This project provides a complete workflow for processing and analyzing data from fiber photometry experiments using Doric files in HDF5 format. The analysis is structured around three different tasks: "Stim," "CS," and "Knob," with results visualized in a variety of formats.
This project aims to process, analyze, and visualize fiber photometry data, producing comprehensive insights into experimental results. It provides:
- Data Processing: Handling various formats, including CSV and HDF5, processing them into usable forms.
- Data Analysis: Generating PSTH (Peri-Stimulus Time Histogram) data, confidence intervals, and other statistical measures.
- Visualization: Creating bar charts, heatmaps, and other visualizations for raw and processed data.
-
Clone the Repository:
git clone <repository_url> cd FiberPhotometryDataAnalysis
-
Install Dependencies:
The project requires various Python packages. Install them using:
pip install -r requirements.txt
-
Data Setup:
Ensure you have your experimental data organized in a folder structure similar to the one described in the project.
- Data Loading: Loads datasets from the "CS" Folder from "Data".
- Data Processing: Generates PSTH data, confidence intervals, and standard deviations, along with raw data processing.
- Visualization: Creates bar charts, heatmaps, and PSTH graphs using matplotlib.
- Results: Processed data and visualizations are saved in the corresponding data and figs directories.
- Data Loading: Loads datasets from the "Knob" Folder from "Data".
- Data Processing: Generates PSTH data and associated statistics.
- Visualization: Creates various visualizations including bar charts, heatmaps, and PSTH graphs.
- Results: Processed data and visualizations are saved in the corresponding data and figs directories.
- Data Loading: Loads datasets from the "Stim" Folder from "Data".
- Data Processing: Generates statistical analyses, including PSTH data and related statistics.
- Visualization: Creates visualizations such as bar charts, heatmaps, and PSTH graphs.
- Results: Processed data and visualizations are saved in the corresponding data and figs directories.
-
- Purpose: Facilitates file selection and data loading for analysis tasks.
- Features: Integrates with
ipywidgets
to create interactive UI elements for selecting files and loads datasets using pandas.
-
- Purpose: Provides utility functions for processing and analyzing fiber photometry data.
- Features: Functions to compute standardized dF/F signals and integrates with numpy and pandas for data manipulations.
-
- Purpose: Designed to explore and process data from HDF5 files used in fiber photometry.
- Features: Uses
h5py
to handle HDF5 files and integrates withnumpy
andpandas
for data manipulations.
Is there anything specific you'd like to modify or add? Let me know if you'd like more details on any part of the documentation.
├── Data
│ ├── CS
│ │ ├── CS_file
│ │ │ ├── Data
│ │ │ │ └── *.csv
│ │ │ └── Figs
│ │ │ └── *.png
│ │ └── *.doric
│ ├── Knob
│ │ ├── Knob_file
│ │ │ ├── Data
│ │ │ │ └── *.csv
│ │ │ └── Figs
│ │ │ └── *.png
│ │ └── *.doric
│ └── stim
│ │ ├── Knob_file
│ │ │ ├── Data
│ │ │ │ └── *.csv
│ │ │ └── Figs
│ │ │ └── *.png
│ │ └── *.doric
├── Docs
├── .gitignore
├── CS-doric-psth.ipynb
├── Knob-doric-psth.ipynb
├── Stim-doric-psth.ipynb
├── dataexplorer.py
├── fileselector.py
└── photometry_functions.py
For contributions, please reach out to the project maintainers through the repository's issue tracker or directly.