Week 10b: From Python to MATLAB: Syntax and Plotting

Week 10b: From Python to MATLAB: Syntax and Plotting#

Introduction#

Welcome to MATLAB! As you transition from Python, you’ll find that many programming concepts you’ve already learned translate directly. However, MATLAB has some important syntax differences and was specifically designed for matrix operations and numerical computing. This guide will help you bridge your Python knowledge to MATLAB, with a focus on plotting.

Installing MATLAB at Boston University#

Boston University has a site-wide license giving all BU students, faculty, and staff unlimited access to MATLAB, Simulink, and 49 add-on products at no additional cost. Here’s how to install it on your personal computer:

Installation Steps#

Create a MathWorks Account
- Go to the MathWorks BU Portal and create an account using your BU email address
- You’ll need to authenticate with your BU credentials
Download MATLAB
- Log into the MathWorks BU Portal
- Select the “40523728 Individual Academic – Total Headcount” license
- Download the installer for your operating system (Windows, Mac, or Linux)
Install the Software
- Run the installer you downloaded
- Follow the on-screen installation prompts
- Choose which toolboxes you want to install (it’s not a bad idea to just install them all)
Activate Your License
- After installation, MATLAB will prompt you to activate
- Select “Activate automatically using the Internet (recommended)”
- Sign in with your MathWorks account when prompted
- The activation process will link MATLAB to BU’s license

Important Notes:

You can install MATLAB on each computer you personally use (home and office machines)
The license requires annual renewal (typically in July), but you’ll receive notifications
If you have any installation issues, contact BU IT Help at ithelp@bu.edu

Resources:

Full installation guide: https://www.bu.edu/tech/services/cccs/desktop/distribution/mathsci/matlab/
FAQ: https://www.bu.edu/tech/services/cccs/desktop/distribution/mathsci/matlab/faqs/

Key Syntax Differences#

Semicolons and Output#

In Python, statements automatically suppress output unless you explicitly print. In MATLAB, it’s the opposite:

Python:

x = 5          # No output
print(x)       # Displays: 5

MATLAB:

x = 5          % Displays: x = 5
x = 5;         % Suppresses output (semicolon!)
disp(x)        % Displays: 5

Key point: Use semicolons in MATLAB to suppress output, especially in loops!

Comments#

Python: # This is a comment
MATLAB: % This is a comment

Indexing#

This is one of the most important differences:

Python: Zero-indexed (starts at 0)

my_list = [10, 20, 30, 40]
print(my_list[0])      # 10 (first element)
print(my_list[-1])     # 40 (last element)

MATLAB: One-indexed (starts at 1)

my_array = [10, 20, 30, 40];
disp(my_array(1))      % 10 (first element)
disp(my_array(end))    % 40 (last element)

Watch out: MATLAB uses parentheses () for indexing, not square brackets!

Arrays vs Lists#

MATLAB is built around arrays (especially matrices). Creating them is straightforward:

Python:

my_list = [1, 2, 3, 4]
import numpy as np
my_array = np.array([1, 2, 3, 4])

MATLAB:

my_array = [1, 2, 3, 4];              % Row vector
my_column = [1; 2; 3; 4];             % Column vector (semicolon!)
my_matrix = [1, 2, 3; 4, 5, 6];       % 2x3 matrix

Ranges and Sequences#

Python:

range(0, 10)           # 0 to 9
range(0, 10, 2)        # 0, 2, 4, 6, 8

MATLAB:

0:9                    % 0 to 9
0:2:9                  % 0, 2, 4, 6, 8 (start:step:end)
linspace(0, 10, 5)     % 5 evenly spaced points from 0 to 10

Logical Operators#

Operation	Python	MATLAB
AND	`and` or `&`	`&&` or `&`
OR	`or` or `\|`	`\|\|` or `\|`
NOT	`not` or `~`	`~`

For single comparisons, use && and || in MATLAB. For element-wise operations on arrays, use & and |.

Plotting in MATLAB#

If you’ve used matplotlib in Python, MATLAB’s plotting will feel familiar—in fact, matplotlib was inspired by MATLAB’s plotting syntax!

Basic Line Plot#

Python (matplotlib):

import matplotlib.pyplot as plt
x = [1, 2, 3, 4, 5]
y = [1, 4, 9, 16, 25]
plt.plot(x, y)
plt.xlabel('X values')
plt.ylabel('Y values')
plt.title('My Plot')
plt.show()

MATLAB:

x = [1, 2, 3, 4, 5];
y = [1, 4, 9, 16, 25];
plot(x, y)
xlabel('X values')
ylabel('Y values')
title('My Plot')

Key difference: No need to import anything or call show()—MATLAB automatically displays the plot!

Customizing Plots#

You can customize line style, color, and markers:

x = 0:0.1:2*pi;
y = sin(x);
plot(x, y, 'r--', 'LineWidth', 2)  % Red dashed line, thickness 2
xlabel('x')
ylabel('sin(x)')
title('Sine Wave')
grid on                             % Add grid lines

Common line styles:

'-' solid line (default)
'--' dashed line
':' dotted line
'-.' dash-dot line

Common markers:

'o' circle
'+' plus sign
'*' asterisk
'.' point
'x' cross
's' square
'd' diamond
'^' upward triangle
'v' downward triangle

Common colors:

'r' red, 'g' green, 'b' blue, 'k' black, 'm' magenta, 'c' cyan, 'y' yellow

You can combine line style, marker, and color: plot(x, y, 'r--o') creates a red dashed line with circle markers.

Multiple Lines on One Plot#

Python:

plt.plot(x, y1, label='Line 1')
plt.plot(x, y2, label='Line 2')
plt.legend()

MATLAB:

x = 0:0.1:2*pi;
y1 = sin(x);
y2 = cos(x);
plot(x, y1, x, y2)           % Multiple pairs of x,y
legend('sin(x)', 'cos(x)')

Or using hold on:

plot(x, y1)
hold on                      % Keep current plot, add to it
plot(x, y2)
hold off                     % Return to default behavior
legend('sin(x)', 'cos(x)')

Subplots#

Python:

plt.subplot(2, 1, 1)  # 2 rows, 1 column, plot 1
plt.plot(x, y1)

plt.subplot(2, 1, 2)  # 2 rows, 1 column, plot 2
plt.plot(x, y2)

MATLAB:

subplot(2, 1, 1)      % 2 rows, 1 column, plot 1
plot(x, y1)
title('First Plot')

subplot(2, 1, 2)      % 2 rows, 1 column, plot 2
plot(x, y2)
title('Second Plot')

Scatter Plots and Other Plot Types#

% Scatter plot
x = randn(100, 1);    % 100 random numbers
y = randn(100, 1);
scatter(x, y)
title('Scatter Plot')

% Bar plot
categories = 1:5;
values = [23, 45, 31, 52, 38];
bar(categories, values)
title('Bar Chart')

% Histogram
data = randn(1000, 1);
histogram(data, 30)   % 30 bins
title('Histogram')

MATLAB Documentation: Your Best Resource#

One of the biggest advantages of MATLAB is its exceptional documentation. As you learn MATLAB, you’ll frequently reference the documentation for built-in functions. Below are summaries of the key functions we’ll use in class, followed by links to the full documentation pages.

Plot Types#

plot(x, y) - 2-D line plot

Creates line plots from vectors of x and y data
Can plot multiple lines: plot(x1, y1, x2, y2, ...)
Customize with line specs: plot(x, y, 'r--') for red dashed line
Many name-value pairs available: 'LineWidth', 'Color', 'Marker', etc.

scatter(x, y) - Scatter plot

Displays data points without connecting lines
Useful for showing relationships between variables
Can control marker size: scatter(x, y, sizes)
Can control marker color: scatter(x, y, sizes, colors)
Optional: 'filled' makes solid markers instead of hollow

bar(x, y) - Bar graph

Creates vertical bar charts (use barh for horizontal)
Great for categorical data or comparing discrete values
Can create grouped or stacked bars for multiple data series
Customize with 'FaceColor', 'EdgeColor', 'BarWidth'

histogram(data) - Histogram plot

Shows distribution of data by grouping into bins
Can specify number of bins: histogram(data, 20)
Can specify bin edges: histogram(data, [0, 5, 10, 15])
Options for normalization: 'probability', 'pdf', 'count'

Colors and Colormaps#

Specify Plot Colors

Short color codes: 'r' (red), 'g' (green), 'b' (blue), 'k' (black), 'm' (magenta), 'c' (cyan), 'y' (yellow), 'w' (white)
RGB triplets: [0.5, 0.2, 0.8] for custom colors (values 0-1)
Hexadecimal: '#FF5733' for precise colors
Named colors: 'crimson', 'teal', etc.

colormap - View and set current colormap

Controls color schemes for images and surface plots
Built-in colormaps: 'parula' (default), 'jet', 'hot', 'cool', 'gray'
Set with: colormap(jet) or colormap('parula')
Create custom colormaps with RGB arrays

Axes and Labels#

Axes Appearance

Control many visual aspects: limits, scale (linear/log), colors, grid
Set axis limits: xlim([0, 10]), ylim([-5, 5])
Toggle grid: grid on or grid off
Set aspect ratio: axis equal, axis square

xticks(values) - Set or query x-axis tick values

Define where tick marks appear: xticks([0, 2, 4, 6, 8, 10])
Query current ticks: current_ticks = xticks
Similarly: yticks for y-axis

xticklabels(labels) - Set or query x-axis tick labels

Change what text appears at tick marks: xticklabels({'Low', 'Med', 'High'})
Useful for categorical data
Similarly: yticklabels for y-axis

xtickangle(angle) - Rotate x-axis tick labels

Rotate labels for better readability: xtickangle(45) for 45-degree rotation
Helpful when labels are long or numerous
Similarly: ytickangle for y-axis

xlabel(text), ylabel(text) - Label axes

Add descriptive text to axes: xlabel('Time (seconds)')
Can customize font, size, interpreter: xlabel('Distance (m)', 'FontSize', 14)

title(text) - Add title to plot

Adds title above the plot: title('Temperature vs Time')
Customize: title('My Plot', 'FontSize', 16, 'FontWeight', 'bold')

legend(labels) - Add legend to axes

Identifies multiple lines/data series: legend('Data 1', 'Data 2')
Control location: legend('Location', 'northwest') or 'best'
Can specify which objects to include in legend

Saving Figures#

saveas(fig, filename) - Save figure to file

Saves current figure: saveas(gcf, 'myplot.png')
Supports many formats: .png, .jpg, .pdf, .fig, .eps
Specify format explicitly: saveas(gcf, 'myplot', 'png')
gcf means “get current figure”

Full Documentation Links#

For complete details, examples, and advanced usage, refer to these MATLAB documentation pages:

Plot Types:

Colors and Appearance:

Axes Customization:

Saving:

saveas - Save figure - MATLAB

Try It Yourself#

Once you have MATLAB installed, try running this complete example:

% Create data
x = linspace(0, 4*pi, 100);
y1 = sin(x);
y2 = sin(x) .* exp(-x/10);  % Note the .* for element-wise multiplication!

% Create figure with two subplots
figure
subplot(2, 1, 1)
plot(x, y1, 'b-', 'LineWidth', 1.5)
title('Simple Sine Wave')
xlabel('x')
ylabel('sin(x)')
grid on

subplot(2, 1, 2)
plot(x, y2, 'r-', 'LineWidth', 1.5)
title('Damped Sine Wave')
xlabel('x')
ylabel('sin(x) * exp(-x/10)')
grid on

Quick Reference Table#

Task	Python	MATLAB
Suppress output	Automatic	Add `;` at end
Comment	`#`	`%`
First index	`0`	`1`
Last index	`-1`	`end`
Indexing	`arr[i]`	`arr(i)`
Range	`range(0, 10)`	`0:9`
Plot	`plt.plot(x, y)`	`plot(x, y)`
Show plot	`plt.show()`	Automatic
Element-wise multiply	`arr1 * arr2` (NumPy)	`arr1 .* arr2`

Coming to Class Prepared#

Before class, make sure you:

Have MATLAB installed and can open it
Can create a simple array: x = 1:10;
Can create a basic plot: plot(x, x.^2) (try it!)
Understand the indexing difference (1-based vs 0-based)

We’ll build on these concepts in class with more advanced plotting techniques and real-world examples!

Week 10b: From Python to MATLAB: Syntax and Plotting

Contents

Week 10b: From Python to MATLAB: Syntax and Plotting#

Introduction#

Installing MATLAB at Boston University#

Installation Steps#

Key Syntax Differences#

Semicolons and Output#

Comments#

Indexing#

Arrays vs Lists#

Ranges and Sequences#

Logical Operators#

Plotting in MATLAB#

Basic Line Plot#

Customizing Plots#

Multiple Lines on One Plot#

Subplots#

Scatter Plots and Other Plot Types#

MATLAB Documentation: Your Best Resource#

Plot Types#

Colors and Colormaps#

Axes and Labels#

Saving Figures#

Full Documentation Links#

Try It Yourself#

Quick Reference Table#

Coming to Class Prepared#