Numpy Session 6 Code

Numy Session 6 Code For Video Click Fahad Hussain CS

import numpy as np

a=np.array([[1,4,7,10],

            [2,5,8,11]])

print(np.mean(a))

b=np.std(a)  

print(b)

a=np.array([[1,4,7,10],[2,5,8,11]]) 

b=np.std(a, axis=1)  

b  

import numpy as np  

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

a[1, :] = 1.0  

a[0, :] = 0.1 

print(a)

# dtype=np.float64 

b=np.std(a)  

print(b)  

import numpy as np  

x = np.arange(20).reshape(4,5) + 7  

print(x)  

y=np.argmax(a)  

print(y)

import numpy as np  

x = np.arange(20).reshape(4,5) + 7 

print(x) 

y=np.argmax(x, axis=0)  

z=np.argmax(x, axis=1)  

print(y)

print(z)  

import numpy as np  

x = np.arange(20).reshape(4,5) + 7  

print(x)

indices = np.unravel_index(np.argmax(x, axis=None), x.shape)  

indices  

x[indices]  

import numpy as np  

arr = np.array([0, 1, 2], dtype=np.uint8)  

print(arr)  

b=np.diff(arr)  

print(b)  

print(arr[2,...] - arr[1,...] - arr[0,...] )

import numpy as np  

x = np.array([[11, 21, 41],

              [71, 1, 12],

              [33, 2, 13]])  

y = np.diff(x, axis=0)  

print(y)  

z = np.diff(x, axis=1)  

print(z) 

import numpy as np  

x = np.arange('1997-10-01', '1997-12-16', dtype=np.datetime64)  

y = np.diff(x)  

y  

import numpy as np  

a=np.histogram([1, 5, 2], bins=[0, 1, 2, 3])  

print(a)

import numpy as np  

x=np.histogram(np.arange(6), bins=np.arange(7), density=True)  

x  

import numpy as np  

a = np.arange(8)  

hist, bin_edges = np.histogram(a, density=True)  

print(hist)  

print(bin_edges) 

import numpy as np  

x = [1,2,3]  

y = np.pad(x, (3, 2), 'constant', constant_values=(6, 4))  

y  

import numpy as np  

x = [1, 3, 2, 5, 4]  

y = np.pad(x, (3, 2), 'edge')  

y  

import numpy as np  

x = [1, 3, 2, 5, 4]  

y = np.pad(x, (3, 2), 'linear_ramp', end_values=(-4, 5))  

y  

import numpy as np  

x = [1, 3, 2, 5, 4]  

# mean, median, minimum, maximum

y = np.pad(x, (3,4), 'median')  

y

import numpy as np  

x = np.array([[1, 3, 5], [11, 35, 56]])  

print(x)

y=np.ravel(x)  

y  

import numpy as np  

x = np.array([[1, 3, 5], [11, 35, 56]])  

y = np.ravel(x, order='F')  

z = np.ravel(x, order='C')  

p = np.ravel(x, order='A')  

q = np.ravel(x, order='K')  

print(x)

print(y)  

print(z)

print(p)

print(q)

import numpy as np  

x = np.arange(12).reshape(3,2,2).swapaxes(1,2)  

print(x)  

y=np.ravel(a, order='C')  

print(y)  

z=np.ravel(a, order='K')  

print(z)

q=np.ravel(a, order='A')  

print(q )

import numpy as np  

from tempfile import TemporaryFile  

out_file = TemporaryFile()  

x=np.arange(15)

print(x)  

np.save(out_file, x)  

_=out_file.seek(0) # Only needed here to simulate closing & reopening file  

np.load(out_file)

import numpy as np  

from tempfile import TemporaryFile  

outfile = TemporaryFile()  

x=np.arange(15)  

np.save(outfile, x, allow_pickle=False)  

_=outfile.seek(0) # Only needed here to simulate closing & reopening file  

np.load(outfile)