The Basics#

This tutorial will introduce some of the basics concepts in NAVis.

This is not supposed to be comprehensive but rather to give you a flavor of how things work. For inspiriation, explore the example gallery and for detailed explanations have a look at the API documentation.

Single Neurons#

NAVis lets you import neurons from a variety of local and remote sources. For demonstration purposes NAVis comes with a bunch of fruit fly neurons from the Janelia hemibrain project:

import navis

# Load a single neuron
n = navis.example_neurons(n=1, kind='skeleton')
n

In above code we loaded one of the example neurons. NAVis represents neurons as navis.TreeNeuron, navis.MeshNeuron, navis.VoxelNeuron or navis.Dotprops.

In the above example we asked for a skeleton, so the neuron returned is a TreeNeuron. This class is essentially a wrapper around the actual neuron data (the SWC table in this case) and has some convenient features.

Node data is stored as pandas.DataFrame:

n.nodes.head()

Try typing in "n." and hitting tab: most attributes and functions are accessible via autocompletion. If you don't know what a function does, check out the documentation using help() or via the API documentation:

help(navis.TreeNeuron.root)

help(navis.TreeNeuron.downsample)

You will notice that many NAVis functions that accept neurons have an inplace parameter. This is analogous to pandas:

Downsample a copy, leaving the original unchanged (this is the default for almost all functions)

n_ds = n.downsample(10, inplace=False)

# Downsample original neuron
n.downsample(10, inplace=True)

n

navis.TreeNeuron functions such as .downsample() are shorthands for calling the actual NAVis functions. So above code is equivalent to:

n = navis.example_neurons(n=1, kind='skeleton')
n_ds = navis.downsample_neuron(n, downsampling_factor=10, inplace=False)
n_ds

Lists of Neurons#

For multiple neurons, NAVis uses navis.NeuronList:

nl = navis.example_neurons(n=3, kind='skeleton')
nl

navis.NeuronList is a container and behaves like a glorified list:

nl[0]

navis.NeuronList lets you run/access all functions (methods) and properties of the neurons it contrains:

nl.cable_length

Out:

array([266476.88, 304332.66, 274703.38], dtype=float32)

nl_ds = nl.downsample(10, inplace=False)

nl_ds

Let's finish this primer with some eye candy

nl.plot3d(backend='plotly')

What next?#

Total running time of the script: ( 0 minutes 0.478 seconds)

Download Python source code: tutorial_basic_00_basics.py

Download Jupyter notebook: tutorial_basic_00_basics.ipynb

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