Customized coloring for grouped bar graph - matlab

clear
clc
a = [0.4152 0.4659 0.506 0.5494 0.5676
;0.371 0.4171 0.4649 0.5209 0.5414
;0.2612 0.2681 0.2701 0.2751 0.2811]
b = [0.3976 0.449 0.4951 0.5494 0.5676
;0.342 0.4057 0.4629 0.5701 0.5342
;0.2796 0.2842 0.2911 0.2939 0.2989]
c=[0.3856 0.4397 0.5348 0.5374 0.5562
;0.3352 0.3975 0.4557 0.5087 0.5286
;0.284 0.2928 0.2991 0.301 0.3059]
od = [a,b,c]; % Original Data
d = categorical(["app" "bnn" "orng"]);
d = reordercats(d,{'app' 'bnn' 'orng'});
bar(d,od,'grouped')
Basically I want three different colors (and not shades) for three rows of od.
Please help.
I am using MATLAB R2017(a).

Related

Error using integral (line 85): A and B must be floating-point scalars

I have the following code that I wish to estimate the parameters of a custom distribution using MATLAB's function mle(). For more details on the distribution.
The main code is:
x = [0 0 0 0 0.000649967501624919 0.00569971501424929 0.0251487425628719 0.0693465326733663 0.155342232888356 0.284835758212089 0.458277086145693 0.658567071646418 0.908404579771011 1.17284135793210 1.43977801109945 1.71951402429879 1.98925053747313 2.27553622318884 2.57147142642868 2.80390980450977 3.03829808509575 3.26583670816459 3.45642717864107 3.65106744662767 3.81950902454877 3.98275086245688 4.11259437028149 4.24683765811709 4.35043247837608 4.43832808359582 4.58427078646068 4.62286885655717 4.68361581920904 4.75686215689216 4.80245987700615 4.84005799710015 4.86280685965702 4.91675416229189 4.92725363731813 4.90890455477226 4.96570171491425 4.92315384230789 4.95355232238388 4.92790360481976 4.93135343232838 4.90310484475776 4.90885455727214 4.86765661716914 4.85490725463727 4.81940902954852 4.81450927453627 4.78621068946553 4.74206289685516 4.71791410429479 4.69961501924904 4.65706714664267 4.63611819409030 4.60176991150443 4.57512124393780 4.53507324633768 4.48252587370631 4.47062646867657 4.43127843607820 4.39963001849908 4.37598120093995 4.29548522573871 4.31033448327584 4.21708914554272 4.21913904304785 4.18669066546673 4.16719164041798 4.09774511274436 4.07989600519974 4.02869856507175 3.98485075746213 3.95785210739463 3.93945302734863 3.90240487975601 3.87025648717564 3.81185940702965 3.78461076946153 3.74091295435228 3.71666416679166 3.67276636168192 3.65846707664617 3.61361931903405 3.58712064396780 3.55452227388631 3.53082345882706 3.49197540122994 3.48582570871456 3.46512674366282 3.41227938603070 3.36278186090695 3.35528223588821 3.31238438078096 3.27213639318034 3.23863806809660 3.24173791310434 3.19339033048348 3.20118994050298 3.16489175541223 3.10739463026849 3.09484525773711 3.08094595270237 3.02129893505325 3.02309884505775 2.99375031248438 2.95765211739413 2.93230338483076 2.89560521973901 2.87805609719514 2.85440727963602 2.82285885705715 2.80175991200440 2.79091045447728 2.73901304934753 2.72701364931753 2.73441327933603 2.71646417679116 2.68236588170592 2.65551722413879 2.63356832158392 2.60361981900905 2.58147092645368 2.57697115144243 2.54287285635718 2.53502324883756 2.47702614869257 2.50387480625969 2.46487675616219 2.45722713864307 2.42707864606770 2.41762911854407 2.39823008849558 2.38708064596770 2.34058297085146 2.35613219339033 2.32123393830309 2.30503474826259 2.27613619319034 2.27248637568122 2.25113744312784 2.24908754562272 2.22703864806760 2.20583970801460 2.17244137793110 2.15709214539273 2.16469176541173 2.12139393030348 2.12809359532023 2.11389430528474 2.09774511274436 2.07629618519074 2.07459627018649 2.05394730263487 2.04724763761812 2.01684915754212 2.01684915754212 2.00409979501025 1.98955052247388 1.96540172991350 1.95890205489726 1.93035348232588 1.92295385230738 1.90605469726514 1.89785510724464 1.87070646467677 1.88000599970002 1.86295685215739 1.84420778961052 1.82510874456277 1.80480975951202 1.80785960701965 1.80870956452177 1.77581120943953 1.76771161441928 1.77131143442828 1.76636168191590 1.75081245937703 1.73156342182891 1.69876506174691 1.70836458177091 1.70376481175941 1.67196640167992 1.68101594920254 1.66586670666467 1.66061696915154 1.64296785160742 1.63291835408230 1.62506874656267 1.62516874156292 1.60556972151392 1.59007049647518 1.59187040647968 1.57947102644868 1.57577121143943 1.54527273636318 1.57237138143093 1.54637268136593 1.54802259887006 1.50492475376231 1.52077396130193 1.50417479126044 1.50162491875406 1.50062496875156 1.48957552122394 1.47997600119994 1.47027648617569 1.44452777361132 1.45407729613519 1.44272786360682 1.43247837608120 1.41657917104145 1.40787960601970 1.39323033848308 1.40282985850707 1.39403029848508 1.38233088345583 1.37888105594720 1.37943102844858 1.36183190840458 1.34808259587021 1.34503274836258 1.33703314834258 1.33308334583271 1.32253387330633 1.32698365081746 1.29963501824909 1.30758462076896 1.29103544822759 1.29473526323684 1.27413629318534 1.26858657067147 1.27888605569722 1.26063696815159 1.27863606819659 1.25168741562922 1.23913804309785 1.24788760561972 1.22308884555772 1.24198790060497 1.22133893305335 1.20678966051697 1.20098995050247 1.20343982800860 1.18779061046948 1.19024048797560 1.17194140292985 1.17369131543423 1.16869156542173 1.15814209289536 1.15429228538573 1.15904204789761 1.12774361281936 1.15344232788361 1.13744312784361 1.12909354532273 1.12479376031198 1.11099445027749 1.11469426528674 1.11064446777661 1.10464476776161 1.10309484525774 1.10689465526724 1.07654617269137 1.07884605769712 1.07359632018399 1.06864656767162 1.07544622768862 1.06689665516724 1.04884755762212 1.06164691765412 1.04979751012449 1.04529773511324 1.02839858007100 1.03634818259087 1.01709914504275 1.02089895505225 1.01024948752562 1.01549922503875 1.01319934003300 1.01404929753512 1.00839958002100 0.995400229988501 0.989850507474626 0.978801059947003 0.977551122443878 0.980450977451127 0.975451227438628 0.969201539923004 0.964151792410380 0.964601769911504 0.958802059897005 0.955702214889256 0.948602569871506 0.960751962401880 0.941352932353382 0.928653567321634 0.949002549872506 0.937053147342633 0.913854307284636 0.916204189790510 0.915454227288636 0.902604869756512 0.909454527273636 0.895505224738763 0.898355082245888 0.894455277236138 0.902454877256137 0.883705814709265 0.888405579721014 0.876356182190891 0.881555922203890 0.878156092195390 0.868456577171141 0.870406479676016 0.863906804659767 0.862456877156142 0.858757062146893 0.851307434628269 0.851107444627769 0.833908304584771 0.843507824608770 0.831708414579271 0.836858157092145 0.829058547072646 0.828508574571272 0.822908854557272 0.820508974551273 0.815559222038898 0.819709014549273 0.809609519524024 0.813409329533523 0.800759962001900 0.806609669516524 0.806959652017399 0.792260386980651 0.787660616969152 0.783810809459527 0.794960251987401 0.771061446927654 0.788910554472276 0.789510524473776 0.763061846907655 0.776761161941903 0.767561621918904 0.773611319434028 0.750262486875656 0.765811709414529 0.765911704414779 0.748012599370032 0.741612919354032 0.757312134393280 0.752612369381531 0.741362931853407 0.742212889355532 0.741912904354782 0.743162841857907 0.732963351832408 0.732813359332033 0.733363331833408 0.721913904304785 0.716664166791661 0.726713664316784 0.709764511774411 0.700064996750163 0.710764461776911 0.717664116794160 0.707314634268287 0.707114644267787 0.705614719264037 0.709164541772911 0.696665166741663 0.680765961701915 0.686715664216789 0.694465276736163 0.683015849207540 0.681715914204290 0.694465276736163 0.688615569221539 0.680665966701665 0.672316384180791 0.672866356682166 0.656517174141293 0.665316734163292 0.671566421678916 0.666266686665667 0.652917354132293 0.663366831658417 0.651917404129794 0.663816809159542 0.661366931653417 0.647017649117544 0.655167241637918 0.647867606619669 0.636918154092295 0.645467726613669 0.633118344082796 0.640217989100545 0.634668266586671 0.618669066546673 0.635068246587671 0.632568371581421 0.623118844057797 0.623868806559672 0.623718814059297 0.621368931553422 0.623768811559422 0.608419579021049 0.616019199040048 0.609869506524674 0.606569671516424 0.614019299035048 0.610269486525674 0.596520173991300 0.595570221488926 0.593270336483176 0.596670166491675 0.598470076496175 0.597770111494425 0.593720313984301 0.592770361481926 0.585420728963552 0.580870956452177 0.584120793960302 0.580270986450677 0.577971101444928 0.579021048947553 0.572821358932053 0.585970701464927 0.572921353932303 0.567071646417679 0.569971501424929 0.571271436428179 0.568421578921054 0.567421628918554 0.569521523923804 0.563721813909305 0.558772061396930 0.562171891405430 0.557872106394680 0.549072546372681 0.558722063896805 0.536973151342433 0.561021948902555 0.544172791360432 0.552122393880306 0.553072346382681 0.546222688865557 0.551472426378681 0.540772961351932 0.541122943852807 0.542772861356932 0.530323483825809 0.526023698815059 0.529273536323184 0.524573771311435 0.525923703814809 0.524923753812309 0.516474176291185 0.527273636318184 0.527723613819309 0.518424078796060 0.517874106294685 0.516074196290186 0.517924103794810 0.523173841307935 0.514474276286186 0.513174341282936 0.498875056247188 0.518024098795060 0.507924603769812 0.505524723763812 0.507174641267937 0.502874856257187 0.502624868756562 0.500624968751562 0.510824458777061 0.490925453727314 0.492675366231688 0.489925503724814 0.478126093695315 0.485775711214439 0.491775411229439 0.489925503724814 0.491325433728314 0.487225638718064 0.485725713714314 0.485675716214189 0.477676116194190 0.483875806209690 0.478026098695065 0.470176491175441 0.471926403679816 0.483625818709065 0.469376531173441 0.474026298685066 0.467826608669567 0.462426878656067];
Censored = ones(1,size(x,2));%
custpdf = #eval_custpdf;
custcdf = #eval_custcdf;
phat = mle(x,'pdf', custpdf,'cdf', custcdf,'start',[1 0.1 0.3 0.1 0.01 -0.3],...
'lowerbound',[0 0 0 0 0 -inf],'upperbound',[inf inf inf inf inf inf],'Censoring',Censored);
% Cheking how close the estimated PDF and CDF match with those from the data x
t = 0.001:0.001:0.5;
figure();
plot(t,x);hold on
plot(t,custpdf(t, phat(1), phat(2), phat(3), phat(4), phat(5), phat(6)))
figure();
plot(t,cumsum(x)./sum(x));hold on
plot(t,custcdf(t, phat(1), phat(2), phat(3), phat(4), phat(5), phat(6)))
The functions are:
function out = eval_custpdf(x,myalpha,mybeta,mytheta,a,b,c)
first_integral = integral(#(x) eval_K(x,a,b,c),0,1).^-1;
theta_t_ratio = (mytheta./x);
incomplete_gamma = igamma(myalpha,theta_t_ratio.^mybeta);
n_gamma = gamma(myalpha);
exponent_term = exp(-theta_t_ratio.^mybeta-(c.*(incomplete_gamma./n_gamma)));
numerator = first_integral.* mybeta.*incomplete_gamma.^(a-1).*...
theta_t_ratio.^(myalpha*mybeta+1).*exponent_term;
denominator = mytheta.* n_gamma.^(a+b-1).* (n_gamma-incomplete_gamma.^mybeta).^(1-b);
out = numerator./denominator;
end
function out = eval_custcdf(x,myalpha,mybeta,mytheta,a,b,c)
first_integral = integral(#(x) eval_K(x,a,b,c),0,1).^-1;
theta_t_ratio = (mytheta./x);
incomplete_gamma = igamma(myalpha,theta_t_ratio.^mybeta);
n_gamma = gamma(myalpha);
second_integral = integral(#(x) eval_K(x,a,b,c),0, incomplete_gamma.^mybeta./n_gamma);
% |<----- PROBLEMATIC LINE ----->|
out = first_integral*second_integral;
end
function out = eval_K(x,a,b,c)
out = x.^(a-1).*(1-x).^(b-1).*exp(-c.*x);
end
The integral that is causing the problem is the second intergral in the function eval_custcdf() as its upper limit is an array (denoted by PROBLEMATIC LINE).
Is there a way to take a single value from the array x such that the upper limit remains a scalar? And then calculate the cdf such that the output of the cdf is an array? Using a forloop, maybe? But I cannot seem to figure how to implement that?
How can I work around this problem?
Any help would be appreciated.
Thanks in advance.

eval_custcdf is a function expected to return 1D array of length n for
a given n data input.
I use a for loop to compute the output for a given input, then
return the whole array as output of eval_custcdf
I passed the input array elements one at a time
This is how eval_custcdf may look like
function out = eval_custcdf(x,myalpha,mybeta,mytheta,a,b,c)
out = zeros(size(x));
for i = 1: length(x)
first_integral = integral(#(w) eval_K(w,a,b,c),0,1).^-1;
theta_t_ratio = (mytheta./x(i));
incomplete_gamma = igamma(myalpha,theta_t_ratio.^mybeta);
n_gamma = gamma(myalpha);
second_integral = integral(#(w) eval_K(w,a,b,c),0, incomplete_gamma.^mybeta./n_gamma);
out(i) = first_integral*second_integral;
end
end

how to read from file and display the data in desired rows in Matlab

I am trying to read from a file and display the data in rows 6, 11, 111 and 127 in Matlab. I could not figure out how to do it. I have been searching Matlab forums and this platform for an answer. I used fscanf, textscan and other functions but they did not work as intended. I also used a for loop but again the output was not what I wanted. I can now only read one row and display it. Simply I want to display all of them(data in rows given above) at the same time. How can I do that?
matlab code
n = [0 :1: 127];
%% Problem 1
figure
x1 = cos(0.17*pi*n)
%it creates file and writes content of x1 to the file
fileID = fopen('file.txt','w');
fprintf(fileID,'%d \n',x1);
fclose(fileID);
%line number can be changed in order to obtain wanted values.
fileID = fopen('file.txt');
line = 6;
C = textscan(fileID,'%s',1,'delimiter','\n', 'headerlines',line-1);
celldisp(C)
fclose(fileID);
and this is the file
1
8.607420e-01
4.817537e-01
-3.141076e-02
-5.358268e-01
-8.910065e-01
-9.980267e-01
-8.270806e-01
-4.257793e-01
9.410831e-02
5.877853e-01
9.177546e-01
9.921147e-01
7.901550e-01
3.681246e-01
-1.564345e-01
-6.374240e-01
-9.408808e-01
-9.822873e-01
-7.501111e-01
-3.090170e-01
2.181432e-01
6.845471e-01
9.602937e-01
9.685832e-01
7.071068e-01
2.486899e-01
-2.789911e-01
-7.289686e-01
-9.759168e-01
-9.510565e-01
-6.613119e-01
-1.873813e-01
3.387379e-01
7.705132e-01
9.876883e-01
9.297765e-01
6.129071e-01
1.253332e-01
-3.971479e-01
-8.090170e-01
-9.955620e-01
-9.048271e-01
-5.620834e-01
-6.279052e-02
4.539905e-01
8.443279e-01
9.995066e-01
8.763067e-01
5.090414e-01
-4.288121e-15
-5.090414e-01
-8.763067e-01
-9.995066e-01
-8.443279e-01
-4.539905e-01
6.279052e-02
5.620834e-01
9.048271e-01
9.955620e-01
8.090170e-01
3.971479e-01
-1.253332e-01
-6.129071e-01
-9.297765e-01
-9.876883e-01
-7.705132e-01
-3.387379e-01
1.873813e-01
6.613119e-01
9.510565e-01
9.759168e-01
7.289686e-01
2.789911e-01
-2.486899e-01
-7.071068e-01
-9.685832e-01
-9.602937e-01
-6.845471e-01
-2.181432e-01
3.090170e-01
7.501111e-01
9.822873e-01
9.408808e-01
6.374240e-01
1.564345e-01
-3.681246e-01
-7.901550e-01
-9.921147e-01
-9.177546e-01
-5.877853e-01
-9.410831e-02
4.257793e-01
8.270806e-01
9.980267e-01
8.910065e-01
5.358268e-01
3.141076e-02
-4.817537e-01
-8.607420e-01
-1
-8.607420e-01
-4.817537e-01
3.141076e-02
5.358268e-01
8.910065e-01
9.980267e-01
8.270806e-01
4.257793e-01
-9.410831e-02
-5.877853e-01
-9.177546e-01
-9.921147e-01
-7.901550e-01
-3.681246e-01
1.564345e-01
6.374240e-01
9.408808e-01
9.822873e-01
7.501111e-01
3.090170e-01
-2.181432e-01
-6.845471e-01
-9.602937e-01
-9.685832e-01
-7.071068e-01
-2.486899e-01
2.789911e-01

Assuming the file is not exceedingly large, the simplest way would probably be read the entire file & index the output to your desired lines.
line = [6 11 111 127];
fileID = fopen('file.txt');
C = textscan(fileID,'%s','delimiter','\n');
fclose(fileID);
disp(C{1}(line))

Quiver list and labeling vectors of my inputs u,d, and r

How do I label each vector of each input component, say u$_1$..., d$_1$..., on my graph at each vector's respective starting point. I want to see if there is a clustering of certain vectors like u$_30$-u$_50$ are all near each other, for example. Here is my code:
fx = [1.01, 1.0165376460248143, 1.016585505356985,...
1.0166786731186357, 1.0166445649045002, 1.01684528204491,...
1.0168363943981442, 1.0169505828006045, 1.0169903647693619,...
1.0170588800755562, 1.0170214556321182, 1.0171007103163394,...
1.0170611565299144, 1.0171737504115423, 1.0171325089936156,...
1.0173884633568437, 1.0173821295549914, 1.017540453473392,...
1.0176091468862674, 1.0177647297690604, 1.017711866139699,...
1.0177536635811828, 1.0178254876275734, 1.0173994306983212,...
1.0200331803664529, 1.0232411092365432, 1.0232773133875106,...
1.023383936276914, 1.0233275057530007, 1.023510835824228,...
1.0234461433923472, 1.023507118352957, 1.0237210297124908,...
1.0236390252916325, 1.0237007559499636, 1.0239084387662698,...
1.0238131746118633, 1.024266374303865, 1.024212732428539,...
1.02440393427416, 1.0245390401237269, 1.0252178000353167,...
1.0252021019242434, 1.0275875709904758, 1.0275871039342042];
fy = [0.99, 0.99, 0.9899194500620327, 0.9897134368447225,...
0.9899339650105077, 0.9895259027418399, 0.9898115223446341,...
0.9896762515189842, 0.9896129792784014, 0.9894766621994305,...
0.9896189382715079, 0.9894614440540032, 0.9896292673356496,...
0.9894095770062209, 0.989655005387203, 0.9892019096930893,...
0.9894189058876284, 0.9892732425545386, 0.9891916768216495,...
0.9889512723219249, 0.9892071461243063, 0.9891515372181835,...
0.9890346980816267, 0.9901802532401042, 0.9892771992437573,...
0.9881487558751526, 0.9880037699743045, 0.9875669935217211,...
0.9878502051001951, 0.9872010568874899, 0.9875329139453003,...
0.9873775054641964, 0.9868251990627905, 0.9871082986923524,...
0.9869819983991632, 0.9865548473263468, 0.9867867860622922,...
0.9859765136441385, 0.9861731333993694, 0.9859212446482857,...
0.9857475603282838, 0.9848759880952044, 0.9850648602644492,...
0.9821891156159342, 0.9822254068452594];
fz =[0.01, -0.0014683388934621459, -0.0028093690242636917,...
-0.006255424514110392, -0.002405171080788649, -0.009167776104980133,...
0.0003750210183572269, -0.001823375333180016, -0.002906415137850454,...
-0.005227263048381278, -0.0028662319950483552, -0.0055329993182467365,...
-0.0027458980004112996, -0.00644276568444028, -0.00226410433801184,...
-0.009832266892691467, 0.0012478354917326469, -0.001163969711179093,...
-0.0026270200357900887, -0.006946260715800828, -0.00188587841967576,...
-0.002880843788516535, -0.0049636661241180685, 0.015586949435911355,...
0.010368914010693711, -0.0010649331940053245, -0.002328942248654949,...
-0.006634620630021168, -0.0020052485893380344, -0.008543368794125199,...
-0.00044976575279103564, -0.0019790036016751333, -0.008330963679008077,...
-0.0006481277669472506, -0.0020539789179887767, -0.0075781311330381336,...
-0.001294365366809558, -0.011629381859506432, 0.003447063734076782,...
0.0011256038145771368, -0.0008637305140054806, -0.012865086502170518,...
0.005283762238371167, -0.016926299226379265, 0.011993515880473204];
x = [1.01, 1.0165376460248143, 1.016585505356985, 1.0166786731186357,...
1.0166445649045002, 1.01684528204491, 1.0168363943981442,...
1.0169505828006045, 1.0169903647693619, 1.0170588800755562,...
1.0170214556321182, 1.0171007103163394, 1.0170611565299144,...
1.0171737504115423, 1.0171325089936156, 1.0173884633568437,...
1.0173821295549914, 1.017540453473392, 1.0176091468862674,...
1.0177647297690604, 1.017711866139699, 1.0177536635811828,...
1.0178254876275734, 1.0173994306983212, 1.0200331803664529,...
1.0232411092365432, 1.0232773133875106, 1.023383936276914,...
1.0233275057530007, 1.023510835824228, 1.0234461433923472,...
1.023507118352957, 1.0237210297124908, 1.0236390252916325,...
1.0237007559499636, 1.0239084387662698, 1.0238131746118633,...
1.024266374303865, 1.024212732428539, 1.02440393427416,...
1.0245390401237269, 1.0252178000353167, 1.0252021019242434,...
1.0275875709904758, 1.0275871039342042];
y = [0.99, 0.99, 0.9899194500620327, 0.9897134368447225,...
0.9899339650105077, 0.9895259027418399, 0.9898115223446341,...
0.9896762515189842, 0.9896129792784014, 0.9894766621994305,...
0.9896189382715079, 0.9894614440540032, 0.9896292673356496,...
0.9894095770062209, 0.989655005387203, 0.9892019096930893,...
0.9894189058876284, 0.9892732425545386, 0.9891916768216495,...
0.9889512723219249, 0.9892071461243063, 0.9891515372181835,...
0.9890346980816267, 0.9901802532401042, 0.9892771992437573,...
0.9881487558751526, 0.9880037699743045, 0.9875669935217211,...
0.9878502051001951, 0.9872010568874899, 0.9875329139453003,...
0.9873775054641964, 0.9868251990627905, 0.9871082986923524,...
0.9869819983991632, 0.9865548473263468, 0.9867867860622922,...
0.9859765136441385, 0.9861731333993694, 0.9859212446482857,...
0.9857475603282838, 0.9848759880952044, 0.9850648602644492,...
0.9821891156159342, 0.9822254068452594];
z =[0.01, -0.0014683388934621459, -0.0028093690242636917,...
-0.006255424514110392, -0.002405171080788649, -0.009167776104980133,...
0.0003750210183572269, -0.001823375333180016, -0.002906415137850454,...
-0.005227263048381278, -0.0028662319950483552, -0.0055329993182467365,...
-0.0027458980004112996, -0.00644276568444028, -0.00226410433801184,...
-0.009832266892691467, 0.0012478354917326469, -0.001163969711179093,...
-0.0026270200357900887, -0.006946260715800828, -0.00188587841967576,...
-0.002880843788516535, -0.0049636661241180685, 0.015586949435911355,...
0.010368914010693711, -0.0010649331940053245, -0.002328942248654949,...
-0.006634620630021168, -0.0020052485893380344, -0.008543368794125199,...
-0.00044976575279103564, -0.0019790036016751333, -0.008330963679008077,...
-0.0006481277669472506, -0.0020539789179887767, -0.0075781311330381336,...
-0.001294365366809558, -0.011629381859506432, 0.003447063734076782,...
0.0011256038145771368, -0.0008637305140054806, -0.012865086502170518,...
0.005283762238371167, -0.016926299226379265, 0.011993515880473204];
figure
q = quiver3(fx,fy,fz,x,y,z)
The problem is that I want to label the starting point of each vector:

You can use text:
q = quiver3(fx,fy,fz,x,y,z)
text(fx,fy,fz,num2str((1:numel(fx)).'))
The first 3 inputs are the coordinates of the label and the next input is a list (column character array or a cell-array) of the labels. I don't understand how your labeling is working (i.e. what is u$_1$ or d$_1$), so I just numbered the vectors from 1 to 45.

Plot a V-shape function given its points

I have the following matrix which rows are points sampled from a function
f = [ -3.7850 -11.5240
-3.7753 -11.4822
-3.7680 -11.5427
-3.7592 -11.5607
-3.7576 -11.5461
-3.7454 -11.5887
-3.7386 -11.4070
-3.7358 -11.4450
-3.7289 -11.5511
-3.7254 -11.3713
-3.7122 -11.4515
-3.6820 -11.5582
-3.6758 -11.5946
-3.6732 -11.5823
-3.6679 -11.6365
-3.6487 -11.3525
-3.6424 -11.2745
-3.6322 -11.3478
-3.6235 -11.6379
-3.6159 -11.6308
-3.5619 -11.1980
-3.5550 -11.2284
-3.5544 -11.5925
-3.5147 -11.6578
-3.5041 -11.6756
-3.4860 -11.1550
-3.4654 -11.6341
-3.4550 -11.1329
-3.3802 -11.6701
-3.3691 -11.1083
-3.3541 -11.0790
-3.3485 -11.5887
-3.3006 -11.6384
-3.2481 -11.5570
-3.2459 -11.0268
-3.2441 -10.9314
-3.2301 -11.5225
-3.2270 -10.8832
-3.1543 -10.8612
-3.1528 -11.5490
-3.1167 -11.5021
-3.1102 -10.8255
-3.0645 -11.5618
-2.9967 -11.5420
-2.9898 -10.8136
-2.9645 -10.7107
-2.9211 -11.4197
-2.9175 -10.6389
-2.8558 -10.6015
-2.8327 -11.5108
-2.7768 -11.4501
-2.7392 -10.5492
-2.7217 -11.4230
-2.6988 -10.4724
-2.6235 -11.3226
-2.6196 -11.3806
-2.5772 -10.4518
-2.5458 -10.4317
-2.5014 -10.3176
-2.4832 -11.3822
-2.4778 -10.2456
-2.4029 -11.2907
-2.3723 -10.3002
-2.3590 -11.2911
-2.3491 -10.2110
-2.2756 -11.2318
-2.2554 -10.1204
-2.2542 -10.1411
-2.2181 -11.2300
-2.1982 -9.9584
-2.1645 -9.7938
-2.1541 -11.1682
-2.1476 -9.8235
-2.1451 -9.9205
-2.1280 -10.0064
-2.1269 -9.8947
-2.0898 -9.7926
-2.0781 -11.1293
-1.9985 -11.0985
-1.9249 -11.0443
-1.8220 -11.0419
-1.7359 -11.0043
-1.6924 -10.9775
-1.6049 -10.9579
-1.5275 -10.9339
-1.4757 -10.9113
-1.4122 -10.8854
-1.3245 -10.8908
-1.2936 -10.7893
-1.2091 -10.8121
-1.1575 -10.8064
-1.1237 -10.7105
-1.0571 -10.7724
-1.0217 -10.7096
-0.9717 -10.6984
-0.9447 -10.7103
-0.9120 -10.6687
-0.8908 -10.6670]
Plotting by plot(f(:,1),f(:,2),'+') it is clear that the function has a V-shape. However, I need to plot it continuously, but doing plot(f(:,1),f(:,2)) results in a zig-zag function. How can I plot the points as I want to? (beside sorting them manually)

You could try rotating your data, sorting it and rotating it back. e.g:
theta = -1;
R = [cos(theta) -sin(theta);sin(theta) cos(theta)];
f2 = f*R;
f3 = sortrows(f2);
f4 = f3*R';
plot(f4(:,1),f4(:,2),'-',f(:,1),f(:,2),'+')
You can tweak theta to change the angle, which affects the sort order, I just took a guess that -1 is about right.

find corresponding peaks in matlab with 95% confidence interval

Suppose that we have following array:
0.196238259763928
0.0886250228175519
0.417543614272817
0.182403230538167
0.136500793051860
0.389922187581014
0.0344012946153299
0.381603315802419
0.0997542838649466
0.274807632628596
0.601652859233616
0.209431489000677
0.396925294300794
0.0351587496999554
0.177321874549738
0.369200511917405
0.287108838007101
0.477076452316346
0.127558716868438
0.792431584110476
0.0459982776925879
0.612598437936600
0.228340227044324
0.190267907472804
0.564751537228850
0.00269368929400299
0.940538666131177
0.101588565140294
0.426175626669060
0.600215481734847
0.127859067121782
0.985881201195063
0.0945679498528667
0.950077461673118
0.415212985598547
0.467423473845033
1.24336273213410
0.0848695928658021
1.84522775800633
0.289288949281834
1.38792131632743
1.73186592736729
0.554254947026916
3.46075557122590
0.0872957577705428
4.93259798197976
2.03544238985229
3.71059303259615
8.47095716918618
0.422940369071662
25.2287636895831
4.14535369056670
63.7312173032838
152.080907190007
1422.19492782494
832.134744027851
0.0220089962114756
60.8238733887811
7.71053463387430
10.4151913932115
11.3141744831953
0.988978595613829
8.65598040591953
0.219820300144944
3.92785491164888
2.28370963778411
1.60232807621444
2.51086405960291
0.0181622519984990
2.27469230188760
0.487809730727909
0.961063613990814
1.90435488292485
0.515640996120482
1.25933693517960
0.0953200831348589
1.52851575480462
0.582109930768162
0.933543409438383
0.717947488528521
0.0445235241119612
1.21157308704582
0.0942421028083462
0.536069075206508
0.821400666720535
0.308956823975938
1.28706199713640
0.0339217632187507
1.19575886464231
0.0853733920496230
0.736744959694641
0.635218502184121
0.262305581223588
0.986899895695809
0.0398800891449550
0.758792061180657
0.134279188964854
0.442531129290843
0.542782326712391
0.377221037448628
0.704787750202814
0.224180325609783
0.998785634315287
0.408055416702400
0.329684702125840
0.522384453408780
0.154542718256493
0.602294251721841
0.240357912028348
0.359040779285709
0.525224294805813
0.427539247203335
0.624034405807298
0.298184846094056
0.498659616687732
0.0962076792277457
0.430092706132805
0.656212420735658
0.278310520474744
0.866037361133916
0.184971060800812
0.481149730712771
0.624405636807668
0.382388147099945
0.435350646037440
0.216499523971397
1.22960953802959
0.330841706900755
0.891793067878849
0.628241046456751
0.278687691121678
1.06358076764171
0.365652714373067
1.34921178081181
0.652888708375276
0.861138633227739
1.02878577330537
0.591174450919664
1.93594290806582
0.497631035062465
1.14486512201656
0.978067581547298
0.948931658572253
2.01004088022982
0.917415940349743
2.24124811810385
1.42691656876436
2.15636037453584
1.92812357585099
1.12786835077183
4.81721425534142
1.70055431306602
4.87939454466131
3.90293284926105
5.16542230018432
10.5783535493504
1.74023535081791
27.0572221453758
7.78813114379733
69.2528169436690
167.769806437531
1490.03057130613
869.247150795648
3.27543244752518
62.3527480644562
9.74192115073051
13.6074209231800
10.5686495478844
7.70239986387120
9.62850426896699
9.85304975304259
7.09026325332085
12.8782040428502
16.3163128995995
7.00070066635845
74.1532966917877
4.80506505312457
1042.52337489620
1510.37374385290
118.514435606795
80.7915675273571
2.96352221859211
27.7825124315786
1.55102367292252
8.66382951478539
5.02910503820560
1.25219344189599
7.72195587189507
0.356973215117373
6.06702456628919
1.01953617014621
2.76489896186652
3.35353608882459
0.793376336025486
4.90341095941571
0.00742857354167949
5.07665716731356
1.16863474789604
4.47635486149688
4.33050121578669
2.42974020115261
9.79494608790444
0.0568839453395247
22.9153086380666
4.48791386399205
59.6962194708933
97.8636220152072
1119.97978883924
806.144299041605
7.33252581243942
57.0699524267842
0.900104994068117
15.2791339483160
3.31266162202546
3.20809490583211
5.36617545130941
0.648122925703121
3.90480316969632
0.0338850542128927
2.58828964019220
0.543604662856673
1.16385064506181
1.01835324272839
0.172915006573539
1.55998411282069
0.00221570175453666
1.14803074836796
0.0769335878967426
0.421762398811163
0.468260146832541
0.203765185125597
0.467641715366303
0.00142988680149041
0.698088976126660
0.0413316717103625
0.190548157914037
0.504713663418641
0.325697764871308
0.375910057283262
0.123307135682793
0.331115262928959
0.00263961045860704
0.204555648718379
0.139008751575803
0.182936666944843
0.154943314848474
0.0840483576044629
0.293075999812128
0.00306911699543199
0.272993318570981
0.0864711337990886
0.280495615619829
0.0910123210559269
0.148399626645134
0.141945002415500
0.0512001531781583
0.0295283557338525
In MATLAB it is very easy to find peaks using findpeaks, like so:
[pxx_peaks,location] = findpeaks(Pxx);
If we plot pxx_peaks, we get
plot(pxx_peaks)
Of course, besides these peaks, there are smaller peaks which are not shown on the picture, but my goal is to find all peaks which are 95-96% above all other peaks.
I have tried like this:
>> average = mean(pxx_peaks);
>> stand = std(pxx_peaks);
>> final_peaks = pxx_peaks( pxx_peaks > average + 3*stand );
The result of this is
>> final_peaks
final_peaks =
1.0e+03 *
1.4222
1.4900
1.5104
1.1200
but how to return their corresponding locations? I want to write it as one m-file, so please help me
EDIT
also please help me in this question: can I parameterize the confidence interval? For instance instead of 95%, I want to find peaks that are 60% above then other peaks, is it possible?

Note that 3σ ≈ 99.73%
As for your first question, it's easy, you just have to keep track of the locations in the same way as you do for the peaks:
inds = pxx_peaks > mean(pxx_peaks) + 3*std(pxx_peaks);
final_peaks = pxx_peaks(inds);
final_locations = location(inds);
plot(Pxx), hold on
plot(final_locations, final_peaks, 'r.')
As for your second question, that's a little more complicated. If you want to formulate it like you say, you'll have to convert a desired percentage to the correct number of σ. That involves an integration of the standard normal, and a root finding:
%// Convert confidence interval percentage to number-of-sigmas
F = #(P) fzero(#(sig) quadgk(#(x) exp(-x.^2/2),-sig,+sig)/sqrt(2*pi) - P/100, 1);
% // Repeat with the desired percentage
inds = pxx_peaks > mean(pxx_peaks) + F(63)*std(pxx_peaks); %// 63%
final_peaks = pxx_peaks(inds);
final_locations = location(inds);
plot(final_locations, final_peaks, 'r.')