BaseTaskState] = None, allocated_worker_facility_id_tuple_set: set[tuple[str, str]] = None, allocated_worker_facility_id_tuple_set_record_list: list[set[tuple[str, str]]] = None, additional_work_amount: float = None, additional_task_flag: bool = False, actual_work_amount: float = None)

Bases: object

BaseTask.

BaseTask class for expressing target workflow. This class will be used as a template.

Parameters:

• name (str, optional) – Name of this task. Defaults to None -> “New Task”.

• ID (str, optional) – ID will be defined automatically. Defaults to None -> str(uuid.uuid4()).

• default_work_amount (float, optional) – Default workamount of this BaseTask. Defaults to None -> 10.0.

• work_amount_progress_of_unit_step_time (float, optional) – Baseline of work amount progress of unit step time. Default to None -> 1.0.

• input_task_id_dependency_set (set(tuple(str, BaseTaskDependency)), optional) – Set of input BaseTask id and type of dependency(FS, SS, SF, F/F) tuple. Defaults to None -> set().

• allocated_team_id_set (set[str], optional) – Set of allocated BaseTeam id. Defaults to None -> set().

• allocated_workplace_id_set (set[str], optional) – Set of allocated BaseWorkplace id. Defaults to None -> set().

• parent_workflow_id (str, optional) – Parent workflow id. Defaults to None.

• workplace_priority_rule (WorkplacePriorityRuleMode, optional) – Workplace priority rule for simulation. Defaults to WorkplacePriorityRuleMode.FSS.

• worker_priority_rule (ResourcePriorityRule, optional) – Worker priority rule for simulation. Defaults to ResourcePriorityRule.SSP.

• facility_priority_rule (ResourcePriorityRule, optional) – Task priority rule for simulation. Defaults to TaskPriorityRule.TSLACK.

• need_facility (bool, optional) – Whether one facility is needed for performing this task or not. Defaults to False.

• target_component_id (str, optional) – Target BaseComponent id. Defaults to None.

• default_progress (float, optional) – Progress before starting simulation (0.0 ~ 1.0). Defaults to None -> 0.0.

• due_time (int, optional) – Due time. Defaults to None -> int(-1).

• auto_task (bool, optional) – If True, this task is performed automatically even if there are no allocated workers. Defaults to False.

• fixing_allocating_worker_id_set (set[str], optional) – Allocating worker ID set for fixing allocation in simulation. Defaults to None.

• fixing_allocating_facility_id_set (set[str], optional) – Allocating facility ID set for fixing allocation in simulation. Defaults to None.

• est (float, optional) – Earliest start time of CPM. This will be updated step by step. Defaults to 0.0.

• eft (float, optional) – Earliest finish time of CPM. This will be updated step by step. Defaults to 0.0.

• lst (float, optional) – Latest start time of CPM. This will be updated step by step. Defaults to -1.0.

• lft (float, optional) – Latest finish time of CPM. This will be updated step by step. Defaults to -1.0.

• remaining_work_amount (float, optional) – Remaining workamount in simulation. Defaults to None -> default_work_amount * (1.0 - default_progress).

• remaining_work_amount_record_list (List[float], optional) – Record of remaining workamount in simulation. Defaults to None -> [].

• state (BaseTaskState, optional) – State of this task in simulation. Defaults to BaseTaskState.NONE.

• state_record_list (List[BaseTaskState], optional) – Record list of state. Defaults to None -> [].

• allocated_worker_facility_id_tuple_set (set(tuple(str, str)), optional) – State of allocating worker and facility id tuple set in simulation. Defaults to None -> set().

• allocated_worker_facility_id_tuple_set_record_list (List[set[tuple(str, str)]], optional) – State of allocating worker and facility id tuple set in simulation. Defaults to None -> [].

• additional_work_amount (float, optional) – Advanced parameter. Defaults to None.

• additional_task_flag (bool, optional) – Advanced variable. Defaults to False.

• actual_work_amount (float, optional) – Advanced variable. Default to None -> default_work_amount*(1.0-default_progress)

add_alloc_pair(pair: tuple[str, str])

1件追加（非破壊）

add_input_task(input_task: BaseTask, task_dependency_mode: BaseTaskDependency = BaseTaskDependency.FS)

Add input task to input_task_id_dependency_set.

Parameters:

• input_task (BaseTask) – Input BaseTask.

• task_dependency_mode (BaseTaskDependency, optional) – Task Dependency mode between input_task to this task. Default to BaseTaskDependency.FS.

add_target_component(target_component: BaseComponent)

Add target component to this task.

Parameters:

target_component (BaseComponent) – Target BaseComponent.

append_input_task_dependency(input_task: BaseTask, task_dependency_mode: BaseTaskDependency = BaseTaskDependency.FS)

Append input task to input_task_id_dependency_set.

Deprecated since version Use: add_input_task instead.

Parameters:

• input_task (BaseTask) – Input BaseTask.

• task_dependency_mode (BaseTaskDependency, optional) – Task Dependency mode between input_task to this task. Default to BaseTaskDependency.FS.

export_dict_json_data()

Export the information of this task to JSON data.

Returns:

JSON format data.

Return type:

dict

extend_input_task_list(input_task_list: list[BaseTask], input_task_dependency_mode: BaseTaskDependency = BaseTaskDependency.FS)

Extend the set of input tasks and FS dependency to input_task_id_dependency_set.

Deprecated since version Use: update_input_task_set instead.

Parameters:

input_task_id_dependency_set (set(tuple(str, BaseTask))) – Set of input BaseTask and type of dependency(FS, SS, SF, F/F).

get_gantt_mermaid_data(range_time: tuple[int, int] = (0, 9223372036854775807), detailed_info: bool = False, id_name_dict: dict[str, str] = None, view_ready: bool = False)

Get gantt mermaid data of this task.

Parameters:

• range_time (tuple[int, int], optional) – Range of gantt chart. Defaults to (0, sys.maxsize).

• detailed_info (bool, optional) – If True, print detailed information. Defaults to False.

• id_name_dict (dict[str, str], optional) – Dictionary to map ID to name. Defaults to None.

• view_ready (bool, optional) – If True, include ready time in Gantt chart. Defaults to False.

Returns:

List of lines for gantt mermaid diagram.

Return type:

list[str]

get_mermaid_diagram(shape: str = 'rect', print_work_amount_info: bool = True, subgraph: bool = False, subgraph_name: str = 'Task', subgraph_direction: str = 'LR')

Get mermaid diagram of this task.

Parameters:

• shape (str, optional) – Shape of mermaid diagram. Defaults to “rect”.

• print_work_amount_info (bool, optional) – Print work amount information or not. Defaults to True.

• subgraph (bool, optional) – Subgraph or not. Defaults to False.

• subgraph_name (str, optional) – Subgraph name. Defaults to “Task”.

• subgraph_direction (str, optional) – Direction of subgraph. Defaults to “LR”.

Returns:

List of lines for mermaid diagram.

Return type:

list[str]

get_state_from_record(time: int)

Get the state information in time.

Parameters:

time (int) – Target simulation time.

Returns:

Task State information.

Return type:

BaseTaskState

get_time_list_for_gantt_chart(finish_margin: float = 1.0)

Get ready/working time_list for drawing Gantt chart.

Parameters:

finish_margin (float, optional) – Margin of finish time in Gantt chart. Defaults to 1.0.

Returns:

• ready_time_list including start_time, length

• working_time_list including start_time, length

Return type:

Tuple[List[tuple(int, int)], List[tuple(int, int)]]

initialize(error_tol: float = 1e-10, state_info: bool = True, log_info: bool = True)

Initialize the changeable variables of BaseTask.

If state_info is True, the following attributes are initialized:

• est

• eft

• lst

• lft

• remaining_work_amount

• state

• allocated_worker_facility_id_tuple_set

• additional_task_flag

• actual_work_amount

If log_info is True, the following attributes are initialized:

• remaining_work_amount_record_list

• state_record_list

• allocated_worker_facility_id_tuple_set_record_list

Parameters:

• error_tol (float, optional) – Error toleration of work amount for checking the state of this task. Defaults to 1e-10.

• state_info (bool, optional) – Whether to initialize state information. Defaults to True.

• log_info (bool, optional) – Whether to initialize log information. Defaults to True.

insert_absence_time_list(absence_time_list: list[int])

Insert record information on absence_time_list.

Parameters:

absence_time_list (List[int]) – List of absence step time in simulation.

print_all_log_in_chronological_order(backward: bool = False)

Print all log in chronological order.

Parameters:

backward (bool, optional) – If True, print logs in reverse order. Defaults to False.

print_log(target_step_time: int)

Print log in target_step_time.

Prints:

• ID

• name

• default_work_amount

• remaining_work_amount_record_list

• state_record_list[target_step_time]

• allocated_worker_facility_id_tuple_set_record_list[target_step_time]

Parameters:

target_step_time (int) – Target step time of printing log.

print_mermaid_diagram(orientations: str = 'LR', shape: str = 'rect', print_work_amount_info: bool = True, subgraph: bool = False, subgraph_name: str = 'Task', subgraph_direction: str = 'LR')

Print mermaid diagram of this task.

Parameters:

• orientations (str, optional) – Orientation of mermaid diagram. Defaults to “LR”.

• shape (str, optional) – Shape of mermaid diagram. Defaults to “rect”.

• print_work_amount_info (bool, optional) – Print work amount information or not. Defaults to True.

• subgraph (bool, optional) – Subgraph or not. Defaults to False.

• subgraph_name (str, optional) – Subgraph name. Defaults to “Task”.

• subgraph_direction (str, optional) – Direction of subgraph. Defaults to “LR”.

remove_absence_time_list(absence_time_list: list[int])

Remove record information on absence_time_list.

Parameters:

absence_time_list (List[int]) – List of absence step time in simulation.

remove_alloc_pair(pair: tuple[str, str])

1件削除（非破壊）

reverse_log_information()

Reverse log information of all.

set_alloc_pairs(pairs_iterable)

割当集合を丸ごと置換（最速）

update_alloc_pairs(add=(), remove=())

まとめて更新（非破壊）

update_input_task_set(input_task_set: set[BaseTask], input_task_dependency_mode: BaseTaskDependency = BaseTaskDependency.FS)

Update the set of input tasks and FS dependency to input_task_id_dependency_set.

Parameters:

input_task_id_dependency_set (set(tuple(str, BaseTask))) – Set of input BaseTask and type of dependency(FS, SS, SF, F/F).

class pDESy.model.base_task.BaseTaskDependency(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: IntEnum

BaseTaskDependency.

Enum for representing task dependency types.

FS

Finish to Start.

Type:

int

SS

Start to Start.

Type:

int

FF

Finish to Finish.

Type:

int

SF

Start to Finish.

Type:

int

FF = 2

FS = 0

SF = 3

SS = 1

class pDESy.model.base_task.BaseTaskState(value, names=None, *, module=None, qualname=None, type=None, start=1, boundary=None)

Bases: IntEnum

BaseTaskState.

Enum for representing the state of a task.

NONE

No state.

Type:

int

READY

Ready to start.

Type:

int

WORKING

Currently working.

Type:

int

WORKING_ADDITIONALLY

Working additionally.

Type:

int

FINISHED

Finished.

Type:

int

FINISHED = -1

NONE = 0

READY = 1

WORKING = 2

WORKING_ADDITIONALLY = 3

pDESy.model.base_team module

pDESy.model.base_worker module

pDESy.model.base_workflow module

base_workflow.

class pDESy.model.base_workflow.BaseWorkflow(name: str = None, ID: str = None, task_set: set[BaseTask] = None, critical_path_length: float = 0.0)

Bases: object

BaseWorkflow.

BaseWorkflow class for expressing workflow in a project. BaseWorkflow consists of multiple BaseTasks. This class will be used as a template.

Parameters:

• name (str, optional) – Name of this workflow. Defaults to None -> “Workflow”.

• ID (str, optional) – ID will be defined automatically. Defaults to None -> str(uuid.uuid4()).

• task_set (set[BaseTask], optional) – List of BaseTask in this BaseWorkflow. Default to None -> set().

• critical_path_length (float, optional) – Critical path length of PERT/CPM. Defaults to 0.0.

add_task(task: BaseTask)

Add target task to this workflow.

Parameters:

task (BaseTask) – Target task.

append_child_task(task: BaseTask)

Append target task to this workflow.

Deprecated since version Use: add_task instead.

Parameters:

task (BaseTask) – Target task.

create_data_for_gantt_plotly(init_datetime: datetime, unit_timedelta: timedelta, target_id_order_list: list[str] = None, finish_margin: float = 1.0, print_workflow_name: bool = True, view_ready: bool = False)

Create data for gantt plotly from task_set.

Parameters:

• init_datetime (datetime.datetime) – Start datetime of project.

• unit_timedelta (datetime.timedelta) – Unit time of simulation.

• target_id_order_list (list[str], optional) – Target ID order list. Defaults to None.

• finish_margin (float, optional) – Margin of finish time in Gantt chart. Defaults to 1.0.

• print_workflow_name (bool, optional) – Print workflow name or not. Defaults to True.

• view_ready (bool, optional) – View READY time or not. Defaults to False.

Returns:

Gantt plotly information of this BaseWorkflow.

Return type:

list[dict]

create_gantt_plotly(init_datetime: datetime, unit_timedelta: timedelta, target_id_order_list: list[str] = None, title: str = 'Gantt Chart', colors: dict[str, str] = None, index_col: str = None, showgrid_x: bool = True, showgrid_y: bool = True, group_tasks: bool = True, show_colorbar: bool = True, finish_margin: float = 1.0, print_workflow_name: bool = True, view_ready: bool = False, save_fig_path: str = None)

Create Gantt chart by plotly.

This method will be used after simulation.

Parameters:

• init_datetime (datetime.datetime) – Start datetime of project.

• unit_timedelta (datetime.timedelta) – Unit time of simulation.

• target_id_order_list (list[str], optional) – Target ID order list. Defaults to None.

• title (str, optional) – Title of Gantt chart. Defaults to “Gantt Chart”.

• colors (Dict[str, str], optional) – Color setting of plotly Gantt chart. Defaults to None -> dict(WORKING=”rgb(146, 237, 5)”, READY=”rgb(107, 127, 135)”).

• index_col (str, optional) – index_col of plotly Gantt chart. Defaults to None -> “State”.

• showgrid_x (bool, optional) – showgrid_x of plotly Gantt chart. Defaults to True.

• showgrid_y (bool, optional) – showgrid_y of plotly Gantt chart. Defaults to True.

• group_tasks (bool, optional) – group_tasks of plotly Gantt chart. Defaults to True.

• show_colorbar (bool, optional) – show_colorbar of plotly Gantt chart. Defaults to True.

• finish_margin (float, optional) – Margin of finish time in Gantt chart. Defaults to 1.0.

• print_workflow_name (bool, optional) – Print workflow name or not. Defaults to True.

• save_fig_path (str, optional) – Path of saving figure. Defaults to None.

Returns:

Figure for a gantt chart.

Return type:

figure

create_simple_gantt(target_id_order_list: list[str] = None, finish_margin: float = 1.0, print_workflow_name: bool = True, view_auto_task: bool = False, view_ready: bool = False, task_color: str = '#00EE00', auto_task_color: str = '#005500', ready_color: str = '#C0C0C0', figsize: tuple[float, float] = None, dpi: float = 100.0, save_fig_path: str = None)

Create Gantt chart by matplotlib.

In this Gantt chart, datetime information is not included. This method will be used after simulation.

Parameters:

• target_id_order_list (list[str], optional) – Target ID order list. Defaults to None.

• finish_margin (float, optional) – Margin of finish time in Gantt chart. Defaults to 1.0.

• print_workflow_name (bool, optional) – Print workflow name or not. Defaults to True.

• view_auto_task (bool, optional) – View auto_task or not. Defaults to False.

• view_ready (bool, optional) – View READY time or not. Defaults to False.

• task_color (str, optional) – Task color setting information. Defaults to “#00EE00”.

• auto_task_color (str, optional) – Auto Task color setting information. Defaults to “#005500”.

• ready_color (str, optional) – Ready Task color setting information. Defaults to “#C0C0C0”.

• figsize ((float, float), optional) – Width, height in inches. Default to None -> [6.4, 4.8].

• dpi (float, optional) – The resolution of the figure in dots-per-inch. Default to 100.0.

• save_fig_path (str, optional) – Path of saving figure. Defaults to None.

Returns:

Figure in plt.subplots(). gnt: Axes in plt.subplots().

Return type:

fig

create_task(name: str = None, ID: str = None, default_work_amount: float = None, work_amount_progress_of_unit_step_time: float = None, input_task_id_dependency_set: set[tuple[str, BaseTaskDependency]] = None, allocated_team_id_set: set[str] = None, allocated_workplace_id_set: set[str] = None, workplace_priority_rule: WorkplacePriorityRuleMode = WorkplacePriorityRuleMode.FSS, worker_priority_rule: ResourcePriorityRuleMode = ResourcePriorityRuleMode.MW, facility_priority_rule: ResourcePriorityRuleMode = ResourcePriorityRuleMode.SSP, need_facility: bool = False, target_component_id: str = None, default_progress: float = None, due_time: float = None, auto_task: bool = False, fixing_allocating_worker_id_set: set[str] = None, fixing_allocating_facility_id_set: set[str] = None, est: float = 0.0, eft: float = 0.0, lst: float = -1.0, lft: float = -1.0, remaining_work_amount: float = None, remaining_work_amount_record_list: list[float] = None, state: BaseTaskState = BaseTaskState.NONE, state_record_list: list[BaseTaskState] = None, allocated_worker_facility_id_tuple_set: set[tuple[str, str]] = None, allocated_worker_facility_id_tuple_set_record_list: list[set[tuple[str, str]]] = None, additional_work_amount: float = None, additional_task_flag: bool = False, actual_work_amount: float = None)

Create a BaseTask instance and add it to this workflow.

Parameters:

• name (str, optional) – Name of this task. Defaults to None -> “New Task”.

• ID (str, optional) – ID will be defined automatically. Defaults to None -> str(uuid.uuid4()).

• default_work_amount (float, optional) – Default workamount of this BaseTask. Defaults to None -> 10.0.

• work_amount_progress_of_unit_step_time (float, optional) – Baseline of work amount progress of unit step time. Default to None -> 1.0.

• input_task_id_dependency_set (set(tuple(str, BaseTaskDependency)), optional) – Set of input BaseTask id and type of dependency(FS, SS, SF, F/F) tuple. Defaults to None -> set().

• allocated_team_id_set (set[str], optional) – Set of allocated BaseTeam id. Defaults to None -> set().

• allocated_workplace_id_set (set[str], optional) – Set of allocated BaseWorkplace id. Defaults to None -> set().

• workplace_priority_rule (WorkplacePriorityRuleMode, optional) – Workplace priority rule for simulation. Defaults to WorkplacePriorityRuleMode.FSS.

• worker_priority_rule (ResourcePriorityRule, optional) – Worker priority rule for simulation. Defaults to ResourcePriorityRule.SSP.

• facility_priority_rule (ResourcePriorityRule, optional) – Task priority rule for simulation. Defaults to TaskPriorityRule.TSLACK.

• need_facility (bool, optional) – Whether one facility is needed for performing this task or not. Defaults to False.

• target_component_id (str, optional) – Target BaseComponent id. Defaults to None.

• default_progress (float, optional) – Progress before starting simulation (0.0 ~ 1.0). Defaults to None -> 0.0.

• due_time (int, optional) – Due time. Defaults to None -> int(-1).

• auto_task (bool, optional) – If True, this task is performed automatically even if there are no allocated workers. Defaults to False.

• fixing_allocating_worker_id_set (set[str], optional) – Allocating worker ID set for fixing allocation in simulation. Defaults to None.

• fixing_allocating_facility_id_set (set[str], optional) – Allocating facility ID set for fixing allocation in simulation. Defaults to None.

• est (float, optional) – Earliest start time of CPM. This will be updated step by step. Defaults to 0.0.

• eft (float, optional) – Earliest finish time of CPM. This will be updated step by step. Defaults to 0.0.

• lst (float, optional) – Latest start time of CPM. This will be updated step by step. Defaults to -1.0.

• lft (float, optional) – Latest finish time of CPM. This will be updated step by step. Defaults to -1.0.

• remaining_work_amount (float, optional) – Remaining workamount in simulation. Defaults to None -> default_work_amount * (1.0 - default_progress).

• remaining_work_amount_record_list (List[float], optional) – Record of remaining workamount in simulation. Defaults to None -> [].

• state (BaseTaskState, optional) – State of this task in simulation. Defaults to BaseTaskState.NONE.

• state_record_list (List[BaseTaskState], optional) – Record list of state. Defaults to None -> [].

• allocated_worker_facility_id_tuple_set (set(tuple(str, str)), optional) – State of allocating worker and facility id tuple set in simulation. Defaults to None -> set().

• allocated_worker_facility_id_tuple_set_record_list (List[set[tuple(str, str)]], optional) – State of allocating worker and facility id tuple set in simulation. Defaults to None -> [].

• additional_work_amount (float, optional) – Advanced parameter. Defaults to None.

• additional_task_flag (bool, optional) – Advanced variable. Defaults to False.

• actual_work_amount (float, optional) – Advanced variable. Default to None -> default_work_amount*(1.0-default_progress)

Returns:

The created task.

Return type:

BaseTask

draw_networkx(g: DiGraph = None, pos: dict = None, arrows: bool = True, task_node_color: str = '#00EE00', auto_task_node_color: str = '#005500', figsize: tuple[float, float] = None, dpi: float = 100.0, save_fig_path: str = None, **kwargs)

Draw networkx.

Parameters:

• g (networkx.Digraph, optional) – The information of networkx graph. Defaults to None -> self.get_networkx_graph().

• pos (networkx.layout, optional) – Layout of networkx. Defaults to None -> networkx.spring_layout(g).

• arrows (bool, optional) – Digraph or Graph(no arrows). Defaults to True.

• task_node_color (str, optional) – Node color setting information. Defaults to “#00EE00”.

• auto_task_node_color (str, optional) – Node color setting information. Defaults to “#005500”.

• figsize ((float, float), optional) – Width, height in inches. Default to None -> [6.4, 4.8].

• dpi (float, optional) – The resolution of the figure in dots-per-inch. Default to 100.0.

• save_fig_path (str, optional) – Path of saving figure. Defaults to None.

• **kwargs – Other networkx settings.

Returns:

Figure for a network.

Return type:

figure

draw_plotly_network(g: DiGraph = None, pos: dict = None, title: str = 'Workflow', node_size: int = 20, task_node_color: str = '#00EE00', auto_task_node_color: str = '#005500', save_fig_path=None)

Draw plotly network.

Parameters:

• g (networkx.Digraph, optional) – The information of networkx graph. Defaults to None -> self.get_networkx_graph().

• pos (networkx.layout, optional) – Layout of networkx. Defaults to None -> networkx.spring_layout(g).

• title (str, optional) – Figure title of this network. Defaults to “Workflow”.

• node_size (int, optional) – Node size setting information. Defaults to 20.

• task_node_color (str, optional) – Node color setting information. Defaults to “#00EE00”.

• auto_task_node_color (str, optional) – Node color setting information. Defaults to “#005500”.

• save_fig_path (str, optional) – Path of saving figure. Defaults to None.

Returns:

Figure for a network.

Return type:

figure

export_dict_json_data()

Export the information of this workflow to JSON data.

Returns:

JSON format data.

Return type:

dict

extend_child_task_list(task_set: set[BaseTask])

Extend target task_set to this workflow.

Deprecated since version Use: updated_task_set instead.

Parameters:

task_set (set[BaseTask]) – Target task set.

extract_finished_task_set(target_time_list: list[int])

Extract FINISHED task list from simulation result.

Parameters:

target_time_list (List[int]) – Target time list. If you want to extract finished task from time 2 to time 4, you must set [2, 3, 4] to this argument.

Returns:

List of BaseTask.

Return type:

List[BaseTask]

extract_none_task_set(target_time_list: list[int])

Extract NONE task set from simulation result.

Parameters:

target_time_list (List[int]) – Target time list. If you want to extract none task from time 2 to time 4, you must set [2, 3, 4] to this argument.

Returns:

List of BaseTask.

Return type:

List[BaseTask]

extract_ready_task_set(target_time_list: list[int])

Extract READY task set from simulation result.

Parameters:

target_time_list (List[int]) – Target time list. If you want to extract ready task from time 2 to time 4, you must set [2, 3, 4] to this argument.

Returns:

List of BaseTask.

Return type:

List[BaseTask]

extract_working_task_set(target_time_list: list[int])

Extract WORKING task list from simulation result.

Parameters:

target_time_list (List[int]) – Target time list. If you want to extract working task from time 2 to time 4, you must set [2, 3, 4] to this argument.

Returns:

List of BaseTask.

Return type:

List[BaseTask]

get_gantt_mermaid(target_id_order_list: list[str] = None, section: bool = True, range_time: tuple[int, int] = (0, 9223372036854775807), view_ready: bool = False, detailed_info: bool = False, id_name_dict: dict[str, str] = None)

Get mermaid diagram of Gantt chart.

Parameters:

• target_id_order_list (list[str], optional) – Target ID order list. Defaults to None.

• section (bool, optional) – Section or not. Defaults to True.

• range_time (tuple[int, int], optional) – Range of Gantt chart. Defaults to (0, sys.maxsize).

• view_ready (bool, optional) – If True, ready tasks are included in gantt chart. Defaults to False.

• detailed_info (bool, optional) – Detailed information or not. Defaults to False.

• id_name_dict (dict[str, str], optional) – Dictionary of ID and name for tasks. Defaults to None.

Returns:

List of lines for mermaid diagram.

Return type:

list[str]

get_mermaid_diagram(shape_task: str = 'rect', print_work_amount_info: bool = True, link_type_str: str = '-->', print_dependency_type: bool = False, subgraph: bool = True, subgraph_direction: str = 'LR')

Get mermaid diagram of this workflow.

Parameters:

• shape_task (str, optional) – Shape of mermaid diagram. Defaults to “rect”.

• print_work_amount_info (bool, optional) – Print work amount information or not. Defaults to True.

• link_type_str (str, optional) – Link type string. Defaults to “–>”.

• print_dependency_type (bool, optional) – Print dependency type information or not. Defaults to False.

• subgraph (bool, optional) – Subgraph or not. Defaults to True.

• subgraph_direction (str, optional) – Direction of subgraph. Defaults to “LR”.

Returns:

List of lines for mermaid diagram.

Return type:

list[str]

get_networkx_graph()

Get the information of networkx graph.

Returns:

Directed graph of the workflow.

Return type:

networkx.DiGraph

get_node_and_edge_trace_for_plotly_network(g: DiGraph = None, pos: dict = None, node_size: int = 20, task_node_color: str = '#00EE00', auto_task_node_color: str = '#005500')

Get nodes and edges information of plotly network.

Parameters:

• g (networkx.Digraph, optional) – The information of networkx graph. Defaults to None -> self.get_networkx_graph().

• pos (networkx.layout, optional) – Layout of networkx. Defaults to None -> networkx.spring_layout(g).

• node_size (int, optional) – Node size setting information. Defaults to 20.

• task_node_color (str, optional) – Node color setting information. Defaults to “#00EE00”.

• auto_task_node_color (str, optional) – Node color setting information. Defaults to “#005500”.

Returns:

Normal Task Node information of plotly network. auto_task_node_trace: Auto Task Node information of plotly network. edge_trace: Edge information of plotly network.

Return type:

task_node_trace

get_target_task_mermaid_diagram(target_task_set: set[BaseTask], shape_task: str = 'rect', print_work_amount_info: bool = True, link_type_str: str = '-->', print_dependency_type: bool = False, subgraph: bool = True, subgraph_direction: str = 'LR')

Get mermaid diagram of target task.

Parameters:

• target_task_set (set[BaseTask]) – Set of target tasks.

• shape_task (str, optional) – Shape of mermaid diagram. Defaults to “rect”.

• print_work_amount_info (bool, optional) – Print work amount information or not. Defaults to True.

• link_type_str (str, optional) – Link type string. Defaults to “–>”.

• print_dependency_type (bool, optional) – Print dependency type information or not. Defaults to False.

• subgraph (bool, optional) – Subgraph or not. Defaults to True.

• subgraph_direction (str, optional) – Direction of subgraph. Defaults to “LR”.

Returns:

List of lines for mermaid diagram.

Return type:

list[str]

get_task_set(name: str = None, ID: str = None, default_work_amount: float = None, input_task_id_dependency_set: set[tuple[str, BaseTaskDependency]] = None, allocated_team_id_set: set[str] = None, allocated_workplace_id_set: set[str] = None, need_facility: bool = None, target_component_id: str = None, default_progress: float = None, due_time: int = None, auto_task: bool = None, fixing_allocating_worker_id_set: set[str] = None, fixing_allocating_facility_id_set: set[str] = None, est: float = None, eft: float = None, lst: float = None, lft: float = None, remaining_work_amount: float = None, state: BaseTaskState = None, allocated_worker_facility_id_tuple_set: set[tuple[str, str]] = None, allocated_worker_facility_id_tuple_set_record_list: list[set[tuple[str, str]]] = None)

Get task list by using search conditions related to BaseTask parameter.

If there is no searching condition, this function returns all task_set

Parameters:

• name (str, optional) – Target task name. Defaults to None.

• ID (str, optional) – Target task ID. Defaults to None.

• default_work_amount (float, optional) – Target task default_work_amount. Defaults to None.

• input_task_id_dependency_set (set(tuple(str, BaseTaskDependency)), optional) – Target task input_task_id_dependency_set. Defaults to None.

• allocated_team_id_set (set[str], optional) – Target task allocated_team_id_set. Defaults to None.

• allocated_workplace_id_set (set[str], optional) – Target task allocated_workplace_id_set. Defaults to None.

• need_facility (bool, optional) – Target task need_facility. Defaults to None.

• target_component_id (str, optional) – Target task target_component_id. Defaults to None.

• default_progress (float, optional) – Target task default_progress. Defaults to None.

• due_time (int, optional) – Target task due_time. Defaults to None.

• auto_task (bool, optional) – Target task auto_task. Defaults to None.

• fixing_allocating_worker_id_set (set[str], optional) – Target task fixing_allocating_worker_id_set. Defaults to None.

• fixing_allocating_facility_id_set (set[str], optional) – Target task fixing_allocating_facility_id_set. Defaults to None.

• est (float, optional) – Target task est. Defaults to None.

• eft (float, optional) – Target task eft. Defaults to None.

• lst (float, optional) – Target task lst. Defaults to None.

• lft (float, optional) – Target task lft. Defaults to None.

• remaining_work_amount (float, optional) – Target task remaining_work_amount. Defaults to None.

• state (BaseTaskState, optional) – Target task state. Defaults to None.

• allocated_worker_facility_id_tuple_set (set(tuple(str, str)), optional) – Target task allocated_worker_facility_id_tuple_set. Defaults to None.

• allocated_worker_facility_id_tuple_set_record_list (List[set(tuple(str, str))], optional) – Target task allocated_worker_facility_id_tuple_set_record_list. Defaults to None.

Returns:

List of BaseTask.

Return type:

List[BaseTask]

initialize(state_info: bool = True, log_info: bool = True)

Initialize the changeable variables of BaseWorkflow including PERT calculation.

If state_info is True, the following attributes are initialized:

• critical_path_length

• PERT data

• The state of each task after all tasks are initialized.

BaseTask in task_set are also initialized by this function.

Parameters:

• state_info (bool, optional) – Whether to initialize state information. Defaults to True.

• log_info (bool, optional) – Whether to initialize log information. Defaults to True.

insert_absence_time_list(absence_time_list: list[int])

Insert record information on absence_time_list.

Parameters:

absence_time_list (List[int]) – List of absence step time in simulation.

plot_simple_gantt(target_id_order_list: list[str] = None, finish_margin: float = 1.0, print_workflow_name: bool = True, view_auto_task: bool = False, view_ready: bool = False, task_color: str = '#00EE00', auto_task_color: str = '#005500', ready_color: str = '#C0C0C0', figsize: tuple[float, float] = None, dpi: float = 100.0, save_fig_path: str = None)

Plot Gantt chart by matplotlib.

In this Gantt chart, datetime information is not included. This method will be used after simulation.

Parameters:

• target_id_order_list (list[str], optional) – Target ID order list. Defaults to None.

• finish_margin (float, optional) – Margin of finish time in Gantt chart. Defaults to 1.0.

• print_workflow_name (bool, optional) – Print workflow name or not. Defaults to True.

• view_auto_task (bool, optional) – View auto_task or not. Defaults to False.

• view_ready (bool, optional) – View READY time or not. Defaults to False.

• task_color (str, optional) – Task color setting information. Defaults to “#00EE00”.

• auto_task_color (str, optional) – Auto Task color setting information. Defaults to “#005500”.

• ready_color (str, optional) – Ready Task color setting information. Defaults to “#C0C0C0”.

• figsize ((float, float), optional) – Width, height in inches. Default to None -> [6.4, 4.8].

• dpi (float, optional) – The resolution of the figure in dots-per-inch. Default to 100.0.

• save_fig_path (str, optional) – Path of saving figure. Defaults to None.

Returns:

Figure in plt.subplots().

Return type:

fig

print_all_log_in_chronological_order(backward: bool = False)

Print all log in chronological order.

Parameters:

backward (bool, optional) – If True, print logs in reverse order. Defaults to False.

print_gantt_mermaid(target_id_order_list: list[str] = None, date_format: str = 'X', axis_format: str = '%s', section: bool = True, range_time: tuple[int, int] = (0, 9223372036854775807), view_ready: bool = False, detailed_info: bool = False, id_name_dict: dict[str, str] = None)

Print mermaid diagram of Gantt chart.

Parameters:

• target_id_order_list (list[str], optional) – Target ID order list. Defaults to None.

• date_format (str, optional) – Date format of mermaid diagram. Defaults to “X”.

• axis_format (str, optional) – Axis format of mermaid diagram. Defaults to “%s”.

• section (bool, optional) – Section or not. Defaults to True.

• range_time (tuple[int, int], optional) – Range of Gantt chart. Defaults to (0, sys.maxsize).

• view_ready (bool, optional) – If True, ready tasks are included in gantt chart. Defaults to False.

• detailed_info (bool, optional) – Detailed information or not. Defaults to False.

• id_name_dict (dict[str, str], optional) – Dictionary of ID and name for tasks. Defaults to None.

print_log(target_step_time: int)

Print log in target_step_time.

Parameters:

target_step_time (int) – Target step time of printing log.

print_mermaid_diagram(orientations: str = 'LR', shape_task: str = 'rect', print_work_amount_info: bool = True, link_type_str: str = '-->', print_dependency_type: bool = False, subgraph: bool = True, subgraph_direction: str = 'LR')

Print mermaid diagram of this workflow.

Parameters:

• orientations (str, optional) – Orientation of mermaid diagram. See: https://mermaid.js.org/syntax/flowchart.html#direction. Defaults to “LR”.

• shape_task (str, optional) – Shape of mermaid diagram. Defaults to “rect”.

• print_work_amount_info (bool, optional) – Print work amount information or not. Defaults to True.

• link_type_str (str, optional) – Link type string. Defaults to “–>”.

• print_dependency_type (bool, optional) – Print dependency type information or not. Defaults to False.

• subgraph (bool, optional) – Subgraph or not. Defaults to True.

• subgraph_direction (str, optional) – Direction of subgraph. Defaults to “LR”.

print_target_task_mermaid_diagram(target_task_set: set[BaseTask], orientations: str = 'LR', shape_task: str = 'rect', print_work_amount_info: bool = True, link_type_str: str = '-->', print_dependency_type: bool = False, subgraph: bool = True, subgraph_direction: str = 'LR')

Print mermaid diagram of target task.

Parameters:

• target_task_set (set[BaseTask]) – Set of target tasks.

• orientations (str, optional) – Orientation of mermaid diagram. See: https://mermaid.js.org/syntax/flowchart.html#direction. Defaults to “LR”.

• shape_task (str, optional) – Shape of mermaid diagram. Defaults to “rect”.

• print_work_amount_info (bool, optional) – Print work amount information or not. Defaults to True.

• link_type_str (str, optional) – Link type string. Defaults to “–>”.

• print_dependency_type (bool, optional) – Print dependency type information or not. Defaults to False.

• subgraph (bool, optional) – Subgraph or not. Defaults to True.

• subgraph_direction (str, optional) – Direction of subgraph. Defaults to “LR”.

read_json_data(json_data: dict)

Read the JSON data for creating BaseWorkflow instance.

Parameters:

json_data (dict) – JSON data.

record(working: bool = True)

Record the state of all tasks in task_set.

Parameters:

working (bool, optional) – Whether to record as working. Defaults to True.

remove_absence_time_list(absence_time_list: list[int])

Remove record information on absence_time_list.

Parameters:

absence_time_list (List[int]) – List of absence step time in simulation.

reverse_dependencies()

Reverse all task dependencies in task_set.

Note

This method is developed only for backward simulation.

reverse_log_information()

Reverse log information of all.

update_pert_data(time: int)

Update PERT data (est, eft, lst, lft) of each BaseTask in task_set.

Parameters:

time (int) – Simulation time.

update_task_set(task_set: set[BaseTask])

Update target task_set to this workflow.

Parameters:

task_set (set[BaseTask]) – Target task set.

pDESy.model.base_workplace module

Module contents

__init__.