[FIXED] Plot three functions that share x-values

Issue

How should I plot three different averages sharing x-axis.

My attempt with errorbars showing also standard deviation doesn't let me insert more than one "score", resulting in a single line plot

This is what I did currently

    times_alg_1_sparse = times_alg1['Sparse']
    avg_alg1_50_sparse, std_alg1_50_sparse = extract_statistics(times_alg_1_sparse.iloc[0])
    avg_alg1_200_sparse, std_alg1_200_sparse = extract_statistics(times_alg_1_sparse.iloc[1])
    avg_alg1_600_sparse, std_alg1_600_sparse = extract_statistics(times_alg_1_sparse.iloc[2])
    x = np.array(times_alg_1_sparse.index)
    y = np.array([avg_alg1_50_sparse*1000, avg_alg1_200_sparse*1000, avg_alg1_600_sparse*1000])
    e = np.array([std_alg1_50_sparse*1000, std_alg1_200_sparse*1000, std_alg1_600_sparse*1000])
fig, ax = plt.subplots()
    ax.errorbar(x, y, e, mfc='red', linestyle='solid', marker='^', color='red')
    plt.ylim(0)
    plt.show()

Solution

You just have to call your plot function any times you want with different values.

I suppose your avg and std vectors have the same size, because they are output of the same function extract_statistics. You may have a problem with your vector x. Maybe the size of this vector does not match the size of avg and std vectors.

In the following solution we have three pairs of vectors avg and std: 50, 200, 600. We combine the 3 vectors in one vector y and e. So, in each iteration of the following for loop, we use the same vector x for the 3 different indexes from the vectors y and e. For this to work, we suppose the vector x and each element of y and e have the same size.

When we call something like y[:,0], for example, we are slicing the vector y and getting all the values of the first column of this vector.

times_alg_1_sparse = times_alg1['Sparse']

avg_alg1_50_sparse, std_alg1_50_sparse = extract_statistics(times_alg_1_sparse.iloc[0])
avg_alg1_200_sparse, std_alg1_200_sparse = extract_statistics(times_alg_1_sparse.iloc[1])
avg_alg1_600_sparse, std_alg1_600_sparse = extract_statistics(times_alg_1_sparse.iloc[2])

x = np.array(times_alg_1_sparse.index)
y = np.array([avg_alg1_50_sparse*1000, avg_alg1_200_sparse*1000, avg_alg1_600_sparse*1000])
e = np.array([std_alg1_50_sparse*1000, std_alg1_200_sparse*1000, std_alg1_600_sparse*1000])

colors = ['red', 'green', 'blue']    

for k in range(3):
    plt.errorbar(x, y[:,k], e[:,k], mfc=colors[k], linestyle='solid', marker='^', color=colors[k])

plt.ylim(0)
plt.show()

You are trying to use subplots. What is indicated when you want to plot, in the same figure, more than one graph.

Answered By - Lorran Sutter