我想对x-y数据执行绘图/拟合,前提是数据集的x值满足条件(即大于10)。
我的尝试:
x_values, y_values = loadtxt(fname, unpack=True, usecols=[1, 0])
for x in x_values:
if x > 10:
(m,b)=polyfit(x_values,y_values,1)
yp = polyval([m,b],x_values)
plot(x_values,yp)
scatter(x_values,y_values)
else:
pass
也许最好删除不符合x值条件的行的x-y条目,然后绘制/拟合?
答案 0 :(得分:16)
当然,只需使用布尔索引。您可以执行y = y[x > 10]
。
E.g。
import numpy as np
import matplotlib.pyplot as plt
#-- Generate some data...-------
x = np.linspace(-10, 50, 100)
y = x**2 + 3*x + 8
# Add a lot of noise to part of the data...
y[x < 10] += np.random.random(sum(x < 10)) * 300
# Now let's extract only the part of the data we're interested in...
x_filt = x[x > 10]
y_filt = y[x > 10]
# And fit a line to only that portion of the data.
model = np.polyfit(x_filt, y_filt, 2)
# And plot things up
fig, axes = plt.subplots(nrows=2, sharex=True)
axes[0].plot(x, y, 'bo')
axes[1].plot(x_filt, y_filt, 'bo')
axes[1].plot(x, np.polyval(model, x), 'r-')
plt.show()