使用相同数据在matlab和R中绘制不同的图

你好，我用相同的数据写了两个程序。一个在R中，另一个在matlab中，但是当我运行这两个程序时，我在图中得到了不同的结果

R中的代码如下所示

c2 = 1660
p1 = 1000
p2 = 1200
f = 500
w = 2 *pi * f
k1 = w / c1
k2 = w / c2


th1 = seq( 0,89, 0.5)
th1 = th1 * pi / 180
th2 = asin( pmin(pmax((c2 / c1) * sin (th1),-1.0),1.0) )
kz1 = k1 * cos(th1)
kz2 = k2 * cos(th2)
Tp = (2 * kz1 * p1) / (kz1 * p2 + kz2 * p1)
MetroTp=abs(Tp)
th1=th1*180/pi
th1 = seq( 0,89, 0.5)
plot(th1 , MetroTp, type = "l", xlab="Angle of Incidence (Deg)", ylab="|Tp|")
title(main="Transmition Coefficient")

print(MetroTp) 

MetroTp打印和绘图的结果如下：

$Rscript main.r
  [1] 0.9507446 0.9507481 0.9507585 0.9507760 0.9508005 0.9508320 0.9508706
  [8] 0.9509163 0.9509690 0.9510290 0.9510961 0.9511704 0.9512520 0.9513410
 [15] 0.9514374 0.9515413 0.9516528 0.9517718 0.9518987 0.9520333 0.9521758
 [22] 0.9523264 0.9524852 0.9526521 0.9528275 0.9530114 0.9532040 0.9534053
 [29] 0.9536157 0.9538352 0.9540639 0.9543022 0.9545502 0.9548080 0.9550759
 [36] 0.9553542 0.9556430 0.9559426 0.9562533 0.9565753 0.9569088 0.9572543
 [43] 0.9576120 0.9579823 0.9583654 0.9587617 0.9591716 0.9595955 0.9600339
 [50] 0.9604870 0.9609555 0.9614397 0.9619401 0.9624574 0.9629919 0.9635444
 [57] 0.9641154 0.9647054 0.9653153 0.9659457 0.9665974 0.9672711 0.9679676
 [64] 0.9686878 0.9694326 0.9702030 0.9710000 0.9718246 0.9726780 0.9735614
 [71] 0.9744761 0.9754233 0.9764045 0.9774213 0.9784751 0.9795678 0.9807010
 [78] 0.9818768 0.9830972 0.9843643 0.9856805 0.9870482 0.9884702 0.9899492
 [85] 0.9914883 0.9930908 0.9947601 0.9965001 0.9983148 1.0002086 1.0021863
 [92] 1.0042529 1.0064141 1.0086758 1.0110446 1.0135277 1.0161329 1.0188687
 [99] 1.0217445 1.0247706 1.0279584 1.0313203 1.0348705 1.0386241 1.0425987
[106] 1.0468134 1.0512900 1.0560530 1.0611301 1.0665530 1.0723579 1.0785865
[113] 1.0852873 1.0925167 1.1003412 1.1088398 1.1181072 1.1282585 1.1394351
[120] 1.1518138 1.1656194 1.1811444 1.1987796 1.2190650 1.2427798 1.2711160
[127] 1.3060537 1.3513290 1.4157978 1.5382863 1.6666667 1.6666667 1.6666667
[134] 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667
[141] 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667
[148] 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667
[155] 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667
[162] 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667
[169] 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667 1.6666667
[176] 1.6666667 1.6666667 1.6666667 1.6666667

现在我在matlab中运行相同的代码 代码如下：

clear all;
clc;

c1=1500;
c2=1660;
p1=1000;
p2=1200;
f=500;
w=2*pi*f;
k1=w/c1;
k2=w/c2;
 
m=1;
for l=1:0.5:90
    
th1=(l-1)*pi/180;
th2=asin((((c2/c1)*sin(th1))));
kz1=k1*cos(th1);
kz2=k2*cos(th2);

Tp=(2*kz1*p1)/(kz1*p2+kz2*p1);
yy(m)=abs(Tp)
m=m+1;

end

plot(0:0.5:89,yy,'-')
title('Transmition Coefficient')
xlabel('Angle of Incidence(Deg)'), ylabel('|Tp|')
axis([0,90])

结果和我的图如下 对于yy（m）

情节是

我们可以看到，在matlab中，1.666之后，绘图中的直线开始减小其值，但在R中，1.666之后的直线保持稳定

我应该在R中写些什么来修复matlab中相同的绘图

 Columns 1 through 7

    0.9507    0.9507    0.9508    0.9508    0.9508    0.9508    0.9509

  Columns 8 through 14

    0.9509    0.9510    0.9510    0.9511    0.9512    0.9513    0.9513

  Columns 15 through 21

    0.9514    0.9515    0.9517    0.9518    0.9519    0.9520    0.9522

  Columns 22 through 28

    0.9523    0.9525    0.9527    0.9528    0.9530    0.9532    0.9534

  Columns 29 through 35

    0.9536    0.9538    0.9541    0.9543    0.9546    0.9548    0.9551

  Columns 36 through 42

    0.9554    0.9556    0.9559    0.9563    0.9566    0.9569    0.9573

  Columns 43 through 49

    0.9576    0.9580    0.9584    0.9588    0.9592    0.9596    0.9600

  Columns 50 through 56

    0.9605    0.9610    0.9614    0.9619    0.9625    0.9630    0.9635

  Columns 57 through 63

    0.9641    0.9647    0.9653    0.9659    0.9666    0.9673    0.9680

  Columns 64 through 70

    0.9687    0.9694    0.9702    0.9710    0.9718    0.9727    0.9736

  Columns 71 through 77

    0.9745    0.9754    0.9764    0.9774    0.9785    0.9796    0.9807

  Columns 78 through 84

    0.9819    0.9831    0.9844    0.9857    0.9870    0.9885    0.9899

  Columns 85 through 91

    0.9915    0.9931    0.9948    0.9965    0.9983    1.0002    1.0022

  Columns 92 through 98

    1.0043    1.0064    1.0087    1.0110    1.0135    1.0161    1.0189

  Columns 99 through 105

    1.0217    1.0248    1.0280    1.0313    1.0349    1.0386    1.0426

  Columns 106 through 112

    1.0468    1.0513    1.0561    1.0611    1.0666    1.0724    1.0786

  Columns 113 through 119

    1.0853    1.0925    1.1003    1.1088    1.1181    1.1283    1.1394

  Columns 120 through 126

    1.1518    1.1656    1.1811    1.1988    1.2191    1.2428    1.2711

  Columns 127 through 133

    1.3061    1.3513    1.4158    1.5383    1.6511    1.6292    1.6069

  Columns 134 through 140

    1.5841    1.5609    1.5371    1.5129    1.4882    1.4631    1.4374

  Columns 141 through 147

    1.4112    1.3845    1.3574    1.3297    1.3015    1.2728    1.2436

  Columns 148 through 154

    1.2139    1.1837    1.1529    1.1217    1.0900    1.0578    1.0251

  Columns 155 through 161

    0.9919    0.9582    0.9240    0.8894    0.8544    0.8189    0.7830

  Columns 162 through 168

    0.7466    0.7099    0.6727    0.6352    0.5974    0.5592    0.5206

  Columns 169 through 175

    0.4818    0.4427    0.4033    0.3637    0.3238    0.2838    0.2436

  Columns 176 through 179

    0.2032    0.1627    0.1221    0.0815