public void OnReceiveUpload(string jsonText)
{
GeneSet genes = null;
try
{
loadingSpinner.SetActive(true);
var json = JSONObject.Parse(jsonText);
var filename = json.GetString("filename");
var data = json.GetString("data");
Debug.Log("OnReceiveUpload filename: " + filename);
Debug.Log("OnReceiveUpload data: " + data);
genes = ParseGeneSet(data);
DebugLogGeneSet(genes);
}
catch
{
loadingSpinner.SetActive(false);
}
StartCoroutine(GameObject.Find("ScriptHolder").GetComponent <Colour>().ColourByGeneSet(genes));
}
internal void SetFamily(Creature motherCreature, Creature fatherCreature, uint no)
{
mother = motherCreature;
father = fatherCreature;
Generation = (uint)Mathf.FloorToInt(Mathf.Max(motherCreature.Generation, fatherCreature.Generation)) + 1;
childNo = no;
birthTime = Time.time;
genes = new GeneSet(motherCreature, fatherCreature);
ReproductiveUrge = 0f;
gender = (Random.Range(0, 2) == 1 ? GenderType.Male : GenderType.Female);
if (gestation != null && gender == GenderType.Male)
{
gestation.enabled = false;
}
gestation.Reactivate();
birthTime = Time.time;
name = ID;
maxNutrition = Mathf.Clamp(Mathf.Lerp(originalMaxNutrition - 2, originalMaxNutrition + 2, ability[Genotype.Nutrition]), 1, Mathf.Infinity);
maxHydration = Mathf.Clamp(Mathf.Lerp(originalMaxHydration - 2, originalMaxHydration + 2, ability[Genotype.Nutrition]), 1, Mathf.Infinity);
Nutrition = maxNutrition;
Hydration = maxHydration;
}
void Mutate(Cell start, Cell destination, int k)
{
switch (mutationType)
{
case MutationType.None:
{
if (destination.Gene != start.Gene)
{
AssignGeneToTile(k, nextGenerationIndex, 0, Cell.CellStatus.Collision);
}
break;
}
case MutationType.Average:
{
int m = (start.Gene + destination.Gene) / 2;
AssignGeneToTile(k, nextGenerationIndex, m, m == 0 ? Cell.CellStatus.Empty : Cell.CellStatus.Normal);
break;
}
case MutationType.AverageWithRandom:
{
int a = (start.Gene + destination.Gene) / 2;
int r = GeneSet.GetRandomGene();
int m = a * 4 + r;
m /= 5;
AssignGeneToTile(k, nextGenerationIndex, m, m == 0 ? Cell.CellStatus.Empty : Cell.CellStatus.Normal);
break;
}
case MutationType.Random:
{
int m = GeneSet.GetRandomGene();
AssignGeneToTile(k, nextGenerationIndex, m, m == 0 ? Cell.CellStatus.Empty : Cell.CellStatus.Normal);
break;
}
case MutationType.Barricelli:
{
if (cells[k, currentGenerationIndex].Status == Cell.CellStatus.Normal)
{
AssignGeneToTile(k, nextGenerationIndex, 0, Cell.CellStatus.Collision);
}
else
{
AssignGeneToTile(k, nextGenerationIndex, FindDistance(k), Cell.CellStatus.Normal);
}
break;
}
}
}
public CreatureBirthDataPoint(string _sn, GeneSet _gns, uint _gen, uint _cno, ParentStats _fth, ParentStats _mth)
{
sn = _sn;
gns = _gns;
gen = _gen;
cno = _cno;
fth = _fth;
mth = _mth;
}
public CreatureBirthDataPoint(Creature creature)
{
sn = creature.name;
gns = creature.genes;
gen = creature.Generation;
cno = creature.childNo;
fth = new ParentStats(creature.father);
mth = new ParentStats(creature.mother);
}
public static GeneSet GetFirstGenerationGenes()
{
GeneSet fgg = new GeneSet();
foreach (string genotype in System.Enum.GetNames(typeof(Genotype)))
{
Genotype enumGenotype;
System.Enum.TryParse(genotype, out enumGenotype);
fgg.Add(enumGenotype, Random.Range(0.4f, 0.7f));
}
fgg[Genotype.MutationChance] = Random.Range(0.01f, 0.1f);
return(fgg);
}
// Find the expression values corresponding with the entered gene, then start the colouring and similarity calculating processes
public void ColourFromText(string geneName, bool panel = false)
{
SetMaxValue();
currentGene = geneName.Trim();
CurrentGeneSet = null;
int geneIndex = FindIndexOfGene(geneName);
// If the gene name was found, load that dataset into the pieces
if (geneIndex > -1)
{
if (panel)
{
computeDistancesP(geneIndex);
//baseGene = currentGene;
}
// Update current gene info
gText.text = "Current gene: " + SentenceCase(geneName);
SetGeneSetLabels("", "");
float lMax = -1;
float lMin = 100;
if (norm)
{ // Find the local min and max if in normalised mode
for (int i = 0; i < 18; i++)
{
if (values[geneIndex].Values[i] > lMax)
{
lMax = values[geneIndex].Values[i];
}
if (values[geneIndex].Values[i] < lMin)
{
lMin = values[geneIndex].Values[i];
}
}
}
for (int i = 0; i < 18; i++)
{
colourHeartPiece(hp[i], values[geneIndex].Values[i], lMax, lMin);
}
}
else
{
// Update current gene info
gText.text = "Current gene: None";
resetColour();
//Debug.Log ("Gene with name " + geneName + " not found.");
content.GetComponent <PanelScript>().sleep();
}
}
public override object ReadJson(JsonReader reader, Type objectType, object existingValue, JsonSerializer serializer)
{
JObject jo = JObject.Load(reader);
GeneSet importedSet = new GeneSet(); // new Dictionary<Genotype, float>
foreach (KeyValuePair <string, JToken> entry in jo)
{
Genotype genotype;
Enum.TryParse(entry.Key, out genotype);
importedSet.Add(genotype, entry.Value.ToObject <float>());
}
return(importedSet);
}
public GeneSet ParseGeneSet(string text)
{
/*
* Parse a list of gene names, one per line. Also detects and parses GSEA/MSigDB format
* 'text', 'grp' and 'gmx' format (where the first two header lines are gene set name
* and description)
*/
var geneset = new GeneSet();
string name = "";
string description = "";
List <string> genes = new List <string>();
// We also split on escaped endline sequences to deal with strings deserialized from JSON
string[] lines = text.Split(
new[] { "\r\n", "\r", "\n", "\\r\\n", "\\r", "\\n" },
System.StringSplitOptions.RemoveEmptyEntries);
int count = 0;
foreach (var line in lines)
{
count++;
if (count == 2 &&
(line.Substring(0, 2) == "> " || line.Substring(0, 2) == "# "))
{
name = genes[0];
genes.RemoveAt(0);
description = line.Substring(2).Trim();
continue;
}
var geneName = line.Trim();
if (!string.IsNullOrEmpty(geneName))
{
genes.Add(geneName);
}
}
geneset.Name = name;
geneset.Description = description;
geneset.Genes = genes;
return(geneset);
}
void AssignGeneToTile(int x, int y, int gene, Cell.CellStatus status)
{
Debug.Assert(textures != null);
Debug.Assert(cells != null);
cells[x, y].Gene = Extensions.Clamp(gene, GeneSet.MinGene, GeneSet.MaxGene);
cells[x, y].Status = status;
int textureX = (x * GeneSet.width) / PNGSize;
int textureY = (y * GeneSet.height) / PNGSize;
int chunkX = (x * GeneSet.width) % PNGSize;
int chunkY = (y * GeneSet.height) % PNGSize;
Texture2D t;
Rect r;
switch (status)
{
case Cell.CellStatus.Normal:
{
t = GeneSet.GetSpriteFromGene(cells[x, y].Gene).texture;
r = GeneSet.GetSpriteFromGene(cells[x, y].Gene).textureRect;
break;
}
case Cell.CellStatus.Collision:
{
t = GeneSet.Collision.texture;
r = GeneSet.Collision.textureRect;
break;
}
default:
{
t = GeneSet.Empty.texture;
r = GeneSet.Empty.textureRect;
break;
}
}
textures[textureX, textureY].SetPixels(chunkX, chunkY,
GeneSet.width, GeneSet.height,
t.GetPixels((int)r.x, (int)r.y, (int)r.width, (int)r.height));
}
// Reset everything to how it was at the start
public void Reset()
{
cb = false;
eyeButton.image.overrideSprite = null;
colourButton.image.overrideSprite = null;
IF.text = "";
resetColour();
gText.text = "Current gene: None";
currentGene = "";
CurrentGeneSet = null;
//baseGene = "";
if (norm)
{
toggleNormalised();
}
SetGeneSetLabels("", "");
SetMaxValue();
}
public GeneSet LoadPresetGeneSet(string resourceName)
{
GeneSet genes = null;
try
{
loadingSpinner.SetActive(true);
TextAsset textAsset = Resources.Load("genesets/" + resourceName) as TextAsset;
genes = ParseGeneSet(textAsset.text);
Resources.UnloadAsset(textAsset);
DebugLogGeneSet(genes);
}
catch {
loadingSpinner.SetActive(false);
}
return(genes);
}
public void FromParentGenes(GeneSet motherGenes, GeneSet fatherGenes)
{
Clear();
foreach (string genotype in System.Enum.GetNames(typeof(Genotype)))
{
Genotype enumGenotype;
System.Enum.TryParse(genotype, out enumGenotype);
bool useFatherGenes = RandomBool;
bool mutate = Random.Range(0, Mathf.Lerp(256, 1, (motherGenes[Genotype.MutationChance] + fatherGenes[Genotype.MutationChance]) / 2)) == 0;
float geneValue = useFatherGenes ? fatherGenes[Genotype.MutationChance] : motherGenes[Genotype.MutationChance];
if (mutate)
{
geneValue += RandomBool ? geneValue : -geneValue;
}
Add(enumGenotype, Mathf.Clamp(geneValue, 0f, 1f));
}
}
private void Awake()
{
transform.parent = GameObject.Find("Creatures").transform;
originalScale = transform.localScale;
navAgent = GetComponent <NavMeshAgent>();
gestation = GetComponent <GestationHandler>();
birthTime = Time.time;
if (Generation == 1)
{
genes = GeneSet.GetFirstGenerationGenes();
birthTime = Time.time - 60f;
maxNutrition = Mathf.Clamp(Mathf.Lerp(originalMaxNutrition - 2, originalMaxNutrition + 2, ability[Genotype.Nutrition]), 1, Mathf.Infinity);
maxHydration = Mathf.Clamp(Mathf.Lerp(originalMaxHydration - 2, originalMaxHydration + 2, ability[Genotype.Nutrition]), 1, Mathf.Infinity);
Nutrition = Random.Range(1f, maxNutrition);
Hydration = Random.Range(1f, maxHydration);
ReproductiveUrge = Random.Range(0.1f, 0.35f);
}
else
{
gender = (Random.Range(0, 2) == 1 ? GenderType.Male : GenderType.Female);
}
if (gestation != null && gender == GenderType.Male)
{
gestation.enabled = false;
}
ReproductiveUrge = 0f;
CreatureDatabase.RegisterCreature(this);
specieNo = (uint)CreatureDatabase.GetCreatureCount(this);
name = ID;
StartCoroutine(UpdateSight());
}
public void DebugLogGeneSet(GeneSet genes)
{
Debug.Log("Gene set name: " + genes.Name);
Debug.Log("Gene set description: " + genes.Description);
Debug.Log("Gene set genes: " + string.Join(", ", genes.Genes.ToArray()));
}
public GeneSet(GeneSet motherGenes, GeneSet fatherGenes)
{
FromParentGenes(motherGenes, fatherGenes);
}
// Find the expression values corresponding with the entered gene, then start the colouring and similarity calculating processes
public void ColourFromText(string geneName, bool panel = false)
{
SetMaxValue();
currentGene = geneName.Trim();
string copyGene = geneCopyField.text;
CurrentGeneSet = null;
int geneIndex = FindIndexOfGene(geneName);
int copyGeneIndex = FindIndexOfGene(copyGene.Trim());
// If the gene name was found, load that dataset into the pieces
if (geneIndex > -1)
{
if (panel)
{
computeDistancesP(geneIndex);
//baseGene = currentGene;
}
// Update current gene info
gText.text = "Current gene: " + SentenceCase(geneName);
SetGeneSetLabels("", "");
float lMax = -1;
float lMin = 100;
if (norm)
{ // Find the local min and max if in normalised mode
for (int i = 0; i < 18; i++)
{
if (values[geneIndex].Values[i] > lMax)
{
lMax = values[geneIndex].Values[i];
}
if (values[geneIndex].Values[i] < lMin)
{
lMin = values[geneIndex].Values[i];
}
}
}
for (int i = 0; i < 18; i++)
{
colourHeartPiece(hp[i], values[geneIndex].Values[i], lMax, lMin);
safeOriginal(values[geneIndex].Values[i], lMax, lMin);
geneOriginalText.text = "Currently selected gene for main model: " + SentenceCase(geneName);
mainGene = SentenceCase(geneName);
}
logFile.writeToFile(SentenceCase(geneName), false);
}
if (copyGeneIndex > -1)
{
if (panel)
{
computeDistancesP(copyGeneIndex);
//baseGene = currentGene;
}
float lMax = -1;
float lMin = 100;
if (norm)
{ // Find the local min and max if in normalised mode
for (int i = 0; i < 18; i++)
{
if (values[copyGeneIndex].Values[i] > lMax)
{
lMax = values[copyGeneIndex].Values[i];
}
if (values[copyGeneIndex].Values[i] < lMin)
{
lMin = values[copyGeneIndex].Values[i];
}
}
}
for (int i = 0; i < 18; i++)
{
colourHeartPiece(copyhp[i], values[copyGeneIndex].Values[i], lMax, lMin);
safeCopy(values[copyGeneIndex].Values[i], lMax, lMin);
geneCopyText.text = "Currently selected gene for second model: " + SentenceCase(copyGene);
secondGene = SentenceCase(copyGene);
}
logFile.writeToFile(SentenceCase(copyGene), true);
}
else
{
// Update current gene info
gText.text = "Current gene: None";
resetColour();
//Debug.Log ("Gene with name " + geneName + " not found.");
content.GetComponent <PanelScript>().sleep();
}
}
void Initialize()
{
GeneSetIndex = geneSetIndex;
rowStates = new Random.State[height];
geneBrushIndex = 0;
UpdateGeneBrushPreview();
if (useSeed)
{
Random.InitState(seed);
}
else
{
seed = (int)System.DateTime.Now.Ticks;
Random.InitState(seed);
}
{
Debug.Assert(currentSeedText != null);
Text t = currentSeedText.GetComponent <Text>();
Debug.Assert(t != null);
t.text = "Seed: " + seed;
}
foreach (Transform child in transform)
{
GameObject.Destroy(child.gameObject);
}
Debug.Assert(GeneSet != null);
textureDimensionX = width * GeneSet.width / PNGSize;
if ((width * GeneSet.width) % PNGSize > 0)
{
++textureDimensionX;
}
textureDimensionY = height * GeneSet.height / PNGSize;
if ((height * GeneSet.height) % PNGSize > 0)
{
++textureDimensionY;
}
textures = new Texture2D[textureDimensionX, textureDimensionY];
chunks = new GameObject[textureDimensionX, textureDimensionY];
for (int i = 0; i < textureDimensionX; ++i)
{
for (int j = 0; j < textureDimensionY; ++j)
{
textures[i, j] = new Texture2D(
Mathf.Min(width * GeneSet.width, PNGSize),
Mathf.Min(height * GeneSet.height, PNGSize));
Debug.Assert(textures[i, j] != null);
textures[i, j].filterMode = FilterMode.Point;
Sprite sprite = Sprite.Create(
textures[i, j],
new Rect(0, 0, textures[i, j].width, textures[i, j].height),
new Vector2(0f, 0f),
1);
Debug.Assert(sprite != null);
chunks[i, j] = GameObject.Instantiate(chunkPrefab);
Debug.Assert(chunks[i, j] != null);
chunks[i, j].transform.position = new Vector3(i * PNGSize, j * PNGSize);
chunks[i, j].transform.parent = transform;
SpriteRenderer sr = chunks[i, j].GetComponent <SpriteRenderer>();
Debug.Assert(sr != null);
sr.sprite = sprite;
}
}
GeneSet.ResetMapping();
if (shuffleTileMapping)
{
Random.State tempState = Random.state;
GeneSet.ShuffleMapping();
Random.state = tempState;
}
cells = new Cell[width, height];
currentGenerationIndex = 0;
nextGenerationIndex = currentGenerationIndex + 1;
for (int y = 0; y < height; ++y)
{
for (int x = 0; x < width; ++x)
{
if (populate && y == currentGenerationIndex)
{
int randomGene = GeneSet.GetRandomGene();
AssignGeneToTile(x, y, randomGene, randomGene == 0 ? Cell.CellStatus.Empty : Cell.CellStatus.Normal);
}
else
{
AssignGeneToTile(x, y, 0, Cell.CellStatus.Empty);
}
}
}
foreach (Texture2D t in textures)
{
t.Apply();
}
}
public IEnumerator ColourByGeneSet(GeneSet geneset)
{
yield return(new WaitForSeconds(5f));
int yield_every = 10;
float yield_time = 0.05f;
//loadingSpinner.SetActive(true);
// allGeneNames gets populated on startup - we can't do anything until it's filled
while (!_allGenes_ready)
{
yield return(new WaitForSeconds(0.2f));
}
var _normalizePerGene = true;
//Debug.Log(geneset.Genes.Count);
// ResetAll();
currentGene = "";
CurrentGeneSet = geneset;
// valid genes in the uploaded gene set which are absent in the expression data
var missingGenes = new List <string>();
var averageValues = new float[18];
int count = 0;
foreach (string geneName in geneset.Genes)
{
count++;
var geneNameLower = geneName.ToLower();
if (!expressionDataNameIndexMapping.ContainsKey(geneNameLower))
{
// Debug.Log("WARNING: Gene name " + geneName + " not found in expression dataset.");
missingGenes.Add(geneName);
#if UNITY_WEBGL
//JsAlert(geneName + " is not a valid gene name.");
#endif
//return;
if (count % yield_every == 0)
{
yield return(new WaitForSeconds(yield_time));
}
continue;
}
if (!allGeneNames.Contains(geneNameLower))
{
Debug.LogError("ERROR: Gene '" + geneName + "' is not a valid mouse gene name.");
JsAlert(geneName + " is not a valid MGI mouse gene symbol (GRCm38, MGI vM9). " +
"Maybe you need to convert your gene identifiers at http://www.informatics.jax.org/batch ?");
//loadingSpinner.SetActive(false);
//return;
yield break;
}
var geneIndex = expressionDataNameIndexMapping[geneNameLower];
// var geneIndex = FindIndexOfGene(geneName);
var expressionForGene = values[geneIndex].Values.ToArray();
if (_normalizePerGene)
{
expressionForGene = NormalizeFloatArray(expressionForGene);
}
#if UNITY_EDITOR
//Debug.Log("geneName, geneIndex: " + geneName + ", " + geneIndex);
#endif
#if UNITY_EDITOR
for (int i = 0; i < 18; i++)
{
// Debug.Log("Gene: " + geneName + ", Piece " + i.ToString() + ", Value: " + expressionForGene[i].ToString());
}
#endif
// sum
for (int i = 0; i < 18; i++)
{
averageValues[i] += expressionForGene[i];
}
if (count % yield_every == 0)
{
yield return(new WaitForSeconds(yield_time));
}
}
if (missingGenes.Count > 0)
{
var _warningMsg = "WARNING: Some genes in the geneset are valid mouse genes but are absent from the expression dataset: " + string.Join(", ", missingGenes);
Debug.Log(_warningMsg);
JsAlert(_warningMsg);
}
// divide by number of genes in the set to obtain the average
for (int i = 0; i < 18; i++)
{
averageValues[i] /= geneset.Genes.Count;
}
yield return(null);
#if UNITY_EDITOR
for (int i = 0; i < 18; i++)
{
Debug.Log("Piece " + i.ToString() + " average: " + averageValues[i].ToString());
}
Debug.Log("Min: " + averageValues.Min().ToString());
Debug.Log("Max: " + averageValues.Max().ToString());
yield return(null);
#endif
// apply average colours to model
maxValue = averageValues.Max();
var minValue = averageValues.Min();
// norm = true;
for (int i = 0; i < 18; i++)
{
colourHeartPiece(hp[i], averageValues[i], maxValue, minValue);
yield return(null);
}
SetGeneSetLabels(geneset.Name, geneset.Description);
//loadingSpinner.SetActive(false);
}
// TODO: Consider making this a coroutine so we can show a loading spinner
// for larger gene sets.
public void ColourByGeneSet(GeneSet geneset)
{
var _normalizePerGene = true;
// ResetAll();
currentGene = "";
CurrentGeneSet = geneset;
var averageValues = new float[18];
foreach (string geneName in geneset.Genes)
{
var geneIndex = FindIndexOfGene(geneName);
var expressionForGene = values[geneIndex].Values.ToArray();
if (_normalizePerGene)
{
expressionForGene = NormalizeFloatArray(expressionForGene);
}
#if UNITY_EDITOR
Debug.Log("geneName, geneIndex: " + geneName + ", " + geneIndex);
#endif
if (geneIndex == -1)
{
Debug.LogError(geneName + " not found.");
#if UNITY_WEBGL
JsAlert(geneName + " is not a valid gene name.");
#endif
return;
}
#if UNITY_EDITOR
for (int i = 0; i < 18; i++)
{
Debug.Log("Gene: " + geneName + ", Piece " + i.ToString() + ", Value: " + expressionForGene[i].ToString());
}
#endif
// sum
for (int i = 0; i < 18; i++)
{
averageValues[i] += expressionForGene[i];
}
}
// divide by number of genes in the set to obtain the average
for (int i = 0; i < 18; i++)
{
averageValues[i] /= geneset.Genes.Count;
}
#if UNITY_EDITOR
for (int i = 0; i < 18; i++)
{
Debug.Log("Piece " + i.ToString() + " average: " + averageValues[i].ToString());
}
Debug.Log("Min: " + averageValues.Min().ToString());
Debug.Log("Max: " + averageValues.Max().ToString());
#endif
// apply average colours to model
maxValue = averageValues.Max();
var minValue = averageValues.Min();
// norm = true;
for (int i = 0; i < 18; i++)
{
colourHeartPiece(hp[i], averageValues[i], maxValue, minValue);
}
SetGeneSetLabels(geneset.Name, geneset.Description);
}
