## Babyplots Documentation

Babyplots is an easy to use library for creating interactive 3d graphs
for exploring and presenting data.

Babyplots is available as a JavaScript library, as an R package, as a Python package, and as
an add-in for Microsoft PowerPoint. While the R package, Python package and JavaScript
library allow the creation of new plots, the PowerPoint add-in can only
be used to display exported plots. This website also provides an interactive node-based
editor for creating babyplots visualizations called NPC (node plot creator)
or simply Creator.

Find the individual documentation pages through the links below:

### Plot types

There are currently five types of visualizations that can be created with babyplots.

#### Point Cloud

Point clouds are 3-dimensional scatter plots, where three variables (x, y and z)
define the positions of points in the coordinate system. One additional variable can
be visualized by the color of the points. Point clouds are optimized for very large data sets.

#### Shape Cloud

Shape clouds are 3-dimensional scatter plots, similar to point clouds, where three variables (x, y and z) define the
positions of 3-dimensional shapes in the coordinate system. One additional variable can be visualized by the color
of the shapes. Each data point of a shape cloud has the same shape, but you can combine multiple shape clouds with
different shapes.

Additionally, each data point can have an information text assigned to it that is displayed when the corresponding
shape in the plot is clicked.

#### Surface

The surface plot creates a 3-dimensional surface that is defined by a height variable
for each point on a x-y plane given by the rows and columns of a 2d matrix. An additional
variable can be visualized by the color of the surface points. The color is interpolated
between the defined points of the surface.

#### Heat Map

The heat map is a 3-dimensional bar chart defined similarly to the surface plot, where
the height of each bar on a x-y plane is given by the value in a row-column pair of a
2d matrix. An additional variable can be visualized by the color of the bar.

#### Image Stack

The image stack visualizes a set of 2-dimensional slices with pixel values. The input is
a tiff stack with rgb channels. It was created and optimized for fluorescent microscopy
z-stack data and therefore works best with black background and bright signal.