python - Pyplot:在右侧以相同的比例添加特定的附加刻度和标签
问题描述
我想在右侧为列表“all_values”中的值添加刻度和标签。我不想在左侧添加这些值,因为它会在 yaxis 上与我的基本刻度重叠。我怎样才能添加这些值。这是我的情节中的代码(我根据下面更短且完全英文的评论更改了代码):
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter
materials = {'42CrMo4 nitrocarburiert DNV': {'N_stat': 1e5, 'N_1': 1e5, 'N_D': 2e6, 'S_stat': 1240, 'S_1': 1240, 'S_D': 1030}}
N_stat_values = []
S_stat_values = []
S_D_values = []
for material in materials:
N = [1, materials[material]['N_stat'], materials[material]['N_1'], materials[material]['N_D'], 1e10]
stress = [materials[material]['S_stat'], materials[material]['S_stat'], materials[material]['S_1'], materials[material]['S_D'], materials[material]['S_D']]
N_stat_values.append(materials[material]['N_stat'])
S_stat_values.append(materials[material]['S_stat'])
S_D_values.append(materials[material]['S_D'])
plt.loglog(N, stress)
all_values = list(set(S_stat_values + S_D_values))
ax = plt.gca()
ax.yaxis.set_major_formatter(ScalarFormatter())
plt.yticks(np.arange(1000, 1400, 100))
plt.grid(True, which='major',linewidth=0.5)
plt.grid(True, which='minor', linestyle='--', linewidth=0.3)
plt.xlim(np.min(N_stat_values)/10, 1e10)
给出下图: 先试试
现在我想从列表 all_values 的右侧添加刻度和标签。我试图遵循 ImportanceOfBeingErnest 的提示:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter
materials = {'42CrMo4 nitrocarburiert DNV': {'N_stat': 1e5, 'N_1': 1e5, 'N_D': 2e6, 'S_stat': 1240, 'S_1': 1240, 'S_D': 1030}}
N_stat_values = []
S_stat_values = []
S_D_values = []
for material in materials:
N = [1, materials[material]['N_stat'], materials[material]['N_1'], materials[material]['N_D'], 1e10]
stress = [materials[material]['S_stat'], materials[material]['S_stat'], materials[material]['S_1'], materials[material]['S_D'], materials[material]['S_D']]
N_stat_values.append(materials[material]['N_stat'])
S_stat_values.append(materials[material]['S_stat'])
S_D_values.append(materials[material]['S_D'])
plt.loglog(N, stress)
all_values = list(set(S_stat_values + S_D_values))
ax = plt.gca()
ax.yaxis.set_major_formatter(ScalarFormatter())
ax.set_yticks(np.arange(1000, 1400, 100))
ax2 = ax.twinx()
ax2.set_yscale('log')
ax2.yaxis.set_major_formatter(ScalarFormatter())
ax2.set_yticks(all_values)
plt.grid(True, which='major',linewidth=0.5)
plt.grid(True, which='minor', linestyle='--', linewidth=0.3)
plt.xlim(np.min(N_stat_values)/10, 1e10)
但我没有得到想要的结果,右侧的刻度线位置错误,x 轴上的小刻度线消失了: 下次尝试
解决方案
有了最新的评论,我能够得到我想要的输出:
import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import ScalarFormatter
materials = {'42CrMo4 nitrocarburiert DNV': {'N_stat': 1e5, 'N_1': 1e5, 'N_D': 2e6, 'S_stat': 1240, 'S_1': 1240, 'S_D': 1030}}
N_stat_werte = []
S_stat_werte = []
S_D_werte = []
for material in materials:
N = [1, materials[material]['N_stat'], materials[material]['N_1'], materials[material]['N_D'], 1e10]
stress = [materials[material]['S_stat'], materials[material]['S_stat'], materials[material]['S_1'], materials[material]['S_D'], materials[material]['S_D']]
N_stat_values.append(materials[material]['N_stat'])
S_stat_values.append(materials[material]['S_stat'])
S_D_values.append(materials[material]['S_D'])
plt.loglog(N, stress)
all_values = list(set(S_stat_values + S_D_values))
ax = plt.gca()
ax.yaxis.set_major_formatter(ScalarFormatter())
ax.set_ylim(1000, 1300)
ax.set_yticks(np.arange(1000, 1400, 100))
ax.grid(True, which='major',linewidth=0.5)
ax.grid(True, which='minor', linestyle='--', linewidth=0.3)
ax2 = ax.twinx()
ax2.set_yscale('log')
ax2.yaxis.set_major_formatter(ScalarFormatter())
ax2.set_yticks(all_values)
ax2.set_ylim(1000, 1300)
ax2.grid(True, which='major',linewidth=0.5)
plt.xlim(np.min(N_stat_values)/10, 1e10)
plt.show()
它看起来像这样: