【python海洋专题二十八】南海四季海流流速图
往期推荐
图片
【python海洋专题一】查看数据nc文件的属性并输出属性到txt文件
【python海洋专题二】读取水深nc文件并水深地形图
【python海洋专题三】图像修饰之画布和坐标轴
【Python海洋专题四】之水深地图图像修饰
【Python海洋专题五】之水深地形图海岸填充
【Python海洋专题六】之Cartopy画地形水深图
【python海洋专题】测试数据
【Python海洋专题七】Cartopy画地形水深图的陆地填充
【python海洋专题八】Cartopy画地形水深图的contourf填充间隔数调整
【python海洋专题九】Cartopy画地形等深线图
【python海洋专题十】Cartopy画特定区域的地形等深线图
【python海洋专题十一】colormap调色
【python海洋专题十二】年平均的南海海表面温度图
【python海洋专题十三】读取多个nc文件画温度季节变化图
【python海洋专题十四】读取多个盐度nc数据画盐度季节变化图
【python海洋专题十五】给colorbar加单位
【python海洋专题十六】对大陆周边的数据进行临近插值
【python海洋专题十七】读取几十年的OHC数据，画四季图
【python海洋专题十八】读取Soda数据，画subplot的海表面高度四季变化图
【python海洋专题十九】找范围的语句进阶版本
【python海洋专题二十】subplots_adjust布局调整
【python海洋专题二十一】subplots共用一个colorbar
【python海洋专题二十二】在海图上text
【python海洋专题二十三】共用坐标轴
【python海洋专题二十四】南海年平均海流图
【python海洋专题二十五】给南海年平均海流+scale
【python海洋专题二十六】南海海流流速图
【python海洋专题二十七】南海四季海流图
【MATLAB海洋专题】历史汇总
【matlab程序】图片平面制作||文末点赞分享||海报制作等
大佬推荐一下物理海洋教材吧?
【matlab海洋专题】高级玫瑰图–风速风向频率玫瑰图–此图细节较多
# -*- coding: utf-8 -*-
# ---导入数据读取和处理的模块-------
from netCDF4 import Dataset
from pathlib import Path
import xarray as xr
import numpy as np
# ------导入画图相关函数--------
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
import matplotlib.ticker as ticker
from cartopy import mpl
import cartopy.crs as ccrs
import cartopy.feature as feature
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
from pylab import *
# -----导入颜色包---------
import seaborn as sns
from matplotlib import cm
import palettable
from palettable.cmocean.diverging import Delta_4
from palettable.colorbrewer.sequential import GnBu_9
from palettable.colorbrewer.sequential import Blues_9
from palettable.scientific.diverging import Roma_20
from palettable.cmocean.diverging import Delta_20
from palettable.scientific.diverging import Roma_20
from palettable.cmocean.diverging import Balance_20
from matplotlib.colors import ListedColormap
# -------导入插值模块-----
from scipy.interpolate import interp1d # 引入scipy中的一维插值库
from scipy.interpolate import griddata # 引入scipy中的二维插值库
from scipy.interpolate import interp2d
# ----define reverse_colourmap定义颜色的反向函数----
def reverse_colourmap(cmap, name='my_cmap_r'):
reverse = []
k = []
for key in cmap._segmentdata:
k.append(key)
channel = cmap._segmentdata[key]
data = []
for t in channel:
data.append((1 - t[0], t[2], t[1]))
reverse.append(sorted(data))
LinearL = dict(zip(k, reverse))
my_cmap_r = mpl.colors.LinearSegmentedColormap(name, LinearL)
return my_cmap_r
# ---colormap的读取和反向----
cmap01 = Balance_20.mpl_colormap
cmap0 = Blues_9.mpl_colormap
cmap_r = reverse_colourmap(cmap0)
cmap1 = GnBu_9.mpl_colormap
cmap_r1 = reverse_colourmap(cmap1)
cmap2 = Roma_20.mpl_colormap
cmap_r2 = reverse_colourmap(cmap2)
# ---read_data---
f1 = xr.open_dataset(r'E:\data\soda\soda3.12.2_5dy_ocean_reg_2017.nc')
print(f1)
# # 提取经纬度（这样就不需要重复读取）
lat = f1['yt_ocean'].data
lon = f1['xt_ocean'].data
u = f1['u'].data
v = f1['v'].data
depth = f1['st_ocean'].data
# print(depth)
time = f1['time'].data
# print(time)
# # -------- find scs 's temp-----------
ln1 = np.where(lon >= 100)[0][0]
ln2 = np.where(lon >= 125)[0][0]
la1 = np.where(lat >= 0)[0][0]
la2 = np.where(lat >= 25)[0][0]
# time_all=[(time>=1058760) & (time<=1059096)] #13-27 Oct
# # # 画图网格
lon1 = lon[ln1:ln2]
lat1 = lat[la1:la2]
X, Y = np.meshgrid(lon1, lat1)
u_aim = u[:, 0, la1:la2, ln1:ln2]
v_aim = v[:, 0, la1:la2, ln1:ln2]
# # # ----------对时间维度求平均 得到年平均的current------------------
u_year_mean = np.mean(u_aim[:, :, :], axis=0)
v_year_mean = np.mean(v_aim[:, :, :], axis=0)
# ------春夏秋冬------
u_spr_mean = np.mean(u_aim[2:5, :, :], axis=0)
u_sum_mean = np.mean(u_aim[5:8, :, :], axis=0)
u_atu_mean = np.mean(u_aim[8:11, :, :], axis=0)
u_win_mean = (u_aim[0, :, :] + u_aim[1, :, :] + u_aim[11, :, :]) / 3
v_spr_mean = np.mean(v_aim[2:5, :, :], axis=0)
v_sum_mean = np.mean(v_aim[5:8, :, :], axis=0)
v_atu_mean = np.mean(v_aim[8:11, :, :], axis=0)
v_win_mean = (v_aim[0, :, :] + v_aim[1, :, :] + v_aim[11, :, :]) / 3
w_spr_mean_new = np.sqrt(np.square(u_spr_mean) + np.square(v_spr_mean))
w_sum_mean_new = np.sqrt(np.square(u_sum_mean) + np.square(v_sum_mean))
w_atu_mean_new = np.sqrt(np.square(u_atu_mean) + np.square(v_atu_mean))
w_win_mean_new = np.sqrt(np.square(u_win_mean) + np.square(v_win_mean))
# ----plot--------------
scale = '50m'
plt.rcParams['font.sans-serif'] = ['Times New Roman'] # 设置整体的字体为Times New Roman
# 设置显示中文字体
mpl.rcParams["font.sans-serif"] = ["SimHei"]
mpl.rcParams["mathtext.fontset"] = 'cm' # 数学文字字体
mpl.rcParams["font.size"] = 12 # 字体大小
mpl.rcParams["axes.linewidth"] = 1 # 轴线边框粗细（默认的太粗了）
fig = plt.figure(dpi=300, figsize=(3.5, 2.6), facecolor='w', edgecolor='blue') # 设置一个画板，将其返还给fig
# 通过subplots_adjust()设置间距配置
fig.subplots_adjust(left=0.06, bottom=0.05, right=0.85, top=0.95, wspace=0.01, hspace=0.15)
# --------第一个子图----------
ax = fig.add_subplot(2, 2, 1, projection=ccrs.PlateCarree(central_longitude=180))
ax.set_extent([100, 123, 0, 25], crs=ccrs.PlateCarree()) # 设置显示范围
land = feature.NaturalEarthFeature('physical', 'land', scale, edgecolor='face', zorder=1,
facecolor=feature.COLORS['land'])
ax.add_feature(land, facecolor='0.6')
ax.add_feature(feature.COASTLINE.with_scale('50m'), lw=0.3, zorder=2) # 添加海岸线：关键字lw设置线宽; lifestyle设置线型
cs = ax.quiver(X, Y, u_spr_mean, v_spr_mean, color='r', scale=5, zorder=1, width=0.003, headwidth=3,
headlength=4.5, transform=ccrs.PlateCarree())
cf = ax.contourf(X, Y, w_spr_mean_new, extend='both', zorder=0, cmap=cmap_r2, levels=np.linspace(0, 1, 50),
transform=ccrs.PlateCarree()) #
font = {'family': 'serif',
'weight': 'normal',
'size': 4,
}
ax.quiverkey(cs, # 传入quiver句柄
X=0.9, Y=1.015, # 确定 label 所在位置，都限制在[0,1]之间
U=0.5, # 参考箭头长度 表示风速为5m/s。
angle=0, # 参考箭头摆放角度。默认为0，即水平摆放
label='0.5m/s', # 箭头的补充：label的内容 +
labelsep=0.01,
labelpos='N', # label在参考箭头的哪个方向; S表示南边
color='r', labelcolor='r', # 箭头颜色 + label的颜色
fontproperties=font, # l abel 的字体设置：大小，样式，weight
zorder=10,
)
# --------------添加标题----------------
ax.set_title('春季', loc="center", fontsize=6, pad=1)
# ------------------利用Formatter格式化刻度标签-----------------
ax.set_xticks(np.arange(100, 123, 5), crs=ccrs.PlateCarree()) # 添加经纬度
ax.set_xticklabels(np.arange(100, 123, 5), fontsize=4)
ax.set_yticks(np.arange(0, 25, 5), crs=ccrs.PlateCarree())
ax.set_yticklabels(np.arange(0, 25, 5), fontsize=4)
ax.xaxis.set_major_formatter(LongitudeFormatter())
ax.yaxis.set_major_formatter(LatitudeFormatter())
ax.tick_params(axis='x', top=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 刻度样式 pad代表标题离轴的远近
ax.tick_params(axis='y', right=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 更改刻度指向为朝内，颜色设置为蓝色
gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=False, xlocs=np.arange(100, 123, 5), ylocs=np.arange(0, 25, 5),
linewidth=0.25, linestyle='--', color='k', alpha=0.8) # 添加网格线
gl.top_labels, gl.bottom_labels, gl.right_labels, gl.left_labels = False, False, False, False
# plt.yticks([])
plt.xticks([])
# -----第二个子图# --------子图----------
ax = fig.add_subplot(2, 2, 2, projection=ccrs.PlateCarree(central_longitude=180))
ax.set_extent([100, 123, 0, 25], crs=ccrs.PlateCarree()) # 设置显示范围
land = feature.NaturalEarthFeature('physical', 'land', scale, edgecolor='face', zorder=1,
facecolor=feature.COLORS['land'])
ax.add_feature(land, facecolor='0.6')
ax.add_feature(feature.COASTLINE.with_scale('50m'), lw=0.3, zorder=2) # 添加海岸线：关键字lw设置线宽; lifestyle设置线型
cs = ax.quiver(X, Y, u_sum_mean, v_sum_mean, color='r', scale=5, zorder=1, width=0.003, headwidth=3,
headlength=4.5, transform=ccrs.PlateCarree())
cf = ax.contourf(X, Y, w_sum_mean_new, extend='both', zorder=0, cmap=cmap_r2, levels=np.linspace(0, 1, 50),
transform=ccrs.PlateCarree()) #
font = {'family': 'serif',
'weight': 'normal',
'size': 4,
}
ax.quiverkey(cs, # 传入quiver句柄
X=0.9, Y=1.015, # 确定 label 所在位置，都限制在[0,1]之间
U=0.5, # 参考箭头长度 表示风速为5m/s。
angle=0, # 参考箭头摆放角度。默认为0，即水平摆放
label='0.5m/s', # 箭头的补充：label的内容 +
labelsep=0.01,
labelpos='N', # label在参考箭头的哪个方向; S表示南边
color='r', labelcolor='r', # 箭头颜色 + label的颜色
fontproperties=font, # l abel 的字体设置：大小，样式，weight
zorder=10,
)
# --------------添加标题----------------
ax.set_title('夏季', loc="center", fontsize=6, pad=1)
# ------------------利用Formatter格式化刻度标签-----------------
ax.set_xticks(np.arange(100, 123, 5), crs=ccrs.PlateCarree()) # 添加经纬度
ax.set_xticklabels(np.arange(100, 123, 5), fontsize=4)
ax.set_yticks(np.arange(0, 25, 5), crs=ccrs.PlateCarree())
ax.set_yticklabels(np.arange(0, 25, 5), fontsize=4)
ax.xaxis.set_major_formatter(LongitudeFormatter())
ax.yaxis.set_major_formatter(LatitudeFormatter())
ax.tick_params(axis='x', top=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 刻度样式 pad代表标题离轴的远近
ax.tick_params(axis='y', right=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 更改刻度指向为朝内，颜色设置为蓝色
gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=False, xlocs=np.arange(100, 123, 5), ylocs=np.arange(0, 25, 5),
linewidth=0.25, linestyle='--', color='k', alpha=0.8) # 添加网格线
gl.top_labels, gl.bottom_labels, gl.right_labels, gl.left_labels = False, False, False, False
plt.yticks([])
plt.xticks([])
# -----第san个子图# --------子图----------
ax = fig.add_subplot(2, 2, 3, projection=ccrs.PlateCarree(central_longitude=180))
ax.set_extent([100, 123, 0, 25], crs=ccrs.PlateCarree()) # 设置显示范围
land = feature.NaturalEarthFeature('physical', 'land', scale, edgecolor='face', zorder=1,
facecolor=feature.COLORS['land'])
ax.add_feature(land, facecolor='0.6')
ax.add_feature(feature.COASTLINE.with_scale('50m'), lw=0.3, zorder=2) # 添加海岸线：关键字lw设置线宽; lifestyle设置线型
cs = ax.quiver(X, Y, u_atu_mean, v_atu_mean, color='r', scale=5, zorder=1, width=0.003, headwidth=3,
headlength=4.5, transform=ccrs.PlateCarree())
cf = ax.contourf(X, Y, w_atu_mean_new, extend='both', zorder=0, cmap=cmap_r2, levels=np.linspace(0, 1, 50),
transform=ccrs.PlateCarree()) #
font = {'family': 'serif',
'weight': 'normal',
'size': 4,
}
ax.quiverkey(cs, # 传入quiver句柄
X=0.9, Y=1.015, # 确定 label 所在位置，都限制在[0,1]之间
U=0.5, # 参考箭头长度 表示风速为5m/s。
angle=0, # 参考箭头摆放角度。默认为0，即水平摆放
label='0.5m/s', # 箭头的补充：label的内容 +
labelsep=0.01,
labelpos='N', # label在参考箭头的哪个方向; S表示南边
color='r', labelcolor='r', # 箭头颜色 + label的颜色
fontproperties=font, # l abel 的字体设置：大小，样式，weight
zorder=10,
)
# --------------添加标题----------------
ax.set_title('秋季', loc="center", fontsize=6, pad=1)
# ------------------利用Formatter格式化刻度标签-----------------
ax.set_xticks(np.arange(100, 123, 5), crs=ccrs.PlateCarree()) # 添加经纬度
ax.set_xticklabels(np.arange(100, 123, 5), fontsize=4)
ax.set_yticks(np.arange(0, 25, 5), crs=ccrs.PlateCarree())
ax.set_yticklabels(np.arange(0, 25, 5), fontsize=4)
ax.xaxis.set_major_formatter(LongitudeFormatter())
ax.yaxis.set_major_formatter(LatitudeFormatter())
ax.tick_params(axis='x', top=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 刻度样式 pad代表标题离轴的远近
ax.tick_params(axis='y', right=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 更改刻度指向为朝内，颜色设置为蓝色
gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=False, xlocs=np.arange(100, 123, 5), ylocs=np.arange(0, 25, 5),
linewidth=0.25, linestyle='--', color='k', alpha=0.8) # 添加网格线
gl.top_labels, gl.bottom_labels, gl.right_labels, gl.left_labels = False, False, False, False
# plt.yticks([])
# plt.xticks([])
# -----第四个子图# --------子图----------
ax = fig.add_subplot(2, 2, 4, projection=ccrs.PlateCarree(central_longitude=180))
ax.set_extent([100, 123, 0, 25], crs=ccrs.PlateCarree()) # 设置显示范围
land = feature.NaturalEarthFeature('physical', 'land', scale, edgecolor='face', zorder=1,
facecolor=feature.COLORS['land'])
ax.add_feature(land, facecolor='0.6')
ax.add_feature(feature.COASTLINE.with_scale('50m'), lw=0.3, zorder=2) # 添加海岸线：关键字lw设置线宽; lifestyle设置线型
cs = ax.quiver(X, Y, u_win_mean, v_win_mean, color='r', scale=5, zorder=1, width=0.003, headwidth=3,
headlength=4.5, transform=ccrs.PlateCarree())
cf = ax.contourf(X, Y, w_win_mean_new, extend='both', zorder=0, cmap=cmap_r2, levels=np.linspace(0, 1, 50),
transform=ccrs.PlateCarree()) #
font = {'family': 'serif',
'weight': 'normal',
'size': 4,
}
ax.quiverkey(cs, # 传入quiver句柄
X=0.9, Y=1.015, # 确定 label 所在位置，都限制在[0,1]之间
U=0.5, # 参考箭头长度 表示风速为5m/s。
angle=0, # 参考箭头摆放角度。默认为0，即水平摆放
label='0.5m/s', # 箭头的补充：label的内容 +
labelsep=0.01,
labelpos='N', # label在参考箭头的哪个方向; S表示南边
color='r', labelcolor='r', # 箭头颜色 + label的颜色
fontproperties=font, # l abel 的字体设置：大小，样式，weight
zorder=10,
)
# --------------添加标题----------------
ax.set_title('冬季', loc="center", fontsize=6, pad=1)
# ------------------利用Formatter格式化刻度标签-----------------
ax.set_xticks(np.arange(100, 123, 5), crs=ccrs.PlateCarree()) # 添加经纬度
ax.set_xticklabels(np.arange(100, 123, 5), fontsize=4)
ax.set_yticks(np.arange(0, 25, 5), crs=ccrs.PlateCarree())
ax.set_yticklabels(np.arange(0, 25, 5), fontsize=4)
ax.xaxis.set_major_formatter(LongitudeFormatter())
ax.yaxis.set_major_formatter(LatitudeFormatter())
ax.tick_params(axis='x', top=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 刻度样式 pad代表标题离轴的远近
ax.tick_params(axis='y', right=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 更改刻度指向为朝内，颜色设置为蓝色
gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=False, xlocs=np.arange(100, 123, 5), ylocs=np.arange(0, 25, 5),
linewidth=0.25, linestyle='--', color='k', alpha=0.8) # 添加网格线
gl.top_labels, gl.bottom_labels, gl.right_labels, gl.left_labels = False, False, False, False
# % 不显示坐标刻度
plt.yticks([])
# plt.xticks([])
# ---------共用colorbar------
cb_ax = fig.add_axes([0.85, 0.1, 0.02, 0.8]) #设置colarbar位置
cbar = fig.colorbar(cf, cax=cb_ax, ax=ax, extend='both', orientation='vertical', ticks=[0, 0.2, 0.4, 0.6, 0.8, 1.0]) #共享colorbar
plt.savefig('subplot_current_45.jpg', dpi=600, bbox_inches='tight', pad_inches=0.1) # 输出地图，并设置边框空白紧密
plt.show()
2
# -*- coding: utf-8 -*-
# ---导入数据读取和处理的模块-------
from netCDF4 import Dataset
from pathlib import Path
import xarray as xr
import numpy as np
# ------导入画图相关函数--------
import matplotlib.pyplot as plt
from matplotlib.font_manager import FontProperties
import matplotlib.ticker as ticker
from cartopy import mpl
import cartopy.crs as ccrs
import cartopy.feature as feature
from cartopy.mpl.ticker import LongitudeFormatter, LatitudeFormatter
from pylab import *
# -----导入颜色包---------
import seaborn as sns
from matplotlib import cm
import palettable
from palettable.cmocean.diverging import Delta_4
from palettable.colorbrewer.sequential import GnBu_9
from palettable.colorbrewer.sequential import Blues_9
from palettable.scientific.diverging import Roma_20
from palettable.cmocean.diverging import Delta_20
from palettable.scientific.diverging import Roma_20
from palettable.cmocean.diverging import Balance_20
from matplotlib.colors import ListedColormap
# -------导入插值模块-----
from scipy.interpolate import interp1d # 引入scipy中的一维插值库
from scipy.interpolate import griddata # 引入scipy中的二维插值库
from scipy.interpolate import interp2d
# ----define reverse_colourmap定义颜色的反向函数----
def reverse_colourmap(cmap, name='my_cmap_r'):
reverse = []
k = []
for key in cmap._segmentdata:
k.append(key)
channel = cmap._segmentdata[key]
data = []
for t in channel:
data.append((1 - t[0], t[2], t[1]))
reverse.append(sorted(data))
LinearL = dict(zip(k, reverse))
my_cmap_r = mpl.colors.LinearSegmentedColormap(name, LinearL)
return my_cmap_r
# ---colormap的读取和反向----
cmap01 = Balance_20.mpl_colormap
cmap0 = Blues_9.mpl_colormap
cmap_r = reverse_colourmap(cmap0)
cmap1 = GnBu_9.mpl_colormap
cmap_r1 = reverse_colourmap(cmap1)
cmap2 = Roma_20.mpl_colormap
cmap_r2 = reverse_colourmap(cmap2)
# ---read_data---
f1 = xr.open_dataset(r'E:\data\soda\soda3.12.2_5dy_ocean_reg_2017.nc')
print(f1)
# # 提取经纬度（这样就不需要重复读取）
lat = f1['yt_ocean'].data
lon = f1['xt_ocean'].data
u = f1['u'].data
v = f1['v'].data
depth = f1['st_ocean'].data
# print(depth)
time = f1['time'].data
# print(time)
# # -------- find scs 's temp-----------
ln1 = np.where(lon >= 100)[0][0]
ln2 = np.where(lon >= 125)[0][0]
la1 = np.where(lat >= 0)[0][0]
la2 = np.where(lat >= 25)[0][0]
# time_all=[(time>=1058760) & (time<=1059096)] #13-27 Oct
# # # 画图网格
lon1 = lon[ln1:ln2]
lat1 = lat[la1:la2]
X, Y = np.meshgrid(lon1, lat1)
u_aim = u[:, 0, la1:la2, ln1:ln2]
v_aim = v[:, 0, la1:la2, ln1:ln2]
# # # ----------对时间维度求平均 得到年平均的current------------------
u_year_mean = np.mean(u_aim[:, :, :], axis=0)
v_year_mean = np.mean(v_aim[:, :, :], axis=0)
# ------春夏秋冬------
u_spr_mean = np.mean(u_aim[2:5, :, :], axis=0)
u_sum_mean = np.mean(u_aim[5:8, :, :], axis=0)
u_atu_mean = np.mean(u_aim[8:11, :, :], axis=0)
u_win_mean = (u_aim[0, :, :] + u_aim[1, :, :] + u_aim[11, :, :]) / 3
v_spr_mean = np.mean(v_aim[2:5, :, :], axis=0)
v_sum_mean = np.mean(v_aim[5:8, :, :], axis=0)
v_atu_mean = np.mean(v_aim[8:11, :, :], axis=0)
v_win_mean = (v_aim[0, :, :] + v_aim[1, :, :] + v_aim[11, :, :]) / 3
w_spr_mean_new = np.sqrt(np.square(u_spr_mean) + np.square(v_spr_mean))
w_sum_mean_new = np.sqrt(np.square(u_sum_mean) + np.square(v_sum_mean))
w_atu_mean_new = np.sqrt(np.square(u_atu_mean) + np.square(v_atu_mean))
w_win_mean_new = np.sqrt(np.square(u_win_mean) + np.square(v_win_mean))
# ----plot--------------
scale = '50m'
plt.rcParams['font.sans-serif'] = ['Times New Roman'] # 设置整体的字体为Times New Roman
# 设置显示中文字体
mpl.rcParams["font.sans-serif"] = ["SimHei"]
mpl.rcParams["mathtext.fontset"] = 'cm' # 数学文字字体
mpl.rcParams["font.size"] = 12 # 字体大小
mpl.rcParams["axes.linewidth"] = 1 # 轴线边框粗细（默认的太粗了）
fig = plt.figure(dpi=300, figsize=(3.5, 2.6), facecolor='w', edgecolor='blue') # 设置一个画板，将其返还给fig
# 通过subplots_adjust()设置间距配置
fig.subplots_adjust(left=0.05, bottom=0.05, right=0.9, top=0.95, wspace=0.05, hspace=0.15)
# --------第一个子图----------
ax = fig.add_subplot(2, 2, 1, projection=ccrs.PlateCarree(central_longitude=180))
ax.set_extent([100, 123, 0, 25], crs=ccrs.PlateCarree()) # 设置显示范围
land = feature.NaturalEarthFeature('physical', 'land', scale, edgecolor='face', zorder=1,
facecolor=feature.COLORS['land'])
ax.add_feature(land, facecolor='0.6')
ax.add_feature(feature.COASTLINE.with_scale('50m'), lw=0.3, zorder=2) # 添加海岸线：关键字lw设置线宽; lifestyle设置线型
cs = ax.quiver(X, Y, u_spr_mean, v_spr_mean, color='r', scale=5, zorder=1, width=0.003, headwidth=3,
headlength=4.5, transform=ccrs.PlateCarree())
cf = ax.contourf(X, Y, w_spr_mean_new, extend='both', zorder=0, cmap=cmap_r2, levels=np.linspace(0, 1, 50),
transform=ccrs.PlateCarree()) #
# ------color-bar设置------------
cb = plt.colorbar(cf, ax=ax, extend='both', orientation='vertical', ticks=np.linspace(0, 1, 6))
cb.ax.tick_params(labelsize=4, direction='in') # 设置color-bar刻度字体大小。
font = {'family': 'serif',
'weight': 'normal',
'size': 4,
}
ax.quiverkey(cs, # 传入quiver句柄
X=0.9, Y=1.015, # 确定 label 所在位置，都限制在[0,1]之间
U=0.5, # 参考箭头长度 表示风速为5m/s。
angle=0, # 参考箭头摆放角度。默认为0，即水平摆放
label='0.5m/s', # 箭头的补充：label的内容 +
labelsep=0.01,
labelpos='N', # label在参考箭头的哪个方向; S表示南边
color='r', labelcolor='r', # 箭头颜色 + label的颜色
fontproperties=font, # l abel 的字体设置：大小，样式，weight
zorder=10,
)
# --------------添加标题----------------
ax.set_title('春季', loc="center", fontsize=6, pad=1)
# ------------------利用Formatter格式化刻度标签-----------------
ax.set_xticks(np.arange(100, 123, 5), crs=ccrs.PlateCarree()) # 添加经纬度
ax.set_xticklabels(np.arange(100, 123, 5), fontsize=4)
ax.set_yticks(np.arange(0, 25, 5), crs=ccrs.PlateCarree())
ax.set_yticklabels(np.arange(0, 25, 5), fontsize=4)
ax.xaxis.set_major_formatter(LongitudeFormatter())
ax.yaxis.set_major_formatter(LatitudeFormatter())
ax.tick_params(axis='x', top=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 刻度样式 pad代表标题离轴的远近
ax.tick_params(axis='y', right=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 更改刻度指向为朝内，颜色设置为蓝色
gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=False, xlocs=np.arange(100, 123, 5), ylocs=np.arange(0, 25, 5),
linewidth=0.25, linestyle='--', color='k', alpha=0.8) # 添加网格线
gl.top_labels, gl.bottom_labels, gl.right_labels, gl.left_labels = False, False, False, False
# -----第二个子图# --------子图----------
ax = fig.add_subplot(2, 2, 2, projection=ccrs.PlateCarree(central_longitude=180))
ax.set_extent([100, 123, 0, 25], crs=ccrs.PlateCarree()) # 设置显示范围
land = feature.NaturalEarthFeature('physical', 'land', scale, edgecolor='face', zorder=1,
facecolor=feature.COLORS['land'])
ax.add_feature(land, facecolor='0.6')
ax.add_feature(feature.COASTLINE.with_scale('50m'), lw=0.3, zorder=2) # 添加海岸线：关键字lw设置线宽; lifestyle设置线型
cs = ax.quiver(X, Y, u_sum_mean, v_sum_mean, color='r', scale=5, zorder=1, width=0.003, headwidth=3,
headlength=4.5, transform=ccrs.PlateCarree())
cf = ax.contourf(X, Y, w_sum_mean_new, extend='both', zorder=0, cmap=cmap_r2, levels=np.linspace(0, 1, 50),
transform=ccrs.PlateCarree()) #
# ------color-bar设置------------
cb = plt.colorbar(cf, ax=ax, extend='both', orientation='vertical', ticks=np.linspace(0, 1, 6))
cb.set_label('current_size', fontsize=4, color='k') # 设置color-bar的标签字体及其大小
font = {'family': 'serif',
'weight': 'normal',
'size': 4,
}
ax.quiverkey(cs, # 传入quiver句柄
X=0.9, Y=1.015, # 确定 label 所在位置，都限制在[0,1]之间
U=0.5, # 参考箭头长度 表示风速为5m/s。
angle=0, # 参考箭头摆放角度。默认为0，即水平摆放
label='0.5m/s', # 箭头的补充：label的内容 +
labelsep=0.01,
labelpos='N', # label在参考箭头的哪个方向; S表示南边
color='r', labelcolor='r', # 箭头颜色 + label的颜色
fontproperties=font, # l abel 的字体设置：大小，样式，weight
zorder=10,
)
# --------------添加标题----------------
ax.set_title('夏季', loc="center", fontsize=6, pad=1)
# ------------------利用Formatter格式化刻度标签-----------------
ax.set_xticks(np.arange(100, 123, 5), crs=ccrs.PlateCarree()) # 添加经纬度
ax.set_xticklabels(np.arange(100, 123, 5), fontsize=4)
ax.set_yticks(np.arange(0, 25, 5), crs=ccrs.PlateCarree())
ax.set_yticklabels(np.arange(0, 25, 5), fontsize=4)
ax.xaxis.set_major_formatter(LongitudeFormatter())
ax.yaxis.set_major_formatter(LatitudeFormatter())
ax.tick_params(axis='x', top=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 刻度样式 pad代表标题离轴的远近
ax.tick_params(axis='y', right=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 更改刻度指向为朝内，颜色设置为蓝色
gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=False, xlocs=np.arange(100, 123, 5), ylocs=np.arange(0, 25, 5),
linewidth=0.25, linestyle='--', color='k', alpha=0.8) # 添加网格线
gl.top_labels, gl.bottom_labels, gl.right_labels, gl.left_labels = False, False, False, False
# -----第san个子图# --------子图----------
ax = fig.add_subplot(2, 2, 3, projection=ccrs.PlateCarree(central_longitude=180))
ax.set_extent([100, 123, 0, 25], crs=ccrs.PlateCarree()) # 设置显示范围
land = feature.NaturalEarthFeature('physical', 'land', scale, edgecolor='face', zorder=1,
facecolor=feature.COLORS['land'])
ax.add_feature(land, facecolor='0.6')
ax.add_feature(feature.COASTLINE.with_scale('50m'), lw=0.3, zorder=2) # 添加海岸线：关键字lw设置线宽; lifestyle设置线型
cs = ax.quiver(X, Y, u_atu_mean, v_atu_mean, color='r', scale=5, zorder=1, width=0.003, headwidth=3,
headlength=4.5, transform=ccrs.PlateCarree())
cf = ax.contourf(X, Y, w_atu_mean_new, extend='both', zorder=0, cmap=cmap_r2, levels=np.linspace(0, 1, 50),
transform=ccrs.PlateCarree()) #
# ------color-bar设置------------
cb = plt.colorbar(cf, ax=ax, extend='both', orientation='vertical', ticks=np.linspace(0, 1, 6))
cb.ax.tick_params(labelsize=4, direction='in') # 设置color-bar刻度字体大小。
font = {'family': 'serif',
'weight': 'normal',
'size': 4,
}
ax.quiverkey(cs, # 传入quiver句柄
X=0.9, Y=1.015, # 确定 label 所在位置，都限制在[0,1]之间
U=0.5, # 参考箭头长度 表示风速为5m/s。
angle=0, # 参考箭头摆放角度。默认为0，即水平摆放
label='0.5m/s', # 箭头的补充：label的内容 +
labelsep=0.01,
labelpos='N', # label在参考箭头的哪个方向; S表示南边
color='r', labelcolor='r', # 箭头颜色 + label的颜色
fontproperties=font, # l abel 的字体设置：大小，样式，weight
zorder=10,
)
# --------------添加标题----------------
ax.set_title('秋季', loc="center", fontsize=6, pad=1)
# ------------------利用Formatter格式化刻度标签-----------------
ax.set_xticks(np.arange(100, 123, 5), crs=ccrs.PlateCarree()) # 添加经纬度
ax.set_xticklabels(np.arange(100, 123, 5), fontsize=4)
ax.set_yticks(np.arange(0, 25, 5), crs=ccrs.PlateCarree())
ax.set_yticklabels(np.arange(0, 25, 5), fontsize=4)
ax.xaxis.set_major_formatter(LongitudeFormatter())
ax.yaxis.set_major_formatter(LatitudeFormatter())
ax.tick_params(axis='x', top=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 刻度样式 pad代表标题离轴的远近
ax.tick_params(axis='y', right=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 更改刻度指向为朝内，颜色设置为蓝色
gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=False, xlocs=np.arange(100, 123, 5), ylocs=np.arange(0, 25, 5),
linewidth=0.25, linestyle='--', color='k', alpha=0.8) # 添加网格线
gl.top_labels, gl.bottom_labels, gl.right_labels, gl.left_labels = False, False, False, False
# -----第四个子图# --------子图----------
ax = fig.add_subplot(2, 2, 4, projection=ccrs.PlateCarree(central_longitude=180))
ax.set_extent([100, 123, 0, 25], crs=ccrs.PlateCarree()) # 设置显示范围
land = feature.NaturalEarthFeature('physical', 'land', scale, edgecolor='face', zorder=1,
facecolor=feature.COLORS['land'])
ax.add_feature(land, facecolor='0.6')
ax.add_feature(feature.COASTLINE.with_scale('50m'), lw=0.3, zorder=2) # 添加海岸线：关键字lw设置线宽; lifestyle设置线型
cs = ax.quiver(X, Y, u_win_mean, v_win_mean, color='r', scale=5, zorder=1, width=0.003, headwidth=3,
headlength=4.5, transform=ccrs.PlateCarree())
cf = ax.contourf(X, Y, w_win_mean_new, extend='both', zorder=0, cmap=cmap_r2, levels=np.linspace(0, 1, 50),
transform=ccrs.PlateCarree()) #
# ------color-bar设置------------
cb = plt.colorbar(cf, ax=ax, extend='both', orientation='vertical', ticks=np.linspace(0, 1, 6))
cb.set_label('current_size', fontsize=4, color='k') # 设置color-bar的标签字体及其大小
font = {'family': 'serif',
'weight': 'normal',
'size': 4,
}
ax.quiverkey(cs, # 传入quiver句柄
X=0.9, Y=1.015, # 确定 label 所在位置，都限制在[0,1]之间
U=0.5, # 参考箭头长度 表示风速为5m/s。
angle=0, # 参考箭头摆放角度。默认为0，即水平摆放
label='0.5m/s', # 箭头的补充：label的内容 +
labelsep=0.01,
labelpos='N', # label在参考箭头的哪个方向; S表示南边
color='r', labelcolor='r', # 箭头颜色 + label的颜色
fontproperties=font, # l abel 的字体设置：大小，样式，weight
zorder=10,
)
# --------------添加标题----------------
ax.set_title('冬季', loc="center", fontsize=6, pad=1)
# ------------------利用Formatter格式化刻度标签-----------------
ax.set_xticks(np.arange(100, 123, 5), crs=ccrs.PlateCarree()) # 添加经纬度
ax.set_xticklabels(np.arange(100, 123, 5), fontsize=4)
ax.set_yticks(np.arange(0, 25, 5), crs=ccrs.PlateCarree())
ax.set_yticklabels(np.arange(0, 25, 5), fontsize=4)
ax.xaxis.set_major_formatter(LongitudeFormatter())
ax.yaxis.set_major_formatter(LatitudeFormatter())
ax.tick_params(axis='x', top=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 刻度样式 pad代表标题离轴的远近
ax.tick_params(axis='y', right=True, which='major', direction='in', length=3, width=0.8, labelsize=5, pad=0.8,
color='k') # 更改刻度指向为朝内，颜色设置为蓝色
gl = ax.gridlines(crs=ccrs.PlateCarree(), draw_labels=False, xlocs=np.arange(100, 123, 5), ylocs=np.arange(0, 25, 5),
linewidth=0.25, linestyle='--', color='k', alpha=0.8) # 添加网格线
gl.top_labels, gl.bottom_labels, gl.right_labels, gl.left_labels = False, False, False, False
plt.savefig('subplot_current_3.jpg', dpi=600, bbox_inches='tight', pad_inches=0.1) # 输出地图，并设置边框空白紧密
plt.show()
![2023年中国汽车铸造模具竞争现状及行业市场规模前景分析[图]](https://img-blog.csdnimg.cn/img_convert/86735421771191cdfc89a36f22745a32.png)
![【C++入门到精通】哈希 (STL) _ unordered_map _ unordered_set [ C++入门 ]](https://img-blog.csdnimg.cn/4868d249e6f9452abf489fbc82caf53b.jpeg#pic_center)
