Human-Swarm Teams uniquely combine the ability of swarms and cognition of humans to achieve complex behaviors. To study unique characteristics of a human-swarm team, there is a need for a human-in-the-loop simulation framework that can capture both the human's action and cognition while interacting with the swarm of robots as well as the actions of the swarm itself. In this repository, we present SHaSTA, an open source simulation platform to study human-swarm applications. The platform provides a unified interface for humans and learning algorithms to command learn swarm robot behaviors. The higher level swarm behavior is achieved by including single robot and swarm primitives such as formation control and path planning. SHaSTA provides a unique ability to collect physiological information from humans and time synchronize it with swarm simulation. Using search-and-rescue as an example, we demonstrate the scalability and utility of SHaSTA in simulating human-swarm applications. We also demonstrate its ability to integrate physiological measurements as part of the simulation through a detailed human-study.