Question

绘制具有不同斜率的多条对角线的图。我想用一个与行斜率相匹配的文本标签来注释这些行。

这样的事情：

Annotated line

有没有一种强有力的方法可以做到这一点？

我已经尝试了text和annotate的旋转参数，但这些参数都是屏幕坐标，而不是数据坐标（即屏幕上始终为x度重要的是xy范围）。我的x和y范围相差几个数量级，显然，明显的斜率受视口大小和其他变量的影响，因此固定度旋转不起作用。还有其他想法吗？

Answer 1

我想出了一些对我有用的东西。请注意灰色虚线：

annotated lines

必须手动设置旋转，但必须在draw()或布局后完成。所以我的解决方案是将行与注释相关联，然后遍历它们并执行此操作：

获取行的数据变换（即从数据坐标到显示坐标）
沿线变换两个点以显示坐标
找到显示行的斜率
设置文字旋转以匹配此斜率

这并不完美，因为matplotlib对旋转文本的处理都是错误的。它通过边界框而不是文本基线对齐。

如果您对文字呈现感兴趣，请参阅一些字体基础知识：http://docs.oracle.com/javase/tutorial/2d/text/fontconcepts.html

此示例显示了matplotlib的作用：http://matplotlib.org/examples/pylab_examples/text_rotation.html

我发现在线旁边有正确标签的唯一方法是在垂直和水平方向上按中心对齐。然后我将标签向左偏移10点，使其不重叠。足以满足我的申请。

这是我的代码。我绘制了我想要的线条，然后绘制注释，然后用辅助函数绑定它们：

line, = fig.plot(xdata, ydata, '--', color=color)

# x,y appear on the midpoint of the line

t = fig.annotate("text", xy=(x, y), xytext=(-10, 0), textcoords='offset points', horizontalalignment='left', verticalalignment='bottom', color=color)
text_slope_match_line(t, x, y, line)

然后在布局之后但在savefig之前调用另一个辅助函数（对于交互式图像，我认为你必须注册绘制事件并在处理程序中调用update_text_slopes）

plt.tight_layout()
update_text_slopes()

助手：

rotated_labels = []
def text_slope_match_line(text, x, y, line):
    global rotated_labels

    # find the slope
    xdata, ydata = line.get_data()

    x1 = xdata[0]
    x2 = xdata[-1]
    y1 = ydata[0]
    y2 = ydata[-1]

    rotated_labels.append({"text":text, "line":line, "p1":numpy.array((x1, y1)), "p2":numpy.array((x2, y2))})

def update_text_slopes():
    global rotated_labels

    for label in rotated_labels:
        # slope_degrees is in data coordinates, the text() and annotate() functions need it in screen coordinates
        text, line = label["text"], label["line"]
        p1, p2 = label["p1"], label["p2"]

        # get the line's data transform
        ax = line.get_axes()

        sp1 = ax.transData.transform_point(p1)
        sp2 = ax.transData.transform_point(p2)

        rise = (sp2[1] - sp1[1])
        run = (sp2[0] - sp1[0])

        slope_degrees = math.degrees(math.atan(rise/run))

        text.set_rotation(slope_degrees)

Answer 2

这与@Adam给出的完全相同的过程和基本代码---它只是重组（希望）更方便一点。

def label_line(line, label, x, y, color='0.5', size=12):
    """Add a label to a line, at the proper angle.

    Arguments
    ---------
    line : matplotlib.lines.Line2D object,
    label : str
    x : float
        x-position to place center of text (in data coordinated
    y : float
        y-position to place center of text (in data coordinates)
    color : str
    size : float
    """
    xdata, ydata = line.get_data()
    x1 = xdata[0]
    x2 = xdata[-1]
    y1 = ydata[0]
    y2 = ydata[-1]

    ax = line.get_axes()
    text = ax.annotate(label, xy=(x, y), xytext=(-10, 0),
                       textcoords='offset points',
                       size=size, color=color,
                       horizontalalignment='left',
                       verticalalignment='bottom')

    sp1 = ax.transData.transform_point((x1, y1))
    sp2 = ax.transData.transform_point((x2, y2))

    rise = (sp2[1] - sp1[1])
    run = (sp2[0] - sp1[0])

    slope_degrees = np.degrees(np.arctan2(rise, run))
    text.set_rotation(slope_degrees)
    return text

用过：

import numpy as np
import matplotlib.pyplot as plt

...
fig, axes = plt.subplots()
color = 'blue'
line, = axes.plot(xdata, ydata, '--', color=color)
...
label_line(line, "Some Label", x, y, color=color)

编辑：请注意，在图形布局完成后，仍然需要调用此方法，否则会有所改变。

请参阅：https://gist.github.com/lzkelley/0de9e8bf2a4fe96d2018f1b1bd5a0d3c

Answer 3

即使这个问题很老，我仍会不断遇到这个问题并感到沮丧，因为它并不奏效。我将其重新制作为LineAnnotation类和辅助对象line_annotate，以使它

使用特定点x上的斜率，
可以重新布局和调整大小，并且
接受垂直于坡度的相对偏移。

x = np.linspace(np.pi, 2*np.pi)
line, = plt.plot(x, np.sin(x))

for x in [3.5, 4.0, 4.5, 5.0, 5.5, 6.0]:
    line_annotate(str(x), line, x)

我最初将其放入public gist中，但是@Adam要求我将其包括在这里。

import numpy as np
from matplotlib.text import Annotation
from matplotlib.transforms import Affine2D


class LineAnnotation(Annotation):
    """A sloped annotation to *line* at position *x* with *text*
    Optionally an arrow pointing from the text to the graph at *x* can be drawn.
    Usage
    -----
    fig, ax = subplots()
    x = linspace(0, 2*pi)
    line, = ax.plot(x, sin(x))
    ax.add_artist(LineAnnotation("text", line, 1.5))
    """

    def __init__(
        self, text, line, x, xytext=(0, 5), textcoords="offset points", **kwargs
    ):
        """Annotate the point at *x* of the graph *line* with text *text*.

        By default, the text is displayed with the same rotation as the slope of the
        graph at a relative position *xytext* above it (perpendicularly above).

        An arrow pointing from the text to the annotated point *xy* can
        be added by defining *arrowprops*.

        Parameters
        ----------
        text : str
            The text of the annotation.
        line : Line2D
            Matplotlib line object to annotate
        x : float
            The point *x* to annotate. y is calculated from the points on the line.
        xytext : (float, float), default: (0, 5)
            The position *(x, y)* relative to the point *x* on the *line* to place the
            text at. The coordinate system is determined by *textcoords*.
        **kwargs
            Additional keyword arguments are passed on to `Annotation`.

        See also
        --------
        `Annotation`
        `line_annotate`
        """
        assert textcoords.startswith(
            "offset "
        ), "*textcoords* must be 'offset points' or 'offset pixels'"

        self.line = line
        self.xytext = xytext

        # Determine points of line immediately to the left and right of x
        xs, ys = line.get_data()

        def neighbours(x, xs, ys, try_invert=True):
            inds, = np.where((xs <= x)[:-1] & (xs > x)[1:])
            if len(inds) == 0:
                assert try_invert, "line must cross x"
                return neighbours(x, xs[::-1], ys[::-1], try_invert=False)

            i = inds[0]
            return np.asarray([(xs[i], ys[i]), (xs[i+1], ys[i+1])])
        
        self.neighbours = n1, n2 = neighbours(x, xs, ys)
        
        # Calculate y by interpolating neighbouring points
        y = n1[1] + ((x - n1[0]) * (n2[1] - n1[1]) / (n2[0] - n1[0]))

        kwargs = {
            "horizontalalignment": "center",
            "rotation_mode": "anchor",
            **kwargs,
        }
        super().__init__(text, (x, y), xytext=xytext, textcoords=textcoords, **kwargs)

    def get_rotation(self):
        """Determines angle of the slope of the neighbours in display coordinate system
        """
        transData = self.line.get_transform()
        dx, dy = np.diff(transData.transform(self.neighbours), axis=0).squeeze()
        return np.rad2deg(np.arctan2(dy, dx))

    def update_positions(self, renderer):
        """Updates relative position of annotation text
        Note
        ----
        Called during annotation `draw` call
        """
        xytext = Affine2D().rotate_deg(self.get_rotation()).transform(self.xytext)
        self.set_position(xytext)
        super().update_positions(renderer)


def line_annotate(text, line, x, *args, **kwargs):
    """Add a sloped annotation to *line* at position *x* with *text*

    Optionally an arrow pointing from the text to the graph at *x* can be drawn.

    Usage
    -----
    x = linspace(0, 2*pi)
    line, = ax.plot(x, sin(x))
    line_annotate("sin(x)", line, 1.5)

    See also
    --------
    `LineAnnotation`
    `plt.annotate`
    """
    ax = line.axes
    a = LineAnnotation(text, line, x, *args, **kwargs)
    if "clip_on" in kwargs:
        a.set_clip_path(ax.patch)
    ax.add_artist(a)
    return a

如何旋转matplotlib注释以匹配一条线？

3 个答案: