chore: 🤖 typo fix

src/arpes/analysis/shirley.py

@@ -128,7 +128,7 @@ def calculate_shirley_background_full_range(
         n_samples: The number of samples to use at the boundaries of the input data.
 
     Returns:
-        A monotonic Shirley backgruond over the entire energy range.
+        A monotonic Shirley background over the entire energy range.
     """
     xps_array = (
         xps.copy(deep=True)
@@ -173,7 +173,7 @@ def calculate_shirley_background(
         n_samples: The number of samples to use at the boundaries of the input data.
 
     Returns:
-        A monotonic Shirley backgruond over the entire energy range.
+        A monotonic Shirley background over the entire energy range.
     """
     if energy_range is None:
         energy_range = slice(None, None)

src/arpes/analysis/tarpes.py

@@ -54,7 +54,7 @@ def build_crosscorrelation(
     Args:
         datalist (Sequence[xr.DataArray]): Data series from the cross-correlation experiments.
         delayline_dim: the dimension name for "delay line", which must be in key of data.attrs
-            When this is the "position" dimention, the unit is assumed to be "mm". If the value has
+            When this is the "position" dimension, the unit is assumed to be "mm". If the value has
             already been converted to "time" dimension, set convert_position_to_time=True
         delayline_origin (float): The value corresponding to the delay zero.
         convert_position_to_time: (bool) If true, no conversion into "delay" is processed.
@@ -189,7 +189,7 @@ def find_t_for_max_intensity(data: xr.DataArray, e_bound: float = 0.02) -> float
     """Finds the time corresponding to the maximum (integrated) intensity.
 
     While the time returned can be used to "t=0" in pump probe exepriments, especially for
-    realtively slow (~ps) phenomena, but not always true.
+    relatively slow (~ps) phenomena, but not always true.
 
     Args:
         data: A spectrum with "eV" and "delay" dimensions.

src/arpes/bootstrap.py

@@ -276,7 +276,7 @@ def propagate_errors(f: Callable[P, R]) -> Callable[P, R]:
         f: The inner function to wrap
 
     Returns:
-        The wrapped function handling distributions tranparently.
+        The wrapped function handling distributions transparently.
     """
 
     @functools.wraps(f)

src/arpes/correction/fermi_edge.py

@@ -154,7 +154,7 @@ def build_direct_fermi_edge_correction(
 
     Args:
         arr (xr.DataArray) : input DataArray
-        energy_range (slice): Energy range, which is used in xr.DataArray.sel(). defautl (-0.1, 0.1)
+        energy_range (slice): Energy range, which is used in xr.DataArray.sel(). default (-0.1, 0.1)
         plot (bool): if True, show the plot
         along (str): axis for non energy axis
 

src/arpes/deep_learning/transforms.py

@@ -125,7 +125,7 @@ def decodes_target(self, y: Incomplete) -> Incomplete:
         return y
 
     def __repr__(self) -> str:
-        """Show both of the constitutent parts of this transform."""
+        """Show both of the constituent parts of this transform."""
         return (
             self.__class__.__name__
             + "(\n\t"

src/arpes/endstations/__init__.py

@@ -572,7 +572,7 @@ def load_single_frame(
 
         Returns:
             xr.Dataset: The dataset containing the loaded spectrum data.
-            Load the single frame fro the file.
+            Load the single frame from the file.
         """
         ext = Path(frame_path).suffix
         if scan_desc is None:

src/arpes/endstations/plugin/ALG_spin_ToF.py

@@ -245,7 +245,7 @@ def load_SToF_fits(self, scan_desc: ScanDesc) -> xr.Dataset:
                 except Exception:
                     # we should probably zero pad in the case where the slices are not the right
                     # size
-                    logger.exception("Exception Occure")
+                    logger.exception("Exception Occur")
                     continue
 
                 altered_dimension = dimensions[spectrum_name][0]

src/arpes/endstations/plugin/IF_UMCS.py

@@ -37,7 +37,7 @@ class IF_UMCSEndstation(  # noqa: N801
     LENS_MAPPING: ClassVar[dict[str, bool]] = {
         "HighAngularDispersion": True,
         "MediumAngularDispersion": True,
-        "LowAngularDispersion":  True,
+        "LowAngularDispersion": True,
         "WideAngleMode": True,
         "LowMagnification": False,
         "MediumMagnification": False,
@@ -77,7 +77,7 @@ def load_single_frame(
             if file.suffix == ".xy":
                 data = load_xy(frame_path, **kwargs)
             elif file.suffix == ".itx":
-                msg = "Not suported yet..."
+                msg = "Not supported yet..."
                 raise RuntimeWarning(msg)
             return xr.Dataset({"spectrum": data}, attrs=data.attrs)
 

src/arpes/endstations/plugin/MAESTRO.py

@@ -2,7 +2,7 @@
 
 Common code is provided by a base class reflecting DAQ similarities between micro- and nanoARPES
 at MAESTRO. This is subclassed for the individual experiments to handle some subtle differences
-in how nanoARPES handles its spatial coordiantes (they are hierarchical) and in the spectrometers.
+in how nanoARPES handles its spatial coordinates (they are hierarchical) and in the spectrometers.
 """
 
 from __future__ import annotations
@@ -294,7 +294,7 @@ def update_hierarchical_coordinates(data: xr.Dataset) -> xr.Dataset:
         high-resolution motion axis of a nano-ARPES system.
 
         Working in two coordinate systems is frustrating, and it makes comparing data cumbersome. In
-        PyARPES x,y,z is always the total inferrable coordinate value,
+        PyARPES x,y,z is always the total inferable coordinate value,
         i.e. (+/- long range +/- high resolution) as appropriate. You can still access the
         underlying coordinates in this case as `long_{dim}` and `short_{dim}`.
 

src/arpes/endstations/plugin/Phelix.py

@@ -94,7 +94,7 @@ def postprocess_final(
         - Calculate phi or x values depending on the lens mode.
         - Add missing parameters.
         - Rename keys and dimensions in particular the third dimension that
-        could be psi andle or theta angle in this endstation.
+        could be psi angle or theta angle in this endstation.
 
         Args:
             data(xr.Dataset): ARPES data
@@ -143,10 +143,12 @@ def postprocess_final(
         if "psi" in data.coords:
             data = data.assign_coords(psi=np.deg2rad(data.psi))
         if "theta" in data.coords:
-            data = data.assign_coords(theta=np.deg2rad(
-                - data.theta - Phelix.NORMAL_EMISSION["theta"],
-            ))
-            data = data.isel(theta=slice(None,None,-1))
+            data = data.assign_coords(
+                theta=np.deg2rad(
+                    -data.theta - Phelix.NORMAL_EMISSION["theta"],
+                )
+            )
+            data = data.isel(theta=slice(None, None, -1))
         return super().postprocess_final(data, scan_desc)
 
 

src/arpes/endstations/plugin/fallback.py

@@ -115,7 +115,7 @@ def find_first_file(cls: type[FallbackEndstation], file_number: int) -> Path:
         """Finds any file associated to this scan.
 
         Instead actually using the superclass code here, we first try to determine
-        which loading pluging should be used. Then, we delegate to that class to
+        which loading plugin should be used. Then, we delegate to that class to
         find the first associated file.
         """
         associated_loader = cls.determine_associated_loader(str(file_number))

src/arpes/endstations/plugin/kaindl.py

@@ -189,7 +189,7 @@ def postprocess_final(
         data: xr.Dataset,
         scan_desc: ScanDesc | None = None,
     ) -> xr.Dataset:
-        """Peforms final data preprocessing for the Kaindl lab Tr-ARPES setup.
+        """Performs final data preprocessing for the Kaindl lab Tr-ARPES setup.
 
         This is very similar to what happens at BL4/MERLIN because the code was adopted
         from an old version of the DAQ on that beamline.

src/arpes/endstations/prodigy_xy.py

@@ -9,7 +9,7 @@
 
 Second dimension "nonenegy" is perpendicular to the energy on the MCP detector,
 stored as # NonEnergyOrdinate in each block of the data.
-This could be both: angular (phi angle) or spacial (along the slit direction).
+This could be both: angular (phi angle) or spatial (along the slit direction).
 
 Third dimension/parameter could be:
 - the deflector shift (psi angle)
@@ -96,7 +96,7 @@ def parse(self, list_from_xy_file: list[str]) -> None:
         else:
             num_of_en = int(self.params["values_curve"])
 
-        kinetic_ef_energy = np.linspace(energies[0], energies[num_of_en-1], num_of_en)
+        kinetic_ef_energy = np.linspace(energies[0], energies[num_of_en - 1], num_of_en)
         # first dimension is always energy
         self.axis_info["d1"] = (kinetic_ef_energy, "eV")
 

src/arpes/fits/__init__.py

@@ -67,5 +67,5 @@ class ParametersArgs(TypedDict, total=False):
     vary: bool  # Whether the parameter is varied during the fit
     min: float  # Lower bound for value (default, -np.inf)
     max: float  # Upper bound for value (default np.inf)
-    expr: str  # Mathematical expression to contstrain the value.
+    expr: str  # Mathematical expression to constrain the value.
     brute_step: float  # step size for grid points in the brute method.

src/arpes/fits/fit_models/x_model_mixin.py

@@ -48,7 +48,7 @@ def _prep_parameters(
 
     Returns:
         lf.Parameters
-        Note that lf.Paramters class not, lf.Parameter
+        Note that lf.Parameters class not, lf.Parameter
 
     Notes:
         Example of lf.Parameters()

src/arpes/fits/utilities.py

@@ -67,7 +67,7 @@ def result_to_hints(
         defaults: Returned if `model_result` is None, useful for cell re-evaluation in Jupyter
 
     Returns:
-        A dict containing parameter specifications in key-value rathar than `lmfit.Parameter`
+        A dict containing parameter specifications in key-value rather than `lmfit.Parameter`
         format, as you might pass as `params=` to PyARPES fitting code.
     """
     if model_result is None:
@@ -170,7 +170,7 @@ def broadcast_model(  # noqa: PLR0913
         prefixes: Prefix for the parameter name.  Pass to MPWorker that pass to
           broadcast_common.compile_model.  When prefixes are specified, the number of prefixes must
           be same as the number of models for fitting. If not specified, the prefix automatically is
-          determined as "a\_", "b\_",....  (We recommend to specifiy them explicitly.)
+          determined as "a\_", "b\_",....  (We recommend to specify them explicitly.)
         window: A specification of cuts/windows to apply to each curve fit
         parallelize: Whether to parallelize curve fits, defaults to True if unspecified and more
           than 20 fits were requested.

src/arpes/io.py

@@ -254,7 +254,7 @@ def _df_or_list_to_files(
     assert not isinstance(
         df_or_list,
         list | tuple,
-    ), "Expected an interable for a list of the scans to stitch together"
+    ), "Expected an iterable for a list of the scans to stitch together"
     return list(df_or_list)
 
 

src/arpes/plotting/dos.py

@@ -91,7 +91,7 @@ def plot_dos(
     Args:
         data: ARPES data to plot.
         out (str | Path): Path to the figure.
-        orientation (Literal["horizontal", "vetical"]): Orientation of the figures.
+        orientation (Literal["horizontal", "vertical"]): Orientation of the figures.
         figsize: The figure size (arg of plt.figure())
         kwargs: Pass to the original data.
 

src/arpes/plotting/holoviews.py

@@ -39,7 +39,7 @@ def _fix_xarray_to_fit_with_holoview(dataarray: xr.DataArray) -> xr.DataArray:
         dataarray (xr.DataArray): input Dataarray
 
     Returns:
-        xr.DataArray, whose coordinates is regularly orderd determined by dataarray.dims.
+        xr.DataArray, whose coordinates is regularly ordered determined by dataarray.dims.
     """
     for coord_name in dataarray.coords:
         if coord_name not in dataarray.dims:

src/arpes/preparation/axis_preparation.py

@@ -75,7 +75,7 @@ def sort_axis(data: xr.DataArray, axis_name: str) -> xr.DataArray:
 
 @update_provenance("Flip data along axis")
 def flip_axis(
-    arr: xr.DataArray,  # valuse is used
+    arr: xr.DataArray,  # values is used
     axis_name: str,
     *,
     flip_data: bool = True,

src/arpes/simulation.py

@@ -427,7 +427,7 @@ def __init__(
             k: The momentum axis.
             omega: The energy axis.
             temperature: The temperature to use for the calculation. Defaults to None.
-            mfl_parameter (tuple[float, float]): The MFL paramter ('a', and 'b').
+            mfl_parameter (tuple[float, float]): The MFL parameter ('a', and 'b').
               Defaults to (10.0, 1.0)
         """
         super().__init__(k, omega, temperature)
@@ -451,7 +451,7 @@ def __init__(
         k: NDArray[np.float64] | None = None,
         omega: NDArray[np.float64] | None = None,
         temperature: float = 20,
-        gap_paramters: tuple[float, float, float] = (50, 30, 0),
+        gap_parameters: tuple[float, float, float] = (50, 30, 0),
     ) -> None:
         """Initializes from parameters.
 
@@ -460,10 +460,10 @@ def __init__(
             omega: The energy axis.
             temperature: The temperature to use for the calculation. Defaults to None.
             delta: The gap size.
-            gap_paramters (tuple[float, float, float]): Gap paramter of the BSSCO,
+            gap_parameters (tuple[float, float, float]): Gap parameter of the BSSCO,
               Delta, and two Gamma pamaramters  (s- and p-wave)
         """
-        self.delta, self.gamma_s, self.gamma_p = gap_paramters
+        self.delta, self.gamma_s, self.gamma_p = gap_parameters
         super().__init__(k, omega, temperature)
 
     def digest_to_json(self) -> dict[str, Any]:

src/arpes/utilities/bz.py

@@ -59,7 +59,7 @@ def process_kpath(
     path: str,
     cell: Cell,
 ) -> NDArray[np.float64]:
-    """Converts paths consiting of point definitions to raw coordinates.
+    """Converts paths consisting of point definitions to raw coordinates.
 
     Args:
         path: String that represents the high symmetry points such as "GMK".

src/arpes/utilities/conversion/grids.py

@@ -24,11 +24,11 @@
 
 
 def is_dimension_convertible_to_momentum(dimension_name: str) -> bool:
-    """Determine whether a dimension can paticipate in the momentum conversion.
+    """Determine whether a dimension can participate in the momentum conversion.
 
     if dimension name is in  {"phi", "theta", "beta", "chi", "psi", "hv"}, return True.
     Originally, is_dimension_unconvertible(dimension_name: str) is defined.
-        {"phi", "theta", "beta", "chi", "psi", "hv"} can be converted to momemtum.
+        {"phi", "theta", "beta", "chi", "psi", "hv"} can be converted to momentum.
 
     Args:
         dimension_name (str): [description]

src/arpes/utilities/xarray.py

@@ -101,7 +101,7 @@ def apply_dataarray(
     Args:
         arr (xr.DataArray): original DataArray.
         f (Callable): Function to apple the DataArray.
-        args: argments for "f".
+        args: arguments for "f".
         kwargs: keyword arguments for "f"
 
     Returns:

src/arpes/xarray_extensions.py

@@ -478,7 +478,7 @@ def switch_energy_notation(self, nonlinear_order: int = 1) -> None:
                 )
                 self._obj.attrs["energy_notation"] = "Binding"
         else:
-            msg = "Not impremented yet."
+            msg = "Not implemented yet."
             raise RuntimeError(msg)
 
 
@@ -939,7 +939,7 @@ def short_history(self, key: str = "by") -> list:
         """Return the short version of history.
 
         Args:
-            key (str): key str in recored dict of self.history.  (default: "by")
+            key (str): key str in recorded dict of self.history.  (default: "by")
         """
         return [h["record"][key] if isinstance(h, dict) else h for h in self.history]  # type: ignore[literal-required]
 
@@ -1129,7 +1129,7 @@ class ARPESProperty(ARPESPropertyBase):
 
     @staticmethod
     def dict_to_html(d: Mapping[str, float | str]) -> str:
-        """Returnn html format of dict object.
+        """Return html format of dict object.
 
         Args:
             d: dict object
@@ -1333,7 +1333,7 @@ def transpose_to_front(self, dim: str) -> XrTypes:
         Returns: (XrTypes)
             Transposed ARPES data
 
-        Tooo:
+        Todo:
             Test
         """
         dims = list(self._obj.dims)
@@ -1350,7 +1350,7 @@ def transpose_to_back(self, dim: str) -> XrTypes:
         Returns: (XrTypes)
             Transposed ARPES data.
 
-        Tooo:
+        Todo:
             Test
         """
         dims = list(self._obj.dims)
@@ -2512,7 +2512,7 @@ def iter_coords(
         *,
         reverse: bool = False,
     ) -> Iterator[dict[Hashable, float]]:
-        """Iterator for cooridinates along the axis.
+        """Iterator for coordinates along the axis.
 
         Args:
             dim_names (Sequence[Hashable]): Dimensions for iteration.

tests/test_xarray_extensions.py

@@ -284,14 +284,14 @@ def test_switch_energy_notation(
 
         with pytest.raises(RuntimeError) as e:
             hv_map.S.switch_energy_notation()
-        assert str(e.value) == "Not impremented yet."
+        assert str(e.value) == "Not implemented yet."
 
         with pytest.raises(RuntimeError) as e:
             hv_map.S.switch_energy_notation()
-        assert str(e.value) == "Not impremented yet."
+        assert str(e.value) == "Not implemented yet."
         with pytest.raises(RuntimeError) as e:
             hv_map.spectrum.S.switch_energy_notation()
-        assert str(e.value) == "Not impremented yet."
+        assert str(e.value) == "Not implemented yet."
 
     def test_spectrum_type(self, dataarray_cut: xr.DataArray) -> None:
         """Test spectrum_type."""