ENH: Allow to flip order of restoration and model.

src/darsia/multi_image_analysis/concentrationanalysis.py

@@ -16,8 +16,7 @@
 
 
 class ConcentrationAnalysis:
-    """
-    Class providing the capabilities to determine concentration/saturation
+    """Class providing the capabilities to determine concentration/saturation
     profiles based on image comparison, and tuning of concentration-intensity
     maps.
 
@@ -40,8 +39,7 @@ def __init__(
         labels: Optional[np.ndarray] = None,
         **kwargs,
     ) -> None:
-        """
-        Constructor of ConcentrationAnalysis.
+        """Constructor of ConcentrationAnalysis.
 
         Args:
             base (Image or list of such): baseline image(s); if multiple provided,
@@ -96,6 +94,9 @@ def __init__(
         self._diff_option = kwargs.get("diff option", "absolute")
         """Option for defining differences of images."""
 
+        self.first_restoration_then_model = kwargs.get("restoration -> model", True)
+        """Option for defining order of routines."""
+
         # Define a cleaning filter based on remaining images.
         self.find_cleaning_filter()
 
@@ -113,8 +114,7 @@ def update(
         base: Optional[darsia.Image] = None,
         mask: Optional[np.ndarray] = None,
     ) -> None:
-        """
-        Update of the baseline image or parameters.
+        """Update of the baseline image or parameters.
 
         Args:
             base (Image, optional): image array
@@ -134,8 +134,7 @@ def find_cleaning_filter(
         baseline_images: Optional[list[darsia.Image]] = None,
         reset: bool = False,
     ) -> None:
-        """
-        Determine structural noise by studying a series of baseline images.
+        """Determine structural noise by studying a series of baseline images.
         The resulting cleaning filter will be used prior to the conversion
         of signal to concentration. The cleaning filter should be understood
         as thresholding mask.
@@ -181,8 +180,7 @@ def find_cleaning_filter(
                 )
 
     def read_cleaning_filter_from_file(self, path: Union[str, Path]) -> None:
-        """
-        Read cleaning filter from file.
+        """Read cleaning filter from file.
 
         Args:
             path (str or Path): path to cleaning filter array.
@@ -200,8 +198,7 @@ def read_cleaning_filter_from_file(self, path: Union[str, Path]) -> None:
                 )
 
     def write_cleaning_filter_to_file(self, path_to_filter: Union[str, Path]) -> None:
-        """
-        Store cleaning filter to file.
+        """Store cleaning filter to file.
 
         Args:
             path_to_filter (str or Path): path for storage of the cleaning filter.
@@ -246,11 +243,14 @@ def __call__(self, img: darsia.Image) -> darsia.Image:
         # Balance signal (take into account possible heterogeneous effects)
         balanced_signal = self._balance_signal(clean_signal)
 
-        # Regularize/upscale signal to Darcy scale
-        smooth_signal = self._prepare_signal(balanced_signal)
-
-        # Convert from signal to concentration
-        concentration = self._convert_signal(smooth_signal, diff)
+        # 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:
+            nonsmooth_concentration = self._convert_signal(balanced_signal, diff)
+            concentration = self._restore_signal(nonsmooth_concentration)
 
         # Invoke plot
         if self.verbosity >= 1:
@@ -265,8 +265,7 @@ def __call__(self, img: darsia.Image) -> darsia.Image:
 
     # ! ---- Inspection routines
     def _inspect_diff(self, img: np.ndarray) -> None:
-        """
-        Routine allowing for plotting of intermediate results.
+        """Routine allowing for plotting of intermediate results.
         Requires overwrite.
 
         Args:
@@ -278,8 +277,7 @@ def _inspect_diff(self, img: np.ndarray) -> None:
             plt.imshow(img)
 
     def _inspect_scalar_signal(self, img: np.ndarray) -> None:
-        """
-        Routine allowing for plotting of intermediate results.
+        """Routine allowing for plotting of intermediate results.
         Requires overwrite.
 
         Args:
@@ -291,8 +289,7 @@ def _inspect_scalar_signal(self, img: np.ndarray) -> None:
             plt.imshow(img)
 
     def _inspect_clean_signal(self, img: np.ndarray) -> None:
-        """
-        Routine allowing for plotting of intermediate results.
+        """Routine allowing for plotting of intermediate results.
         Requires overwrite.
 
         Args:
@@ -305,8 +302,7 @@ def _inspect_clean_signal(self, img: np.ndarray) -> None:
 
     # ! ---- Pre- and post-processing methods
     def _subtract_background(self, img: darsia.Image) -> darsia.Image:
-        """
-        Take difference between input image and baseline image, based
+        """Take difference between input image and baseline image, based
         on cached option.
 
         Args:
@@ -346,8 +342,7 @@ def _subtract_background(self, img: darsia.Image) -> darsia.Image:
         return diff
 
     def _reduce_signal(self, img: np.ndarray) -> np.ndarray:
-        """
-        Make a scalar image from potentially multi-colored image.
+        """Make a scalar image from potentially multi-colored image.
 
         Args:
             img (np.ndarray): image
@@ -362,8 +357,7 @@ def _reduce_signal(self, img: np.ndarray) -> np.ndarray:
             return self.signal_reduction(img)
 
     def _clean_signal(self, img: np.ndarray) -> np.ndarray:
-        """
-        Apply cleaning thresholds.
+        """Apply cleaning thresholds.
 
         Args:
             img (np.ndarray): input image
@@ -379,8 +373,7 @@ def _clean_signal(self, img: np.ndarray) -> np.ndarray:
         )
 
     def _balance_signal(self, img: np.ndarray) -> np.ndarray:
-        """
-        Routine responsible for rescaling wrt segments.
+        """Routine responsible for rescaling wrt segments.
 
         Here, it is assumed that only one segment is present.
         Thus, no rescaling is performed.
@@ -394,9 +387,8 @@ def _balance_signal(self, img: np.ndarray) -> np.ndarray:
         """
         return img if self.balancing is None else self.balancing(img)
 
-    def _prepare_signal(self, signal: np.ndarray) -> np.ndarray:
-        """
-        Apply restoration.
+    def _restore_signal(self, signal: np.ndarray) -> np.ndarray:
+        """Apply restoration.
 
         Args:
             signal (np.ndarray): input signal
@@ -411,8 +403,7 @@ def _prepare_signal(self, signal: np.ndarray) -> np.ndarray:
         return signal
 
     def _convert_signal(self, signal: np.ndarray, diff: np.ndarray) -> np.ndarray:
-        """
-        Postprocessing routine, essentially converting a continuous
+        """Postprocessing routine, essentially converting a continuous
         signal into physical data (binary, continuous concentration etc.)
 
         Args:
@@ -433,8 +424,7 @@ def _convert_signal(self, signal: np.ndarray, diff: np.ndarray) -> np.ndarray:
 
 
 class PriorPosteriorConcentrationAnalysis(ConcentrationAnalysis):
-    """
-    Special case of the ConcentrationAnalysis performing a
+    """Special case of the ConcentrationAnalysis performing a
     prior-posterior analysis, i.e., allowing to review the
     conversion performed through a prior model.
 
@@ -470,8 +460,7 @@ def __init__(
         )
 
     def _convert_signal(self, signal: np.ndarray, diff: np.ndarray) -> np.ndarray:
-        """
-        Postprocessing routine, essentially converting a continuous
+        """Postprocessing routine, essentially converting a continuous
         signal into physical data (binary, continuous concentration etc.)
         Use a prior-posterior approach, allowing to review the prior choice.