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2020-06-25 22:56:24 -03:00
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# Seals - Program made for educational intent, can be freely distributed
# and can be used for economical intent. I will not take legal actions
# unless my intelectual propperty, the code, is stolen or change without permission.
# Copyright (C) 2020 VItor Hideyoshi Nakazone Batista
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License version 2 as published by
# the Free Software Foundation.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
import numpy as np
import csv
import pandas as pd
import math
def scan(path):
df=pd.read_csv(path, sep=';',decimal=",",header=None)
array = df.to_numpy()
return array
def write(array, path):
with open(path, mode='w') as sistema_linear:
solution_writer = csv.writer(sistema_linear, delimiter=',', quotechar='"', quoting=csv.QUOTE_MINIMAL)
solution_writer.writerows(array)
return array
class Insert:
def __init__(self):
pass
def matrix(self, matrix):
i = 0
while (i < matrix.shape[0]):
j = 0
while (j < matrix.shape[1]):
matrix[i][j] = float(input('Insira o elemento {}x{}: '.format((i+1),(j+1))))
j += 1
i += 1
return matrix
def vector(self, vector):
j=0
while (j < vector.shape[0]):
vector[j] = float(input('Insira o elemento b{}: '.format((j+1))))
j += 1
return vector
class process:
def __init__(self):
pass
def identity(self, matrix):
i = 0
while (i < matrix.shape[0]):
j = 0
while (j < matrix.shape[0]):
if (i == j):
matrix[i][j] = 1
elif (i != j):
matrix[i][j] = 0
j += 1
i += 1
return matrix
def gauss(self, matrix):
i = 0
k = 0
while (i < matrix.shape[0]):
if (matrix[i][i] == 0):
n = i
while (matrix[i][i] == 0) and (n < matrix.shape[0]):
temp = matrix[i].copy()
matrix[i] = matrix[n]
matrix[n] = temp
n += 1
while (k < matrix.shape[0]):
if (k == i) or (matrix[i][i] == 0):
k += 1
else:
mult = matrix[k][i]/matrix[i][i]
matrix[k] = matrix[k] - mult*matrix[i]
k += 1
i += 1
k = 0
i = 0
while ((i) < matrix.shape[0]) and (matrix[i][i] != 0):
matrix[i] = matrix[i]/matrix[i][i]
i += 1
return matrix[:,(matrix.shape[0]):]
def inverse(self, matrix):
return self.gauss(np.hstack((matrix, self.identity(np.zeros(matrix.shape)))))
def cholesky(self, A, b):
g = np.zeros((A.shape))
i = 0
j = 0
while j < A.shape[1]:
while i < A.shape[0]:
if i == 0 and j == 0:
g[i][j] = math.sqrt(A[0][0])
elif j == 0:
g[i][j] = A[i][0]/g[0][0]
elif i == j:
k = 0
theta = 0
while k < i:
theta += g[i][k]**2
k += 1
g[i][j] = math.sqrt(A[i][i] - theta)
else:
k = 0
theta = 0
while k < j:
theta += g[i][k]*g[j][k]
k += 1
g[i][j] = (A[i][j] - theta)/g[j][j]
i += 1
j += 1
i = j
y = (self.inverse(g)).dot(b)
x = (self.inverse(g.T)).dot(y)
return x
def decomposition(self, U, b):
L = self.identity(np.zeros(U.shape))
i = 0
k = 0
while (i < U.shape[0]):
k = 0
if (U[i][i] == 0):
n = i
while (U[i][i] == 0) and (n < U.shape[0]):
temp = U[i].copy()
U[i] = U[n]
U[n] = temp
n += 1
while (k < U.shape[0]):
if (k <= i) or (U[i][i] == 0):
k += 1
else:
L[k][i] = U[k][i]/U[i][i]
U[k] = U[k] - L[k][i]*U[i]
k += 1
i += 1
y = (self.inverse(L)).dot(b)
x = (self.inverse(U)).dot(y)
return x
def cramer(self, A, b):
x = np.vstack(np.zeros(b.shape))
k = 0
while (k < A.shape[0]):
temp = A.copy()
temp[:,k] = b
x[k] = np.linalg.det(temp)/np.linalg.det(A)
k += 1
return x

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# Seals - Program made for educational intent, can be freely distributed
# and can be used for economical intent. I will not take legal actions
# unless my intelectual propperty, the code, is stolen or change without permission.
# Copyright (C) 2020 VItor Hideyoshi Nakazone Batista
# This program is free software; you can redistribute it and/or modify
# it under the terms of the GNU General Public License version 2 as published by
# the Free Software Foundation.
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
# You should have received a copy of the GNU General Public License along
# with this program; if not, write to the Free Software Foundation, Inc.,
# 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
from .Seals import process
from .Seals import Insert
from .Seals import scan
from .Seals import write