E211 - Relatório 1 - Monitora: Muriel

import numpy as np import matplotlib.pyplot as plt

vetor_1 = np.array([1, 2, 3, 4]) print(vetor_1)

[1 2 3 4]

vetor_2 = np.arange(0, 1, 0.1) print(vetor_2)

[0.  0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9]

vetor_3 = np.ones(6) print(vetor_3)

[1. 1. 1. 1. 1. 1.]

vetor_4 = np.zeros(6) print(vetor_4)

[0. 0. 0. 0. 0. 0.]

vetor_5 = np.random.random(6) print(vetor_5)

[0.53491007 0.05287884 0.56552985 0.94219221 0.82190494 0.70760239]

vetor_6 = np.linspace(-5, 5, 10) print(vetor_6)

[-5.         -3.88888889 -2.77777778 -1.66666667 -0.55555556  0.55555556
  1.66666667  2.77777778  3.88888889  5.        ]

a = 25 raiz = np.sqrt(a) print(raiz)

5.0

t=np.arange(0,1,1/10000) x=np.sin(2*np.pi*1000*t)

maximo = np.max(vetor_5) print("max = ", maximo) minimo = np.min(vetor_5) print("min = ", minimo)

max =  0.9421922105069954
min =  0.0528788371016925

x = np.array([2, 1, 4, 3]) h = np.array([1, -1]) y = np.convolve(x,h) print(y)

[ 2 -1  3 -1 -3]

t=np.arange(0,1,1/10000) x=np.sin(2*np.pi*1000*t) plt.plot(t[200:300],x[200:300]) plt.title("Senoide") plt.xlabel("t (s)") plt.ylabel("x(t)") plt.grid() plt.show()

import numpy as np v = np.array([1,2,3,4,5,6,7,8]).reshape(4,2,1) print("tensor \n",v) print("Número de dimensoes ", v.ndim) print("Número de elementos", np.size(v)) print("OUTROS EXEMPLOS") V = np.zeros((3,3)) print("Matriz com zeros") print('V = \n', V) U = np.ones((3,4,5)) print("Matriz com uns") print('U = \n', U) D = np.diag([10, 10, 10]) print("Matriz identidade com valores definidos") print('D = \n', D)

tensor 
 [[[1]
  [2]]

 [[3]
  [4]]

 [[5]
  [6]]

 [[7]
  [8]]]
Número de dimensoes  3
Número de elementos 8
OUTROS EXEMPLOS
Matriz com zeros
V = 
 [[0. 0. 0.]
 [0. 0. 0.]
 [0. 0. 0.]]
Matriz com uns
U = 
 [[[1. 1. 1. 1. 1.]
  [1. 1. 1. 1. 1.]
  [1. 1. 1. 1. 1.]
  [1. 1. 1. 1. 1.]]

 [[1. 1. 1. 1. 1.]
  [1. 1. 1. 1. 1.]
  [1. 1. 1. 1. 1.]
  [1. 1. 1. 1. 1.]]

 [[1. 1. 1. 1. 1.]
  [1. 1. 1. 1. 1.]
  [1. 1. 1. 1. 1.]
  [1. 1. 1. 1. 1.]]]
Matriz identidade com valores definidos
D = 
 [[10  0  0]
 [ 0 10  0]
 [ 0  0 10]]

#As funções arange e linspace permitem a criação de sequências como tensores NumPy: import numpy as np v = np.arange(0, 5, 3) u = np.linspace(3.88,3 , 10) # aqui a conta é (3-3.7)/(10-1) cada unidade / resolucao --> 0.7/9 => somando a cd amostra # 10 "espaços" -- de 0 até 5 # #--> RESOLVA usando linspace # comecando de 2 e indo ate 3 e de 0.11111... em 0.1111... x = np.linspace(2,3,10) w = np.arange(0,4,3) #for i in range(0,len(u)): # print(u[i]) print("v =", v) print("u =", u) print("w =", w) print("x =", x)

v = [0 3]
u = [3.88       3.78222222 3.68444444 3.58666667 3.48888889 3.39111111
 3.29333333 3.19555556 3.09777778 3.        ]
w = [0 3]
x = [2.         2.11111111 2.22222222 2.33333333 2.44444444 2.55555556
 2.66666667 2.77777778 2.88888889 3.        ]