如何获得多个文本文件的误差条图的拟合曲线

Question

我写了一个代码来获取误差条和曲线拟合线。但是我收到一个错误。我已经从这个网页的答案中尝试了这个曲线拟合线代码，但它对我不起作用。你能帮我吗？

我的代码：

#!/home/zahid/anaconda3/bin/python
import numpy as np
import matplotlib.pyplot as plt
import numpy
from scipy.optimize import curve_fit


x1, y1, y2,y3,y4,y5,y6 = [], [], [],[],[], [], [],[],[], [], [],[]

with open("1_peak.txt") as f:
    for line in f:
    cols = line.split()
    x1.append(float(cols[0]))
    y1.append(float(cols[2]))

with open("2_peak.txt") as f:
    for line in f:
    cols = line.split()
    x2.append(float(cols[0]))
    y2.append(float(cols[2]))
.
.
.

with open("6_peak.txt") as f:
    for line in f:
    cols = line.split()
    x6.append(float(cols[0]))
    y6.append(float(cols[2]))


for item_a, item_b, item_d, item_e, item_f, item_g, item_c in zip(y1, y2,y3,y4,y5,y6, x1):


 B = (item_a + item_b + item_d + item_e + item_f + item_g)/6
 arr = numpy.array([item_a, item_b, item_d, item_e, item_f, item_g])
 C = numpy.mean(arr, axis=0)
 D = numpy.std(arr, axis=0)

 print (item_c, C , D)

 x = np.array(item_c)
 y = np.array(C) 
 e = np.array(D)

 def line(x, a, b):
    return a * x + b

 popt, pcov = curve_fit(line, x, y)
 plt.errorbar(x, y, e, linestyle='None', marker='^')
 xfine = np.linspace(0., 100., 100)  
 plt.plot(xfine, line(xfine, popt[0], popt[1]), 'r-')
 plt.xlabel('PKA_energy in keV')
 plt.ylabel('intersitial')
 plt.savefig("1.jpeg", dpi=500)

我遇到以下错误：

Traceback (most recent call last):
File "./value_analysis_peak_SIA_energy.py", line 70, in <module>
popt, pcov = curve_fit(line, x, y)
File "/home/zahid/anaconda3/lib/python3.6/site-packages/scipy/optimize/minpack.py", line 736, in curve_fit
res = leastsq(func, p0, Dfun=jac, full_output=1, **kwargs)
File "/home/zahid/anaconda3/lib/python3.6/site-packages/scipy/optimize/minpack.py", line 380, in leastsq
raise TypeError('Improper input: N=%s must not exceed M=%s' % (n, m))
TypeError: Improper input: N=2 must not exceed M=1

Answer 1

我认为这与您想要做的类似，请尝试并根据您的工作需要进行修改。这里我用二次曲线来拟合数据，多项式阶数设置在代码的顶部。

#!/home/zahid/anaconda3/bin/python
import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit


polynomialOrder = 2 # example quadratic

x1 = []
x2 = []
x6 = []

y1 = []
y2 = []
y6 = []


# load the raw data
with open("1_peak.txt") as f:
    for line in f:
        cols = line.split()
        x1.append(float(cols[0]))
        y1.append(float(cols[2]))

with open("2_peak.txt") as f:
    for line in f:
        cols = line.split()
        x2.append(float(cols[0]))
        y2.append(float(cols[2]))

with open("6_peak.txt") as f:
    for line in f:
        cols = line.split()
        x6.append(float(cols[0]))
        y6.append(float(cols[2]))


# fit each data set to individual polynomials
parms1 = np.polyfit(x1, y1, polynomialOrder)
parms2 = np.polyfit(x2, y2, polynomialOrder)
parms6 = np.polyfit(x6, y6, polynomialOrder)


# calculate errors for each fit
err1 = np.polyval(parms1, x1) - y1
err2 = np.polyval(parms2, x2) - y2
err6 = np.polyval(parms6, x6) - y6


# graph size is set before calling plot commands
graphWidth = 800 # pixels
graphHeight = 600 # pixels
plt.figure(figsize=(graphWidth/100.0, graphHeight/100.0), dpi=100)


# plot the raw data as error-bar scatter plots
plt.errorbar(x1, y1, err1, linestyle='None', marker='^')
plt.errorbar(x2, y2, err2, linestyle='None', marker='^')
plt.errorbar(x6, y6, err6, linestyle='None', marker='^')


# plot the fitted polynomials
xmodel1 = np.linspace(min(x1), max(x1))
ymodel1 = np.polyval(parms1, xmodel1)

xmodel2 = np.linspace(min(x2), max(x2))
ymodel2 = np.polyval(parms2, xmodel2)

xmodel6 = np.linspace(min(x6), max(x6))
ymodel6 = np.polyval(parms6, xmodel6)

plt.plot(xmodel1, ymodel1)
plt.plot(xmodel2, ymodel2)
plt.plot(xmodel6, ymodel6)


# final code here
plt.xlabel('PKA_energy in keV')
plt.ylabel('intersitial')

plt.show()



'''
popt, pcov = curve_fit(line, x, y)
plt.errorbar(x, y, e, linestyle='None', marker='^')
xfine = np.linspace(0., 100., 100)  
plt.plot(xfine, line(xfine, popt[0], popt[1]), 'r-')
plt.xlabel('PKA_energy in keV')
plt.ylabel('intersitial')
#plt.savefig("1.jpeg", dpi=500)
plt.show()
'''

如何获得多个文本文件的误差条图的拟合曲线

How to get fitted curve for errorbar graph for several text files

matplotlib

curve-fitting

python-3.x

anaconda

errorbar