Improving robustness on 2D plots and update statistics when rescaling…

… only the likelihood (#74)

* Reset means to None for forcing reevaluation in updateBaseStatistics for mcsamples objects

* Bound corr by max_corr_2D for avoiding potential issues with matrix inversion

Co-authored-by: chris <chris@ringeval.com>

getdist/mcsamples.py

@@ -491,6 +491,7 @@ def updateBaseStatistics(self):
 
         :return: self
         """
+        self.means = None
         super().updateBaseStatistics()
         mult_max = (self.mean_mult * self.numrows) / min(self.numrows // 2, 500)
         outliers = np.sum(self.weights > mult_max)
@@ -1659,6 +1660,7 @@ def get2DDensityGridData(self, j, j2, num_plot_contours=None, get_density=False,
         corr = self.getCorrelationMatrix()[j2][j]
         if corr == 1:
             logging.warning('Parameters are 100%% correlated: %s, %s', parx.name, pary.name)
+            corr = self.max_corr_2D
 
         logging.debug('Doing 2D: %s - %s', parx.name, pary.name)
         logging.debug('sample x_err, y_err, correlation: %s, %s, %s', parx.err, pary.err, corr)