Merge pull request #72 from PNNL-CompBio/Abby

Abby

environment_Windows.yml

@@ -0,0 +1,23 @@
+name: snekmer
+channels:
+  - anaconda
+  - bioconda
+  - numba
+  - conda-forge
+dependencies:
+  - python >= 3.9
+  - biopython
+  - matplotlib
+  - numpy >= 1.22.3
+  - numba >= 0.56
+  - scipy
+  - pandas
+  - seaborn
+  - scikit-learn
+  - snakemake-minimal == 7.0
+  - umap-learn
+  - hdbscan
+  - pip
+  - pip:
+      - -e git+https://github.com/PNNL-CompBio/Snekmer#egg=snekmer
+

snekmer/plot.py

@@ -89,7 +89,7 @@ def cv_roc_curve(clf, X, y, title="ROC Curve", ax=None, dpi=400):
         mean_fpr,
         mean_tpr,
         color="b",
-        label=(f"Mean ROC (AUC = {mean_auc:0.2f}" r" $\pm$ " f" {std_auc:0.2f})"),
+        label=f"Mean ROC (AUC = {mean_auc:0.2f} ± {std_auc:0.2f})",
         lw=2,
         alpha=0.8,
     )

snekmer/rules/model.smk

@@ -374,15 +374,16 @@ rule model:
         # save ROC-AUC figure
         if not exists(output.figs):
             makedirs(output.figs)
-        plt.savefig(
+        fig.savefig(
             join(
                 output.figs,
                 (
                     f"{family}_roc-auc-curve_{alphabet_name.lower()}"
                     f"_k-{config['k']:02d}.png"
                 ),
-            )
+            ), dpi=fig.dpi
         )
+        fig.clf()
         plt.close("all")
 
         # PR-AUC figure
@@ -399,15 +400,16 @@ rule model:
         results["cv_split"] += [i + 1 for i in range(cv)]
 
         # save PR-AUC figure
-        plt.savefig(
+        fig.savefig(
             join(
                 output.figs,
                 (
                     f"{family}_aupr-curve_{alphabet_name.lower()}"
                     f"_k-{config['k']:02d}.png"
                 ),
-            )
+            ), dpi=fig.dpi
         )
+        fig.clf()
         plt.close("all")
 
         # save model