Lab 2: Plotting and Visualization

Goal

The goal of this lab was to learn how to plot complex functions and how to visualize them since we will be doing this throughout the semester. We downloaded data sets and modified them into arrays to be plotted showing their relationships. We downloaded images and created lines of best fit for a data set. Used standard deviation and mean lines on a histogram to show values.

Overview

Download Data Set

Use the !wget to download data sets and use np.loadtxt to read the data

!wget
star_data = np.loadtxt('stars.txt')

Plot Sine and Cosine Functions

theta = np.linspace(0,2*np.pi,200)
r = np.sin(theta)

Downloading Images

!wget
myimage = image.imread("_____")

plt.imshow(myimage)

Fitting a Straight Line to Data

c = np.polyfit(x,y,1)
xline = np.linspace(xmin,xmax,100)
yline = np.polyval(c,xline)

Histogram of Random Numbers Showing Mean and Standard Deviation

gauss_values = np.random.normal(size=100)
plt.hist(gauss_values)
print("average value = {:.2f}".format(np.mean(gauss_values)))
print("the STD = {:.2f}".format(np.std(gauss_values)))

plt.axvline(np.mean(gauss_values),color='red')

plt.axvline(np.std(gauss_values),color='blue',linestyle='--')
plt.axvline(-np.std(gauss_values),color='cyan',linestyle='--')

Important Figures

Image of Star Data

Image of Sin and Cos

Custom Image

Plot Showing Line of Best Fit