updated dependencies

theislab · Oct 31, 2022 · 8567b5a · 8567b5a
1 parent e68f5f7
commit 8567b5a
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Showing 2 changed files with 14 additions and 10 deletions.
diff --git a/pyproject.toml b/pyproject.toml
@@ -6,7 +6,7 @@ requires = ["hatchling"]
 [project]
 name = "multigrate"
 version = "0.0.1"
-description = "A very interesting piece of code"
+description = "Multigrate: multimodal data integration for single-cell genomics."
 readme = "README.md"
 requires-python = ">=3.9,<3.11"
 license = {file = "LICENSE"}
@@ -20,11 +20,7 @@ urls.Documentation = "https://multigrate.readthedocs.io/"
 urls.Source = "https://github.com/theislab/multigrate"
 urls.Home-page = "https://github.com/theislab/multigrate"
 dependencies = [
-    "anndata==0.8.0",
-    "scikit-learn==1.0.2",
-    "statsmodels==0.13.2",
-    "numba==0.55.1",
-    "tables==3.7.0",
+    "scanpy==1.9.0",
     "scvi-tools==0.14.6",
     "torchmetrics==0.6.0",
     "matplotlib"

diff --git a/src/multigrate/module/_multivae_torch.py b/src/multigrate/module/_multivae_torch.py
@@ -523,15 +523,19 @@ def loss(
         else:
             integ_loss = torch.tensor(0.0).to(self.device)
             if self.mmd == "latent" or self.mmd == "both":
-                integ_loss += self._calc_integ_loss(z_joint, integrate_on).to(self.device)
+                integ_loss += self.calc_integ_loss(z_joint, integrate_on).to(
+                    self.device
+                )
             if self.mmd == "marginal" or self.mmd == "both":
                 for i in range(len(masks)):
                     for j in range(i + 1, len(masks)):
                         idx_where_to_calc_mmd = torch.eq(
                             masks[i] == masks[j],
                             torch.eq(masks[i], torch.ones_like(masks[i])),
                         )
-                        if idx_where_to_calc_mmd.any():  # if need to calc mmd for a group between modalities
+                        if (
+                            idx_where_to_calc_mmd.any()
+                        ):  # if need to calc mmd for a group between modalities
                             marginal_i = z_marginal[:, i, :][idx_where_to_calc_mmd]
                             marginal_j = z_marginal[:, j, :][idx_where_to_calc_mmd]
                             marginals = torch.cat([marginal_i, marginal_j])
@@ -542,13 +546,17 @@ def loss(
                                 ]
                             ).to(self.device)
 
-                            integ_loss += self._calc_integ_loss(marginals, modalities).to(self.device)
+                            integ_loss += self.calc_integ_loss(
+                                marginals, modalities
+                            ).to(self.device)
 
                 for i in range(len(masks)):
                     marginal_i = z_marginal[:, i, :]
                     marginal_i = marginal_i[masks[i]]
                     group_marginal = integrate_on[masks[i]]
-                    integ_loss += self._calc_integ_loss(marginal_i, group_marginal).to(self.device)
+                    integ_loss += self.calc_integ_loss(marginal_i, group_marginal).to(
+                        self.device
+                    )
 
         cycle_loss = (
             torch.tensor(0.0).to(self.device)