Merge branch 'enhancement/fix_ransac_random_state' into 'main'

Enhancement/fix ransac random state

See merge request danschef/arosics!35

HISTORY.rst

@@ -8,6 +8,7 @@ History
 * Re-implemented interpolation of tie point attributes into space (!23).
   Three techniques are now supported: RBF, GPR, and Ordinary Kriging. Added scikit-learn to dependencies.
 * Fixed GDAL warning related to PROJ_DATA/PROJ_LIB environment variables (!34).
+* Added parameter 'rs_random_state' (RANSAC random state) and set it to 0 by default (!35).
 
 
 1.8.1 (2023-03-10)

arosics/CoReg_local.py

@@ -84,6 +84,7 @@ def __init__(self,
                  min_reliability: float = 60,
                  rs_max_outlier: float = 10,
                  rs_tolerance: float = 2.5,
+                 rs_random_state: Optional[int] = 0,
                  align_grids: bool = True,
                  match_gsd: bool = False,
                  out_gsd: float = None,
@@ -181,6 +182,9 @@ def __init__(self,
         :param rs_tolerance:
             RANSAC tie point filtering: percentage tolerance for max_outlier_percentage (default: 2.5%)
 
+        :param rs_random_state:
+            RANSAC random state (an integer corresponds to a fixed/pseudo-random state, None randomizes the result)
+
         :param align_grids:
             True: align the input coordinate grid to the reference (does not affect the output pixel size as long as
             input and output pixel sizes are compatible (5:30 or 10:30 but not 4:30), default = True
@@ -293,6 +297,7 @@ def __init__(self,
         self.min_reliability = min_reliability
         self.rs_max_outlier = rs_max_outlier
         self.rs_tolerance = rs_tolerance
+        self.rs_random_state = rs_random_state
         self.align_grids = align_grids
         self.match_gsd = match_gsd
         self.out_gsd = out_gsd
@@ -475,7 +480,8 @@ def calculate_spatial_shifts(self) -> None:
                            outlDetect_settings=dict(
                                min_reliability=self.min_reliability,
                                rs_max_outlier=self.rs_max_outlier,
-                               rs_tolerance=self.rs_tolerance),
+                               rs_tolerance=self.rs_tolerance,
+                               rs_random_state=self.rs_random_state),
                            dir_out=self.projectDir,
                            CPUs=self.CPUs,
                            progress=self.progress,

arosics/Tie_Point_Grid.py

@@ -130,7 +130,7 @@ def __init__(self,
         :param outlDetect_settings:
             a dictionary with the settings to be passed to arosics.TiePointGrid.Tie_Point_Refiner.
             Available keys: min_reliability, rs_max_outlier, rs_tolerance, rs_max_iter, rs_exclude_previous_outliers,
-            rs_timeout, q. See documentation there.
+            rs_timeout, rs_random_state, q. See documentation there.
 
         :param dir_out:
             output directory to be used for all outputs if nothing else is given to the individual methods
@@ -1000,6 +1000,7 @@ def __init__(self, GDF,
                  rs_max_iter: int = 15,
                  rs_exclude_previous_outliers: bool = True,
                  rs_timeout: float = 20,
+                 rs_random_state: Optional[int] = 0,
                  q: bool = False):
         """Get an instance of Tie_Point_Refiner.
 
@@ -1016,6 +1017,8 @@ def __init__(self, GDF,
         :param rs_exclude_previous_outliers:    RANSAC: whether to exclude points that have been flagged as
                                                 outlier by earlier filtering (default:True)
         :param rs_timeout:                      RANSAC: timeout for iteration loop in seconds (default: 20)
+        :param rs_random_state:                 RANSAC random state (an integer corresponds to a fixed/pseudo-random
+                                                state, None randomizes the result)
 
         :param q:
         """
@@ -1026,6 +1029,7 @@ def __init__(self, GDF,
         self.rs_max_iter = rs_max_iter
         self.rs_exclude_previous_outliers = rs_exclude_previous_outliers
         self.rs_timeout = rs_timeout
+        self.rs_random_state = rs_random_state
         self.q = q
         self.new_cols = []
         self.ransac_model_robust = None
@@ -1198,7 +1202,8 @@ def _RANSAC_outlier_detection(self, inGDF):
                            ),
                            stop_residuals_sum=int(
                                (self.rs_max_outlier_percentage - self.rs_tolerance) /
-                               100 * src_coords.shape[0])
+                               100 * src_coords.shape[0]),
+                           random_state=self.rs_random_state
                            )
             else:
                 warnings.warn('RANSAC filtering could not be applied '