This struct can be used to specify the size of a receptive field (RF) radius in 3 dimensions x, y, and z. Receptive fields will be circular with radius as specified. The 3 dimensions follow the ones defined by Grid3D. If the radius in one dimension is 0, say x==0, then pre.x must be equal to post.x in order to be connected. If the radius in one dimension is -1, say x==-1, then pre and post will be connected no matter their x coordinate (effectively making an RF of infinite size). Otherwise, if the radius is a positive real number, the RF radius will be exactly this number. Call RadiusRF with only one argument to make that radius apply to all 3 dimensions.
- Parameters
-
[in] | rad_x | the RF radius in the x (first) dimension |
[in] | rad_y | the RF radius in the y (second) dimension |
[in] | rad_z | the RF radius in the z (third) dimension |
Examples:
- Create a 2D Gaussian RF of radius 10 in z-plane: RadiusRF(10, 10, 0) Neuron pre will be connected to neuron post iff (pre.x-post.x)^2 + (pre.y-post.y)^2 <= 100 and pre.z==post.z.
- Create a 2D heterogeneous Gaussian RF (an ellipse) with semi-axes 10 and 5: RadiusRF(10, 5, 0) Neuron pre will be connected to neuron post iff (pre.x-post.x)/100 + (pre.y-post.y)^2/25 <= 1 and pre.z==post.z.
- Connect all, no matter the RF (default): RadiusRF(-1, -1, -1)
- Connect one-to-one: RadiusRF(0, 0, 0) Neuron pre will be connected to neuron post iff pre.x==post.x, pre.y==post.y, pre.z==post.z. Note: Use CARLsim::connect with type "one-to-one" instead.
- Note
- A receptive field is defined from the point of view of a post-neuron.
Definition at line 488 of file carlsim_datastructures.h.