remove filterreg registration function as it did not work well

setup.py

@@ -12,7 +12,6 @@ setup(name='situr',
           'numpy>=1.21.0',
           'open3d>=0.13.0',
           'Pillow>=8.3.1',
-          'probreg>=0.3.4',
           'scikit-image>=0.18.2',
           'scikit-learn>=0.24.2',
           'scipy>=1.7.0'

situr/registration/__init__.py

@@ -1,4 +1,4 @@
-from .registration import Registration, RegistrationFunction, IcpRegistrationFunction, FilterregRegistrationFunction
+from .registration import Registration, RegistrationFunction, IcpRegistrationFunction
 from .channel_registration import SituImageChannelRegistration, ChannelRegistration, AcrossRoundChannelRegistration
 from .round_registration import RoundRegistration, AllChannelRoundRegistration
 from .tile_registration import CombinedRegistration

situr/registration/channel_registration.py

@@ -4,7 +4,7 @@ from situr.image import situ_image
 from situr.image.situ_tile import Tile
 from situr.registration.peak_finder import PeakFinder, PeakFinderDifferenceOfGaussian
 from situr.image.situ_image import SituImage
-from situr.registration import Registration, RegistrationFunction, FilterregRegistrationFunction
+from situr.registration import Registration, RegistrationFunction, IcpRegistrationFunction
 
 
 class SituImageChannelRegistration(Registration):

situr/registration/registration.py

@@ -5,7 +5,7 @@ from probreg import filterreg
 import numpy as np
 
 from situr.image import extend_dim
-from situr.transformation import Transform, ScaleRotateTranslateTransform
+from situr.transformation import Transform, RotateTranslateTransform
 
 
 class RegistrationFunction:
@@ -28,46 +28,29 @@ class RegistrationFunction:
         """
         raise NotImplementedError(self.__class__.__name__ + '.do_registration')
 
-
-class FilterregRegistrationFunction(RegistrationFunction):
-    def do_registration(self,
-                        data_peaks: np.ndarray,
-                        reference_peaks: np.ndarray) -> ScaleRotateTranslateTransform:
-        """Method that uses filterregregistration to register the data_peaks.
-
-        Args:
-            data_peaks (np.ndarray): The peaks to be registered to the reference
-            reference_peaks (np.ndarray): The reference peaks
-
-        Returns:
-            ScaleRotateTranslateTransform: the resulting transformaton from the registration
-        """
-        source = o3.geometry.PointCloud()
-        source.points = o3.utility.Vector3dVector(extend_dim(data_peaks))
-        target = o3.geometry.PointCloud()
-        target.points = o3.utility.Vector3dVector(extend_dim(reference_peaks))
-
-        registration_method = filterreg.registration_filterreg
-        tf_param, _, _ = filterreg.registration_filterreg(source, target)
-
-        return ScaleRotateTranslateTransform(transform_matrix=tf_param.rot[0:2, 0:2],
-                                             scale=tf_param.scale, offset=tf_param.t[0:2])
-
-
 class IcpRegistrationFunction(RegistrationFunction):
     def __init__(self, max_correspondence_distance=50) -> None:
         self.max_distance = max_correspondence_distance
 
     def do_registration(self,
                         data_peaks: np.ndarray,
-                        reference_peaks: np.ndarray) -> ScaleRotateTranslateTransform:
+                        reference_peaks: np.ndarray) -> RotateTranslateTransform:
+        """Method that uses ICP to register the data_peaks.
+
+        Args:
+            data_peaks (np.ndarray): The peaks to be registered to the reference
+            reference_peaks (np.ndarray): The reference peaks
+
+        Returns:
+            RotateTranslateTransform: the resulting transformaton from the registration
+        """
         source = o3.geometry.PointCloud()
         source.points = o3.utility.Vector3dVector(extend_dim(data_peaks))
         target = o3.geometry.PointCloud()
         target.points = o3.utility.Vector3dVector(extend_dim(reference_peaks))
         reg_p2p = o3.pipelines.registration.registration_icp(
             source, target, self.max_distance)
-        return ScaleRotateTranslateTransform(
+        return RotateTranslateTransform(
             reg_p2p.transformation[0:2, 0:2],
             offset=reg_p2p.transformation[[1, 0], 3])
 
@@ -76,13 +59,13 @@ class Registration:
     __metaclass__ = abc.ABCMeta
 
     def __init__(self,
-                 registration_function: RegistrationFunction() = FilterregRegistrationFunction(),
+                 registration_function: RegistrationFunction() = IcpRegistrationFunction(),
                  peak_finder=PeakFinderDifferenceOfGaussian()):
         """Initialize channel registration and tell which registration function to use.
 
         Args:
             registration_function (RegistrationFunction, optional): Registration function.
-                Defaults to FilterregRegistrationFunction().
+                Defaults to IcpRegistrationFunction().
             peak_finder (PeakFinder, optional): The peak finder to be used for the registration.
                 Defaults to PeakFinderDifferenceOfGaussian().
         """

situr/registration/round_registration.py

@@ -1,7 +1,7 @@
 from situr.image.situ_tile import Tile
 import numpy as np
 
-from situr.registration import Registration, RegistrationFunction, FilterregRegistrationFunction
+from situr.registration import Registration, RegistrationFunction, IcpRegistrationFunction
 
 
 class RoundRegistration(Registration):

situr/transformation/__init__.py

@@ -1 +1 @@
-from .transformation import Transform, IdentityTransform, ScaleRotateTranslateTransform
+from .transformation import Transform, IdentityTransform, RotateTranslateTransform

situr/transformation/transformation.py

@@ -23,7 +23,7 @@ class IdentityTransform(Transform):
         return img
 
 
-class ScaleRotateTranslateTransform(Transform):
+class RotateTranslateTransform(Transform):
     def __init__(self,
                  transform_matrix: np.ndarray,
                  scale: int = 1,