Follow get_crystal_sys->crystal_sys_from_spg_num rename in pymatviz

.pre-commit-config.yaml

@@ -5,7 +5,7 @@ ci:
 
 repos:
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.2
+    rev: v0.1.5
     hooks:
       - id: ruff
         args: [--fix]
@@ -27,6 +27,7 @@ repos:
     hooks:
       - id: codespell
         exclude_types: [json]
+        args: [--check-filenames]
 
   - repo: https://github.com/pre-commit/mirrors-mypy
     rev: v1.6.1

examples/wrenformer/mat_bench/compare_spglib_vs_aflow_wyckoff_labels.py

@@ -6,7 +6,7 @@
 from pymatgen.core import Structure
 from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
 from pymatviz import sankey_from_2_df_cols, spacegroup_sunburst
-from pymatviz.utils import get_crystal_sys
+from pymatviz.utils import crystal_sys_from_spg_num
 from tqdm import tqdm
 
 from aviary import ROOT
@@ -84,13 +84,13 @@
 # %%
 fig = spacegroup_sunburst(df_perovskites.spglib_spg)
 fig.update_layout(title=dict(text="Spglib Spacegroups", x=0.5, y=0.93))
-# fig.write_image(f"{MODULE_DIR}/plots/matbench_perovskites_aflow_sunburst.png", scale=2)
+# fig.write_image(f"{MODULE_DIR}/plots/matbench_perovskites_aflow_sunburst.pdf")
 
 
 # %%
 fig = spacegroup_sunburst(df_perovskites.aflow_spg, title="Aflow")
 fig.update_layout(title=dict(text="Aflow Spacegroups", x=0.5, y=0.85))
-# fig.write_image(f"{MODULE_DIR}/plots/matbench_perovskites_spglib_sunburst.png", scale=2)
+# fig.write_image(f"{MODULE_DIR}/plots/matbench_perovskites_spglib_sunburst.pdf")
 
 
 # %%
@@ -104,7 +104,7 @@
 # %%
 for src in ("aflow", "spglib"):
     df_perovskites[f"{src}_crys_sys"] = df_perovskites[f"{src}_spg_num"].map(
-        get_crystal_sys
+        crystal_sys_from_spg_num
     )
 
 

examples/wrenformer/mat_bench/make_plots.py

@@ -194,7 +194,7 @@
     MAE = (df[y_col] - df[target]).abs().mean()
     pretty_title = y_col.replace("-", " ")
     R2 = r2_score(df[target], df[y_col])
-    labels[y_col] = f"{pretty_title}<br>{MAE = :.2f}, {R2 = :.2f}"
+    labels[y_col] = f"{pretty_title}<br>{MAE=:.2f}, {R2=:.2f}"
 
 fig = px.scatter(
     df.rename(columns=labels).reset_index(),

examples/wrenformer/mat_bench/plotting_functions.py

@@ -4,7 +4,6 @@
 
 import numpy as np
 import plotly.express as px
-import plotly.graph_objs as go
 import plotly.io as pio
 from matbench.constants import CLF_KEY, REG_KEY
 from matbench.metadata import mbv01_metadata
@@ -115,16 +114,14 @@ def plot_leaderboard(
     )
 
     # add scatter for the best algorithms on scaled error
-    fig.add_trace(
-        go.Scatter(
-            mode="markers",
-            x=best_values.index,
-            y=best_values,
-            marker_color="yellow",
-            text=best_algos,
-            visible="legendonly",
-            name="Best algorithms",
-        )
+    fig.add_scatter(
+        mode="markers",
+        x=best_values.index,
+        y=best_values,
+        marker_color="yellow",
+        text=best_algos,
+        visible="legendonly",
+        name="Best algorithms",
     )
     fig.update_traces(marker_size=10)
     fig.update_xaxes(linecolor="grey", gridcolor="grey")

tests/conftest.py

@@ -19,7 +19,7 @@ def df_matbench_phonons():
     """Returns the dataframe for the Matbench phonon DOS peak task."""
 
     df = load_dataset("matbench_phonons")
-    df["material_id"] = [f"mb_phdos_{i+1}" for i in range(len(df))]
+    df["material_id"] = [f"mb_phdos_{i + 1}" for i in range(len(df))]
     df = df.set_index("material_id", drop=False)
     df["composition"] = [x.composition.formula.replace(" ", "") for x in df.structure]
 
@@ -30,10 +30,10 @@ def df_matbench_phonons():
 
 @pytest.fixture(scope="session")
 def df_matbench_jdft2d():
-    """Returns the dataframe for the Matbench experimental band gap task. Currently unused."""
+    """Returns Matbench experimental band gap task dataframe. Currently unused."""
 
     df = load_dataset("matbench_jdft2d")
-    df["material_id"] = [f"mb_jdft2d_{i+1}" for i in range(len(df))]
+    df["material_id"] = [f"mb_jdft2d_{i + 1}" for i in range(len(df))]
     df = df.set_index("material_id", drop=False)
     df["composition"] = [x.composition.formula.replace(" ", "") for x in df.structure]