Add adi2() function

Author: AlexeyPechnikov

insardev/insardev/Stack.py

@@ -243,73 +243,69 @@ def optimize2(self, angle_coarse: float = 15, angle_fine: float = 5, device: str
 
         return type(self)(s_opt_dict)
 
-    def adi(self, device: str = 'auto') -> Batch:
+    def adi2(self,
+             angle_coarse: float = 15,
+             angle_fine: float = 5,
+             device: str = 'auto') -> Batch:
         """
-        Compute Amplitude Dispersion Index (ADI) for calibrated σ₀ data.
+        Dual-pol ADI: optimize2() + adi() in one call.
 
-        Wrapper that calls BatchComplex.adi() on complex variables.
+        NOTE: Requires insardev_polsar extension.
+
+        Finds optimal VV/VH amplitude combination that minimizes ADI,
+        then computes ADI on the optimized amplitudes.
 
         Parameters
         ----------
+        angle_coarse : float
+            Coarse grid step in degrees. Default 15.
+        angle_fine : float
+            Fine grid step in degrees. Default 5.
         device : str
             PyTorch device: 'auto', 'cuda', 'mps', or 'cpu'.
 
         Returns
         -------
         Batch
-            ADI values for each polarization variable present.
+            ADI values computed on polarimetrically optimized amplitudes.
 
         Examples
         --------
-        >>> adi = stack.adi()
-        >>> ps_mask = adi < 0.25
+        >>> import insardev_polsar
+        >>> adi = stack.adi2()
+        >>> ps_mask = adi[['VV']] < 0.4
         """
-        # Get complex variables
         sample_ds = next(iter(self.values()))
-        complex_vars = [v for v in sample_ds.data_vars
-                        if sample_ds[v].dtype.kind == 'c' and 'date' in sample_ds[v].dims]
-
-        if not complex_vars:
-            raise ValueError("No complex time-series data found")
+        if 'VV' in sample_ds.data_vars and 'VH' in sample_ds.data_vars:
+            pols = ['VV', 'VH']
+        elif 'HH' in sample_ds.data_vars and 'HV' in sample_ds.data_vars:
+            pols = ['HH', 'HV']
+        else:
+            raise ValueError("Dual-pol data required (VV+VH or HH+HV)")
 
-        # Get as BatchComplex and call adi()
-        batch_complex = self[complex_vars]
-        return batch_complex.adi(device)
+        batch_complex = self[pols]
+        return batch_complex.adi2(angle_coarse, angle_fine, device)
 
-    def similars(
-        self,
-        window: tuple = (5, 5),
-        threshold: float = 0.5,
-        valid_threshold: float = 0.5,
-        device: str = 'auto'
-    ) -> Batch:
+    def adi(self, device: str = 'auto') -> Batch:
         """
-        Count temporally phase-similar neighbors per pixel.
-
-        NOTE: Requires insardev_polsar extension.
+        Compute Amplitude Dispersion Index (ADI) for calibrated σ₀ data.
 
-        Wrapper that calls BatchComplex.similars() on complex variables.
+        Wrapper that calls BatchComplex.adi() on complex variables.
 
         Parameters
         ----------
-        window : tuple of int
-            Window size (y, x). Asymmetric to account for different pixel spacing.
-        threshold : float
-            Maximum phase std (radians) for a neighbor to count as similar.
-        valid_threshold : float
-            Minimum fraction of dates with valid (non-NaN) data.
         device : str
-            PyTorch device: 'auto', 'cuda', 'mps', 'cpu'
+            PyTorch device: 'auto', 'cuda', 'mps', or 'cpu'.
 
         Returns
         -------
         Batch
-            Count of phase-similar neighbors per pixel. Higher = more stable.
+            ADI values for each polarization variable present.
 
         Examples
         --------
-        >>> sim = stack.similars(window=(11, 41), threshold=1.0)
-        >>> ps_mask = sim >= 40
+        >>> adi = stack.adi()
+        >>> ps_mask = adi < 0.25
         """
         # Get complex variables
         sample_ds = next(iter(self.values()))
@@ -319,9 +315,9 @@ def similars(
         if not complex_vars:
             raise ValueError("No complex time-series data found")
 
-        # Get as BatchComplex and call similars()
+        # Get as BatchComplex and call adi()
         batch_complex = self[complex_vars]
-        return batch_complex.similars(window, threshold, valid_threshold, device)
+        return batch_complex.adi(device)
 
     def neighbors(
         self,

insardev/insardev/__init__.py

@@ -8,7 +8,7 @@
 # See the LICENSE file in the insardev directory for license terms.
 # Professional use requires an active per-seat subscription at: https://patreon.com/pechnikov
 # ----------------------------------------------------------------------------
-__version__ = '2026.3.8.post8'
+__version__ = '2026.3.8.post10'
 
 # processing functions
 from .Stack import Stack