drop duplicates in set literals

.pre-commit-config.yaml

@@ -8,7 +8,7 @@ ci:
 
 repos:
   - repo: https://github.com/charliermarsh/ruff-pre-commit
-    rev: v0.0.269
+    rev: v0.0.270
     hooks:
       - id: ruff
         args: [--fix]

pymatgen/command_line/gulp_caller.py

@@ -204,7 +204,6 @@
     "meanke",
     "nodensity_out",
     "nodpsym",
-    "nofirst_point",
     "nofrequency",
     "nokpoints",
     "operators",
@@ -217,8 +216,6 @@
     "save",
     "terse",
     # Structure control
-    "full",
-    "hexagonal",
     "lower_symmetry",
     "nosymmetry",
     # PDF control

pymatgen/io/lammps/data.py

@@ -1080,7 +1080,7 @@ def map_mass(v):
 
         self.topo_coeffs = topo_coeffs
         if self.topo_coeffs:
-            self.topo_coeffs = {k: v for k, v in self.topo_coeffs.items() if k in SECTION_KEYWORDS["ff"][2:]}
+            self.topo_coeffs = {key: v for key, v in self.topo_coeffs.items() if key in SECTION_KEYWORDS["ff"][2:]}
             for k in self.topo_coeffs:
                 coeffs, mapper = self._process_topo(k)
                 ff_dfs.update(coeffs)
@@ -1091,20 +1091,20 @@ def map_mass(v):
     def _process_nonbond(self):
         pair_df = pd.DataFrame(self.nonbond_coeffs)
         assert self._is_valid(pair_df), "Invalid nonbond coefficients with rows varying in length"
-        npair, ncoeff = pair_df.shape
-        pair_df.columns = [f"coeff{i}" for i in range(1, ncoeff + 1)]
+        n_pair, n_coeff = pair_df.shape
+        pair_df.columns = [f"coeff{i}" for i in range(1, n_coeff + 1)]
         nm = len(self.mass_info)
-        ncomb = int(nm * (nm + 1) / 2)
-        if npair == nm:
+        n_comb = int(nm * (nm + 1) / 2)
+        if n_pair == nm:
             kw = "Pair Coeffs"
             pair_df.index = range(1, nm + 1)
-        elif npair == ncomb:
+        elif n_pair == n_comb:
             kw = "PairIJ Coeffs"
             ids = list(itertools.combinations_with_replacement(range(1, nm + 1), 2))
             id_df = pd.DataFrame(ids, columns=["id1", "id2"])
             pair_df = pd.concat([id_df, pair_df], axis=1)
         else:
-            raise ValueError(f"Expecting {nm} Pair Coeffs or {ncomb} PairIJ Coeffs for {nm} atom types, got {npair}")
+            raise ValueError(f"Expecting {nm} Pair Coeffs or {n_comb} PairIJ Coeffs for {nm} atom types, got {n_pair}")
         return {kw: pair_df}
 
     def _process_topo(self, kw):
@@ -1113,7 +1113,7 @@ def find_eq_types(label, section):
                 label_arr = np.array(label)
                 seqs = [[0, 1, 2, 3], [0, 2, 1, 3], [3, 1, 2, 0], [3, 2, 1, 0]]
                 return [tuple(label_arr[s]) for s in seqs]
-            return [label] + [label[::-1]]
+            return [label, label[::-1]]
 
         main_data, distinct_types = [], []
         class2_data = {k: [] for k in self.topo_coeffs[kw][0] if k in CLASS2_KEYWORDS.get(kw, [])}

pymatgen/io/phonopy.py

@@ -669,7 +669,6 @@ def get_thermal_displacement_matrices(
         structure_path: path to POSCAR
 
     Returns:
-
     """
     thermal_displacements_dict = loadfn(thermal_displacements_yaml)
 

pymatgen/io/qchem/tests/test_outputs.py

@@ -159,10 +159,7 @@
     "tfsi_nbo.qcout",
     "crowd_nbo_charges.qcout",
     "h2o_aimd.qcout",
-    "quinoxaline_anion.qcout",
-    "crowd_gradient_number.qcout",
     "bsse.qcout",
-    "thiophene_wfs_5_carboxyl.qcout",
     "time_nan_values.qcout",
     "pt_dft_180.0.qcout",
     "qchem_energies/hf-rimp2.qcout",

pymatgen/io/vasp/outputs.py

@@ -4677,29 +4677,21 @@ def __init__(self, filename="WAVECAR", verbose=False, precision="normal", vasp_t
                     np.fromfile(f, dtype=np.float64, count=(recl8 - 4 - 3 * self.nb) % recl8)
 
                     if self.vasp_type is None:
-                        (
-                            self.Gpoints[ink],
-                            extra_gpoints,
-                            extra_coeff_inds,
-                        ) = self._generate_G_points(kpoint, gamma=True)
+                        self.Gpoints[ink], extra_gpoints, extra_coeff_inds = self._generate_G_points(kpoint, gamma=True)
                         if len(self.Gpoints[ink]) == nplane:
                             self.vasp_type = "gam"
                         else:
-                            (
-                                self.Gpoints[ink],
-                                extra_gpoints,
-                                extra_coeff_inds,
-                            ) = self._generate_G_points(kpoint, gamma=False)
+                            self.Gpoints[ink], extra_gpoints, extra_coeff_inds = self._generate_G_points(
+                                kpoint, gamma=False
+                            )
                             self.vasp_type = "std" if len(self.Gpoints[ink]) == nplane else "ncl"
 
                         if verbose:
-                            print("\ndetermined vasp_type =", self.vasp_type, "\n")
+                            print(f"\ndetermined {self.vasp_type = }\n")
                     else:
-                        (
-                            self.Gpoints[ink],
-                            extra_gpoints,
-                            extra_coeff_inds,
-                        ) = self._generate_G_points(kpoint, gamma=self.vasp_type.lower()[0] == "g")
+                        self.Gpoints[ink], extra_gpoints, extra_coeff_inds = self._generate_G_points(
+                            kpoint, gamma=self.vasp_type.lower()[0] == "g"
+                        )
 
                     if len(self.Gpoints[ink]) != nplane and 2 * len(self.Gpoints[ink]) != nplane:
                         raise ValueError(

pymatgen/util/convergence.py

@@ -37,7 +37,6 @@ def id_generator(size=8, chars=string.ascii_uppercase + string.digits):
         chars ():
 
     Returns:
-
     """
     return "".join(random.choice(chars) for _ in range(size))
 
@@ -103,7 +102,6 @@ def print_and_raise_error(xs, ys, name):
         name ():
 
     Returns:
-
     """
     print("Index error in", name)
     print("ys: ", ys)
@@ -168,7 +166,6 @@ def p0_exponential(xs, ys):
         ys ():
 
     Returns:
-
     """
     n0 = 1.005
     b0 = (n0 ** -xs[-1] - n0 ** -xs[1]) / (ys[-1] - ys[1])
@@ -200,7 +197,6 @@ def p0_single_reciprocal(xs, ys):
         ys ():
 
     Returns:
-
     """
     c = 1
     b = (1 / (xs[-1] - c) - 1 / (xs[1] - c)) / (ys[-1] - ys[1])
@@ -230,7 +226,6 @@ def p0_simple_reciprocal(xs, ys):
         ys ():
 
     Returns:
-
     """
     b = (ys[-1] - ys[-2]) / (1 / (xs[-1]) - 1 / (xs[-2]))
     a = ys[-2] - b / (xs[-2])
@@ -260,7 +255,6 @@ def p0_simple_2reciprocal(xs, ys):
         ys ():
 
     Returns:
-
     """
     c = 2
     b = (ys[-1] - ys[1]) / (1 / xs[-1] ** c - 1 / xs[1] ** c)
@@ -291,7 +285,6 @@ def p0_simple_4reciprocal(xs, ys):
         ys ():
 
     Returns:
-
     """
     c = 4
     b = (ys[-1] - ys[1]) / (1 / xs[-1] ** c - 1 / xs[1] ** c)
@@ -321,7 +314,6 @@ def p0_simple_5reciprocal(xs, ys):
         ys ():
 
     Returns:
-
     """
     c = 0.5
     b = (ys[-1] - ys[1]) / (1 / xs[-1] ** c - 1 / xs[1] ** c)
@@ -337,7 +329,6 @@ def extrapolate_simple_reciprocal(xs, ys):
         ys ():
 
     Returns:
-
     """
     b = (ys[-2] - ys[-1]) / (1 / (xs[-2]) - 1 / (xs[-1]))
     a = ys[-1] - b / (xs[-1])
@@ -383,7 +374,7 @@ def measure(function, xs, ys, popt, weights):
                 raise NotImplementedError
             n += 1
         except IndexError:
-            raise RuntimeError("y does not exist for x = ", x, " this should not happen")
+            raise RuntimeError(f"y does not exist for {x = }, this should not happen")
 
     return m
 
@@ -396,7 +387,6 @@ def get_weights(xs, ys, mode=2):
         mode ():
 
     Returns:
-
     """
     ds = get_derivatives(xs, ys, fd=True)
     if mode == 1:
@@ -407,10 +397,10 @@ def get_weights(xs, ys, mode=2):
         for d in ds:
             weights.append(abs(mind / d))
     if mode == 2:
-        maxxs = max(xs) ** 2
+        x_max = max(xs) ** 2
         weights = []
         for x in xs:
-            weights.append(x**2 / maxxs)
+            weights.append(x**2 / x_max)
     else:
         weights = [1] * len(xs)
     return weights