parameters: (self)
return_statement: return np.log10(covTrans / paramSizes)
docstring: Coverage vector considering the logarithmic transformation.
docstring_summary: Coverage vector considering the logarithmic transformation.
docstring_tokens: Coverage vector considering the logarithmic transformation .
function: def coverage(self):
          """Coverage vector considering the logarithmic transformation."""
          covTrans = pg.core.coverageDCtrans(self.fop.jacobian(),
                                             1.0 / self.inv.response,
                                             1.0 / self.inv.model)
  
          paramSizes = np.zeros(len(self.inv.model))
          for c in self.fop.paraDomain.cells():
              paramSizes[c.marker()] += c.size()
  
          return np.log10(covTrans / paramSizes)
function_tokens: def coverage ( self ) : covTrans = pg . core . coverageDCtrans ( self . fop . jacobian ( ) , 1.0 / self . inv . response , 1.0 / self . inv . model ) paramSizes = np . zeros ( len ( self . inv . model ) ) for c in self . fop . paraDomain . cells ( ) : paramSizes [ c . marker ( ) ] += c . size ( ) return np . log10 ( covTrans / paramSizes )