In my experience it lines of code to number of tests isn't an easily correlated thing.  To give an example I built an ETL tool using Apache Spark and one of my team had invented a great way of testing it.  We had our business analysts and testers capture the different input data sets and expected outputs in Git markdown tables held as files in the project.  The project structure for where the markdown files resided mirrored the project structure of the ETL components.   This meant that a few simple tests could test a huge number of transforms and scenarios.
Similarly the PyTest framework allows metadata to be supplied so again, one test run multiple times for different scenarios.
The need to test and to do so efficiently was a considerable factor in the design of the solution.  The result is an ETL framework that we can extend amd refactor with confidence and with greater speed than we ever imagined.  So much so that the biggest time consumer is now business people deciding what they want and fighting about priorities