如何绘制温度计? [英] How to plot a thermometer?

问题描述

在最近非常广泛的

此外，这种字体符号的颜色是统一的，但理想情况下，温度计的内部(水银柱")应该是不同的颜色(出于联想的原因，可能主要是红色)或不同的颜色，以便也可以用颜色对温度进行编码.

那么可能有一个温度符号，其中汞柱根据颜色和填充水平编码温度(或实际上任何其他量)?如果可以，怎么办?

(我在下面给出了答案，欢迎对该方法的替代或改进作为进一步的答案.)

解决方案

绘制由两部分组成的温度计的一种方法是创建两个 Path ，分别是外壳和内部汞柱.为此，可以从头开始创建路径，并允许内部路径根据(规范化的)输入参数而变化.

然后可以将两个路径绘制为单独的散点图.在下面的代码中，我们创建一个具有 scatter 方法的类，该方法的工作原理与常见的

或者我们可以使用颜色(c)和temp来显示温度，如

np.random.seed(42)无花果，ax = plt.subplots()n = 42x = np.linspace(0,100,n)y = np.cumsum(np.random.randn(n))+5ax.plot(x,y, color="darkgrey", lw=2.5)p = 温度图()p.scatter(x[::4],y[::4]+3, s=300, temp=y[::4], c=y[::4], edgecolor="k", cmap="RdYlBu_r")ax.set_ylim(-6,18)plt.show()

In a recent, very broad question it was asked how to plot several symbols, like "circles, squares, rectangles, stars, thermometers, and boxplots" with matplotlib. From that list, all but thermometers are obvious as either shown in the documentation or in many existing stackoverflow answers. Since the OP did not seem interested in thermomenters at all, I'd rather ask a new question specifically about thermometers here.

How to plot thermometers in matplotlib?

In principle you can plot any symbol you like, making it either a marker or a Path. There does not seem to be any unicode symbol for thermometers though. Font awesome has a thermometer symbol and plotting FontAwesome symbols in matplotlib is possible. Yet there are only 5 differnt fillings

Also, the color of such font symbol is uniform, yet ideally one would have the inner part of a thermometer (the "mercury pillar") in a different color (probably mostly red for associative reasons) or in different colors as to encode temperature in color as well.

So is it possible to have a temperature symbol where the mercury pillar encodes temperature (or in fact any other quantity) in terms of color and filling level? And if so, how?

(I gave an answer below, alternatives to or improvements of that method are welcome as further answers here.)

解决方案

An option to plot a thermometer consisting of two parts is to create two Paths, the outer hull and the inner mercury pillar. For this one can create the Paths from scratch and allow the inner path to be variable depending on a (normalized) input parameter.

Then plotting both paths as individual scatter plots is possible. In the following, we create a class that has a scatter method, which works similar to a usual scatter, except that it would also take the additional arguments temp for the temperature and tempnorm for the normalization of the temperature as input.

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.path as mpath

class TemperaturePlot():

    @staticmethod
    def get_hull():
        verts1 = np.array([[0,-128],[70,-128],[128,-70],[128,0],
                          [128,32.5],[115.8,61.5],[96,84.6],[96,288],
                          [96,341],[53,384],[0,384]])
        verts2 = verts1[:-1,:] * np.array([-1,1])
        codes1 = [1,4,4,4,4,4,4,2,4,4,4]
        verts3 = np.array([[0,-80],[44,-80],[80,-44],[80,0],
                          [80,34.3],[60.7,52],[48,66.5],[48,288],
                          [48,314],[26.5,336],[0,336]])
        verts4 = verts3[:-1,:] * np.array([-1,1])
        verts = np.concatenate((verts1, verts2[::-1], verts4, verts3[::-1]))
        codes = codes1 + codes1[::-1][:-1]
        return mpath.Path(verts/256., codes+codes)

    @staticmethod
    def get_mercury(s=1):
        a = 0; b = 64; c = 35
        d = 320 - b
        e = (1-s)*d
        verts1 = np.array([[a,-b],[c,-b],[b,-c],[b,a],[b,c],[c,b],[a,b]])
        verts2 = verts1[:-1,:] * np.array([-1,1])
        verts3 = np.array([[0,0],[32,0],[32,288-e],[32,305-e],
                           [17.5,320-e],[0,320-e]])
        verts4 = verts3[:-1,:] * np.array([-1,1])
        codes = [1] + [4]*12 + [1,2,2,4,4,4,4,4,4,2,2]
        verts = np.concatenate((verts1, verts2[::-1], verts3, verts4[::-1]))
        return mpath.Path(verts/256., codes)

    def scatter(self, x,y, temp=1, tempnorm=None, ax=None, **kwargs):
        self.ax = ax or plt.gca()
        temp = np.atleast_1d(temp)
        ec = kwargs.pop("edgecolor", "black")
        kwargs.update(linewidth=0)
        self.inner = self.ax.scatter(x,y, **kwargs)
        kwargs.update(c=None, facecolor=ec, edgecolor=None, color=None)
        self.outer = self.ax.scatter(x,y, **kwargs)
        self.outer.set_paths([self.get_hull()])
        if not tempnorm:
            mi, ma = np.nanmin(temp), np.nanmax(temp)
            if mi == ma:
                mi=0
            tempnorm = plt.Normalize(mi,ma)
        ipaths = [self.get_mercury(tempnorm(t)) for t in temp]
        self.inner.set_paths(ipaths)

Usage of this class could look like this,

plt.rcParams["figure.figsize"] = (5.5,3) 
plt.rcParams["figure.dpi"] = 72*3

fig, ax = plt.subplots()
p = TemperaturePlot()
p.scatter([.25,.5,.75], [.3,.4,.5], s=[800,1200,1600], temp=[28,39,35], color="C3",
          ax=ax, transform=ax.transAxes)

plt.show()

where we plot 3 Thermometers with different temperatures depicted by the fill of the "mercury" pillar. Since no normalization is given it will normalize the temperatures of [28,39,35] between their minimum and maximum.

Or we can use color (c) and temp to show the temparature as in

np.random.seed(42)
fig, ax = plt.subplots()
n = 42
x = np.linspace(0,100,n)
y = np.cumsum(np.random.randn(n))+5

ax.plot(x,y, color="darkgrey", lw=2.5)

p = TemperaturePlot()
p.scatter(x[::4],y[::4]+3, s=300, temp=y[::4], c=y[::4], edgecolor="k", cmap="RdYlBu_r")

ax.set_ylim(-6,18)
plt.show()

这篇关于如何绘制温度计?的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！