Interact in real time

Write and share scripts for repeatable automation, or command your Moku hardware live, to record and analyze your data all in a single place by partnering our Python API with Jupyter.[/lq_image_text][lq_image_text image=”1612″]

Automated control

The Python API takes Moku hardware to the next level, turning it into an automated test, measurement, and control device for your lab. Python integration enables your Moku to automatically:

• Switch instruments
• Acquire and process measurements in real-time
• Save data logs/metadata for post-processing
• Generate output signals to control your system

[/lq_image_text][text_with_code_block typist_markup=”>> data = oscilloscope.get_data()
>>
>>” code_lines=”import seaborn # Beautiful visualisation^ seaborn.tsplot(data.time, data.ch1)
import pandas # Data science^ pandas.describe(data.ch1)
import scipy # Science, engineering, math^ scipy.optimize.curvefit(f, data.time, data.ch1)” code_position=”Right” data=”oscilloscope.get_data()”]

Open-source integration

Add depth to your Moku applications by integrating with the many open-source Python libraries available on the web.

Create beautiful visualizations with seaborn, or track progress of your experiment remotely by streaming to the web using plotly. Got data? Pandas provides an endless list of high-performance data structures and easy-to-use analysis tools to get the job done.[/text_with_code_block][lq_image_text image=”1613″]

Cross-platform performance

The Python API for Moku can be dropped in to any existing lab infrastructure. It’s fully supported on Windows, Linux, and OSX, and in many cases you can install it without special privileges.

Share your programs with all your colleagues and computers, regardless of operating system — they’ll run anywhere.[/lq_image_text][lq_image_text_top_bottom]

Supported hardware platforms

Python integration is available across all Moku hardware platforms.

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