[英]TypeError: 'numpy.ndarray' object is not callable, for comparing two lines
I tried to compare two plotted lines.
我试图比较两条绘制的线。 I first load two data files and assign the x and y, and then tried to even the points on the x axes.
我首先加载两个数据文件并分配 x 和 y,然后尝试平衡 x 轴上的点。 However, an error popped out:
但是,弹出一个错误:
Traceback (most recent call last): File "/Users/renzha/Documents/compare two lines.py", line 33, in
xnew = data1[:,0] ( min(x), max(x), num = points)
TypeError: 'numpy.ndarray' object is not callable回溯(最近一次调用最后一次):文件“/Users/renzha/Documents/compare two lines.py”,第33行,在
xnew = data1[:,0] ( min(x), max(x), num = points)
TypeError: 'numpy.ndarray' 对象不可调用
Original code is:
原代码为:
import numpy as np
from scipy.interpolate import interp1d
import matplotlib.pyplot as plt
import scipy.spatial.distance as ssd
import scipy.stats as ss
data1 = np.loadtxt(filedialog.askopenfilename(), delimiter='\t')
data2 = np.loadtxt(filedialog.askopenfilename(), delimiter='\t')
x = data1[:,0]
y = data1[:,1]
x2 = data2[:,0]
y2 = data2[:,1]
f = interp1d(x, y)
f2 = interp1d(x2,y2)
points = 150
xnew = data1[:,0] ( min(x), max(x), num = points)
xnew2 = data2[:,0] ( min(x2), max(x2), num = points)
ynew = f(xnew)
ynew2 = f2(xnew2)
plt.plot(x,y, 'r', x2, y2, 'g', xnew, ynew, 'r--', xnew2, ynew2, 'g--')
plt.show()
print (ssd.correlation(ynew, ynew2))
print (np.correlate(ynew, ynew2, mode='valid'))
print (np.corrcoef(ynew, ynew2))
print (ss.spearmanr(ynew, ynew2))
As the errors said, your data data1[:,0]
and data2[:,0]
are numpy arrays.正如错误所说,您的数据
data1[:,0]
和data2[:,0]
是 numpy 数组。 I guess you are trying to apply a function with parameters ( min(x), max(x), num = points)
, check again the code to see which function should be used there.我猜你正在尝试应用一个带参数的函数
( min(x), max(x), num = points)
,再次检查代码以查看应该在那里使用哪个函数。 Looking at the name of the parameters, maybe numpy.linspace(start, stop, num= ...)
could help.查看参数的名称,也许
numpy.linspace(start, stop, num= ...)
会有所帮助。
https://numpy.org/doc/stable/reference/generated/numpy.linspace.html#numpy.linspace https://numpy.org/doc/stable/reference/generated/numpy.linspace.html#numpy.linspace
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