# Types/AutoplaceSpecification

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Autoplace specification is used to determine which entities are placed when generating map. Currently it is used for enemy bases, resources and other entities (trees, fishes, ...).

## General structure

Autoplace specification describe conditions for placing tiles, entities, and decoratives during surface generation. Probability (of placement on any given tile) and richness (which has different meaning depending on the thing being placed) can be defined either in terms of a set of peaks, or using explicit expressions.

## General properties

### control

**Type**: Types/string

**Default**: ""

ID of autoplace control that applies to this entity.

### default_enabled

**Type**: Types/bool

**Default**: true

Indicates whether the thing should be placed even if MapGenSettings do not provide frequency/size/richness for it (either for the specific prototype of for the control named by AutoplaceSpecification.control).

If true, normal frequency/size/richness (value=1) are used in that case. Otherwise it is treated as if 'none' were selected.

### force

**Type**: Types/string

**Default**: "neutral"

Force of the placed entity. One of "enemy", "player", "neutral", or a custom force name. Only matters for Prototype/EntityWithOwner.

### order

**Type**: Types/Order

**Default**: ""

Order for placing the entity (has no effect when placing tiles). Entities whose order compares less are placed earlier (this influences placing multiple entities which collide with itself), from entities with equal order string only one with the highest probability is placed.

### placement_density

**Type**: Types/uint32

**Default**: 1

For entities and decoratives, how many times to attempt to place on each tile (probability and collisions are taken into account each attempt).

### tile_restriction

**Type**: list of specifications, see below

**Default**: empty list

Restricts tiles or tile transitions the entity can appear on.

Contains list of specifications. Each specification is a single Types/string with the name of an allowed tile, or a list of two tile names for entities allowed on transitions.

## Properties for Expression-based AutoplaceSpecifications

### probability_expression

**Type**: Types/NoiseExpression

If specified, provides a noise expression that will be evaluated at every point on the map to determine probability. If left blank, probability is determined by the 'peaks' system based on the properties listed below.

### richness_expression

**Type**: Types/NoiseExpression

If specified, provides a noise expression that will be evaluated to determine richness.

If probability_expression is specified and richness_expression is not, then probability_expression will be used as the richness expression.

If neither are specified, then probability and richness are both determined by the 'peaks' system based on the properties listed below.

## Properties for Peak-based AutoplaceSpecifications

### sharpness

**Type**: Types/double

**Default**: 0

Parameter of the sharpness filter for post-processing probability of entity placement. Value of 0 disables the filter, with value 1, the filter is a step function centered around 0.5.

### max_probability

**Type**: Types/double

**Default**: 1

Multiplier for output of the sharpness filter.

### richness_base

**Type**: Types/double

**Default**: 0

### richness_multiplier

**Type**: Types/double

**Default**: 0

### richness_multiplier_distance_bonus

**Type**: Types/double

**Default**: 0

Bonus to richness multiplier per tile of distance from starting point. See #Richness calculation.

### random_probability_penalty

**Type**: Types/double

**Default**: 0

A random value between 0 and this number is subtracted from a probability after sharpness filter. Only works for entities.

### peaks

**Type**: list of #Autoplace Peaks

If this property is missing, then the whole autoplace specification is interpreted as a single peak.

### coverage

** Type**: Types/double

**Default**: Calculated from existing peaks.

Sets a fraction of surface that should be covered by this item.

Internally this adds an additive influence modifier, so that expected fraction of tiles where total influence > 0.5 (the threshold for sharpness filter) equals the parameter.

Because of the autoplace system's complexity, this is only accurate on simple rules and does some simplification on the more complex ones:

- There is always just one combination of tile properties (see #Dimensions) for which the coverage is calculated. This combination is given by a first *_optimal value encountered of each type other than starting_area and tier_from_start. Starting_area value is fixed to 0 and tier_from_start to 4.
- min_influence and max_influence are completely ignored.

### starting_area_amount

** Type**: Types/uint32

**Default**: 0

If this value is non zero, influence of this entity will be calculated differently in starting area: For each entity with this parameter a position in starting area is selected and a blob is placed centered on this position. The central tile of this blob will have approximately amount of resources selected by this value.

### starting_area_size

** Type**: Types/double

**Default**: 10

See #starting_area_amount. Controls approximate radius of the blob in tiles.

## Autoplace peaks

### influence

**Type**: Types/double

**Default**: 1

Influence multiplier. See #Influence calculation.

### min_influence

**Type**: Types/double

**Default**: min double

Minimal influence (after all calculations) of current peak. See #Influence calculation.

### max_influence

**Type**: Types/double

**Default**: max double

Maximal influence (after all calculations) of current peak. See #Influence calculation.

### richness_influence

**Type**: Types/double

**Default**: 0

Bonus for influence multiplier when calculating richness. See #Influence calculation.

### noise_layer

**Type**: Types/string

**Default**: ""

Name of noise layer to use for this peak. If empty, then no noise is added to this peak.

### noise_persistence

**Type**: Types/double

**Default**: 0.5

Must be between 0 and 1. Persistence of the noise.

### noise_octaves_difference

**Type**: Types/double

**Default**: 0

Difference between number of octaves of the world and of the noise.

### noise_scale

**Type**: Types/double

**Default**: 1

### *_optimal

**Type**: Types/double

Optimal value of a tile property. If the property is close to this value, peak influence is 1. See #Dimensions.

### *_range

**Type**: Types/double

**Default**: 0

Distance from the optimal parameters that is still considered optimal. See #Dimensions.

### *_max_range

**Type**: Types/double

Distance from the optimal parameters that get influence of -1. See #Dimensions.

### *_top_property_limit

**Type**: Types/double

**Default**: max double

Limit distance from the optimum on a single (positive) side. This is pure magic. See #Dimensions.

## Dimensions

Peaks may reference a number of tile properties, specifying range of optimal values of the property and a range over which it is interpolated to no effect. All tile properties are of Types/double.

Currently the properties are:

- starting_area_weight — Number from 1 (inside starting area) to 0 (not influenced by starting area).
- elevation — elevation of the terrain, up to 5000. Values smaller than 0 mean under water (elevation < 0 doesn't imply water tile, though)
- water — amount of available water on tile. Very simple dependence on elevation for now.
- temperature — average temperature on tile. Depends on elevation and some noise.
- aux
- tier_from_start — Distance from start in starting area sizes, rounded to integers.
- distance

## Influence calculation

There are two possible modes in which influence is calculated. By default influence is calculated as a sum of influences of peaks (see next paragraph). When #starting_area_amount parameter is non zero a position in starting area is selected and a blob is placed centered on this position. Influence is then a maximum of the default calculated value and a value obtained from this blob.

Influence of a peak is obtained by calculating a distance from each of its dimensions and sum of these individual distances is used as a distance from optimal conditions. Based on this distance a peak gets influence between -1 and 1, which is then multiplied by the noise function, if it is specified, and by the influence constant (or by influence + richness_influence if calculating richness). Finally this value is clamped to a range between min_influence and max_influence.

## Richness calculation

If an entity is to be placed at a position and it's a resource or a part of an enemy base, then richness is calculated in the next step. as sum of influences * (richness_multiplier + distance * richness_multiplier_distance_bonus) + richness_base.

Note, that when calculating richness, influences of individual peaks use richness_influence bonus.