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jbrezmorf
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Mar 31, 2026
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| import marimo | |||
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rename marimo ntb to : scalar_field_diff.py
| for i in range(grid_size): | ||
| for j in range(grid_size): | ||
| # Booleovská maska pro výběr bodů, které spadají přesně do aktuálního čtverce (okna) | ||
| mask = (x >= i*dx) & (x < (i+1)*dx) & (y >= j*dy) & (y < (j+1)*dy) |
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Make function for this kind of mask.
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| # Refaktorovat kód -> výpočty a složitější grafy do samostatného modulu/ modulů. | ||
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| class MeanCalculator: |
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Move ploting functions to separate file plots.py
| return plot1 + plot2 | ||
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| def multiscale_analysis(x: np.ndarray, y: np.ndarray, q_a_vals: np.ndarray, q_b_vals: np.ndarray) -> Tuple[plt.Figure, plt.Figure]: | ||
| grid_sizes = [2, 4, 8] |
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REmove, with replacement of matplotlib plots.
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| # Refaktorovat kód -> výpočty a složitější grafy do samostatného modulu/ modulů. | ||
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| class MeanCalculator: |
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create three classes one for each mean type with common interface:
@DataClass
class Geometric:
name: str
def mean(X):
return ....
| # … přepínání typu průměru | ||
| grid_slider = mo.ui.slider(start=2, stop=30, step=2, value=10, label="Velikost buněk (interaktivní)") | ||
| mean_dropdown = mo.ui.dropdown(options=["Aritmetický", "Geometrický", "Harmonický"], value="Aritmetický", label="Typ průměru") | ||
| return grid_slider, mean_dropdown |
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mean_dict = {'aritmetic' : Aritmetic, ...}
mean_class : Union[Aritmetic, Geometric, Harmonic]= mean_dict[mean_dropdown]
mean_obj = mean_class()
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zadani 24.03