PyCon AU 2024

Juan Nunez-Iglesias

I'm a research scientist helping other scientists get insights from their image data using Python. I've been using Python since 2008, and the main scientific Python ecosystem (NumPy, SciPy, & co) since 2010. In 2012, on a whim, I went to my first SciPy (US) conference, and it changed my life! I realised that "open source" didn't mean just posting the code online. It meant actively collaborating on code with other scientists, across vast distances and at different times. Before you could say "import numpy as np", I had joined the scikit-image team, written a paper about it, written a whole book on SciPy (!), spoken at various SciPys and PyConAUs, started new collaborative, open source libraries, and just generally been all-in on Scientific Python. I love this community and what it has done for me, and always try to pay it forward for new folks in our community! 😊


What is your Mastodon/Fediverse handle? –

@jni@fosstodon.org

What is your Twitter/X handle? –

jnuneziglesias


Session

11-22
12:20
30min
Explore, annotate, and analyse multidimensional image data with napari
Juan Nunez-Iglesias, Draga Doncila Pop

napari is an n-dimensional image viewer for Python. If you’ve ever tried plt.imshow(arr) and made Matplotlib unhappy because arr has more than two dimensions, then napari might be for you! napari will gladly display higher-dimensional arrays by providing sliders to explore additional dimensions. But napari can also: overlay derived data, such as points, segmentations, polygons, surfaces, and more; and annotate and edit these data, using standard data structures like NumPy or Zarr arrays, allowing you to seamlessly weave exploration, computation, and annotation in image analysis.

Scientific Python
Eureka 2