📚 Fix autodoc reference warnings

Added some to the `nitpick_ignore`, since I couldn't immediately figure out
why it isn't finding these...

docs/source/conf.py

@@ -54,7 +54,8 @@
 intersphinx_mapping = {
     "python": ("https://docs.python.org/3/", None),
     "numpy": ("https://numpy.org/doc/stable/", None),
-    "aiida": ("https://aiida.readthedocs.io/projects/aiida-core/en/latest", None),
+    "aiida": ("https://aiida.readthedocs.io/projects/aiida-core/en/latest/", None),
+    "aiida_pseudo": ("https://aiida-pseudo.readthedocs.io/en/latest/", None),
 }
 
 # Settings for the `sphinx_copybutton` extension
@@ -64,8 +65,6 @@
 )
 copybutton_prompt_is_regexp = True
 
-nitpick_ignore = [("py:obj", "module")]
-
 # Add any paths that contain templates here, relative to this directory.
 templates_path = ["_templates"]
 
@@ -187,6 +186,10 @@
 # Warnings to ignore when using the -n (nitpicky) option
 # We should ignore any python built-in exception, for instance
 nitpick_ignore = [
+    ("py:obj", "module"),
+    ("py:class", "numpy.array"),
+    ("py:class", "np.array"),
+    ("py:class", "ty.Tuple"),
     ("py:exc", "ArithmeticError"),
     ("py:exc", "AssertionError"),
     ("py:exc", "AttributeError"),

src/aiida_wannier90_workflows/utils/bands/distance.py

@@ -114,15 +114,10 @@ def bands_distance(
     """Calculate bands distance with ``mu`` set as Ef to Ef+5.
 
     :param bands_dft: [description]
-    :type bands_dft: orm.BandsData
     :param bands_wannier: [description]
-    :type bands_wannier: orm.BandsData
     :param fermi_energy: [description]
-    :type fermi_energy: float
     :param exclude_list_dft: [description], defaults to None
-    :type exclude_list_dft: list, optional
     :return: [description], unit is eV.
-    :rtype: np.array
     """
     if isinstance(bands_dft, orm.BandsData):
         dft_bands = bands_dft.get_bands()

src/aiida_wannier90_workflows/utils/code.py

@@ -31,9 +31,7 @@ def identify_codes(
     ```
 
     :param codes: a list of code identifier
-    :type codes: ty.Iterable[str, int, orm.Code]
     :return: a dict with plugin name as key, ``Code`` as value.
-    :rtype: ty.Dict[str, orm.Code]
     """
     results = {}
 

src/aiida_wannier90_workflows/utils/kpoints.py

@@ -50,13 +50,9 @@ def create_kpoints_from_distance(
     this is not a ``calcfunction``, so the AiiDA database is unchanged.
 
     :param structure: [description]
-    :type structure: [type]
     :param distance: [description]
-    :type distance: [type]
     :param force_parity: whether the generated mesh is even or odd.
-    :type force_parity: bool, aiida.orm.Bool
     :return: [description]
-    :rtype: [type]
     """
     kpoints = orm.KpointsData()
     kpoints.set_cell_from_structure(structure)
@@ -89,7 +85,6 @@ def cartesian_product(*arrays: np.ndarray) -> np.ndarray:
     """Cartesian product.
 
     :return: _description_
-    :rtype: np.ndarray
     """
     la = len(arrays)  # pylint: disable=invalid-name
     dtype = np.result_type(*arrays)
@@ -103,10 +98,8 @@ def get_mesh_from_kpoints(kpoints: orm.KpointsData) -> ty.List:
     """From .
 
     :param kpoints: contains a N1 * N2 * N3 mesh
-    :type kpoints: aiida.orm.KpointsData
     :raises AttributeError: if kmesh does not contains a mesh
     :return: an explicit list of kpoints
-    :rtype: aiida.orm.KpointsData
     """
     try:  # test if it is a mesh
         mesh, _ = kpoints.get_kpoints_mesh()
@@ -137,11 +130,8 @@ def create_kpoints_from_mesh(
     """Create KpointsData from a given distance.
 
     :param structure: [description]
-    :type structure: [type]
     :param mesh: [description]
-    :type mesh: [type]
     :return: [description]
-    :rtype: [type]
     """
     kpoints = orm.KpointsData()
     kpoints.set_cell_from_structure(structure)
@@ -159,11 +149,8 @@ def get_explicit_kpoints_from_mesh(
     """Create an explicit list of kpoints with a given distance.
 
     :param structure: [description]
-    :type structure: [type]
     :param mesh: [description]
-    :type mesh: [type]
     :return: [description]
-    :rtype: [type]
     """
     kpoints = create_kpoints_from_mesh(structure, mesh)
     kpoints = get_explicit_kpoints(kpoints)
@@ -178,9 +165,7 @@ def get_path_from_kpoints(kpoints: orm.KpointsData) -> orm.Dict:
     to the input `kpoint_path` (a Dict object) of Wannier90Calculation.
 
     :param kpoints: the input KpointsData must contain `labels`.
-    :type kpoints: orm.KpointsData
     :return: the returned Dict object contains two keys: `path` and `point_coords`.
-    :rtype: orm.Dict
     """
     assert kpoints.labels is not None, "`kpoints` must have `labels`"
     assert len(kpoints.labels) >= 2
@@ -231,9 +216,7 @@ def get_kpoints_from_bands(bands: orm.BandsData) -> orm.KpointsData:
     """Create a ``KpointsData`` from a ``BandsData``.
 
     :param bands: the input ``BandsData`` object .
-    :type bands: aiida.orm.BandsData
     :return: the returned ``KpointsData`` must contain ``labels``.
-    :rtype: aiida.orm.KpointsData
     """
     kpoints = orm.KpointsData()
 

src/aiida_wannier90_workflows/utils/parser/center.py

@@ -60,11 +60,8 @@ def generate_supercell(
     """Generate a supercell for finding nearest neighbours.
 
     :param cell: each row is a lattice vector
-    :type cell: np.array
     :param size: number of repetitions = 2*size + 1, defaults to 2
-    :type size: int, optional
     :return: supercell and the translation index
-    :rtype: list[np.array, np.array]
     """
     # Generate a supercell (2D: square, 3D: cube).
     # If the angles between lattice vectors are small, a 3*3*3 supercell is not enough
@@ -221,9 +218,7 @@ def get_wigner_seitz(cell: np.array, search_size: int = 2) -> np.array:
     """Get Wigner-Seitz cell.
 
     :param cell: each row is a lattice vector.
-    :type cell: np.array
     :return: Wigner-Seitz cell
-    :rtype: np.array
     """
     import itertools
 

src/aiida_wannier90_workflows/utils/pseudo/__init__.py

@@ -17,13 +17,10 @@ def get_pseudo_and_cutoff(
     """Get pseudo potential and cutoffs of a given pseudo family and structure.
 
     :param pseudo_family: [description]
-    :type pseudo_family: str
     :param structure: [description]
-    :type structure: orm.StructureData
     :raises ValueError: [description]
     :raises ValueError: [description]
     :return: [description]
-    :rtype: ty.Tuple[ty.Mapping[str, PseudoPotentialData], float, float]
     """
     try:
         pseudo_set = (PseudoDojoFamily, SsspFamily, CutoffsPseudoPotentialFamily)
@@ -88,11 +85,8 @@ def get_semicore_list(structure: orm.StructureData, pseudo_orbitals: dict) -> li
     """Get semicore states (a subset of pseudo wavefunctions) in the pseudopotential.
 
     :param structure: [description]
-    :type structure: orm.StructureData
     :param pseudo_orbitals: [description]
-    :type pseudo_orbitals: dict
     :return: [description]
-    :rtype: list
     """
     from copy import deepcopy
 
@@ -147,7 +141,6 @@ def get_wannier_number_of_bands(
     """Estimate number of bands for a Wannier90 calculation.
 
     :param structure: crystal structure
-    :type structure: aiida.orm.StructureData
     :param pseudos: dictionary of pseudopotentials
     :type pseudos: dict of aiida.orm.UpfData
     :param only_valence: return only occupied number of badns

src/aiida_wannier90_workflows/utils/scdm.py

@@ -82,13 +82,9 @@ def fit_scdm_mu_sigma(
     This is the AiiDA wrapper of `fit_scdm_mu_sigma_raw`.
 
     :param pw2wan_parameters: pw2wannier90 input parameters (the one to update with this calcfunction)
-    :type pw2wan_parameters: orm.Dict
     :param bands: band structure of the projwfc output
-    :type bands: orm.BandsData
     :param projections: projectability of the projwfc output
-    :type projections: orm.ProjectionData
     :param sigma_factor: sigma_factor of SCDM
-    :type sigma_factor: orm.Float
     """
     bands_array, projections_array = get_projectability_arrays(bands, projections)
     return fit_scdm_mu_sigma_raw(
@@ -128,9 +124,7 @@ def sort_projectability_arrays(bands: np.array, projections: np.array):
     """Sort projectability arrays by energy in ascending order.
 
     :param bands: output of projwfc, it was computed in the nscf calc
-    :type bands: np.array, shape num_kpoints * num_bands
     :param projections: output of projwfc
-    :type projections: np.array, shape num_kpoints * num_bands
     """
     # Flattening (projection modulus squared according to QE, energies)
     projwfc_flat = projections.flatten()
@@ -153,11 +147,8 @@ def get_energy_of_projectability(
     """Return energy corresponds to projectability = thresholds.
 
     :param bands: [description]
-    :type bands: orm.BandsData
     :param projections: [description]
-    :type projections: orm.ProjectionData
     :param thresholds: [description]
-    :type thresholds: float
     """
     bands_array, projections_array = get_projectability_arrays(bands, projections)
     sorted_bands, sorted_projwfc = sort_projectability_arrays(