title: Fitting multiple component GammaDistribution using PomeGranate
body: <p>I am trying to generate a HMM model from some data, It should consist of 3 independent Gamma distributions, but i get the following error which i cannot seem to solve:</p>
  
  <pre><code>ValueError: shapes (909,1) and (909,1) not aligned: 1 (dim 1) != 909 (dim 0)
  </code></pre>
  
  <p>The follow is my setup and some generated data to work with:
  from pomegranate import *
      import random
      import numpy as np</p>
  
  <pre><code>data = list(np.random.normal(loc = 0, scale = 1,size = 1000))
  data = np.asarray(data)
  data = data.reshape(-1, 1)
  
  model3 = HiddenMarkovModel.from_samples(GammaDistribution, n_components=3, X=data)
  </code></pre>
  
  <p>The setup works if i simply use a NormalDistribution instead</p>