Types/NoiseExpression: Difference between revisions
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Revision as of 17:46, 1 September 2018
Types/NoiseExpression
Basics
A fragment of a functional program used to generate coherent noise, probably for purposes related to terrain generation.
Mandatory properties
type
Type: Types/string
Name of the type of this expression. Which other properties apply depend on the expression type.
Expression types
variable
Reference to a pre-defined variable, constant, or a named noise expression.
Predefined variables include "x", "y", and "distance".
Properties:
- variable_name: a Types/string
function-application
Apply a function to a list or associative array of arguments. Some functions expect arguments to be named and some expect them not to be.
Function calls are their own class of expression
(as opposed to every function just being its own expression type)
because function calls all have similar properties --
arguments are themselves expressions,
a call to any pure function (i.e. most functions other than random()
)
is referentially transparent
and can be constant-folded if all of its arguments are constant, etc.
Properties:
- function_name (a string; see functions, below)
- arguments (a list or associative array of argument expressions)
literal-number
Evaluates to the same number every time, given by the literal_value property.
literal-string
Evaluates to the same string every time, given by the literal_value property.
Since the noise generation runtime has no notion of strings or use for them, this is useful only in constant contexts.
literal-object
Evaluates to the same object every time, given by the literal_value property.
e.g.
{ type = "literal-object", literal_value = { name = "Bob Hope", birth_date = { year = 1903, month = 5, day_of_month = 29 } } }
Since the noise generation runtime has no notion of objects or use for them, this is useful only in constant contexts, such as the points argument of the distance-from-nearest-point function.
Functions
add
Arguments (positional): term, other term
Takes 2 positional arguments and adds them.
subtract
Arguments (positional): minuend, subtrahend
Takes 2 positional arguments and subtracts the second from the first.
multiply
Arguments (positional): factor, other factor
Takes 2 positional arguments and multiplies them.
divide
Arguments (positional): dividend, divisor
Takes 2 positional arguments and divides the first by the second.
exponentiate
Arguments (positional): base, exponent
Takes 2 positional arguments, and raises the first to the second power.
absolute-value
Arguments (positional): value to be absoluted
Takes a single positional argument and returns its absolute value. i.e. If the argument is negative, it is inverted.
clamp
Arguments (positional): value to be clamped, lower limit, upper limit
First argument is clamped between the second and third. The second is treated as a lower limit and the third the upper limit.
ridge
Arguments (positional): value to be ridged, lower limit, upper limit
Similar to clamp but the input value is folded back across the upper and lower limits until it lies between them.
factorio-basis-noise
Arguments (named):
- x
- y
- seed0 - integer between 0 and 4294967295 (inclusive) used to populate the backing random noise
- seed1 - integer between 0 and 255 (inclusive) used to provide extra randomness when sampling
- input_scale (default: 1) - x and y will be multiplied by this before sampling
- output_scale (default: 1) - output will be multiplied by this before being returned
Scaling input and output can be accomplished other ways, but are done so commonly as to be built into this function for performance reasons.
factorio-multioctave-noise
Arguments (named):
- x
- y
- seed0 - integer between 0 and 4294967295 (inclusive) used to populate the backing random noise
- seed1 - integer between 0 and 255 (inclusive) used to provide extra randomness when sampling
- octaves - how many layers of noise at different scales to sum
- persistence (constant) - how strong is each layer compared to the next larger one
- input_scale (default: 1) - x and y will be multiplied by this before sampling
- output_scale (default: 1) - output will be multiplied by this before being returned