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MANE 3351 - Manufacturing Engineering Analysis

Laboratory 7 Assignment

Assigned: October 14, 2024

Due: October 23, 2024 (before 3:30 pm)

Learning Goals

  1. Vectorize function,
  2. Create arrays using Numpy, and
  3. Customize figures created with Matplotlib.

Description

This lab will utilize the standard (mu=0, sigma=1) largest value distribution introduced in Laboratory 6 to cover vectorizing functions, creating arrays using Numpy and customizing figures created with Matplotlib.

Step 1

Edit the first cell (markdown), to update your personal information.

Step 2

In cell two below the comment for step 2, vectorize the pdf function from Lab 6. Vectorizing a function was discussed in Lecture 11 on October 2.

Steps 3 - 6 are based upon the Python code from a laboratory assignment from a previous course that is provided below. Instead of using the gumbel_l function from Scipy.Stats, you will use the vectorized function created in step 2. You will ask the user to input and store a value (between -10 and +10). You will modify the code so that you plot the pdf highlighting values greater than the inputted value.

from scipy.stats import gumbel_l
import numpy as np
import matplotlib.pyplot as plt

a=float(input("Enter the value of x: "))

x=np.linspace(-8,8,500)
y=gumbel_l.pdf(x,0,1)
y2=0.0*x
maske =(x<a)

plt.plot(x,y,'b')
plt.fill_between(x,y,color='#666666',where=maske)
plt.plot(x,y2,'b')
plt.show()

Step 3

In cell two below the comment for step 3, create an array named x using the Numpy linspace function that creates an array containing 500 points from -10 to +10.

Step 4

In cell two below the step 4 comment line, create the array y using the vectorized function created in step 2 and create the array y2 using the same code provided in the example code.

Step 5

In cell two below the step 5 comment line, ask the user to input a value b between -10 and +10. Create the array maske that contains values of True when X>b and False when X<b.

Step 6

Copy the code to create a plot from the sample code to cell two below the comments for step 6. You are to change the color for the line used to plot y and y2 versus x. https://matplotlib.org/stable/gallery/color/named_colors.html provides a list of base colors that can easily be used.

Modify the color of the fill from #666666 to any other value. https://www.rapidtables.com/web/color/RGB_Color.html provides tools to pick a color. We are using the hex codes and not the RGB codes.

Step 7

After running and testing your program, save the Jupyter Notebook. Upload your repository using GitHub desktop.