«Оптимал квадратур формулалар орқали Фурье интегралларини тақрибий ҳисоблаш алгоритми» дастурий тизими


''' The interval[a, b] is the wider interval than[a1, b1] in which we extent the given function with zero value '''



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'''
The interval[a, b] is the wider interval than[a1, b1] in which we extent the given function with zero value
'''
a = 0;
b = 1;
'''
the set of nodes in the interval[a, b]
with respect to variable x and step h=0.1
'''

import numpy as np
x = np.arange(a,b,0.01)

print(x)
assert False



'''
the set of nodes in the interval[a1, b1]
with respect to variable x and step
'''
h = 0.1
'''
defining the step h in the
interval[a1, b1] with respect to x
'''
'''
% the set of nodes in the interval[a, b]
with respect to variable w, with step
'''
tau = 0.01

w = np.arange(a,b+0.01,0.01)


M = len(w) - 1
'''
%
defining the step tau in the interval[a, b]
with respect to w
'''
h = (b - a) / M
N = len(x) - 1

'''
f0(n) is the set of values of the rec[a1, b1] function
f1(n) is the set of values of the sin[a1, b1] function
f2(n) is the set of values of the exp[a1, b1] function
'''

'''
the function g0, g1 and g2 are Fourier transforms of the functions


rect[-1, 1], sin[-1, 1] and exp[-1, 1] C is coefficients matrix

'''


C = np.zeros(len(w), len(x))
E0 = np.zeros(1, len(w))
E1 = np.zeros(1, len(w))
E2 = np.zeros(1, len(w))
E11 = np.zeros(1, len(w))
E21 = np.zeros(1, len(w))
f0 = np.zeros(1, len(x))
f1 = np.zeros(1, len(x))
f2 = np.zeros(1, len(x))
f11 = np.zeros(1, len(x))
f21 = np.zeros(1, len(x))
for n in range(N+1):
f0[n] = rectfunc(x(n), a1, b1) #linear
f1[n] = sinfunc(x(n), a1, b1) # sin
f2[n] = expfunc(x(n), a1, b1) # exp
f11[n] = linearfunc(x(n), a1, b1) # linear
f21[n] = quadfunc(x(n), a1, b1) # quad


for m in range(M+1):
E0[n] = g0(w(m), a1, b1)
E1[n] = gsin(w(m), a1, b1)
E2[n] = gexp(w(m), a1, b1)
E11[n] = g1(w(m), a1, b1)
E21[n] = g2(w(m), a1, b1)

C[m, 0] = C0(w(m), h, a)


C[m, N] = CN(w(m), h, b)
for n in range(1,N):
C[m, n] = Cb(n - 1, w(m), h, a)

F0 = C * np.transpose(f0)


F1 = C * np.transpose(f1)
F2 = C * np.transpose(f2)
F11 = C * np.transpose(f11)
F21 = C * np.transpose(f21)

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