ABRA is a web application created using Streamlit which allows users to batch-upload and analyze ABR data. Read the preprint here!
It can either be run on the web OR locally (instructions below).
If using the web interface, click here or scroll down to Usage instructions below.
Quick install instructions are below. For more detail see the full ABRA Instructions.
(Recommended) Install in a separate conda environment:
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If conda is not installed, first install miniconda
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Open “Anaconda Prompt (miniconda3)” to run miniconda after install
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Create and activate a conda environment for the abra installation:
conda create -y -n abra python=3.12 git
conda activate abra
- Clone this github repo and install:
git clone https://github.com/ucsdmanorlab/abranalysis.git
Type yes if prompted, then:
cd abranalysis
pip install -r requirements.txt
- Launch the streamlit app:
streamlit run ABRA.py
On future uses, you only need to open the Anaconda Prompt, then run the following to activate the ABRA environment, move to the ABRA installation directory, and launch the streamlit app.
conda activate abra
cd abranalysis
streamlit run ABRA.py
As new updates are released in the future, you can always pull the latest version by running git remote update from inside your abranalysis directory.
If you only want to use ABRA's analysis functions programmatically without the web interface:
conda create -y -n abra python=3.12
conda activate abra
pip install -r requirements-api.txt
See notebooks for usage.
- Upload a file (Tucker Davis .arf, EPFL .tsv or .asc, or standardized .csv). If you're uploading a .csv, there must be a
Level(dB)column and aFreq(Hz)column, and the vector of data points ends each corresponding row.
Click the thumbnail below to see an example of the .csv format: