start sandialabs#82 spot analysis for peak intensity correction

contrib/app/SpotAnalysis/PeakFlux.py

@@ -0,0 +1,86 @@
+import os
+
+
+import opencsp.common.lib.cv.SpotAnalysis as sa
+import opencsp.common.lib.cv.spot_analysis.SpotAnalysisOperableAttributeParser as saoap
+from opencsp.common.lib.cv.spot_analysis.image_processor import *
+import opencsp.common.lib.tool.file_tools as ft
+import opencsp.common.lib.tool.log_tools as lt
+import opencsp.common.lib.tool.time_date_tools as tdt
+
+
+class PeakFlux:
+    """
+    A class to process images from heliostat sweeps across a target, to find the spot of maximum flux from the
+    heliostat.
+
+    The input includes::
+
+        - A series of images with the heliostat on target, and with the target in ambient light conditions. These images
+          should be clearly labeled with the name of the heliostat under test, and whether the target is under ambient
+          light or heliostat reflected light.
+        - The pixel intensity to flux correction mapping.
+
+    The generated output includes::
+
+        - Over/under exposure warnings
+        - Per-heliostat heatmap visualizations
+        - Per-heliostat peak flux identification
+    """
+
+    def __init__(self, indir: str, outdir: str, experiment_name: str):
+        self.indir = indir
+        self.outdir = outdir
+
+        self.image_processors: list[AbstractSpotAnalysisImagesProcessor] = [
+            # TODO
+        ]
+        self.spot_analysis = sa.SpotAnalysis(
+            experiment_name, self.image_processors, save_dir=outdir, save_overwrite=True
+        )
+
+    def run(self):
+        # process all images from indir
+        for result in self.spot_analysis:
+            # save the processed image
+            save_path = self.spot_analysis.save_image(
+                result, self.outdir, save_ext="png", also_save_supporting_images=False, also_save_attributes_file=True
+            )
+            if save_path is None:
+                lt.warn(
+                    f"Warning in PeakFlux.run(): failed to save image. "
+                    + "Maybe SpotAnalaysis.save_overwrite is False? ({self.spot_analysis.save_overwrite=})"
+                )
+            else:
+                lt.info(f"Saved image to {save_path}")
+
+            # Get the attributes of the processed image, to save the results we're most interested in into a single
+            # condensed csv file.
+            parser = saoap.SpotAnalysisOperableAttributeParser(result, self.spot_analysis)
+
+            # TODO append these results to the csv file
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser(
+        prog=__file__.rstrip(".py"), description='Processes images to find the point of peak flux.'
+    )
+    parser.add_argument('indir', type=str, help="Directory with images to be processed.")
+    parser.add_argument('outdir', type=str, help="Directory for where to put processed images and computed results.")
+    parser.add_argument('experiment_name', type=str, help="A description of the current data collection.")
+    args = parser.parse_args()
+
+    # create the output directory
+    ft.create_directories_if_necessary(args.outdir)
+
+    # create the log file
+    log_path_name_ext = os.path.join(args.outdir, "PeakFlux_" + tdt.current_date_time_string_forfile() + ".log")
+    lt.logger(log_path_name_ext)
+
+    # validate the rest of the inputs
+    if not ft.directory_exists(args.indir):
+        lt.error_and_raise(FileNotFoundError, f"Error in PeakFlux.py: input directory '{args.indir}' does not exist!")
+
+    PeakFlux(args.indir, args.outdir).run()