umbaのjitを用いて行列の計算を早くしたい。

###numbaのjitを用いて行列の計算を早くしたい。

pythonで関数を定義してjitを使って計算速度を早くしようとしたら次のようなエラーがでました。
このエラーはどうやったら取り除けるのでしょうか？

発生している問題・エラーメッセージ

NumbaWarning: 
Compilation is falling back to object mode WITH looplifting enabled because Function "ap" failed type inference due to: Invalid use of Function(<built-in function setitem>) with argument(s) of type(s): (readonly array(float64, 1d, C), int64, float64)
 * parameterized
In definition 0:
    All templates rejected with literals.
In definition 1:
    All templates rejected without literals.
In definition 2:
    All templates rejected with literals.
In definition 3:
    All templates rejected without literals.
In definition 4:
    All templates rejected with literals.
In definition 5:
    All templates rejected without literals.
In definition 6:
    All templates rejected with literals.
In definition 7:
    All templates rejected without literals.
In definition 8:
    TypeError: Cannot modify value of type readonly array(float64, 1d, C)
    raised from C:\Users\yusei\anaconda3\lib\site-packages\numba\typing\arraydecl.py:179
In definition 9:
    TypeError: Cannot modify value of type readonly array(float64, 1d, C)
    raised from C:\Users\yusei\anaconda3\lib\site-packages\numba\typing\arraydecl.py:179
This error is usually caused by passing an argument of a type that is unsupported by the named function.
[1] During: typing of setitem at C:\Users\yusei\OneDrive\ドキュメント\Desktop\Desktop.spyder-py3\CIM.py (80)

File "CIM.py", line 80:
def ap():
    <source elided>
            n_p = np.random.normal(0,np.sqrt(1-e)/2)*e_p
            
             ^

  @jit
C:\Users\yusei\OneDrive\ドキュメント\Desktop\Desktop.spyder-py3\CIM.py:74: NumbaWarning: 
Compilation is falling back to object mode WITHOUT looplifting enabled because Function "ap" failed type inference due to: cannot determine Numba type of <class 'numba.dispatcher.LiftedLoop'>

File "CIM.py", line 77:
def ap():
    <source elided>
    
    for k in range(box-1):
    ^

  @jit
C:\Users\yusei\anaconda3\lib\site-packages\numba\object_mode_passes.py:178: NumbaWarning: Function "ap" was compiled in object mode without forceobj=True, but has lifted loops.

File "CIM.py", line 77:
def ap():
    <source elided>
    
    for k in range(box-1):
    ^

  state.func_ir.loc))
C:\Users\yusei\anaconda3\lib\site-packages\numba\object_mode_passes.py:188: NumbaDeprecationWarning: 
Fall-back from the nopython compilation path to the object mode compilation path has been detected, this is deprecated behaviour.

For more information visit http://numba.pydata.org/numba-doc/latest/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit

File "CIM.py", line 77:
def ap():
    <source elided>
    
    for k in range(box-1):
    ^

  state.func_ir.loc))
C:\Users\yusei\OneDrive\ドキュメント\Desktop\Desktop.spyder-py3\CIM.py:74: NumbaWarning: 
Compilation is falling back to object mode WITHOUT looplifting enabled because Function "ap" failed type inference due to: Invalid use of Function(<built-in function setitem>) with argument(s) of type(s): (readonly array(float64, 1d, C), int64, float64)
 * parameterized
In definition 0:
    All templates rejected with literals.
In definition 1:
    All templates rejected without literals.
In definition 2:
    All templates rejected with literals.
In definition 3:
    All templates rejected without literals.
In definition 4:
    All templates rejected with literals.
In definition 5:
    All templates rejected without literals.
In definition 6:
    All templates rejected with literals.
In definition 7:
    All templates rejected without literals.
In definition 8:
    TypeError: Cannot modify value of type readonly array(float64, 1d, C)
    raised from C:\Users\yusei\anaconda3\lib\site-packages\numba\typing\arraydecl.py:179
In definition 9:
    TypeError: Cannot modify value of type readonly array(float64, 1d, C)
    raised from C:\Users\yusei\anaconda3\lib\site-packages\numba\typing\arraydecl.py:179
This error is usually caused by passing an argument of a type that is unsupported by the named function.
[1] During: typing of setitem at C:\Users\yusei\OneDrive\ドキュメント\Desktop\Desktop.spyder-py3\CIM.py (80)

File "CIM.py", line 80:
def ap():
    <source elided>
            n_p = np.random.normal(0,np.sqrt(1-e)/2)*e_p
            
             ^

  @jit
C:\Users\yusei\anaconda3\lib\site-packages\numba\object_mode_passes.py:178: NumbaWarning: Function "ap" was compiled in object mode without forceobj=True.

File "CIM.py", line 77:
def ap():
    <source elided>
    
    for k in range(box-1):
    ^

  state.func_ir.loc))
C:\Users\yusei\anaconda3\lib\site-packages\numba\object_mode_passes.py:188: NumbaDeprecationWarning: 
Fall-back from the nopython compilation path to the object mode compilation path has been detected, this is deprecated behaviour.

For more information visit http://numba.pydata.org/numba-doc/latest/reference/deprecation.html#deprecation-of-object-mode-fall-back-behaviour-when-using-jit

File "CIM.py", line 77:
def ap():
    <source elided>
    
    for k in range(box-1):
    ^

  state.func_ir.loc))

該当のソースコード

python
1import numpy as np 
2import matplotlib.pyplot as plt
3import time
4from numba import jit,prange
5start = time.time()
6spin = 2000
7c = 130
8P_k = 65*10**(-3)
9L = 0.05
10k = 0
11e_p = 2.59e-19
12box = 1000
13P = np.arange(0,1000,1e-4)
14G = np.zeros(spin)
15asd = np.zeros(box*spin).reshape(box,spin)
16
17e =1/12.6
18
19import sys
20import numpy as np
21mat = []  # 結果を入れるリスト(行列)
22
23with open('G22.txt', 'r', encoding='utf-8') as fin:  # ファイルを開く
24    
25    x = fin.readline()
26    for line in fin.readlines():  # 行をすべて読み込んで1行ずつfor文で回す
27        row = []  # 行のデータを保存するリスト
28        toks = line.split(' ')  # 行を半角スペースで分割する
29        for tok in toks:  # 分割したトークン列を回す
30            try:
31                num = int(tok)  # 整数に変換
32            except ValueError:
33                print(file=sys.stderr)  # エラーが出たら画面に出力して
34                continue  # スキップ
35            row_append = row.append
36            row_append(num)  # 行に保存
37
38        mat.append(row)  # 行をnumsに保存
39J= np.zeros(2000*2000).reshape(2000,2000)
40for a in range(19990):
41    x = mat[a][0] 
42    y = mat[a][1] 
43    z = float(mat[a][2]) 
44    J[x-1][y-1]=J[y-1][x-1] = -z
45    
46for a in range(spin):
47    N_1 = np.random.normal(0,np.sqrt(G[a])/2)*e_p#自然放出光
48    asd[0][a] = np.sqrt(G[a])*0 + N_1
49    G[a] = np.exp(2*c*np.sqrt(P[0]*L)) 
50
51
52@jit
53def saturated(a,p):
54    A_P = np.zeros(50)
55    A_S = np.zeros(50)
56    A_S[0] = a
57    A_P[0] = p
58    
59    for l in prange(49):
60        A_P[l+1] = A_P[l] - c*(A_S[l])**2*0.05/50
61        A_S[l+1] = A_S[l] + c*A_P[l]*A_S[l]*0.05/50
62    K = A_S[49]**2/A_S[0]**2
63    out = np.sqrt(K)*a
64    return out
65
66@jit
67def interact(a,b):
68    
69    
70    result = 0.015*np.dot(J[b],asd[a])
71    
72    return result
73    
74@jit
75def ap():
76    
77    for k in range(box-1):
78        for i in range(spin):
79            n_p = float(np.random.normal(0,np.sqrt(1-e)/2)*e_p)
80            asd[k+1][i] = saturated(asd[k][i]*np.sqrt(e)+n_p+interact(k,i),np.sqrt(P[k]))
81           
82        
83
84
85 
86    #plt.plot(asd)  
87    #plt.xlabel('kaisuu')
88    #plt.ylabel('sinpuku')
89    A = np.sign(asd[box-1])
90    sum=0
91    for i in range(spin):
92        for j in range(i+1,spin):
93            sum += 1/2*(-J[i][j])*(1-A[i]*A[j])
94                  
95    print(sum)
96for a in range(1):
97    ap()    
98elapsedtime = time.time() - start
99print(elapsedtime)
100