Misc v2
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@@ -11,7 +11,7 @@ def print_filters(filters):
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def pprint(v):
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return f"\tMédia: {v[0]} \u00b1 {v[1]}; Mediana: {v[2]}; Máximo: {v[4]}; Mínimo: {v[3]}"
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return f"\tMédia: {v[0]} \u00b1 {v[1]}; 1o Quartil: {v[3]}; Mediana: {v[2]}; 3o Quartil: {v[4]}; Máximo: {v[5]}; Mínimo: {v[6]}"
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def stats(data):
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@@ -27,7 +27,7 @@ def stats(data):
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m = calc_mag(aux)
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d = calc_depth(aux)
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aux = []
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_stats += f"{currMonth.strftime('%Y-%m')}:\n\tMagnitude: {pprint(m)}\n\tProfundidade: {pprint(d)}\n"
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_stats += f"{currMonth.strftime('%Y-%m')}:\n\tMagnitude: {pprint(m)}\n\tProfundidade: {pprint(d)}\n\n"
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currMonth = data[idx]["DateTime"]
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m = calc_mag(aux)
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@@ -45,6 +45,7 @@ def calc_depth(data):
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if len(data) == 0:
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return 0
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depths = np.array([v["Depth"] for v in data], dtype=float)
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quantile = np.quantile(depths, [0.25, 0.75])
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return list(
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map(
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float,
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@@ -52,6 +53,8 @@ def calc_depth(data):
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round(np.average(depths), 3),
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round(np.std(depths), 3),
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round(np.median(depths), 3),
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round(quantile[0], 3),
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round(quantile[1], 3),
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np.min(depths),
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np.max(depths),
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),
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@@ -63,6 +66,7 @@ def calc_mag(data):
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if len(data) == 0:
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return 0
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mags = np.array([v["Magnitudes"]["L"]["Magnitude"] for v in data], dtype=float)
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quantile = np.quantile(mags, [0.25, 0.75])
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return list(
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map(
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float,
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@@ -70,6 +74,8 @@ def calc_mag(data):
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round(np.average(mags), 3),
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round(np.std(mags), 3),
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round(np.median(mags), 3),
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round(quantile[0], 3),
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round(quantile[1], 3),
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np.min(mags),
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np.max(mags),
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),
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