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，通过控制和操纵空中超声波实现新颖而激动人心的应用。这些应用涵盖空中触觉反馈、体三维显示、非接触式制造，甚至包括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其效应（如施加的力或散射模式）的软件框架。目前已有多种软件库和平台尝试填补这一角色，但尚未出现一个能够作为'全栈式'解决方案的单一软件。我们将'全栈'定义为从抽象到物理实现的完整流程，包括设备配置、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。现有方法往往无法满足其中一个或多个环节。为此，我们提出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，并展示其满足全栈各环节需求的能力。AcousTools有望成为声学全息领域的标准代码库，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型应用及准确评估他人工作的能力。除软件外，全栈框架本身也将为研究人员提供价值——通过理解各方法在技术栈中的定位，实现方法论的可视化比较。