### Install FOOOF (Editable Version)

Source: https://github.com/fooof-tools/fooof/blob/main/doc/index.md

Installs an editable version of FOOOF by cloning the repository and installing with the -e flag.

```shell
git clone https://github.com/fooof-tools/fooof
pip install -e .
```

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

### Install fooof (Development Version)

Source: https://github.com/fooof-tools/fooof/blob/main/README.rst

Install the current development version of fooof by cloning the repository and installing locally. This provides access to the latest features but may be less stable.

```shell
git clone https://github.com/fooof-tools/fooof
cd fooof
pip install .
```

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

### Install fooof (Stable Version)

Source: https://github.com/fooof-tools/fooof/blob/main/README.rst

Install the latest stable release of the fooof package using pip. This is the recommended version for most users.

```shell
pip install fooof
```

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

### Install fooof with Conda

Source: https://github.com/fooof-tools/fooof/blob/main/README.rst

Install the fooof package from the conda-forge channel using conda. This is an alternative installation method for users who prefer conda.

```shell
conda install -c conda-forge fooof
```

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

### Install fooof (Editable Version)

Source: https://github.com/fooof-tools/fooof/blob/main/README.rst

Install an editable version of fooof for development purposes. This allows you to modify the code and see changes reflected immediately without reinstalling.

```shell
git clone https://github.com/fooof-tools/fooof
cd fooof
pip install -e .
```

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

### Install specparam (Release Candidate)

Source: https://github.com/fooof-tools/fooof/blob/main/README.rst

Install the current release candidate version of specparam for the upcoming 2.0 release. Note that this version is not finalized and may undergo further changes.

```shell
pip install specparam
```

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

### Check specparam version

Source: https://github.com/fooof-tools/fooof/blob/main/doc/reference.md

Retrieve the currently installed version of the specparam module.

```python
# Check the version of the tool
from specparam import __version__ as specparam_version
print('Current specparam version:', specparam_version)
```

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

### FOOOF Class Documentation

Source: https://github.com/fooof-tools/fooof/blob/main/doc/_templates/autosummary/class.rst

Documentation for the main FOOOF class, including its initialization, methods, and attributes.

```APIDOC
## FOOOF Class

### Description
Represents the main FOOOF class for fitting the power spectrum.

### Methods

#### `__init__`
Initializes the FOOOF object.

#### Other Methods
(List of other methods will be dynamically generated based on the FOOOF class definition)

### Attributes
(List of attributes will be dynamically generated based on the FOOOF class definition)

### Examples
(Examples will be dynamically generated based on the FOOOF class definition)
```

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

### Function Documentation Template

Source: https://github.com/fooof-tools/fooof/blob/main/doc/_templates/autosummary/function.rst

Standard documentation format for FOOOF library functions.

```APIDOC
## Function Reference

### Description
This documentation covers the usage of the specified function within the FOOOF module.

### Usage
- **Module**: {{ module }}
- **Function**: {{ objname }}

### Examples
Refer to the included examples file: {{fullname}}.examples
```

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

### Fit and Report a Single Power Spectrum

Source: https://github.com/fooof-tools/fooof/blob/main/README.rst

Initialize the SpectralModel, define the frequency range, and then parameterize the power spectrum. The report method fits the model, plots the results, and prints a summary.

```python
from specparam import SpectralModel

fm = SpectralModel()

freq_range = [3, 40]

fm.report(freqs, spectrum, freq_range)
```

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

### FOOOF Fitting Method

Source: https://github.com/fooof-tools/fooof/blob/main/doc/_templates/data_object.rst

Details on how to use the `fit` method of the FOOOF object to analyze power spectra.

```APIDOC
## fit Method

### Description
Fits the FOOOF model to a given power spectrum.

### Method
`fit(freqs, power_spectrum)`

### Endpoint
N/A (Method of FOOOF class)

### Parameters
#### Path Parameters
N/A

#### Query Parameters
N/A

#### Request Body
N/A (Parameters are passed directly to the method)

- **freqs** (array-like) - Required - The frequency bins corresponding to the power spectrum.
- **power_spectrum** (array-like) - Required - The power spectral density values.

### Request Example
```python
import numpy as np
from fooof import FOOOF

# Example frequency bins and power spectrum data
freqs = np.arange(1, 50, 0.5)
# Simulate some power spectrum data (e.g., with a peak)
simulated_power = 10**(-1.5) * (freqs**(-1.5)) + 2 * (1 / (1 + ((freqs - 10)/1)**2))

fooof_obj = FOOOF()
fooof_obj.fit(freqs, simulated_power)
```

### Response
#### Success Response (fit)
The FOOOF object is updated with the fitting results, including model parameters, goodness of fit, and error metrics.

#### Response Example
```python
# After fitting, you can access results like:
print(f"Number of peaks found: {fooof_obj.n_peaks}")
print(f"R-squared: {fooof_obj.r_squared:.2f}")
# Example output:
# Number of peaks found: 1
# R-squared: 0.95
```
```

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

### Utilities

Source: https://github.com/fooof-tools/fooof/blob/main/doc/api.md

General utilities for spectral analysis and array manipulation.

```APIDOC
## Utilities

### Spectral Utilities

### Array Utilities


```

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

### Extract methods reporting information

Source: https://github.com/fooof-tools/fooof/blob/main/doc/reference.md

Print the necessary configuration and metadata from a model object for inclusion in a methods section.

```python
# Import the utility to print out information for reporting
from specparam.utils.reports import methods_report_info

# Print out all the methods information for reporting
methods_report_info(model_obj)
```

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

### Fit a Group of Power Spectra

Source: https://github.com/fooof-tools/fooof/blob/main/README.rst

Initialize SpectralGroupModel with desired parameters and fit it to a matrix of power spectra. This allows for group-level analysis of spectral data.

```python
from specparam import SpectralGroupModel

fg = SpectralGroupModel(peak_width_limits=[1.0, 8.0], max_n_peaks=8)

fg.fit(freqs, spectra)

fg.save_report()

fg.save(file_name='group_results', save_results=True)
```

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

### FOOOF Plotting Methods

Source: https://github.com/fooof-tools/fooof/blob/main/doc/_templates/data_object.rst

Documentation for methods used to visualize the FOOOF model fits and results.

```APIDOC
## Plotting Methods (e.g., `plot`, `plot_model`, `plot_components`)

### Description
Provides methods to visualize the power spectrum, the fitted FOOOF model, and its components.

### Method
- `plot(freqs, power_spectrum, **plot_kwargs)`
- `plot_model(ax=None, **plot_kwargs)`
- `plot_components(ax=None, **plot_kwargs)`

### Endpoint
N/A (Methods of FOOOF class)

### Parameters
- **freqs** (array-like) - Required for `plot` - The frequency bins.
- **power_spectrum** (array-like) - Required for `plot` - The power spectral density values.
- **ax** (matplotlib.axes.Axes, optional) - For `plot_model` and `plot_components`, allows plotting on a pre-existing axes.
- **plot_kwargs** (dict, optional) - Additional keyword arguments passed to the plotting functions.

### Request Example
```python
import matplotlib.pyplot as plt
from fooof import FOOOF

# Assuming fooof_obj is already fitted with freqs and power_spectrum
# fooof_obj.fit(freqs, power_spectrum)

# Plot the fit
fooof_obj.plot()
plt.show()

# Plot only the model
fig, ax = plt.subplots()
fooof_obj.plot_model(ax=ax)
plt.show()
```

### Response
#### Success Response (Plotting)
Generates matplotlib plots visualizing the power spectrum and the FOOOF model fit.

#### Response Example
(Visual output, no direct code example for the plot itself, but the code above generates it.)
```

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

### FOOOF Class Documentation

Source: https://github.com/fooof-tools/fooof/blob/main/doc/_templates/data_object.rst

Documentation for the main FOOOF class, which is used to fit the power spectrum of neural data.

```APIDOC
## FOOOF Class

### Description
Represents the core object for fitting the power spectrum of neural oscillations using the FOOOF model.

### Method
N/A (Class definition)

### Endpoint
N/A (Library class)

### Parameters
This class takes various parameters during initialization to configure the fitting process. Refer to the FOOOF documentation for a detailed list of parameters such as `peak_width_limits`, `max_n_peaks`, `min_peak_height`, etc.

### Request Example
```python
from fooof import FOOOF

# Example initialization with custom parameters
fooof_obj = FOOOF(peak_width_limits=[1, 8], max_n_peaks=3, min_peak_height=0.5)
```

### Response
#### Success Response (Initialization)
An instance of the FOOOF class is created.

#### Response Example
```python
# fooof_obj is now an initialized FOOOF object
print(type(fooof_obj))
# Output: <class 'fooof.core.FOOOF'>
```
```

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

### Define SpectralModel Settings

Source: https://github.com/fooof-tools/fooof/blob/main/README.rst

Initialize a SpectralModel object with custom settings for peak fitting and aperiodic parameterization. These settings control the fitting process and the resulting model.

```python
fm = SpectralModel(peak_width_limits=[1.0, 8.0], max_n_peaks=6, min_peak_height=0.1,
                   peak_threshold=2.0, aperiodic_mode='fixed')
```

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

### Input / Output (IO)

Source: https://github.com/fooof-tools/fooof/blob/main/doc/api.md

Functions related to input and output operations for power spectrum models.

```APIDOC
## Input / Output (IO)


```

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

### Plotting Functions

Source: https://github.com/fooof-tools/fooof/blob/main/doc/api.md

Visualizations for power spectra, model properties, objects, and annotated plots, along with utilities for plot styling.

```APIDOC
## Plotting Functions

Visualizations.

### Plot Power Spectra

Plots for visualizing power spectra and spectrograms.

Plots for plotting power spectra with shaded regions.

### Plot Model Properties & Parameters

### Plot Model Objects

### Annotated Plots

### Plot Utilities & Styling
```

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

### Data Objects

Source: https://github.com/fooof-tools/fooof/blob/main/doc/api.md

Objects to manage model information, simulation parameters, periodic components, and frequency bands.

```APIDOC
## Data Objects

Objects to manage model information, and simulation parameters.

### Model Information

Objects to store settings, metadata and results for power spectrum models.

### Simulation Parameters

Object to store information about simulated data.

### Periodic Components

Functions for accessing the periodic components of model fits.

**Object Inputs**

The following functions take in model objects directly, which is the typical use case.

**Array Inputs**

The following functions operate on arrays of peak parameters, which may be useful for more custom work-flows.

### Bands

An object for defining frequency band definitions.
```

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

### Generate automated methods report text

Source: https://github.com/fooof-tools/fooof/blob/main/doc/reference.md

Generate a pre-formatted methods report string using data from a model object.

```python
# Import the utility to print out information for reporting
from specparam.utils.reports import methods_report_text

# Generate methods text, with methods information inserted
methods_report_text(model_obj)
```

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

### Simulation Code

Source: https://github.com/fooof-tools/fooof/blob/main/doc/api.md

Code and utilities for simulating power spectra, including functions for generating, managing parameters for, and transforming power spectra.

```APIDOC
## Simulation Code

Code & utilities for simulating power spectra.

### Generate Power Spectra

Functions for simulating neural power spectra and spectrograms.

### Manage Parameters

Functions and objects for managing parameters for simulated power spectra.

### Transform Power Spectra

Functions for transforming power spectra.

### Simulation Utilities

Utilities for simulating power spectra.
```

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

### Metrics

Source: https://github.com/fooof-tools/fooof/blob/main/doc/api.md

The Metric object and related utilities provide functionality for defining metrics to evaluate model fitting performance, including error and goodness-of-fit functions.

```APIDOC
## Metrics

The Metric object & related utilties, providing functionality for definining metrics to evaluate model fitting performance.

### Metric Object

### Metric Functions (Error)

### Metric Functions (GoF)
```

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

### Model Objects

Source: https://github.com/fooof-tools/fooof/blob/main/doc/api.md

Objects that manage data and fit the model to parameterize neural power spectra. This includes the base SpectralModel object for individual spectra and SpectralGroupModel for groups of spectra.

```APIDOC
## Model Objects

Objects that manage data and fit the model to parameterize neural power spectra.

### Model Object

The SpectralModel object is the base object for the model, and can be used to fit individual power spectra.

### Group Object

The SpectralGroupModel object allows for parameterizing groups of power spectra.

### Time & Event Objects

The time & event objects allows for parameterizing power spectra organized across time and/or events.

### Object Utilities

Functions to manipulate, examine, and analyze model objects.
```

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

### Model Definitions

Source: https://github.com/fooof-tools/fooof/blob/main/doc/api.md

Spectral models are defined by the defining fit Modes. This section covers the Mode object and related utilities, as well as Fit Functions for aperiodic and peak components.

```APIDOC
## Model Definitions

Spectral models are defined by the defining fit Modes. This section

### Mode

The Mode object & related utilties, providing functionality for defining fit modes.

### Fit Functions (Aperiodic)

### Fit Functions (Peaks)
```

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

### Reports

Source: https://github.com/fooof-tools/fooof/blob/main/doc/api.md

Functionality for generating reports related to model methods.

```APIDOC
## Reports

### Methods Reports


```

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

### Measures

Source: https://github.com/fooof-tools/fooof/blob/main/doc/api.md

Functionality to analyze power spectrum models and their results, including model errors, parameters, and related utilities.

```APIDOC
## Measures

Functionality to analyze power spectrum models and the results parameters / components.

### Model Errors

Functions for analyzing the error of model fits.

**Object Inputs**

The following functions take in model objects directly.

**Array Inputs**

The following functions operate on arrays of models and data, which may be useful for more custom work-flows.

### Parameters

Measures & utilities for working with and converting parameters.
```

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

### Model Sub-Objects

Source: https://github.com/fooof-tools/fooof/blob/main/doc/api.md

The model object combines multiple sub-objects that define and store different elements of the model definition, data, and results. Key sub-objects include Algorithm, Modes, Data, and Results.

```APIDOC
## Model Sub-Objects

The model object combines multiple sub-objects that define and store different elements of the model definition, data, and results. Here, the main sub-objects are listed.

### Algorithm

### Modes

### Data

### Results
```

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