Demo list¶
A number of demos have been created to help you exploit the accelerated tSNE and HSNE offered by this package. The demos are available in a single demos.zip file (see demos + data).
Demo |
Description |
|---|---|
Basic HSNE demo (see demos + data) |
A limited demo showing HSNE visual
analytics on the mnist data set
|
Extended HSNE demo (see demos + data) |
A complete demonstration including
three different datatypes:
* Image is datapoint (MNIST)
* Pixel is data point (Hyperspectral solar images)
* Multi-dimensional plus meta data (Genetic data)
|
HSNE Louvain Demo (see demos + data) |
Louvain clustering applied to
levels in the HSNE hierarchy
|
TextureTsne (see demos + data) |
GPU accelerated t-SNE
on 70000 MNIST points
|
TextureTsneExtended (see demos + data) |
GPU accelerated t-SNE
on 70000 MNIST points
with intermediate results
|
DocTest (see demos + data) |
Run the internal doctest examples in nptsne
Can be used for install verification
|
Jupyter notebook for GPU accelerated tSNE
|
A Jupyter notebook demonstration
of the tSNE API.
Illustrates the following options:
* a plain tSNE
* a pre-loaded embedding
* controlling the iteration when the
exaggeration factor is removed.
|