Source code for contourpy.util.bokeh_renderer

from __future__ import annotations

import io
from typing import TYPE_CHECKING, Any

from bokeh.io import export_png, export_svg, show
from bokeh.io.export import get_screenshot_as_png
from bokeh.layouts import gridplot
from bokeh.models.annotations.labels import Label
from bokeh.palettes import Category10
from bokeh.plotting import figure
import numpy as np

from contourpy.enum_util import as_fill_type, as_line_type
from contourpy.util.bokeh_util import filled_to_bokeh, lines_to_bokeh
from contourpy.util.renderer import Renderer

if TYPE_CHECKING:
    from bokeh.models import GridPlot
    from bokeh.palettes import Palette
    from numpy.typing import ArrayLike
    from selenium.webdriver.remote.webdriver import WebDriver

    from contourpy import FillType, LineType
    from contourpy._contourpy import FillReturn, LineReturn


[docs] class BokehRenderer(Renderer): """Utility renderer using Bokeh to render a grid of plots over the same (x, y) range. Args: nrows (int, optional): Number of rows of plots, default ``1``. ncols (int, optional): Number of columns of plots, default ``1``. figsize (tuple(float, float), optional): Figure size in inches (assuming 100 dpi), default ``(9, 9)``. show_frame (bool, optional): Whether to show frame and axes ticks, default ``True``. want_svg (bool, optional): Whether output is required in SVG format or not, default ``False``. Warning: :class:`~.BokehRenderer`, unlike :class:`~.MplRenderer`, needs to be told in advance if output to SVG format will be required later, otherwise it will assume PNG output. """ _figures: list[figure] _layout: GridPlot _palette: Palette _want_svg: bool def __init__( self, nrows: int = 1, ncols: int = 1, figsize: tuple[float, float] = (9, 9), show_frame: bool = True, want_svg: bool = False, ) -> None: self._want_svg = want_svg self._palette = Category10[10] total_size = 100*np.asarray(figsize, dtype=int) # Assuming 100 dpi. nfigures = nrows*ncols self._figures = [] backend = "svg" if self._want_svg else "canvas" for _ in range(nfigures): fig = figure(output_backend=backend) fig.xgrid.visible = False fig.ygrid.visible = False self._figures.append(fig) if not show_frame: fig.outline_line_color = None # type: ignore[assignment] fig.axis.visible = False self._layout = gridplot( self._figures, ncols=ncols, toolbar_location=None, # type: ignore[arg-type] width=total_size[0] // ncols, height=total_size[1] // nrows) def _convert_color(self, color: str) -> str: if isinstance(color, str) and color[0] == "C": index = int(color[1:]) color = self._palette[index] return color def _get_figure(self, ax: figure | int) -> figure: if isinstance(ax, int): ax = self._figures[ax] return ax
[docs] def filled( self, filled: FillReturn, fill_type: FillType | str, ax: figure | int = 0, color: str = "C0", alpha: float = 0.7, ) -> None: """Plot filled contours on a single plot. Args: filled (sequence of arrays): Filled contour data as returned by :meth:`~.ContourGenerator.filled`. fill_type (FillType or str): Type of :meth:`~.ContourGenerator.filled` data as returned by :attr:`~.ContourGenerator.fill_type`, or a string equivalent. ax (int or Bokeh Figure, optional): Which plot to use, default ``0``. color (str, optional): Color to plot with. May be a string color or the letter ``"C"`` followed by an integer in the range ``"C0"`` to ``"C9"`` to use a color from the ``Category10`` palette. Default ``"C0"``. alpha (float, optional): Opacity to plot with, default ``0.7``. """ fill_type = as_fill_type(fill_type) fig = self._get_figure(ax) color = self._convert_color(color) xs, ys = filled_to_bokeh(filled, fill_type) if len(xs) > 0: fig.multi_polygons(xs=[xs], ys=[ys], color=color, fill_alpha=alpha, line_width=0)
[docs] def grid( self, x: ArrayLike, y: ArrayLike, ax: figure | int = 0, color: str = "black", alpha: float = 0.1, point_color: str | None = None, quad_as_tri_alpha: float = 0, ) -> None: """Plot quad grid lines on a single plot. Args: x (array-like of shape (ny, nx) or (nx,)): The x-coordinates of the grid points. y (array-like of shape (ny, nx) or (ny,)): The y-coordinates of the grid points. ax (int or Bokeh Figure, optional): Which plot to use, default ``0``. color (str, optional): Color to plot grid lines, default ``"black"``. alpha (float, optional): Opacity to plot lines with, default ``0.1``. point_color (str, optional): Color to plot grid points or ``None`` if grid points should not be plotted, default ``None``. quad_as_tri_alpha (float, optional): Opacity to plot ``quad_as_tri`` grid, default ``0``. Colors may be a string color or the letter ``"C"`` followed by an integer in the range ``"C0"`` to ``"C9"`` to use a color from the ``Category10`` palette. Warning: ``quad_as_tri_alpha > 0`` plots all quads as though they are unmasked. """ fig = self._get_figure(ax) x, y = self._grid_as_2d(x, y) xs = list(x) + list(x.T) ys = list(y) + list(y.T) kwargs = {"line_color": color, "alpha": alpha} fig.multi_line(xs, ys, **kwargs) if quad_as_tri_alpha > 0: # Assumes no quad mask. xmid = (0.25*(x[:-1, :-1] + x[1:, :-1] + x[:-1, 1:] + x[1:, 1:])).ravel() ymid = (0.25*(y[:-1, :-1] + y[1:, :-1] + y[:-1, 1:] + y[1:, 1:])).ravel() fig.multi_line( list(np.stack((x[:-1, :-1].ravel(), xmid, x[1:, 1:].ravel()), axis=1)), list(np.stack((y[:-1, :-1].ravel(), ymid, y[1:, 1:].ravel()), axis=1)), **kwargs) fig.multi_line( list(np.stack((x[:-1, 1:].ravel(), xmid, x[1:, :-1].ravel()), axis=1)), list(np.stack((y[:-1, 1:].ravel(), ymid, y[1:, :-1].ravel()), axis=1)), **kwargs) if point_color is not None: fig.circle( x=x.ravel(), y=y.ravel(), fill_color=color, line_color=None, alpha=alpha, size=8)
[docs] def lines( self, lines: LineReturn, line_type: LineType | str, ax: figure | int = 0, color: str = "C0", alpha: float = 1.0, linewidth: float = 1, ) -> None: """Plot contour lines on a single plot. Args: lines (sequence of arrays): Contour line data as returned by :meth:`~.ContourGenerator.lines`. line_type (LineType or str): Type of :meth:`~.ContourGenerator.lines` data as returned by :attr:`~.ContourGenerator.line_type`, or a string equivalent. ax (int or Bokeh Figure, optional): Which plot to use, default ``0``. color (str, optional): Color to plot lines. May be a string color or the letter ``"C"`` followed by an integer in the range ``"C0"`` to ``"C9"`` to use a color from the ``Category10`` palette. Default ``"C0"``. alpha (float, optional): Opacity to plot lines with, default ``1.0``. linewidth (float, optional): Width of lines, default ``1``. Note: Assumes all lines are open line strips not closed line loops. """ line_type = as_line_type(line_type) fig = self._get_figure(ax) color = self._convert_color(color) xs, ys = lines_to_bokeh(lines, line_type) if xs is not None: fig.line(xs, ys, line_color=color, line_alpha=alpha, line_width=linewidth)
[docs] def mask( self, x: ArrayLike, y: ArrayLike, z: ArrayLike | np.ma.MaskedArray[Any, Any], ax: figure | int = 0, color: str = "black", ) -> None: """Plot masked out grid points as circles on a single plot. Args: x (array-like of shape (ny, nx) or (nx,)): The x-coordinates of the grid points. y (array-like of shape (ny, nx) or (ny,)): The y-coordinates of the grid points. z (masked array of shape (ny, nx): z-values. ax (int or Bokeh Figure, optional): Which plot to use, default ``0``. color (str, optional): Circle color, default ``"black"``. """ mask = np.ma.getmask(z) # type: ignore[no-untyped-call] if mask is np.ma.nomask: return fig = self._get_figure(ax) color = self._convert_color(color) x, y = self._grid_as_2d(x, y) fig.circle(x[mask], y[mask], fill_color=color, size=10)
[docs] def save( self, filename: str, transparent: bool = False, *, webdriver: WebDriver | None = None, ) -> None: """Save plots to SVG or PNG file. Args: filename (str): Filename to save to. transparent (bool, optional): Whether background should be transparent, default ``False``. webdriver (WebDriver, optional): Selenium WebDriver instance to use to create the image. .. versionadded:: 1.1.1 Warning: To output to SVG file, ``want_svg=True`` must have been passed to the constructor. """ if transparent: for fig in self._figures: fig.background_fill_color = None # type: ignore[assignment] fig.border_fill_color = None # type: ignore[assignment] if self._want_svg: export_svg(self._layout, filename=filename, webdriver=webdriver) else: export_png(self._layout, filename=filename, webdriver=webdriver)
[docs] def save_to_buffer(self, *, webdriver: WebDriver | None = None) -> io.BytesIO: """Save plots to an ``io.BytesIO`` buffer. Args: webdriver (WebDriver, optional): Selenium WebDriver instance to use to create the image. .. versionadded:: 1.1.1 Return: BytesIO: PNG image buffer. """ image = get_screenshot_as_png(self._layout, driver=webdriver) buffer = io.BytesIO() image.save(buffer, "png") return buffer
[docs] def show(self) -> None: """Show plots in web browser, in usual Bokeh manner. """ show(self._layout)
[docs] def title(self, title: str, ax: figure | int = 0, color: str | None = None) -> None: """Set the title of a single plot. Args: title (str): Title text. ax (int or Bokeh Figure, optional): Which plot to set the title of, default ``0``. color (str, optional): Color to set title. May be a string color or the letter ``"C"`` followed by an integer in the range ``"C0"`` to ``"C9"`` to use a color from the ``Category10`` palette. Default ``None`` which is ``black``. """ fig = self._get_figure(ax) fig.title = title # type: ignore[assignment] fig.title.align = "center" # type: ignore[attr-defined] if color is not None: fig.title.text_color = self._convert_color(color) # type: ignore[attr-defined]
[docs] def z_values( self, x: ArrayLike, y: ArrayLike, z: ArrayLike, ax: figure | int = 0, color: str = "green", fmt: str = ".1f", quad_as_tri: bool = False, ) -> None: """Show ``z`` values on a single plot. Args: x (array-like of shape (ny, nx) or (nx,)): The x-coordinates of the grid points. y (array-like of shape (ny, nx) or (ny,)): The y-coordinates of the grid points. z (array-like of shape (ny, nx): z-values. ax (int or Bokeh Figure, optional): Which plot to use, default ``0``. color (str, optional): Color of added text. May be a string color or the letter ``"C"`` followed by an integer in the range ``"C0"`` to ``"C9"`` to use a color from the ``Category10`` palette. Default ``"green"``. fmt (str, optional): Format to display z-values, default ``".1f"``. quad_as_tri (bool, optional): Whether to show z-values at the ``quad_as_tri`` centres of quads. Warning: ``quad_as_tri=True`` shows z-values for all quads, even if masked. """ fig = self._get_figure(ax) color = self._convert_color(color) x, y = self._grid_as_2d(x, y) z = np.asarray(z) ny, nx = z.shape kwargs = {"text_color": color, "text_align": "center", "text_baseline": "middle"} for j in range(ny): for i in range(nx): fig.add_layout(Label(x=x[j, i], y=y[j, i], text=f"{z[j, i]:{fmt}}", **kwargs)) if quad_as_tri: for j in range(ny-1): for i in range(nx-1): xx = np.mean(x[j:j+2, i:i+2]) yy = np.mean(y[j:j+2, i:i+2]) zz = np.mean(z[j:j+2, i:i+2]) fig.add_layout(Label(x=xx, y=yy, text=f"{zz:{fmt}}", **kwargs))