[FIXED] How to use fill_between utilizing the where parameter

Issue

So following a tutorial, I tried to create a graph using the following code:

time_values = [i for i in range(1,100)]
execution_time = [random.randint(0,100) for i in range(1,100)]
fig = plt.figure()
ax1 = plt.subplot()
threshold=[.8 for i in range(len(execution_time))]
ax1.plot(time_values, execution_time)
ax1.margins(x=-.49, y=0)
ax1.fill_between(time_values,execution_time, 1,where=(execution_time>1), color='r', alpha=.3)

This did not work as I got an error saying I could not compare a list and an int. However, I then tried:

ax1.fill_between(time_values,execution_time, 1)

And that gave me a graph with all area in between the execution time and the y=1 line, filled in. Since I want the area above the y=1 line filled in, with the area below left un-shaded, I created a list called threshold, and populated it with 1 so that I could recreate the comparison. However,

ax1.fill_between(time_values,execution_time, 1,where=(execution_time>threshold)

and

ax1.fill_between(time_values,execution_time, 1)

create the exact same graph, even though the execution times values do go beyond 1.

I am confused for two reasons: firstly, in the tutorial I was watching, the teacher was able to successfully compare a list and an integer within the fill_between function, why was I not able to do this? Secondly, why is the where parameter not identifying the regions I want to fill? Ie, why is the graph shading in the areas between the y=1 and the value of the execution time?

Solution

The problem is mainly due the use of python lists instead of numpy arrays. Clearly you could use lists, but then you need to use them throughout the code.

import numpy as np
import matplotlib.pyplot as plt

time_values = list(range(1,100))
execution_time = [np.random.randint(0,100) for _ in range(len(time_values))]
threshold = 50


fig, ax = plt.subplots()

ax.plot(time_values, execution_time)
ax.fill_between(time_values, execution_time, threshold,
                where= [e > threshold for e in execution_time], 
                color='r', alpha=.3)

ax.set_ylim(0,None)
plt.show()

Better is the use of numpy arrays throughout. It's not only faster, but also easier to code and understand.

import numpy as np
import matplotlib.pyplot as plt

time_values = np.arange(1,100)
execution_time = np.random.randint(0,100, size=len(time_values))
threshold = 50


fig, ax = plt.subplots()

ax.plot(time_values, execution_time)
ax.fill_between(time_values,execution_time, threshold,
                where=(execution_time > threshold), color='r', alpha=.3)

ax.set_ylim(0,None)
plt.show()

Answered By - ImportanceOfBeingErnest