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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 import FillType, LineType
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 contourpy._contourpy import FillReturn, LineReturn
class BokehRenderer(Renderer):
_figures: list[figure]
_layout: GridPlot
_palette: Palette
_want_svg: bool
"""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:`~contourpy.util.bokeh_renderer.BokehRenderer`, unlike
:class:`~contourpy.util.mpl_renderer.MplRenderer`, needs to be told in advance if output to
SVG format will be required later, otherwise it will assume PNG output.
"""
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
def filled(
self,
filled: FillReturn,
fill_type: FillType,
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
:func:`~contourpy.ContourGenerator.filled`.
fill_type (FillType): Type of ``filled`` data, as returned by
:attr:`~contourpy.ContourGenerator.fill_type`.
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``.
"""
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)
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 = [row for row in x] + [row for row in x.T]
ys = [row for row in y] + [row for row in y.T]
kwargs = dict(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(
[row for row in np.stack((x[:-1, :-1].ravel(), xmid, x[1:, 1:].ravel()), axis=1)],
[row for row in np.stack((y[:-1, :-1].ravel(), ymid, y[1:, 1:].ravel()), axis=1)],
**kwargs)
fig.multi_line(
[row for row in np.stack((x[:-1, 1:].ravel(), xmid, x[1:, :-1].ravel()), axis=1)],
[row for row in 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)
def lines(
self,
lines: LineReturn,
line_type: LineType,
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
:func:`~contourpy.ContourGenerator.lines`.
line_type (LineType): Type of ``lines`` data, as returned by
:attr:`~contourpy.ContourGenerator.line_type`.
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.
"""
fig = self._get_figure(ax)
color = self._convert_color(color)
xs, ys = lines_to_bokeh(lines, line_type)
if len(xs) > 0:
fig.multi_line(xs, ys, line_color=color, line_alpha=alpha, line_width=linewidth)
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)
def save(self, filename: str, transparent: bool = False) -> 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``.
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)
else:
export_png(self._layout, filename=filename)
def save_to_buffer(self) -> io.BytesIO:
"""Save plots to an ``io.BytesIO`` buffer.
Return:
BytesIO: PNG image buffer.
"""
image = get_screenshot_as_png(self._layout)
buffer = io.BytesIO()
image.save(buffer, "png")
return buffer
def show(self) -> None:
"""Show plots in web browser, in usual Bokeh manner.
"""
show(self._layout)
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]
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 = dict(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))
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