compat: Support numpy >=1.24

ELEKTRONN · Jun 21, 2023 · a8b8fa0 · a8b8fa0
1 parent ce73d7f
commit a8b8fa0
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Showing 3 changed files with 7 additions and 7 deletions.
diff --git a/elektronn3/data/coord_transforms.py b/elektronn3/data/coord_transforms.py
@@ -261,7 +261,7 @@ def make_dest_coords(sh):
     Make coordinate list for destination array of shape sh
     """
     zz,xx,yy = np.mgrid[0:sh[0], 0:sh[1], 0:sh[2]]
-    hh = np.ones(sh, dtype=np.int)
+    hh = np.ones(sh, dtype=np.int64)
     coords = np.concatenate([zz[...,None], xx[...,None],
                              yy[...,None], hh[...,None]], axis=-1)
     return coords.astype(floatX)
@@ -382,8 +382,8 @@ def warp_slice(
 
     # check corners
     src_corners = src_corners[:,:3]
-    lo = np.min(np.floor(src_corners), 0).astype(np.int)
-    hi = np.max(np.ceil(src_corners + 1), 0).astype(np.int)
+    lo = np.min(np.floor(src_corners), 0).astype(np.int64)
+    hi = np.max(np.ceil(src_corners + 1), 0).astype(np.int64)
     # compute/transform dense coords
     dest_coords = make_dest_coords(patch_shape)
     src_coords = np.tensordot(dest_coords, M_inv, axes=[[-1], [1]])
@@ -438,8 +438,8 @@ def warp_slice(
             target_offset[2]:(target_offset[2] + target_patch_shape[2])
         ]
         # shift coords to be w.r.t. to origin of target_src array
-        lo_targ = np.floor(src_coords_target.min(2).min(1).min(0) - target_src_offset).astype(np.int)
-        hi_targ = np.ceil(src_coords_target.max(2).max(1).max(0) + 1 - target_src_offset).astype(np.int)
+        lo_targ = np.floor(src_coords_target.min(2).min(1).min(0) - target_src_offset).astype(np.int64)
+        hi_targ = np.ceil(src_coords_target.max(2).max(1).max(0) + 1 - target_src_offset).astype(np.int64)
         if np.any(lo_targ < 0) or np.any(hi_targ >= target_src_shape - 1):
             raise WarpingOOBError("Out of bounds for target_src")
 

diff --git a/elektronn3/inference/inference.py b/elektronn3/inference/inference.py
@@ -653,7 +653,7 @@ def _ensure_matching_shapes(self, inp: np.ndarray) -> Tuple[np.ndarray, Optional
                 padded_out_shape = np.array(self.out_shape)
                 padded_out_shape[1:] = np.ceil(self.out_shape[1:] / self.tile_shape) * self.tile_shape
                 if self.offset is None:
-                    offset = np.zeros(shape=len(padded_out_shape) - 1, dtype=np.int)
+                    offset = np.zeros(shape=len(padded_out_shape) - 1, dtype=np.int64)
                 else:
                     offset = np.array(self.offset)
                 padded_inp_shape = (*inp.shape[:2], *padded_out_shape[1:] + 2 * offset)

diff --git a/elektronn3/training/plotting.py b/elektronn3/training/plotting.py
@@ -208,7 +208,7 @@ def add_timeticks(ax, times, steps, time_str='mins', num=5):
     k = int(np.log10(k))  # 10-base of locators
     m = int(np.round(float(N) / (num * 10 ** k)))  # multiple of base
     s = max(m * 10 ** k, 1)
-    x_labs = np.arange(0, N, s, dtype=np.int)
+    x_labs = np.arange(0, N, s, dtype=np.int64)
     x_ticks = np.interp(x_labs, times, steps)
     ax.set_xticks(x_ticks)
     ax.set_xticklabels(x_labs)