How can I make a better plot?

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Hi, I have 5 sets of data and I want to write a script that reads my 5 matrices (1x21 double) and displays a single figure that plots the mean error (y) against the gain (x) in decibel. The output of my script should has:
  • The lines for each segment should be displayed using a different color. With point where is the value on the segment.
  • A legend should be included indicating wich line corresponds to wich segment
  • Each segment should has his linear fit (courve fitting) in wich I can find the ratio between the axes
I think I have to use iteraction for a solution of this kind, but I'm not sure how.
These are my 5 data:
err20 = [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1.08935539299999,2.06473429585112,5.31643514302866,12.1807063663099,23.4911626896201,37.8143988479465,53.0667200958471];
err40 = [1,1,1,1,1,1,1.00980392156863,1.21923952036955,1.83719863383950,3.35132045800776,6.15310998083444,10.4540779879203,16.3935058175317,24.4567825083250,34.2731876493287,44.8404803207833,56.1569894419756,67.9621753642978,80.3418716316936,92.6177152673935,105.509145868874];
err60 = [1.39130582788671,2.06089077044959,3.06870791245791,4.79824204787542,7.43102274858528,11.1839078762097,15.8879812010210,21.5982089544676,28.3128632729741,36.0451923666447,44.3639384800055,53.0905553702049,62.0750621155379,70.5611743877611,79.2822679481440,87.4151859346590,95.2561517964825,102.939651014533,111.592224212783,119.481125788707,128.101212449710];
err80 = [17.4311417284922,22.2395558126501,27.9265106941469,34.2412676054684,40.8661898327012,47.9425873245325,55.0569858602196,62.0452743182326,68.6517414695066,75.0178392624680,81.3553772590478,87.8836526599804,93.1726477983694,99.2482660012320,104.954811955097,110.618897123263,116.985855082487,123.136684599450,129.996356750259,137.015229368536,144.682941495957];
err100= [50.0098577942206,55.6474590816719,61.3114187709398,66.7658549295944,72.0226315556860,76.6917932491624,81.7675527655915,86.5206979973362,90.9380438970932,95.6093452209315,99.8809271502719,104.517882995723,109.232695936831,113.888646043589,118.823549750783,124.212683308618,129.481920951591,135.262067967506,141.525996933700,147.328685524455,153.893747639987];

采纳的回答

C B
C B 2021-10-2
编辑:C B 2021-10-3
@Agnese Chini Is this fulfill your requirement?
err20 = [1,1,1,1,1,1,1,1,1,1,1,1,1,1,1.08935539299999,2.06473429585112,5.31643514302866,12.1807063663099,23.4911626896201,37.8143988479465,53.0667200958471];
err40 = [1,1,1,1,1,1,1.00980392156863,1.21923952036955,1.83719863383950,3.35132045800776,6.15310998083444,10.4540779879203,16.3935058175317,24.4567825083250,34.2731876493287,44.8404803207833,56.1569894419756,67.9621753642978,80.3418716316936,92.6177152673935,105.509145868874];
err60 = [1.39130582788671,2.06089077044959,3.06870791245791,4.79824204787542,7.43102274858528,11.1839078762097,15.8879812010210,21.5982089544676,28.3128632729741,36.0451923666447,44.3639384800055,53.0905553702049,62.0750621155379,70.5611743877611,79.2822679481440,87.4151859346590,95.2561517964825,102.939651014533,111.592224212783,119.481125788707,128.101212449710];
err80 = [17.4311417284922,22.2395558126501,27.9265106941469,34.2412676054684,40.8661898327012,47.9425873245325,55.0569858602196,62.0452743182326,68.6517414695066,75.0178392624680,81.3553772590478,87.8836526599804,93.1726477983694,99.2482660012320,104.954811955097,110.618897123263,116.985855082487,123.136684599450,129.996356750259,137.015229368536,144.682941495957];
err100= [50.0098577942206,55.6474590816719,61.3114187709398,66.7658549295944,72.0226315556860,76.6917932491624,81.7675527655915,86.5206979973362,90.9380438970932,95.6093452209315,99.8809271502719,104.517882995723,109.232695936831,113.888646043589,118.823549750783,124.212683308618,129.481920951591,135.262067967506,141.525996933700,147.328685524455,153.893747639987];
gain =1:21;
plot(gain,err20,'redo')
hold on
plot(gain,err40,'green*')
hold on
plot(gain,err60,'blue+')
hold on
plot(gain,err80,'cyanx')
hold on
plot(gain,err100,'magentad')
legend('err20','err40','err60','err80','err100')
ylabel('Error')
xlabel('Gain')
  5 个评论
C B
C B 2021-10-4
Maybe like this
p = polyfit(gain,err100,1) ;
slope5 = p(1)

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