535 lines
20 KiB
Python
535 lines
20 KiB
Python
from __future__ import annotations
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import io
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from typing import TYPE_CHECKING, Any, cast
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import matplotlib.collections as mcollections
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import matplotlib.pyplot as plt
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import numpy as np
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from contourpy import FillType, LineType
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from contourpy.convert import convert_filled, convert_lines
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from contourpy.enum_util import as_fill_type, as_line_type
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from contourpy.util.mpl_util import filled_to_mpl_paths, lines_to_mpl_paths
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from contourpy.util.renderer import Renderer
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if TYPE_CHECKING:
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from collections.abc import Sequence
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from matplotlib.axes import Axes
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from matplotlib.figure import Figure
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from numpy.typing import ArrayLike
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import contourpy._contourpy as cpy
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class MplRenderer(Renderer):
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"""Utility renderer using Matplotlib to render a grid of plots over the same (x, y) range.
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Args:
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nrows (int, optional): Number of rows of plots, default ``1``.
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ncols (int, optional): Number of columns of plots, default ``1``.
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figsize (tuple(float, float), optional): Figure size in inches, default ``(9, 9)``.
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show_frame (bool, optional): Whether to show frame and axes ticks, default ``True``.
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backend (str, optional): Matplotlib backend to use or ``None`` for default backend.
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Default ``None``.
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gridspec_kw (dict, optional): Gridspec keyword arguments to pass to ``plt.subplots``,
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default None.
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"""
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_axes: Sequence[Axes]
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_fig: Figure
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_want_tight: bool
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def __init__(
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self,
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nrows: int = 1,
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ncols: int = 1,
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figsize: tuple[float, float] = (9, 9),
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show_frame: bool = True,
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backend: str | None = None,
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gridspec_kw: dict[str, Any] | None = None,
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) -> None:
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if backend is not None:
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import matplotlib as mpl
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mpl.use(backend)
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kwargs: dict[str, Any] = {"figsize": figsize, "squeeze": False,
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"sharex": True, "sharey": True}
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if gridspec_kw is not None:
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kwargs["gridspec_kw"] = gridspec_kw
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else:
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kwargs["subplot_kw"] = {"aspect": "equal"}
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self._fig, axes = plt.subplots(nrows, ncols, **kwargs)
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self._axes = axes.flatten()
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if not show_frame:
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for ax in self._axes:
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ax.axis("off")
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self._want_tight = True
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def __del__(self) -> None:
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if hasattr(self, "_fig"):
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plt.close(self._fig)
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def _autoscale(self) -> None:
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# Using axes._need_autoscale attribute if need to autoscale before rendering after adding
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# lines/filled. Only want to autoscale once per axes regardless of how many lines/filled
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# added.
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for ax in self._axes:
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if getattr(ax, "_need_autoscale", False):
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ax.autoscale_view(tight=True)
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ax._need_autoscale = False # type: ignore[attr-defined]
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if self._want_tight and len(self._axes) > 1:
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self._fig.tight_layout()
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def _get_ax(self, ax: Axes | int) -> Axes:
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if isinstance(ax, int):
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ax = self._axes[ax]
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return ax
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def filled(
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self,
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filled: cpy.FillReturn,
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fill_type: FillType | str,
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ax: Axes | int = 0,
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color: str = "C0",
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alpha: float = 0.7,
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) -> None:
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"""Plot filled contours on a single Axes.
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Args:
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filled (sequence of arrays): Filled contour data as returned by
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:func:`~contourpy.ContourGenerator.filled`.
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fill_type (FillType or str): Type of ``filled`` data as returned by
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:attr:`~contourpy.ContourGenerator.fill_type`, or string equivalent
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ax (int or Maplotlib Axes, optional): Which axes to plot on, default ``0``.
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color (str, optional): Color to plot with. May be a string color or the letter ``"C"``
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followed by an integer in the range ``"C0"`` to ``"C9"`` to use a color from the
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``tab10`` colormap. Default ``"C0"``.
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alpha (float, optional): Opacity to plot with, default ``0.7``.
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"""
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fill_type = as_fill_type(fill_type)
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ax = self._get_ax(ax)
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paths = filled_to_mpl_paths(filled, fill_type)
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collection = mcollections.PathCollection(
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paths, facecolors=color, edgecolors="none", lw=0, alpha=alpha)
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ax.add_collection(collection)
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ax._need_autoscale = True # type: ignore[attr-defined]
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def grid(
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self,
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x: ArrayLike,
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y: ArrayLike,
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ax: Axes | int = 0,
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color: str = "black",
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alpha: float = 0.1,
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point_color: str | None = None,
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quad_as_tri_alpha: float = 0,
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) -> None:
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"""Plot quad grid lines on a single Axes.
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Args:
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x (array-like of shape (ny, nx) or (nx,)): The x-coordinates of the grid points.
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y (array-like of shape (ny, nx) or (ny,)): The y-coordinates of the grid points.
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ax (int or Matplotlib Axes, optional): Which Axes to plot on, default ``0``.
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color (str, optional): Color to plot grid lines, default ``"black"``.
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alpha (float, optional): Opacity to plot lines with, default ``0.1``.
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point_color (str, optional): Color to plot grid points or ``None`` if grid points
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should not be plotted, default ``None``.
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quad_as_tri_alpha (float, optional): Opacity to plot ``quad_as_tri`` grid, default 0.
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Colors may be a string color or the letter ``"C"`` followed by an integer in the range
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``"C0"`` to ``"C9"`` to use a color from the ``tab10`` colormap.
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Warning:
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``quad_as_tri_alpha > 0`` plots all quads as though they are unmasked.
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"""
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ax = self._get_ax(ax)
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x, y = self._grid_as_2d(x, y)
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kwargs: dict[str, Any] = {"color": color, "alpha": alpha}
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ax.plot(x, y, x.T, y.T, **kwargs)
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if quad_as_tri_alpha > 0:
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# Assumes no quad mask.
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xmid = 0.25*(x[:-1, :-1] + x[1:, :-1] + x[:-1, 1:] + x[1:, 1:])
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ymid = 0.25*(y[:-1, :-1] + y[1:, :-1] + y[:-1, 1:] + y[1:, 1:])
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kwargs["alpha"] = quad_as_tri_alpha
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ax.plot(
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np.stack((x[:-1, :-1], xmid, x[1:, 1:])).reshape((3, -1)),
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np.stack((y[:-1, :-1], ymid, y[1:, 1:])).reshape((3, -1)),
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np.stack((x[1:, :-1], xmid, x[:-1, 1:])).reshape((3, -1)),
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np.stack((y[1:, :-1], ymid, y[:-1, 1:])).reshape((3, -1)),
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**kwargs)
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if point_color is not None:
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ax.plot(x, y, color=point_color, alpha=alpha, marker="o", lw=0)
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ax._need_autoscale = True # type: ignore[attr-defined]
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def lines(
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self,
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lines: cpy.LineReturn,
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line_type: LineType | str,
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ax: Axes | int = 0,
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color: str = "C0",
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alpha: float = 1.0,
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linewidth: float = 1,
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) -> None:
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"""Plot contour lines on a single Axes.
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Args:
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lines (sequence of arrays): Contour line data as returned by
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:func:`~contourpy.ContourGenerator.lines`.
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line_type (LineType or str): Type of ``lines`` data as returned by
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:attr:`~contourpy.ContourGenerator.line_type`, or string equivalent.
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ax (int or Matplotlib Axes, optional): Which Axes to plot on, default ``0``.
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color (str, optional): Color to plot lines. May be a string color or the letter ``"C"``
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followed by an integer in the range ``"C0"`` to ``"C9"`` to use a color from the
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``tab10`` colormap. Default ``"C0"``.
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alpha (float, optional): Opacity to plot lines with, default ``1.0``.
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linewidth (float, optional): Width of lines, default ``1``.
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"""
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line_type = as_line_type(line_type)
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ax = self._get_ax(ax)
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paths = lines_to_mpl_paths(lines, line_type)
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collection = mcollections.PathCollection(
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paths, facecolors="none", edgecolors=color, lw=linewidth, alpha=alpha)
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ax.add_collection(collection)
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ax._need_autoscale = True # type: ignore[attr-defined]
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def mask(
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self,
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x: ArrayLike,
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y: ArrayLike,
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z: ArrayLike | np.ma.MaskedArray[Any, Any],
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ax: Axes | int = 0,
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color: str = "black",
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) -> None:
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"""Plot masked out grid points as circles on a single Axes.
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Args:
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x (array-like of shape (ny, nx) or (nx,)): The x-coordinates of the grid points.
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y (array-like of shape (ny, nx) or (ny,)): The y-coordinates of the grid points.
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z (masked array of shape (ny, nx): z-values.
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ax (int or Matplotlib Axes, optional): Which Axes to plot on, default ``0``.
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color (str, optional): Circle color, default ``"black"``.
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"""
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mask = np.ma.getmask(z) # type: ignore[no-untyped-call]
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if mask is np.ma.nomask:
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return
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ax = self._get_ax(ax)
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x, y = self._grid_as_2d(x, y)
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ax.plot(x[mask], y[mask], "o", c=color)
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def save(self, filename: str, transparent: bool = False) -> None:
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"""Save plots to SVG or PNG file.
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Args:
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filename (str): Filename to save to.
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transparent (bool, optional): Whether background should be transparent, default
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``False``.
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"""
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self._autoscale()
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self._fig.savefig(filename, transparent=transparent)
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def save_to_buffer(self) -> io.BytesIO:
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"""Save plots to an ``io.BytesIO`` buffer.
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Return:
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BytesIO: PNG image buffer.
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"""
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self._autoscale()
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buf = io.BytesIO()
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self._fig.savefig(buf, format="png")
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buf.seek(0)
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return buf
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def show(self) -> None:
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"""Show plots in an interactive window, in the usual Matplotlib manner.
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"""
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self._autoscale()
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plt.show()
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def title(self, title: str, ax: Axes | int = 0, color: str | None = None) -> None:
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"""Set the title of a single Axes.
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Args:
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title (str): Title text.
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ax (int or Matplotlib Axes, optional): Which Axes to set the title of, default ``0``.
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color (str, optional): Color to set title. May be a string color or the letter ``"C"``
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followed by an integer in the range ``"C0"`` to ``"C9"`` to use a color from the
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``tab10`` colormap. Default is ``None`` which uses Matplotlib's default title color
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that depends on the stylesheet in use.
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"""
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if color:
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self._get_ax(ax).set_title(title, color=color)
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else:
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self._get_ax(ax).set_title(title)
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def z_values(
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self,
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x: ArrayLike,
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y: ArrayLike,
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z: ArrayLike,
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ax: Axes | int = 0,
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color: str = "green",
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fmt: str = ".1f",
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quad_as_tri: bool = False,
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) -> None:
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"""Show ``z`` values on a single Axes.
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Args:
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x (array-like of shape (ny, nx) or (nx,)): The x-coordinates of the grid points.
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y (array-like of shape (ny, nx) or (ny,)): The y-coordinates of the grid points.
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z (array-like of shape (ny, nx): z-values.
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ax (int or Matplotlib Axes, optional): Which Axes to plot on, default ``0``.
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color (str, optional): Color of added text. May be a string color or the letter ``"C"``
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followed by an integer in the range ``"C0"`` to ``"C9"`` to use a color from the
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``tab10`` colormap. Default ``"green"``.
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fmt (str, optional): Format to display z-values, default ``".1f"``.
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quad_as_tri (bool, optional): Whether to show z-values at the ``quad_as_tri`` centers
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of quads.
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Warning:
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``quad_as_tri=True`` shows z-values for all quads, even if masked.
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"""
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ax = self._get_ax(ax)
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x, y = self._grid_as_2d(x, y)
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z = np.asarray(z)
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ny, nx = z.shape
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for j in range(ny):
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for i in range(nx):
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ax.text(x[j, i], y[j, i], f"{z[j, i]:{fmt}}", ha="center", va="center",
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color=color, clip_on=True)
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if quad_as_tri:
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for j in range(ny-1):
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for i in range(nx-1):
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xx = np.mean(x[j:j+2, i:i+2])
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yy = np.mean(y[j:j+2, i:i+2])
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zz = np.mean(z[j:j+2, i:i+2])
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ax.text(xx, yy, f"{zz:{fmt}}", ha="center", va="center", color=color,
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clip_on=True)
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class MplTestRenderer(MplRenderer):
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"""Test renderer implemented using Matplotlib.
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No whitespace around plots and no spines/ticks displayed.
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Uses Agg backend, so can only save to file/buffer, cannot call ``show()``.
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"""
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def __init__(
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self,
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nrows: int = 1,
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ncols: int = 1,
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figsize: tuple[float, float] = (9, 9),
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) -> None:
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gridspec = {
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"left": 0.01,
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"right": 0.99,
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"top": 0.99,
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"bottom": 0.01,
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"wspace": 0.01,
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"hspace": 0.01,
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}
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super().__init__(
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nrows, ncols, figsize, show_frame=True, backend="Agg", gridspec_kw=gridspec,
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)
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for ax in self._axes:
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ax.set_xmargin(0.0)
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ax.set_ymargin(0.0)
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ax.set_xticks([])
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ax.set_yticks([])
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self._want_tight = False
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class MplDebugRenderer(MplRenderer):
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"""Debug renderer implemented using Matplotlib.
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Extends ``MplRenderer`` to add extra information to help in debugging such as markers, arrows,
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text, etc.
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"""
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def __init__(
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self,
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nrows: int = 1,
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ncols: int = 1,
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figsize: tuple[float, float] = (9, 9),
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show_frame: bool = True,
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) -> None:
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super().__init__(nrows, ncols, figsize, show_frame)
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def _arrow(
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self,
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ax: Axes,
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line_start: cpy.CoordinateArray,
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line_end: cpy.CoordinateArray,
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color: str,
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alpha: float,
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arrow_size: float,
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) -> None:
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mid = 0.5*(line_start + line_end)
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along = line_end - line_start
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along /= np.sqrt(np.dot(along, along)) # Unit vector.
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right = np.asarray((along[1], -along[0]))
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arrow = np.stack((
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mid - (along*0.5 - right)*arrow_size,
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mid + along*0.5*arrow_size,
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mid - (along*0.5 + right)*arrow_size,
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))
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ax.plot(arrow[:, 0], arrow[:, 1], "-", c=color, alpha=alpha)
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def filled(
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self,
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filled: cpy.FillReturn,
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fill_type: FillType | str,
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ax: Axes | int = 0,
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color: str = "C1",
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alpha: float = 0.7,
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line_color: str = "C0",
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line_alpha: float = 0.7,
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point_color: str = "C0",
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start_point_color: str = "red",
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arrow_size: float = 0.1,
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) -> None:
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fill_type = as_fill_type(fill_type)
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super().filled(filled, fill_type, ax, color, alpha)
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if line_color is None and point_color is None:
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return
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ax = self._get_ax(ax)
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filled = convert_filled(filled, fill_type, FillType.ChunkCombinedOffset)
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# Lines.
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if line_color is not None:
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for points, offsets in zip(*filled):
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if points is None:
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continue
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for start, end in zip(offsets[:-1], offsets[1:]):
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xys = points[start:end]
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ax.plot(xys[:, 0], xys[:, 1], c=line_color, alpha=line_alpha)
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if arrow_size > 0.0:
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n = len(xys)
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for i in range(n-1):
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self._arrow(ax, xys[i], xys[i+1], line_color, line_alpha, arrow_size)
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# Points.
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if point_color is not None:
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for points, offsets in zip(*filled):
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if points is None:
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continue
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mask = np.ones(offsets[-1], dtype=bool)
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mask[offsets[1:]-1] = False # Exclude end points.
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if start_point_color is not None:
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start_indices = offsets[:-1]
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mask[start_indices] = False # Exclude start points.
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ax.plot(
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points[:, 0][mask], points[:, 1][mask], "o", c=point_color, alpha=line_alpha)
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if start_point_color is not None:
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ax.plot(points[:, 0][start_indices], points[:, 1][start_indices], "o",
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c=start_point_color, alpha=line_alpha)
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def lines(
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self,
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lines: cpy.LineReturn,
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line_type: LineType | str,
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ax: Axes | int = 0,
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color: str = "C0",
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alpha: float = 1.0,
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linewidth: float = 1,
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point_color: str = "C0",
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start_point_color: str = "red",
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arrow_size: float = 0.1,
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) -> None:
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line_type = as_line_type(line_type)
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super().lines(lines, line_type, ax, color, alpha, linewidth)
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if arrow_size == 0.0 and point_color is None:
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return
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ax = self._get_ax(ax)
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separate_lines = convert_lines(lines, line_type, LineType.Separate)
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if TYPE_CHECKING:
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separate_lines = cast(cpy.LineReturn_Separate, separate_lines)
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if arrow_size > 0.0:
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for line in separate_lines:
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for i in range(len(line)-1):
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self._arrow(ax, line[i], line[i+1], color, alpha, arrow_size)
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if point_color is not None:
|
|
for line in separate_lines:
|
|
start_index = 0
|
|
end_index = len(line)
|
|
if start_point_color is not None:
|
|
ax.plot(line[0, 0], line[0, 1], "o", c=start_point_color, alpha=alpha)
|
|
start_index = 1
|
|
if line[0][0] == line[-1][0] and line[0][1] == line[-1][1]:
|
|
end_index -= 1
|
|
ax.plot(line[start_index:end_index, 0], line[start_index:end_index, 1], "o",
|
|
c=color, alpha=alpha)
|
|
|
|
def point_numbers(
|
|
self,
|
|
x: ArrayLike,
|
|
y: ArrayLike,
|
|
z: ArrayLike,
|
|
ax: Axes | int = 0,
|
|
color: str = "red",
|
|
) -> None:
|
|
ax = self._get_ax(ax)
|
|
x, y = self._grid_as_2d(x, y)
|
|
z = np.asarray(z)
|
|
ny, nx = z.shape
|
|
for j in range(ny):
|
|
for i in range(nx):
|
|
quad = i + j*nx
|
|
ax.text(x[j, i], y[j, i], str(quad), ha="right", va="top", color=color,
|
|
clip_on=True)
|
|
|
|
def quad_numbers(
|
|
self,
|
|
x: ArrayLike,
|
|
y: ArrayLike,
|
|
z: ArrayLike,
|
|
ax: Axes | int = 0,
|
|
color: str = "blue",
|
|
) -> None:
|
|
ax = self._get_ax(ax)
|
|
x, y = self._grid_as_2d(x, y)
|
|
z = np.asarray(z)
|
|
ny, nx = z.shape
|
|
for j in range(1, ny):
|
|
for i in range(1, nx):
|
|
quad = i + j*nx
|
|
xmid = x[j-1:j+1, i-1:i+1].mean()
|
|
ymid = y[j-1:j+1, i-1:i+1].mean()
|
|
ax.text(xmid, ymid, str(quad), ha="center", va="center", color=color, clip_on=True)
|
|
|
|
def z_levels(
|
|
self,
|
|
x: ArrayLike,
|
|
y: ArrayLike,
|
|
z: ArrayLike,
|
|
lower_level: float,
|
|
upper_level: float | None = None,
|
|
ax: Axes | int = 0,
|
|
color: str = "green",
|
|
) -> None:
|
|
ax = self._get_ax(ax)
|
|
x, y = self._grid_as_2d(x, y)
|
|
z = np.asarray(z)
|
|
ny, nx = z.shape
|
|
for j in range(ny):
|
|
for i in range(nx):
|
|
zz = z[j, i]
|
|
if upper_level is not None and zz > upper_level:
|
|
z_level = 2
|
|
elif zz > lower_level:
|
|
z_level = 1
|
|
else:
|
|
z_level = 0
|
|
ax.text(x[j, i], y[j, i], str(z_level), ha="left", va="bottom", color=color,
|
|
clip_on=True)
|