質問編集履歴
3
式の修正
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```
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この部分で、変数i,kをどのようにコードに組み込んだらいいのか分かりません。
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式の前半部分は書けているのですが、Σ以降がまだ書けていません。
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Python初心者なので分かりやすく教えていただきたいです。
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2
式、コードの変更・修正
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Pythonで微分方程式を解いてグラフに表示させたいです。
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dy/dt=-
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dy(i)/dt=-a*y(i){b-exp(b-c*x(i)**4)}+Σ[d*y(k)*exp{(x(i)-x(k)/2)**2/(e*x(k)**2)}]
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Σの変数はkで0<k<3です。
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縦軸に変数y、横軸に変数x(0<x<
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縦軸に変数y、横軸に変数x(0<x<3)
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時間は120sec,dt=6.0sec
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```
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F_dy=lambda value: -self._a*value[1]*(self._b-math.exp(self._b-self._c*value[0]**4))
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```
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この部分で、変数i,kをどのようにコードに組み込んだらいいのか分かりません。
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Python初心者なので分かりやすく教えていただきたいです。
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宜しくお願いします。
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---------------------------------------------------------------------------
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ValueError Traceback (most recent call last)
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<ipython-input-27-854e133ed99b> in <module>
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25 dt=6.0
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26 t=numpy.arange(0,120,dt)
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---> 27 Phelps_Model(x,y,t).calc()
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<ipython-input-27-854e133ed99b> in calc(self)
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15 def calc(self):
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16 initval=[self._x,self._y]
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---> 17 result=scipy.integrate.odeint(self.func, initval, self._t)
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18 self.show(result[:].T[0],result[:].T[1])
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~\anaconda3\lib\site-packages\scipy\integrate\odepack.py in odeint(func, y0, t, args, Dfun, col_deriv, full_output, ml, mu, rtol, atol, tcrit, h0, hmax, hmin, ixpr, mxstep, mxhnil, mxordn, mxords, printmessg, tfirst)
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231 mu = -1 # changed to zero inside function call
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232
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--> 233 dt = np.diff(t)
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234 if not((dt >= 0).all() or (dt <= 0).all()):
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235 raise ValueError("The values in t must be monotonically increasing "
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<__array_function__ internals> in diff(*args, **kwargs)
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~\anaconda3\lib\site-packages\numpy\lib\function_base.py in diff(a, n, axis, prepend, append)
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1244 nd = a.ndim
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1245 if nd == 0:
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-> 1246 raise ValueError("diff requires input that is at least one dimensional")
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1247 axis = normalize_axis_index(axis, nd)
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ValueError: diff requires input that is at least one dimensional
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現在のコードでのエラーはありません。
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import matplotlib.pyplot as plt
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import numpy
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import numpy as np
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import math
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class Phelps_Model(object):
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def __init__(self, a, b, c, t, dt, x, y):
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def __init__(self, a, b, c, d, e, t, dt, x, y):
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self._a=a
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self._b=b
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self._c=c
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self._d=d
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self._e=e
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self._t=t
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resulty=[]
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F_dy=lambda value: -a*value[1]*(b-math.exp(b-c*value[0]**4))
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F_dy=lambda value: -self._a*value[1]*(self._b-math.exp(self._b-self._c*value[0]**4))
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for i in range(0,len(self._t)):
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yy=F_dy([self._x,self._y])*self._dt
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self._x+=xx
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self._y+=yy
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self.show(resultx,resulty)
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def show(self,x,y):
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fig=plt.figure()
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ax=fig.add_subplot()
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ax.plot(x,y,'o')
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plt.ylim(0, 100)
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ax.set_xlabel('fiber length')
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ax.set_ylabel('Number of fibers')
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plt.show()
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def Phelps_Model.calc()
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c=1.337
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d=0.002
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e=0.02
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x=0.0
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y=0.0
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dt=6.0
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t=n
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t=np.arange(0,120,dt)
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Phelps_Model(a,b,c,t,dt,x,y).calc()
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Phelps_Model(a,b,c,d,e,t,dt,x,y).calc()
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```
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1
ソースコードを修正しました。宜しくお願い致します。
test
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File without changes
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test
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```
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import
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import matplotlib.pyplot as plt
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class Phelps_Model(object):
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def __init__(self, a, b, c, t, dt, x, y):
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self._dt=dt
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F_dy=lambda result: -0.02*result[1](1-exp(1-1.337*result[0]**4))
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return [F_dy(result)]
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def calc(self):
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resultx=[]
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result=
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F_dy=lambda value: -a*value[1]*(b-math.exp(b-c*value[0]**4))
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for i in range(0,len(self._t)):
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yy=F_dy([self._x,self._y])*self._dt
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self._x+=xx
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self._y+=yy
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resultx.append(self._x)
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resulty.append(self._y)
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self.show(resultx,resulty)
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def show(self,x,y):
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plt.xlim(0, 4.0)
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plt.ylim(0, 100)
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plt.show()
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def Phelps_Model.calc()
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a=0.2
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b=1.0
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c=1.337
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t=numpy.arange(0,120,dt)
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Phelps_Model(a,b,c,t,dt,x,y).calc()
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```
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