Fix: fixed electronic step check with algo = exact and nelm = 1 (#4071)

* fixed electronic step check with algo = exact and nelm = 1

* pre-commit auto-fixes

* fixed the cases in which ALGO does not appear in incar

* pre-commit auto-fixes

---------

Co-authored-by: yanghan-microsoft <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

src/pymatgen/io/vasp/outputs.py

@@ -624,6 +624,8 @@ def converged_electronic(self) -> bool:
             while set(final_elec_steps[idx]) == to_check:
                 idx += 1
             return idx + 1 != self.parameters["NELM"]
+        if self.incar.get("ALGO", "").upper() == "EXACT" and self.incar.get("NELM") == 1:
+            return True
         return len(final_elec_steps) < self.parameters["NELM"]
 
     @property
@@ -1699,8 +1701,10 @@ def __init__(
         self.separate_spins = separate_spins
 
         with zopen(filename, mode="rt") as file:
-            self.efermi = self.eigenvalues = self.projected_eigenvalues = None
-            parsed_header = in_kpoints_opt = False
+            self.efermi = None
+            parsed_header = False
+            in_kpoints_opt = False
+            self.eigenvalues = self.projected_eigenvalues = None
             self.kpoints_opt_props = None
             for event, elem in ET.iterparse(file, events=["start", "end"]):
                 tag = elem.tag
@@ -1980,7 +1984,10 @@ def __init__(self, filename: PathLike) -> None:
 
         # For single atom systems, VASP doesn't print a total line, so
         # reverse parsing is very difficult
-        read_charge = read_mag_x = read_mag_y = read_mag_z = False  # for SOC calculations only
+        read_charge = False
+        read_mag_x = False
+        read_mag_y = False  # for SOC calculations only
+        read_mag_z = False
         all_lines.reverse()
         for clean in all_lines:
             if read_charge or read_mag_x or read_mag_y or read_mag_z:
@@ -1999,7 +2006,10 @@ def __init__(self, filename: PathLike) -> None:
                     elif read_mag_z:
                         mag_z.append(dict(zip(header, tokens, strict=True)))
                 elif clean.startswith("tot"):
-                    read_charge = read_mag_x = read_mag_y = read_mag_z = False
+                    read_charge = False
+                    read_mag_x = False
+                    read_mag_y = False
+                    read_mag_z = False
             if clean == "total charge":
                 charge = []
                 read_charge = True
@@ -2486,8 +2496,10 @@ def read_cs_core_contribution(self) -> None:
         self.data["cs_core_contribution"] = core_contrib
 
     def read_cs_raw_symmetrized_tensors(self) -> None:
-        """Parse the matrix form of NMR tensor before corrected to table
-        and set as self.data["unsym_cs_tensor"].
+        """Parse the matrix form of NMR tensor before corrected to table.
+
+        Returns:
+            nsymmetrized tensors list in the order of atoms.
         """
         header_pattern = r"\s+-{50,}\s+\s+Absolute Chemical Shift tensors\s+\s+-{50,}$"
         first_part_pattern = r"\s+UNSYMMETRIZED TENSORS\s+$"
@@ -3475,7 +3487,8 @@ def parse_file(filename: PathLike) -> tuple[Poscar, dict, dict]:
         dim: list[int] = []
         dimline = ""
         read_dataset = False
-        ngrid_pts = data_count = 0
+        ngrid_pts = 0
+        data_count = 0
         poscar = None
         with zopen(filename, mode="rt") as file:
             for line in file:
@@ -3941,13 +3954,16 @@ def _read(self, filename: PathLike, parsed_kpoints: set[tuple[Kpoint]] | None =
             ion_expr = re.compile(r"^ion.*")
             total_expr = re.compile(r"^tot.*")
             expr = re.compile(r"^([0-9]+)\s+")
-            current_kpoint = current_band = 0
+            current_kpoint = 0
+            current_band = 0
             spin = Spin.down  # switched to Spin.up for first block
 
             n_kpoints = None
             kpoints: list[tuple[float, float, float]] = []
-            n_bands = n_ions = headers = None
+            n_bands = None
+            n_ions = None
             weights: np.ndarray[float] | None = None
+            headers = None
             data: dict[Spin, np.ndarray] = {}
             eigenvalues: dict[Spin, np.ndarray] | None = None
             occupancies: dict[Spin, np.ndarray] | None = None
@@ -3960,7 +3976,8 @@ def _read(self, filename: PathLike, parsed_kpoints: set[tuple[Kpoint]] | None =
 
             # first dynamically determine whether PROCAR is SOC or not; SOC PROCARs have 4 lists of projections (
             # total and x,y,z) for each band, while non-SOC have only 1 list of projections:
-            tot_count = band_count = 0
+            tot_count = 0
+            band_count = 0
             for line in file_handle:
                 if total_expr.match(line):
                     tot_count += 1
@@ -4516,7 +4533,8 @@ def get_str(
         lines.extend((" ".join(self.site_symbols), " ".join(map(str, self.natoms))))
 
         format_str = f"{{:.{significant_figures}f}}"
-        ionicstep_cnt = output_cnt = 1
+        ionicstep_cnt = 1
+        output_cnt = 1
         for cnt, structure in enumerate(self.structures, start=1):
             ionicstep_cnt = cnt
             if (
@@ -5137,7 +5155,7 @@ def get_parchg(
 
         # Scaling of ng for the fft grid, need to restore value at the end
         temp_ng = self.ng
-        self.ng = self.ng * scale  # (ruff-preview) noqa: PLR6104
+        self.ng = self.ng * scale
         N = np.prod(self.ng)
 
         data = {}