original_docstring: 
          Create track from unassociated measurement.
  
          Args:
              measurement (ndarray): Bounding box coordinates (x, y, a, h) with
                  center position (x, y), aspect ratio a, and height h.
  
          Returns:
              The mean vector (8 dimensional) and covariance matrix (8x8
              dimensional) of the new track. Unobserved velocities are
              initialized to 0 mean.
          
docstring: Create track from unassociated measurement.
docstring_tokens: Create track from unassociated measurement .
code: def initiate(self, measurement):
          """
          Create track from unassociated measurement.
  
          Args:
              measurement (ndarray): Bounding box coordinates (x, y, a, h) with
                  center position (x, y), aspect ratio a, and height h.
  
          Returns:
              The mean vector (8 dimensional) and covariance matrix (8x8
              dimensional) of the new track. Unobserved velocities are
              initialized to 0 mean.
          """
          mean_pos = measurement
          mean_vel = np.zeros_like(mean_pos)
          mean = np.r_[mean_pos, mean_vel]
  
          std = [
              2 * self._std_weight_position * measurement[3], 2 * self._std_weight_position * measurement[3], 1e-2,
              2 * self._std_weight_position * measurement[3], 10 * self._std_weight_velocity * measurement[3],
              10 * self._std_weight_velocity * measurement[3], 1e-5, 10 * self._std_weight_velocity * measurement[3]
          ]
          covariance = np.diag(np.square(std))
          return mean, covariance
code_tokens: def initiate ( self , measurement ) : mean_pos = measurement mean_vel = np . zeros_like ( mean_pos ) mean = np . r_ [ mean_pos , mean_vel ] std = [ 2 * self . _std_weight_position * measurement [ 3 ] , 2 * self . _std_weight_position * measurement [ 3 ] , 1e-2 , 2 * self . _std_weight_position * measurement [ 3 ] , 10 * self . _std_weight_velocity * measurement [ 3 ] , 10 * self . _std_weight_velocity * measurement [ 3 ] , 1e-5 , 10 * self . _std_weight_velocity * measurement [ 3 ] ] covariance = np . diag ( np . square ( std ) ) return mean , covariance
short_docstring: Create track from unassociated measurement.
short_docstring_tokens: Create track from unassociated measurement .
comment: """
          Create track from unassociated measurement.
  
          Args:
              measurement (ndarray): Bounding box coordinates (x, y, a, h) with
                  center position (x, y), aspect ratio a, and height h.
  
          Returns:
              The mean vector (8 dimensional) and covariance matrix (8x8
              dimensional) of the new track. Unobserved velocities are
              initialized to 0 mean.
          """