# numeric variables
# are
a =
5.0
% numeric variables
% are double precision by default
a = 5.0;
# repeat which assigns values to array elements
#
arrays are known as "lists" in Python
# array indexes start at 0 in Python
#
structures are defined by indentation, no 'end'
A =
[] # initialize array A
for i in range(1,11):
A.append(i)
print(A[i-1])
% array indexes start at 1 in
Matlab
%
indentation is for readability only
for i=1:10
A(i) = i;
end
A % display contents of A
# repeat which prints a series of
#
values
for i
in range(0,11,2):
print(i)
for i=0:2:10
fprintf(' %i \n', i)
end
# import the numpy library for matrix operations
import numpy as np
B = np.identity(3)
% MATLAB has built-in
functions for
% common array initializations
B = eye(100);
# known as a list in Python
C = [1, 2, 3]
C = [1, 2, 3]; % or C = [1 2 3];
# array name = arange(start,stop,step)
import numpy as np
C = np.arange(2,10,2)
print(C)
% array name = [start:increment:end];
C = [2:2:8] % leave off ; to display
value
# array indexes start at 0
print(C[1])
# prints 4 using C from above table cell
# note square brackets C[1]
% array indexes start at 1
C(2)
% prints 4 using C from above
table cell
% note parentheses C(2)
# declare and initialize an array
# with fixed interval between values
import numpy as np
C = np.linspace(2,8,4)
# third param is optional and = # points
# between and including 1st two points
# if third param left off, default
# is 50 points
C = linspace(2,8,4);
% third param is optional and = # points
% between and including 1st two points
% if third param left off, default
% is 100 points
D = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
% these three examples accomplish the
% same thing
D = [1 2 3; 4 5 6; 7 8 9];
D = [1:3; 4:6; 7:9];
D = [1 2 3
4 5 6
7 8 9];
# array indexes start at 0
print(D[1][1]) # row 2, column 2
# prints 5 using D from above table cell
% array indexes start at
1
D(2,2) % row 2, column 2
% prints 5 using
D from above table cell
# e.g., print rows 1 to 2 of column 1
for i in range(0,2):
print(D[i][0])
D(1:2,1) % rows 1 to 2 of
column 1
# print all rows of column 1 of 2D
# array
import numpy as np
D = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
Dsub = D[0:,0:1]
print(Dsub)
D(:,1) % all rows, column 1
a = 1
b = 2
if a == 1 or b == 3:
print('a = 2 or b = 3')
a = 1
b = 2;
if a == 1 || b == 3
fprintf('a = 2 or b = 3 \n');
end
if a == 1 and b != 3:
print('a=1 and b not 3');
print('OK?')
if a == 1 && b ~= 3
fprintf('a=1 and b not 3 \n');
fprintf('OK? \n');
end
if a != 1:
print('a is not 1')
elif b != 3:
print('b is not 3')
else:
print('huh?')
a ~= 1
fprintf('a is not 1 \n')
elseif b ~= 3
fprintf('b is not 3 \n')
else
fprintf('huh? \n')
end
# Python doesn't have a switch structure
# any switch structure can be
# written as an if-else structure
# switch structures may be quicker to
# read and write for applications such as menus
switch menuChoice
case 1
% can do any actions in a case, e.g.,
% call a
user-defined function
myMenuFunc01();
case
2
myMenuFunc02();
case 3
myMenuFunc03();
otherwise
fprintf('invalid selection, try again')
end
# define function, here I chose name myfunc
def myfunc(x,y):
return x**y # ** is exponentiation operator
# call function
z = myfunc(2,3)
print(z)
# prints 8 for this input
% main program and function definition must
% be in separate files and function file
% must have same name as function name
z = myfunc(2,3)
% prints 8 for
this input
----- LISTING OF FILE myfunc.m ------
function returnValue = myfunc(x,y)
returnValue = x^y; % ^ is exponentiation operator
% function is a
keyword
% returnValue is arbitrary variable name
import numpy as np
A = np.matrix( ((2,3), (3, 5)) )
B = np.matrix( ((1,2), (5, -1)) )
C = A * B
print(C)
A = [2,3; 3,5];
B = [1,2; 5,-1];
C = A * B
import numpy as np
import matplotlib.pyplot as plt
x = np.linspace(0,2*np.pi,100)
y = np.sin(x)
plt.plot(x,y)
plt.ylabel('sin(x)')
plt.xlabel('x')
plt.show()
x = linspace(0,2*pi,100);
y = sin(x);
plot(x,y)
ylabel('sin(x)')
xlabel('x')