Matplotlib底图：自定义子图和颜色栏位置
我有4个不同值的贴图，我想用matplotlib Basemap一起绘制为1个图中的4个子图，每个子图都有自己的颜色条。但是我设置颜色条和子图的大小和方向的努力似乎失败了（请参见下面的代码）。有人知道我在做什么错吗？使用底图时无法自定义子图和颜色栏设置吗？
import math
import matplotlib.cm as cm
import matplotlib.colors as colors
import matplotlib.image as mpimg
import matplotlib as mpl
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import numpy.ma as ma
import numpy as np
import pylab
# Create Variables:
B = np.full((4,60,360), np.nan)
B[0] = np.random.randint(16, size=(60, 360)) + 291
B[1] = np.random.randint(201, size=(60, 360)) - 100
B[2] = np.random.randint(56, size=(60, 360)) - 50
B[3] = np.random.randint(46, size=(60, 360))
# Colorbar Boundary Definitions:
cmap_1 = cm.jet
cmap_2 = cm.BrBG
cmap_3 = cm.hot
cmap_4 = cm.CMRmap_r
B_plot = np.ma.array ( B, mask=np.isnan(B))
bounds_B = []
norm_B = []
for b in np.arange(4):
bounds_B.append(b)
norm_B.append(b)
bounds_B[0] = np.arange(291, 306, 1)
bounds_B[1] = np.arange(-100, 110, 10)
bounds_B[2] = np.arange(-50, -7.5, 2.5)
bounds_B[3] = np.arange(0, 47.5, 2.5)
norm_B[0] = mpl.colors.BoundaryNorm(bounds_B[0], cmap_1.N)
norm_B[1] = mpl.colors.BoundaryNorm(bounds_B[1], cmap_2.N)
norm_B[2] = mpl.colors.BoundaryNorm(bounds_B[2], cmap_3.N)
norm_B[3] = mpl.colors.BoundaryNorm(bounds_B[3], cmap_4.N)
lat = (-1) * (np.arange(-29.5, 30.5, 1))
lon = np.arange(0.5, 360.5, 1)
llc_LON = 0.5
urc_LON = 359.5
llc_LAT = -29.5
urc_LAT = 29.5
fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(9, 5))
# Variable 1
m1 = Basemap(projection='cyl', llcrnrlon=llc_LON, urcrnrlon=urc_LON, llcrnrlat=llc_LAT, urcrnrlat=urc_LAT, resolution='c')
m1.drawcoastlines(color='k')
m1.fillcontinents(color='white') # mask land mass
lons, lats = np.meshgrid(lon,lat)
x, y = m1(lons,lats)
m1.pcolor(x, y, B_plot[0], cmap=cmap_1, norm=norm_B[0])
img_1 = m1.pcolor(x, y, B_plot[0], cmap=cmap_1, norm=norm_B[0])
axes[0, 0].set_title('Variable 1')
axes[0, 0].set_xlim(llc_LON, urc_LON)
axes[0, 0].set_xticks([0, 45, 90, 135, 180, 225, 270, 315, 360], ['0', '45E', '90E', '135E', '180', '135W', '90W', '45W', '0']) # 0E to 360E
axes[0, 0].set_ylim(llc_LAT, urc_LAT)
axes[0, 0].set_yticks([-30, -15, 0, 15, 30], ['30S', '15S', '0', '15N', '30N']) # 30S to 30N
axes[0, 0].set_ylabel('Latitude')
plt.grid()
# Variable 2
m2 = Basemap(projection='cyl', llcrnrlon=llc_LON, urcrnrlon=urc_LON, llcrnrlat=llc_LAT, urcrnrlat=urc_LAT, resolution='c')
m2.drawcoastlines(color='k')
m2.fillcontinents(color='white') # mask land mass
lons, lats = np.meshgrid(lon,lat)
x, y = m2(lons,lats)
m2.pcolor(x, y, B_plot[1], cmap=cmap_2, norm=norm_B[1])
img_2 = m2.pcolor(x, y, B_plot[1], cmap=cmap_2, norm=norm_B[1])
axes[0, 1].set_title('Variable 2')
axes[0, 1].set_xlim(llc_LON, urc_LON)
axes[0, 1].set_xticks([0, 45, 90, 135, 180, 225, 270, 315, 360], ['0', '45E', '90E', '135E', '180', '135W', '90W', '45W', '0']) # 0E to 360E
axes[0, 1].set_ylim(llc_LAT, urc_LAT)
axes[0, 1].set_yticks([-30, -15, 0, 15, 30], ['30S', '15S', '0', '15N', '30N']) # 30S to 30N
plt.grid()
# Variable 3
m3 = Basemap(projection='cyl', llcrnrlon=llc_LON, urcrnrlon=urc_LON, llcrnrlat=llc_LAT, urcrnrlat=urc_LAT, resolution='c')
m3.drawcoastlines(color='k')
m3.fillcontinents(color='white') # mask land mass
lons, lats = np.meshgrid(lon,lat)
x, y = m3(lons,lats)
m3.pcolor(x, y, B_plot[2], cmap=cmap_3, norm=norm_B[2])
img_3 = m3.pcolor(x, y, B_plot[2], cmap=cmap_3, norm=norm_B[2])
axes[1, 0].set_title('Variable 3')
axes[1, 0].set_xlim(llc_LON, urc_LON)
axes[1, 0].set_xticks([0, 45, 90, 135, 180, 225, 270, 315, 360], ['0', '45E', '90E', '135E', '180', '135W', '90W', '45W', '0']) # 0E to 360E
axes[1, 0].set_ylim(llc_LAT, urc_LAT)
axes[1, 0].set_yticks([-30, -15, 0, 15, 30], ['30S', '15S', '0', '15N', '30N']) # 30S to 30N
axes[1, 0].set_ylabel('Latitude')
plt.grid()
# Variable 4
m4 = Basemap(projection='cyl', llcrnrlon=llc_LON, urcrnrlon=urc_LON, llcrnrlat=llc_LAT, urcrnrlat=urc_LAT, resolution='c')
m4.drawcoastlines(color='k')
m4.fillcontinents(color='white') # mask land mass
lons, lats = np.meshgrid(lon,lat)
x, y = m4(lons,lats)
m4.pcolor(x, y, B_plot[3], cmap=cmap_4, norm=norm_B[3])
img_4 = m4.pcolor(x, y, B_plot[3], cmap=cmap_4, norm=norm_B[3])
axes[1, 1].set_title('Variable 4')
axes[1, 1].set_xlim(llc_LON, urc_LON)
axes[1, 1].set_xticks([0, 45, 90, 135, 180, 225, 270, 315, 360], ['0', '45E', '90E', '135E', '180', '135W', '90W', '45W', '0']) # 0E to 360E
axes[1, 1].set_ylim(llc_LAT, urc_LAT)
axes[1, 1].set_yticks([-30, -15, 0, 15, 30], ['30S', '15S', '0', '15N', '30N']) # 30S to 30N
plt.grid()
plt.subplots_adjust(bottom=0.1, hspace=0.2)
colorbar_1 = fig.add_axes([0.1, 0.48, 0.30, 0.015])
fig.colorbar(img_1, cax=colorbar_1, orientation="horizontal", label='Unit 1', ticks=[291, 293, 295, 297, 299, 301, 303, 305])
colorbar_2 = fig.add_axes([0.55, 0.48, 0.30, 0.015])
fig.colorbar(img_2, cax=colorbar_2, orientation="horizontal", label='Unit 2', ticks=[-100, -80, -60, -40, -20, 0, 20, 40, 60, 80, 100])
plt.subplots_adjust(bottom=0.05, right=0.80, left=0.21, hspace=0.2)
colorbar_3 = fig.add_axes([0.1, 0.08, 0.30, 0.015])
fig.colorbar(img_3, cax=colorbar_3, orientation="horizontal", label='Unit 3', ticks=[-50, -45, -40, -35, -30, -25, 20, -15, -10])
colorbar_4 = fig.add_axes([0.55, 0.08, 0.30, 0.015])
fig.colorbar(img_4, cax=colorbar_4, orientation="horizontal", label='Unit 4', ticks=[0, 5, 10, 15, 20, 25, 30, 35, 40, 45])
plt.show()
1 个答案:
答案 0 :(得分：2)
主要问题是如何定义plotbar。在这里，我使用for循环中的当前轴来执行此操作。另外，未显示xthick，要显示它们，我使用了set_xticklabels。
然后，我清理了您的代码，因为您大部分时间都在做同一件事的四倍。
import math
import matplotlib.cm as cm
import matplotlib.colors as colors
import matplotlib.image as mpimg
import matplotlib as mpl
import matplotlib.pyplot as plt
from mpl_toolkits.basemap import Basemap
import numpy.ma as ma
import numpy as np
import pylab
# Create Variables:
B = np.array([np.random.randint(16, size=(60, 360)) + 291,
np.random.randint(201, size=(60, 360)) - 100,
np.random.randint(56, size=(60, 360)) - 50,
np.random.randint(46, size=(60, 360))])
# Colorbar Boundary Definitions:
cmap = [cm.jet, cm.BrBG, cm.hot, cm.CMRmap_r]
B_plot = np.ma.array(B, mask=np.isnan(B))
norm_B = []
bounds_B = [np.arange(291, 306, 1),
np.arange(-100, 110, 10),
np.arange(-50, -7.5, 2.5),
np.arange(0, 47.5, 2.5)]
for b in np.arange(4):
norm_B.append(mpl.colors.BoundaryNorm(bounds_B[b], cmap[b].N))
lat = (-1) * (np.arange(-29.5, 30.5, 1))
lon = np.arange(0.5, 360.5, 1)
llc_LON = 0.5
urc_LON = 359.5
llc_LAT = -29.5
urc_LAT = 29.5
fig, axes = plt.subplots(nrows=2, ncols=2, figsize=(9, 5))
thicks = [[291, 293, 295, 297, 299, 301, 303, 305],
[-100, -80, -60, -40, -20, 0, 20, 40, 60, 80, 100],
[-50, -45, -40, -35, -30, -25, 20, -15, -10],
[0, 5, 10, 15, 20, 25, 30, 35, 40, 45]]
lons, lats = np.meshgrid(lon, lat)
for row_ind in range(2):
for col_ind in range(2):
index = row_ind*2+col_ind
current_ax = axes[row_ind, col_ind]
print("row_ind: {0} col_ind: {1} index: {2}".format(row_ind, col_ind, index))
map = Basemap(projection='cyl', llcrnrlon=llc_LON, urcrnrlon=urc_LON,
llcrnrlat=llc_LAT, urcrnrlat=urc_LAT, resolution='c',
ax=current_ax)
map.drawcoastlines(color='k')
map.fillcontinents(color='white') # mask land mass
x, y = map(lons, lats)
img_colors = map.pcolor(x, y, B_plot[index], cmap=cmap[index], norm=norm_B[index])
fig.colorbar(img_colors, ax=current_ax, orientation="horizontal",
label='Unit ' + str(index+1), ticks=thicks[index])
current_ax.set_title('Variable ' + str(index+1))
current_ax.set_xlim(llc_LON, urc_LON)
current_ax.set_xticks([0, 45, 90, 135, 180, 225, 270, 315, 360])
current_ax.set_xticklabels(['0', '45E', '90E', '135E', '180', '135W', '90W', '45W', '0']) # 0E to 360E
current_ax.set_ylim(llc_LAT, urc_LAT)
current_ax.set_yticks([-30, -15, 0, 15, 30]) # 30S to 30N
current_ax.set_yticklabels(['30S', '15S', '0', '15N', '30N'])
current_ax.set_ylabel('Latitude')
fig.suptitle('My maps')
plt.show()
相关问题
最新问题
- 我写了这段代码，但我无法理解我的错误
- 我无法从一个代码实例的列表中删除 None 值，但我可以在另一个实例中。为什么它适用于一个细分市场而不适用于另一个细分市场？
- 是否有可能使 loadstring 不可能等于打印？卢阿
- java中的random.expovariate()
- Appscript 通过会议在 Google 日历中发送电子邮件和创建活动
- 为什么我的 Onclick 箭头功能在 React 中不起作用？
- 在此代码中是否有使用“this”的替代方法？
- 在 SQL Server 和 PostgreSQL 上查询，我如何从第一个表获得第二个表的可视化
- 每千个数字得到
- 更新了城市边界 KML 文件的来源？