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jbrezmorf
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Mar 24, 2026
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| def multiscale_analysis(x, y, q_a_vals, q_b_vals): | ||
| grid_sizes = [2, 4, 8] |
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Používat typing: a: str, a: Dict[Union[str, int], float], a:Dict[Any,Any]
Pro xarray, ndarray:
Přidat k hlavním funkcím doc string s popisem vstupních parametrů.
"""
x - field A, has shape (N,N)
| qa_w = q_a_vals[mask, :] | ||
| qb_w = q_b_vals[mask, :] | ||
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| qa_arith = np.mean(qa_w, axis=0) |
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Modularize - create a class representing a "mean"
| dx = 1.0 / gs | ||
| dy = 1.0 / gs | ||
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| p_map_arith = np.full((gs, gs), np.nan) |
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Compute mean of whole array and use it as default value.
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| def perform_ttest(grid_A, grid_B): | ||
| t_stat, p_value = ttest_ind(grid_A, grid_B, axis=-1, equal_var=False, alternative='two-sided') |
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Je shape (gs, gs, N) ?
Nutno upravit aby se t_test pro jednu buňku počítal z původních hodnot bodů v buňce. V každé buňce je počet bodů jiný.
? test_ind s ignorováním NaN nebo pro maskovaná pole. np.masked_array
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