Python numpy Library Learning common functions (matrix operations) __ function

Matrix summation, maximum, minimum, average, log, open root, Square, decimal up

Import NumPy as np
a = Np.arange (10,100,5) print (
a)
print (' Vector size: ', a.size)
A36 = A.reshape (3,6)
Print (A36) print ('
-------------------')
print (' Sum: ', A36.sum ())
print (' Sum by line: ', A36.sum (Axis=1))
Print (' Sum by column: ', A36.sum (axis=0)) print ('
max: ', A36.max ()) Print (
' maximum per row: ', A36.max (Axis=1))
print (' Maximum per column: ', A36.max (axis=0)) print (' min
: ', A36.min ()) Print (
' Minimum per line: ', A36.min (Axis=1))
print (' Minimum value per column: ' , A36.min (axis=0)) print ('
average: ', A36.mean ()) print ('
average per line: ', A36.mean (Axis=1))
print (' Average per column: ', A36.mean (axis=0)) print ('
max index: ', A36.argmax ()) Print
(' Maximum index per row: ', A36.argmax (Axis=1))
print (' Maximum index per column: ', A36.argmax (axis=0)) print (
' log value: ', Np.log (A36)) print ('
log10 value: ', Np.log10 (A36)) print ('
Log2 value: ', Np.log2 (A36)) print ('
exponential value: ', Np.exp (A36)) print ('
square root: ', np.sqrt (A36)) Print
('------------- -------')
a = Np.random.random ((3,4)) *10 print (
a)
print (' Decimal rounding: ', Np.floor (a))
print (' Decimal rounding up : ', Np.ceil (a))

Matrix Subtraction

Import NumPy as np
A12 = Np.arange ()
print (A12)
A34 = A12.reshape (3,4)
print (A34)
# # structure can be directly used + * -/symbol for Operation
Print (A34 + A34)
print (A34 * A34)
A43 = A12.reshape (4,3)
print (A43)
# # The structure is not the same as dot () C10/>print (' Dot (): ', Np.dot (A43,a34))

matrix Stitching and splitting

Import NumPy as np
R23 = Np.random.random ((2,3))
R22 = Np.random.random ((2,2))
print (R23)
print ( R22)
# # Number of lines to stitch two matrices must be the same
print (' concatenation: \ n ', Np.hstack (R23,R22))
# # Concatenation of two matrices by column must be the same
r53 = Np.vstack ((R23,np.random.random (4,3))) Print
(' concatenation by column: \ n ', r53)

print (' Average of 3 pieces by column: \ n ', Np.hsplit (r53,3))
print (' Specify column index split, index 1 and index 2 each cut: \ n ', Np.hsplit (r53, (1,2))
print (' average of 3 in rows: \ n ', Np.vsplit (r53,3))
Print (' Specify row index split, index 1 and index 3 each cut: \ n ', Np.vsplit (r53, (1,3))