def ts_stats_significance_bootstrap(ts, stats_ts, stats_func, B=<NUM_LIT:1000>, b=<NUM_LIT:3>):
pvals = []<EOL>for tp in np.arange(<NUM_LIT:0>, len(stats_ts)):<EOL><INDENT>pf = partial(stats_func, t=tp)<EOL>bs = bootstrap_ts(ts, pf, B=B, b=b)<EOL>ci = get_ci(bs, blockratio=b / len(stats_ts))<EOL>pval = abs(get_pvalue(stats_ts[tp], ci))<EOL>pvals.append(pval)<EOL><DEDENT>return pvals<EOL>
Compute  the statistical significance of a test statistic at each point
        of the time series by using timeseries boootstrap.