[FIXED] Summing Values automatically in Bar Chart

Issue

I'm trying to do a simple barchart on some data.

I've got a list of values x:

objective_values = np.array([ 0., -1., -1., 0., -1., 0., 0., 3., -1., -2., -2., -1., 0., 1. , 1., 4.])

and associated probabilities: probabilites = np.array([0.05664819, 0.09759888, 0.09759888 ,0.02133367, 0.14491666, 0.03902614, 0.03902614, 0.00385143, 0.08802889, 0.15658646, 0.15658646, 0.03704651, 0.04752267, 0.00210716, 0.00210716, 0.01001469])

which I'm trying to whack into a barchart together. However, when I do the simple code

objective,probabilities,objective_values = compute_mwis_energy_sv_bar_chart(statevector,G)

plt.bar(objective_values,probabilities)

Matplot doesn't sum the ordered probabilities I.e the value of -2 is 0.156, not 0.30. I've scoured all over but I can't find a way to do this simply - am I missing something ?

Solution

You can use .zip() to create a dictionary where you yourself sum up the probabilities for each objective value. Then pass that on to matplotlib

sums = {}
for key, value in zip(objective_values, probabilites):
    try:
        sums[key] += value
    except KeyError:
        sums[key] = value
print(sums)

Sums would be

{0.0: 0.20355680999999998, -1.0: 0.46518982000000003, 3.0: 0.00385143, -2.0: 0.31317292, 1.0: 0.00421432, 4.0: 0.01001469}

Then get the keys and values to get the lists

objective_values = list(sums.keys())
probabilites = list(sums.values())

This will give you

([0.0, -1.0, 3.0, -2.0, 1.0, 4.0],
 [0.20355680999999998,
  0.46518982000000003,
  0.00385143,
  0.31317292,
  0.00421432,
  0.01001469])

Answered By - Shubham Periwal