docs

Author: jmmshn

pyproject.toml

@@ -76,7 +76,6 @@ select = [
   # "ERA001",
   "RUF",
   "D409",
-  "D416",
   "TCH",
   "TID251",
   "T20",
@@ -98,7 +97,7 @@ skip-magic-trailing-comma = false
 line-ending = "auto"
 
 [tool.ruff.lint.pydocstyle]
-convention = "google"
+convention = "numpy"
 
 [tool.mypy]
 ignore_missing_imports = true

src/pyrho/charge_density.py

@@ -30,7 +30,7 @@ class ChargeDensity(MSONable):
 
     Defines a charge density with a PGrid object along with the atomic structure.
 
-    Attributes:
+    Attributes
     ----------
     pgrids: Dict[str, PGrid]
         Dictionaries whose values are periodic ``PGrid`` objects
@@ -67,7 +67,7 @@ def normalized_data(self) -> dict[str, npt.NDArray]:
         Since different codes use different normalization methods for
         volumetric data we should convert them to the same units (electrons / Angstrom^3)
 
-        Returns:
+        Returns
         -------
         dict[str, NDArray]:
             The normalized data in units of (electrons / Angstrom^3)
@@ -94,7 +94,7 @@ def normalized_pgrids(self) -> dict[str, PGrid]:
         Since different codes use different normalization methods for
         volumetric data we should convert them to the same units (electrons / Angstrom^3)
 
-        Returns:
+        Returns
         -------
         dict[str, PGrid]:
             The normalized pgrids in units of (electrons / Angstrom^3)
@@ -134,7 +134,7 @@ def from_pmg(
             - 'vasp' sum of the data / number of grid points == number of electrons
             - None/"none" no normalization
 
-        Returns:
+        Returns
         -------
         ChargeDensity:
             The charge density object
@@ -173,7 +173,7 @@ def get_data_in_cube(self, s: float, ngrid: int, key: str = "total") -> npt.NDAr
         key:
             The key to read from ``self.normalized_data``
 
-        Returns:
+        Returns
         -------
         NDArray:
             Regridded data in a ngrid x ngrid x ngrid array
@@ -205,7 +205,7 @@ def get_transformed(
         up_sample:
             The factor to scale up the sampling of the grid data using Fourier interpolation
 
-        Returns:
+        Returns
         -------
         ChargeDensity:
             The transformed ChargeDensity object
@@ -256,7 +256,7 @@ def to_Chgcar(self) -> Chgcar:
 
         Scale and convert each key in the pgrids dictionary and create a ``Chgcar`` object
 
-        Returns:
+        Returns
         -------
         Chgcar:
             The charge density object
@@ -271,7 +271,7 @@ def to_VolumetricData(
 
         Scale and convert each key in the pgrids dictionary and create a ``VolumetricData`` object
 
-        Returns:
+        Returns
         -------
         VolumetricData:
             The charge density object
@@ -299,7 +299,7 @@ def from_file(
             The pymatgen object to read from the file (default: Chgcar).
             the `from_file` method from this class will be called to read the file.
 
-        Returns:
+        Returns
         -------
             ChargeDensity: The ChargeDensity object
 
@@ -320,7 +320,7 @@ def from_hdf5(
             The pymatgen object to read from the file (default: Chgcar).
             the `from_file` method from this class will be called to read the file.
 
-        Returns:
+        Returns
         -------
             ChargeDensity: The ChargeDensity object
 
@@ -342,7 +342,7 @@ def get_matched_structure_mapping(
     sc_struct: bigger cell
     sm: StructureMatcher instance
 
-    Returns:
+    Returns
     -------
     sc_m : supercell matrix to apply to s1 to get s2
     total_t : translation to apply on s1 * sc_m to get s2
@@ -372,7 +372,7 @@ def get_volumetric_like_sc(
 ):
     """Get the volumetric data in the supercell.
 
-    Parameters:
+    Parameters
     ----------
     vd: VolumeData instance
     sc_struct: supercell structure.
@@ -384,7 +384,7 @@ def get_volumetric_like_sc(
         same as VASP's CHGCAR file. If None, no normalization is
         done.
 
-    Returns:
+    Returns
     -------
     VolumetricData: volumetric data in the supercell
     """
@@ -422,7 +422,7 @@ def multiply_aug(data_aug: list[str], factor: int) -> list[str]:
     factor:
         The multiplication factor (some integer number of times it gets repeated)
 
-    Returns:
+    Returns
     -------
     List[str]:
         Each line of the augmentation data.
@@ -477,7 +477,7 @@ def _normalize_data(
             where the second `/vol` account for the different number of electrons in
             different cells
 
-    Returns:
+    Returns
     -------
     NDArray:
         The normalized grid data
@@ -505,7 +505,7 @@ def _scaled_data(
     normalization:
         The normalization method defaults to vasp
 
-    Returns:
+    Returns
     -------
     NDArray:
         The un-normalized grid data

src/pyrho/pgrid.py

@@ -24,7 +24,7 @@ class PGrid(MSONable):
     def __init__(self, grid_data: npt.NDArray, lattice: npt.NDArray):
         """Initialize the PGrid object.
 
-        Attributes:
+        Attributes
         ----------
         grid_data:
             Data stored on the regular rid
@@ -61,7 +61,7 @@ def _transform_data(
         up_sample:
             The factor to scale up the sampling of the grid data using Fourier interpolation
 
-        Returns:
+        Returns
         -------
         NDArray:
             The transformed data
@@ -89,7 +89,7 @@ def __mul__(self, factor: float) -> PGrid:
         factor:
             The factor to multiply the grid data by
 
-        Returns:
+        Returns
         -------
         PGrid:
             The new PGrid object
@@ -105,7 +105,7 @@ def __truediv__(self, factor: float) -> PGrid:
         factor:
             The factor to divide the grid data by
 
-        Returns:
+        Returns
         -------
         PGrid:
             The new PGrid object
@@ -133,7 +133,7 @@ def get_transformed(
         up_sample:
             The factor to scale up the sampling of the grid data using Fourier interpolation
 
-        Returns:
+        Returns
         -------
         PGrid:
             The transformed PGrid object
@@ -161,7 +161,7 @@ def lossy_smooth_compression(
         smear_std:
             standard deviation of the Gaussian smoothing
 
-        Returns:
+        Returns
         -------
         NDArray:
             Smoothed array

src/pyrho/utils.py

@@ -51,7 +51,7 @@ def pad_arr(arr_in: NDArray, shape: List[int]) -> NDArray:
     shape:
         Desired shape of the array
 
-    Returns:
+    Returns
     -------
     NDArray:
         padded data
@@ -117,7 +117,7 @@ def interpolate_fourier(arr_in: NDArray, shape: List[int]) -> NDArray:
     shape:
         Desired shape shape of the interpolated data
 
-    Returns:
+    Returns
     -------
     NDArray:
         Interpolated data in the desired shape
@@ -144,7 +144,7 @@ def roll_array(arr: NDArray, roll_vec: List[int]) -> NDArray:
     roll_vec:
         number of indices in each direction to roll
 
-    Returns:
+    Returns
     -------
     NDArray:
         The rolled array
@@ -194,7 +194,7 @@ def get_sc_interp(
     origin:
         Shift applied to the origin in fractional coordinates
 
-    Returns:
+    Returns
     -------
     NDArray:
         size ``(ndim x prod(grid_size))`` the cartesian coordinates of each point in the new data
@@ -238,7 +238,7 @@ def get_padded_array(data_in: NDArray) -> NDArray:
     data_in:
         Array to be padded
 
-    Returns:
+    Returns
     -------
     NDArray:
         Padded array
@@ -267,7 +267,7 @@ def get_plane_spacing(lattice: NDArray) -> List[float]:
     lattice:
         List of lattice vectors in cartesian coordinates
 
-    Returns:
+    Returns
     -------
     List[float]:
         List where the k-th element is is the spacing of planes generated by all
@@ -312,7 +312,7 @@ def get_ucell_frac_fit_sphere(lattice: np.ndarray, r: float = 0.2) -> Iterable[f
     r:
         width of the sphere
 
-    Returns:
+    Returns
     -------
     Iterable of floats
         fraction of lattice vector in each direction need to fit the sphere
@@ -347,7 +347,7 @@ def gaussian_smear(
     multiple:
         ``multiple * sigma`` is the cutoff radius for the smearing
 
-    Returns:
+    Returns
     -------
     NDArray:
         The smear data array.

src/pyrho/vis/scatter.py

@@ -48,7 +48,7 @@ def get_scatter_plot(
         Plotter to use, either "matplotlib" or "plotly"
 
 
-    Returns:
+    Returns
     -------
     Figure | Axes:
         `Figure` object or `Axes` object from matplotlib to be rendered in a notebook