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đŸ”ĸ Number Format

caution

These number formats work in most places, except for the early-developed item-data stuff. We'll try to redesign the number support during the next item system refactor, to better handle randomized items.

constant​

Provide a fixed numerical value.

type: constant
value: 1
tip

In most cases, you can use the following abbreviated notation.

count:
  type: constant
  value: 1

->

count: 1

uniform​

Provide a random number within the given range.

type: uniform
min: 1
max: 3
tip

In most cases, you can use the following abbreviated notation.

count:
  type: uniform
  min: 1
  max: 3

->

count: 1~3

Both min and max also support the nested use of number provider. 

count:
  type: uniform
  min:
    type: uniform
    min: 2
    max: 7
  max: "<papi:skilllevel_farming>*5~<papi:skilllevel_farming>*10"

expression​

https://ezylang.github.io/EvalEx/references/references.html

type: expression
expression: "20 + 70 / 2"
tip

In most cases, you can use the following abbreviated notation.

count:
  type: expression
  expression: "<papi:skilllevel_farming> / 20 + 5"

->

count: "<papi:skilllevel_farming> / 20 + 5"

gaussian​

Using Gaussian/Normal Distribution as a random number generator

type: gaussian

# Required parameter: Lower bound for random number generation
# Generated random values will not be less than this value
# Purpose: Ensures random numbers stay within a reasonable range for the application, avoiding abnormally small values
min: 10

# Required parameter: Upper bound for random number generation
# Generated random values will not be greater than this value
# Purpose: Ensures random numbers stay within a reasonable range for the application, avoiding abnormally large values
max: 20

# Optional parameter: Mean (expected value) of the Gaussian distribution
# Defines the center of the distribution, i.e., the value most likely to occur
# Default: (min + max) / 2.0 (the midpoint of the range)
# In this example: If not specified, the default value would be 15
mean: 15

# Optional parameter: Standard deviation of the Gaussian distribution
# Measures the dispersion of data. A smaller value means data is more concentrated, a larger value means data is more spread out.
# Default: (max - min) / 6.0, based on the "6Īƒ principle" (99.7% of values fall within ÎŧÂą3Īƒ)
# In this example: If not specified, the default value would be (20-10)/6≈1.67
std-dev: 1

# Optional parameter: Maximum number of attempts to generate a valid random number, defaults to 128
# Since the theoretical range of the Gaussian distribution is (-∞, +∞), but is truncated by min/max,
# values generated outside the [min, max] range will be regenerated.
# This parameter prevents infinite loops in extreme cases.
# If no valid value is generated after the maximum attempts, the closest boundary value (min or max) is typically returned.
max-attempts: 128