ruff format

Author: aarmey

pf2rnaseq/figures/commonFuncs/plotFactors.py

@@ -18,18 +18,18 @@ def plot_condition_factors(
     cond_group_labels: pd.Series | None = None,
     groupConditions=False,
     cond="Condition",
-    log_scale=True
+    log_scale=True,
 ):
     """Plots Pf2 condition factors"""
     pd.set_option("display.max_rows", None)
     yt = pd.Series(np.unique(data.obs[cond]))
     X = np.array(data.uns["Pf2_A"])
     if log_scale:
         X = np.log10(X)
-    
+
     X -= np.median(X, axis=0)
-    X /= np.std(X, axis=0)+1e-3
-    ind = reorder_table(X+1e-3)
+    X /= np.std(X, axis=0) + 1e-3
+    ind = reorder_table(X + 1e-3)
 
     X = X[ind]
     yt = yt.iloc[ind]

pf2rnaseq/figures/figureHeiserCompPac.py

@@ -2,7 +2,6 @@
 Weighted projections per component in PaCMAP and boxplot of cell types
 """
 
-
 import numpy as np
 
 from ..factorization import correct_conditions, pf2

pf2rnaseq/figures/figureParseFactorsDeconv.py

@@ -37,7 +37,6 @@ def makeFigure():
 
     W, H = deconvolution_cytokine(X.uns["Pf2_A"], alpha=1e-1, max_iter=5000)
 
-
     # Get cytokine names in correct order
     samples_df = samples_only(X)
 
@@ -51,7 +50,7 @@ def makeFigure():
         samples_df["cytokine"],
         groupConditions=True,
         cond="cytokine",
-        log_scale=False
+        log_scale=False,
     )
     ax[0].set_title("Deconvolved matrix (H)", fontsize=12, fontweight="bold")
 
@@ -61,7 +60,7 @@ def makeFigure():
         samples_df["cytokine"],
         groupConditions=True,
         cond="cytokine",
-        log_scale=False
+        log_scale=False,
     )
     ax[1].set_title("Original Effects (A)", fontsize=12, fontweight="bold")
 

pf2rnaseq/imports.py

@@ -92,9 +92,8 @@ def import_Parse(geneThreshold=0.1, doublet=False) -> anndata.AnnData:
     X = anndata.read_h5ad("/home/nicoleb/Pf2-scRNAseq-1/pf2rnaseq/Parse_Donor11.h5ad")
     if doublet:
         doubletDF = pd.read_csv(
-        path_here / "pf2rnaseq/Data/DN11Doublets.csv.gz",
-        index_col=0  
-    )
+            path_here / "pf2rnaseq/Data/DN11Doublets.csv.gz", index_col=0
+        )
         X.obs = X.obs.join(doubletDF.reindex(X.obs.index))
         singlet_mask = X.obs["doublet"] == 0
         X = X[singlet_mask, :].copy()

pf2rnaseq/top_bot_genes_export.py

@@ -2,7 +2,6 @@
 exports csv of top 30 and bottom 30 genes per component
 """
 
-
 import numpy as np
 import pandas as pd
 from anndata import read_h5ad

pyproject.toml

@@ -36,6 +36,7 @@ dev = [
     "pytest>=8.0",
     "pytest-cov>=6.0",
     "pyright>=1.1",
+    "ruff>=0.14.4",
 ]
 
 [project.scripts]