import matplotlib.pyplot as plt #包含绘图模块 fig= plt._____(2)______() #创建一个空白画布 ax1=fig._______(3)___________(1,1,1) #添加一个子图 plt.show() #显示图表
时间: 2023-06-14 17:05:17 浏览: 90
import matplotlib.pyplot as plt #包含绘图模块
fig= plt.figure() #创建一个空白画布
ax1=fig.add_subplot(1,1,1) #添加一个子图
plt.show() #显示图表
相关问题
import matplotlib.pyplot as plt import numpy as np import netCDF4 as nc import cartopy.crs as ccrs from cartopy.util import add_cyclic_point
I'm sorry, as an AI language model, I am not capable of displaying images or visualizations. However, I can provide you with the code for displaying a map using Cartopy and NetCDF4. Here's an example code:
```
import matplotlib.pyplot as plt
import numpy as np
import netCDF4 as nc
import cartopy.crs as ccrs
from cartopy.util import add_cyclic_point
# Load the NetCDF data
data = nc.Dataset('data.nc')
# Extract the variables
lon = data.variables['lon'][:]
lat = data.variables['lat'][:]
temp = data.variables['temp'][:]
# Add a cyclic point for plotting
temp, lon = add_cyclic_point(temp, coord=lon)
# Create a map projection
projection = ccrs.PlateCarree()
# Create a figure and axis
fig, ax = plt.subplots(subplot_kw={'projection': projection})
# Add coastlines
ax.coastlines()
# Plot the data
plt.contourf(lon, lat, temp, cmap='coolwarm', transform=projection)
# Add a colorbar
plt.colorbar()
plt.show()
```
In this example, we first load the NetCDF data and extract the variables we need. We then add a cyclic point to the temperature data to ensure it wraps around the plot correctly. Next, we create a map projection and a figure with an axis that uses the projection. We add coastlines to the plot and use `plt.contourf()` to plot the temperature data on the map. Finally, we add a colorbar to the plot and display it using `plt.show()`.
import matplotlib.pyplot as plt #【错误行】 包含绘图模块 fig= plt.figure() #创建一个空白画布 ax1=fig.plot(1,1,1) #【错误行】 添加一个子图 plt.show() #显示图表
代码中存在两个错误:
1. 导入的 matplotlib 库中的 pyplot 模块应该使用 import matplotlib.pyplot as plt 的方式导入;
2. 绘图函数应该使用 plt.subplot(1, 1, 1) 而不是 fig.plot(1, 1, 1)。
修改后的代码如下:
```python
import matplotlib.pyplot as plt #导入绘图模块
fig = plt.figure() #创建一个空白画布
ax1 = plt.subplot(1, 1, 1) #添加一个子图
plt.show() #显示图表
```
这段代码可以创建一个空白画布,并在其中添加一个子图,最后显示出来。