from __future__ import annotations
import numpy as np
from matplotlib import pyplot as plt
from matplotlib.axes import Axes
from matplotlib.cm import ScalarMappable
from matplotlib.figure import Figure
from pylbo.visualisation.modes.cartesian_2d import CartesianSlicePlot2D
from pylbo.visualisation.modes.mode_data import ModeVisualisationData
[docs]class CartesianSlicePlot3D(CartesianSlicePlot2D):
"""
Class for handling Cartesian 3D plots of the eigenmode solution.
Parameters
----------
data : ModeVisualisationData
The data for the visualisation.
u2 : np.ndarray
The :math:`y` coordinate of the eigenmode solution.
u3 : np.ndarray
The :math:`z` coordinate of the eigenmode solution.
time : float
The time at which the eigenmode solution is calculated.
slicing_axis : str
The axis along which the eigenmode solution is sliced.
figsize : tuple[int, int]
The size of the figure.
vmin : float
The minimum value of the colourbar. If None, the minimum value of the
solution is used.
vmax : float
The maximum value of the colourbar. If None, the maximum value of the
solution is used.
"""
def __init__(
self,
data: ModeVisualisationData,
u2: np.ndarray,
u3: np.ndarray,
time: float,
slicing_axis: str,
figsize: tuple[int, int],
vmin: float = None,
vmax: float = None,
**kwargs,
) -> None:
if figsize is None:
figsize = (8, 8)
if slicing_axis == "y":
raise NotImplementedError("3D slicing is not implemented for y-axis.")
super().__init__(data, u2, u3, time, slicing_axis, figsize, False, **kwargs)
self.vmin = np.min(self._solutions) if vmin is None else vmin
self.vmax = np.max(self._solutions) if vmax is None else vmax
self._view = [None] * len(self._u3)
self.set_contours(levels=25, fill=True)
[docs] def _create_cbar_axes(self, width: float) -> Axes:
box = self.ax.get_position()
position = (box.x0, box.height + 0.02 + 0.1)
dims = (box.width, width)
return self.fig.add_axes([*position, *dims])
[docs] def _validate_u2(self, u2: np.ndarray, *args, **kwargs) -> np.ndarray:
return u2
[docs] def _validate_u3(self, u3: np.ndarray, *args, **kwargs) -> np.ndarray:
return u3
[docs] def set_plot_arrays(self) -> None:
self.solution_shape = (len(self._u1), len(self._u2))
for ef, omega in zip(self.data.eigenfunction, self.data.omega):
data = np.broadcast_to(ef, shape=reversed(self.solution_shape)).transpose()
self.ef_data.append({"ef": data, "omega": omega})
x_2d, y_2d = np.meshgrid(self.data.ds.ef_grid, self._u2, indexing="ij")
self.u1_data = x_2d
self.u2_data = y_2d
self.u3_data = self._u3
self.time_data = self._time
[docs] def calculate_mode_solution(
self, efdata: np.ndarray, u2: np.ndarray, u3: np.ndarray, t: np.ndarray
) -> np.ndarray:
solutions = np.zeros(shape=(*self.solution_shape, len(u3)))
for i, z in enumerate(u3):
for efdata in self.ef_data:
solutions[..., i] += super().calculate_mode_solution(efdata, u2, z, t)
return solutions
[docs] def draw_eigenfunction(self) -> None:
pass
[docs] def draw_solution(self) -> None:
level_kwargs = {}
if self._contour_levels is not None:
level_kwargs["levels"] = self._contour_levels
for i, z in enumerate(self._u3):
self._view[i] = self._contour_recipe(
self.u1_data,
self.u2_data,
self.solutions[..., i],
zdir="z",
offset=z,
alpha=max(0.4, 1 - i * 0.1),
vmin=self.vmin,
vmax=self.vmax,
**level_kwargs,
**self._kwargs,
)
self.cbar = self.fig.colorbar(
ScalarMappable(norm=self._view[0].norm, cmap=self._view[0].cmap),
cax=self.cbar_ax,
orientation="horizontal",
)
self.ax.set_xlim(np.min(self._u1), np.max(self._u1))
self.ax.set_ylim(np.min(self._u2), np.max(self._u2))
self.ax.set_zlim(np.min(self._u3), np.max(self._u3))
[docs] def add_axes_labels(self) -> None:
super().add_axes_labels()
self.ax.set_zlabel("z")
[docs] def draw_textboxes(self) -> None:
self.t_txt = self.ax.text2D(
0.9,
0.9,
f"t = {self._time:.2f}",
fontsize=15,
transform=self.ax.transAxes,
ha="center",
bbox=dict(facecolor="grey", alpha=0.2, boxstyle="round", pad=0.2),
)
[docs] def _clear_contours(self) -> None:
for view in self._view:
for coll in view.collections:
try:
coll.remove()
except ValueError:
pass
[docs] def _update_view(self, updated_solution: np.ndarray) -> None:
super()._update_contour_plot(updated_solution)
[docs] def _update_view_clims(self, solution: np.ndarray) -> None:
if self.update_colorbar:
self.vmin, self.vmax = np.min(solution), np.max(solution)
[docs] def _set_t_txt(self, t):
self.t_txt.set_text(f"t = {t:.2f}")