optional relative vs absolute positioning for neighborhoods, cleaner …

…neighborhoods impl, new variable-distance band fn

cactice/bands.py

@@ -0,0 +1,37 @@
+from typing import Tuple, Dict
+
+import numpy as np
+
+
+def get_band(
+        grid: np.ndarray,
+        i: int,
+        j: int,
+        start: int,
+        exclude_zero: bool = False,
+        absolute_coords: bool = False) -> Dict[Tuple[int, int], int]:
+    """
+
+    :param grid: The grid
+    :param i: The central cell's row index
+    :param j: The central cell's column index
+    :param start: The distance from the central cell to start the band
+    :param exclude_zero: Whether to exclude zero-valued cells
+    :param absolute_coords: Use absolute coordinates rather than location relative to the central cell (the default)
+    :return: A dictionary mapping cell locations to their respective values
+    """
+
+    if start < 1 or start > min(grid.shape):
+        raise ValueError(f"Band starting distance must be greater than 0 and less than min(grid length, grid width)")
+
+    band = {}
+    for ii in range(max(i - start, 0), min(i + 2, grid.shape[0])):
+        for jj in range(max(j - 1, 0), min(j + 2, grid.shape[1])):
+            coords = (ii, jj) if absolute_coords else (ii - i, jj - j)
+            band[coords] = grid[ii, jj]
+
+    # optionally exclude zeros (missing)
+    if exclude_zero:
+        band = {k: v for k, v in band.items() if (k == (0, 0) or (k != (0, 0) and v != 0))}
+
+    return band

cactice/knn.py

@@ -88,7 +88,7 @@ def predict(self, grids: List[np.ndarray] = None) -> List[np.ndarray]:
                     i=i,
                     j=j,
                     neighbors=self.__neighbors,
-                    layers=self.__layers,
+                    width=self.__layers,
                     exclude_zero=True)
 
                 # ignore central cell

cactice/mrf.py

@@ -93,7 +93,7 @@ def neighborhood_H(
         i=i,
         j=j,
         neighbors=neighbors,
-        layers=layers,
+        width=layers,
         exclude_zero=True)
 
     # ignore central cell

cactice/neighbors.py

@@ -15,68 +15,40 @@ def get_neighborhood(
         i: int,
         j: int,
         neighbors: Neighbors = Neighbors.CARDINAL,
-        layers: int = 1,
-        exclude_zero: bool = False) -> Dict[Tuple[int, int], int]:
+        exclude_zero: bool = False,
+        absolute_coords: bool = False) -> Dict[Tuple[int, int], int]:
     """
-    Computes the neighborhood around the given grid cell.
+    Gets the neighborhood around the given grid cell.
 
     :param grid: The grid
     :param i: The cell's row index
     :param j: The cell's column index
     :param neighbors: The cells to consider neighbors
-    :param layers: The width of the neighborhood
     :param exclude_zero: Whether to exclude zero-valued neighbors
-    :return: A dictionary mapping relative locations from the central cell to neighboring cell values
+    :param absolute_coords: Use absolute coordinates rather than location relative to the central cell (the default)
+    :return: A dictionary mapping cell locations to their respective values
     """
 
     # set the center of the neighborhood
-    neighborhood = {(0, 0): grid[i, j]}
-
-    for layer in range(1, layers + 1):
-        # check if we're up against any boundaries
-        bt = (i - layer < 0)  # top
-        bb = i >= (grid.shape[0] - layer)  # bottom
-        bl = (j - layer < 0)  # left
-        br = j >= (grid.shape[1] - layer)  # right
-
-        # compute cardinal neighbors (set to None if on or beyond boundary)
-        top = None if bt else grid[i - layer, j]
-        bottom = None if bb else grid[i + layer, j]
-        left = None if bl else grid[i, j - layer]
-        right = None if br else grid[i, j + layer]
-
-        # compute diagonal neighbors (set to None if on or beyond boundary)
-        topleft = None if (bt or bl) else grid[i - layer, j - layer]
-        topright = None if (bt or br) else grid[i - layer, j + layer]
-        bottomleft = None if (bb or bl) else grid[i + layer, j - layer]
-        bottomright = None if (bb or br) else grid[i + layer, j + layer]
-
-        # TODO: compute off-cardinal/-diagonal neighbors
-
-        # store cardinal neighbors
-        if neighbors == Neighbors.CARDINAL or neighbors == Neighbors.COMPLETE:
-            neighborhood[(-1, 0)] = top
-            neighborhood[(1, 0)] = bottom
-            neighborhood[(0, -1)] = left
-            neighborhood[(0, 1)] = right
-
-        # store diagonal neighbors
-        elif neighbors == Neighbors.DIAGONAL or neighbors == Neighbors.COMPLETE:
-            neighborhood[(-1, -1)] = topleft
-            neighborhood[(-1, 1)] = topright
-            neighborhood[(1, -1)] = bottomleft
-            neighborhood[(1, 1)] = bottomright
-
-        if neighbors == Neighbors.COMPLETE:
-            # TODO: store off-cardinal/-diagonal neighbors
-            pass
-
-    # optionally exclude zero-valued neighbors
+    # neighborhood = {(0, 0): grid[i, j]}
+
+    neighborhood = {}
+    for ii in range(max(i - 1, 0), min(i + 2, grid.shape[0])):
+        for jj in range(max(j - 1, 0), min(j + 2, grid.shape[1])):
+            if not (i == ii and j == jj): continue  # ignore the center
+            coords = (ii, jj) if absolute_coords else (ii - i, jj - j)
+            if (neighbors == Neighbors.CARDINAL or neighbors == Neighbors.COMPLETE) and \
+                    (i == ii and j != jj) or (i != ii and j == jj):
+                neighborhood[coords] = grid[ii, jj]
+            elif (neighbors == Neighbors.DIAGONAL or neighbors == Neighbors.COMPLETE) and \
+                    (i != ii and j != jj):
+                neighborhood[coords] = grid[ii, jj]
+
+    # optionally exclude zeros (missing)
     if exclude_zero:
         neighborhood = {k: v for k, v in neighborhood.items() if (k == (0, 0) or (k != (0, 0) and v != 0))}
 
-    # return only non-None neighbors
-    return {k: v for k, v in neighborhood.items() if v is not None}
+    return neighborhood
 
 
 def get_neighborhoods(

cactice/rns.py

@@ -72,7 +72,7 @@ def predict(self, grids: List[np.ndarray] = None) -> List[np.ndarray]:
                     i=i,
                     j=j,
                     neighbors=self.__neighbors,
-                    layers=self.__layers,
+                    width=self.__layers,
                     exclude_zero=True)
 
                 # ignore central cell