Update Kalman_filter

Kalman_filter

@@ -94,10 +94,8 @@ stdprior = np.sqrt(np.diag(samp_var))
 gausspri = np.random.normal(loc=pri_mn[0], scale=stdprior[0], size=1000)
 gausspost = np.random.normal(loc=pos_mn[0], scale=stdfinal[0], size=1000)
 
-post_stats_90_pri = stats.quantiles(gausspri, qlist=(5, 95))
-post_stats_90_pri = [ v for v in post_stats_90_pri.values()]
-post_stats_90_post = stats.quantiles(gausspost, qlist=(5, 95))
-post_stats_90_post = [ v for v in post_stats_90_post.values()]
+post_stats_90_pri = np.percentile(gausspri, q=(5, 95))
+post_stats_90_post = np.percentile(gausspost, q=(5, 95))
 
 plt.xlabel('Climate Sensitivity')
 plt.ylabel('LGM tropical (20S - 30N) temperature change')