还有高手？气象要素廓线局部放大绘制
前言
首先，我们需要使用Python中的Matplotlib库来创建一个简单的气象数据可视化。
我们将使用Matplotlib的plot函数来绘制气象数据的整体趋势图，
然后使用mark_inset函数来创建一局部放大的子图，以便更详细地查看数据的某个特定部分。
以下是步骤：
导入必要的库
创建示例气象数据
绘制整体趋势图
创建局部放大的子图
在子图中绘制局部放大的气象数据
显示图形
让我们逐步实现这些步骤。
import matplotlib.pyplot as plt
import numpy as np
from mpl_toolkits.axes_grid1.inset_locator import TransformedBbox, BboxPatch, BboxConnector
def mark_inset(parent_axes, inset_axes, loc1a=1, loc1b=1, loc2a=2, loc2b=2, **kwargs):
rect = TransformedBbox(inset_axes.viewLim, parent_axes.transData)
pp = BboxPatch(rect, fill=False, **kwargs)
parent_axes.add_patch(pp)
p1 = BboxConnector(inset_axes.bbox, rect, loc1=loc1a, loc2=loc1b, **kwargs)
inset_axes.add_patch(p1)
p1.set_clip_on(False)
p2 = BboxConnector(inset_axes.bbox, rect, loc1=loc2a, loc2=loc2b, **kwargs)
inset_axes.add_patch(p2)
p2.set_clip_on(False)
return pp, p1, p2
# 生成随机数据
height = np.arange(0, 5000, 100)
temperature = np.random.randint(-50, 50, size=len(height))
# 创建图形对象和子图对象
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(20,12))
# 在第一个子图中绘制温度随高度变化的曲线图
ax1.plot(temperature, height)
ax1.set_xlabel('Temperature (°C)')
ax1.set_ylabel('Height (m)')
ax1.set_title('Temperature vs. Height')
# 在第二个子图中绘制放大的子图
ax2.plot(temperature, height)
ax2.set_xlabel('Temperature (°C)')
ax2.set_ylabel('Height (m)')
ax2.set_title('Temperature vs. Height (Zoomed)')
# 设置第二个子图的范围
ax2.set_ylim()
ax2.set_xlim([-50, 50])
mark_inset(ax1, ax2, loc1a=2, loc1b=1, loc2a=3, loc2b=4, fc='none', ec='black', lw=1.75)
plt.show()
正在我自鸣得意时，上网一看，没想到还有高手
matplotlib早就做了，那么我们来学习一下
import matplotlib.pyplot as plt
import numpy as np
# 生成随机数据
height = np.linspace(0, 5000, 50)
temperature = np.random.randint(-50, 50, size=len(height))
# 创建图形对象和子图对象
fig, (ax1) = plt.subplots(1, figsize=(10,20))
# 在第一个子图中绘制温度随高度变化的曲线图
ax1.plot(temperature, height)
ax1.set_xlabel('Temperature (°C)')
ax1.set_ylabel('Height (m)')
ax1.set_title('Temperature vs. Height')
# 添加放大的子图及连接线
x1, x2, y1, y2 = -50, 50, 1000, 3000# subregion of the original image
axins = ax1.inset_axes(, xlim=(x1, x2), ylim=(y1, y2), xticklabels=[], yticklabels=[])
axins.plot(temperature, height)
axins.set_title('Zoomed Inset')
ax1.indicate_inset_zoom(axins, edgecolor="black")
plt.show()
总的来说，Python的魅力就是路不只有一条。
如果觉得有帮得到的地方，麻烦您动动小手指文末的广告都给我点一下，然后一键三连啦，感谢！
文章来源于微信公众号：气ython风雨
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