More precise typing of arguments by using Literal

pde/fields/base.py

@@ -19,6 +19,7 @@
     Callable,
     Dict,
     List,
+    Literal,
     Optional,
     Tuple,
     Type,
@@ -924,7 +925,7 @@ def random_normal(
         mean: float = 0,
         std: float = 1,
         *,
-        scaling: str = "none",
+        scaling: Literal["none", "physical"] = "none",
         label: Optional[str] = None,
         dtype: Optional[DTypeLike] = None,
         rng: Optional[np.random.Generator] = None,
@@ -2135,7 +2136,7 @@ def _update_image_plot(self, reference: PlotReference) -> None:
     def _plot_vector(
         self,
         ax,
-        method: str = "quiver",
+        method: Literal["quiver", "streamplot"] = "quiver",
         transpose: bool = False,
         max_points: int = 16,
         **kwargs,
@@ -2163,7 +2164,7 @@ def _plot_vector(
             the plot with new data later.
         """
         # store the parameters of this plot for later updating
-        parameters = {
+        parameters: Dict[str, Any] = {
             "method": method,
             "transpose": transpose,
             "kwargs": kwargs,

pde/fields/scalar.py

@@ -8,7 +8,17 @@
 
 import numbers
 from pathlib import Path
-from typing import TYPE_CHECKING, Callable, Dict, List, Optional, Sequence, Tuple, Union
+from typing import (
+    TYPE_CHECKING,
+    Callable,
+    Dict,
+    List,
+    Literal,
+    Optional,
+    Sequence,
+    Tuple,
+    Union,
+)
 
 import numpy as np
 from numpy.typing import DTypeLike
@@ -267,7 +277,7 @@ def integral(self) -> Number:
     def project(
         self,
         axes: Union[str, Sequence[str]],
-        method: str = "integral",
+        method: Literal["integral", "average", "mean"] = "integral",
         label: Optional[str] = None,
     ) -> ScalarField:
         """project scalar field along given axes
@@ -323,7 +333,7 @@ def slice(
         self,
         position: Dict[str, float],
         *,
-        method: str = "nearest",
+        method: Literal["nearest"] = "nearest",
         label: Optional[str] = None,
     ) -> ScalarField:
         """slice data at a given position

pde/grids/base.py

@@ -55,6 +55,7 @@
 
 PI_4 = 4 * np.pi
 PI_43 = 4 / 3 * np.pi
+CoordsType = Literal["cartesian", "grid", "cells"]
 
 
 class OperatorInfo(NamedTuple):
@@ -835,7 +836,7 @@ def get_image_data(self, data: np.ndarray) -> Dict[str, Any]:
 
     @abstractmethod
     def get_random_point(
-        self, *, boundary_distance: float = 0, coords: str = "cartesian"
+        self, *, boundary_distance: float = 0, coords: CoordsType = "cartesian"
     ) -> np.ndarray:
         ...
 

pde/grids/boundaries/local.py

@@ -70,6 +70,7 @@
     Callable,
     Dict,
     List,
+    Literal,
     Optional,
     Tuple,
     Type,
@@ -1097,6 +1098,9 @@ def ghost_cell_setter(data_full: np.ndarray, args=None) -> None:
         return ghost_cell_setter  # type: ignore
 
 
+ExpressionBCTargetType = Literal["value", "derivative", "mixed", "virtual_point"]
+
+
 class ExpressionBC(BCBase):
     """represents a boundary whose virtual point is calculated from an expression
 
@@ -1118,7 +1122,7 @@ def __init__(
         rank: int = 0,
         value: Union[float, str, Callable] = 0,
         const: Union[float, str, Callable] = 0,
-        target: str = "virtual_point",
+        target: ExpressionBCTargetType = "virtual_point",
     ):
         r"""
         Warning:
@@ -1485,7 +1489,7 @@ def __init__(
         *,
         rank: int = 0,
         value: Union[float, str, Callable] = 0,
-        target: str = "value",
+        target: ExpressionBCTargetType = "value",
     ):
         super().__init__(grid, axis, upper, rank=rank, value=value, target=target)
 
@@ -1511,7 +1515,7 @@ def __init__(
         *,
         rank: int = 0,
         value: Union[float, str, Callable] = 0,
-        target: str = "derivative",
+        target: ExpressionBCTargetType = "derivative",
     ):
         super().__init__(grid, axis, upper, rank=rank, value=value, target=target)
 
@@ -1538,7 +1542,7 @@ def __init__(
         rank: int = 0,
         value: Union[float, str, Callable] = 0,
         const: Union[float, str, Callable] = 0,
-        target: str = "mixed",
+        target: ExpressionBCTargetType = "mixed",
     ):
         super().__init__(
             grid, axis, upper, rank=rank, value=value, const=const, target=target

pde/grids/cartesian.py

@@ -23,7 +23,7 @@
 
 from ..tools.cuboid import Cuboid
 from ..tools.plotting import plot_on_axes
-from .base import DimensionError, GridBase, _check_shape
+from .base import CoordsType, DimensionError, GridBase, _check_shape
 
 if TYPE_CHECKING:
     from .boundaries.axes import Boundaries, BoundariesData  # @UnusedImport
@@ -254,7 +254,7 @@ def get_random_point(
         self,
         *,
         boundary_distance: float = 0,
-        coords: str = "cartesian",
+        coords: CoordsType = "cartesian",
         rng: Optional[np.random.Generator] = None,
     ) -> np.ndarray:
         """return a random point within the grid

pde/grids/cylindrical.py

@@ -6,12 +6,28 @@
 
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Any, Dict, Generator, Optional, Sequence, Tuple, Union
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Dict,
+    Generator,
+    Literal,
+    Optional,
+    Sequence,
+    Tuple,
+    Union,
+)
 
 import numpy as np
 
 from ..tools.cache import cached_property
-from .base import DimensionError, GridBase, _check_shape, discretize_interval
+from .base import (
+    CoordsType,
+    DimensionError,
+    GridBase,
+    _check_shape,
+    discretize_interval,
+)
 from .cartesian import CartesianGrid
 
 if TYPE_CHECKING:
@@ -213,7 +229,7 @@ def get_random_point(
         *,
         boundary_distance: float = 0,
         avoid_center: bool = False,
-        coords: str = "cartesian",
+        coords: CoordsType = "cartesian",
         rng: Optional[np.random.Generator] = None,
     ) -> np.ndarray:
         """return a random point within the grid
@@ -461,7 +477,9 @@ def polar_coordinates_real(
         else:
             return dist
 
-    def get_cartesian_grid(self, mode: str = "valid") -> CartesianGrid:
+    def get_cartesian_grid(
+        self, mode: Literal["valid", "full"] = "valid"
+    ) -> CartesianGrid:
         """return a Cartesian grid for this Cylindrical one
 
         Args:

pde/grids/operators/cartesian.py

@@ -15,7 +15,7 @@
 .. codeauthor:: David Zwicker <[email protected]>   
 """
 
-from typing import Callable, Tuple
+from typing import Callable, Literal, Tuple
 
 import numba as nb
 import numpy as np
@@ -165,7 +165,9 @@ def _get_laplace_matrix(bcs: Boundaries) -> Tuple[np.ndarray, np.ndarray]:
 
 
 def _make_derivative(
-    grid: CartesianGrid, axis: int = 0, method: str = "central"
+    grid: CartesianGrid,
+    axis: int = 0,
+    method: Literal["central", "forward", "backward"] = "central",
 ) -> OperatorType:
     """make a derivative operator along a single axis using numba compilation
 
@@ -520,7 +522,10 @@ def laplace(arr: np.ndarray, out: np.ndarray) -> None:
 
 
 @CartesianGrid.register_operator("laplace", rank_in=0, rank_out=0)
-def make_laplace(grid: CartesianGrid, backend: str = "auto") -> OperatorType:
+def make_laplace(
+    grid: CartesianGrid,
+    backend: Literal["auto", "numba", "numba-spectral", "scipy"] = "auto",
+) -> OperatorType:
     """make a Laplace operator on a Cartesian grid
 
     Args:
@@ -691,7 +696,9 @@ def gradient(arr: np.ndarray, out: np.ndarray) -> None:
 
 
 @CartesianGrid.register_operator("gradient", rank_in=0, rank_out=1)
-def make_gradient(grid: CartesianGrid, backend: str = "auto") -> OperatorType:
+def make_gradient(
+    grid: CartesianGrid, backend: Literal["auto", "numba", "scipy"] = "auto"
+) -> OperatorType:
     """make a gradient operator on a Cartesian grid
 
     Args:
@@ -1046,7 +1053,9 @@ def divergence(arr: np.ndarray, out: np.ndarray) -> None:
 
 
 @CartesianGrid.register_operator("divergence", rank_in=1, rank_out=0)
-def make_divergence(grid: CartesianGrid, backend: str = "auto") -> OperatorType:
+def make_divergence(
+    grid: CartesianGrid, backend: Literal["auto", "numba", "scipy"] = "auto"
+) -> OperatorType:
     """make a divergence operator on a Cartesian grid
 
     Args:
@@ -1090,7 +1099,10 @@ def make_divergence(grid: CartesianGrid, backend: str = "auto") -> OperatorType:
 
 
 def _vectorize_operator(
-    make_operator: Callable, grid: CartesianGrid, *, backend: str = "numba"
+    make_operator: Callable,
+    grid: CartesianGrid,
+    *,
+    backend: Literal["auto", "numba", "scipy"] = "numba",
 ) -> OperatorType:
     """apply an operator to on all dimensions of a vector
 
@@ -1120,7 +1132,9 @@ def vectorized_operator(arr: np.ndarray, out: np.ndarray) -> None:
 
 
 @CartesianGrid.register_operator("vector_gradient", rank_in=1, rank_out=2)
-def make_vector_gradient(grid: CartesianGrid, backend: str = "numba") -> OperatorType:
+def make_vector_gradient(
+    grid: CartesianGrid, backend: Literal["auto", "numba", "scipy"] = "numba"
+) -> OperatorType:
     """make a vector gradient operator on a Cartesian grid
 
     Args:
@@ -1136,7 +1150,9 @@ def make_vector_gradient(grid: CartesianGrid, backend: str = "numba") -> Operato
 
 
 @CartesianGrid.register_operator("vector_laplace", rank_in=1, rank_out=1)
-def make_vector_laplace(grid: CartesianGrid, backend: str = "numba") -> OperatorType:
+def make_vector_laplace(
+    grid: CartesianGrid, backend: Literal["auto", "numba", "scipy"] = "numba"
+) -> OperatorType:
     """make a vector Laplacian on a Cartesian grid
 
     Args:
@@ -1152,7 +1168,9 @@ def make_vector_laplace(grid: CartesianGrid, backend: str = "numba") -> Operator
 
 
 @CartesianGrid.register_operator("tensor_divergence", rank_in=2, rank_out=1)
-def make_tensor_divergence(grid: CartesianGrid, backend: str = "numba") -> OperatorType:
+def make_tensor_divergence(
+    grid: CartesianGrid, backend: Literal["auto", "numba", "scipy"] = "numba"
+) -> OperatorType:
     """make a tensor divergence operator on a Cartesian grid
 
     Args:
@@ -1168,7 +1186,9 @@ def make_tensor_divergence(grid: CartesianGrid, backend: str = "numba") -> Opera
 
 
 @CartesianGrid.register_operator("poisson_solver", rank_in=0, rank_out=0)
-def make_poisson_solver(bcs: Boundaries, method: str = "auto") -> OperatorType:
+def make_poisson_solver(
+    bcs: Boundaries, method: Literal["auto", "scipy"] = "auto"
+) -> OperatorType:
     """make a operator that solves Poisson's equation
 
     Args:

pde/grids/operators/common.py

@@ -6,7 +6,7 @@
 
 import logging
 import warnings
-from typing import Callable, Optional
+from typing import Callable, Literal, Optional
 
 import numpy as np
 
@@ -56,7 +56,9 @@ def laplace(arr: np.ndarray, out: Optional[np.ndarray] = None) -> np.ndarray:
     return laplace
 
 
-def make_general_poisson_solver(matrix, vector, method: str = "auto") -> OperatorType:
+def make_general_poisson_solver(
+    matrix, vector, method: Literal["auto", "scipy"] = "auto"
+) -> OperatorType:
     """make an operator that solves Poisson's problem
 
     Args:

pde/grids/operators/cylindrical_sym.py

@@ -15,7 +15,7 @@
 .. codeauthor:: David Zwicker <[email protected]>
 """
 
-from typing import Tuple
+from typing import Literal, Tuple
 
 import numba as nb
 import numpy as np
@@ -430,7 +430,9 @@ def tensor_divergence(arr: np.ndarray, out: np.ndarray) -> None:
 
 @CylindricalSymGrid.register_operator("poisson_solver", rank_in=0, rank_out=0)
 @fill_in_docstring
-def make_poisson_solver(bcs: Boundaries, method: str = "auto") -> OperatorType:
+def make_poisson_solver(
+    bcs: Boundaries, method: Literal["auto", "scipy"] = "auto"
+) -> OperatorType:
     """make a operator that solves Poisson's equation
 
     {DESCR_CYLINDRICAL_GRID}

pde/grids/operators/polar_sym.py

@@ -14,7 +14,7 @@
 .. codeauthor:: David Zwicker <[email protected]>
 """
 
-from typing import Tuple
+from typing import Literal, Tuple
 
 import numpy as np
 
@@ -310,7 +310,9 @@ def _get_laplace_matrix(bcs: Boundaries) -> Tuple[np.ndarray, np.ndarray]:
 
 @PolarSymGrid.register_operator("poisson_solver", rank_in=0, rank_out=0)
 @fill_in_docstring
-def make_poisson_solver(bcs: Boundaries, method: str = "auto") -> OperatorType:
+def make_poisson_solver(
+    bcs: Boundaries, method: Literal["auto", "scipy"] = "auto"
+) -> OperatorType:
     """make a operator that solves Poisson's equation
 
     {DESCR_POLAR_GRID}