337 lines
13 KiB
Python
337 lines
13 KiB
Python
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from __future__ import annotations
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import io
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from typing import TYPE_CHECKING, Any
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from bokeh.io import export_png, export_svg, show
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from bokeh.io.export import get_screenshot_as_png
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from bokeh.layouts import gridplot
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from bokeh.models.annotations.labels import Label
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from bokeh.palettes import Category10
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from bokeh.plotting import figure
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import numpy as np
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from contourpy.enum_util import as_fill_type, as_line_type
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from contourpy.util.bokeh_util import filled_to_bokeh, lines_to_bokeh
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from contourpy.util.renderer import Renderer
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if TYPE_CHECKING:
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from bokeh.models import GridPlot
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from bokeh.palettes import Palette
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from numpy.typing import ArrayLike
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from selenium.webdriver.remote.webdriver import WebDriver
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from contourpy import FillType, LineType
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from contourpy._contourpy import FillReturn, LineReturn
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class BokehRenderer(Renderer):
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"""Utility renderer using Bokeh 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 (assuming 100 dpi), default
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``(9, 9)``.
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show_frame (bool, optional): Whether to show frame and axes ticks, default ``True``.
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want_svg (bool, optional): Whether output is required in SVG format or not, default
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``False``.
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Warning:
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:class:`~contourpy.util.bokeh_renderer.BokehRenderer`, unlike
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:class:`~contourpy.util.mpl_renderer.MplRenderer`, needs to be told in advance if output to
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SVG format will be required later, otherwise it will assume PNG output.
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"""
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_figures: list[figure]
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_layout: GridPlot
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_palette: Palette
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_want_svg: 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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want_svg: bool = False,
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) -> None:
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self._want_svg = want_svg
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self._palette = Category10[10]
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total_size = 100*np.asarray(figsize, dtype=int) # Assuming 100 dpi.
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nfigures = nrows*ncols
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self._figures = []
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backend = "svg" if self._want_svg else "canvas"
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for _ in range(nfigures):
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fig = figure(output_backend=backend)
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fig.xgrid.visible = False
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fig.ygrid.visible = False
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self._figures.append(fig)
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if not show_frame:
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fig.outline_line_color = None # type: ignore[assignment]
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fig.axis.visible = False
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self._layout = gridplot(
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self._figures, ncols=ncols, toolbar_location=None, # type: ignore[arg-type]
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width=total_size[0] // ncols, height=total_size[1] // nrows)
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def _convert_color(self, color: str) -> str:
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if isinstance(color, str) and color[0] == "C":
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index = int(color[1:])
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color = self._palette[index]
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return color
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def _get_figure(self, ax: figure | int) -> figure:
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if isinstance(ax, int):
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ax = self._figures[ax]
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return ax
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def filled(
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self,
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filled: FillReturn,
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fill_type: FillType | str,
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ax: figure | 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 plot.
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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 a string equivalent.
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ax (int or Bokeh Figure, optional): Which plot to use, 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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``Category10`` palette. 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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fig = self._get_figure(ax)
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color = self._convert_color(color)
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xs, ys = filled_to_bokeh(filled, fill_type)
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if len(xs) > 0:
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fig.multi_polygons(xs=[xs], ys=[ys], color=color, fill_alpha=alpha, line_width=0)
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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: figure | 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 plot.
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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 Bokeh Figure, optional): Which plot to use, 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
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``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 ``Category10`` palette.
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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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fig = self._get_figure(ax)
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x, y = self._grid_as_2d(x, y)
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xs = list(x) + list(x.T)
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ys = list(y) + list(y.T)
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kwargs = {"line_color": color, "alpha": alpha}
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fig.multi_line(xs, ys, **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:])).ravel()
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ymid = (0.25*(y[:-1, :-1] + y[1:, :-1] + y[:-1, 1:] + y[1:, 1:])).ravel()
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fig.multi_line(
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list(np.stack((x[:-1, :-1].ravel(), xmid, x[1:, 1:].ravel()), axis=1)),
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list(np.stack((y[:-1, :-1].ravel(), ymid, y[1:, 1:].ravel()), axis=1)),
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**kwargs)
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fig.multi_line(
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list(np.stack((x[:-1, 1:].ravel(), xmid, x[1:, :-1].ravel()), axis=1)),
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list(np.stack((y[:-1, 1:].ravel(), ymid, y[1:, :-1].ravel()), axis=1)),
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**kwargs)
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if point_color is not None:
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fig.circle(
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x=x.ravel(), y=y.ravel(), fill_color=color, line_color=None, alpha=alpha, size=8)
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def lines(
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self,
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lines: LineReturn,
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line_type: LineType | str,
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ax: figure | 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 plot.
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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 a string equivalent.
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ax (int or Bokeh Figure, optional): Which plot to use, 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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``Category10`` palette. 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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Note:
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Assumes all lines are open line strips not closed line loops.
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"""
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line_type = as_line_type(line_type)
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fig = self._get_figure(ax)
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color = self._convert_color(color)
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xs, ys = lines_to_bokeh(lines, line_type)
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if xs is not None:
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fig.line(xs, ys, line_color=color, line_alpha=alpha, line_width=linewidth)
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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: figure | 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 plot.
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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 Bokeh Figure, optional): Which plot to use, 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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fig = self._get_figure(ax)
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color = self._convert_color(color)
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x, y = self._grid_as_2d(x, y)
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fig.circle(x[mask], y[mask], fill_color=color, size=10)
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def save(
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self,
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filename: str,
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transparent: bool = False,
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*,
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webdriver: WebDriver | None = None,
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) -> 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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webdriver (WebDriver, optional): Selenium WebDriver instance to use to create the image.
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.. versionadded:: 1.1.1
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Warning:
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To output to SVG file, ``want_svg=True`` must have been passed to the constructor.
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"""
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if transparent:
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for fig in self._figures:
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fig.background_fill_color = None # type: ignore[assignment]
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fig.border_fill_color = None # type: ignore[assignment]
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if self._want_svg:
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export_svg(self._layout, filename=filename, webdriver=webdriver)
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else:
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export_png(self._layout, filename=filename, webdriver=webdriver)
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def save_to_buffer(self, *, webdriver: WebDriver | None = None) -> io.BytesIO:
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"""Save plots to an ``io.BytesIO`` buffer.
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Args:
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webdriver (WebDriver, optional): Selenium WebDriver instance to use to create the image.
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.. versionadded:: 1.1.1
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Return:
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BytesIO: PNG image buffer.
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"""
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image = get_screenshot_as_png(self._layout, driver=webdriver)
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buffer = io.BytesIO()
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image.save(buffer, "png")
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return buffer
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def show(self) -> None:
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"""Show plots in web browser, in usual Bokeh manner.
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"""
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show(self._layout)
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def title(self, title: str, ax: figure | int = 0, color: str | None = None) -> None:
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"""Set the title of a single plot.
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Args:
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title (str): Title text.
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ax (int or Bokeh Figure, optional): Which plot 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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``Category10`` palette. Default ``None`` which is ``black``.
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"""
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fig = self._get_figure(ax)
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fig.title = title # type: ignore[assignment]
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fig.title.align = "center" # type: ignore[attr-defined]
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if color is not None:
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fig.title.text_color = self._convert_color(color) # type: ignore[attr-defined]
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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: figure | 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 plot.
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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 Bokeh Figure, optional): Which plot to use, 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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``Category10`` palette. 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`` centres
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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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fig = self._get_figure(ax)
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color = self._convert_color(color)
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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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kwargs = {"text_color": color, "text_align": "center", "text_baseline": "middle"}
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for j in range(ny):
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for i in range(nx):
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fig.add_layout(Label(x=x[j, i], y=y[j, i], text=f"{z[j, i]:{fmt}}", **kwargs))
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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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fig.add_layout(Label(x=xx, y=yy, text=f"{zz:{fmt}}", **kwargs))
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