我试着在嵌入的图中做一个缩放:

代码的第一部分正在工作,即绘制文件。只有当我试图绘制缩放部分,它给出了以下错误,我试图找出它,但没有一个帖子真的有用。
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I am trying to do a zoomed in inset plot like the image:

The first part of the code is working i.e. it is plotting the file. Only when I try to plot the zoomed part it gives the following error I have trying to figure it out but none of the posts have been really helpful.

AttributeError Traceback (most recent call last)
in ()
44 plt.close()
45
—> 46 fit_data()

in fit_data()
16 #axins.xaxis.set_major_locator(MaxNLocator(nbins=1, prune=‘lower’))
17
—> 18 plt1 = zoomed_inset_axes(plt, 2.5, loc=4 )
19 plt1.plot(data1[‘pm’], data1[‘Dis(pc)’])#,marker=‘o’, color=‘red’, edgecolor=‘red’, s=100)
20 plt1.axis([5.062645643, 6.482765605, 487.026819, 569.4313421])

~/anaconda3/lib/python3.6/site-packages/mpl_toolkits/axes_grid1/inset_locator.py in zoomed_inset_axes(parent_axes, zoom, loc, bbox_to_anchor, bbox_transform, axes_class, axes_kwargs, borderpad)
529
530 if axes_kwargs is None:
–> 531 inset_axes = axes_class(parent_axes.figure, parent_axes.get_position())
532 else:
533 inset_axes = axes_class(parent_axes.figure, parent_axes.get_position(),

AttributeError: module ‘matplotlib.pyplot’ has no attribute ‘get_position’
这是我一直使用的代码。
import numpy as np
import matplotlib as mpl
import pandas as pd
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator
from matplotlib.colors import ListedColormap, LinearSegmentedColormap
from matplotlib.ticker import MaxNLocator
from mpl_toolkits.axes_grid1.inset_locator import zoomed_inset_axes, mark_inset

file1 = ‘inset_trial.dat’

data1 = pd.read_csv(file1, delimiter=’\s+’, header=None, engine=‘python’)
data1.columns = [‘x1’, ‘y1’, ‘xin’, ‘yin’]

def fit_data():

fig = plt.figure(1,figsize=(12,12))

plt.subplot(111)
mpl.rcParams['figure.dpi']=200
plt.scatter(data1['x1'], data1['y1'],  marker='o', color='red', edgecolor='red', s=100)

plt1 = zoomed_inset_axes(plt, 2.5,  loc=4 )
plt1.plot(data1['xin'], data1['yin'])#,marker='o', color='blue', edgecolor='blue', s=100)
plt1.axis([5.062645643, 6.482765605, 487.026819, 569.4313421])
plt1.set_yticks([])
plt1.set_xticks([])
plt1.set_axis_bgcolor('none')
axes = mark_inset(axins, axins_2, loc1=2, loc2=4, fc="none", ec="0.5")

plt.minorticks_on()

plt.tick_params(axis=‘both’,which=‘minor’,length=5,width=2,labelsize=28)
plt.tick_params(axis=‘both’,which=‘major’,length=8,width=2,labelsize=28)
plt.tick_params(direction=‘out’, length=8, width=3)
plt.tick_params(labelsize=28)

plt.show()
plt.close()

fit_data()
我一直试图拟合的样本数据是
797.3266855 9.518953577 487.026819 6.41595323
457.3328822 9.408619701 493.8012816 6.352140859
321.4279994 10.99152002 505.8109589 6.482765605
643.1595144 11.33567151 515.0500793 5.689992589
897.9396964 7.098272377 523.5118663 5.062645643
658.5927932 8.401072532 526.8570713 5.951114622
885.8478465 9.59502937 537.6740407 6.123622699
569.4313421 5.913067314 563.2567733 6.089519297
419.540411 31.7279367 569.4313421 5.913067314
386.0084504 13.82448229
487.026819 6.41595323
790.5056852 14.17210085
736.5781168 4.142827023
927.9643155 13.42713535
106.249016 49.12866299
678.4950877 3.174864242
108.0434865 60.24915209
809.8782024 8.371119015
692.3002948 7.215181213
915.4764187 15.4360679
874.5699615 8.706973258
962.0774108 3.223371528
401.4037586 31.03032051
671.4700933 11.1975808
834.7473745 15.30785654

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转载自blog.csdn.net/weixin_43198791/article/details/82772733
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