For highly articulated robots, there is a tradeoff between the capability to navigate complex unstructured environments and the high computational cost of coordinating many degrees-of-freedom. In this work, an approach that we refer to as shape-based control helps to balance this trade-off using shape functions, geometric abstractions that determine the coupling between multiple degrees-of-freedom during locomotion. This approach provides a way to intuitively adapt the shape of highly articulated robots using joint-level torque feedback control, allowing a robot to compliantly feel its way through unstructured terrain. In this work we specifically focus on compliance in the spatial frequency and temporal phase parameters of a snake-like robot's wave-like periodic wave-like kinematics. We show how varying the spatial frequency within the shape-based control architecture allows a single controller to vary the degree to which different degrees-of-freedom are coupled throughout a mechanism's body, i.e., the controller's degree of centralization. We experimentally find that for a snake-like robot locomoting through an irregularly spaced peg array, shape-based control results in more effective locomotion when compared to a central pattern generator-based approach.