VAT22.txt

x86 chapter in let us C


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import numpy
from numpy import *
from numpy import ones
import numpy as np
from numpy import ones as npones

import numpy as np
arr=np.array([[1,2,3],[4,2,5]])
print('Array is of type',type(arr))
print('No of dimensions:',arr.ndim)
print('Shape of array:',arr.shape)
print('Size of array',arr.size)
print('Array stores elements of type',arr.dtype)

o/p
Array is of type <class 'numpy.ndarray'>
No of dimensions: 2
Shape of array: (2, 3)
Size of array 6
Array stores elements of type int32

a=np.array([[1,2,4],[5,8,7]],dtype='float')
print('Array created using passed list:\n',a)

o/p
Array created using passed list:
 [[1. 2. 4.]
 [5. 8. 7.]]


b=np.array((1,3,2))
print('\nArray created using passed tuple:\n',b)

Array created using passed list:
 [1 3 2]

c=np.zeros((3,4))
print('\nAn array initialised with all zeros:\n',c)
o/p

An array initialised with all zeros:
 [[0. 0. 0. 0.]
 [0. 0. 0. 0.]
 [0. 0. 0. 0.]]

d=np.full((3,3),6,dtype='complex')
print('\nAn array initialized with all 6s.''Array type is complex:\n',d)
o/p
An array initialized with all 6s.Array type is complex:
 [[6.+0.j 6.+0.j 6.+0.j]
 [6.+0.j 6.+0.j 6.+0.j]
 [6.+0.j 6.+0.j 6.+0.j]]

e=np.random.random((2,2))
print('\nA random(garbage value) array:\n',e)
o/p
A random(garbage value) array:
 [[0.66801979 0.28622739]
 [0.27776717 0.80394206]]

f=np.arange(0,30,5)
print('\nA sequential array with steps of 5:\n',f)
o/p
A sequential array with steps of 5:
 [ 0  5 10 15 20 25]

f=np.arange(10,100,3)
print('\nA sequential array with steps of 5:\n',f)
o/p
A sequential array with steps of 5:
 [10 13 16 19 22 25 28 31 34 37 40 43 46 49 52 55 58 61 64 67 70 73 76 79
 82 85 88 91 94 97]

g=np.linspace(0,5,10)
print('\nA sequential array with 10 values between''0 and 5:\n',g)
o/p
A sequential array with 10 values between0 and 5:
 [0.         0.55555556 1.11111111 1.66666667 2.22222222 2.77777778
 3.33333333 3.88888889 4.44444444 5.        ]


arr=np.array([[1,2,3,4],[5,2,4,2],[1,2,0,4]])
print('\nOriginal array:\n',arr)
newarr=arr.reshape(2,2,3)
print('Reshaped array:/n',newarr)
o/p
Original array:
 [[1 2 3 4]
 [5 2 4 2]
 [1 2 0 4]]
Reshaped array:/n [[[1 2 3]
  [4 5 2]]

 [[4 2 1]
  [2 0 4]]]

arr=np.array([[1,2,3,4],[5,2,4,2],[1,2,0,4]])
print('\nOriginal array:\n',arr)
newarr=arr.reshape(2,2,3)
print('Reshaped array:/n',newarr)
o/p
Original array:
 [[1 2 3 4]
 [5 2 4 2]
 [1 2 0 4]]
Reshaped array:/n [[[1 2 3]
  [4 5 2]]

 [[4 2 1]
  [2 0 4]]]

arr=np.array([[1,2,3,4],[5,6,7,8]])
f1=arr.flatten()
print('Flattened array:\n',f1)
o/p
Flattened array:
 [1 2 3 4 5 6 7 8]

arr=np.array([[1,2,3,4],[5,2,4,2],[1,2,0,4],[5,3,1,0]])
temp=arr[:2,::2]
print('Array with first two rows and alternate''column(0 and 2):\n',temp)
o/p
Array with first two rows and alternatecolumn(0 and 2):
 [[1 4]
 [5 2]
 [1 4]]

arr=np.array([[1,2,3,4],[5,2,4,2],[1,2,0,4],[5,3,1,0]])
temp=arr[:3,::3]
print('Array with first three rows and alternate''column(0 and 3):\n',temp)
o/p
Array with first two rows and alternatecolumn(0 and 2):
 [[1 4]
 [5 2]
 [1 4]]

temp=arr[[0,1,2,3],[3,2,1,0]]
print('\nElements at indices (0,3),(1,2),(2,1),''(3,0):\n',temp)
o/p
Elements at indices (0,3),(1,2),(2,1),(3,0):
 [4 4 2 5]


cond=arr>0 #cond is boolean array
temp=arr[cond]
print('\nBoolean data\n',temp)
o/p
Boolean data
 [1 2 3 4 5 2 4 2 1 2 4 5 3 1]



a=np.array([1,2,5,3])
print('Adding 1 to every element:',a+1)
print('subtracting 3 from each element:',a-3)
print('multiplying each element by 10:',a*10)
print('Squaring each element:',a**2)
a *=2
print('Doubled each element of original array:',a)
o/p
Adding 1 to every element: [2 3 6 4]
subtracting 3 from each element: [-2 -1  2  0]
multiplying each element by 10: [10 20 50 30]
Squaring each element: [ 1  4 25  9]
Doubled each element of original array: [ 2  4 10  6]



a=np.array([[1,2,3],[3,4,5],[9,6,0]])
print('original array:',a)
print('transpose of original array:',a.T)
o/p
original array: [[1 2 3]
 [3 4 5]
 [9 6 0]]
transpose of original array: [[1 3 9]
 [2 4 6]
 [3 5 0]]

#Array operation
arr=np.array([[1,2,3,4],[5,2,4,2],[1,2,6,4],[7,3,1,0]])
print('Largest element is:',arr.max())
print('Row-wise maximum element:',arr.max(axis=1))
print('Row-wise minimum element:',arr.min(axis=0))
print('Sum of all arrays elements: ',arr.sum())
o/p
Largest element is: 7
Row-wise maximum element: [4 5 6 7]
Row-wise minimum element: [1 2 1 0]
Sum of all arrays elements:  47

a=np.array([[1,2],[3,4]])
b=np.array([[5,6],[7,8]])
print('Array sum:\n',a+b)
print('Array multiplication:\n',a*b)
print('Matrix multiplication:\n',a.dot(b))
o/p
Array sum:
 [[ 6  8]
 [10 12]]
Array multiplication:
 [[ 5 12]
 [21 32]]
Matrix multiplication:
 [[19 22]
 [43 50]]



a=np.array([0, np.pi/2,np.pi])
print('Sine value of array elements:\n',np.sin(a))
o/p
Sine value of array elements:
 [0.0000000e+00 1.0000000e+00 1.2246468e-16]



a=np.array([0,1,2,3])
print('Exponent of array elements:',np.exp(a))
print('Square root of every element',np.sqrt(a))
o/p
Exponent of array elements: [ 1.          2.71828183  7.3890561  20.08553692]
Square root of every element [0.         1.         1.41421356 1.73205081]


arr=np.array([[1,2,3,4],
              [5,2,4,2],
              [1,2,6,4]])
print('Array elements in sorted order:\n',np.sort(arr,axis=None))
print('Row wise sorted array:\n',np.sort(arr,axis=1))
print('Column wise sort by applying merge sort:\n',np.sort(arr,axis=0,kind='mergesort'))
o/p
Array elements in sorted order:
 [1 1 2 2 2 2 3 4 4 4 5 6]
Row wise sorted array:
 [[1 2 3 4]
 [2 2 4 5]
 [1 2 4 6]]
Column wise sort by applying merge sort:
 [[1 2 3 2]
 [1 2 4 4]
 [5 2 6 4]]


dtypes=[('name','S10'),('grad_year', int),('cgpa',float)]
values=[('Hrithik',2009,8.5),('Ajay',2008,8.7),('Pankaj',2008,7.9),('Aakash',2009,9.0)]
arr=np.array(values, dtype=dtypes)
print('\nArray sorted by names:\n',np.sort(arr,order='name'))
print('sorted data',np.sort(arr,order=['grad_year','cgpa']))
o/p
Array sorted by names:
 [(b'Aakash', 2009, 9. ) (b'Ajay', 2008, 8.7) (b'Hrithik', 2009, 8.5)
 (b'Pankaj', 2008, 7.9)]
sorted data [(b'Pankaj', 2008, 7.9) (b'Ajay', 2008, 8.7) (b'Hrithik', 2009, 8.5)
 (b'Aakash', 2009, 9. )]
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