Introduce logging

src/darsia/image/image.py

@@ -7,9 +7,11 @@
 from __future__ import annotations
 
 import copy
+import logging
 import math
 from datetime import datetime, timedelta
 from pathlib import Path
+from time import time as tm
 from typing import Any, Optional, Union
 from warnings import warn
 
@@ -24,6 +26,8 @@
 
 import darsia
 
+logger = logging.getLogger(__name__)
+
 
 class Image:
     """General image class."""
@@ -185,9 +189,14 @@ def __init__(
         # NOTE: Require mapping format: darsia.Image -> darsia.Image
         # May require redefinition of the coordinate system.
         if transformations is not None:
+
             for transformation in transformations:
                 if transformation is not None and hasattr(transformation, "__call__"):
+                    tic = tm()
                     transformation(self, overwrite=True)
+                    logger.debug(
+                        f"{type(transformation)} transformation applied in {tm() - tic:.3f} s."
+                    )
 
         # ! ---- Safety check on dimensionality and resolution of image.
         assert len(self.shape) == self.space_dim + self.time_dim + self.range_dim

src/darsia/multi_image_analysis/concentrationanalysis.py

@@ -5,7 +5,9 @@
 from __future__ import annotations
 
 import copy
+import logging
 from pathlib import Path
+from time import time
 from typing import Optional, Union
 from warnings import warn
 
@@ -16,6 +18,8 @@
 
 import darsia
 
+logger = logging.getLogger(__name__)
+
 
 class ConcentrationAnalysis:
     """Class providing the capabilities to determine concentration/saturation
@@ -248,7 +252,11 @@ def __call__(self, img: darsia.Image) -> darsia.Image:
             probe_img = copy.deepcopy(img)
 
         # Remove background image
+        tic = time()
         diff = self._subtract_background(probe_img)
+        logger.debug(f"subtraction: {time() - tic}")
+
+        tic = time()
 
         # Provide possibility for tuning and inspection of intermediate results
         self._inspect_diff(diff)
@@ -268,14 +276,20 @@ def __call__(self, img: darsia.Image) -> darsia.Image:
         # Balance signal (take into account possible heterogeneous effects)
         balanced_signal = self._balance_signal(clean_signal)
 
+        logger.debug(f"processing: {time() - tic}")
+
         # Regularize/upscale signal to Darcy scale and convert from signal to concentration
         # or other way around.
         if self.first_restoration_then_model:
             smooth_signal = self._restore_signal(balanced_signal)
             concentration = self._convert_signal(smooth_signal, diff)
         else:
+            tic = time()
             nonsmooth_concentration = self._convert_signal(balanced_signal, diff)
+            logger.debug(f"conversion: {time() - tic}")
+            tic = time()
             concentration = self._restore_signal(nonsmooth_concentration)
+            logger.debug(f"restoration: {time() - tic}")
 
         # Invoke plot
         if self.verbosity >= 1:

src/darsia/presets/analysis/multichromatictracer.py

@@ -3,12 +3,15 @@
 
 """
 
+import logging
 from typing import Optional
 
 import numpy as np
 
 import darsia
 
+logger = logging.getLogger(__name__)
+
 
 class MultichromaticTracerAnalysis(darsia.ConcentrationAnalysis):
     """Multichomratic concentration analysis tailored to labeled media.
@@ -108,8 +111,14 @@ def __call__(self, image: darsia.Image) -> darsia.Image:
             Image: concentration map
 
         """
+        from time import time
+
+        tic = time()
         concentration = super().__call__(image)
+        logger.debug(f"concentration call: {time() - tic}")
+        tic = time()
         self.expert_knowledge(concentration)
+        logger.debug(f"expert knowledge - concentration: {time() - tic}")
         return concentration
 
     # ! ---- SAVE AND LOAD ----