(data, med, iqr, bootstrap)
| 1242 | return CI |
| 1243 | |
| 1244 | def _compute_conf_interval(data, med, iqr, bootstrap): |
| 1245 | if bootstrap is not None: |
| 1246 | # Do a bootstrap estimate of notch locations. |
| 1247 | # get conf. intervals around median |
| 1248 | CI = _bootstrap_median(data, N=bootstrap) |
| 1249 | notch_min = CI[0] |
| 1250 | notch_max = CI[1] |
| 1251 | else: |
| 1252 | |
| 1253 | N = len(data) |
| 1254 | notch_min = med - 1.57 * iqr / np.sqrt(N) |
| 1255 | notch_max = med + 1.57 * iqr / np.sqrt(N) |
| 1256 | |
| 1257 | return notch_min, notch_max |
| 1258 | |
| 1259 | # output is a list of dicts |
| 1260 | bxpstats = [] |
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