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Articles about computational science and data science, neuroscience, and open source solutions. Personal stories are filed under Weekend Stories. Browse all topics here. All posts are CC BY-NC-SA licensed unless otherwise stated. Feel free to share, remix, and adapt the content as long as you give appropriate credit and distribute your contributions under the same license.

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Using pip to install Python packages

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pip is another package installer for Python. Learn how to use it for installing and managing Python packages in your projects.

Virtual environments with venv

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In addition to conda’s create command, Python’s built-in venv command offers another way for creating virtual environments.

How to install and run Python code from GitHub

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Learn how to install code from GitHub, that is, e.g., not (yet) available via conda or pip.

A minimal Python installation with miniconda

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Learn how to install miniconda to have a quick and minimal Python installation on any operating system. Also learn how to use conda to create and manage virtual environments, install packages, run Python scripts and run Jupyter Notebooks and JupyterLab.

Stable installation of Napari on a M1 Mac

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In case you’re having problems installing Napari on your M1 Mac, try to install it from conda instead of pip.

Open Zarr files in Fiji

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Both Zarr and OME-ZARR files are supported in Fiji. Here’s how to get it working.

Using Zarr for images – The OME-ZARR standard

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As for any other NumPy array, we can use the Zarr file format to store image files. In this post we additionally explore the NGFF (next-generation file format) OME-ZARR standard.

Zarr – or: How to save NumPy arrays

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What is Zarr and why is it probably the most suitable file format for saving NumPy arrays?

How to read patch clamp recordings in WaveMetrics IGOR binary files (ibw) in Python

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This is a mini tutorial on how to read patch clamp recordings in WaveMetrics IGOR binary files (*.ibw) in Python using the neo and igor packages.

How to add statistical annotations to matplotlib plots

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This mini tutorial shows, how to add statistical annotations to matplotlib plots with just a few commands.

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