Introduction to
Raspberry Pi¶
What is a Raspberry Pi?¶
A Raspberry Pi is a mini computer based on the ARM architecture designed to increase accessibility to computing. It is designed to be cheap and easy to use, and is a great way to learn about computers and programming.
Raspberry Pi in a Glance¶
Connectivity¶
- WiFi 2.4 GHz and 5.0 GHz IEEE 802.11ac wireless, Bluetooth 5.0, BLE
- Wired Network Gigabit Ethernet
Ports¶
- USB 2 USB 3.0 ports; 2 USB 2.0 ports.
- Peripherals Raspberry Pi standard 40 pin GPIO header (fully backwards compatible with previous boards)
- Video 2 × micro-HDMI® ports (up to 4kp60 supported)
- Display 2-lane MIPI DSI (Display Serial Interface) display port
- Camera 2-lane MIPI CSI (Camera Serial Interface) camera port
- Audio 4-pole stereo audio and composite video port
Graphics¶
- Codecs H.265 (4kp60 decode), H264 (1080p60 decode, 1080p30 encode)
- API (Application Programming Interface) OpenGL ES 3.1, Vulkan 1.0[^note]
[^note]: same as PlayStation3, Xbox 360, PSP, PS Vita, Nintendo Switch, and many Android devices
Operation¶
- Power
- 5V DC via USB-C connector (minimum 3A*)
- 5V DC via GPIO header (minimum 3A*)
- Power over Ethernet (PoE) enabled (requires separate PoE HAT)
- Environment Operating temperature: 0 – 50 degrees C ambient
Programming Languages¶
Raspberry Pi OS comes with a number of programming languages pre-installed, including python and C++.
Additional Software¶
If you want to install additional software, you can use the apt package manager to install software from the official repositories.
sudo su -
apt-get update
apt-get install python3-matplotlib
apt-get install python3-scipy
It should be noticed that the Raspberry Pi is not a very powerful computer, and the official package manager may provide the most optimised version of the required software, even if not up-to-date.
Using a Raspberry Pi¶
Before starting the Raspberry Pi, you need to install the operating system on a microSD card.
Once the OS is installed, you can insert the microSD card into the Raspberry Pi and power it on by plugging in the power adapter.
To use the Raspberry Pi, you need to connect it to a monitor (HDMI), keyboard and mouse (USB).
Acquire Images and Videos¶
There is official software from Raspberry Pi to acquire images and videos from the camera, namely the libcamera software stack and the Picamera2 Python library.
We found though that the OpenCV library is more convenient to use, and it is also more powerful. See the tutorial next.
Data Analysis¶
You can use whatever you like to analyse the data, but we recommend using Python and the Jupyter Notebook. In case you find the Raspberry Pi too slow for your analysis, you can use your own computer or Google Colab to analyse the data.
Install Jupyter Notebook¶
To install Jupyter Notebook on the Raspberry Pi, you can use the following commands (assuming python3-matplotlib and python3-scipy are already installed, see above):
pip3 install --upgrade pip
reboot
pip3 install jupyter
Plotting data¶
A quick reminder on how to plot data in Python using the matplotlib library.
from matplotlib import pyplot as plt
import numpy as np
An example of plotting a cosine and sine wave:
X = np.linspace(-np.pi, np.pi, 256, endpoint=True)
C, S = np.cos(X), np.sin(X)
plt.figure(figsize=(4,3))
plt.plot(X, C, color="blue", linewidth=2.5, linestyle="-", label="cos(x)")
plt.plot(X, S, color="red", linewidth=2.5, linestyle="-", label="sin(x)")
plt.xlabel("x")
plt.ylabel("y")
plt.legend(loc='upper left')
<matplotlib.legend.Legend at 0x122035010>
Let's see how to use it to fit a sine distribution to a set of data.
X = np.array([1,2,3,4,5,6,7,8,9,10])
Y = np.sin(X)+np.random.normal(0,0.05,10)
sY= np.ones(10)*0.1
plt.figure(figsize=(4,3))
plt.errorbar(X,Y,sY,fmt='o',color='black')
plt.xlabel("x")
plt.ylabel("y")
Text(0, 0.5, 'y')
Fitting Function¶
We need to specify the fitting function, which is a sine function in this case:
def func(x,A,w,phi):
return A*np.sin(w*x+phi)
iMinuit¶
iMinuit can be loaded with the following commands:
from iminuit import Minuit
from iminuit.cost import LeastSquares
and is called with the following syntax:
least_squares = LeastSquares (X, Y, sY, func)
my_minuit = Minuit (least_squares, A = 1, w = 1, phi=0) # starting values for A, w, and phi
my_minuit.migrad () # finds minimum of least_squares function
my_minuit.hesse () # accurately computes uncertainties
| Migrad | |
|---|---|
| FCN = 1.175 (χ²/ndof = 0.2) | Nfcn = 70 |
| EDM = 2.87e-05 (Goal: 0.0002) | |
| Valid Minimum | Below EDM threshold (goal x 10) |
| No parameters at limit | Below call limit |
| Hesse ok | Covariance accurate |
| Name | Value | Hesse Error | Minos Error- | Minos Error+ | Limit- | Limit+ | Fixed | |
|---|---|---|---|---|---|---|---|---|
| 0 | A | 0.99 | 0.04 | |||||
| 1 | w | 0.995 | 0.016 | |||||
| 2 | phi | 0.02 | 0.10 |
| A | w | phi | |
|---|---|---|---|
| A | 0.00201 | 0.01e-3 (0.013) | -0.0002 (-0.037) |
| w | 0.01e-3 (0.013) | 0.000253 | -1.50e-3 (-0.902) |
| phi | -0.0002 (-0.037) | -1.50e-3 (-0.902) | 0.011 |
Fit Results¶
Fit results are stored in the Minuit object and can be accessed with the following commands:
fit_info = []
for p, v, e in zip(my_minuit.parameters, my_minuit.values, my_minuit.errors):
fit_info.append(f"{p} = ${v:.3f} \\pm {e:.3f}$")
print(fit_info)
['A = $0.988 \\pm 0.045$', 'w = $0.995 \\pm 0.016$', 'phi = $0.016 \\pm 0.105$']
iMinuit in Colab¶
If you want to use iminuit in Colab, you can install it via pip in your notebook by calling
%pip install iminuit
ROOT with C++¶
As alternative to iminuit, you can use ROOT with C++ to fit your data.