rand()
function return value?\_
of a.a = rand(1, 11);
b = sort(a);
c = b(1, ceil(end/2));
while
loop?a = 0;
do
a = a + 1;
while a < 5
end
a = 0;
while(a < 5)
a = a + 1;
a = 0;
while a < 5:
a = a + 1;
a = 0;
while a < 5
a = a + 1;
end
b
contain?a =
19 20 12 0 6
6 9 56 0 3
46 8 9 8 19
9 8 8 19 46
1 9 46 6 19
b =
56 0
9 8
b =
8 19
19 46
myfun
and want to measure how long it takes to run. Which code segment will return in t
the time in seconds it takes myfun
to run?t = cputime(myfun());
tic;
myfun();
toc;
timer.start;
myfun()
t = timer.stop;
t = timer(myfun());
%%
used for?.
character NOT used for?mean
, median
, and mode
return the same value?x = [-1:0.1:1];
y = X.^2;
plot(x, y)
figure
was not called immediately in advance.plot
syntax is incorrect.name
in structure S?a = [1 2 3; 4 5 6];
b = zeros(size(a));
for i_row = 1:size(a, 1)
for i_col = 1:size(a, 2)
b(i_row, i_col) = a(i_row, i_col)^2;
end
end
c
?a = ones(1,3);
b = 1:3;
c = conv(a,b)
switch
statement?x = 7;
switch x
case 2
disp("two");
otherwise
disp("not two");
end
x = 7;
switch x :
case 2
disp("two");
otherwise
disp("not two");
end
x = 7;
switch x
case 2
disp("two");
else
disp("not two");
end
x = 7;
switch x
case 2
disp("two");
default
disp("not two");
end
a = 1;
b = 2;
c = 3;
d = 4;
e = c / (~a - b == c - d);
c =
NaN
c =
Inf
c =
-0.2500
eq
function.f10
than the other three?f10 = 1;
for i = 1:10
f10 = f10 * i;
end
f10 = factorial(10)
f10 = 1;
i = 1;
while i <= 10
i = i + 1;
f10 = i * f10;
end
f10 = prod(1:10)
a = rand(5);
round(a * inv(a))
diag(ones(5, 1))
identity(5)
eye(5)
dog =
name: 'Bindy'
breed: 'border collie'
weight: 32
dog = struct('name', 'Bindy'; 'breed', 'border collie'; 'weight', 32);
dog.name = 'Bindy';
dog.breed = 'border collie';
dog.weight = 32;
dog = {
'name' : 'Bindy',
'breed' : 'border collie',
'weight': 32;
}
dog('name') = 'Bindy';
dog('breed') = 'border collie';
dog('weight') = 32;
my_func
is a function as follows. What is the value of a
at the end of the code beneath?function a = my_func(a)
a = a + 1;
end
------------------
a = 0;
for i = 1:3
my_func(a);
end
a = my_func(a);
c =
{["hello world"]} {1×1 cell} {["goodbye"]} {1×3 double}
b
to each row of a
?a = ones(4, 4);
b= [1 2 3 4];
a
s with o
s?for i = 1:length(fruit)
fruit{i}(fruit{i} == a) == o;
end
for i = 1:length(fruit)
fruit(i)(fruit(i) == 'a') == 'o';
end
for i = 1:length(fruit)
fruit{i}(fruit{i} == 'a') == 'o';
end
for i = 1:length(fruit)
fruit{i}(fruit{i} == 'a') == 'o';
x^2 + 2x - 4
?a
to the end of 1x 2 dimensional cell array C
?height
. Which statement will return a 100 x 1 array, sim_height
, with values from a normal distribution with the same mean and variance as your height data?burger
’ from menu
?menu = {'hot dog' 'corn dog' 'regular burger' 'cheeseburger' 'veggie burger'}
a
may contain?a = randi(10, [1, 10]);
a(3) = 11;
a(a>2) = 12;
sparse
function to remove empty cells from cell array variables.sparse
function requires its input to be a full matrix with at least 50% zero elements.a = 1:10;
[ ] b = a(a | 1) |
menu
into the variable menu_string
below?menu = {'hot dog' 'corn dog' 'regular burger' 'cheeseburger' 'veggie burger'}
menu_string =
'hot dog
corn dog
regular burger
cheeseburger
veggie burger'
rng_settings_curr = rng('shuffle');
rng(time());
rng_settings_curr = rng();
rng_settings_curr = rand('shuffle');
rng('shuffle');
rng_settings_curr = rng();
data
in which each column is mono audio recording from a room in your house. You’ve noticed that each column has a very different mean and when you plot them all on the same graph, the spread across the y axis make it impossible to see anything. You want to subtract the mean from each column. Which code block will accomplish this?data_nomean = data - repmat(median(data), size(data, 1), 1);
data_nomean = bsxfun(@minus, data, mean(data));
data_nomean = zeros(size(data));
for i = 1:size(data, 1)
data_nomean(i, :) = data(i, :) - mean(data(i, :));
end
data_nomean = zscore(data');
b
containing the mean values of each array within C
?b = zeros(1, size(C, 2));
for i_C = 1:size(C, 2)
b(i_C) = mean(C(i_C));
end
b = cellfun(@mean, C);
b = zeros(1, size(C, 1));
for i_C = 1:size(C, 1)
b(i_C) = mean(C{i_C}(:));
end
b = cellfun(@(m) mean(m(:)), C)
passwords
contains a digit and 0 if it does not?passwords = {'abcd' '1234' 'qwerty' 'love1'};
figure
x = rand(10,10);
r = corrcoef(x);
surf(r)
colorbar
figure
x = rand(10,10);
r = corrcoef(x);
imagesc(r)
colorbar
a = 1:10;
b = a(randi(10, 1, 10));
m = perms(a);
i = randi(factorial(10), 1);
b = a(m(i, :))
[s, j] = sort(rand(10, 1));
b = a(i);
b = a(randperm(10));
a = 'stand'
b = "stand"
C = {'dog' 'cat' 'mouse'}
D = {'cow' 'piranha' 'mouse'}
E = setdiff(C,D)
x = 9.0646 6.4362 7.8266 8.3945 5.6135 4.8186 2.8862 10.9311 1.1908 3.2586
y = 15.4357 11.0923 14.1417 14.9506 8.7687 8.0416 5.1662 20.5005 1.0978
coeff_line = polyfit(x,y,1)
x_line = floor(min(x)):0.1:ceil(max(x));
y_line = polyval(coeff_line,x_line)
figure; plot(x,y,'o')
hold on
plot(x_linemy_line)
figure
plot(x,y,'o')
coeff_line = polyfit(x,y,1);
x_line = floor(min(x)):0.1:ceil(max(x));
y_line = polyval(coeff_line,x_line);
plot(x_line,y_line)
figure
plot(x,y)
coeff_line = polyfit(x,y,1);
x_line = floor(min(x)):0.1:ceil(max(x));
y_line = polyval(coeff_line,x_line);
hold on; plot(x_line,y_line)
coeff_line = polyfit(x,y,1);
x_line = floor(min(x)):0.1:ceil(max(x));
y_line = polyval(coeff_line,x_line);
figure; plot(x,y,'o')
hold on
plot(x_line,y_line)
a = [0 1 2 3; 4 5 6 7];
a = a^2;