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:
fill =
segments =
circles =

Segment Type:
type = trap
rect

Leaves:
leaf =