Merge pull request #16 from Intron7/v0.5.1

v0.5.1
scverse · Feb 27, 2023 · 229bb90 · 229bb90
2 parents 96d8f00 + 5cda5d1
commit 229bb90
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Showing 15 changed files with 1,464 additions and 2,317 deletions.
diff --git a/conda/rsc_rapids_22.12.yml b/conda/rsc_rapids_22.12.yml
@@ -1,4 +1,4 @@
-name: rapids_singlecell_0.5.0
+name: rapids_singlecell
 channels:
  - rapidsai
  - nvidia

diff --git a/conda/rsc_rapids_23.02.yml b/conda/rsc_rapids_23.02.yml
@@ -1,4 +1,4 @@
-name: rapids_singlecell_0.5.0
+name: rapids_singlecell
 channels:
  - rapidsai
  - nvidia

diff --git a/docs/api.md b/docs/api.md
@@ -38,7 +38,7 @@ import rapids_singlecell as rsc
 .. autosummary::
    :toctree: generated/
 
-   pp.calculate_qc
+   pp.calculate_qc_metrics
    pp.filter_cells
    pp.filter_genes
    pp.normalize_total

diff --git a/docs/conf.py b/docs/conf.py
@@ -15,6 +15,8 @@
 
 info = metadata("rapids_singlecell")
 project_name = "rapids-singlecell"
+project = "rapids-singlecell"
+title = "accelerating single cell analysis"
 author = info["Author"]
 copyright = f"{datetime.now():%Y}, {author}."
 version = info["Version"]

diff --git a/docs/notebooks/demo_gpu-PR.ipynb b/docs/notebooks/demo_gpu-PR.ipynb
diff --git a/docs/notebooks/demo_gpu-seuratv3-brain.ipynb b/docs/notebooks/demo_gpu-seuratv3-brain.ipynb
diff --git a/docs/notebooks/demo_gpu-seuratv3.ipynb b/docs/notebooks/demo_gpu-seuratv3.ipynb
diff --git a/docs/notebooks/demo_gpu.ipynb b/docs/notebooks/demo_gpu.ipynb
diff --git a/notebooks/demo_gpu-PR.ipynb b/notebooks/demo_gpu-PR.ipynb
diff --git a/notebooks/demo_gpu-seuratv3-brain.ipynb b/notebooks/demo_gpu-seuratv3-brain.ipynb
diff --git a/notebooks/demo_gpu-seuratv3.ipynb b/notebooks/demo_gpu-seuratv3.ipynb
diff --git a/notebooks/demo_gpu.ipynb b/notebooks/demo_gpu.ipynb
diff --git a/rapids_singlecell/cunnData/__init__.py b/rapids_singlecell/cunnData/__init__.py
@@ -94,7 +94,7 @@ def __init__(
             if adata:
                 if not issparse_cpu(adata.X):
                     inter = scipy.sparse.csr_matrix(adata.X)
-                    self.X = cp.sparse.csr_matrix(inter, dtype=cp.float32)
+                    self._X = cp.sparse.csr_matrix(inter, dtype=cp.float32)
                     del inter
                 else:
                     self._X = cp.sparse.csr_matrix(adata.X, dtype=cp.float32)
@@ -318,29 +318,27 @@ def _sanitize(self):
 
     def __getitem__(self, index):
         obs_dx,var_dx = _normalize_indices(index, self.obs_names, self.var_names)
-        self.X = self.X[obs_dx,var_dx]
+        cudata = cunnData(X =self.X[obs_dx,var_dx].copy(),
+                        obs = self.obs.iloc[obs_dx,:].copy(),
+                        var = self.var.iloc[var_dx,:].copy(),
+                        uns=self.uns)
+
         if self.layers:
             for key, matrix in self.layers.items():
-                self.layers[key] = matrix[obs_dx, var_dx]
+                cudata.layers[key] = matrix[obs_dx, var_dx].copy()
         if self.obsm:
             for key, matrix in self.obsm.items():
                 if isinstance(matrix, pd.DataFrame):
-                    self.obsm[key] = matrix.iloc[obs_dx, :]
+                    cudata.obsm[key] = matrix.iloc[obs_dx, :].copy()
                 else:
-                    self.obsm[key] = matrix[obs_dx, :]
+                    cudata.obsm[key] = matrix[obs_dx, :].copy()
         if self.varm:
             for key, matrix in self.varm.items():
                 if isinstance(matrix, pd.DataFrame):
-                    self.varm[key] = matrix.iloc[var_dx, :]
+                    cudata.varm[key] = matrix.iloc[var_dx, :].copy()
                 else:
-                    self.varm[key] = matrix[var_dx, :]
-        return(cunnData(X = self.X,
-                        obs = self.obs.iloc[obs_dx,:],
-                        var = self.var.iloc[var_dx,:],
-                        uns=self.uns,
-                        layers= self.layers,
-                        obsm= self.obsm,
-                        varm= self.varm))
+                    cudata.varm[key] = matrix[var_dx, :].copy()
+        return(cudata)
 
     def _gen_repr(self, n_obs, n_vars) -> str:
         descr = f"cunnData object with n_obs × n_vars = {n_obs} × {n_vars}"

diff --git a/rapids_singlecell/cunnData_funcs/__init__.py b/rapids_singlecell/cunnData_funcs/__init__.py
@@ -4,4 +4,4 @@
 from ._hvg import highly_variable_genes
 from ._normalize import normalize_pearson_residuals, log1p, normalize_total
 from ._simple import filter_cells, filter_genes, filter_highly_variable
-from ._simple import calc_gene_qc, calculate_qc, flag_gene_family
+from ._simple import calc_gene_qc, calculate_qc_metrics, flag_gene_family