Use the LEFT and RIGHT arrow keys or MOUSEDRAG to rotate tree.

ENTER to redraw.

Weird things happen occasionally.

The following options are measured in pixels and radians, and automatically scale with b_node. Base values are assuming b_node = 1 which places nodes 1 pixel apart.

See the old version here.

seed =

The seed to use for random number generation.

Background Color:

rgb (,
,
)

Stroke Color:

rgba(,
,
,
)

Fill Color:

rgba(,
,
,
)

Leaf Color:

rgba(,
,
,
)

Leaf Color Deviation:

rgba(,
,
,
)

The components of Leaf Color are uniformly distributed between the Color value plus/minus the Deviation value

Node Distance:

b_node =

How far apart the nodes on a branch are placed

Branch Length Mean:

b_mu =

The mean length of the branches

Branch Length Deviation:

b_sigma =

The length of the branches is normally distributed using this standard deviation

Branch Initial Width:

b_init =

The initial width of the branch (width of trunk) measured with the stroke

Branch Initial Stroke Width:

b_stroke =

The initial stroke width of the branch

Branch Thinning:

b_thin =

At each node, the branch width is thinned by this percentage

Branch Curvature:

b_curve =

At each node, the direction of the branch may change by an angle from 0 to this value (cosine weighted). This value does not scale well with b_node

Branching Probability:

b_prob =

At each node, there is a probability equal to this for a new branch to spawn

Branching Angle:

b_branch =

When a new branch is formed, the direction of the new branch may change by an angle from 0 to this value (cosine weighted)

Leafing Distance:

l_dist =

The mean distance from the node that a leaf will be placed

Leafing Deviation:

l_dev =

The leaf distance is uniformly distributed between the mean plus/minus this value

Leaf Size:

l_size =

The mean diameter of the leaves

Leaf Size Deviation:

l_sdev =

The leaf size is uniformly distributed between the mean plus/minus this value

Leafing Start:

l_start =

Will wait for these many nodes before leaves will be placed

Leafing Probability:

l_prob =

At each node, there is a probability equal to this for a leaf to be placed

Scale:

scale =

Offset X:

off_x =

Offset Y:

off_y =

Branches:

Segment Type:

type =

Leaves:

\

/

/

/

\

\