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Groundbreaking usability, model clarity, reuse and automation. The acclaimed flexibility and performance of Emme via a refreshing user interface and an amazing component-based system that lets you build, deploy, maintain and run transportation forecasting models better than ever.
Emme Modeller is an application framework for travel demand forecasting, transportation planning and transport data science applications that lets you:
Work efficiently with transportation forecasting models across the entire modelling lifecycle. A modern component-based application framework provides an open, extensible system that promotes understanding, experimentation and design. Each tool provides its own processing logic, a clean and refreshing user interface, and logbook history. The Modeller framework takes care of the rest, providing a seamless transition from interactive use to automation and component reuse, removing much of the tedium of developing models from scratch. Virtually any model or application can be accommodated using 100+ tools provided out-of-the-box in the Emme Standard Toolbox.
You can open more than one tool in Modeller to prepare multiple procedures at once, then determine the order in which they are run. Preparing model procedures has never been easier with universal search and built-in snapshot capabilities to save your work and resume where you left off the next time. Each tool has a run button with its own progress indicator, and when you switch between tabs tool pages automatically refresh. Tools are always kept in-sync with the current scenario in Emme Desktop, so you can switch easily between modelling and mapping or reporting.
You can even create new tools from simple drag-and-drop workflows, without scripting, for repetitive tasks. In Modeller, every tool is a first-class citizen and benefits from the same run control, error handling and logging.
With Modeller, you can expect all of the same powerful and proven modelling components as previous versions of Emme, including results compatibility. And because Emme Modeller provides direct facilities for running Emme macros and the Emme Prompt, you are free to make migration decisions on your own time.
Introducing literate, visual and reproducible transportation forecasting and transport data science application development. The Emme Notebook is an interactive computing environment for travel demand modelling and transportation forecasting applications in which you can combine Emme Modeller tools and Logbook entries, Emme Desktop worksheets and tables, Python code execution, rich text, mathematics, plots and rich media, as shown above.
Easily drag-and-drop tools to automate model workflows, or add maps and charts to create visual model dashboards that can be re-run at any time so results are always up-to-date. Or, author sophisticated transport modelling applications in Python with the Emme APIs, and bring modern data science to your transportation applications with the included SciPy stack, a great foundation for solving a variety of scientific and technical challenges. Then share your work with other Emme users in a single notebook document or with anyone else as a simple web page.
See your models in striking detail. Bring clarity to even the most elaborate model systems. Explore model structure, not just network structure, in stunning hierarchical detail that unfolds while models run. Then review, revise and re-run any step for iterative model development.
The Logbook always contains a reliable record of execution, and a way to review, revise or re-run any step, even weeks or months after it was run. You can even assemble new workflows using the steps of different model runs.
For full model applications or more complex procedures involving many tools, the effects are often illuminating, clarifying even conditional logic that may vary from run to run. Because Modeller works the same whether interactive or scripted, the Logbook always matches your model results.
Because the Logbook shows what actually happened, even errors, you get a degree of visual debugging without even opening model code. So you can make sure that anyone running your model will understand precisely what occurred, even across the most complex logic. You get professional, maintainable source code. Everyone else gets a transparent run-time visual representation of model structure.
The Logbook is also useful for model communications and team collaboration, as it provides a visual representation of model flow and structure and reports, along with Emme Desktop maps, charts and tables recorded during execution. And when you are ready, you can delete logbook entries to preserve only the essentials.
Rapidly build and deploy complete applications using any Modeller Tool. Modeller Tools provide the same services whether used interactively or scripted, so there are no new model systems to learn, and no differences in model behavior between scripted and interactive work. Also, model specifications transition easily from interactive, text-based formats to the richer data structures needed for professional model development.
Your models automatically inherit clear step-by-step logging and reports in the Logbook, without the need to maintain anything but model scripts. Even if you automate all model runs, you can still visually inspect the details of any model step. This also provides invaluable and built-in support for model auditing, troubleshooting and historical/version comparison.
The Emme Modeller API for Python makes it easy to automate any tool, or to combine tools into sophisticated model applications with minimal scripting - often just enough to chain tools together. Or, use the Modeller API to add your own tools to extend the framework and offer new functionality to your teammates or other Emme users. Your new tools will be available via the Modeller API, just like the standard components. You can even create great looking user-interfaces for your tools. And with the other hundreds of Emme APIs and services offered, like the Database API, Network API and Matrix API, you can work directly with your Emme data in Python. The future is completely open.
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