Fix how the joint MultivariateGaussian prior is set when reading it from a file

import bilby

names = ["m", "c"]
mus = [[-5.0, -5.0], [5.0, 5.0]]  # means of the two modes
corrcoefs = [
    [[1.0, -0.7], [-0.7, 1.0]],
    [[1.0, 0.7], [0.7, 1.0]],
]  # correlation coefficients of the two modes
sigmas = [[1.5, 1.5], [2.1, 2.1]]  # standard deviations of the two modes
weights = [1.0, 3.0]  # relative weights of each mode
nmodes = 2
mvg = bilby.core.prior.MultivariateGaussianDist(
    names, nmodes=2, mus=mus, corrcoefs=corrcoefs, sigmas=sigmas, weights=weights
)
priors = bilby.core.prior.PriorDict()
priors["m"] = bilby.core.prior.MultivariateGaussian(mvg, "m")
priors["c"] = bilby.core.prior.MultivariateGaussian(mvg, "c")

# write out to file
priors.to_file(".", "mvgprior")

# write out to JSON file
priors.to_json(".", "mvgprior")

from bilby.core.prior import PriorDict
p = PriorDict()
p.from_file("mvgprior.prior")

from matplotlib import pyplot as plt

p = PriorDict.from_json("mvgprior_prior.json")

samps = priors.sample(10000)  # original prior dict
plt.scatter(samps["m"], samps["c"], label="Original")

nsamps = p.sample(10000)  # read-in prior
plt.scatter(nsamps["m"], nsamps["c"], alpha=0.1, label="read-in")
plt.legend()