Work on jupyter notebooks target identification

contrib/common/lib/cv/spot_analysis/image_processor/EnclosedEnergyImageProcessor.py

@@ -19,6 +19,7 @@
     AbstractSpotAnalysisImageProcessor,
 )
 import opencsp.common.lib.tool.log_tools as lt
+import matplotlib.pyplot as plt
 
 
 if TYPE_CHECKING:
@@ -296,7 +297,6 @@ def build_enclosed_energy_plot(self, enclosed_energy_sums: list[int]) -> tuple[n
 
         # close the figure
         fig_record.close()
-
         return plot_image, percentages_of_interest_radii
 
     def build_poi_annotations(
@@ -342,9 +342,15 @@ def _execute(self, operable: SpotAnalysisOperable, is_last: bool) -> list[SpotAn
         # Generate a visual plot of the enclosed energy
         enclosed_energy_plot, percentages_of_interest_radii = self.build_enclosed_energy_plot(enclosed_energy_sums)
 
+        plt.imshow(enclosed_energy_plot)
+        plt.show()
+
         # Attach the enclosed energy annotations
         enclosed_energy_annos = self.build_poi_annotations(center, percentages_of_interest_radii)
 
+        plt.imshow(example_enclosed_energy_image, cmap="grey")
+        plt.show()
+
         # Build the new operable
         notes = copy.copy(operable.image_processor_notes)
         notes.append(tuple([self.name, tuple([percentages_of_interest_radii, [str(v) for v in enclosed_energy_sums]])]))

contrib/common/lib/tool/ImageGrid.py

@@ -47,7 +47,9 @@ def __init__(
         self._subimage_size = subimage_size
         self.number_images = number_images
         self.numbering_color = clr.Color.from_generic(numbering_color)
-        self.numbering_outline_color = clr.Color.from_generic(numbering_outline_color)
+        self.numbering_outline_color = (
+            None if numbering_outline_color is None else clr.Color.from_generic(numbering_outline_color)
+        )
 
         self.images: list[Image.Image] = []
         self.add_images(*images)

opencsp/common/lib/cv/spot_analysis/image_processor/ViewCrossSectionImageProcessor.py

@@ -340,9 +340,15 @@ def visualize_operable(
         graphs_per_plot_cnt += self._draw_cross_section(np_image, cs_loc, cropped_region)
 
         # draw
+        first_view = True
         for view in self.views:
             legend = graphs_per_plot_cnt > 1
-            view.show(block=False, legend=legend)
+
+            # jhs modified, only the first view has actual data to display in the enclosed_energy jupyter notebook
+            # example, so I am only showing that one here. Also, this is true for the target_identification example
+            if first_view:
+                view.show(block=False, legend=legend)
+            first_view = False
 
         # explicitly set the y-axis range
         if self.y_range is not None:

opencsp/common/lib/cv/spot_analysis/image_processor/ViewFalseColorImageProcessor.py

@@ -148,6 +148,12 @@ def visualize_operable(
         else:
             ret = [self.apply_mapping_jet(operable, base_image)]
 
+        processed_image = ret[0].nparray
+
+        self.figure.clear()
+        self.figure.view.imshow(processed_image)
+        self.figure.view.show(block=False)
+
         return ret
 
     def close_figures(self):

opencsp/common/lib/render/lib/PowerpointImage.py

@@ -29,6 +29,9 @@ class PowerpointImage(pps.PowerpointShape):
     """
 
     _tmp_save_path = ft.join(orp.opencsp_temporary_dir(), "PowerpointImage/images/tmp")
+    # _tmp_save_path = ft.join(
+    # "C:/ctemp", "OpenCSP_example_data/target_identification/HeliostatsSpotSize/3_Process/PowerPointFigures"
+    # )
 
     def __init__(
         self,
@@ -636,7 +639,9 @@ def save(self) -> None | str:
         # get a temporary name to save to
         found_unused_name = False
         for tmp_slide_idx in slide_idx_range:
-            max_img_idx = 20  # probably shouldn't need more than 20 images in a slide
+            max_img_idx = (
+                20  # probably shouldn't need more than 20 images in a slide, TODO, marked, revisit 20 image limit
+            )
             dir_name_ext_pattern = self._get_save_dir_name_ext_pattern(tmp_slide_idx)
             max_image_path_name_ext = dir_name_ext_pattern % (max_img_idx - 1)
             if ft.file_exists(max_image_path_name_ext):
@@ -656,6 +661,7 @@ def save(self) -> None | str:
         lt.info(f"saving image to {image_path_name_ext}")
 
         # save the image
+        # saved_path, body_ext = self._save(image_path_name_ext) # jhs commented out
         saved_path, body_ext = self._save(image_path_name_ext)
         if saved_path != self._tmp_save_path:
             lt.error_and_raise(
@@ -690,8 +696,8 @@ def clear_tmp_save(self):
         # TODO verify that the path is the expected temporary path
 
         # delete the saved files
-        ft.delete_file(path_name_ext, error_on_not_exists=False)
-        ft.delete_file(path_name_ext_serialized, error_on_not_exists=False)
+        # ft.delete_file(path_name_ext, error_on_not_exists=False) # jhs, commented out in order to retain powerpoint figures
+        # ft.delete_file(path_name_ext_serialized, error_on_not_exists=False)
 
     @classmethod
     def clear_tmp_save_all(cls):