![]() It is always possible to go from the Builder to python code in this way. If you then save and run this code, it would look the same as running it directly from the Builder. The view will automatically switch to the Coder, and display the python code. Instead of running the program, explicitly convert it into python: Type F5, or click the Compile icon: In the Builder, load or recreate your “hello world” program. To get a better feel for what was happening “behind the scenes” in the Builder program above: Whenever you run a Builder experiment, PsychoPy ® will first translate it into python code, and then execute that code. ![]() You can quit PsychoPy ® from the File menu, or typing Ctrl-Q / Cmd-Q. When running an experiment, you can quit by pressing the escape key (this can be configured or disabled). What if you wanted to display your cheerful greeting for longer than the default time?Ĭlick on your Text component (the existing one, not a new one).Įdit the Stop duration (s) to be 3.2 times are in seconds. If nothing happens or it looks wrong, recheck all the steps above be sure to start from a new Builder view. (Components, Routines, and other Builder concepts are explained in the Builder documentation.)īack in the main Builder, type Ctrl-R (Windows, Linux) or Cmd-R (Mac), or use the mouse to click the Run icon.Īssuming you typed in “Hello world!”, your screen should have looked like this (briefly): Your text component now resides in a routine called trial. (Properties dialogs have a link to online help-an icon at the bottom, near the OK button.) When you run the program, the text you type here will be shown on the screen.Ĭlick OK (near the bottom of the dialog box). In the Text field, replace the default text with your message. To get a new Builder view, type Ctrl-N on Windows or Linux, or Cmd-N on Mac.Ĭlick on a Text component and a Text Properties dialog will pop up. If you have poked around a bit in the Builder already, be sure to start with a clean slate. Tensor learning, algebra and backends to seamlessly use NumPy, MXNet, PyTorch, TensorFlow or CuPy.Start PsychoPy ®, and be sure to be in the Builder view. Python backend system that decouples API from implementation unumpy provides a NumPy API. Multi-dimensional arrays with broadcasting and lazy computing for numerical analysis.ĭevelop libraries for array computing, recreating NumPy's foundational concepts. NumPy-compatible sparse array library that integrates with Dask and SciPy's sparse linear algebra.ĭeep learning framework that accelerates the path from research prototyping to production deployment.Īn end-to-end platform for machine learning to easily build and deploy ML powered applications.ĭeep learning framework suited for flexible research prototyping and production.Ī cross-language development platform for columnar in-memory data and analytics. ![]() Labeled, indexed multi-dimensional arrays for advanced analytics and visualization NumPy-compatible array library for GPU-accelerated computing with Python.Ĭomposable transformations of NumPy programs: differentiate, vectorize, just-in-time compilation to GPU/TPU. NumPy's API is the starting point when libraries are written to exploit innovative hardware, create specialized array types, or add capabilities beyond what NumPy provides.ĭistributed arrays and advanced parallelism for analytics, enabling performance at scale. With this power comes simplicity: a solution in NumPy is often clear and elegant. NumPy brings the computational power of languages like C and Fortran to Python, a language much easier to learn and use. Nearly every scientist working in Python draws on the power of NumPy.
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