Index
module-attribute
__all__ = [
"GNST",
"LadeDuncan",
"MatsuokaNakai",
"MohrCoulomb",
"SMP",
"Tresca",
"VonMises",
"Wang2025",
"Wang2025CA",
"YieldFunction",
"yield_function_registry",
]
module-attribute
yield_function_registry: Registry[str, Type[YieldFunction]] = Registry()
Bases: YieldFunction
class-attribute
instance-attribute
Bases: YieldFunction
Bases: YieldFunction
Bases: YieldFunction
Bases: YieldFunction, Tresca
class-attribute
instance-attribute
Bases: YieldFunction, VonMises
class-attribute
instance-attribute
Bases: YieldFunction
class-attribute
instance-attribute
PARAMETERS = [
"phi",
"F1",
"F2",
"F12",
"F13",
"F23",
"weight_mises",
"weight_tresca",
"weight_mohr_coulomb",
"weight_smp",
"unit",
"vectorize",
"fast_orthotropy",
"elastoplastic_with_modified_stress_tensor",
]
class-attribute
instance-attribute
bounds = {
"phi": (0, 90),
"F1": (-10, 10),
"F2": (-10, 10),
"F12": (-10, 10),
"F13": (-10, 10),
"F23": (-10, 10),
"weight_mises": (0, 100000.0),
"weight_tresca": (0, 100000.0),
"weight_mohr_coulomb": (0, 100000.0),
"weight_smp": (0, 100000.0),
}
class-attribute
instance-attribute
Whether to use the elastoplastic framework with the modified stress tensor
class-attribute
instance-attribute
stds = {
"phi": 1.0,
"F1": 0.1,
"F2": 0.1,
"F12": 0.1,
"F13": 0.1,
"F23": 0.1,
"weight_mises": 0.1,
"weight_tresca": 0.1,
"weight_mohr_coulomb": 0.1,
"weight_smp": 0.1,
}
class-attribute
instance-attribute
class-attribute
instance-attribute
x0 = {
"phi": 30.0,
"F1": 0.0,
"F2": 0.0,
"F12": 0.0,
"F13": 0.0,
"F23": 0.0,
"weight_mises": 0.0,
"weight_tresca": 0.0,
"weight_mohr_coulomb": 1.0,
"weight_smp": 0.0,
}
__init__(
phi: float,
F1: float = 0.0,
F2: float = 0.0,
F12: float = 0.0,
F13: float = 0.0,
F23: float = 0.0,
weight_mises: float = 0.0,
weight_tresca: float = 0.0,
weight_mohr_coulomb: float = 1.0,
weight_smp: float = 0.0,
*,
unit: Literal["rad", "deg"] = "deg",
vectorize: bool = True,
fast_orthotropy: bool = True,
**kwargs
)
staticmethod
residual(
fitting_params: List[float],
stress_states: ndarray,
fitting_param_names: List[str],
**kwargs
)
setCriterion(
criterion: (
Literal[
"Mises",
"Tresca",
"MohrCoulomb",
"SMP",
"Mises-SMP",
"Tresca-MohrCoulomb",
]
| str
),
*args,
**kwargs
)
Set the criterion to use.
setFabricTensor(
*args: float | ndarray,
r1: float = 0.0,
r2: float = 0.0,
r3: float = 0.0,
unit: Literal["rad", "deg"] = "deg"
)
Set fabric tensor.
| PARAMETER | DESCRIPTION |
|---|---|
args
|
A tuple of 5 floats for F1, F2, F12, F13, F23 or a 3x3 fabric tensor.
TYPE:
|
r1
|
Rotation angle around axis-1, by default 0.0.
TYPE:
|
r2
|
Rotation angle around axis-2, by default 0.0.
TYPE:
|
r3
|
Rotation angle around axis-3, by default 0.0.
TYPE:
|
unit
|
Unit of rotation angles, by default "deg".
TYPE:
|
Use Mises-SMP criterion.
Bases: Wang2025
__init__(
phi: float,
F1: float | None = None,
F2: float | None = None,
F3: float | None = None,
major_axes: int = 1,
weight_mises: float = 0.0,
weight_tresca: float = 0.0,
weight_mohr_coulomb: float = 1.0,
weight_smp: float = 0.0,
*,
unit: Literal["rad", "deg"] = "deg",
vectorize: bool = True,
fast_orthotropy: bool = True,
**kwargs
)
Bases: YieldFunction, CalibrationABC
class-attribute
caches: Dict[str, LRUCache] = {
"get": cachetools.LRUCache(maxsize=128),
"get_2d_xydata": cachetools.LRUCache(maxsize=128),
}
class-attribute
instance-attribute
class-attribute
instance-attribute
get_2d_xydata(
polar: bool = False,
normalize: bool | Literal["max", "mean", "x"] | float = True,
normalize_x: float | None = None,
resolution: int = 500,
min_theta: float | None = None,
max_theta: float | None = None,
**kwargs
) -> Tuple[ndarray, ndarray]
Get the x and y data for plotting the yield function in 2D.
| PARAMETER | DESCRIPTION |
|---|---|
polar
|
Whether to plot in polar coordinates.
TYPE:
|
normalize
|
Whether to normalize the yield function. If True or "max", normalize by the maximum value. If "mean",
normalize by the mean value, if "x", normalize by the value corresponding to this angle specified by
TYPE:
|
normalize_x
|
The angle to normalize the yield function.
TYPE:
|
resolution
|
The resolution of the plot.
TYPE:
|
min_theta
|
The minimum angle to plot.
TYPE:
|
max_theta
|
The maximum angle to plot.
TYPE:
|
kwargs
|
Keyword arguments for 2D project functions.
DEFAULT:
|
| RETURNS | DESCRIPTION |
|---|---|
Tuple[ndarray, ndarray]
|
The x and y data for plotting the yield function. |
Lode angle in Sector I (0, pi/3).
Lode angle in Sector II (pi/3, 2*pi/3).
Lode angle in Sector III (2*pi/3, pi).
Friction angle in Sector I (0, pi/3).
Friction angle in Sector II (pi/3, 2*pi/3).
Friction angle in Sector III (2*pi/3, pi).
plot2d(
plane: Tuple[float, float, float] | None = None,
origin: Tuple[float, float, float] | None = None,
polar: bool = False,
normalize: bool | Literal["max", "mean", "x"] | float = True,
normalize_x: float | None = None,
resolution: int = 500,
eq_stress: float | None = None,
min_stress: float | None = None,
max_stress: float | None = None,
min_theta: float | None = None,
max_theta: float | None = None,
*,
on: Plottable | None = None,
backend: Literal["matplotlib", "bokeh"] | str | None = None,
subplots_kwargs: dict | None = None,
props: Dict[str, Any] | None = None,
bokeh_show: bool = False,
tight_layout: bool = True,
fill_color: str | None = None,
fill_kwargs: Dict | None = None,
**kwargs
) -> Union["MplFigure", "BkGridPlot"]
Plot the yield function in 2D.
| PARAMETER | DESCRIPTION |
|---|---|
plane
|
The direction of the plane to plot the yield function.
TYPE:
|
origin
|
The origin of the plane to plot the yield function.
TYPE:
|
polar
|
Whether to plot in polar coordinates.
TYPE:
|
normalize
|
Whether to normalize the yield function. If True or "max", normalize by the maximum value. If "mean",
normalize by the mean value, if "x", normalize by the value corresponding to this angle specified by
TYPE:
|
normalize_x
|
The angle to normalize the yield function.
TYPE:
|
resolution
|
The resolution of the plot.
TYPE:
|
eq_stress
|
The equivalent stress to plot.
TYPE:
|
min_stress
|
The minimum stress to plot.
TYPE:
|
max_stress
|
The maximum stress to plot.
TYPE:
|
min_theta
|
The minimum angle to plot.
TYPE:
|
max_theta
|
The maximum angle to plot.
TYPE:
|
on
|
Axes to plot on, by default None
TYPE:
|
backend
|
Backend to use, by default None which means the backend set in the environment variable
TYPE:
|
subplots_kwargs
|
Keyword arguments for creating the subplots, by default None
TYPE:
|
props
|
Properties passed to the
TYPE:
|
bokeh_show
|
Whether to show the figure in the browser, by default False
TYPE:
|
tight_layout
|
Whether to use tight layout in the matplotlib figure, by default True
TYPE:
|
fill_color
|
Fill color
TYPE:
|
fill_kwargs
|
Keyword arguments for the fill
TYPE:
|
kwargs
|
Keyword arguments for
DEFAULT:
|
| RETURNS | DESCRIPTION |
|---|---|
Figure | GridPlot
|
The matplotlib figure or bokeh gridplot |
plot3d(
type: Literal["surface", "trisurf", "wireframe"] = "trisurf",
resolution: int = 100,
eq_stress: float | None = None,
min_stress: float | None = None,
max_stress: float | None = None,
min_mean_stress: float | None = None,
max_mean_stress: float | None = None,
*,
on: Plottable | None = None,
backend: Literal["matplotlib", "bokeh"] | str | None = None,
subplots_kwargs: dict | None = None,
props: Dict[str, Any] | None = None,
bokeh_show: bool = False,
tight_layout: bool = True,
**kwargs
) -> Union["MplFigure", "BkGridPlot"]
Plot the yield function in 3D.
| PARAMETER | DESCRIPTION |
|---|---|
type
|
The type of the plot.
TYPE:
|
resolution
|
The resolution of the plot.
TYPE:
|
eq_stress
|
The equivalent stress to plot.
TYPE:
|
min_stress
|
The minimum stress to plot.
TYPE:
|
max_stress
|
The maximum stress to plot.
TYPE:
|
min_mean_stress
|
The minimum mean stress to plot.
TYPE:
|
max_mean_stress
|
The maximum mean stress to plot.
TYPE:
|
on
|
Axes to plot on, by default None
TYPE:
|
backend
|
Backend to use, by default None which means the backend set in the environment variable
TYPE:
|
subplots_kwargs
|
Keyword arguments for creating the subplots, by default None
TYPE:
|
props
|
Properties passed to the
TYPE:
|
bokeh_show
|
Whether to show the figure in the browser, by default False
TYPE:
|
tight_layout
|
Whether to use tight layout in the matplotlib figure, by default True
TYPE:
|
kwargs
|
Keyword arguments for
DEFAULT:
|
| RETURNS | DESCRIPTION |
|---|---|
Figure | GridPlot
|
The matplotlib figure or bokeh gridplot |
Angle in Sector I (0, pi/3).
Angle in Sector II (pi/3, 2*pi/3).