Search
Login
Register
Menu
Getting Started
Home
Community
Forum
Animat Warehouse
Wiki
Contributers
David Cofer
Download
AnimatLab 2.0
AnimatLab Windows SDK
AnimatLab Linux SDK
SDK on an NVIDIA Jetson TK1
AnimatLab 1.0
Store
Help
Documentation
Project Workspace
Environment
Organism
Structure
Simulation
Playback Speed
Neural Network Editor
Neural Simulation Plug-ins
Node Properties
Link Properties
Relabel
Relabel Selected
Select By Type
Biomechanical Editor
Biomechanical Body Parts
Food Sources
Joints
Receptive Fields
Material Types
Bullet Physics Engine
Robotics
Robot Interfaces
Robot IO Controllers
Dynamixel USB
Firmata
Arbotix Firmata
XBee Commander
Remote Control
Remote Controls
XBee Commander
AnimatSerial
Simulator
Data Tools
Line Chart
Scripted Simulation Window
Stimuli
Neural Stimuli
Mechanical Stimuli
General Stimuli
References
Tutorials
Using AnimatLab
AnimatLab Scripting
Biomechanical Editor
Line Charts
Neural Network Editor
Relabeling Items
User Interface V2
User Interface V1
Examples
Belly Flopper
Crayfish
Eating Frog
Hexapod Robot
Human Stretch Reflex
Limb Stiffness
Locust
Predator-Prey
Stretch Reflex
Touch Receptors
Body Parts
Hinge
Motorized Joints
Muscle
Spring
Stretch Receptor
Meshes
Constraint Relaxation
Data Tools
Line Charts
Scripted Simulation Window
Mechanical Tests
Balancing Forces
Pendulum
Springs
Neural Networks
Bistable Firing Rate Neuron
Classical Conditioning
Compartmental Model
Coordination
Endogenous Bursters
Electrical Synapses
Firing Rate Gated Synapse
Firing Rate Modulatory Synapse
Firing Rate Normal Synapse
Integrate And Fire Neurons
Lateral Inhibition
Long-Term Potentiation
Network Oscillators
Non-Spiking Chemical Synapses
Normal Firing Rate Neuron
Property Control
Random Firing Rate Neuron
Spiking Chemical Synapses
Voltage Dependent Synapses
Sensory Systems
Contact Sensors
Eating
Joint Angle
Odor Tracking
Touch Receptive Fields
Stimuli
Adding Current Stimuli
Enabler Stimulus
Force Stimulus
Motor Velocity
Position Clamp
Property Control
SDK
AnimatLab Scripting
Neural Module
Physics Module
Program Modules
SDK Basics
Robotics
Robot Arm Tutorials
Robot Arm Description
Robot Arm Simulation Setup
Robot Arm Control Part 1
Robot Arm Control Part 2
Robot Arm Position and Velocity Control
Robot Arm Joystick Control
PhantomX Hexapod Tutorials
PhantomX Hexapod Preview
SDK Help
Help
Documentation
Neural Network Editor
Select By Type
Select Items by Type
The Select By Type command gives you the ability to select objects in AnimtLab based on what type of object they are. For example, you can select all neurons and not links, or all random neurons and no others, or only
electrical synapses
. In the biomechanical editor you can select all joints, or all spheres. When you hit the command button for this features, , its dialog provides a drop down list that shows not only the types for all objects in that area, but also all of the parent types as well. Say you have some boxes, cones, hinges, and spheres in the body you are building. You can select all members of each of these types individually, or you can choose RigidBody to select all the body parts but not the joints. This feature gives you the ability to easily select large numbers of similar objects so they can be changed at the same time.
Figure 1.
Select By Type Dialog.
If you like AnimatLab and find it useful, then please donate in order to help support it.
Thanks for your support
!
Neural Simulation Plug-ins
C++ DLL libraries that implement a variety of different neuron and synapse models including integrate and fire spiking neurons and firing rate neurons
Node Properties
Describes properties of neural nodes in the AnimatLab neural editor.
Link Properties
Describes how a link object can connect two neurons or other objects within the AnimatLab neural editor.
Relabel
Relabel entire groups of items within the AnimatLab biomechanics or neural editor windows.
Relabel Selected
Relabel selected items within the AnimatLab biomechanics or neural editor windows.
Select By Type
Users have the ability to select items by the type of object within the AnimatLab biomechanics or neural network editors.
This project was supported by:
National Science Foundation
exploratory grant (GM065762)