(Optional) Step 1: Data Analyzer

PyTrackDat includes an automatic data analyzer which can read a one or a series of CSV files in (i.e. data files with variable names in the headers), as well as their desired relation names, and generate a PyTrackDat design file, which contains human-readable CSV-formatted instructions for the structure of the database. This design file is not final, and should be checked over and added to/edited by a human. However, it provides a good starting point for generating a database for a particular dataset.

To run the data analyzer on one or more CSV-formatted data files, run the following command:

ptd-analyze design.csv sample_type_1 samples1.csv sample_type_2 samples2.csv [...]

Where design.csv is the name of the design file to output, and sample_type_1 and sample_type_2 are singular terms for the types of entries stored in samples1.csv and samples2.csv, respectively. Feel free to add more sample types (with corresponding data files) as necessary for your dataset, or leave out sample_type_2 and samples2.csv if only one data type is necessary for the database.