Updated Variable Names

docs/source/notebooks/paste_tutorial.ipynb

@@ -477,7 +477,7 @@
     "start = time.time()\n",
     "\n",
     "center_slice, pis = center_align(\n",
-    "    initial_slice, slices, lmbda, random_seed=5, pis_init=b\n",
+    "    initial_slice, slices, lmbda, random_seed=5, pi_inits=b\n",
     ")\n",
     "\n",
     "print(\"Runtime: \" + str(time.time() - start))"

scripts/workflow.py

@@ -85,7 +85,7 @@ def find_pis(self, overlap_fraction: float, max_iters: int = 1000):
                 pairwise_align(
                     self.slices[i].adata,
                     self.slices[i + 1].adata,
-                    s=overlap_fraction,
+                    overlap_fraction=overlap_fraction,
                     numItermax=max_iters,
                     maxIter=max_iters,
                 )
@@ -109,7 +109,7 @@ def find_center_slice(
         if reference_slice is None:
             reference_slice = self.slices[0]
         center_slice, pis = center_align(
-            reference_slice.adata, self.slices_adata, pis_init=pis
+            reference_slice.adata, self.slices_adata, pi_inits=pis
         )
         return Slice(adata=center_slice), pis
 

src/paste3/align.py

@@ -70,13 +70,13 @@ def align(
         cost_matrix = np.genfromtxt(cost_matrix, delimiter=",", dtype="float64")
 
     if start is None:
-        pis_init = [None] * (n_slices - 1) if mode == "pairwise" else None
+        pi_inits = [None] * (n_slices - 1) if mode == "pairwise" else None
     elif mode == "pairwise" and not (len(start) == n_slices - 1):
         raise ValueError(
             f"Number of slices {n_slices} is not equal to number of start pi files {len(start)}"
         )
     else:
-        pis_init = [np.genfromtxt(pi, delimiter=",") for pi in start]
+        pi_inits = [np.genfromtxt(pi, delimiter=",") for pi in start]
 
     # make output directory if it doesn't exist
     output_directory = Path(output_directory)
@@ -87,15 +87,15 @@ def align(
         pis = []
         for i in range(n_slices - 1):
             pi = pairwise_align(
-                sliceA=slices[i],
-                sliceB=slices[i + 1],
-                s=overlap_fraction,
-                M=cost_matrix,
+                a_slice=slices[i],
+                b_slice=slices[i + 1],
+                overlap_fraction=overlap_fraction,
+                exp_dissim_matrix=cost_matrix,
                 alpha=alpha,
-                dissimilarity=cost,
-                G_init=pis_init[i],
-                a_distribution=slices[i].obsm["weights"],
-                b_distribution=slices[i + 1].obsm["weights"],
+                exp_dissim_metric=cost,
+                pi_init=pi_inits[i],
+                a_spots_weight=slices[i].obsm["weights"],
+                b_spots_weight=slices[i + 1].obsm["weights"],
                 norm=norm,
                 numItermax=numItermax,
                 backend=ot.backend.TorchBackend(),
@@ -104,7 +104,7 @@ def align(
                 maxIter=max_iter,
                 optimizeTheta=optimizeTheta,
                 eps=eps,
-                is_histology=is_histology,
+                do_histology=is_histology,
                 armijo=armijo,
             )
             pis.append(pi)
@@ -124,18 +124,18 @@ def align(
         initial_slice = slices[initial_slice - 1].copy()
 
         center_slice, pis = center_align(
-            A=initial_slice,
+            initial_slice=initial_slice,
             slices=slices,
-            lmbda=lmbda,
+            slice_weights=lmbda,
             alpha=alpha,
             n_components=n_components,
             threshold=threshold,
             max_iter=max_iter,
-            dissimilarity=cost,
+            exp_dissim_metric=cost,
             norm=norm,
             random_seed=seed,
-            pis_init=pis_init,
-            distributions=[slice.obsm["weights"] for slice in slices],
+            pi_inits=pi_inits,
+            spots_weights=[slice.obsm["weights"] for slice in slices],
             backend=ot.backend.TorchBackend(),
             use_gpu=use_gpu,
         )