4.8.3 Interpolar - tortuga Galápagos

Ejercicio de interpolación

espol polito logo
  • Desarrollar por grupos
  • integrar soluciones en un mismo gráfico
  • mostrar polinomios y rangos de existencia
mascota Tortuga Galápagos interpolar por partes
# caparazon superior
xiA = [113., 117, 134, 153, 169, 184, 194, 203]
fiA = [127., 141, 161, 166, 160, 155, 140, 132]

# caparazon inferior 1
xiB = [113., 123, 130, 149, 182, 197, 208, 211]
fiB = [127., 116, 112, 107, 110, 114, 112, 108]

# caparazon inferior 2
xiC = [107., 114, 120, 143, 170, 192, 210]
fiC = [124., 114, 108, 99, 99, 106, 107]

# Patas 01
xiD = [110., 116, 120, 121, 134, 143, 153, 168, 173, 177, 181, 188, 194, 201, 205, 210, 214, 218]
fiD = [92., 86, 89, 86, 87, 95, 91, 93, 85, 85, 83, 86, 88, 86, 91, 87, 92, 92]

# Patas 02
xiE = [109., 115, 117, 120, 125, 130, 134, 138, 142, 145, 150, 152, 154]
fiE = [91., 87, 82, 82, 78, 78, 81, 78, 76, 79, 77, 80, 86]

# Patas 03
xiF = [172., 175, 182, 186, 191, 195, 201, 205, 210, 211, 217]
fiF = [86., 79, 79, 77, 82, 78, 81, 79, 82, 85, 90]

# Patas 04
xiG = [113., 118, 122, 127, 132, 136, 140, 144, 149, 152]
fiG = [88., 90, 88, 86, 85, 83, 87, 84, 86, 85]

# Rabito 01
xiH = [97., 102, 108, 111, 117, 121]
fiH = [120., 113, 108, 105, 102, 102]

# cabeza 01
xiI = [194., 196, 203, 210, 211, 209]
fiI = [177., 167, 157, 149, 138, 135]

# cabeza 02
xiJ = [195., 199, 207, 214, 219, 224, 229, 234, 239, 242, 244]
fiJ = [177., 185, 190, 190, 188, 193, 192, 185, 175, 172, 168]

# cabeza 03
xiK = [220., 226, 234, 239, 241]
fiK = [164., 162, 163, 163, 163]

# cabeza 04
xiL = [203., 211, 214, 219, 223, 224, 225, 230, 236, 241]
fiL = [115., 119, 125, 124, 127, 137, 146, 149, 154, 162]

# cabeza 05
xiM = [208., 212, 215, 219, 221, 225, 228]
fiM = [174., 177, 178, 179, 182, 183, 178]

# cabeza 06
xiN = [206., 210, 214, 218, 220, 224, 229, 233, 232]
fiN = [179., 182, 182, 181, 174, 171, 170, 175, 180]

1.1 Algoritmo inicial en Python para puntos en la gráfica

# taller de Interpolacion
# gráfica de puntos por grupos
import numpy as np

# INGRESO
titulo = 'tortuga galapagos'

# caparazon superior
xiA = [113., 117, 134, 153, 169, 184, 194, 203]
fiA = [127., 141, 161, 166, 160, 155, 140, 132]

# caparazon inferior 1
xiB = [113., 123, 130, 149, 182, 197, 208, 211]
fiB = [127., 116, 112, 107, 110, 114, 112, 108]

# caparazon inferior 2
xiC = [107., 114, 120, 143, 170, 192, 210]
fiC = [124., 114, 108, 99, 99, 106, 107]

# Patas 01
xiD = [110., 116, 120, 121, 134, 143, 153, 168, 173, 177, 181, 188, 194, 201, 205, 210, 214, 218]
fiD = [92., 86, 89, 86, 87, 95, 91, 93, 85, 85, 83, 86, 88, 86, 91, 87, 92, 92]

# Patas 02
xiE = [109., 115, 117, 120, 125, 130, 134, 138, 142, 145, 150, 152, 154]
fiE = [91., 87, 82, 82, 78, 78, 81, 78, 76, 79, 77, 80, 86]

# Patas 03
xiF = [172., 175, 182, 186, 191, 195, 201, 205, 210, 211, 217]
fiF = [86., 79, 79, 77, 82, 78, 81, 79, 82, 85, 90]

# Patas 04
xiG = [113., 118, 122, 127, 132, 136, 140, 144, 149, 152]
fiG = [88., 90, 88, 86, 85, 83, 87, 84, 86, 85]

# Rabito 01
xiH = [97., 102, 108, 111, 117, 121]
fiH = [120., 113, 108, 105, 102, 102]

# cabeza 01
xiI = [194., 196, 203, 210, 211, 209]
fiI = [177., 167, 157, 149, 138, 135]

# cabeza 02
xiJ = [195., 199, 207, 214, 219, 224, 229, 234, 239, 242, 244]
fiJ = [177., 185, 190, 190, 188, 193, 192, 185, 175, 172, 168]

# cabeza 03
xiK = [220., 226, 234, 239, 241]
fiK = [164., 162, 163, 163, 163]

# cabeza 04
xiL = [203., 211, 214, 219, 223, 224, 225, 230, 236, 241]
fiL = [115., 119, 125, 124, 127, 137, 146, 149, 154, 162]

# cabeza 05
xiM = [208., 212, 215, 219, 221, 225, 228]
fiM = [174., 177, 178, 179, 182, 183, 178]

# cabeza 06
xiN = [206., 210, 214, 218, 220, 224, 229, 233, 232]
fiN = [179., 182, 182, 181, 174, 171, 170, 175, 180]

# todos los grupos
xi = [xiA,xiB,xiC,xiD,xiE,xiF,xiG,xiH,xiI,xiJ,xiK,xiL,xiM]
fi = [fiA,fiB,fiC,fiD,fiE,fiF,fiG,fiH,fiI,fiJ,fiK,fiL,fiM]
etiq = ['A','B','C','D','E','F','G','H','I','J','K','L','M']

# PROGRAMA
n = len(xi)
# convierte en arreglos cada grupo de datos
for j in range(0,n,1):
    xi[j] = np.array(xi[j],dtype=float)
    fi[j] = np.array(fi[j],dtype=float)

# SALIDA
print(titulo)

# GRAFICA ---------------------
import matplotlib.pyplot as plt

for j in range(0,n,1):
    plt.plot(xi[j],fi[j],'.', label=etiq[j])
    
# entorno de gráfica
plt.xlabel('xi')
plt.ylabel('fi')
plt.title(titulo)
plt.legend()
plt.grid()
plt.tight_layout()
plt.show()

Unidades MN