Acoustic Holography is an emerging field where mid-air ultrasound is controlled and manipulated for novel and exciting applications. These range from mid-air haptics, volumetric displays, contactless fabrication, and even chemical and biomedical applications such as drug delivery. To develop these applications, a software framework to predict acoustic behaviour and simulating resulting effects, such as applied forces or scattering patterns is desirable. There have been various software libraries and platforms that attempt to fill this role, but there is yet to be a single piece of software that acts as a 'full-stack' solution. We define this full-stack as the process from abstraction to physicalisation starting with setup, modelling acoustic propagation, transducer phase retrieval, sound field analysis, and control of the acoustic holographic hardware itself. Existing methods fail to fulfil one or more of these categories. To address this, we present AcousTools, a Python-based acoustic holography library, designed to support the full suite of acoustic holographic applications and we show AcousTools's ability to meet each step of the full-stack's requirements. AcousTools has the potential to become the standard code library for acoustic holography, with the uniquely complete suite of features wrapped in a language that is known to be easy to use, AcousTools will increase the ability for researchers to develop novel applications as well as accurately review other's work. The full-stack, aside from software, will also be useful for researchers - providing a way to view and compare methodologies by understanding where they fit into the stack.

翻译：声学全息是一门新兴领域，通过控制和操纵中空超声波实现新颖而激动人心的应用，涵盖中空触觉反馈、体三维显示、非接触式制造，乃至药物递送等化学与生物医学应用。为开发这些应用，需要一个能够预测声学行为并模拟相关效应（如施加的力或散射模式）的软件框架。尽管已有多种软件库和平台尝试填补这一角色，但尚未出现一个作为'全栈'解决方案的单一软件。我们将全栈定义为从抽象到物理化的全过程，包括设置、声传播建模、换能器相位恢复、声场分析以及声学全息硬件本身的控制。现有方法未能满足其中一类或多类需求。为此，我们提出了AcousTools——一个基于Python的声学全息库，旨在支持完整的声学全息应用套件，并展示了AcousTools满足全栈各阶段要求的能力。AcousTools有望成为声学全息的标准代码库，其独特而完整的功能套件封装于易于使用的编程语言中，将提升研究人员开发新应用及准确评估他人工作的能力。除软件外，全栈框架本身也有助于研究人员——通过理解各方法在栈中的位置，提供一种审视和比较不同方法的途径。