I need help with my code in MATLAB. I am trying to pull out each of the $8$ matrices I created in the loop as shown in the code in the end. It is giving me an error or just says $1\backslash$times $1$ cell array $\{3\backslash$times $10$ double$\}.$ Can you help me pull each matrix out?

clc; clear all;

$\%$ Number of unit vectors

n $=10$;

$\%$ Define noise levels in degrees

noise$\_$levels$\_$deg $=[1/3600,10/3600,1,5]$;

$\%$ Define a random rotation matrix $($Direction Cosine Matrix$)$

R $=$ orth$($randn$(3))$;

$\%$ Generate $10$ random unit vectors in the body frame

unit$\_$vectors$\_$body $=$ randn$(3,$ n$)$;

unit$\_$vectors$\_$body $=$ unit$\_$vectors$\_$body $./$ vecnorm$($unit$\_$vectors$\_$body$)$;

$\%$ Pre$-$allocate matrices to store the noisy vectors for Gaussian and Poisson noise

noisy$\_$vectors$\_$body$\_$gaussian $=$ cell$(1,$ length$($noise$\_$levels$\_$deg$))$;

noisy$\_$vectors$\_$inertial$\_$gaussian $=$ cell$(1,$ length$($noise$\_$levels$\_$deg$))$;

noisy$\_$vectors$\_$body$\_$poisson $=$ cell$(1,$ length$($noise$\_$levels$\_$deg$))$;

noisy$\_$vectors$\_$inertial$\_$poisson $=$ cell$(1,$ length$($noise$\_$levels$\_$deg$))$;

$\%$ Define noise distributions

noise$\_$types $=["$Gaussian$",$ "Poisson"$]$;

$\%$ Loop through noise types $($Gaussian and Poisson$)$

for noise$\_$type $=$ noise$\_$types

disp$([\text{'}$Noise Type: $\text{'},$ char$($noise$\_$type$)])$;

$\%$ Loop through noise levels

for i $=1$:length$($noise$\_$levels$\_$deg$)$

noise$\_$level $=$ noise$\_$levels$\_$deg$($i$)$;

$\%$ Convert noise level to radians

noise$\_$level$\_$rad $=$ deg$2$rad$($noise$\_$level$)$;

disp$([\text{'}$Noise Level: $\text{'},$ num$2$str$($noise$\_$level$),\text{'}$ degrees'$])$;

$\%$ Initialize arrays to hold noisy vectors

noisy$\_$vectors$\_$body $=$ zeros$(3,$ n$)$;

noisy$\_$vectors$\_$inertial $=$ zeros$(3,$ n$)$;

$\%$ Loop through unit vectors

for j $=1$:n

$\%$ Apply noise to the unit vectors

if noise$\_$type $==$ "Gaussian"

noise $=$ noise$\_$level$\_$rad $*$ randn$(3,1)$; $\%$ Gaussian noise

else

noise $=$ noise$\_$level$\_$rad $*$ poissrnd$(1,3,1)$; $\%$ Poisson noise

end

$\%$ Perturb the unit vector's direction

perturbed$\_$vector $=$ unit$\_$vectors$\_$body$($:$,$ j$)+$ noise;

perturbed$\_$vector $=$ perturbed$\_$vector $/$ norm$($perturbed$\_$vector$)$; $\%$ Renormalize

$\%$ Store noisy vector in body frame

noisy$\_$vectors$\_$body$($:$,$ j$)=$ perturbed$\_$vector;

$\%$ Transform to inertial frame using rotation matrix

noisy$\_$vectors$\_$inertial$($:$,$ j$)=$ R $*$ perturbed$\_$vector;

end

$\%$ Store the noisy vectors for each noise level and distribution

if noise$\_$type $==$ "Gaussian"

noisy$\_$vectors$\_$body$\_$gaussian$\{$i$\}=$ noisy$\_$vectors$\_$body;

noisy$\_$vectors$\_$inertial$\_$gaussian$\{$i$\}=$ noisy$\_$vectors$\_$inertial;

else

noisy$\_$vectors$\_$body$\_$poisson$\{$i$\}=$ noisy$\_$vectors$\_$body;

noisy$\_$vectors$\_$inertial$\_$poisson$\{$i$\}=$ noisy$\_$vectors$\_$inertial;

end

$\%$ Display the noisy vectors in the inertial frame for this noise level

$\%$ disp$(\text{'}$Noisy Vectors in Inertial Frame:$\text{'})$;

$\%$ disp$($noisy$\_$vectors$\_$inertial$)$;

end

end

a $=$ noisy$\_$vectors$\_$inertial$\_$guassian$(1)$

b $=$ noisy$\_$vectors$\_$inertial$\_$guassian$(2)$

c $=$ noisy$\_$vectors$\_$inertial$\_$guassian$(3)$

d $=$ noisy$\_$vectors$\_$inertial$\_$guassian$(4)$

e $=$ noisy$\_$vectors$\_$inertial$\_$poisson$(1)$

f $=$ noisy$\_$vectors$\_$inertial$\_$poisson$(2)$

g $=$ noisy$\_$vectors$\_$inertial$\_$poisson$(3)$

h $=$ noisy$\_$vectors$\_$inertial$\_$poisson$(4)$