質問編集履歴
2
初めての質問で失礼しました。挿入いたしました。
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```
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import numpy as np
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from scipy import integrate
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from scipy.optimize import curve_fit
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import math
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import pandas as pd
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Eins = 2.01 * 10**8
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Lorentzbroad = Eins / 2 / math.pi
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widthL = Lorentzbroad / 10**9
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df = pd.read_csv('book1.csv')
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array_x=np.array(df['t'])
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array_y=np.array(df['y'])
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def func(x, param1, param2):
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def voigt(z):
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return param1 * 0.8256 / np.pi**(3/2) / param2 / widthL * np.exp((-1) * (2 * z / param2)**2 * np.log(2)) / (1 + (2 * (x - z) / widthL)**2)
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integration = integrate.quad(voigt, -np.inf, np.inf)[0]
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return integration
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p0 = 0.5, 0.5
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popt, pcov = curve_fit(func, array_x, array_y, p0)
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### 試したこと
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1
初めての質問で失礼しました。挿入いたしました。
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### 発生している問題・エラーメッセージ
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```
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---------------------------------------------------------------------------
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TypeError Traceback (most recent call last)
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<ipython-input-10-baa10670dc7d> in <module>
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22 p0 = 0.5, 0.5
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---> 23 popt, pcov = curve_fit(func, array_x, array_y, p0)
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~\Anaconda3\lib\site-packages\scipy\optimize\minpack.py in curve_fit(f, xdata, ydata, p0, sigma, absolute_sigma, check_finite, bounds, method, jac, **kwargs)
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750 # Remove full_output from kwargs, otherwise we're passing it in twice.
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751 return_full = kwargs.pop('full_output', False)
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--> 752 res = leastsq(func, p0, Dfun=jac, full_output=1, **kwargs)
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753 popt, pcov, infodict, errmsg, ier = res
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754 cost = np.sum(infodict['fvec'] ** 2)
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~\Anaconda3\lib\site-packages\scipy\optimize\minpack.py in leastsq(func, x0, args, Dfun, full_output, col_deriv, ftol, xtol, gtol, maxfev, epsfcn, factor, diag)
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381 if not isinstance(args, tuple):
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382 args = (args,)
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--> 383 shape, dtype = _check_func('leastsq', 'func', func, x0, args, n)
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384 m = shape[0]
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~\Anaconda3\lib\site-packages\scipy\optimize\minpack.py in _check_func(checker, argname, thefunc, x0, args, numinputs, output_shape)
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24 def _check_func(checker, argname, thefunc, x0, args, numinputs,
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25 output_shape=None):
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---> 26 res = atleast_1d(thefunc(*((x0[:numinputs],) + args)))
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27 if (output_shape is not None) and (shape(res) != output_shape):
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28 if (output_shape[0] != 1):
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~\Anaconda3\lib\site-packages\scipy\optimize\minpack.py in func_wrapped(params)
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456 if transform is None:
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457 def func_wrapped(params):
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--> 458 return func(xdata, *params) - ydata
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459 elif transform.ndim == 1:
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460 def func_wrapped(params):
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<ipython-input-10-baa10670dc7d> in func(x, param1, param2)
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17 def voigt(z):
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18 return param1 * 0.8256 / np.pi**(3/2) / param2 / widthL * np.exp((-1) * (2 * z / param2)**2 * np.log(2)) / (1 + (2 * (x - z) / widthL)**2)
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---> 19 integration = integrate.quad(voigt, -np.inf, np.inf)[0]
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20 return integration
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~\Anaconda3\lib\site-packages\scipy\integrate\quadpack.py in quad(func, a, b, args, full_output, epsabs, epsrel, limit, points, weight, wvar, wopts, maxp1, limlst)
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339 if weight is None:
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340 retval = _quad(func, a, b, args, full_output, epsabs, epsrel, limit,
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--> 341 points)
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342 else:
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343 retval = _quad_weight(func, a, b, args, full_output, epsabs, epsrel,
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~\Anaconda3\lib\site-packages\scipy\integrate\quadpack.py in _quad(func, a, b, args, full_output, epsabs, epsrel, limit, points)
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448 return _quadpack._qagse(func,a,b,args,full_output,epsabs,epsrel,limit)
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449 else:
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--> 450 return _quadpack._qagie(func,bound,infbounds,args,full_output,epsabs,epsrel,limit)
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451 else:
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452 if infbounds != 0:
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15
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only size-1 arrays can be converted to Python scalars
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TypeError: only size-1 arrays can be converted to Python scalars
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```
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### 該当のソースコード
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```python
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import numpy as np
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from scipy import integrate
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from scipy.optimize import curve_fit
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import math
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import pandas as pd
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Eins = 2.01 * 10**8
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Lorentzbroad = Eins / 2 / math.pi
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widthL = Lorentzbroad / 10**9
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@@ -60,6 +184,54 @@
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popt, pcov = curve_fit(func, array_x, array_y, p0)
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```
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import numpy as np
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from scipy import integrate
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from scipy.optimize import curve_fit
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import math
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import pandas as pd
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Eins = 2.01 * 10**8
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Lorentzbroad = Eins / 2 / math.pi
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widthL = Lorentzbroad / 10**9
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df = pd.read_csv('book1.csv')
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array_x=np.array(df['t'])
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array_y=np.array(df['y'])
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def func(x, param1, param2):
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def voigt(z):
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return param1 * 0.8256 / np.pi**(3/2) / param2 / widthL * np.exp((-1) * (2 * z / param2)**2 * np.log(2)) / (1 + (2 * (x - z) / widthL)**2)
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integration = integrate.quad(voigt, -np.inf, np.inf)[0]
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return integration
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p0 = 0.5, 0.5
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popt, pcov = curve_fit(func, array_x, array_y, p0)
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63
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64
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65
237
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### 試したこと
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