tp/scripts/valores_normalizados_H1.py (2329B)
1 import itertools 2 3 # Capacitores 4 E6_C = [1.0, 1.5, 2.2, 3.3, 4.7, 6.8] 5 6 # resistencias de 5% de error 7 E24_R = [ 8 1.0, 1.1, 1.2, 1.3, 1.5, 1.6, 1.8, 2.0, 2.2, 2.4, 2.7, 3.0, 9 3.3, 3.6, 3.9, 4.3, 4.7, 5.1, 5.6, 6.2, 6.8, 7.5, 8.2, 9.1 10 ] 11 12 E24_R_custom = [ 13 1.0, 1.1, 1.2, 1.3, 1.5, 1.6, 1.8, 2.0, 2.2, 2.4, 2.7, 3.0, 14 3.3, 3.6, 3.9, 4.3, 4.7, 5.1, 5.6, 6.2, 6.8, 7.5, 8.2 15 ] 16 17 # resistencias de 2% de error 18 E48_R = [ 19 1.00, 1.05, 1.10, 1.15, 1.21, 1.27, 1.33, 1.40, 1.47, 1.54, 1.62, 1.69, 20 1.78, 1.87, 1.96, 2.05, 2.15, 2.26, 2.37, 2.49, 2.61, 2.74, 2.87, 3.01, 21 3.16, 3.32, 3.48, 3.65, 3.83, 4.02, 4.22, 4.42, 4.64, 4.87, 5.11, 5.36, 22 5.62, 5.90, 6.19, 6.49, 6.81, 7.15, 7.50, 7.87, 8.25, 8.66, 9.09, 9.53 23 ] 24 25 # resistencias de 1% de error 26 E96_R = [ 27 1.00, 1.02, 1.05, 1.07, 1.10, 1.13, 1.15, 1.18, 1.21, 1.24, 1.27, 1.30, 28 1.33, 1.37, 1.40, 1.43, 1.47, 1.50, 1.54, 1.58, 1.62, 1.65, 1.69, 1.74, 29 1.78, 1.82, 1.87, 1.91, 1.96, 2.00, 2.05, 2.10, 2.15, 2.21, 2.26, 2.32, 30 2.37, 2.43, 2.49, 2.55, 2.61, 2.67, 2.74, 2.80, 2.87, 2.94, 3.01, 3.09, 31 3.16, 3.24, 3.32, 3.40, 3.48, 3.57, 3.65, 3.74, 3.83, 3.92, 4.02, 4.12, 32 4.22, 4.32, 4.42, 4.53, 4.64, 4.75, 4.87, 4.99, 5.11, 5.23, 5.36, 5.49, 33 5.62, 5.76, 5.90, 6.04, 6.19, 6.34, 6.49, 6.65, 6.81, 6.98, 7.15, 7.32, 34 7.50, 7.68, 7.87, 8.06, 8.25, 8.45, 8.66, 8.87, 9.09, 9.31, 9.53, 9.76 35 ] 36 37 SERIE_R = E24_R_custom 38 SERIE_C = E6_C 39 40 # décadas 41 DECADAS_R = [1, 10, 100, 1_000, 10_000, 100_000] 42 DECADAS_C = [1e-9, 10e-9, 100e-9, 1e-6] # pF–uF 43 44 # lista de resistencias y capacitores disponibles 45 resistencias = [v * d for v, d in itertools.product(SERIE_R, DECADAS_R)] 46 capacitores = [v * d for v, d in itertools.product(SERIE_C, DECADAS_C)] 47 48 # a = 1/(RC) 49 def find_lower_error(a, res_list=resistencias, cap_list=capacitores): 50 resultados = [] 51 52 for R in resistencias: 53 C_ideal = 1/(250*R) 54 55 for C in capacitores: 56 err = abs((C - C_ideal)/C_ideal)*100 57 resultados.append((err, R, C, C_ideal)) 58 59 resultados.sort(key=lambda x: x[0]) 60 61 return resultados 62 63 if __name__ == "__main__": 64 resultados = find_lower_error(250) 65 66 print(" R [Ω] C [F] Cideal [F] Error [%]") 67 for err, R, C, Cideal in resultados[:20]: 68 print(f"{R:9.0f} {C:9.2e} {Cideal:9.2e} {err:6.2f}")