Releases | Open Source Science

navis - Version 1.10.0

This version includes: - improvements to reading skeletons from tar archives - fixes to make sure that navis plays nicely with numpy 2.x (@floesche) - various other fixes (including by @floesche)

See the Changelog for details.

- Python
Published by schlegelp about 1 year ago

navis - Version 1.9.1

This minor version bump fixes a few smaller issues:

MICrONS & H01 interfaces:
- fetch_neurons now accepts a materialization parameter that determines which materialization version is used for synapse and nucleus queries; defaults to "auto" which means navis will try to find a materialization version matching the queried root IDs
- fetch_neurons will now also assign soma positions for H01 neurons (see the .soma_pos neuron property); previously this only worked for MICrONS neurons
- datastack="cortex65" now points to the correct MICrONS datastack
CloudVolume.mesh.get_navis (see navis.patch_cloudvolume) now accepts a process (default is False) parameter that determines whether the NeuroGlancer mesh is processed (deduplication of vertices, etc.); contribute by @fcollman
fixed a bug in navis.subset_neuron that caused branch points to not be re-calculated

- Python
Published by schlegelp over 1 year ago

This version comes with: - a new and shiny interface to pull data from the H01 human cortex dataset (by @jinhan) - TreeNeurons can now be initialized from vertices and edges - improvements in handling and processing of image data - general I/O improvements

See the changelog for details!

- Python
Published by schlegelp over 1 year ago

navis - Version 1.8.0

This version contains a major internal rework of both navis.plot2d and navis.plot3d to make them more consistent and easier to use.

Breaking

Plotting: the synapse_layout parameter was renamed to cn_layout (matching e.g. other parameters such as cn_colors)
Negative views in navis.plot2d (e.g. view=("x", "-z")) will now invert axes rather than changing the underlying data
Minimum version of matplotlib is now 3.9 (was 3.6)
The plotly backend is not part of a minimal install anymore (still installed via navis[all])
The Vispy backend is now deprecated and will be removed in a future release
Removed navis.screenshot - please use the Octarine/Vispy viewer's .screenshot() method instead
navis.tortuosity now calculates tortuosity as-is (i.e. without resampling) by default

Additions

Added Octarine as the default backend for plotting from terminal
New Function: navis.ivscc_features() computes some basic ICSCC features
New function: navis.graph.skeleton_adjacency_matrix() computes the node adjacency for skeletons
New function: navis.graph.simplify_graph() simplifies skeleton graphs to only root, branch and leaf nodes while preserving branch length (i.e. weights)
New NeuronList method: get_neuron_attributes is analagous to dict.get
NeuronLists now implement the | (__or__) operator which can be used to get the union of two [NeuronLists]navis.NeuronList]
Tree/MeshNeurons, Volumes and Dotprops now support addition/subtraction (similar to the already existing multiplication and division) to allow offsetting neurons
navis.Volume now have an (optional) .units property similar to neurons

Improvements

Plotting:
- navis.plot3d:
- legendgroup parameter (plotly backend) now also sets the legend group's title
- new parameters for the plotly backend:
  - legend (default True): determines whether legends is shown
  - legend_orientation (default v): determines whether legend is aranged vertically (v) or horizontally (h)
  - linestyle (default -): determines line style for skeletons
- default for radius is now "auto"
- navis.plot2d:
- the view parameter now also works with methods 3d and 3d_complex
- the color_by and shade_by parameters now also work when plotting skeletons with radius=True
- new defaults: radius="auto", alpha=1, figsize=None (use matplotlib defaults)
- new parameters for methods 3d and 3d_complex: mesh_shade=False and non_view_axes3d
- the scalebar and soma parameters can now also be dictionaries to style (color, width, etc) the scalebar/soma
- the connectors parameter can now be used to show specific connector types (e.g. connectors="pre")
I/O:
- read_* functions are now able to read from FTP servers (ftp://...)
- the limit parameter used in many read_* functions can now also be a regex pattern or a slice
New parameter in navis.resample_skeleton() use map_column to include arbitrary columns in the resampling
navis.prune_twigs() and navis.cable_length() now accept a mask parameter
General improvements to docs and tutorials

Fixes

Memory usage of Neuron/Lists is now correctly re-calculated when the neuron is modified
Various fixes and improvements for the MICrONS interface (navis.interfaces.microns)
navis.graph.node_label_sorting() now correctly prioritizes total branch length
navis.TreeNeuron.simple now correctly drops soma nodes if they aren't root, branch or leaf points themselves

Full Changelog: v1.7.0...v1.8.0

- Python
Published by schlegelp over 1 year ago

navis - Version 1.7.0

With this release we integrate navis-fastcore into navis which contains a number of core functions re-implemented in Rust 🎉

For now this is a soft dependency but if you pip install navis-fastcore, navis will automatically use these improved functions under the hood, which can speed things up by up to 20x 🚀

In other news:

Breaking

plotting functions: dropped the cluster parameter in favour of an improved color_by logic (see below)

New

new method navis.NeuronList.add_metadata to quickly add metadata to neurons

Improved

navis.find_soma and navis.graph.neuron2nx (used under the hood) are now much faster
all I/O functions, such as navis.read_swc, now show which file caused an error (if any); original filenames are tracked as .file property
navis.NeuronList will only search the first 100 neurons for autocompletion to avoid freezing with very large lists
plotting functions: color_by now accepts either a list of labels (one per neuron) or the name of a neuron property
navis.subset_neuron is now faster and more memory efficient when subsetting meshes
navis.TreeNeuron.cable_length is now faster

Fixed

all I/O functions such as navis.read_swc now ignore hidden files (filename starts with ._) instead of breaking
navis.read_swc now actually uses the soma label (if present) to set the soma node
fixed a bug in plotting when using vertex colors
fixed the progress bar in navis.interfaces.neuprint.fetch_mesh_neuron
fixed a bug in navis.synblast that caused multiprocessing to fail (pickling issue with pykdtree)
navis.interfaces.neuprint.fetch_mesh_neuron will now ignore the lod parameter if the data source does not support it instead of breaking
fixed a number of depcrecation warnings in the codebase

- Python
Published by schlegelp over 1 year ago

navis - Version 1.6.0

It has been a long time (7 months, to be precise) since the last release but we've not been idle!

Version 1.6.0 is chock-full with new features, improvements and fixes. Here are some of the highlights:

Breaking

with this release we've dropped support for Python 3.8 as per NEP 29
navis.write_swc no longer writes Dotprops

New Features

navis.read_parquet and navis.write_parquet let you read/write large set of skeletons or dotprops; note: these are experimental and the format specs might still change but feel free to take it for a spin
new navis.NeuronConnector class for creating connectivity graphs from groups of neurons with consistent connector IDs (e.g. from pymaid neurons)

Improvements

improved logic for splitting NBLASTs across multiple cores
i/o functions can now read directly from .tar or .tar.gz files (.zip was already supported)

Fixes

fixes to the neuPrint interface by @stuarteberg
plotting empty TreeNeurons no longer breaks things thanks to @floesche
reading large files (i.e. mostly meshes) directly from a URL should not break anymore

New Contributors

@stuarteberg made their first contribution in https://github.com/navis-org/navis/pull/124
@floesche made their first contribution in https://github.com/navis-org/navis/pull/125

Full Changelog: https://navis.readthedocs.io/en/latest/source/whats_new.html Commit history: https://github.com/navis-org/navis/compare/v1.5.0...v1.6.0

- Python
Published by schlegelp almost 2 years ago

navis - Version 1.5.0

Changes: - BREAKING: dropped support for Python 3.7 - new function: navis.pop3d() removes the most recently added object from the vispy 3d viewer - new experimental functions for (pairwise) alignment of neurons using the pycpd package: navis.nblast_align(), navis.align.align_deform(), navis.align.align_rigid(), navis.align.align_pca(), navis.align.align_pairwise() - navis.xform_brain() now recognizes the target template’s units if available - new NeuronList method: navis.NeuronList.set_neuron_attributes() - new utility functions: navis.nbl.compress_scores(), navis.nbl.nblast_prime() - improved persistence functions: navis.persistence_distances(), navis.persistence_vector(), navis.persistence_diagram() - navis.longest_neurite() and navis.cellbodyfiber() now also allow removing the longest neurite and CBF, respectively - navis.heal_skeleton() now accepts a mask parameter that allows restricting where fragments are stitched - various other bugfixes

- Python
Published by schlegelp over 2 years ago

navis - Version 1.4.0

This is release contains various improvements and fixes. Importantly, it fixes a couple incompatibilities with numpy 1.24.0.

Even though this is not a new major version there is one breaking change:

navis.flow_centrality was renamed to navis.synapse_flow_centrality and a new non-synaptic navis.flow_centrality function was added. This also impacts the method parameter in navis.split_axon_dendrite!

Please see the change log for other changes.

- Python
Published by schlegelp about 3 years ago

navis - Version 1.3.1

This is a small release containing 2 fixes: 1. Fixes a bug with the most recent version of dill which impact parallel processing. 2. In Jupyter, NBLAST now uses classic progress bars. This is not ideal and all progress bars are printed on top of another but the widgets seem to be entirely broken with the most recent version of tqdm.

- Python
Published by schlegelp over 3 years ago

navis - Version 1.3.0

as of this version pip install navis won't install a vispy backend (see install instructions for details)
new interface to fetch data from Virtual Fly Brain: navis.interfaces.vfb
tools to build custom NBLAST score matrices (big thanks to @clbarnes): see the new tutorial
Bayesian implementation of the network traversal model: navis.models.network_models.BayesianTraversalModel (big thanks to @aschampion)
NBLASTs: new approx_nn parameter (sacrifices precision for speed)
example neurons now come with some meta data
new morphometrics functions: navis.segment_analysis &navis.form_factor
new function to write meshes: navis.write_mesh
lots of fixes and improvements in particular for i/o-related functions

- Python
Published by schlegelp almost 4 years ago

navis - Version 1.2.1

Small fix for split_axon_dendrite.

- Python
Published by schlegelp almost 4 years ago

navis - Version 1.2.0

What's new:

new function: navis.betweeness_centrality
new function: navis.combine_neurons to simply concatenate neurons
new set of persistence functions: navis.persistence_vectors, navis.persistence_points and navis.persistence_distances
improvements to various functions: e.g. navis.bending_flow, navis.flow_centrality, navis.split_axon_dendrite and navis.longest_neurite
navis.read_swc now accepts a limit parameter that enables reading on the the first N neurons (useful to sample large collections)
navis.write_nrrd and navis.read_nrrd can now be used to write/read Dotprops to/from NRRD files
navis.nblast (and variants) now accept a precision parameter that allows setting the datatype for the matrix (useful to keep memory usage low for large NBLASTs)
navis.simplify_mesh (and therefore navis.downsample_neuron with skeletons) now uses the pyfqmr if present (much faster!)
improved the interface to Neuromorpho
added a new interface with the Allen Cell Types Atlas (see navis.interfaces.allen_celltypes)
myriads of small and big bugfixes

Thanks to @clbarnes and @Robbie1977 for contributing various PRs!

- Python
Published by schlegelp almost 4 years ago

navis - Version 1.1.0

This is primarily a bug fix release for an issue when plotting skeletons with the newest plotly (5.4.0) but still managed to squeeze in a new function:

new function :func:navis.sholl_analysis
plotly is now correctly chosen as default backend in Google colab
fixes a critical bug with plotting skeletons with plotly 5.4.0

- Python
Published by schlegelp over 4 years ago

navis - Version 1.0.0

This new version comes packed with goodies (including breaking changes)! Here are the highlights: - new neuron type VoxelNeuron for image-type neurons - conversion between neuron types (e.g. meshing VoxelNeurons or skeletonising MeshNeurons) - new plotting function plot_flat for dendrogram style figures - function names now better reflect what neuron type they work on (e.g. reroot_neuron is now called reroot_skeleton)

Check out the changelog for a full list.

- Python
Published by schlegelp over 4 years ago

navis - Version 0.6.0

This new version comes with tons of goodies:

Multi-core processing as (almost) first-class citizen

Many functions now accept a parallel=True. If the input is a NeuronList, navis will then use multiple cores to run that function. You can use n_cores=some number (defaults to half the available cores) to set the number of cores used.

A toy example:

```Python

nl = navis.exampleneurons(4) pr = navis.prunebystrahler(nl, toprune=1, parallel=True) ```

To run generic (i.e. non-navis functions) in parallel you can use NeuronList.apply:

``` Python

nl = navis.example_neurons(4) nl.apply(lambda x: x.id, parallel=True) [1734350788, 1734350908, 722817260, 754534424] ```

Note that this requires that you install pathos:

bash $ pip3 install pathos -U

Read and write SWC files directly from/to zip files

```python

nl = navis.example_neurons(4)

Write to zip

navis.write_swc(nl, '~/Downloads/SWCs.zip')

Read from zip

unzipped = navis.read_swc('~/Downloads/SWCs.zip') ```

Unit awareness

For a while now, navis neurons had an (optional) units property, and some downstream libraries (e.g. fafbseg and pymaid) make use of that:

```python

Example neurons are in raw (i.e. voxel) hemibrain space

n = navis.example_neurons(1) n.units 8 ```

Under the hood, this is using a neat library called pint which also lets you convert between units. So you can do stuff like this:

```python

Example neuron is in 8nm voxels (see above)

nvxl = navis.exampleneurons(1)

Convert to microns

num = nvxl.convertunits('um') num.units 1.0 ``Likewise, manynavisfunctions that work with spatial units now alternatively accept a "unit str" that can be parsed bypint`. For example:

```python

n = navis.example_neurons(1)

Prune twigs smaller than 5 microns

(which would be 5 * 1000 / 8 = 625 in this neuron's space)

npr = navis.prunetwigs(n, '5 microns') ```

New functions

navis.prune_at_depth: to prune at given distance from root
navis.read_rda: read nat neuron-data R data (.rda) - also works for basic stuff like dataframes
navis.cell_body_fiber: prune neuron down to its cell body fiber

For a complete list of changes, see the change log and the commit history.

- Python
Published by schlegelp almost 5 years ago

navis - Version 0.5.3

New functions: - navis.nblast_smart - navis.synblast - navis.symmetrize_brain - navis.write_google_binary

New transform: - navis.transforms.MovingLeastSquaresTransform (thanks to @clbarnes)

Improved: - navis.Viewer - navis.simplify_mesh - navis.write_swc and read_swc (thanks to @clbarnes) - better and more tests (thanks to @clbarnes)

Plus many many bug fixes.

See the Changelog for details.

- Python
Published by schlegelp almost 5 years ago

navis - Version 0.5.2

added a lower-level xform() and mirror() function that requires transform(s)/mirror axis size as input
new NBLAST variant NBLAST_smart()
new io functions:
- write_google_binary() to write skeletons to Google's binary format
- read_h5() and write_h5() implement storing neurons in HDF5 files
new function merge_duplicate_nodes() to de-duplicate nodes in skeletons
new transform function: symmetrize_brain()
downsample_neuron() now works on dotprops
connectors are now included in a neuron's bounding box
NeuronList division & multiplication now has a progress bar
improve how HDF5 transforms deal with points outside the deformation field
many small and big bug fixes

Check out the API docs to learn more about the new functions.

- Python
Published by schlegelp almost 5 years ago