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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def prop_triangle(self, **kwargs):
 """ Makes corner plot of only observable properties. The idea here is to compare the predictions of the samples with the actual observed data---this can be a quick way to check if there are outlier properties that aren't predicted well by the model. :param **kwargs: Keyword arguments passed to :func:`StarModel.triangle`. :return: Figure object containing corner plot. """

        truths = []
        params = []
        for p in self.properties:
            try:
                val, err = self.properties[p]
            except:
                continue

            if p in self.ic.bands:
                params.append('{}_mag'.format(p))
                truths.append(val)
            elif p=='parallax':
                params.append('distance')
                truths.append(1/(val/1000.))
            else:
                params.append(p)
                truths.append(val)
        return self.triangle(params, truths=truths, **kwargs)