mcmc_inversion.py
def generate_prior(self):
        """
        Generate a prior starting model from a uniform probability
        distribution
        """
        prior_model = np.random.uniform(low=self.prior_low, 
                                        high=self.prior_high, 
                                        size=self.mlen)

        return prior_model

        Generate a prior starting model from a uniform probability
        distribution
        
Generate a prior starting model from a uniform probability
distribution
Generate a prior starting model from a uniform probability distribution
def generate_prior(self):
        prior_model = np.random.uniform(low=self.prior_low, 
                                        high=self.prior_high, 
                                        size=self.mlen)
        return prior_model
def generate_prior ( self ) : prior_model = np . random . uniform ( low = self . prior_low , high = self . prior_high , size = self . mlen ) return prior_model
Generate a prior starting model from a uniform probability
distribution
Generate a prior starting model from a uniform probability distribution
"""
        Generate a prior starting model from a uniform probability
        distribution
        """
self