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886 行
36 KiB
886 行
36 KiB
using System;
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using System.Collections.Generic;
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using UnityEngine;
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using UnityEngine.Assertions;
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using Unity.MLAgents.Sensors;
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namespace Unity.MLAgents.Extensions.Sensors
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{
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/// <summary>
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/// Grid-based sensor.
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/// </summary>
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public class GridSensor : SensorComponent, ISensor, IBuiltInSensor
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{
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/// <summary>
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/// Name of this grid sensor.
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/// </summary>
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public string Name;
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//
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// Main Parameters
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//
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/// <summary>
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/// The width of each grid cell.
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/// </summary>
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[Header("Grid Sensor Settings")]
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[Tooltip("The width of each grid cell")]
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[Range(0.05f, 1000f)]
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public float CellScaleX = 1f;
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/// <summary>
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/// The depth of each grid cell.
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/// </summary>
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[Tooltip("The depth of each grid cell")]
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[Range(0.05f, 1000f)]
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public float CellScaleZ = 1f;
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/// <summary>
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/// The width of the grid .
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/// </summary>
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[Tooltip("The width of the grid")]
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[Range(2, 2000)]
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public int GridNumSideX = 16;
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/// <summary>
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/// The depth of the grid .
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/// </summary>
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[Tooltip("The depth of the grid")]
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[Range(2, 2000)]
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public int GridNumSideZ = 16;
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/// <summary>
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/// The height of each grid cell. Changes how much of the vertical axis is observed by a cell.
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/// </summary>
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[Tooltip("The height of each grid cell. Changes how much of the vertical axis is observed by a cell")]
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[Range(0.01f, 1000f)]
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public float CellScaleY = 0.01f;
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/// <summary>
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/// Rotate the grid based on the direction the agent is facing.
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/// </summary>
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[Tooltip("Rotate the grid based on the direction the agent is facing")]
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public bool RotateToAgent;
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/// <summary>
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/// Array holding the depth of each channel.
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/// </summary>
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[Tooltip("Array holding the depth of each channel")]
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public int[] ChannelDepth;
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/// <summary>
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/// List of tags that are detected.
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/// </summary>
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[Tooltip("List of tags that are detected")]
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public string[] DetectableObjects;
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/// <summary>
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/// The layer mask.
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/// </summary>
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[Tooltip("The layer mask")]
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public LayerMask ObserveMask;
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/// <summary>
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/// Enum describing what kind of depth type the data should be organized as
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/// </summary>
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public enum GridDepthType { Channel, ChannelHot };
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/// <summary>
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/// The data layout that the grid should output.
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/// </summary>
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[Tooltip("The data layout that the grid should output")]
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public GridDepthType gridDepthType = GridDepthType.Channel;
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/// <summary>
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/// The reference of the root of the agent. This is used to disambiguate objects with the same tag as the agent. Defaults to current GameObject.
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/// </summary>
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[Tooltip("The reference of the root of the agent. This is used to disambiguate objects with the same tag as the agent. Defaults to current GameObject")]
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public GameObject rootReference;
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//
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// Hidden Parameters
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//
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/// <summary>
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/// The total number of observations per cell of the grid. Its equivalent to the "channel" on the outgoing tensor.
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/// </summary>
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[HideInInspector]
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public int ObservationPerCell;
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/// <summary>
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/// The total number of observations that this GridSensor provides. It is the length of m_PerceptionBuffer.
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/// </summary>
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[HideInInspector]
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public int NumberOfObservations;
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/// <summary>
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/// The offsets used to specify where within a cell's allotted data, certain observations will be inserted.
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/// </summary>
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[HideInInspector]
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public int[] ChannelOffsets;
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/// <summary>
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/// The main storage of perceptual information.
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/// </summary>
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protected float[] m_PerceptionBuffer;
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/// <summary>
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/// The default value of the perceptionBuffer when using the ChannelHot DepthType. Used to reset the array/
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/// </summary>
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protected float[] m_ChannelHotDefaultPerceptionBuffer;
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/// <summary>
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/// Array of Colors needed in order to load the values of the perception buffer to a texture.
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/// </summary>
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protected Color[] m_PerceptionColors;
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/// <summary>
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/// Texture where the colors are written to so that they can be compressed in PNG format.
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/// </summary>
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protected Texture2D m_perceptionTexture2D;
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//
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// Utility Constants Calculated on Init
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//
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/// <summary>
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/// Number of PNG formated images that are sent to python during training.
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/// </summary>
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private int NumImages;
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/// <summary>
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/// Number of relevant channels on the last image that is sent/
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/// </summary>
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private int NumChannelsOnLastImage;
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/// <summary>
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/// Radius of grid, used for normalizing the distance.
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/// </summary>
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protected float SphereRadius;
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/// <summary>
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/// Total Number of cells (width*height)
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/// </summary>
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private int NumCells;
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/// <summary>
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/// Difference between GridNumSideZ and gridNumSideX.
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/// </summary>
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protected int DiffNumSideZX = 0;
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/// <summary>
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/// Offset used for calculating CellToPoint
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/// </summary>
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protected float OffsetGridNumSide = 7.5f; // (gridNumSideZ - 1) / 2;
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/// <summary>
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/// Half of the grid in the X direction
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/// </summary>
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private float HalfOfGridX;
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/// <summary>
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/// Half of the grid in the z direction
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/// </summary>
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private float HalfOfGridZ;
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/// <summary>
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/// Used in the PointToCell method to scale the x value to land in the calculated cell.
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/// </summary>
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private float PointToCellScalingX;
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/// <summary>
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/// Used in the PointToCell method to scale the y value to land in the calculated cell.
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/// </summary>
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private float PointToCellScalingZ;
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/// <summary>
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/// Bool if initialized or not.
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/// </summary>
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protected bool Initialized = false;
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/// <summary>
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/// Array holding the dimensions of the resulting tensor
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/// </summary>
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private int[] m_Shape;
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//
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// Debug Parameters
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//
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/// <summary>
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/// Array of Colors used for the grid gizmos.
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/// </summary>
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[Header("Debug Options")]
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[Tooltip("Array of Colors used for the grid gizmos")]
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public Color[] DebugColors;
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/// <summary>
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/// The height of the gizmos grid.
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/// </summary>
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[Tooltip("The height of the gizmos grid")]
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public float GizmoYOffset = 0f;
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/// <summary>
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/// Whether to show gizmos or not.
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/// </summary>
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[Tooltip("Whether to show gizmos or not")]
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public bool ShowGizmos = false;
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public SensorCompressionType CompressionType = SensorCompressionType.PNG;
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/// <summary>
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/// Array of colors displaying the DebugColors for each cell in OnDrawGizmos. Only updated if ShowGizmos.
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/// </summary>
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protected Color[] CellActivity;
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/// <summary>
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/// Array of positions where each position is the center of a cell.
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/// </summary>
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private Vector3[] CellPoints;
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/// <summary>
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/// List representing the multiple compressed images of all of the grids
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/// </summary>
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private List<byte[]> compressedImgs;
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/// <summary>
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/// List representing the sizes of the multiple images so they can be properly reconstructed on the python side
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/// </summary>
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private List<byte[]> byteSizesBytesList;
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private Color DebugDefaultColor = new Color(1f, 1f, 1f, 0.25f);
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/// <inheritdoc/>
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public override ISensor CreateSensor()
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{
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return this;
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}
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/// <summary>
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/// Sets the parameters of the grid sensor
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/// </summary>
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/// <param name="detectableObjects">array of strings representing the tags to be detected by the sensor</param>
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/// <param name="channelDepth">array of ints representing the depth of each channel</param>
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/// <param name="gridDepthType">enum representing the GridDepthType of the sensor</param>
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/// <param name="cellScaleX">float representing the X scaling of each cell</param>
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/// <param name="cellScaleZ">float representing the Z scaling of each cell</param>
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/// <param name="gridWidth">int representing the number of cells in the X direction. Width of the Grid</param>
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/// <param name="gridHeight">int representing the number of cells in the Z direction. Height of the Grid</param>
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/// <param name="observeMaskInt">int representing the layer mask to observe</param>
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/// <param name="rotateToAgent">bool if true then the grid is rotated to the rotation of the transform the rootReference</param>
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/// <param name="debugColors">array of colors corresponding the the tags in the detectableObjects array</param>
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public virtual void SetParameters(string[] detectableObjects, int[] channelDepth, GridDepthType gridDepthType,
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float cellScaleX, float cellScaleZ, int gridWidth, int gridHeight, int observeMaskInt, bool rotateToAgent, Color[] debugColors)
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{
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this.ObserveMask = observeMaskInt;
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this.DetectableObjects = detectableObjects;
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this.ChannelDepth = channelDepth;
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this.gridDepthType = gridDepthType;
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this.CellScaleX = cellScaleX;
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this.CellScaleZ = cellScaleZ;
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this.GridNumSideX = gridWidth;
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this.GridNumSideZ = gridHeight;
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this.RotateToAgent = rotateToAgent;
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this.DiffNumSideZX = (GridNumSideZ - GridNumSideX);
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this.OffsetGridNumSide = (GridNumSideZ - 1f) / 2f;
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this.DebugColors = debugColors;
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}
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/// <summary>
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/// Initializes the constant parameters used within the perceive method call
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/// </summary>
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public void InitGridParameters()
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{
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NumCells = GridNumSideX * GridNumSideZ;
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float sphereRadiusX = (CellScaleX * GridNumSideX) / Mathf.Sqrt(2);
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float sphereRadiusZ = (CellScaleZ * GridNumSideZ) / Mathf.Sqrt(2);
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SphereRadius = Mathf.Max(sphereRadiusX, sphereRadiusZ);
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ChannelOffsets = new int[ChannelDepth.Length];
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DiffNumSideZX = (GridNumSideZ - GridNumSideX);
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OffsetGridNumSide = (GridNumSideZ - 1f) / 2f;
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HalfOfGridX = CellScaleX * GridNumSideX / 2;
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HalfOfGridZ = CellScaleZ * GridNumSideZ / 2;
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PointToCellScalingX = GridNumSideX / (CellScaleX * GridNumSideX);
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PointToCellScalingZ = GridNumSideZ / (CellScaleZ * GridNumSideZ);
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}
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/// <summary>
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/// Initializes the constant parameters that are based on the Grid Depth Type
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/// Sets the ObservationPerCell and the ChannelOffsets properties
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/// </summary>
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public virtual void InitDepthType()
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{
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switch (gridDepthType)
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{
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case GridDepthType.Channel:
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ObservationPerCell = ChannelDepth.Length;
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break;
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case GridDepthType.ChannelHot:
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ObservationPerCell = 0;
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ChannelOffsets[ChannelOffsets.Length - 1] = 0;
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for (int i = 1; i < ChannelDepth.Length; i++)
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{
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ChannelOffsets[i] = ChannelOffsets[i - 1] + ChannelDepth[i - 1];
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}
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for (int i = 0; i < ChannelDepth.Length; i++)
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{
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ObservationPerCell += ChannelDepth[i];
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}
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break;
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}
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// The maximum number of channels in the final output must be less than 255 * 3 because the "number of PNG images" to generate must fit in one byte
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Assert.IsTrue(ObservationPerCell < (255 * 3), "The maximum number of channels per cell must be less than 255 * 3");
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}
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/// <summary>
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/// Initializes the location of the CellPoints property
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/// </summary>
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private void InitCellPoints()
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{
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CellPoints = new Vector3[NumCells];
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for (int i = 0; i < NumCells; i++)
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{
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CellPoints[i] = CellToPoint(i, false);
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}
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}
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/// <summary>
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/// Initializes the m_ChannelHotDefaultPerceptionBuffer with default data in the case that the grid depth type is ChannelHot
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/// </summary>
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public virtual void InitChannelHotDefaultPerceptionBuffer()
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{
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m_ChannelHotDefaultPerceptionBuffer = new float[ObservationPerCell];
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for (int i = 0; i < ChannelDepth.Length; i++)
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{
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if (ChannelDepth[i] > 1)
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{
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m_ChannelHotDefaultPerceptionBuffer[ChannelOffsets[i]] = 1;
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}
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}
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}
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/// <summary>
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/// Initializes the m_PerceptionBuffer as the main data storage property
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/// Calculates the NumImages and NumChannelsOnLastImage that are used for serializing m_PerceptionBuffer
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/// </summary>
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public void InitPerceptionBuffer()
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{
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if (Application.isPlaying)
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Initialized = true;
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NumberOfObservations = ObservationPerCell * NumCells;
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m_PerceptionBuffer = new float[NumberOfObservations];
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if (gridDepthType == GridDepthType.ChannelHot)
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{
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InitChannelHotDefaultPerceptionBuffer();
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}
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m_PerceptionColors = new Color[NumCells];
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NumImages = ObservationPerCell / 3;
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NumChannelsOnLastImage = ObservationPerCell % 3;
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if (NumChannelsOnLastImage == 0)
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NumChannelsOnLastImage = 3;
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else
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NumImages += 1;
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CellActivity = new Color[NumCells];
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}
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/// <summary>
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/// Calls the initialization methods. Creates the data storing properties used to send the data
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/// Establishes
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/// </summary>
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public virtual void Start()
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{
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InitGridParameters();
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InitDepthType();
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InitCellPoints();
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InitPerceptionBuffer();
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// Default root reference to current game object
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if (rootReference == null)
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rootReference = gameObject;
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m_Shape = new[] { GridNumSideX, GridNumSideZ, ObservationPerCell };
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compressedImgs = new List<byte[]>();
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byteSizesBytesList = new List<byte[]>();
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m_perceptionTexture2D = new Texture2D(GridNumSideX, GridNumSideZ, TextureFormat.RGB24, false);
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}
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/// <summary>
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/// Clears the perception buffer before loading in new data. If the gridDepthType is ChannelHot, then it initializes the
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/// Reset() also reinits the cell activity array (for debug)
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/// </summary>
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public void Reset()
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{
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if (m_PerceptionBuffer != null)
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{
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if (gridDepthType == GridDepthType.ChannelHot)
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{
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// Copy the default value to the array
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for (int i = 0; i < NumCells; i++)
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{
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Array.Copy(m_ChannelHotDefaultPerceptionBuffer, 0, m_PerceptionBuffer, i * ObservationPerCell, ObservationPerCell);
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}
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}
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else
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{
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Array.Clear(m_PerceptionBuffer, 0, m_PerceptionBuffer.Length);
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}
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}
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else
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{
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m_PerceptionBuffer = new float[NumberOfObservations];
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}
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if (ShowGizmos)
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{
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// Ensure to init arrays if not yet assigned (for editor)
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if (CellActivity == null)
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CellActivity = new Color[NumCells];
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// Assign the default color to the cell activities
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for (int i = 0; i < NumCells; i++)
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{
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CellActivity[i] = DebugDefaultColor;
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}
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}
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}
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/// <summary>Gets the shape of the grid observation</summary>
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/// <returns>integer array shape of the grid observation</returns>
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public int[] GetFloatObservationShape()
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{
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m_Shape = new[] { GridNumSideX, GridNumSideZ, ObservationPerCell };
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return m_Shape;
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}
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/// <inheritdoc/>
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public string GetName()
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{
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return Name;
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}
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/// <inheritdoc/>
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public virtual SensorCompressionType GetCompressionType()
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{
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return CompressionType;
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}
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/// <inheritdoc/>
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public BuiltInSensorType GetBuiltInSensorType()
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{
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return BuiltInSensorType.GridSensor;
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}
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/// <summary>
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/// GetCompressedObservation - Calls Perceive then puts the data stored on the perception buffer
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/// onto the m_perceptionTexture2D to be converted to a byte array and returned
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/// </summary>
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/// <returns>byte[] containing the compressed observation of the grid observation</returns>
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public byte[] GetCompressedObservation()
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{
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using (TimerStack.Instance.Scoped("GridSensor.GetCompressedObservation"))
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{
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Perceive(); // Fill the perception buffer with observed data
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var allBytes = new List<byte>();
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for (int i = 0; i < NumImages - 1; i++)
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{
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ChannelsToTexture(3 * i, 3);
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allBytes.AddRange(m_perceptionTexture2D.EncodeToPNG());
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}
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ChannelsToTexture(3 * (NumImages - 1), NumChannelsOnLastImage);
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allBytes.AddRange(m_perceptionTexture2D.EncodeToPNG());
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return allBytes.ToArray();
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}
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}
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/// <summary>
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/// ChannelsToTexture - Takes the channel index and the numChannelsToAdd.
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/// For each cell and for each channel to add, sets it to a value of the color specified for that cell.
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/// All colors are then set to the perceptionTexture via SetPixels.
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/// m_perceptionTexture2D can then be read as an image as it now contains all of the information that was
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/// stored in the channels
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/// </summary>
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/// <param name="channelIndex"></param>
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/// <param name="numChannelsToAdd"></param>
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protected void ChannelsToTexture(int channelIndex, int numChannelsToAdd)
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{
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for (int i = 0; i < NumCells; i++)
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{
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for (int j = 0; j < numChannelsToAdd; j++)
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{
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m_PerceptionColors[i][j] = m_PerceptionBuffer[i * ObservationPerCell + channelIndex + j];
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}
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}
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m_perceptionTexture2D.SetPixels(m_PerceptionColors);
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}
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/// <summary>
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/// Perceive - Clears the buffers, calls overlap box on the actual cell (the actual perception part)
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/// for all found colliders, LoadObjectData is called
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/// at the end, Perceive returns the float array of the perceptions
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/// </summary>
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/// <returns>A float[] containing all of the information collected from the gridsensor</returns>
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public float[] Perceive()
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{
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Reset();
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using (TimerStack.Instance.Scoped("GridSensor.Perceive"))
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{
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// TODO: make these part of the class
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Collider[] foundColliders = null;
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Vector3 cellCenter = Vector3.zero;
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Vector3 halfCellScale = new Vector3(CellScaleX / 2f, CellScaleY, CellScaleZ / 2f);
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for (int cellIndex = 0; cellIndex < NumCells; cellIndex++)
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{
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if (RotateToAgent)
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{
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cellCenter = transform.TransformPoint(CellPoints[cellIndex]);
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foundColliders = Physics.OverlapBox(cellCenter, halfCellScale, transform.rotation, ObserveMask);
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}
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else
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{
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cellCenter = transform.position + CellPoints[cellIndex];
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foundColliders = Physics.OverlapBox(cellCenter, halfCellScale, Quaternion.identity, ObserveMask);
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}
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if (foundColliders != null && foundColliders.Length > 0)
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{
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ParseColliders(foundColliders, cellIndex, cellCenter);
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}
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}
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}
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return m_PerceptionBuffer;
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}
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/// <summary>
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/// Parses the array of colliders found within a cell. Finds the closest gameobject to the agent root reference within the cell
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/// </summary>
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/// <param name="foundColliders">Array of the colliders found within the cell</param>
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/// <param name="cellIndex">The index of the cell</param>
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/// <param name="cellCenter">The center position of the cell</param>
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protected virtual void ParseColliders(Collider[] foundColliders, int cellIndex, Vector3 cellCenter)
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{
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GameObject currentColliderGo = null;
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GameObject closestColliderGo = null;
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Vector3 closestColliderPoint = Vector3.zero;
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float distance = float.MaxValue;
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float currentDistance = 0f;
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for (int i = 0; i < foundColliders.Length; i++)
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{
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currentColliderGo = foundColliders[i].gameObject;
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// Continue if the current collider go is the root reference
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if (currentColliderGo == rootReference)
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continue;
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closestColliderPoint = foundColliders[i].ClosestPointOnBounds(cellCenter);
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currentDistance = Vector3.Distance(closestColliderPoint, rootReference.transform.position);
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// Checks if our colliders contain a detectable object
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if ((Array.IndexOf(DetectableObjects, currentColliderGo.tag) > -1) && (currentDistance < distance))
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{
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distance = currentDistance;
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closestColliderGo = currentColliderGo;
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}
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}
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if (closestColliderGo != null)
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LoadObjectData(closestColliderGo, cellIndex, distance / SphereRadius);
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}
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/// <summary>
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/// GetObjectData - returns an array of values that represent the game object
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/// This is one of the few methods that one may need to override to get their required functionality
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/// For instance, if one wants specific information about the current gameobject, they can use this method
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/// to extract it and then return it in an array format.
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/// </summary>
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/// <returns>
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/// A float[] containing the data that holds the representative information of the passed in gameObject
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/// </returns>
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/// <param name="currentColliderGo">The game object that was found colliding with a certain cell</param>
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/// <param name="typeIndex">The index of the type (tag) of the gameObject.
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/// (e.g., if this GameObject had the 3rd tag out of 4, type_index would be 2.0f)</param>
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/// <param name="normalizedDistance">A float between 0 and 1 describing the ratio of
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/// the distance currentColliderGo is compared to the edge of the gridsensor</param>
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/// <example>
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/// Here is an example of extenind GetObjectData to include information about a potential Rigidbody:
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/// <code>
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/// protected override float[] GetObjectData(GameObject currentColliderGo,
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/// float type_index, float normalized_distance)
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/// {
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/// float[] channelValues = new float[ChannelDepth.Length]; // ChannelDepth.Length = 4 in this example
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/// channelValues[0] = type_index;
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/// Rigidbody goRb = currentColliderGo.GetComponent<Rigidbody>();
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/// if (goRb != null)
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/// {
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/// channelValues[1] = goRb.velocity.x;
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/// channelValues[2] = goRb.velocity.y;
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/// channelValues[3] = goRb.velocity.z;
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/// }
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/// return channelValues;
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/// }
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/// </code>
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/// </example>
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protected virtual float[] GetObjectData(GameObject currentColliderGo, float typeIndex, float normalizedDistance)
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{
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float[] channelValues = new float[ChannelDepth.Length];
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channelValues[0] = typeIndex;
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return channelValues;
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}
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/// <summary>
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/// Runs basic validation assertions to check that the values can be normalized
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/// </summary>
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/// <param name="channelValues">The values to be validated</param>
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/// <param name="currentColliderGo">The gameobject used for better error messages</param>
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protected virtual void ValidateValues(float[] channelValues, GameObject currentColliderGo)
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{
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for (int j = 0; j < channelValues.Length; j++)
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{
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if (channelValues[j] < 0)
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throw new UnityAgentsException("Expected ChannelValue[" + j + "] for " + currentColliderGo.name + " to be non-negative, was " + channelValues[j]);
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if (channelValues[j] > ChannelDepth[j])
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throw new UnityAgentsException("Expected ChannelValue[" + j + "] for " + currentColliderGo.name + " to be less than ChannelDepth[" + j + "] (" + ChannelDepth[j] + "), was " + channelValues[j]);
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}
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}
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/// <summary>
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/// LoadObjectData - If the GameObject matches a tag, GetObjectData is called to extract the data from the GameObject
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/// then the data is transformed based on the GridDepthType of the gridsensor.
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/// Further documetation on the GridDepthType can be found below
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/// </summary>
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/// <param name="currentColliderGo">The game object that was found colliding with a certain cell</param>
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/// <param name="cellIndex">The index of the current cell</param>
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/// <param name="normalized_distance">A float between 0 and 1 describing the ratio of
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/// the distance currentColliderGo is compared to the edge of the gridsensor</param>
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protected virtual void LoadObjectData(GameObject currentColliderGo, int cellIndex, float normalized_distance)
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{
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for (int i = 0; i < DetectableObjects.Length; i++)
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{
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if (currentColliderGo != null && currentColliderGo.CompareTag(DetectableObjects[i]))
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{
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// TODO: Create the array already then set the values using "out" in GetObjectData
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// Using i+1 as the type index as "0" represents "empty"
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float[] channelValues = GetObjectData(currentColliderGo, (float)i + 1, normalized_distance);
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ValidateValues(channelValues, currentColliderGo);
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if (ShowGizmos)
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{
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Color debugRayColor = Color.white;
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if (DebugColors.Length > 0)
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{
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debugRayColor = DebugColors[i];
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}
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CellActivity[cellIndex] = new Color(debugRayColor.r, debugRayColor.g, debugRayColor.b, .5f);
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}
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switch (gridDepthType)
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{
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case GridDepthType.Channel:
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/// <remarks>
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/// The observations are "channel based" so each grid is WxHxC where C is the number of channels
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/// This typically means that each channel value is normalized between 0 and 1
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/// If channelDepth is 1, the value is assumed normalized, else the value is normalized by the channelDepth
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/// The channels are then stored consecutively in PerceptionBuffer.
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/// NOTE: This is the only grid type that uses floating point values
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/// For example, if a cell contains the 3rd type of 5 possible on the 2nd team of 3 possible teams:
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/// channelValues = {2, 1}
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/// ObservationPerCell = channelValues.Length
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/// channelValues = {2f/5f, 1f/3f} = {.4, .33..}
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/// Array.Copy(channelValues, 0, PerceptionBuffer, cell_id*ObservationPerCell, ObservationPerCell);
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/// </remarks>
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for (int j = 0; j < channelValues.Length; j++)
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{
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channelValues[j] /= ChannelDepth[j];
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}
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Array.Copy(channelValues, 0, m_PerceptionBuffer, cellIndex * ObservationPerCell, ObservationPerCell);
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break;
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case GridDepthType.ChannelHot:
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/// <remarks>
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/// The observations are "channel hot" so each grid is WxHxD where D is the sum of all of the channel depths
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/// The opposite of the "channel based" case, the channel values are represented as one hot vector per channel and then concatenated together
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/// Thus channelDepth is assumed to be greater than 1.
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/// For example, if a cell contains the 3rd type of 5 possible on the 2nd team of 3 possible teams,
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/// channelValues = {2, 1}
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/// channelOffsets = {5, 3}
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/// ObservationPerCell = 5 + 3 = 8
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/// channelHotVals = {0, 0, 1, 0, 0, 0, 1, 0}
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/// Array.Copy(channelHotVals, 0, PerceptionBuffer, cell_id*ObservationPerCell, ObservationPerCell);
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/// </remarks>
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float[] channelHotVals = new float[ObservationPerCell];
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for (int j = 0; j < channelValues.Length; j++)
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{
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if (ChannelDepth[j] > 1)
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{
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channelHotVals[(int)channelValues[j] + ChannelOffsets[j]] = 1f;
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}
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else
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{
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channelHotVals[ChannelOffsets[j]] = channelValues[j];
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}
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}
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Array.Copy(channelHotVals, 0, m_PerceptionBuffer, cellIndex * ObservationPerCell, ObservationPerCell);
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break;
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}
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break;
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}
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}
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}
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/// <summary>Converts the index of the cell to the 3D point (y is zero)</summary>
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/// <returns>Vector3 of the position of the center of the cell</returns>
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/// <param name="cell">The index of the cell</param>
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/// <param name="shouldTransformPoint">Bool weather to transform the point to the current transform</param>
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protected Vector3 CellToPoint(int cell, bool shouldTransformPoint = true)
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{
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float x = (cell % GridNumSideZ - OffsetGridNumSide) * CellScaleX;
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float z = (cell / GridNumSideZ - OffsetGridNumSide) * CellScaleZ - DiffNumSideZX;
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if (shouldTransformPoint)
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return transform.TransformPoint(new Vector3(x, 0, z));
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return new Vector3(x, 0, z);
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}
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/// <summary>Finds the cell in which the given global point falls</summary>
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/// <returns>
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/// The index of the cell in which the global point falls or -1 if the point does not fall into a cell
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/// </returns>
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/// <param name="globalPoint">The 3D point in global space</param>
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public int PointToCell(Vector3 globalPoint)
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{
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Vector3 point = transform.InverseTransformPoint(globalPoint);
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if (point.x < -HalfOfGridX || point.x > HalfOfGridX || point.z < -HalfOfGridZ || point.z > HalfOfGridZ)
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return -1;
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float x = point.x + HalfOfGridX;
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float z = point.z + HalfOfGridZ;
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int _x = (int)Mathf.Floor(x * PointToCellScalingX);
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int _z = (int)Mathf.Floor(z * PointToCellScalingZ);
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return GridNumSideX * _z + _x;
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}
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/// <summary>Copies the data from one cell to another</summary>
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/// <param name="fromCellID">index of the cell to copy from</param>
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/// <param name="toCellID">index of the cell to copy into</param>
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protected void CopyCellData(int fromCellID, int toCellID)
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{
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Array.Copy(m_PerceptionBuffer,
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fromCellID * ObservationPerCell,
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m_PerceptionBuffer,
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toCellID * ObservationPerCell,
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ObservationPerCell);
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if (ShowGizmos)
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CellActivity[toCellID] = CellActivity[fromCellID];
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}
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/// <summary>Creates a copy of a float array</summary>
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/// <returns>float[] of the original data</returns>
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/// <param name="array">The array to copy from</parma>
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private static float[] CreateCopy(float[] array)
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{
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float[] b = new float[array.Length];
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System.Buffer.BlockCopy(array, 0, b, 0, array.Length * sizeof(float));
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return b;
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}
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/// <summary>Utility method to find the index of a tag</summary>
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/// <returns>Index of the tag in DetectableObjects, if it is in there</returns>
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/// <param name="tag">The tag to search for</param>
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public int IndexOfTag(string tag)
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{
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return Array.IndexOf(DetectableObjects, tag);
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}
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void OnDrawGizmos()
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{
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if (ShowGizmos)
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{
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if (Application.isEditor && !Application.isPlaying)
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Start();
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Perceive();
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Vector3 scale = new Vector3(CellScaleX, 1, CellScaleZ);
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Vector3 offset = new Vector3(0, GizmoYOffset, 0);
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Matrix4x4 oldGizmoMatrix = Gizmos.matrix;
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Matrix4x4 cubeTransform = Gizmos.matrix;
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for (int i = 0; i < NumCells; i++)
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{
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if (RotateToAgent)
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{
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cubeTransform = Matrix4x4.TRS(CellToPoint(i) + offset, transform.rotation, scale);
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}
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else
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{
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cubeTransform = Matrix4x4.TRS(CellToPoint(i, false) + transform.position + offset, Quaternion.identity, scale);
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}
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Gizmos.matrix = oldGizmoMatrix * cubeTransform;
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Gizmos.color = CellActivity[i];
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Gizmos.DrawCube(Vector3.zero, Vector3.one);
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}
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Gizmos.matrix = oldGizmoMatrix;
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if (Application.isEditor && !Application.isPlaying)
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DestroyImmediate(m_perceptionTexture2D);
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}
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}
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/// <inheritdoc/>
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void ISensor.Update() { }
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/// <summary>Gets the observation shape</summary>
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/// <returns>int[] of the observation shape</returns>
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public override int[] GetObservationShape()
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{
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m_Shape = new[] { GridNumSideX, GridNumSideZ, ObservationPerCell };
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return m_Shape;
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}
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/// <inheritdoc/>
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public int Write(ObservationWriter writer)
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{
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using (TimerStack.Instance.Scoped("GridSensor.WriteToTensor"))
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{
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Perceive();
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int index = 0;
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for (var h = GridNumSideZ - 1; h >= 0; h--) // height
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{
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for (var w = 0; w < GridNumSideX; w++) // width
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{
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for (var d = 0; d < ObservationPerCell; d++) // depth
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{
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writer[h, w, d] = m_PerceptionBuffer[index];
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index++;
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}
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}
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}
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return index;
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}
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}
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}
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}
|