v1.01 : added the "Ipr/Lipase/Compute Globules Area" plugin

fixes #2

Makefile

@@ -5,7 +5,7 @@ FIJI_EXE_PATH=$(FIJI_ROOT_PATH)/ImageJ-linux64
 RAW_IMAGES_ROOT_PATH:=$(shell echo ~/work/lipase/raw-images)
 LIB_SRC_FILES=$(shell find ./src/lipase -name "*.py")
 PLUGINS_SRC_FILES=$(shell find ./src/ij-plugins -name "*.py")
-LIPASE_VERSION=1.00
+LIPASE_VERSION=1.01
 
 BUILD_ROOT_PATH=$(shell pwd)/build
 PACKAGE_FILE_PATH=$(shell pwd)/lipase-$(LIPASE_VERSION).zip
@@ -96,6 +96,18 @@ test0001: install
 		echo "test's return code : $$ERROR_CODE" ; \
 		exit $$ERROR_CODE
 
+.PHONY: test_globules_area
+test_globules_area: install
+	# on macosx : /Applications/Fiji.app/Contents/MacOS/ImageJ-macosx --ij2 --headless --run './test0001.py'
+	# /Applications/Fiji.app/Contents/MacOS/ImageJ-macosx --ij2 --headless --run './tests/test0001.py' "lipase_src_root_path='$(pwd)',raw_images_root_path='/Users/graffy/ownCloud/ipr/lipase/raw-images'"
+	echo 2 > '/tmp/test_result.txt' ; \
+	 	$(FIJI_EXE_PATH) --ij2 --headless --run './src/ij-plugins/Ipr/Lipase/Compute_Globules_Area.py' "INPUT_STACK='$RAW_IMAGES_ROOT_PATH/res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0/img_000000000_DM300_nofilter_vis_000.tif', INPUT_BACKGROUND='$RAW_IMAGES_ROOT_PATH/res_soleil2018/GGH/GGH_2018_cin2_phiG_I_327_vis_-40_1/Pos0/img_000000000_DM300_nofilter_vis_000.tif', PARTICLE_THRESHOLD='2000'" ; \
+		ERROR_CODE=$$? ; \
+		echo "Fiji 's return code : $$ERROR_CODE" ; \
+		ERROR_CODE=$$(cat '/tmp/test_result.txt') ; \
+		echo "test's return code : $$ERROR_CODE" ; \
+		exit $$ERROR_CODE
+
 .PHONY: test
 test: test0001
 

src/ij-plugins/Ipr/Lipase/Compute_Globules_Area.py

@@ -0,0 +1,59 @@
+#@ ImagePlus (label="the input image stack") INPUT_STACK
+#@ ImagePlus (label="the background image") INPUT_BACKGROUND
+#@ Integer (label="particle threshold (in gray levels)", value=2000, min=0, max=32768, style="slider") PARTICLE_THRESHOLD
+
+#@output ImagePlus OUTPUT_PLOT
+"""This script is supposed to be launched from fiji's jython interpreter
+"""
+
+
+# # note: fiji's jython doesn't support encoding keyword
+
+import sys
+print('python version %s' % sys.version)  # prints python version
+
+from lipase.settings import UserSettings
+
+# from lipase import Lipase, ImageLogger
+from lipase.imageengine import IImageEngine, PixelType, StackImageFeeder
+from lipase.imagej.ijimageengine import IJImageEngine
+from lipase.lipase import UserProvidedBackground, GlobulesAreaEstimator
+
+# from ij import IJ  # pylint: disable=import-error
+# from ij.gui import GenericDialog, DialogListener # pylint: disable=import-error
+# from java.awt.event import ItemListener # pylint: disable=import-error
+import ij.gui
+from jarray import zeros, array
+
+def run_script():
+    global INPUT_STACK  # pylint:disable=global-variable-not-assigned
+    global INPUT_BACKGROUND  # pylint:disable=global-variable-not-assigned
+    global PARTICLE_THRESHOLD  # pylint:disable=global-variable-not-assigned
+    global OUTPUT_PLOT  # pylint:disable=global-variable-not-assigned
+
+    IImageEngine.set_instance(IJImageEngine())
+
+    src_hyperstack = IImageEngine.get_instance().create_hyperstack(width=1, height=1, num_channels=1, num_slices=1, num_frames=1, pixel_type=PixelType.U8)
+    src_hyperstack.hyperstack = INPUT_STACK  # pylint: disable=undefined-variable
+
+    src_background = IImageEngine.get_instance().create_image(width=1, height=1, pixel_type=PixelType.U8)
+    src_background.ij_image = INPUT_BACKGROUND  # pylint: disable=undefined-variable
+
+    background_estimator = UserProvidedBackground(background_image=src_background)
+    processor = GlobulesAreaEstimator(background_estimator=background_estimator, particle_threshold=PARTICLE_THRESHOLD)  # pylint: disable=undefined-variable
+
+    results = processor.detect_particles(src_hyperstack)
+    # save_hdf5_file('results.h5', results)
+    # results file could be checked with "h5dump --xml ./lipase.git/results.h5"
+
+
+    x = array(results['frame index'].elements, 'f')
+    y = array(results['globules_area_ratio'].elements, 'f')
+
+    plot = ij.gui.Plot('my_title', 'frame', 'globules area ratio', x, y)
+    plot.show()
+    OUTPUT_PLOT = plot
+
+
+# note : when launched from fiji, __name__ doesn't have the value "__main__", as when launched from python
+run_script()

src/lipase/lipase.py

@@ -148,6 +148,18 @@ class IBackgroundEstimator(ABC):
         """
         pass
 
+class UserProvidedBackground(IBackgroundEstimator):
+
+    def __init__(self, background_image):
+        """
+        :param IImage background_image: the image chosen as background (it is supposed to not contain any particle, only static objects (traps, lens spots, etc.))
+        """
+        IBackgroundEstimator.__init__(self)
+        self.background_image = background_image
+
+    def estimate_background(self, visible_traps_sequence):
+        return self.background_image
+
 class EmptyFrameBackgroundEstimator(IBackgroundEstimator):
 
     def __init__(self, empty_frame_index):
@@ -184,7 +196,7 @@ class GlobulesAreaEstimator(object):
         # particles_stack = ie.create_hyperstack(width=background_image.width, height=background_image.height, num_slices=1, num_frames=visible_traps_sequence.num_frames(), num_channels=1, pixel_type=PixelType.F32)
         
         results = Group('')
-        globules_area = DataSet('globuls_area_ratio', (visible_traps_sequence.num_frames(), ), ElementType.F32)
+        globules_area = DataSet('globules_area_ratio', (visible_traps_sequence.num_frames(), ), ElementType.F32)
         frame_indices = DataSet('frame index', (visible_traps_sequence.num_frames(), ), ElementType.U32)
         results.add_dataset(globules_area)
         results.add_dataset(frame_indices)

tests/test0001.py

@@ -103,7 +103,7 @@ class TestLipase(unittest.TestCase):
         results = processor.detect_particles(visible_traps_sequence)
         save_hdf5_file('results.h5', results)
         # results file could be checked with "h5dump --xml ./lipase.git/results.h5"
-        first_frame_measured_ratio = results['globuls_area_ratio'][(0,)]
+        first_frame_measured_ratio = results['globules_area_ratio'][(0,)]
         first_frame_expected_ratio = 0.008
         self.assertAlmostEqual(first_frame_measured_ratio, first_frame_expected_ratio, delta=0.01)