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datatour

Seeing is important. `datatour` - allows you to see your data in it's native dimension. Currently implemented as a `plotly` scatter plot projected from it's original dimension in the 2D on the screen with timeline animation inspired by GrandTour and common sense.

0.2.8
pipPyPI
Maintainers
1

DataTour

datatour

License PyPI Python Version CI codecov

DataTour

Seeing is important. datatour - allows you to see your data in its native dimension. Currently implemented as a plotly scatter plot projected from its original dimension in the 2D on the screen with timeline animation inspired by GrandTour and common sense.

Installation

Available via pip:

pip install datatour

Usage

If you have array of feature vectors f: shape(shape)==(n_smpl, n_dim), you can create data tour object, and display it:

from datatour import DataTour as dt

ndv = dt(f)
ndv.display()

By default, selects randomly n_subsample=500 samples for efficiency reason.

To visualize vector field vf of the same dimension (in the same feature space):

ndv = dt(f, vf)
ndv.display_quiver(color='z_scaled')

Also check examples:

dt().display()

cube

ndv = dt(example='sphere', n_subsample=0)
ndv.display(color='z_scaled')

sphere

Installation

Available via pip:

pip install datatour

Usage

If you have array of feature vectors f: shape(shape)==(n_smpl, n_dim), you can create data tour object, and display it:

from datatour import DataTour as dt

ndv = dt(f)
ndv.display()

By default, selects randomly n_subsample=500 samples for efficiency reason.

To visualize vector field vf of the same dimension (in the same feature space):

ndv = dt(f, vf)
ndv.display_quiver(color='z_scaled')

Also check examples:

dt().display()

cube

ndv = dt(example='sphere', n_subsample=0)
ndv.display(color='z_scaled')

sphere

Licence

Distributed under BSD 3 licence

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