我试图使用np.polyfit
来填充一个相当简单的数据集,但它的相关幅度相当大:
代码:
import numpy as np
import matplotlib as plt
fit = np.polyfit(xvals, yvals, 1)
f = np.poly1d(fit)
plt.scatter(xvals, yvals, color="blue", label="input")
plt.scatter(xvals, f(yvals), color="red", label="fit")
plt.legend()
我做错了什么?我怎样才能提高适合度?
原始数据:
xvals = array([ 0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 14,
15, 16, 17, 18, 20, 21, 22, 23, 24, 25, 27, 28, 29,
30, 31, 32, 34, 35, 36, 37, 38, 40, 41, 42, 43, 44,
45, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 60,
61, 62, 63, 64, 65, 67, 68, 69, 70, 71, 72, 74, 75,
76, 77, 78, 80, 81, 82, 83, 84, 85, 87, 88, 89, 90,
91, 92, 94, 95, 96, 97, 98, 100])
yvals = array([ 0, 3, 5, 8, 10, 12, 15, 17, 19, 21, 23, 25, 27,
28, 30, 32, 33, 35, 36, 37, 39, 40, 41, 43, 44, 45,
46, 47, 48, 49, 50, 51, 52, 53, 54, 54, 55, 56, 57,
58, 58, 59, 60, 61, 61, 62, 63, 63, 64, 65, 66, 66,
67, 67, 68, 69, 70, 70, 71, 72, 73, 73, 74, 75, 76,
77, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 89,
90, 91, 92, 94, 95, 97, 98, 100])
答案 0 :(得分:5)
您需要f(xvals)
而不是f(yvals)
。但是当然你可以为这个数据做更好的更高阶多项式。例如,
import numpy as np
import matplotlib.pyplot as plt
xvals = np.array([ 0, 1, 2, 3, 4, 5, 7, 8, 9, 10, 11, 12, 14,
15, 16, 17, 18, 20, 21, 22, 23, 24, 25, 27, 28, 29,
30, 31, 32, 34, 35, 36, 37, 38, 40, 41, 42, 43, 44,
45, 47, 48, 49, 50, 51, 52, 54, 55, 56, 57, 58, 60,
61, 62, 63, 64, 65, 67, 68, 69, 70, 71, 72, 74, 75,
76, 77, 78, 80, 81, 82, 83, 84, 85, 87, 88, 89, 90,
91, 92, 94, 95, 96, 97, 98, 100])
yvals = np.array([ 0, 3, 5, 8, 10, 12, 15, 17, 19, 21, 23, 25, 27,
28, 30, 32, 33, 35, 36, 37, 39, 40, 41, 43, 44, 45,
46, 47, 48, 49, 50, 51, 52, 53, 54, 54, 55, 56, 57,
58, 58, 59, 60, 61, 61, 62, 63, 63, 64, 65, 66, 66,
67, 67, 68, 69, 70, 70, 71, 72, 73, 73, 74, 75, 76,
77, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 89,
90, 91, 92, 94, 95, 97, 98, 100])
fit = np.polyfit(xvals, yvals, 3)
f = np.poly1d(fit)
#print f
fig, ax = plt.subplots(1,1,figsize=(6,4),dpi=400)
ax.scatter(xvals, yvals, color="blue", label="input")
ax.scatter(xvals, f(xvals), color="red", label="fit")
ax.legend()
plt.show()