Updated to use ZarrV3 and NumpyV2

pyproject.toml

@@ -4,20 +4,22 @@ build-backend = "hatchling.build"
 
 [project]
 name = "scarr"
-version = "0.1.1"
+version = "0.2.1"
 authors = [
   { name="Jonah Bosland", email="boslandj@oregonstate.edu" },
   { name="Stefan Ene", email="enes@oregonstate.edu" },
   { name="Vincent Immler", email="vincent.immler+scarr@oregonstate.edu" },
+  { name="Alex Zerkel", email="zerkela@oregonstate.edu" }
 ]
 description = "A high-performance SCA library for datasets that include NxM EM trace grids."
 readme = "README.md"
-requires-python = ">=3.10"
+requires-python = ">=3.12"
 dependencies = [
-	'numpy<2',
+	'numpy>=2, <3',
 	'numba',
-	'zarr[jupyter]<3',
+	'zarr>3.0.4, <4',
   'torch',
+  'rich',
 	'ruff',
     'mpmath',
     'matplotlib',

requirements.txt

@@ -1,9 +1,10 @@
-numpy<2
+numpy>=2, <3 
 numba
-zarr[jupyter]<3
+zarr>=3.0.4, <4
 torch
 ruff
 mpmath
 matplotlib
 scipy
 liccheck
+rich

src/scarr/container/container.py

@@ -86,13 +86,13 @@ def configure(self, tile_x, tile_y, model_positions, convergence_step = None):
         for filter in self.filters:
             filter.configure(tile_x, tile_y)
         # int() casting needed for random typing linux bug
-        return int(self.data.configure(tile_x, tile_y, model_positions, self.slab_points, self.trace_index, self.slab_range, self.stride, convergence_step))
+        return self.data.configure(tile_x, tile_y, model_positions, self.slab_points, self.trace_index, self.slab_range, self.stride, convergence_step)
 
     def configure2(self, tile_x, tile_y, model_positions, convergence_step = None):
         for filter in self.filters:
             filter.configure(tile_x, tile_y)
         # int() casting needed for random typing linux bug
-        return int(self.data2.configure(tile_x, tile_y, model_positions, self.slab_points, self.trace_index, self.slab_range, self.stride, convergence_step))
+        return self.data2.configure(tile_x, tile_y, model_positions, self.slab_points, self.trace_index, self.slab_range, self.stride, convergence_step)
 
     def get_batches(self, tile_x, tile_y):
         for batch in self.data.get_batch_generator():

src/scarr/file_handling/trace_handler.py

@@ -40,7 +40,7 @@ def configure(self, tile_x, tile_y, model_positions, slab_points=[], trace_index
         try:
             self.model_positions = model_positions
             self.current_tile = f'{tile_x}/{tile_y}'
-            self.data_length = len(self.data[f'{self.current_tile}{"/traces"}'])
+            self.data_length = self.data[f'{self.current_tile}{"/traces"}'].shape[0]
 
             if len(slab_points) > 0:
                 self.sample_slab = slab_points
@@ -51,6 +51,7 @@ def configure(self, tile_x, tile_y, model_positions, slab_points=[], trace_index
             elif stride > 1:
                 self.sample_slab= slice(0, self.sample_length, stride)
             else:
+                #self.sample_slab = slice(0, self.sample_length)
                 self.sample_slab = slice(None)
 
             if len(trace_index) > 0: