empty space ok, started K

MontpellierRessourcesImagerie · Nov 6, 2023 · 82389c0 · 82389c0
1 parent 91c457c
commit 82389c0
Show file tree

Hide file tree

Showing 9 changed files with 139 additions and 30 deletions.
diff --git a/all_distances_eCDF_workspace.py b/all_distances_eCDF_workspace.py
@@ -0,0 +1,37 @@
+from ij import IJ
+from ij.process import StackStatistics
+from ij.measure import ResultsTable
+from fr.cnrs.mri.cialib.stats import Histogram
+
+
+TABLE = "DistCenterCenterUnit"
+
+table = ResultsTable.getResultsTable(TABLE)
+image = IJ.getImage()
+cal = image.getCalibration()
+width, height, _, nSlices, _ = image.getDimensions()
+print(width, height, nSlices)
+width = cal.getX(width)
+height = cal.getY(height)
+depth = cal.getZ(nSlices)
+print(width, height, depth)
+volume = width * height * depth
+print("volume", volume)
+
+N = int(StackStatistics(image).max)
+distances = []
+
+for i in range(2, N+1):
+    dists = list(table.getColumn("V" + str(i)))
+    print(i, len(dists))
+    distances.extend(dists)
+
+print(max(distances))
+print(len(distances))
+
+hist = Histogram(distances, start=0, end=100, nBins=1000)
+hist.calculate()
+hist.getPlot().show()
+hist.cumulate()
+hist.normalizeRipley(volume)
+hist.getPlot().show()
diff --git a/createESeCDF.py b/createESeCDF.py
@@ -8,7 +8,7 @@
 
 image = IJ.getImage()
 nrOfRefPoints = int(StackStatistics(image).max)
-eCDF = EmptySpaceEmpiricalCDF(image, 300)
+eCDF = EmptySpaceEmpiricalCDF(image, nrOfRefPoints)
 hist = eCDF.get()
 plot = hist.getPlot(title=image.getTitle()+" (empty space eCDF)")
 plot.setStyle(0, COLOR+","+COLOR+",2,line")

diff --git a/sample_clustered_points.json b/sample_clustered_points.json
@@ -52,7 +52,7 @@
             "label": "Number Of Samples: ", 
             "type": "int", 
             "sameRow": false, 
-            "value": 1000, 
+            "value": 910, 
             "key": "number", 
             "order": 8
         }, 
@@ -85,7 +85,7 @@
             "label": "Number of Images: ", 
             "type": "int", 
             "sameRow": true, 
-            "value": 100, 
+            "value": 10, 
             "key": "number-of-images", 
             "order": 15
         }, 
@@ -118,7 +118,7 @@
             "label": "Output Folder: ", 
             "type": "directory", 
             "sameRow": true, 
-            "value": "/home/baecker/Documents/mri/2023/mifobio/experiments/A01-spot-detection/clustered2/", 
+            "value": "/home/baecker/Documents/mri/2023/mifobio/experiments/A01-C-spot-detection-extreme-patterns/clustered/", 
             "key": "output-folder", 
             "order": 16
         }, 
@@ -129,7 +129,7 @@
             "label": "Max.-Dist. from cluster center: ", 
             "type": "float", 
             "sameRow": true, 
-            "value": 5.0, 
+            "value": 10.0, 
             "key": "max.-dist.", 
             "order": 13
         }, 
@@ -140,7 +140,7 @@
             "label": "Clusters: ", 
             "type": "int", 
             "sameRow": false, 
-            "value": 50, 
+            "value": 100, 
             "key": "clusters", 
             "order": 12
         }, 

diff --git a/sample_dispersed_points.json b/sample_dispersed_points.json
@@ -10,7 +10,7 @@
             "label": "Batch ", 
             "type": "bool", 
             "sameRow": false, 
-            "value": false, 
+            "value": true, 
             "key": "batch", 
             "order": 11
         }, 
@@ -85,7 +85,7 @@
             "label": "Number of Images: ", 
             "type": "int", 
             "sameRow": true, 
-            "value": 100, 
+            "value": 10, 
             "key": "number-of-images", 
             "order": 12
         }, 
@@ -118,7 +118,7 @@
             "label": "Output Folder: ", 
             "type": "directory", 
             "sameRow": true, 
-            "value": "/home/baecker/Documents/mri/2023/mifobio/experiments/A01-spot-detection/", 
+            "value": "/home/baecker/Documents/mri/2023/mifobio/experiments/A01-C-spot-detection-extreme-patterns/dispersed/", 
             "key": "output-folder", 
             "order": 12
         }, 
@@ -129,7 +129,7 @@
             "label": "Max.-Dist. from grid: ", 
             "type": "float", 
             "sameRow": false, 
-            "value": 3.0, 
+            "value": 2.0, 
             "key": "max.-dist.", 
             "order": 9
         }, 

diff --git a/sample_random_points.json b/sample_random_points.json
@@ -74,7 +74,7 @@
             "label": "Number of Images: ", 
             "type": "int", 
             "sameRow": true, 
-            "value": 100, 
+            "value": 10, 
             "key": "number-of-images", 
             "order": 11
         }, 
@@ -118,7 +118,7 @@
             "label": "Output Folder: ", 
             "type": "directory", 
             "sameRow": true, 
-            "value": "/home/baecker/Documents/mri/2023/mifobio/experiments/A01-spot-detection/uniform/", 
+            "value": "/home/baecker/Documents/mri/2023/mifobio/experiments/A01-C-spot-detection-extreme-patterns/uniform/", 
             "key": "output-folder", 
             "order": 12
         }, 

diff --git a/spatialstats.py b/spatialstats.py
@@ -32,13 +32,17 @@ def __init__(self, density):
     def getPlot(self, start, end, n):  
         X = [start + (x * ((end-start)/n)) for x in range(0, n)]
         Y = [self.v(x) for x in X]
-        plot = Plot(self.name() +"(density=" + str(self.density) + ")", "distance d[micron]", "fraction of distances <= d")
+        plot = Plot(self.getPlotTitle(), "distance d[micron]", "fraction of distances <= d")
         plot.setLineWidth(2)
         plot.setLimitsToFit(True)
         plot.add("line", X, Y)
         return plot
 
 
+    def getPlotTitle(self):
+        title = self.name() +"(density=" + str(self.density) + ")"        
+        return title    
+
 
 class GFunction(SpatialStatFunction):
 
@@ -49,7 +53,6 @@ def __init__(self, density):
 
 
     def v(self, r):
-        l = self.density
         res = 1 - math.exp(self.factor * r**3)
         return res
 
@@ -68,7 +71,6 @@ def __init__(self, density):
 
 
     def v(self, r):
-        l = self.density
         res = 1 - math.exp(self.factor * r**3)
         return res
 
@@ -78,6 +80,70 @@ def name(self):
 
 
 
+class KFunction(SpatialStatFunction):
+
+
+    def __init__(self):
+        self.factor = (4 * math.pi) / 3
+
+
+    def v(self, r):
+        res = self.factor * r**3
+        return res
+
+
+    def name(self):
+        return "K"
+
+
+    def getPlotTitle(self):
+        title = self.name()  
+        return title    
+
+
+
+class LFunction(SpatialStatFunction):
+
+
+    def __init__(self):
+        factor = 1
+
+
+    def v(self, r):
+        return r
+
+
+    def name(self):
+        return "L"
+
+
+    def getPlotTitle(self):
+        title = self.name()  
+        return title
+
+
+
+class HFunction(SpatialStatFunction):
+
+
+    def __init__(self):
+        factor = 0
+
+
+    def v(self, r):
+        return 0
+
+
+    def name(self):
+        return "H"
+
+
+    def getPlotTitle(self):
+        title = self.name()  
+        return title
+
+
+
 class ECDF(object):
 
 
@@ -192,7 +258,7 @@ def calculateDistances(self):
         pop.addObjects(objects)
         refPop = Objects3DIntPopulation()
         refPop.addObjects(refObjects)
-        analyzer = MeasurePopulationClosestDistance(pop, refPop, Double.POSITIVE_INFINITY, MeasurePopulationClosestDistance.CLOSEST_CC1_UNIT)
+        analyzer = MeasurePopulationClosestDistance(refPop, pop, Double.POSITIVE_INFINITY, MeasurePopulationClosestDistance.CLOSEST_CC1_UNIT)
         table = analyzer.getResultsTableOnlyColoc(True)
         self.distances = list(table.getColumn("V1"))
 
@@ -205,18 +271,6 @@ def getReferencePoints(self):
         return self.referencePoints
 
 
-    def getGenerator(self, nrOfSamples):
-        generator = DispersedRandomSpotGenerator()
-        width, height, _, nSlices, _ = self.source.getDimensions()
-        generator.width = width
-        generator.height = height
-        generator.depth = nSlices
-        generator.calibration = self.source.getCalibration()
-        generator.bitDepth = self.source.getBitDepth()        
-        generator.numberOfSamples = nrOfSamples      
-        return generator
-
-
 
 class Envelope(object):
 

diff --git a/stats.py b/stats.py
@@ -24,6 +24,7 @@ def __init__(self, data, start=0, end=0, nBins=0):
         self.mode = 0
         self.xLabel =  "distance [micron]"
         self.yLabel = "count"
+        self.N = 0
 
 
     def calculate(self):
@@ -46,11 +47,22 @@ def cumulate(self):
             self.calculate()
         for i in range(1, len(self.counts)):
             self.counts[i] = self.counts[i] + self.counts[i-1]
+        self.N = self.counts[-1]
+        print("N", self.N)
         for i in range(0, len(self.counts)):
-            self.counts[i] = self.counts[i] / self.counts[-1]
+            self.counts[i] = self.counts[i] / self.N
         self.xLabel = "distance d [micron]"
         self.yLabel = "fraction of distances <= d"
 
+
+    def normalizeRipley(self, volume):
+        density = self.N / volume
+        print('N', self.N)
+        print("volume", volume)
+        print("density", density)
+        for i in range(0, len(self.counts)):
+            self.counts[i] = self.counts[i] / density
+
 
     def getPlot(self, title = "data"):
         label = self.xLabel + " (N=" + str(self.stats.count) \

diff --git a/tools/K_func.py b/tools/K_func.py
@@ -0,0 +1,6 @@
+from fr.cnrs.mri.cialib.spatialstats import KFunction 
+
+
+k = KFunction()
+plot = k.getPlot(0, 95, 1000)
+plot.show()
diff --git a/workspace3.py b/workspace3.py
@@ -9,7 +9,7 @@
 cal = IJ.getImage().getCalibration()
 gen.calibration = None
 
-N = 3000
+N = 1200
 width = 1030
 height = 1030
 depth = 64