Numpy Session 4 Code

Numy Session 4 Code For Video Click Fahad Hussain CS

#### Builtin Function Numpy

import numpy as np  

a=np.array([2, 4, 6, 3**8])  

print(a)  

b=np.log(a)  

print(b)  

c=np.log2(a)  

print(c)  

d=np.log10(a)  

print(d)

import numpy as np  

import matplotlib.pyplot as plt  

arr = [2, 2.2, 2.4, 2.6,2.8, 3]  

result1=np.log(arr)  

result2=np.log2(arr)  

result3=np.log10(arr)  

plt.plot(arr,arr, color='blue', marker="*")  

plt.plot(result1,arr, color='green', marker="o")  

plt.plot(result2,arr, color='red', marker="*")  

plt.plot(result3,arr, color='black', marker="*")  

plt.show() 

import numpy as np  

x=np.log([2, np.e, np.e**3, 0])  

x  

import numpy as np  

a=np.arange(12)  

b=np.where(a<6,a,5*a)  

b  

# Broadcasting x, y, and condition

import numpy as np  

a=np.arange(12)  

b=np.where([[True, False], [True, True]],[[1, 2], [3, 4]],[[9, 8], [7, 6]])  

b 

import numpy as np  

x, y = np.ogrid[:3, :4]  

a=np.where(x > y, x, 10 + y)  

a 

x=np.array([[0,1,2],[0,2,5],[0,4,8]])  

y=np.where(x<4,x,-2)  

y  

import numpy as np  

a=np.array([456,11,63])  

print(a)  

b=np.argsort(a)  

print(b)

import numpy as np  

a = np.array([[0, 5], 

              [3, 2]])  

indices = np.argsort(a, axis=0)    

print(indices)  

np.take_along_axis(a, indices, axis=0) 

import numpy as np  

a = np.array([[0, 5], [3, 2]])  

indices = np.argsort(a, axis=1)    

indices 

import numpy as np  

a = np.array([[0, 5], [3, 2]])  

indices = np.argsort(a, axis=1)  

indices  

np.take_along_axis(a, indices, axis=1)  

import numpy as np  

a = np.array([[0, 5], [3, 2]])  

indices = np.unravel_index(np.argsort(a, axis=None), a.shape)  

indices  

a[indices]  # same as np.sort(a, axis=None) 

import numpy as np  

a= np.array([(0, 5), (3, 2)], dtype=[('x', '<i4'), ('y', '<i4')])  

print(a)  

b=np.argsort(a, order=('x','y'))  

print(b)  

c=np.argsort(a, order=('y','x'))  

print(c)  

import numpy as np  

a= np.arange(6).reshape((2,3))  

print(a) 

b=np.transpose(a)  

b

import numpy as np  

a= np.array([[1, 2], [4, 5], [7, 8]])  

a  

b=np.transpose(a, (1,0))  

print(b)   

import numpy as np  

a=np.ones((12,32,123,64))  

print(a)

b=np.transpose(a,(1,3,0,2)).shape  

print(b) 

c=np.transpose(a,(0,3,1,2)).shape  

print(c) 

import numpy as np  

a = np.array([[1, 1], [1, 1]])  

b=np.mean(a)  

print(b)  

x = np.array([[5, 6], [7, 34]])  

y=np.mean(x)  

print(y )

import numpy as np  

a = np.array([[2, 4], 

              [3, 5]])  

b=np.mean(a,axis=0)  

c=np.mean(a,axis=1)  

print(b)  

print(c)  

import numpy as np  

a = np.zeros((2, 512*512), dtype=np.float32)  

a[0, :] = 23.0  

a[1, :] = 32.0  

c=np.mean(a)  

c  

import numpy as np  

a[0, :] = 2.0  

a[1, :] = 0.2  

c=np.mean(a)  

print(c)  

d=np.mean(a, dtype=np.float64)  

print(d)