### Install PeakUtils from Source

Source: https://github.com/lucashn/peakutils/blob/master/README.rst

Use this command to install the PeakUtils package directly from its source code. Ensure you have Python 2.7 or later installed.

```bash
python setup.py install
```

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

### peakutils.prepare

Source: https://github.com/lucashn/peakutils/blob/master/docs/reference.rst

Provides functions for data preparation. The contents of this submodule are imported into the main peakutils module.

```APIDOC
## peakutils.prepare

### Description
Provides functions for data preparation. The contents of this submodule are imported into the main peakutils module.

### Module
peakutils.prepare

### Members
This submodule exposes its members directly. Use `peakutils.prepare.function_name` or rely on the members being imported into the main `peakutils` namespace.
```

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

### Detect Initial Peaks

Source: https://github.com/lucashn/peakutils/blob/master/docs/tutorial_a.rst

Uses peakutils.indexes to find the approximate indices of peaks in the noisy data. Prints the detected indices and corresponding x, y values.

```python
indexes = peakutils.indexes(y, thres=0.5, min_dist=30)
print(indexes)
print(x[indexes], y[indexes])
pyplot.figure(figsize=(10,6))
pplot(x, y, indexes)
pyplot.title('First estimate')
```

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

### Prepare Noisy Data

Source: https://github.com/lucashn/peakutils/blob/master/docs/tutorial_a.rst

Generates sample 1D data by combining two Gaussian functions with added random noise. Visualizes the generated data.

```python
centers = (30.5, 72.3)
x = numpy.linspace(0, 120, 121)
y = (peakutils.gaussian(x, 5, centers[0], 3) +
    peakutils.gaussian(x, 7, centers[1], 10) +
    numpy.random.rand(x.size))
pyplot.figure(figsize=(10,6))
pyplot.plot(x, y)
pyplot.title("Data with noise")
```

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

### Import Libraries

Source: https://github.com/lucashn/peakutils/blob/master/docs/tutorial_a.rst

Imports necessary libraries including numpy, peakutils, and plotting functions. Sets up inline plotting for matplotlib.

```python
import numpy
import peakutils
from peakutils.plot import plot as pplot
from matplotlib import pyplot
%matplotlib inline
```

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

### Add Baseline to Data

Source: https://github.com/lucashn/peakutils/blob/master/docs/tutorial_a.rst

Creates a new dataset by adding a polynomial baseline to the existing noisy data. Visualizes the data with the added baseline.

```python
y2 = y + numpy.polyval([0.002,-0.08,5], x)
pyplot.figure(figsize=(10,6))
pyplot.plot(x, y2)
pyplot.title("Data with baseline")
```

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

### peakutils.baseline

Source: https://github.com/lucashn/peakutils/blob/master/docs/reference.rst

Provides functions for baseline correction. The contents of this submodule are imported into the main peakutils module.

```APIDOC
## peakutils.baseline

### Description
Provides functions for baseline correction. The contents of this submodule are imported into the main peakutils module.

### Module
peakutils.baseline

### Members
This submodule exposes its members directly. Use `peakutils.baseline.function_name` or rely on the members being imported into the main `peakutils` namespace.
```

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

### peakutils.plot

Source: https://github.com/lucashn/peakutils/blob/master/docs/reference.rst

Provides plotting functions, requiring explicit import due to matplotlib dependency.

```APIDOC
## peakutils.plot

### Description
Provides plotting functions. This submodule must be explicitly imported due to its `matplotlib` dependency.

### Module
peakutils.plot

### Members
This submodule exposes its members directly. Use `peakutils.plot.function_name`.
```

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

### peakutils.peak

Source: https://github.com/lucashn/peakutils/blob/master/docs/reference.rst

Provides functions for peak detection. The contents of this submodule are imported into the main peakutils module.

```APIDOC
## peakutils.peak

### Description
Provides functions for peak detection. The contents of this submodule are imported into the main peakutils module.

### Module
peakutils.peak

### Members
This submodule exposes its members directly. Use `peakutils.peak.function_name` or rely on the members being imported into the main `peakutils` namespace.
```

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

### Estimate and Remove Baseline

Source: https://github.com/lucashn/peakutils/blob/master/docs/tutorial_a.rst

Estimates the baseline of the data using an iterative polynomial regression algorithm and then removes it. Visualizes the data with the baseline removed.

```python
base = peakutils.baseline(y2, 2)
pyplot.figure(figsize=(10,6))
pyplot.plot(x, y2-base)
pyplot.title("Data with baseline removed")
```

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

### Enhance Peak Resolution with Interpolation

Source: https://github.com/lucashn/peakutils/blob/master/docs/tutorial_a.rst

Applies interpolation to refine the detected peak locations, aiming for a more precise estimation of peak positions.

```python
peaks_x = peakutils.interpolate(x, y, ind=indexes)
print(peaks_x)
```

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