This document discusses the API and underlying implementation of the generic entrance randomization algorithm exposed in entrance_rando.py. Throughout the doc, entrance randomization is frequently abbreviated as "ER."
This doc assumes familiarity with Archipelago's graph logic model. If you don't have a solid understanding of how regions work, you should start there.
Some important terminology to understand when reading this doc and working with ER is listed below.
- Entrance rando - sometimes called "room rando," "transition rando," "door rando," or similar,
this is a game mode in which the game map itself is randomized.
In Archipelago, these things are often represented as
Entrance
s in the region graph, so we call it Entrance rando. - Entrances and exits - entrances are ways into your region, exits are ways out of the region. In code, they are both
represented as
Entrance
objects. In this doc, the terms "entrances" and "exits" will be used in this sense; theEntrance
class will always be referenced in a code block with an uppercase E. - Dead end - a connected group of regions which can never help ER progress. This means that it:
- Is not in any indirect conditions/access rules.
- Has no plando'd or otherwise preplaced progression items, including events.
- Has no randomized exits.
- One way transition - a transition that, in the game, is not safe to reverse through (for example, in Hollow Knight, some transitions are inaccessible backwards in vanilla and would put you out of bounds). One way transitions are paired together during randomization to prevent such unsafe game states. Most transitions are not one way.
The Generic ER algorithm works by using the logic structures you are already familiar with. To give a basic example, let's assume a toy world is defined with the vanilla region graph modeled below. In this diagram, the smaller boxes represent regions while the larger boxes represent scenes. Scenes are not an Archipelago concept, the grouping is purely illustrative.
%%{init: {"graph": {"defaultRenderer": "elk"}} }%%
graph LR
subgraph startingRoom [Starting Room]
S[Starting Room Right Door]
end
subgraph sceneB [Scene B]
BR1[Scene B Right Door]
end
subgraph sceneA [Scene A]
AL1[Scene A Lower Left Door] <--> AR1[Scene A Right Door]
AL2[Scene A Upper Left Door] <--> AR1
end
subgraph sceneC [Scene C]
CL1[Scene C Left Door] <--> CR1[Scene C Upper Right Door]
CL1 <--> CR2[Scene C Lower Right Door]
end
subgraph sceneD [Scene D]
DL1[Scene D Left Door] <--> DR1[Scene D Right Door]
end
subgraph endingRoom [Ending Room]
EL1[Ending Room Upper Left Door] <--> Victory
EL2[Ending Room Lower Left Door] <--> Victory
end
Menu --> S
S <--> AL2
BR1 <--> AL1
AR1 <--> CL1
CR1 <--> DL1
DR1 <--> EL1
CR2 <--> EL2
classDef hidden display:none;
First, the world begins by splitting the Entrance
s which should be randomized. This is essentially all that has to be
done on the world side; calling the randomize_entrances
function will do the rest, using your region definitions and
logic to generate a valid world layout by connecting the partially connected edges you've defined. After you have done
that, your region graph might look something like the following diagram. Note how each randomizable entrance/exit pair
(represented as a bidirectional arrow) is disconnected on one end.
Note
It is required to use explicit indirect conditions when using Generic ER. Without this restriction, Generic ER would have no way to correctly determine that a region may be required in logic, leading to significantly higher failure rates due to mis-categorized regions.
%%{init: {"graph": {"defaultRenderer": "elk"}} }%%
graph LR
subgraph startingRoom [Starting Room]
S[Starting Room Right Door]
end
subgraph sceneA [Scene A]
AL1[Scene A Upper Left Door] <--> AR1[Scene A Right Door]
AL2[Scene A Lower Left Door] <--> AR1
end
subgraph sceneB [Scene B]
BR1[Scene B Right Door]
end
subgraph sceneC [Scene C]
CL1[Scene C Left Door] <--> CR1[Scene C Upper Right Door]
CL1 <--> CR2[Scene C Lower Right Door]
end
subgraph sceneD [Scene D]
DL1[Scene D Left Door] <--> DR1[Scene D Right Door]
end
subgraph endingRoom [Ending Room]
EL1[Ending Room Upper Left Door] <--> Victory
EL2[Ending Room Lower Left Door] <--> Victory
end
Menu --> S
S <--> T1:::hidden
T2:::hidden <--> AL1
T3:::hidden <--> AL2
AR1 <--> T5:::hidden
BR1 <--> T4:::hidden
T6:::hidden <--> CL1
CR1 <--> T7:::hidden
CR2 <--> T11:::hidden
T8:::hidden <--> DL1
DR1 <--> T9:::hidden
T10:::hidden <--> EL1
T12:::hidden <--> EL2
classDef hidden display:none;
From here, you can call the randomize_entrances
function and Archipelago takes over. Starting from the Menu region,
the algorithm will sweep out to find eligible region exits to randomize. It will then select an eligible target entrance
and connect them, prioritizing giving access to unvisited regions first until all regions are placed. Once the exit has
been connected to the new region, placeholder entrances are deleted. This process is visualized in the diagram below
with the newly connected edge highlighted in red.
%%{init: {"graph": {"defaultRenderer": "elk"}} }%%
graph LR
subgraph startingRoom [Starting Room]
S[Starting Room Right Door]
end
subgraph sceneA [Scene A]
AL1[Scene A Upper Left Door] <--> AR1[Scene A Right Door]
AL2[Scene A Lower Left Door] <--> AR1
end
subgraph sceneB [Scene B]
BR1[Scene B Right Door]
end
subgraph sceneC [Scene C]
CL1[Scene C Left Door] <--> CR1[Scene C Upper Right Door]
CL1 <--> CR2[Scene C Lower Right Door]
end
subgraph sceneD [Scene D]
DL1[Scene D Left Door] <--> DR1[Scene D Right Door]
end
subgraph endingRoom [Ending Room]
EL1[Ending Room Upper Left Door] <--> Victory
EL2[Ending Room Lower Left Door] <--> Victory
end
Menu --> S
S <--> CL1
T2:::hidden <--> AL1
T3:::hidden <--> AL2
AR1 <--> T5:::hidden
BR1 <--> T4:::hidden
CR1 <--> T7:::hidden
CR2 <--> T11:::hidden
T8:::hidden <--> DL1
DR1 <--> T9:::hidden
T10:::hidden <--> EL1
T12:::hidden <--> EL2
classDef hidden display:none;
linkStyle 8 stroke:red,stroke-width:5px;
This process is then repeated until all disconnected Entrance
s have been connected or deleted, eventually resulting
in a randomized region layout.
%%{init: {"graph": {"defaultRenderer": "elk"}} }%%
graph LR
subgraph startingRoom [Starting Room]
S[Starting Room Right Door]
end
subgraph sceneA [Scene A]
AL1[Scene A Upper Left Door] <--> AR1[Scene A Right Door]
AL2[Scene A Lower Left Door] <--> AR1
end
subgraph sceneB [Scene B]
BR1[Scene B Right Door]
end
subgraph sceneC [Scene C]
CL1[Scene C Left Door] <--> CR1[Scene C Upper Right Door]
CL1 <--> CR2[Scene C Lower Right Door]
end
subgraph sceneD [Scene D]
DL1[Scene D Left Door] <--> DR1[Scene D Right Door]
end
subgraph endingRoom [Ending Room]
EL1[Ending Room Upper Left Door] <--> Victory
EL2[Ending Room Lower Left Door] <--> Victory
end
Menu --> S
S <--> CL1
AR1 <--> DL1
BR1 <--> EL2
CR1 <--> EL1
CR2 <--> AL1
DR1 <--> AL2
classDef hidden display:none;
In general, even on minimal accessibility, ER will prefer to provide access to as many regions as possible. This is for 2 reasons:
- Generally, having items spread across the world is going to be a more fun/engaging experience for players than severely restricting their map. Imagine an ER arrangement with just the start region, the goal region, and exactly enough locations in between them to get the goal - this may be the intuitive behavior of minimal, or even the desired behavior in some cases, but it is not a particularly interesting randomizer.
- Giving access to more of the world will give item fill a higher chance to succeed.
However, ER will cull unreachable regions and exits if necessary to save the generation of a beaten minimal.
The first step to using generic ER is defining entrances to be randomized. In order to do this, you will need to
leave partially disconnected exits without a target_region
and partially disconnected entrances without a
parent_region
. You can do this either by hand using region.create_exit
and region.create_er_target
, or you can
create your vanilla region graph and then use disconnect_entrance_for_randomization
to split the desired edges.
If you're not sure which to use, prefer the latter approach as it will automatically satisfy the requirements for
coupled randomization (discussed in more depth later).
Tip
It's recommended to give your Entrance
s non-default names when creating them. The default naming scheme is
f"{parent_region} -> {target_region}"
which is generally not helpful in an entrance rando context - after all,
the target region will not be the same as vanilla and regions are often not user-facing anyway. Instead consider names
that describe the location of the exit, such as "Starting Room Right Door."
When creating your Entrance
s you should also set the randomization type and group. One-way Entrance
s represent
transitions which are impossible to traverse in reverse. All other transitions are two-ways. To ensure that all
transitions can be accessed in the game, one-ways are only randomized with other one-ways and two-ways are only
randomized with other two-ways. You can set whether an Entrance
is one-way or two-way using the randomization_type
attribute.
Entrance
s can also set the randomization_group
attribute to allow for grouping during randomization. This can be
any integer you define and may be based on player options. Some possible use cases for grouping include:
- Directional matching - only match leftward-facing transitions to rightward-facing ones
- Terrain matching - only match water transitions to water transitions and land transitions to land transitions
- Dungeon shuffle - only shuffle entrances within a dungeon/area with each other
- Combinations of the above
By default, all Entrance
s are placed in the group 0. An entrance can only be a member of one group, but a given group
may connect to many other groups.
Once you have defined all your entrances and exits and connected the Menu region to your region graph, you can call
randomize_entrances
to perform randomization.
In coupled randomization, an entrance placed from A to B guarantees that the reverse placement B to A also exists (assuming that A and B are both two-way doors). Uncoupled randomization does not make this guarantee.
When using coupled mode, there are some requirements for how placeholder ER targets for two-ways are named.
disconnect_entrance_for_randomization
will handle this for you. However, if you opt to create your ER targets and
exits by hand, you will need to ensure that ER targets into a region are named the same as the exit they correspond to.
This allows the randomizer to find and connect the reverse pairing after the first pairing is completed. See the diagram
below for an example of incorrect and correct naming.
Incorrect target naming:
%%{init: {"graph": {"defaultRenderer": "elk"}} }%%
graph LR
subgraph a [" "]
direction TB
target1
target2
end
subgraph b [" "]
direction TB
Region
end
Region["Room1"] -->|Room1 Right Door| target1:::hidden
Region --- target2:::hidden -->|Room2 Left Door| Region
linkStyle 1 stroke:none;
classDef hidden display:none;
style a display:none;
style b display:none;
Correct target naming:
%%{init: {"graph": {"defaultRenderer": "elk"}} }%%
graph LR
subgraph a [" "]
direction TB
target1
target2
end
subgraph b [" "]
direction TB
Region
end
Region["Room1"] -->|Room1 Right Door| target1:::hidden
Region --- target2:::hidden -->|Room1 Right Door| Region
linkStyle 1 stroke:none;
classDef hidden display:none;
style a display:none;
style b display:none;
When you created your entrances, you defined the group each entrance belongs to. Now you will have to define how groups
should connect with each other. This is done with the target_group_lookup
and preserve_group_order
parameters.
There is also a convenience function bake_target_group_lookup
which can help to prepare group lookups when more
complex group mapping logic is needed. Some recipes for target_group_lookup
are presented here.
For the recipes below, assume the following groups (if the syntax used here is unfamiliar to you, "bit masking" and "bitwise operators" would be the terms to search for):
class Groups(IntEnum):
# Directions
LEFT = 1
RIGHT = 2
TOP = 3
BOTTOM = 4
DOOR = 5
# Areas
FIELD = 1 << 3
CAVE = 2 << 3
MOUNTAIN = 3 << 3
# Bitmasks
DIRECTION_MASK = FIELD - 1
AREA_MASK = ~0 << 3
Directional matching:
direction_matching_group_lookup = {
# with preserve_group_order = False, pair a left transition to either a right transition or door randomly
# with preserve_group_order = True, pair a left transition to a right transition, or else a door if no
# viable right transitions remain
Groups.LEFT: [Groups.RIGHT, Groups.DOOR],
# ...
}
Terrain matching or dungeon shuffle:
def randomize_within_same_group(group: int) -> List[int]:
return [group]
identity_group_lookup = bake_target_group_lookup(world, randomize_within_same_group)
Directional + area shuffle:
def get_target_groups(group: int) -> List[int]:
# example group: LEFT | CAVE
# example result: [RIGHT | CAVE, DOOR | CAVE]
direction = group & Groups.DIRECTION_MASK
area = group & Groups.AREA_MASK
return [pair_direction | area for pair_direction in direction_matching_group_lookup[direction]]
target_group_lookup = bake_target_group_lookup(world, get_target_groups)
The correct step for this is World.connect_entrances
.
Currently, you could theoretically do it as early as World.create_regions
or as late as pre_fill
.
However, there are upcoming changes to Item Plando and Generic Entrance Randomizer to make the two features work better
together.
These changes necessitate that entrance randomization is done exactly in World.connect_entrances
.
It is fine for your Entrances to be connected differently or not at all before this step.
randomize_entrances
returns the completed ERPlacementState
. The pairings
attribute contains a list of the
created placements by name which can be used to populate slot data.
Generic ER is, as the name implies, generic! That means that your world may have some use case which is not covered by
the ER implementation. To solve this, you can create a custom Entrance
class which provides custom implementations
for is_valid_source_transition
and can_connect_to
. These allow arbitrary constraints to be implemented on
randomization, for instance helping to prevent restrictive sphere 1s or ensuring a maximum distance from a "hub" region.
Important
When implementing these functions, make sure to use super().is_valid_source_transition
and super().can_connect_to
as part of your implementation. Otherwise ER may behave unexpectedly.
This section is a medium-level explainer of the implementation of ER for those who don't want to decipher the code.
However, a basic understanding of the mechanics of fill_restrictive
will be helpful as many of the underlying
algorithms are shared
ER uses a forward fill approach to create the region layout. First, ER collects all_state
and performs a region sweep
from Menu, similar to fill. ER then proceeds in stages to complete the randomization:
- Attempt to connect all non-dead-end regions, prioritizing access to unseen regions so there will always be new exits to pair off.
- Attempt to connect all dead-end regions, so that all regions will be placed
- Connect all remaining dangling edges now that all regions are placed.
- Connect any other dead end entrances (e.g. second entrances to the same dead end regions).
- Connect all remaining non-dead-ends amongst each other.
The process for each connection will do the following:
- Select a randomizable exit of a reachable region which is a valid source transition.
- Get its group and check
target_group_lookup
to determine which groups are valid targets. - Look up ER targets from those groups and find one which is valid according to
can_connect_to
- Connect the source exit to the target's target_region and delete the target.
- In stage 1, before placing the last valid source transition, an additional speculative sweep is performed to ensure that there will be an available exit after the placement so randomization can continue.
- If it's coupled mode, find the reverse exit and target by name and connect them as well.
- Sweep to update reachable regions.
- Call the
on_connect
callback.
This process repeats until the stage is complete, no valid source transition is found, or no valid target transition is found for any source transition. Unlike fill, there is no attempt made to save a failed randomization.