Add more instructions

README.md

@@ -0,0 +1,25 @@
+## Pooled testing simulation
+
+Your goal is to implement a pooled testing strategy which minimizes the average number of tests for some specific prevalence _p_ and sample size _n_. Relevant slides can be found [here](https://docs.google.com/presentation/d/1ef4VCuorFMAF8eCewnktcQ7swXsg7pUmOdWHe1swtkQ/edit?usp=sharing).
+
+### Instructions
+
+1. Someone from the group should fork this repository.
+2. Copy the `StudentProtocols/Baseline.py` file to `StudentProtocols/<YOUR_GROUP_NAME>.py`.
+3. Implement the `isolate_positives` function in your protocol file. Essentially, the `isolate_positives` function is provided a `TestSample` object. Using the `query` method of the sample, you can query any set of numbers `0, 1, ..., n-1`, and the `query` method will return true of any of the queried numbers are "positive". In other words, you provide `query` a _pooled_ sample. Your task is to correctly return the IDs of the positive samples in the provided `TestSample` using as few tests as possible (on average). 
+4. Run the simulation in the `CovidTester.ipynb` notebook. You should get a table that looks like this
+
+```
++--------------+-------+----------+
+|  Group Name  |  Mean | Variance |
++--------------+-------+----------+
+| ProjectOwler | 7.129 |  30.643  |
+|   Baseline   |  32.0 |   0.0    |
++--------------+-------+----------+
+```
+
+5. Once you are satisfied, create a pull request back to this repo. *Only add+commit your new file!*
+```
+git add `StudentProtocols/<YOUR_GROUP_NAME>.py`
+git commit `StudentProtocols/<YOUR_GROUP_NAME>.py` -m "Updates"
+```

StudentProtocols/Baseline.py

@@ -30,4 +30,9 @@ def isolate_positives(self, sample: TestSample) -> set:
         # while minimizing the number of calls to sample.query
         #
         # Not correctly identifying the set of positive samples results in disqualification!
+        #
+        # The input will be a TestSample object, which allows you to query
+        # a subset of 0 ... n-1
+        #
+        # sample.query([1, 3, 4]) will return True if any of 1, 3, or 4 are positive
         return {i for i in range(self.n) if sample.query(set([i]))}