Question

在以下代码中，条形图的颜色会随着阈值的变化而变化。我没有使用阈值并在代码中绘制水平线，而是想在OnMouseMove函数中使用y参数，以便用户可以更改＆＃34; threshold＆＃34;的位置。然后，我想要在更改y时更新颜色。

我认为我需要的是＃34;观察者模式＆＃34;或者使用动画工具但不确定如何实现它的技巧。我很欣赏有关如何做到这一点的任何见解。感谢

%matplotlib notebook
import pandas as pd
import numpy as np
from scipy import stats
import matplotlib.colors as mcol
import matplotlib.cm as cm
import matplotlib.pyplot as plt

np.random.seed(12345)
df = pd.DataFrame([np.random.normal(335,1500,300), 
                   np.random.normal(410,900,300), 
                   np.random.normal(410,1200,300), 
                   np.random.normal(480,550,300)], 
                  index=[1,2,3,4])

fig, ax = plt.subplots()
plt.show()
bars = plt.bar(range(df.shape[0]), df.mean(axis = 1), color = 'lightslategrey')

fig = plt.gcf()
threshold=420
plt.axhline(y = threshold, color = 'grey', alpha = 0.5)

cm1 = mcol.LinearSegmentedColormap.from_list("Test",["b", "white", "purple"])
cpick = cm.ScalarMappable(cmap=cm1)
cpick.set_array([])

percentages = []
for bar in bars:
    percentage = (bar.get_height()-threshold)/bar.get_height()
    if percentage>1: percentage = 1
    if percentage<0: percentage=0
    percentages.append(percentage)

cpick.to_rgba(percentages)
bars = plt.bar(range(df.shape[0]), df.mean(axis = 1), color = cpick.to_rgba(percentages))
plt.colorbar(cpick, orientation='horizontal')

def onMouseMove(event):
    ax.lines = [ax.lines[0]]
    plt.axhline(y=event.ydata, color="k")

fig.canvas.mpl_connect('motion_notify_event', onMouseMove)

plt.xticks(range(df.shape[0]), df.index, alpha = 0.8)

Answer 1

首先你应该使用一个条形图和一个axhline（使用更多将使一切变得混乱）。您可以通过

设置条形图的颜色

for bar in bars:
    bar.set_color(..)

您可以通过line.set_ydata(position)更新axhline的位置。

现在，对于每个鼠标移动事件，您需要更新axhline的位置，计算百分比并将新颜色应用于条形。所以这些事情应该在一个函数中完成，每次触发鼠标移动事件时都会调用它。应用这些设置后，需要绘制画布以使其可见。

这是一个完整的代码。

import pandas as pd
import numpy as np
import matplotlib.colors as mcol
import matplotlib.cm as cm
import matplotlib.pyplot as plt

np.random.seed(12345)
df = pd.DataFrame([np.random.normal(335,1500,300), 
                   np.random.normal(410,900,300), 
                   np.random.normal(410,1200,300), 
                   np.random.normal(480,550,300)], 
                  index=[1,2,3,4])

fig, ax = plt.subplots()

threshold=420.
bars = plt.bar(range(df.shape[0]), df.mean(axis = 1), color = 'lightslategrey')
axline = plt.axhline(y = threshold, color = 'grey', alpha = 0.5)

cm1 = mcol.LinearSegmentedColormap.from_list("Test",["b", "white", "purple"])
cpick = cm.ScalarMappable(cmap=cm1) 
cpick.set_array([])
plt.colorbar(cpick, orientation='horizontal')

def percentages(threshold):
    percentages = []
    for bar in bars:
        percentage = (bar.get_height()-threshold)/bar.get_height()
        if percentage>1: percentage = 1
        if percentage<0: percentage=0
        percentages.append(percentage)
    return percentages

def update(threshold):
    axline.set_ydata(threshold)
    perc = percentages(threshold)
    for bar, p in zip(bars, perc):
        bar.set_color(cpick.to_rgba(p))

# update once before showing
update(threshold)

def onMouseMove(event):
    if event.inaxes == ax:
        update(event.ydata)
        fig.canvas.draw_idle()

fig.canvas.mpl_connect('motion_notify_event', onMouseMove)

plt.xticks(range(df.shape[0]), df.index, alpha = 0.8)

plt.show()

更改参数后如何自动更改颜色

1 个答案: