bayesmark/experiment_analysis.py [149:158]:
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        rand_perf_med = baseline_ds[PERF_MED].sel({TEST_CASE: func_name}, drop=True).values
        rand_perf_mean = baseline_ds[PERF_MEAN].sel({TEST_CASE: func_name}, drop=True).values
        best_opt = baseline_ds[PERF_BEST].sel({TEST_CASE: func_name}, drop=True).values
        base_clip_val = baseline_ds[PERF_CLIP].sel({TEST_CASE: func_name}, drop=True).values

        assert np.all(np.diff(rand_perf_med) <= 0), "Baseline should be decreasing with iteration"
        assert np.all(np.diff(rand_perf_mean) <= 0), "Baseline should be decreasing with iteration"
        assert np.all(rand_perf_med > best_opt)
        assert np.all(rand_perf_mean > best_opt)
        assert np.all(rand_perf_mean <= base_clip_val)
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bayesmark/experiment_baseline.py [45:54]:
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        rand_perf_med = baseline_ds[PERF_MED].sel({TEST_CASE: func_name}, drop=True).values
        rand_perf_mean = baseline_ds[PERF_MEAN].sel({TEST_CASE: func_name}, drop=True).values
        best_opt = baseline_ds[PERF_BEST].sel({TEST_CASE: func_name}, drop=True).values
        base_clip_val = baseline_ds[PERF_CLIP].sel({TEST_CASE: func_name}, drop=True).values

        assert np.all(np.diff(rand_perf_med) <= 0), "Baseline should be decreasing with iteration"
        assert np.all(np.diff(rand_perf_mean) <= 0), "Baseline should be decreasing with iteration"
        assert np.all(rand_perf_med > best_opt)
        assert np.all(rand_perf_mean > best_opt)
        assert np.all(rand_perf_mean <= base_clip_val)
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