### Glob Examples

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/operation

Retrieve examples from the library based on the specified return type.

```python
glob_examples(
    return_type: Literal["module"], module: ModuleType | None = None, recursive: bool = True
) -> Iterable[ModuleType]
```

```python
glob_examples(
    return_type: Literal["engine"], module: ModuleType | None = None, recursive: bool = True
) -> Iterable[Engine]
```

```python
glob_examples(
    return_type: Literal["dataset"] | Literal["fld"], module: ModuleType | None = None, recursive: bool = True
) -> Iterable[ScalarArray]
```

```python
glob_examples(
    return_type: Literal["language"] | Literal["fll"], module: ModuleType | None = None, recursive: bool = True
) -> Iterable[str]
```

```python
glob_examples(
    return_type: Literal["files"], module: ModuleType | None = None, recursive: bool = True
) -> Iterable[Path]
```

```python
glob_examples(
    return_type: (
        Literal["module"]
        | Literal["engine"]
        | Literal["dataset"]
        | Literal["fld"]
        | Literal["language"]
        | Literal["fll"]
        | Literal["files"]
    ) = "engine",
    module: ModuleType | None = None,
    recursive: bool = True,
) -> Iterable[ModuleType | Engine | ScalarArray | str | Path]
```

--------------------------------

### glob_examples

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/operation

Glob the examples (alphabetically and in ascending order) returning the specified type. This method is useful for discovering and retrieving example data structures from the library.

```APIDOC
## glob_examples

### Description
Glob the examples (alphabetically and in ascending order) returning the specified type.

### Method
staticmethod

### Parameters
#### Query Parameters
- **return_type** (Literal['module'] | Literal['engine'] | Literal['dataset'] | Literal['fld'] | Literal['language'] | Literal['fll'] | Literal['files']) - Optional - type of objects to return. Default: 'engine'
- **module** (ModuleType | None) - Optional - package (eg, `fuzzylite.examples`) or module (eg, `fuzzylite.examples.terms.arc`) to glob. Default: None
- **recursive** (bool) - Optional - recursively glob into subdirectories. Default: True

### Yields
- **Type** (Iterable[ModuleType | Engine | ScalarArray | str | Path]) - Description: Iterable of the specified type.
```

--------------------------------

### Configure Comparator Parameters

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/activation

Configures the activation method with the specified comparator and threshold parameters. Example format: '> 0.5'.

```python
configure(parameters: str) -> None

```

--------------------------------

### Benchmark Class Method for_example in pyfuzzylite

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/benchmark/Benchmark

Creates and returns a Benchmark instance configured for a specific example module. Allows customization of data rows, shuffling, and seeding.

```python
for_example(example: ModuleType, rows: int | float = 1.0, shuffle: bool = True, seed: int | None = None) -> Benchmark
```

--------------------------------

### Initialize TermFactory - pyfuzzylite

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/factory/TermFactory

Constructs a new TermFactory instance. No specific setup or imports are required beyond the class definition.

```python
__init__() -> None


```

--------------------------------

### Get Comparator Parameters

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/activation

Returns the current comparator and threshold settings as a string. Useful for inspecting the configuration.

```python
parameters() -> str

```

--------------------------------

### Arc Constructor

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/term/Arc

Initializes a new Arc instance with optional name, start, end, and height parameters.

```python
__init__(name: str = '', start: float = nan, end: float = nan, height: float = 1.0) -> None
```

--------------------------------

### Configure Binary Term Parameters in pyfuzzylite

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/term/Binary

Configures the Binary Term using a string of parameters. The expected format is 'start direction [height]'.

```python
configure(parameters: str) -> None

Configure the term with the parameters.
Parameters:
Name | Type | Description | Default  
---|---|---|---  
`parameters` |  `str` |  `start direction [height]`. |  _required_  
```

--------------------------------

### Initialize First activation

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/activation/First

Constructor for the First activation method.

```python
__init__(rules: int = 1, threshold: float = 0.0) -> None
```

--------------------------------

### Initialize Node

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/term

Constructor for creating a new Node instance.

```python
__init__(
    element: Element | None = None,
    variable: str = "",
    constant: float = nan,
    left: Node | None = None,
    right: Node | None = None,
) -> None
```

--------------------------------

### GET /highest_activated_term

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/term

Finds the term with the maximum aggregated activation degree.

```APIDOC
## GET /highest_activated_term

### Description
Find the term with the maximum aggregated activation degree.

### Method
GET

### Endpoint
/highest_activated_term

### Response
#### Success Response (200)
- **Activated | None** - term with the maximum aggregated activation degree.
```

--------------------------------

### Get Node Value

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/term

Retrieves the string representation of the node's content.

```python
value() -> str
```

--------------------------------

### GET /grouped_terms

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/term

Retrieves grouped activated terms and their aggregated activation degrees.

```APIDOC
## GET /grouped_terms

### Description
Group the activated terms and aggregate their activation degrees.

### Method
GET

### Endpoint
/grouped_terms

### Response
#### Success Response (200)
- **dict[str, Activated]** - grouped activated terms by name with aggregated activation degrees.
```

--------------------------------

### Engine Initialization

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/engine/Engine

Constructor for creating a new Engine instance with optional variables and rule blocks.

```APIDOC
## __init__

### Description
Initializes a new Engine instance.

### Parameters
#### Request Body
- **name** (str) - Optional - name of the engine
- **description** (str) - Optional - description of the engine
- **input_variables** (Iterable[InputVariable] | None) - Optional - list of input variables
- **output_variables** (Iterable[OutputVariable] | None) - Optional - list of output variables
- **rule_blocks** (Iterable[RuleBlock] | None) - Optional - list of rule blocks
- **load** (bool) - Optional - whether to automatically update references to this engine and load the rules in the rule blocks.
```

--------------------------------

### RuleBlock __init__ Constructor

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/rule/RuleBlock

Initializes a new RuleBlock instance. Configure name, description, enabled status, and fuzzy logic operators.

```python
__init__(
    name: str = "",
    description: str = "",
    enabled: bool = True,
    conjunction: TNorm | None = None,
    disjunction: SNorm | None = None,
    implication: TNorm | None = None,
    activation: Activation | None = None,
    rules: Iterable[Rule] | None = None,
) -> None
```

--------------------------------

### Get package name

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/library/Representation

Returns the qualified class name for a given object.

```python
package_of(x: Any) -> str
```

--------------------------------

### Get List of Functions

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/factory/FunctionFactory

Retrieves a list of all available functions managed by the FunctionFactory.

```python
_create_functions() -> list[Element]
```

--------------------------------

### Import FuzzyLite Language File

Source: https://fuzzylite.github.io/pyfuzzylite

Loads a fuzzy logic engine configuration from a FuzzyLite Language (.fll) file.

```python
import fuzzylite as fl

engine = fl.FllImporter().from_file("examples/mamdani/ObstacleAvoidance.fll")

```

--------------------------------

### Get Final Representation

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/library

Assigns the final representation object to the 'repr' attribute.

```python
repr: Final = repr
```

--------------------------------

### Get method arity

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/operation

Returns the number of arguments expected by the provided callable.

```python
arity_of(method: Callable) -> int
```

--------------------------------

### Configure activation parameters

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/activation/First

Configures the activation method using a string of parameters.

```python
configure(parameters: str) -> None
```

--------------------------------

### General Activation Method

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/activation

Activates every rule of a rule block in insertion order.

```APIDOC
## General

Bases: `Activation`

Activation method that activates every rule of a rule block in insertion order.

### Functions

#### `activate(rule_block: RuleBlock)`

```
activate(rule_block: RuleBlock) -> None
```

Activate every rule in the rule block in the order they were added.

Parameters:
Name | Type | Description | Default
---|---|---|---
`rule_block` | `RuleBlock` | rule block to activate. | _required_
```

--------------------------------

### SShape Attributes

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/term/SShape

Represents the start and end points of the S-shaped membership function.

```python
start = start
```

```python
end = end
```

--------------------------------

### ActivationFactory Class

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/factory/ActivationFactory

Documentation for the ActivationFactory class and its initialization method.

```APIDOC
## ActivationFactory

### Description
Construction factory of activation methods for rule blocks. Inherits from ConstructionFactory[Activation].

### Functions
#### __init__
- **Description**: Constructor for the ActivationFactory class.
- **Signature**: __init__() -> None
```

--------------------------------

### Arc Attribute Definitions

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/term/Arc

Definitions for the start and end attributes of the Arc term.

```python
end = end
```

```python
start = start
```

--------------------------------

### Get InputVariable fuzzy value

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/variable

Computes and returns the current fuzzy input value.

```python
fuzzy_value() -> Array[str_]
```

--------------------------------

### Initialize ActivationFactory

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/factory

Constructor for the ActivationFactory class.

```python
__init__() -> None
```

--------------------------------

### Get InputVariable FuzzyLite string representation

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/variable

Returns the FuzzyLite language string for the variable.

```python
__str__() -> str
```

--------------------------------

### GET /engine/component

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/engine

Retrieves a specific component (InputVariable, OutputVariable, or RuleBlock) from the engine by its name.

```APIDOC
## GET /engine/component

### Description
Allows retrieval of engine components using their name as an identifier.

### Method
GET

### Parameters
#### Query Parameters
- **item** (str) - Required - The name of the component to find.

### Response
#### Success Response (200)
- **component** (InputVariable | OutputVariable | RuleBlock) - The first component found with the specified name.
```

--------------------------------

### Initialize OutputVariable

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/variable/OutputVariable

Constructor for creating an OutputVariable instance with specified parameters.

```python
__init__(
    name: str = "",
    description: str = "",
    enabled: bool = True,
    minimum: float = -inf,
    maximum: float = inf,
    lock_range: bool = False,
    lock_previous: bool = False,
    default_value: float = nan,
    aggregation: SNorm | None = None,
    defuzzifier: Defuzzifier | None = None,
    terms: Iterable[Term] | None = None,
) -> None

```

--------------------------------

### Initialize Settings Object

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/library

Initializes and assigns a Settings object to the 'settings' attribute.

```python
settings: Final = Settings()
```

--------------------------------

### Get List of Function Operators

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/factory/FunctionFactory

Retrieves a list of all available operators for functions managed by the FunctionFactory.

```python
_create_operators() -> list[Element]
```

--------------------------------

### ConstructionFactory __init__ Method

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/factory/ConstructionFactory

Initializes the ConstructionFactory. Optionally accepts a dictionary of constructors to pre-populate the factory.

```python
__init__(constructors: dict[str, type[T]] | None = None) -> None
```

--------------------------------

### Get class name

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/operation

Retrieves the class name of an object, with an option for fully qualified names.

```python
class_name(x: Any, /, qualname: bool = False) -> str
```

--------------------------------

### GaussianProduct Constructor

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/term/GaussianProduct

Initializing a GaussianProduct term with its name, means, standard deviations, and height.

```python
def __init__(
    name: str = "",
    mean_a: float = nan,
    standard_deviation_a: float = nan,
    mean_b: float = nan,
    standard_deviation_b: float = nan,
    height: float = 1.0,
) -> None:
```

--------------------------------

### Hedge Types and Examples

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/hedge/Hedge

This section lists the available hedge types and their corresponding fuzzy term modifications.

```APIDOC
## Hedge Types

### Description
This section illustrates how different hedges can be applied to various fuzzy terms.

### Available Hedges
- `fuzzylite.hedge.Not`
- `fuzzylite.hedge.Seldom`
- `fuzzylite.hedge.Somewhat`
- `fuzzylite.hedge.Very`
- `fuzzylite.hedge.Extremely`
- `fuzzylite.hedge.Any

### Examples of Hedge Application

#### Arc Term
- `fuzzylite.hedge.Seldom fuzzylite.term.Arc`
- `fuzzylite.hedge.Somewhat fuzzylite.term.Arc`
- `fuzzylite.hedge.Very fuzzylite.term.Arc`
- `fuzzylite.hedge.Extremely fuzzylite.term.Arc`
- `fuzzylite.hedge.Not fuzzylite.term.Arc`
- `fuzzylite.hedge.Any fuzzylite.term.Arc`

#### Binary Term
- `fuzzylite.hedge.Seldom fuzzylite.term.Binary`
- `fuzzylite.hedge.Somewhat fuzzylite.term.Binary`
- `fuzzylite.hedge.Very fuzzylite.term.Binary`
- `fuzzylite.hedge.Extremely fuzzylite.term.Binary`
- `fuzzylite.hedge.Not fuzzylite.term.Binary`
- `fuzzylite.hedge.Any fuzzylite.term.Binary`

#### Concave Term
- `fuzzylite.hedge.Seldom fuzzylite.term.Concave`
- `fuzzylite.hedge.Somewhat fuzzylite.term.Concave`
- `fuzzylite.hedge.Very fuzzylite.term.Concave`
- `fuzzylite.hedge.Extremely fuzzylite.term.Concave`
- `fuzzylite.hedge.Not fuzzylite.term.Concave`
- `fuzzylite.hedge.Any fuzzylite.term.Concave`

#### Ramp Term
- `fuzzylite.hedge.Seldom fuzzylite.term.Ramp`
- `fuzzylite.hedge.Somewhat fuzzylite.term.Ramp`
- `fuzzylite.hedge.Very fuzzylite.term.Ramp`
- `fuzzylite.hedge.Extremely fuzzylite.term.Ramp`
- `fuzzylite.hedge.Not fuzzylite.term.Ramp`
- `fuzzylite.hedge.Any fuzzylite.term.Ramp`

#### Sigmoid Term
- `fuzzylite.hedge.Seldom fuzzylite.term.Sigmoid`
- `fuzzylite.hedge.Somewhat fuzzylite.term.Sigmoid`
- `fuzzylite.hedge.Very fuzzylite.term.Sigmoid`
- `fuzzylite.hedge.Extremely fuzzylite.term.Sigmoid`
- `fuzzylite.hedge.Not fuzzylite.term.Sigmoid`
- `fuzzylite.hedge.Any fuzzylite.term.Sigmoid`

#### SShape - ZShape Term
- `fuzzylite.hedge.Seldom fuzzylite.term.SShape - fuzzylite.hedge.Seldom fuzzylite.term.ZShape`
- `fuzzylite.hedge.Somewhat fuzzylite.term.SShape - fuzzylite.hedge.Somewhat fuzzylite.term.ZShape`
- `fuzzylite.hedge.Very fuzzylite.term.SShape - fuzzylite.hedge.Very fuzzylite.term.ZShape`
- `fuzzylite.hedge.Extremely fuzzylite.term.SShape - fuzzylite.hedge.Extremely fuzzylite.term.ZShape`
- `fuzzylite.hedge.Not fuzzylite.term.SShape - fuzzylite.hedge.Not fuzzylite.term.ZShape`
- `fuzzylite.hedge.Any fuzzylite.term.SShape - fuzzylite.hedge.Any fuzzylite.term.ZShape`

#### SShape Term
- `fuzzylite.hedge.Seldom fuzzylite.term.SShape`
- `fuzzylite.hedge.Somewhat fuzzylite.term.SShape`
- `fuzzylite.hedge.Very fuzzylite.term.SShape`
- `fuzzylite.hedge.Extremely fuzzylite.term.SShape`
- `fuzzylite.hedge.Not fuzzylite.term.SShape`
- `fuzzylite.hedge.Any fuzzylite.term.SShape`

#### ZShape Term
- `fuzzylite.hedge.Seldom fuzzylite.term.ZShape`
- `fuzzylite.hedge.Somewhat fuzzylite.term.ZShape`
- `fuzzylite.hedge.Very fuzzylite.term.ZShape`
- `fuzzylite.hedge.Extremely fuzzylite.term.ZShape`
- `fuzzylite.hedge.Not fuzzylite.term.ZShape`
- `fuzzylite.hedge.Any fuzzylite.term.ZShape`
```

--------------------------------

### Rule Loading

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/rule/Rule

Loads the rule using an engine to identify and get references to input and output variables.

```APIDOC
## load

### Description
Load the rule using the engine to identify and get references to the input and output variables.

### Method
`load`

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Parameters
- **engine** (Engine) - Required - engine that the rule (partially) controls

### Request Example
None

### Response
#### Success Response (200)
None

#### Response Example
None
```

--------------------------------

### Importer from_file Method

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/importer/Importer

Reads and parses an engine configuration directly from a specified file path. Ensure the file contains a valid text representation of an engine.

```python
from_file(path: Path | str) -> Engine
```

--------------------------------

### Get the fuzzy value

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/term/Activated

Returns the fuzzy value formatted as {degree}/{name}, with an optional padding parameter.

```python
fuzzy_value(padding: bool = False) -> Array[str_]
```

--------------------------------

### Initialize Threshold Activation

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/activation/Threshold

Constructor for the Threshold activation method.

```python
__init__(comparator: Comparator | str = GreaterThan, threshold: float = 0.0) -> None
```

--------------------------------

### Get Rule Block

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/engine/Engine

Retrieves a rule block by its name or index. Performance is optimal when using indices.

```APIDOC
## rule_block

### Description
Finds the rule block of the given name or at the given index. Performance is O(1) when using indices and O(n) when using names.

### Method
`rule_block(name_or_index: str | int)`

### Endpoint
N/A (Method within an object)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

#### Parameters
- **name_or_index** (str | int) - Required - name or index of the rule block

### Request Example
```python
rule_block = engine.rule_block("my_rule_block")
# or
rule_block = engine.rule_block(0)
```

### Response
#### Success Response (RuleBlock)
- **RuleBlock** - The rule block object corresponding to the provided name or index.

#### Response Example
```json
{
  "name": "my_rule_block",
  "rules": [
    // ... list of rules ...
  ]
}
```

#### Errors
- **ValueError**: when there is no rule block with the given name.
- **IndexError**: when the index is out of range.
```

--------------------------------

### Get Available Operators Dictionary

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/factory/FunctionFactory

Returns a dictionary mapping operator names to their corresponding Element objects.

```python
operators() -> dict[str, Element]
```

--------------------------------

### Load Engine from String

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/importer/FllImporter

Creates an Engine object from a string describing the engine in FuzzyLite Language.

```APIDOC
## from_string

### Description
Return the engine described using the FuzzyLite Language.

### Method
```python
from_string(text: str) -> Engine
```

### Parameters
#### Path Parameters
- **text** (str) - Required - engine described using the FuzzyLite Language

### Returns
- **Engine** - engine described using the FuzzyLite Language
```

--------------------------------

### Get Available Functions Dictionary

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/factory/FunctionFactory

Returns a dictionary mapping function names to their corresponding Element objects.

```python
functions() -> dict[str, Element]
```

--------------------------------

### Activation Method Configuration

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/activation/Activation

Methods to configure the activation method using space-separated parameters or retrieve current parameters.

```python
configure(parameters: str) -> None
```

```python
parameters() -> str
```

--------------------------------

### Benchmark Prepare Method in pyfuzzylite

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/benchmark/Benchmark

Prepares the engine and dataset for benchmarking. This typically involves loading and configuring them.

```python
prepare() -> None
```

--------------------------------

### GaussianProduct Configure Method

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/term/GaussianProduct

Configuring a GaussianProduct term using a string of parameters. The expected format is 'mean_a standard_deviation_a mean_b standard_deviation_b [height]'.

```python
configure(parameters: str) -> None:
```

--------------------------------

### Get Operator Function Reference

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/activation

Returns the function reference for the comparator operator. This is useful for dynamic operations.

```python
operator: Callable[[Scalar, Scalar], bool | Array[bool_]]

```

--------------------------------

### Settings Constructor

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/library/Settings

Initializes the Settings object with specified floating-point type, decimal precision, tolerances, alias, logger, and factory manager.

```python
__init__(
    float_type: Any = float64,
    decimals: int = 3,
    atol: float = 0.001,
    rtol: float = 0.0,
    alias: str = "fl",
    logger: Logger | None = None,
    factory_manager: FactoryManager | None = None,
) -> None
```

--------------------------------

### Activation Methods Overview

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/activation

This section provides an overview of the different activation methods available in pyfuzzylite.

```APIDOC
## Activation Methods

Pyfuzzylite offers several activation methods to control how fuzzy rules are triggered based on their activation degrees. These methods determine which rules are considered active and are essential for the fuzzy inference process.

### Available Activation Methods:

*   **Highest**: Activates the rules with the highest activation degrees.
*   **Last**: Activates the first n rules (in reverse insertion order) whose activation degrees are greater than or equal to the threshold.
*   **Lowest**: Activates only the rules with the lowest activation degrees in ascending order.
*   **Proportional**: Activates rules using normalized activation degrees, where the sum of activation degrees equals one.
*   **Threshold**: Activates rules whose activation degrees satisfy a comparison operator and a threshold, deactivating the rest.
```

--------------------------------

### Settings Factory Manager Property

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/library/Settings

Get or set the factory manager for the library. This is essential for object creation and management.

```python
factory_manager: FactoryManager
```

--------------------------------

### Import Activation Method from FLL

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/importer

Imports an activation method described in the FuzzyLite Language.

```python
activation(fll: str) -> Activation | None
```

--------------------------------

### Initialize InputVariable

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/variable

Constructor for creating an InputVariable instance.

```python
__init__(
    name: str = "",
    description: str = "",
    enabled: bool = True,
    minimum: float = -inf,
    maximum: float = inf,
    lock_range: bool = False,
    terms: Iterable[Term] | None = None,
) -> None
```

--------------------------------

### CloningFactory Get Item

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/factory/CloningFactory

Retrieves an object from the factory using its string key. Raises a KeyError if the key is not found.

```python
__getitem__(key: str) -> T
```

--------------------------------

### Operator Class Constructor

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/rule/Operator

Documentation for the __init__ method of the Operator class.

```APIDOC
## __init__

### Description
Constructor for the Operator class, which represents a non-terminal node in an expression tree as a binary operator.

### Parameters
- **name** (str) - Optional - Name of the operator (default: '')
- **right** (Expression | None) - Optional - Right expression in the binary tree (default: None)
- **left** (Expression | None) - Optional - Left expression in the binary tree (default: None)

### Request Example
operator = Operator(name='and', left=expr1, right=expr2)
```

--------------------------------

### Get Variable

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/engine/Engine

Finds a variable by its name, searching through input and then output variables. For better performance, access variables by index.

```APIDOC
## variable

### Description
Finds the variable by the name, iterating first over the input variables and then over the output variables. The cost of this method is O(n), where n is the number of variables in the engine. For better performance, get the variables by index.

### Method
`variable(name: str)`

### Endpoint
N/A (Method within an object)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

#### Parameters
- **name** (str) - Required - name of the input or output variable

### Request Example
```python
input_var = engine.variable("temperature")
output_var = engine.variable("output_level")
```

### Response
#### Success Response (Variable)
- **Variable** - The variable object corresponding to the provided name.

#### Response Example
```json
{
  "name": "temperature",
  "range": [0, 100],
  "terms": [
    // ... list of terms ...
  ]
}
```

#### Errors
- **ValueError**: when there is no variable by the given name.
```

--------------------------------

### ZShape Membership Function

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/term

Represents a Z-shaped membership function. It is defined by a start point, an end point, and an optional height.

```APIDOC
## ZShape Membership Function

### Description
Edge Term that represents the ZShape membership function.
Equation
μ(x)={1if x≤sh−2h(x−se−s)2if s<x<s+e22h(x−ee−s)2if s+e2≤x<e0otherwise
where
  * h: height of the Term
  * s: start of the ZShape
  * e: end of the ZShape

### Attributes
#### end `instance-attribute`
```
end = end
```

#### start `instance-attribute`
```
start = start
```

### Functions
#### __init__
```
__init__(name: str = '', start: float = nan, end: float = nan, height: float = 1.0) -> None
```

Constructor.
Parameters:
Name | Type | Description | Default  
---|---|---|---  
`name` |  `str` |  name of the Term |  `''`  
`start` |  `float` |  start of the ZShape |  `nan`  
`end` |  `float` |  end of the ZShape |  `nan`  
`height` |  `float` |  height of the Term |  `1.0`  

#### configure
```
configure(parameters: str) -> None
```

Configure the term with the parameters.
Parameters:
Name | Type | Description | Default  
---|---|---|---  
`parameters` |  `str` |  `start end [height]`. |  _required_  

#### is_monotonic
```
is_monotonic() -> bool
```

Return `True` because the term is monotonic.
Returns:
Type | Description  
---|---  
`bool` |  `True`  

#### membership
```
membership(x: Scalar) -> Scalar
```

Computes the membership function evaluated at x.
Parameters:
Name | Type | Description | Default  
---|---|---|---  
`x` |  `Scalar` |  scalar |  _required_  
Returns:
Type | Description  
---|---  
`Scalar` |  μ(x)={1if x≤sh−2h(x−se−s)2if s<x<s+e22h(x−ee−s)2if s+e2≤x<e0otherwise  

#### parameters
```
parameters() -> str
```

Return the parameters of the term.
Returns:
Type | Description  
---|---  
`str` |  `start end [height]`.  

#### tsukamoto
```
tsukamoto(y: Scalar) -> Scalar
```

Compute the tsukamoto value of the monotonic term for activation degree y.
Equation
y={1if x≤sh−2h(x−se−s)2if s<x<s+e22h(x−ee−s)2if s+e2≤x<e0otherwise
x={e+(e−s)y2hif y≤h2s+(e−s)h−y2hotherwise
Parameters:
Name | Type | Description | Default  
---|---|---|---  
`y` |  `Scalar` |  activation degree |  _required_  
Returns:
Type | Description  
---|---  
`Scalar` |  x={e+(e−s)y2hif y≤h2s+(e−s)h−y2hotherwise  
```

--------------------------------

### FllImporter component Method (Activation)

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/importer/FllImporter

Imports an Activation component from an FLL string. Returns None if the FLL string is invalid.

```python
component(cls: type[Activation], fll: str) -> Activation | None
```

--------------------------------

### Initialize Proposition

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/rule/Proposition

Constructor for the Proposition class. It takes an optional variable, a list of hedges, and a term to define the proposition.

```python
__init__(variable: Variable | None = None, hedges: Iterable[Hedge] | None = None, term: Term | None = None) -> None
```

--------------------------------

### Get Variable Range Magnitude

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/variable

Returns the difference between the maximum and minimum values of the variable. This indicates the total span of possible values.

```python
drange: float
```

--------------------------------

### First Activation Method

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/activation/First

Details on the 'First' activation method, which activates the first n rules based on a threshold.

```APIDOC
## First Activation Method

### Description
Activates the first n rules (in insertion order) whose activation degrees are greater than or equal to the threshold.

### Method
N/A (Class method)

### Endpoint
N/A

### Parameters
N/A

### Attributes
#### `rules` (instance-attribute)
- **rules**: `int` - The maximum number of rules to activate.

#### `threshold` (instance-attribute)
- **threshold**: `float` - The minimum activation degree required to activate a rule.

### Functions
#### `__init__`
- **Description**: Constructor for the First activation method.
- **Parameters**:
  - `rules` (int): Maximum number of rules to activate. Default is 1.
  - `threshold` (float): Minimum activation degree required. Default is 0.0.

#### `activate`
- **Description**: Activates rules in a rule block based on the 'First' method's criteria.
- **Parameters**:
  - `rule_block` (RuleBlock): The rule block to activate. Required.

#### `configure`
- **Description**: Configures the activation method with specified parameters.
- **Parameters**:
  - `parameters` (str): A string containing the number of rules and threshold (e.g., "3 0.5"). Required.

#### `parameters`
- **Description**: Returns the configured number of rules and threshold.
- **Returns**:
  - `str`: A string representing the number of rules and threshold.
```

--------------------------------

### Get and Set Variable Value

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/variable

Accesses the current value of the variable. When 'lock_range' is true, the value will be clipped to the variable's defined range.

```python
value: Scalar
```

--------------------------------

### Get and Set Variable Range

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/variable

Manages the minimum and maximum bounds of the variable. The setter takes a tuple of (minimum, maximum) to define the range.

```python
range: tuple[float, float]
```

--------------------------------

### Retrieve activation parameters

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/activation/First

Returns the current number of rules and threshold as a string.

```python
parameters() -> str
```

--------------------------------

### GET /engine/input_values

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/engine

Retrieves the current 2D array of input values for the engine, where columns represent input variables and rows represent values.

```APIDOC
## GET /engine/input_values

### Description
Returns a 2D array of input values for each input variable.

### Method
GET

### Response
#### Success Response (200)
- **input_values** (ScalarArray) - 2D array of input values (rows) for each input variable (columns).
```

--------------------------------

### Initialize DefuzzifierFactory

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/factory/DefuzzifierFactory

Constructor for the DefuzzifierFactory. No arguments are required.

```python
__init__() -> None

```

--------------------------------

### Initialize Binary Term

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/term

Constructor for the Binary term. Initializes a binary membership function with a given name, start point, direction, and height.

```python
__init__(name: str = '', start: float = nan, direction: float = nan, height: float = 1.0) -> None
```

--------------------------------

### Settings Class Overview

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/library/Settings

Provides an overview of the Settings class and its purpose within the pyfuzzylite library.

```APIDOC
## Settings

### Description
Settings for the library.

### Attributes
#### `_factory_manager` (instance-attribute)
`_factory_manager = factory_manager`

#### `alias` (instance-attribute)
`alias = alias`

#### `atol` (instance-attribute)
`atol = atol`

#### `debugging` (property, writable)
`debugging: bool`

Get/Set the library in debug mode.
##### Getter
Returns:
Type | Description
---|---
`bool` | whether the library is in debug mode
##### Setter
Parameters:
Name | Type | Description | Default
---|---|---|---
`value` | `bool` | set logging level to `DEBUG` if `true`, and to `ERROR` otherwise | _required_

#### `decimals` (instance-attribute)
`decimals = decimals`

#### `factory_manager` (property, writable)
`factory_manager: FactoryManager`

Get/Set the factory manager.
##### Getter
Returns:
Type | Description
---|---
`FactoryManager` | factory manager
##### Setter
Parameters:
Name | Type | Description | Default
---|---|---|---
`value` | `FactoryManager` | factory manager | _required_

#### `float_type` (instance-attribute)
`float_type = float_type`

#### `logger` (instance-attribute)
`logger = logger or getLogger('fuzzylite')`

#### `rtol` (instance-attribute)
`rtol = rtol`

### Functions
#### `__init__`
```python
__init__(
    float_type: Any = float64,
    decimals: int = 3,
    atol: float = 0.001,
    rtol: float = 0.0,
    alias: str = "fl",
    logger: Logger | None = None,
    factory_manager: FactoryManager | None = None,
) -> None
```
Constructor.
Parameters:
Name | Type | Description | Default
---|---|---|---
`float_type` | `Any` | floating point type. | `float64`
`decimals` | `int` | number of decimals. | `3`
`atol` | `float` | absolute tolerance. | `0.001`
`rtol` | `float` | relative tolerance. | `0.0`
`alias` | `str` | alias to use when representing objects (ie, `__repr__()`). Cases: - fully qualified package when alias == "" (eg, `fuzzylite.term.Constant(name="A", height=1.0)`) - no prefixes when alias == "*" (eg, `Constant(name="A", height=1.0)`) - alias otherwise (eg, `{alias}.Constant(name="A", height=1.0)`) | `'fl'`
`logger` | `Logger | None` | logger. | `None`
`factory_manager` | `FactoryManager | None` | factory manager. | `None`

#### `__repr__`
```python
__repr__() -> str
```
Return code to construct the settings in Python.
Returns:
Type | Description
---|---
`str` | code to construct the settings in Python

#### `context`
```python
context(
    *, 
    float_type: Any | None = None,
    decimals: int | None = None,
    atol: float | None = None,
    rtol: float | None = None,
    alias: str | None = None,
    logger: Logger | None = None,
    factory_manager: FactoryManager | None = None
) -> Generator[None, None, None]
```
Create a context with specific settings.
Parameters:
Name | Type | Description | Default
---|---|---|---
`float_type` | `Any | None` | floating point type | `None`
`decimals` | `int | None` | number of decimals. | `None`
`atol` | `float | None` | absolute tolerance. | `None`
`rtol` | `float | None` | relative tolerance. | `None`
`alias` | `str | None` | alias for the library. | `None`
`logger` | `Logger | None` | logger. | `None`
`factory_manager` | `FactoryManager | None` | factory manager. | `None`

Returns:
Type | Description
---|---
`None` | context with specific settings.
```

--------------------------------

### Initialize Function

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/term

Constructor for creating a Function term.

```python
__init__(
    name: str = "",
    formula: str = "",
    engine: Engine | None = None,
    variables: dict[str, Scalar] | None = None,
    load: bool = False,
) -> None
```

--------------------------------

### PiShape Class Documentation

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/term/PiShape

Detailed documentation for the PiShape class, including its inheritance, equation, related terms, attributes, and methods.

```APIDOC
## PiShape

### Description
Extended term that represents the Pi-shaped membership function.

Equation:
μ(x)=h(SShapeab(x)×ZShapecd(x))
where
  * h: height of the Term
  * a,b: bottom left and top left parameters of the PiShape
  * c,d: top right and bottom right parameters of the PiShape

Related:
  * fuzzylite.term.SShape
  * fuzzylite.term.ZShape

### Attributes
#### `bottom_left` instance-attribute
```
bottom_left = bottom_left
```

#### `bottom_right` instance-attribute
```
bottom_right = bottom_right
```

#### `top_left` instance-attribute
```
top_left = top_left
```

#### `top_right` instance-attribute
```
top_right = top_right
```

### Functions
#### `__init__`
```python
__init__(
    name: str = "",
    bottom_left: float = nan,
    top_left: float = nan,
    top_right: float = nan,
    bottom_right: float = nan,
    height: float = 1.0,
) -> None
```
Constructor.

Parameters:
Name | Type | Description | Default  
---|---|---|---
`name` |  `str` |  name of the Term |  `''`  
`bottom_left` |  `float` |  bottom-left value of the PiShape |  `nan`  
`top_left` |  `float` |  top-left value of the PiShape |  `nan`  
`top_right` |  `float` |  top-right value of the PiShape |  `nan`  
`bottom_right` |  `float` |  bottom-right value of the PiShape |  `nan`  
`height` |  `float` |  height of the Term. |  `1.0`  

#### `configure`
```python
configure(parameters: str) -> None
```
Configure the term with the parameters.

Parameters:
Name | Type | Description | Default  
---|---|---|---
`parameters` |  `str` |  `bottom_left top_left top_right bottom_right [height]`. |  _required_  

#### `membership`
```python
membership(x: Scalar) -> Scalar
```
Computes the membership function evaluated at x.

Parameters:
Name | Type | Description | Default  
---|---|---|---
`x` |  `Scalar` |  scalar |  _required_  

Returns:
Type | Description  
---|---
`Scalar` |  μ(x)=h(SShapeab(x)×ZShapecd(x))  

#### `parameters`
```python
parameters() -> str
```
Return the parameters of the term.

Returns:
Type | Description  
---|---
`str` |  `bottom_left top_left top_right bottom_right [height]`. 
```

--------------------------------

### Get or set the activation degree

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/term/Activated

Access or modify the activation degree of the term. Non-finite values are automatically replaced with 0.0 for NaN/-inf and 1.0 for inf.

```python
degree: Scalar
```

--------------------------------

### Settings Debugging Property

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/library/Settings

Get or set the library's debug mode. Setting to true enables DEBUG logging, while false sets it to ERROR.

```python
debugging: bool
```

--------------------------------

### Initialize InputVariable

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/variable/InputVariable

Constructs an InputVariable with specified parameters. Use this to define input variables for your fuzzy logic system.

```python
__init__(name: str = "", description: str = "", enabled: bool = True, minimum: float = -inf, maximum: float = inf, lock_range: bool = False, terms: Iterable[Term] | None = None) -> None
```

--------------------------------

### Binary Term Attributes in pyfuzzylite

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/term/Binary

Shows the instance attributes 'direction' and 'start' for the Binary Term. These are fundamental properties defining the term's behavior.

```python
direction = direction
```

```python
start = start
```

--------------------------------

### Initialize ConstructionFactory

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/factory

Constructor for the ConstructionFactory class.

```python
constructors = constructors or {}

__init__(constructors: dict[str, type[T]] | None = None) -> None
```

--------------------------------

### Export Activation Method

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/exporter/FllExporter

Converts an Activation object to its FuzzyLite Language string representation. Requires an Activation object as input.

```python
activation(activation: Activation | None) -> str
```

--------------------------------

### Benchmark Class Method engine_and_data in pyfuzzylite

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/benchmark/Benchmark

A class method to create a fuzzy engine and load a dataset from a given example module. Useful for setting up benchmarks.

```python
engine_and_data(example: ModuleType) -> tuple[Engine, ScalarArray]
```

--------------------------------

### Retrieve Binary Term Parameters in pyfuzzylite

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/term/Binary

Returns the current parameters of the Binary Term as a formatted string. The output string represents 'start direction [height]'.

```python
parameters() -> str

Return the parameters of the term.
Returns:
Type | Description  
---|---  
`str` |  `start direction [height]`. 
```

--------------------------------

### Term Class Initialization

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/term/Term

Constructor for creating a new linguistic term instance.

```APIDOC
## __init__

### Description
Initializes a new instance of a linguistic term.

### Parameters
- **name** (str) - Optional - Name of the term (default: '')
- **height** (float) - Optional - Height of the term (default: 1.0)

### Request Example
term = Term(name="example", height=1.0)
```

--------------------------------

### Binary Term Constructor in pyfuzzylite

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/term/Binary

The constructor for the Binary Term, allowing initialization with name, start position, direction, and height. Default values are provided for convenience.

```python
__init__(name: str = '', start: float = nan, direction: float = nan, height: float = 1.0) -> None

Constructor.
Parameters:
Name | Type | Description | Default  
---|---|---|---  
`name` |  `str` |  name of the Term |  `''`  
`start` |  `float` |  start of the Binary |  `nan`  
`direction` |  `float` |  direction of the Binary (-inf, inf) |  `nan`  
`height` |  `float` |  height of the Term |  `1.0`  
```

--------------------------------

### Rule Constructor

Source: https://fuzzylite.github.io/pyfuzzylite/fuzzylite/__all__/rule

Initializes a new Rule object with optional parameters for enabled status, weight, antecedent, and consequent. Defaults are provided for convenience.

```python
__init__(enabled: bool = True, weight: float = 1.0, antecedent: Antecedent | None = None, consequent: Consequent | None = None) -> None
```