Differences

This shows you the differences between two versions of the page.

--- documents:120206pyip_cooking:python_imagej_cookbook [2025/10/05 22:32] – [Java native 2D Array from Python2D] kota
+++ documents:120206pyip_cooking:python_imagej_cookbook [2025/10/05 22:53] (current) – [Converting Java array types] kota
@@ Line 783: / Line 783: @@
 Here is an example of creating a floating-point image from 2D array.
-<code python>
+<code python linenums:1>
 from jarray import zeros
 from ij import ImagePlus
@@ Line 806: / Line 806: @@
 ImagePlus('fp', fp).show()
 </code>
+In short, as simple as:
+<code python linenums:1>
+from jarray import zeros
+from ij import ImagePlus
+from ij.process import FloatProcessor
+matrix2D = [zeros(100, 'f')]*200
+ImagePlus('fp', FloatProcessor(matrix2D)).show()
+</code>
 ==== Converting Java array types ====
-Sometimes we need to convert the type of Java array e.g. double[] to int[]. For this, there is no magic trick and need to run a loop. Below is a code fragment.
+Sometimes we need to convert the type of Java array e.g. double[] to int[]. In Java we can do this by a for-loop with casting from float to int, but in Jython we can use the map function.
 <code:py>
+from ij import IJ
 from ij.process import StackStatistics
 import jarray
+imp = IJ.getImage() #stack
 stackstats = StackStatistics(imp)
-histD = stackstats.histogram()
+histD = stackstats.histogram() #double[] returned, taken as floats in python
-hist = jarray.zeros(len(histD), 'i')
+print(type(histD[0]))
-for i in range(len(histD)):
-    hist[i] = int(histD[i])
+hist = map(int, histD)
+histInt = jarray.array(hist, 'i')
+print(type(histInt[0])) #Java int[]
 </code>