### Findpeaks Quickstart Example

Source: https://github.com/erdogant/findpeaks/blob/master/docs/source/Installation.rst

Demonstrates the basic workflow of the findpeaks library, including importing data, performing peak detection using the 'topology' method, and visualizing the results and persistence diagram.

```python
# Import library
from findpeaks import findpeaks

# Initialize with topology method (most robust)
fp = findpeaks(method='topology')

# Example data:
X = fp.import_example('1dpeaks')

# Peak detection
results = fp.fit(X)

# Plot results
fp.plot()

# Plot persistence diagram
fp.plot_persistence()
```

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

### Bash: Install findpeaks via pip

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/Installation.html

Instructions for installing the findpeaks library using pip, both from PyPI (recommended) and directly from GitHub for the latest development version.

```bash
# Installation from PyPI (recommended):
pip install findpeaks

# Install directly from GitHub (unstable version but it is the latest development version):
pip install git+https://github.com/erdogant/findpeaks
```

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

### Bash: Install findpeaks via pip

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/Installation.html

Instructions for installing the findpeaks library using pip, both from PyPI (recommended) and directly from GitHub for the latest development version.

```bash
# Installation from PyPI (recommended):
pip install findpeaks

# Install directly from GitHub (unstable version but it is the latest development version):
pip install git+https://github.com/erdogant/findpeaks
```

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

### Findpeaks Quickstart Example

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/_sources/Installation.rst.txt

Demonstrates the basic workflow of the findpeaks library, including importing data, performing peak detection using the 'topology' method, and visualizing the results and persistence diagram.

```python
# Import library
from findpeaks import findpeaks

# Initialize with topology method (most robust)
fp = findpeaks(method='topology')

# Example data:
X = fp.import_example('1dpeaks')

# Peak detection
results = fp.fit(X)

# Plot results
fp.plot()

# Plot persistence diagram
fp.plot_persistence()
```

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

### Findpeaks Quickstart Example

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/_sources/Installation.rst.txt

Demonstrates the basic workflow of the findpeaks library, including importing data, performing peak detection using the 'topology' method, and visualizing the results and persistence diagram.

```python
# Import library
from findpeaks import findpeaks

# Initialize with topology method (most robust)
fp = findpeaks(method='topology')

# Example data:
X = fp.import_example('1dpeaks')

# Peak detection
results = fp.fit(X)

# Plot results
fp.plot()

# Plot persistence diagram
fp.plot_persistence()
```

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

### Python: Initialize and Use findpeaks Library

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/Installation.html

Demonstrates initializing the findpeaks library with the topology method, importing example data, performing peak detection, and plotting the results and persistence diagram.

```python
from findpeaks import findpeaks

fp = findpeaks(method='topology')
X = fp.import_example('1dpeaks')

results = fp.fit(X)

fp.plot()
fp.plot_persistence()
```

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

### Python: Initialize and Use findpeaks Library

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/Installation.html

Demonstrates initializing the findpeaks library with the topology method, importing example data, performing peak detection, and plotting the results and persistence diagram.

```python
from findpeaks import findpeaks

fp = findpeaks(method='topology')
X = fp.import_example('1dpeaks')

results = fp.fit(X)

fp.plot()
fp.plot_persistence()
```

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

### Quick Start Peak Detection

Source: https://github.com/erdogant/findpeaks/blob/master/README.md

A quick start guide to using the findpeaks library. It shows how to initialize the library with the 'topology' method, load example data, perform peak detection, and plot the results.

```python
# Import library
from findpeaks import findpeaks

# Initialize with topology method (most robust)
fp = findpeaks(method='topology')

# Example data
X = fp.import_example('1dpeaks')

# Peak detection
results = fp.fit(X)

# Plot results
fp.plot()

# Plot persistence diagram
fp.plot_persistence()
```

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

### Bash: Create and Activate Conda Environment

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/Installation.html

Commands to create a new conda environment named 'env_findpeaks' with Python 3.6 and activate it for installing the findpeaks library.

```bash
conda create -n env_findpeaks python=3.6
conda activate env_findpeaks
```

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

### Bash: Create and Activate Conda Environment

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/Installation.html

Commands to create a new conda environment named 'env_findpeaks' with Python 3.6 and activate it for installing the findpeaks library.

```bash
conda create -n env_findpeaks python=3.6
conda activate env_findpeaks
```

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

### Import Example Dataset

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/findpeaks.findpeaks.html

Illustrates how to import example datasets provided by the findpeaks library. It shows the basic usage of the import_example function with the default '2dpeaks' dataset.

```Python
from findpeaks import findpeaks

X = fp.import_example('2dpeaks')
```

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

### Findpeaks Installation

Source: https://github.com/erdogant/findpeaks/blob/master/docs/source/Installation.rst

Instructions for installing the findpeaks library. It covers creating a conda environment, activating it, and installing the package via pip from PyPI or directly from GitHub.

```console
conda create -n env_findpeaks python=3.6
conda activate env_findpeaks
```

```console
# Installation from PyPI (recommended):
pip install findpeaks

# Install directly from GitHub (unstable version but it is the latest development version):
pip install git+https://github.com/erdogant/findpeaks
```

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

### Findpeaks Installation

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/_sources/Installation.rst.txt

Instructions for installing the findpeaks library. It covers creating a conda environment, activating it, and installing the package via pip from PyPI or directly from GitHub.

```console
conda create -n env_findpeaks python=3.6
conda activate env_findpeaks
```

```console
# Installation from PyPI (recommended):
pip install findpeaks

# Install directly from GitHub (unstable version but it is the latest development version):
pip install git+https://github.com/erdogant/findpeaks
```

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

### Import Example Dataset

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/findpeaks.findpeaks.html

Illustrates how to import example datasets provided by the findpeaks library. It shows the basic usage of the import_example function with the default '2dpeaks' dataset.

```Python
from findpeaks import findpeaks

X = fp.import_example('2dpeaks')
```

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

### Findpeaks Installation

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/_sources/Installation.rst.txt

Instructions for installing the findpeaks library. It covers creating a conda environment, activating it, and installing the package via pip from PyPI or directly from GitHub.

```console
conda create -n env_findpeaks python=3.6
conda activate env_findpeaks
```

```console
# Installation from PyPI (recommended):
pip install findpeaks

# Install directly from GitHub (unstable version but it is the latest development version):
pip install git+https://github.com/erdogant/findpeaks
```

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

### Build PDF Documentation with Sphinx

Source: https://github.com/erdogant/findpeaks/blob/master/docs/HOWTO.txt

This command demonstrates how to build a PDF version of the documentation using Sphinx. It specifies the PDF builder and the source and build directories.

```bash
sphinx-build -b pdf source build
```

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

### Importing and Preprocessing Images with findpeaks

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/_sources/Use-cases.rst.txt

This snippet demonstrates the initial steps of using the findpeaks library, including importing an example image and applying several preprocessing techniques. These include resizing, converting to grayscale, and scaling the image data to prepare it for peak detection.

```python
from findpeaks import findpeaks
fp = findpeaks(limit=160)
img = fp.import_example('2dpeaks_image')
import findpeaks
img = findpeaks.stats.resize(img, size=(300,300))
img = findpeaks.stats.togray(img)
img = findpeaks.stats.scale(img)
```

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

### Import Example Dataset

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/findpeaks.findpeaks.html

Imports a specified example dataset from the library's GitHub source. The function supports various dataset names and allows specifying a custom download URL or data directory.

```Python
from findpeaks import findpeaks

data = fp.import_example('2dpeaks')
# or
# data = fp.import_example(data='btc', url='http://example.com/data.csv')

```

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

### Import Example Dataset

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/findpeaks.findpeaks.html

Imports a specified example dataset from the library's GitHub source. The function supports various dataset names and allows specifying a custom download URL or data directory.

```Python
from findpeaks import findpeaks

data = fp.import_example('2dpeaks')
# or
# data = fp.import_example(data='btc', url='http://example.com/data.csv')

```

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

### Compare Peak Detection Methods with Interpolation

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/Examples.html

Illustrates the effect of interpolation on both 'peakdetect' and 'topology' methods. This example initializes findpeaks with the 'interpolate' parameter for both methods to show enhanced detection capabilities.

```Python
# Initialize with interpolate parameter
fp = findpeaks(method='peakdetect', lookahead=1, interpolate=10)
results = fp.fit(X)
fp.plot()
```

```Python
fp = findpeaks(method='topology', lookahead=1, interpolate=10)
results = fp.fit(X)
fp.plot()
```

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

### Find Peaks using Default Settings

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/Examples.html

This snippet demonstrates how to find peaks in data using the findpeaks library with its default settings. It includes importing the library, loading example data, initializing the findpeaks object, fitting the data, and plotting the preprocessing steps and the final results.

```Python
from findpeaks import findpeaks

X = fp.import_example()
print(X)

fp = findpeaks(method='mask')
fp.fit(X)

fp.plot_preprocessing()
fp.plot()
```

```Python
fp = findpeaks(method='topology')
fp.fit(X)

fp.plot()
fp.plot_mesh()
```

```Python
fp.plot_persistence()
```

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

### Compare Peak Detection Methods with Interpolation

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/Examples.html

Illustrates the effect of interpolation on both 'peakdetect' and 'topology' methods. This example initializes findpeaks with the 'interpolate' parameter for both methods to show enhanced detection capabilities.

```Python
# Initialize with interpolate parameter
fp = findpeaks(method='peakdetect', lookahead=1, interpolate=10)
results = fp.fit(X)
fp.plot()
```

```Python
fp = findpeaks(method='topology', lookahead=1, interpolate=10)
results = fp.fit(X)
fp.plot()
```

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

### Import Example Function

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/genindex.html

Provides an example of how to import and use functions within the findpeaks library. It demonstrates the usage pattern for methods within the findpeaks class.

```Python
def import_example():
    # Function implementation details...
```

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

### Redirect to HTML Index in index.html

Source: https://github.com/erdogant/findpeaks/blob/master/docs/HOWTO.txt

This HTML meta tag is used within the docs/index.html file to automatically redirect the user to the main HTML documentation located at ./html/index.html.

```html
<meta http-equiv="refresh" content="0; url=./html/index.html" />
```

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

### Import Example Function

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/genindex.html

Provides an example of how to import and use functions within the findpeaks library. It demonstrates the usage pattern for methods within the findpeaks class.

```Python
def import_example():
    # Function implementation details...
```

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

### Find Peaks using Default Settings

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/Examples.html

This snippet demonstrates how to find peaks using the default settings of the findpeaks library. It includes importing the library, loading example data, initializing the findpeaks object with the 'mask' method, fitting the data, and plotting the preprocessing steps and the final results.

```python
from findpeaks import findpeaks

X = fp.import_example()
print(X)

fp = findpeaks(method='mask')
fp.fit(X)

fp.plot_preprocessing()
fp.plot()
```

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

### Install findpeaks Python Library

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/index.html

This snippet provides instructions on how to install the findpeaks Python library using pip. It's a common first step for using the library.

```bash
pip install findpeaks
```

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

### Apply Lee Filter to Image (Example)

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/findpeaks.findpeaks.html

Demonstrates the application of the Lee filter to an image. The example shows preprocessing steps like resizing, converting to grayscale, scaling, and then applying the Lee filter.

```Python
import findpeaks
import matplotlib.pyplot as plt
img = findpeaks.import_example('2dpeaks_image')
# Resize
img = findpeaks.stats.resize(img, size=(300,300))
# Make grey image
img = findpeaks.stats.togray(img)
# Scale between [0-255]
img = findpeaks.stats.scale(img)
# Filter
img_filtered = findpeaks.stats.lee_filter(img.copy(), win_size=15, cu=0.25)

plt.figure()
fig, axs = plt.subplots(1,2)
axs[0].imshow(img, cmap='gray'); axs[0].set_title('Input')
axs[1].imshow(img_filtered, cmap='gray'); axs[1].set_title('Lee filter')
```

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

### Apply Lee Filter to Image (Example)

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/findpeaks.findpeaks.html

Demonstrates the application of the Lee filter to an image. The example shows preprocessing steps like resizing, converting to grayscale, scaling, and then applying the Lee filter.

```Python
import findpeaks
import matplotlib.pyplot as plt
img = findpeaks.import_example('2dpeaks_image')
# Resize
img = findpeaks.stats.resize(img, size=(300,300))
# Make grey image
img = findpeaks.stats.togray(img)
# Scale between [0-255]
img = findpeaks.stats.scale(img)
# Filter
img_filtered = findpeaks.stats.lee_filter(img.copy(), win_size=15, cu=0.25)

plt.figure()
fig, axs = plt.subplots(1,2)
axs[0].imshow(img, cmap='gray'); axs[0].set_title('Input')
axs[1].imshow(img_filtered, cmap='gray'); axs[1].set_title('Lee filter')
```

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

### Import Example and Pre-processing

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/Use-cases.html

This code imports an example image, resizes it, converts it to grayscale, and scales the pixel values between 0 and 255. These pre-processing steps are often necessary before applying denoising filters.

```Python
from findpeaks import findpeaks
fp = findpeaks(limit=160)
img = fp.import_example('2dpeaks_image')
import findpeaks

# Some pre-processing
# Resize
img = findpeaks.stats.resize(img, size=(300,300))
# Make grey image
img = findpeaks.stats.togray(img)
# Scale between [0-255]
img = findpeaks.stats.scale(img)
```

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

### Import Example and Pre-processing

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/Use-cases.html

This code imports an example image, resizes it, converts it to grayscale, and scales the pixel values between 0 and 255. These pre-processing steps are often necessary before applying denoising filters.

```Python
from findpeaks import findpeaks
fp = findpeaks(limit=160)
img = fp.import_example('2dpeaks_image')
import findpeaks

# Some pre-processing
# Resize
img = findpeaks.stats.resize(img, size=(300,300))
# Make grey image
img = findpeaks.stats.togray(img)
# Scale between [0-255]
img = findpeaks.stats.scale(img)
```

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

### Import Example Data and Perform 2D Peak Detection

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/findpeaks.findpeaks.html

Imports a 2D peaks example dataset and performs peak detection using the topology method. It then prints the number of significant features found. This demonstrates the basic workflow for 2D data analysis.

```Python
from findpeaks import findpeaks

# 2D peak detection
X = fp.import_example('2dpeaks')
fp = findpeaks(method='topology', limit=0.1)
results = fp.fit(X)
print(f"Found {len(results['persistence'])} significant features")
```

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

### Set Sphinx Build Directory in Makefile

Source: https://github.com/erdogant/findpeaks/blob/master/docs/HOWTO.txt

This line in the Makefile configures Sphinx to use the 'pages' directory as the build output directory for the documentation.

```makefile
BUILDDIR = pages
```

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

### Load Example Data and Fit with Caerus

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/Caerus.html

Imports example 'facebook' stock market data using the initialized findpeaks object and then applies the 'fit' method to detect peaks and valleys based on the Caerus algorithm's parameters. The results of the fitting process are stored within the findpeaks object.

```Python
# Import example data
X = fp.import_example('facebook')

# Fit
results = fp.fit(X)
```

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

### Import Example Data and Perform 2D Peak Detection

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/findpeaks.findpeaks.html

Imports a 2D peaks example dataset and performs peak detection using the topology method. It then prints the number of significant features found. This demonstrates the basic workflow for 2D data analysis.

```Python
from findpeaks import findpeaks

# 2D peak detection
X = fp.import_example('2dpeaks')
fp = findpeaks(method='topology', limit=0.1)
results = fp.fit(X)
print(f"Found {len(results['persistence'])} significant features")
```

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

### Load Example Data and Fit with Caerus

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/Caerus.html

Imports example 'facebook' stock market data using the initialized findpeaks object and then applies the 'fit' method to detect peaks and valleys based on the Caerus algorithm's parameters. The results of the fitting process are stored within the findpeaks object.

```Python
# Import example data
X = fp.import_example('facebook')

# Fit
results = fp.fit(X)
```

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

### Compare Peak Detection Methods with Interpolation (1D) (Python)

Source: https://github.com/erdogant/findpeaks/blob/master/docs/source/Examples.rst

Demonstrates how interpolation affects both 'peakdetect' and 'topology' methods for 1D peak detection. The example initializes findpeaks with the 'interpolate' parameter for both methods and plots the results.

```python
fp = findpeaks(method='peakdetect', lookahead=1, interpolate=10)
results = fp.fit(X)
fp.plot()

fp = findpeaks(method='topology', lookahead=1, interpolate=10)
results = fp.fit(X)
fp.plot()
```

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

### Import and Get Version

Source: https://github.com/erdogant/findpeaks/blob/master/README.md

Demonstrates how to import the findpeaks library and print its installed version. This is a common first step after installation.

```python
import findpeaks
print(findpeaks.__version__)

# Import library
from findpeaks import findpeaks
```

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

### Install findpeaks Library

Source: https://github.com/erdogant/findpeaks/blob/master/README.md

Installs the findpeaks Python library using pip. This is the primary method to get the library into your Python environment.

```bash
pip install findpeaks
```

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

### findpeaks.findpeaks.findpeaks.import_example Function

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/_sources/Function_Reference.rst.txt

Imports example datasets for testing and demonstration purposes. This function provides sample data to help users understand and test the library's functionality.

```Python
from findpeaks.findpeaks import findpeaks

# Import an example dataset
example_data = findpeaks.import_example('sample_1d')

```

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

### Build HTML Documentation with Sphinx

Source: https://github.com/erdogant/findpeaks/blob/master/docs/HOWTO.txt

This snippet shows the commands to clean and build the HTML documentation using Sphinx. It's a common workflow to repeat these steps until the documentation meets the desired standard.

```bash
make clean
make html
```

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

### findpeaks.findpeaks.findpeaks.import_example Function

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/_sources/Function_Reference.rst.txt

Imports example datasets for testing and demonstration purposes. This function provides sample data to help users understand and test the library's functionality.

```Python
from findpeaks.findpeaks import findpeaks

# Import an example dataset
example_data = findpeaks.import_example('sample_1d')

```

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

### findpeaks.findpeaks.findpeaks.import_example Function

Source: https://github.com/erdogant/findpeaks/blob/master/docs/source/Function_Reference.rst

Imports example datasets for testing and demonstration purposes. This function provides sample data to help users understand and test the library's functionality.

```Python
from findpeaks.findpeaks import findpeaks

# Import an example dataset
example_data = findpeaks.import_example('sample_1d')

```

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

### Find Peaks with Default Settings using findpeaks

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/_sources/Examples.rst.txt

Demonstrates importing data, initializing the findpeaks library with the 'mask' method, fitting the data, and plotting the preprocessing steps and results. It also shows initialization with the 'topology' method and fitting.

```python
from findpeaks import findpeaks

X = fp.import_example()
print(X)

fp = findpeaks(method='mask')
fp.fit(X)

fp.plot_preprocessing()
fp.plot()

fp = findpeaks(method='topology')
fp.fit(X)
```

```python
fp.plot()
```

```python
fp.plot_mesh()
```

```python
fp.plot_persistence()
```

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

### Initialize and Plot 1D Peaks Data

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/_sources/Topology.rst.txt

Initializes the findpeaks library with the 'topology' method and imports/plots a 1D example dataset. This sets up the data for topological analysis.

```Python
# Import library
from findpeaks import findpeaks
# Initialize
fp = findpeaks(method='topology')
# Example 1d-vector
X = fp.import_example('1dpeaks')
# Plot
plt.plot(X); plt.grid(True)
```

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

### Find Peaks with Default Settings using findpeaks

Source: https://github.com/erdogant/findpeaks/blob/master/docs/source/Examples.rst

Demonstrates importing data, initializing the findpeaks library with the 'mask' method, fitting the data, and plotting the preprocessing steps and results. It also shows initialization with the 'topology' method and fitting.

```python
from findpeaks import findpeaks

X = fp.import_example()
print(X)

fp = findpeaks(method='mask')
fp.fit(X)

fp.plot_preprocessing()
fp.plot()

fp = findpeaks(method='topology')
fp.fit(X)
```

```python
fp.plot()
```

```python
fp.plot_mesh()
```

```python
fp.plot_persistence()
```

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

### Find Peaks with Default Settings using findpeaks

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/_sources/Examples.rst.txt

Demonstrates importing data, initializing the findpeaks library with the 'mask' method, fitting the data, and plotting the preprocessing steps and results. It also shows initialization with the 'topology' method and fitting.

```python
from findpeaks import findpeaks

X = fp.import_example()
print(X)

fp = findpeaks(method='mask')
fp.fit(X)

fp.plot_preprocessing()
fp.plot()

fp = findpeaks(method='topology')
fp.fit(X)
```

```python
fp.plot()
```

```python
fp.plot_mesh()
```

```python
fp.plot_persistence()
```

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

### Initialize and Plot 1D Peaks Data

Source: https://github.com/erdogant/findpeaks/blob/master/docs/source/Topology.rst

Initializes the findpeaks library with the 'topology' method and imports/plots a 1D example dataset. This sets up the data for topological analysis.

```Python
# Import library
from findpeaks import findpeaks
# Initialize
fp = findpeaks(method='topology')
# Example 1d-vector
X = fp.import_example('1dpeaks')
# Plot
plt.plot(X); plt.grid(True)
```

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

### Visualizing Peaks with 3D Mesh Plots using findpeaks

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/_sources/Use-cases.rst.txt

This code illustrates how to generate 3D mesh plots using the findpeaks library to better understand the detected peaks and the effectiveness of denoising. It includes options for rotating the view to get a top-down perspective, aiding in the analysis of image features.

```python
fp.plot_mesh()
fp.plot_mesh(view=(90,0))
```

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

### Configure GitHub Pages Source

Source: https://github.com/erdogant/findpeaks/blob/master/docs/HOWTO.txt

This section describes how to configure your GitHub repository settings to deploy your documentation using GitHub Pages. It involves selecting the master branch and the docs folder as the source.

```text
Source: master branch/docs folder
```

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

### Install findpeaks using pip

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/index.html

This snippet shows the command to install the findpeaks library using pip, the Python package installer. Ensure you have Python and pip installed.

```bash
pip install findpeaks
```

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

### Install findpeaks using pip

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/index.html

This snippet shows the command to install the findpeaks library using pip, the Python package installer. Ensure you have Python and pip installed.

```bash
pip install findpeaks
```

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

### Initializing and Preprocessing Image

Source: https://github.com/erdogant/findpeaks/blob/master/docs/source/Use-cases.rst

Demonstrates the initialization of the findpeaks object and preprocessing steps for an image. This includes resizing, converting to grayscale, and scaling the image data to prepare it for peak detection and denoising.

```python
from findpeaks import findpeaks

fp = findpeaks(limit=160)
img = fp.import_example('2dpeaks_image')
import findpeaks

# Some pre-processing
# Resize
img = findpeaks.stats.resize(img, size=(300,300))
# Make grey image
img = findpeaks.stats.togray(img)
# Scale between [0-255]
img = findpeaks.stats.scale(img)
```

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

### Initializing and Preprocessing Image

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/_sources/Use-cases.rst.txt

Demonstrates the initialization of the findpeaks object and preprocessing steps for an image. This includes resizing, converting to grayscale, and scaling the image data to prepare it for peak detection and denoising.

```python
from findpeaks import findpeaks

fp = findpeaks(limit=160)
img = fp.import_example('2dpeaks_image')
import findpeaks

# Some pre-processing
# Resize
img = findpeaks.stats.resize(img, size=(300,300))
# Make grey image
img = findpeaks.stats.togray(img)
# Scale between [0-255]
img = findpeaks.stats.scale(img)
```

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

### Install findpeaks from GitHub

Source: https://github.com/erdogant/findpeaks/blob/master/README.md

Installs the findpeaks library directly from its GitHub repository source. This is useful for installing the latest development version.

```bash
pip install git+https://github.com/erdogant/findpeaks
```

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

### Install findpeaks from PyPI

Source: https://github.com/erdogant/findpeaks/blob/master/README.md

Installs the findpeaks library using pip from the Python Package Index (PyPI). This is the standard way to install Python packages.

```bash
pip install findpeaks
```

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

### Compare Peak Detection Methods (Peakdetect vs Topology)

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/Examples.html

Compares the 'peakdetect' and 'topology' methods for peak detection on the same dataset. It shows how to initialize findpeaks with different methods and visualize the results, including persistence plots for the topology method.

```Python
# Load library
from findpeaks import findpeaks
# Data
X = [10,11,9,23,21,11,45,20,11,12]
# Initialize
fp = findpeaks(method='peakdetect', lookahead=1)
results = fp.fit(X)
# Plot
fp.plot()
```

```Python
fp = findpeaks(method='topology', lookahead=1)
results = fp.fit(X)
fp.plot()
fp.plot_persistence()
```

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

### Install findpeaks Python Package

Source: https://github.com/erdogant/findpeaks/blob/master/docs/source/index.rst

This snippet shows the command to install the findpeaks library using pip, the Python package installer. It ensures you have the necessary tools to use the library for peak and valley detection.

```console
pip install findpeaks
```

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

### Compare Peak Detection Methods (Peakdetect vs Topology)

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/Examples.html

Compares the 'peakdetect' and 'topology' methods for peak detection on the same dataset. It shows how to initialize findpeaks with different methods and visualize the results, including persistence plots for the topology method.

```Python
# Load library
from findpeaks import findpeaks
# Data
X = [10,11,9,23,21,11,45,20,11,12]
# Initialize
fp = findpeaks(method='peakdetect', lookahead=1)
results = fp.fit(X)
# Plot
fp.plot()
```

```Python
fp = findpeaks(method='topology', lookahead=1)
results = fp.fit(X)
fp.plot()
fp.plot_persistence()
```

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

### Initialize and Use findpeaks Preprocessing

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/_sources/Pre-processing.rst.txt

Demonstrates how to initialize the findpeaks object with specific preprocessing parameters like image size, scaling, grayscale conversion, and denoising. It also shows how to import an example dataset, apply the preprocessing and peak detection using the fit method, and plot the results.

```python
from findpeaks import findpeaks
fp = findpeaks(method="topology", whitelist=['peak'], imsize=(50,100), scale=True, togray=True, denoise=None)
X = fp.import_example("2dpeaks")
results = fp.fit(X)
fp.plot(figure_order='horizontal')
```

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

### Install findpeaks Python Package

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/_sources/index.rst.txt

This snippet shows the command to install the findpeaks library using pip, the Python package installer. It ensures you have the necessary tools to use the library for peak and valley detection.

```console
pip install findpeaks
```

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

### Install findpeaks Python Package

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/_sources/index.rst.txt

This snippet shows the command to install the findpeaks library using pip, the Python package installer. It ensures you have the necessary tools to use the library for peak and valley detection.

```console
pip install findpeaks
```

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

### Initialize and Use findpeaks Preprocessing

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/_sources/Pre-processing.rst.txt

Demonstrates how to initialize the findpeaks object with specific preprocessing parameters like image size, scaling, grayscale conversion, and denoising. It also shows how to import an example dataset, apply the preprocessing and peak detection using the fit method, and plot the results.

```python
from findpeaks import findpeaks
fp = findpeaks(method="topology", whitelist=['peak'], imsize=(50,100), scale=True, togray=True, denoise=None)
X = fp.import_example("2dpeaks")
results = fp.fit(X)
fp.plot(figure_order='horizontal')
```

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

### Find Peaks in Facebook Stock Data with Caerus Method

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/_sources/Use-cases.rst.txt

This code example shows how to apply the findpeaks library using the 'Caerus' method to analyze Facebook stock data. It covers importing the library, initializing the findpeaks object, loading the example Facebook stock data, fitting the model to the data, and visualizing the detected peaks.

```python
# Import library
from findpeaks import findpeaks
# Initialize findpeaks with cearus method.
# The default setting is that it only return peaks-vallyes with at least 5% difference. We can change this using params
fp = findpeaks(method='caerus')
# Import example data
X = fp.import_example('facebook')
# Fit
results = fp.fit(X)
# Make the plot
fp.plot()
```

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

### Find Peaks in Facebook Stock Data with Caerus Method

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/_sources/Use-cases.rst.txt

This code example shows how to apply the findpeaks library using the 'Caerus' method to analyze Facebook stock data. It covers importing the library, initializing the findpeaks object, loading the example Facebook stock data, fitting the model to the data, and visualizing the detected peaks.

```python
# Import library
from findpeaks import findpeaks
# Initialize findpeaks with cearus method.
# The default setting is that it only return peaks-vallyes with at least 5% difference. We can change this using params
fp = findpeaks(method='caerus')
# Import example data
X = fp.import_example('facebook')
# Fit
results = fp.fit(X)
# Make the plot
fp.plot()
```

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

### Initialize and Fit Peak Detection Methods (Python)

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/_sources/Performance.rst.txt

Demonstrates initializing and fitting the 'peakdetect' and 'topology' methods from the findpeaks library on a small 1D dataset. It shows how to configure interpolation and lookahead parameters and then plots the results.

```python
from findpeaks import findpeaks
# peakdetect without interpolation
fp_peakdetect = findpeaks(method='peakdetect', interpolate=None, lookahead=1)
# peakdetect with interpolation
fp_peakdetect_int = findpeaks(method='peakdetect', interpolate=10, lookahead=1)
# topology without interpolation
fp_topology = findpeaks(method='topology', interpolate=None)
# topology with interpolation
fp_topology_int = findpeaks(method='topology', interpolate=10)

# Example 1d-vector with mixed peak sizes
X = [1,1,1.1,1,0.9,1,1,1.1,1,0.9,1,1.1,1,1,0.9,1,1,1.1,1,1,1,1,1.1,0.9,1,1.1,1,1,0.9,1,1.1,1,1,1.1,1,0.8,0.9,1,1.2,0.9,1,1,1.1,1.2,1,1.5,1,3,2,5,3,2,1,1,1,0.9,1,1,3,2.6,4,3,3.2,2,1,1,0.8,4,4,2,2.5,1,1,1]

# Fit the methods on the 1d-vector
results_1 = fp_peakdetect.fit(X)
results_2 = fp_peakdetect_int.fit(X)
results_3 = fp_topology.fit(X)
results_4 = fp_topology_int.fit(X)

# Plot results
fp_peakdetect.plot()
fp_peakdetect_int.plot()
fp_topology.plot()
fp_topology_int.plot()
```

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

### Install findpeaks Python Library

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/index.html

This snippet provides instructions on how to install the findpeaks Python library using pip. It's a common first step for using the library.

```bash
pip install findpeaks
```

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

### Initialize and Use findpeaks Preprocessing

Source: https://github.com/erdogant/findpeaks/blob/master/docs/source/Pre-processing.rst

Demonstrates how to initialize the findpeaks object with specific preprocessing parameters like image size, scaling, grayscale conversion, and denoising. It also shows how to import an example dataset, apply the preprocessing and peak detection using the fit method, and plot the results.

```python
from findpeaks import findpeaks
fp = findpeaks(method="topology", whitelist=['peak'], imsize=(50,100), scale=True, togray=True, denoise=None)
X = fp.import_example("2dpeaks")
results = fp.fit(X)
fp.plot(figure_order='horizontal')
```

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

### 1D Peak Detection with Interpolation (Python)

Source: https://github.com/erdogant/findpeaks/blob/master/docs/source/Examples.rst

Shows how interpolation using `interpolate_line1d` can improve peak detection results in 1D data. The example initializes findpeaks with an 'interpolate' parameter and plots the results.

```python
fp = findpeaks(lookahead=1, interpolate=10)
results = fp.fit(X)
fp.plot()
```

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

### 1D Peak Detection with Interpolation (Python)

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/_sources/Examples.rst.txt

Shows how interpolation can improve peak detection results in 1D data. This example initializes the findpeaks library with an interpolation parameter and then fits and plots the data.

```python
# Initialize with interpolation parameter
fp = findpeaks(lookahead=1, interpolate=10)
results = fp.fit(X)
fp.plot()
```

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

### Find Peaks in High Sampled Dataset (Peakdetect vs Topology)

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/Examples.html

Demonstrates peak detection on a large, noisy dataset using both 'peakdetect' and 'topology' methods. It shows how to generate synthetic data and visualize the detection results, including persistence for the topology method.

```Python
# Load library
import numpy as np
from findpeaks import findpeaks

# Data
i = 10000
xs = np.linspace(0,3.7*np.pi,i)
X = (0.3*np.sin(xs) + np.sin(1.3 * xs) + 0.9 * np.sin(4.2 * xs) + 0.06 * np.random.randn(i))

# Initialize
fp = findpeaks(method='peakdetect')
results = fp.fit(X)
# Plot
fp.plot1d()
```

```Python
fp = findpeaks(method='topology', limit=1)
results = fp.fit(X)
fp.plot1d()
fp.plot_persistence()
```

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

### 1D Peak Detection with Interpolation (Python)

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/_sources/Examples.rst.txt

Shows how interpolation can improve peak detection results in 1D data. This example initializes the findpeaks library with an interpolation parameter and then fits and plots the data.

```python
# Initialize with interpolation parameter
fp = findpeaks(lookahead=1, interpolate=10)
results = fp.fit(X)
fp.plot()
```

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

### Initialize and Fit Topology Method in Python

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/Topology.html

Demonstrates how to initialize the findpeaks object with the 'topology' method and then fit it to one-dimensional data (X). It also shows how to print the keys of the results dictionary.

```Python
from findpeaks import findpeaks
fp = findpeaks(method='topology', interpolate=None, limit=None, figsize=(15, 8))
results = fp.fit(X)
print(results.keys())
```

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

### Initialize and Fit Topology Method in Python

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/Topology.html

Demonstrates how to initialize the findpeaks object with the 'topology' method and then fit it to one-dimensional data (X). It also shows how to print the keys of the results dictionary.

```Python
from findpeaks import findpeaks
fp = findpeaks(method='topology', interpolate=None, limit=None, figsize=(15, 8))
results = fp.fit(X)
print(results.keys())
```

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

### Find Peaks with Advanced Pre-processing

Source: https://github.com/erdogant/findpeaks/blob/master/docs/pages/html/Examples.html

This snippet illustrates finding peaks with advanced pre-processing enabled. It includes initializing findpeaks with parameters like scaling, denoising, converting to grayscale, and resizing the image. The code demonstrates fitting the data and plotting the preprocessing pipeline and final results.

```python
from findpeaks import findpeaks

X = fp.import_example()

fp = findpeaks(method='topology', scale=True, denoise=10, togray=True, imsize=(50,100))

results = fp.fit(X)

fp.plot()
fp.plot_preprocessing()
```

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

### Compare Peak Detection Methods (1D) (Python)

Source: https://github.com/erdogant/findpeaks/blob/master/docs/source/Examples.rst

Compares the 'peakdetect' and 'topology' methods for peak detection on the same 1D dataset. It demonstrates the different characteristics of each approach and includes plotting of the results and persistence diagrams.

```python
from findpeaks import findpeaks
X = [10,11,9,23,21,11,45,20,11,12]
fp = findpeaks(method='peakdetect', lookahead=1)
results = fp.fit(X)
fp.plot()

fp = findpeaks(method='topology', lookahead=1)
results = fp.fit(X)
fp.plot()
fp.plot_persistence()
```