import numpy as np import matplotlib.pyplot as plt import 数据 a_time = 数据.a_time a_flow = 数据.a_flow c_time = 数据.c_time c_flow = 数据.c_flow def lex(x,flow,time):#三项插值（抛物插值） lnx = flow[i] * (x - time[i + 1]) * (x - time[i + 2]) / ( (time[i] - time[i + 1]) * (time[i] - time[i + 2])) + \ flow[i + 1] * (x - time[i]) * (x - time[i + 2]) / ( (time[i + 1] - time[i]) * (time[i + 1] - time[i + 2])) + \ flow[i + 2] * (x - time[i]) * (x - time[i + 1]) / ( (time[i + 2] - time[i]) * (time[i + 2] - time[i + 1])) return lnx x1 = list() y1 = list() #a插值数据 x2 = list() y2 = list() #c插值数据 #a流量 for i in range(8): for x in np.arange(a_time[i], a_time[i + 2], 0.01): lx = lex(x,a_flow,a_time) y1.append(lx) x1.append(x) for i in range(len(x1)): #a插值平均 x1[i] = float('%.2f'%x1[i]) for j in range(len(x1)): for k in range(j+1,len(x1)): if x1[j] == x1[k]: y1[j] = (y1[j] + y1[k]) / 2 y1[k] = y1[j] #c流量 for i in range(13): for x in np.arange(c_time[i], c_time[i + 2], 0.01): lx = lex(x,c_flow,c_time) y2.append(lx) x2.append(x) for i in range(len(x2)): #c插值平均 x2[i] = float('%.2f'%x2[i]) for j in range(len(x2)): for k in range(j+1,len(x2)): if x2[j] == x2[k]: y2[j] = (y2[j] + y2[k]) / 2 y2[k] = y2[j] b_time = list() b_flow = list() for j in range(len(x1)): for k in range(len(x2)): if x1[j] == x2[k]: b_time.append(x1[j]) b_flow.append(y2[k]-y1[j]) plt.title("parabolic interpolation") plt.plot(x1, y1, '.') plt.plot(x2, y2, '.') plt.plot(b_time, b_flow, '.') plt.show()
能不能发个图片。。。文本太乱了吧。。。