二维轮廓 plot 使用 Python 中的数据文件
[英]2D contour plot using a data file in Python
问题描述
I have a data file which comprises of 5 rows and 4642 columns.
我有一个包含 5 行和 4642 列的数据文件。 I wanted to create a contour file using 2,3 and 5 row.我想使用 2,3 和 5 行创建一个轮廓文件。 I tried to write a simple code of Python which looks like:我尝试编写一个简单的 Python 代码，如下所示：
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import math
df = pd.read_csv('inlet_v.csv', skiprows=1, header = None)
tt = plt.contourf(df.iloc[:,1], df.iloc[:,2], df.iloc[:,4])
plt.show()
But as expected that since the "z" or 3rd entry in the data is not 2D thus it is throwing and error which says:但正如预期的那样，由于数据中的“z”或第三个条目不是 2D 的，因此它会抛出错误并显示：
tt = plt.contourf(df.iloc[:,1], df.iloc[:,2], df.iloc[:,4])
TypeError: Input z must be a 2D array.
Any comment/suggestion will be a great help.任何评论/建议都会有很大帮助。 The data looks like:数据如下：
0 0.02 0 0.12674 5.4805E-05
0 0.021 0 0.12674 5.7583E-05
0 0.02 0.03 0.12674 2.1107E-05
0 0.021 0.03 0.12674 2.2177E-05
0 0.02098 0 0.12674 0.00011227
0 0.02096 0 0.12674 0.00022133
0 0.02094 0 0.12674 0.00032951
0 0.02092 0 0.12674 0.00043639
0 0.0209 0 0.12674 0.00054155
0 0.02088 0 0.12674 0.00064457
0 0.02086 0 0.12674 0.00074506
0 0.02084 0 0.12674 0.00084261
0 0.02082 0 0.12674 0.00093683
0 0.0208 0 0.12674 0.0010274
0 0.02078 0 0.12674 0.0011138
0 0.02076 0 0.12674 0.0011959
0 0.02074 0 0.12674 0.0012733
0 0.02072 0 0.12674 0.0013457
0 0.0207 0 0.12674 0.0014127
0 0.02068 0 0.12674 0.0014742
0 0.02066 0 0.12674 0.0015299
0 0.02064 0 0.12674 0.0015795
0 0.02062 0 0.12674 0.0016229
0 0.0206 0 0.12674 0.0016599
0 0.02058 0 0.12674 0.0016904
0 0.02056 0 0.12674 0.0017142
0 0.02054 0 0.12674 0.0017312
0 0.02052 0 0.12674 0.0017414
0 0.0205 0 0.12674 0.0017448
0 0.02048 0 0.12674 0.0017413
0 0.02046 0 0.12674 0.0017309
0 0.02044 0 0.12674 0.0017137
0 0.02042 0 0.12674 0.0016897
0 0.0204 0 0.12674 0.0016591
0 0.02038 0 0.12674 0.0016219
0 0.02036 0 0.12674 0.0015783
0 0.02034 0 0.12674 0.0015285
0 0.02032 0 0.12674 0.0014727
0 0.0203 0 0.12674 0.0014111
0 0.02028 0 0.12674 0.0013439
0 0.02026 0 0.12674 0.0012714
0 0.02024 0 0.12674 0.0011939
0 0.02022 0 0.12674 0.0011117
0 0.0202 0 0.12674 0.0010251
0 0.02018 0 0.12674 0.00093448
0 0.02016 0 0.12674 0.00084017
0 0.02014 0 0.12674 0.00074254
0 0.02012 0 0.12674 0.00064199
0 0.0201 0 0.12674 0.00053891
0 0.02008 0 0.12674 0.0004337
0 0.02006 0 0.12674 0.00032678
0 0.02004 0 0.12674 0.00021857
0 0.02002 0 0.12674 0.0001095
0 0.02002 0.03 0.12674 4.2172E-05
0 0.02004 0.03 0.12674 8.4178E-05
0 0.02006 0.03 0.12674 0.00012585
0 0.02008 0.03 0.12674 0.00016703
0 0.0201 0.03 0.12674 0.00020755
0 0.02012 0.03 0.12674 0.00024725
0 0.02014 0.03 0.12674 0.00028598
0 0.02016 0.03 0.12674 0.00032358
0 0.02018 0.03 0.12674 0.0003599
0 0.0202 0.03 0.12674 0.0003948
0 0.02022 0.03 0.12674 0.00042815
0 0.02024 0.03 0.12674 0.00045981
0 0.02026 0.03 0.12674 0.00048966
0 0.02028 0.03 0.12674 0.00051757
0 0.0203 0.03 0.12674 0.00054345
0 0.02032 0.03 0.12674 0.00056718
0 0.02034 0.03 0.12674 0.00058868
0 0.02036 0.03 0.12674 0.00060786
0 0.02038 0.03 0.12674 0.00062463
0 0.0204 0.03 0.12674 0.00063895
0 0.02042 0.03 0.12674 0.00065075
0 0.02044 0.03 0.12674 0.00065998
0 0.02046 0.03 0.12674 0.00066661
0 0.02048 0.03 0.12674 0.00067061
0 0.0205 0.03 0.12674 0.00067197
0 0.02052 0.03 0.12674 0.00067068
0 0.02054 0.03 0.12674 0.00066675
0 0.02056 0.03 0.12674 0.00066018
0 0.02058 0.03 0.12674 0.00065102
0 0.0206 0.03 0.12674 0.00063928
0 0.02062 0.03 0.12674 0.00062503
0 0.02064 0.03 0.12674 0.00060831
0 0.02066 0.03 0.12674 0.00058919
0 0.02068 0.03 0.12674 0.00056776
0 0.0207 0.03 0.12674 0.00054408
0 0.02072 0.03 0.12674 0.00051825
0 0.02074 0.03 0.12674 0.00049039
0 0.02076 0.03 0.12674 0.00046059
0 0.02078 0.03 0.12674 0.00042897
0 0.0208 0.03 0.12674 0.00039567
0 0.02082 0.03 0.12674 0.0003608
0 0.02084 0.03 0.12674 0.00032451
0 0.02086 0.03 0.12674 0.00028694
0 0.02088 0.03 0.12674 0.00024825
0 0.0209 0.03 0.12674 0.00020857
0 0.02092 0.03 0.12674 0.00016807
0 0.02094 0.03 0.12674 0.0001269
0 0.02096 0.03 0.12674 8.524E-05
0 0.02098 0.03 0.12674 4.324E-05
0 0.02 0.00033333 0.12674 6.2219E-05
0 0.02 0.00066667 0.12674 6.1847E-05
0 0.02 0.001 0.12674 3.3238E-05
0 0.02 0.0013333 0.12674 -1.1494E-05
0 0.02 0.0016667 0.12674 -5.0586E-05
0 0.02 0.002 0.12674 -6.5667E-05
0 0.02 0.0023333 0.12674 -5.2608E-05
0 0.02 0.0026667 0.12674 -2.3248E-05
0 0.02 0.003 0.12674 2.9907E-06
0 0.02 0.0033333 0.12674 1.1943E-05
0 0.02 0.0036667 0.12674 3.5166E-06
0 0.02 0.004 0.12674 -9.2539E-06
0 0.02 0.0043333 0.12674 -1.0113E-05
0 0.02 0.0046667 0.12674 8.3196E-06
0 0.02 0.005 0.12674 3.8492E-05
0 0.02 0.0053333 0.12674 6.2114E-05
0 0.02 0.0056667 0.12674 6.1961E-05
0 0.02 0.006 0.12674 3.3541E-05
0 0.02 0.0063333 0.12674 -1.1146E-05
0 0.02 0.0066667 0.12674 -5.0363E-05
0 0.02 0.007 0.12674 -6.5664E-05
0 0.02 0.0073333 0.12674 -5.2792E-05
0 0.02 0.0076667 0.12674 -2.3484E-05
0 0.02 0.008 0.12674 2.8461E-06
0 0.02 0.0083333 0.12674 1.195E-05
0 0.02 0.0086667 0.12674 3.6189E-06
0 0.02 0.009 0.12674 -9.184E-06
0 0.02 0.0093333 0.12674 -1.0179E-05
0 0.02 0.0096667 0.12674 8.1163E-06
0 0.02 0.01 0.12674 3.8261E-05
0 0.02 0.010333 0.12674 6.2008E-05
0 0.02 0.010667 0.12674 6.2074E-05
0 0.02 0.011 0.12674 3.3842E-05
0 0.02 0.011333 0.12674 -1.0798E-05
0 0.02 0.011667 0.12674 -5.0139E-05
0 0.02 0.012 0.12674 -6.566E-05
0 0.02 0.012333 0.12674 -5.2975E-05
0 0.02 0.012667 0.12674 -2.372E-05
0 0.02 0.013 0.12674 2.7004E-06
0 0.02 0.013333 0.12674 1.1957E-05
0 0.02 0.013667 0.12674 3.721E-06
0 0.02 0.014 0.12674 -9.1134E-06
0 0.02 0.014333 0.12674 -1.0244E-05
0 0.02 0.014667 0.12674 7.9138E-06
0 0.02 0.015 0.12674 3.803E-05
0 0.02 0.015333 0.12674 6.1901E-05
0 0.02 0.015667 0.12674 6.2186E-05
1 个解决方案
解决方案1
0 2021-05-28 08:37:31
Using @JohanC ( https://stackoverflow.com/users/12046409/johanc ) comment I could now plot it correctly, the code looks like:使用@JohanC ( https://stackoverflow.com/users/12046409/johanc ) 评论我现在可以正确使用 plot 它，代码如下所示：
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import math
df = pd.read_csv('inlet_v.csv', skiprows=1, header = None)
plt.figure(1)
tt = plt.tricontourf(df.iloc[:,2], df.iloc[:,1], df.iloc[:,4], cmap="jet")
plt.show()
The corresponding plot looks like the attached figure.对应的plot如附图。 Thanks again @JohanC for your kind help.再次感谢@JohanC 的帮助。
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