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# scipy.odr.RealData

class `scipy.odr.``RealData`(x, y=None, sx=None, sy=None, covx=None, covy=None, fix=None, meta={})

  The RealData class stores the weightings as actual standard deviations and/or covariances.

  The weights needed for ODRPACK are generated on-the-fly with __getattr__ trickery.

  sx and sy are standard deviations of x and y and are converted to weights by dividing 1.0 by their squares.

  > E.g. wd = 1./numpy.power(sx, 2)

  covx and covy are arrays of covariance matrices and are converted to weights by performing a matrix inversion on each observation’s covariance matrix.

  > E.g. we[i] = numpy.linalg.inv(covy[i]) # i in range(len(covy))
  >   # if covy.shape == (n,q,q)

  These arguments follow the same structured argument conventions as wd and we only restricted by their natures: sx and sy can’t be rank-3, but covx and covy can be.

  Only set either sx or covx (not both). Setting both will raise an exception. Same with sy and covy.

  The argument and member fix is the same as Data.fix and ODR.ifixx:
    It is an array of integers with the same shape as data.x that determines which input observations are treated as fixed. One can use a sequence of length m (the dimensionality of the input observations) to fix some dimensions for all observations. A value of 0 fixes the observation, a value > 0 makes it free.

  Methods

  `set_meta` |

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