0

我有一个读取 50 个文本文件的代码，每个文件生成一个直方图，并且为每个直方图拟合一个高斯。然后获取每个高斯下的区域并根据时间绘制（本质上是它乘以 18 的文本文件）。

然后我想在原始数据中单独操作这些数据。我可以获取代码以从图表中打印出 y 值，但我正在努力将其更改为可以复制并粘贴到原始电子表格格式的表单。

打印出来的是：

77.78630383833547, 62.92926582239441, 63.84025706577048, 55.489066870438165, 38.60797989548756, 40.771390484048545, 14.679073842876978, 33.95959972488966, 29.41960790300141, 32.93241034391399, 30.927428194781815, 31.086396885182356, 21.52771899125612, 4.27684299160886, 6.432975528727562, 7.500376934048583, 18.730555740591637, 4.355896959987761, 11.677509915219987, 12.865482314301719, 0.6120306267606219, 12.614420497451556, 2.2025029753442404, 9.447046999592711, 4.0688197216393425, 0.546672901996845, 1.12780050608251, 2.2030852358874635, 2.202804718915858, 0.5726686031033587, 0.5465322281618783, 0.5185100682386156, 0.575055917739342, 0.5681697592593679

完整代码在这里，如果需要的话。我猜另一个变量我只写了 0, 18, 36, 54 ......所以可能不需要 python！

更新 请求了相关的代码示例。我认为这是一个最小的例子。我正在尝试输出的相关变量是安培。我不介意这是通过保存文件（可能是首选）还是在 IDE 控制台中完成的。

import numpy as np
import matplotlib.pyplot as plt
from scipy.optimize import curve_fit
from numpy import exp, loadtxt, pi, sqrt, random, linspace
from lmfit import Model
import glob, os

## Define gaussian
def gaussian(x, amp, cen, wid):
    """1-d gaussian: gaussian(x, amp, cen, wid)"""
    return (amp / (sqrt(2*pi) * wid)) * exp(-(x-cen)**2 / (2*wid**2))

## Define exponential decay
def expdecay(x, t, A): 
     return A*exp(-x/t)

## Define constants
fileToRun = 'Run0'
location = 'ControlRoom6'
stderrThreshold = 10
minimumAmplitude = 0.1
approxcen = 780
DeadTime = 3
LiveTime = 15


## Get location of files to be loaded

## Define paramaters
amps = []; ampserr = []; ts = []
folderToAnalyze = baseFolder + fileToRun + '\\'

## Generate the time array and coincidence plots
for n in range(0, numfiles):
    
    ## Load text file
    x = np.linspace(0, 8191, 8192)
    finalprefix = str(n).zfill(3)
    fullprefix = folderToAnalyze + prefix + finalprefix
    y = loadtxt(fullprefix + ".Spe", skiprows= 12, max_rows = 8192) 

    ## Make figure and label
    fig, ax = plt.subplots(figsize=(15,8))

    ## Plot data
    ax.bar(x, y)
    ax.set_xlim(600,960)
    
    # Fit data to a gaussian
    gmodel = Model(gaussian)
    result = gmodel.fit(y, x=x, amp=8, cen=approxcen, wid=1)
        
    ## Append to list if error in amplitude and amplitude itself is within reasonable bounds
    if result.params['amp'].stderr < stderrThreshold and result.params['amp'] > minimumAmplitude:
        amps.append(result.params['amp'].value) 
        ampserr.append(result.params['amp'].stderr) 
        ts.append(MaestroT*n)

## Plot decay curve
print(amps)
fig, ax = plt.subplots()
ax.errorbar(ts, amps, yerr= 2*np.array(ampserr), fmt="ko-", capsize = 5, capthick= 2, elinewidth=3, markersize=5)
plt.xlabel('Time', fontsize=14)
plt.ylabel('Peak amplitude', fontsize=14)
plt.title("Decay curve of P-31 by $β^+$ emission", fontsize=14)
    
## Fit decay curve
4

2 回答 2

1

如果您使用的是最近的 Origin，您可以使用 originpro 模块来传输数据

import originpro as op
import pandas as pd

# balabalabala

df = pd.DataFrame(list(zip(ts, amps, ampserr)), columns=['ts', 'Amp', 'Err']) # create a dataframe
op.find_sheet('w').from_df(df) # import dataframe to activated worksheet

如果您使用的是旧版本，则必须将数据保存为文件。有关更多信息，请查看他们的文档页面： https ://www.originlab.com/python/doc/originpro/index.html

于 2020-11-30T15:54:39.240 回答
0

amps如果您的想法是将您的、ampserr和的值打印ts到文件中以供以后操作，您可能会执行以下操作：

    ## Append to list if error in amplitude and amplitude itself is within reasonable bounds
    if result.params['amp'].stderr < stderrThreshold and result.params['amp'] > minimumAmplitude:
        amps.append(result.params['amp'].value) 
        ampserr.append(result.params['amp'].stderr) 
        ts.append(MaestroT*n)

## convert results to list of strings for csv file
buffer = ['# fit results ...']
for _t, _a, _e in zip(ts, amps, ampserr):
    buff.append("{:.8g}, {:.8g}, {:.8g}".format(_t, _a, _e))
buff.append('')
## save results
with open('results.csv', 'w') as fh:
     f.write('\n'.join(buffer))

希望对您遇到的问题有所帮助。如果不是，请细化问题。

于 2020-11-30T05:34:03.677 回答