Formatting - comp.codata

pyrolite/comp/codata.py

@@ -1,4 +1,5 @@
 import warnings
+
 import numpy as np
 import pandas as pd
 import scipy.special
@@ -39,7 +40,10 @@ def close(X: np.ndarray, sumf=np.sum):
     """
 
     if np.any(X <= 0):
-        warnings.warn("Non-positive entries found. Closure operation assumes all positive entries.", UserWarning)
+        warnings.warn(
+            "Non-positive entries found. Closure operation assumes all positive entries.",
+            UserWarning,
+        )
 
     if X.ndim == 2:
         C = np.array(sumf(X, axis=1), dtype=float)[:, np.newaxis]
@@ -81,16 +85,20 @@ def renormalise(df: pd.DataFrame, components: list = [], scale=100.0):
         dfc = dfc[components]
 
     if (dfc <= 0).any().any():
-        warnings.warn("Non-positive entries found in specified components. "
-                      "Negative values have been replaced with NaN. "
-                      "Renormalisation assumes all positive entries.", UserWarning)
+        warnings.warn(
+            "Non-positive entries found in specified components. "
+            "Negative values have been replaced with NaN. "
+            "Renormalisation assumes all positive entries.",
+            UserWarning,
+        )
 
     # Replace negative values with NaN
     dfc[dfc < 0] = np.nan
 
     # Renormalise all columns if no components are specified
     sum_rows = dfc.sum(axis=1)
-    sum_rows.replace(0, np.nan, inplace=True)  # Handle division by zero by replacing zeros with NaN
+    # Handle division by zero by replacing zeros with NaN
+    sum_rows.replace(0, np.nan, inplace=True)
     dfc = dfc.divide(sum_rows, axis=0) * scale
 
     return dfc
@@ -347,9 +355,11 @@ def get_ALR_labels(df, mode="simple", ind=-1, **kwargs):
 
     names = [
         r"{} / {}".format(
-            c
-            if c not in __sympy_protected_variables__
-            else __sympy_protected_variables__[c],
+            (
+                c
+                if c not in __sympy_protected_variables__
+                else __sympy_protected_variables__[c]
+            ),
             df.columns[ind],
         )
         for c in df.columns
@@ -399,9 +409,11 @@ def get_CLR_labels(df, mode="simple", **kwargs):
 
     names = [
         r"{} / γ".format(
-            c
-            if c not in __sympy_protected_variables__
-            else __sympy_protected_variables__[c],
+            (
+                c
+                if c not in __sympy_protected_variables__
+                else __sympy_protected_variables__[c]
+            ),
         )
         for c in df.columns
     ]
@@ -462,9 +474,11 @@ def get_ILR_labels(df, mode="latex", **kwargs):
     # sub in Phi (the CLR normalisation variable)
     names = [
         r"{} / γ".format(
-            c
-            if c not in __sympy_protected_variables__
-            else __sympy_protected_variables__[c],
+            (
+                c
+                if c not in __sympy_protected_variables__
+                else __sympy_protected_variables__[c]
+            ),
         )
         for c in df.columns
     ]