{.homepage-heading}
# GuPPy

```{image} ../assets/GuppyLogo.png
:alt: GuPPy logo
:width: 300px
:align: center
```

**Guided Photometry Analysis in Python** is an open-source tool for processing and analyzing fiber photometry recordings. It provides a GUI-based pipeline covering raw data ingestion, signal preprocessing, PSTH computation, transient detection, visualization, and export to NWB. Data formats supported include TDT, Doric, Neurophotometrics (NPM), NWB, and generic CSV.

::::{grid} 1 1 2 2
:gutter: 3

:::{grid-item-card} {octicon}`download;1.5em;sd-mr-1` Installation
:link: installation
:link-type: doc

Set up a conda environment and install GuPPy from PyPI or from source.
:::

:::{grid-item-card} {octicon}`rocket;1.5em;sd-mr-1` Tutorials
:link: tutorials/index
:link-type: doc

Learning-oriented guides that walk you through a complete workflow from start to finish. Start here if you are new to GuPPy.
:::

:::{grid-item-card} {octicon}`checklist;1.5em;sd-mr-1` How-to Guides
:link: how-to/index
:link-type: doc

Task-oriented recipes for readers who already know what they want to accomplish.
:::

:::{grid-item-card} {octicon}`light-bulb;1.5em;sd-mr-1` Explanation
:link: explanation/index
:link-type: doc

Background and context: the science behind fiber photometry, the design of the GuPPy pipeline, and the reasoning behind key parameter choices.
:::

:::{grid-item-card} {octicon}`book;1.5em;sd-mr-1` Reference
:link: reference/index
:link-type: doc

Lookup material: every input parameter the GUI exposes, every file GuPPy writes, and the vocabulary GuPPy uses for its data entities.
:::

:::{grid-item-card} {octicon}`git-pull-request;1.5em;sd-mr-1` Contributor's Guide
:link: contributing/index
:link-type: doc

Get oriented in the codebase: pipeline architecture, the test suite, and how to add support for a new recording format.
:::

::::

```{toctree}
:maxdepth: 1
:hidden:

installation
tutorials/index
how-to/index
explanation/index
reference/index
Contributing <contributing/index>
Cite <citing>
```