The fundamental feature of linear algebra are vectors, these are the objects having both direction and magnitude. In Python, NumPy arrays can be used to depict a vector.
There are mainly two ways of getting the magnitude of vector:
- By defining an explicit function which computes the magnitude of a given vector based on the below mathematical formula:
if V is vector such that, V = (a, b, c) then ||V|| = ?(a*a + b*b + c*c)
Here are some programs which computes the magnitude of a vector following the above approach:
# program to compute magnitude of a vector
# importing required libraries
import
numpy
import
math
# function defination to compute magnitude o f the vector
def
magnitude(vector):
return
math.sqrt(
sum
(
pow
(element,
2
)
for
element
in
vector))
# displaying the original vector
v
=
numpy.array([
0
,
1
,
2
,
3
,
4
])
print
(
'Vector:'
, v)
# computing and displaying the magnitude of the vector
print
(
'Magnitude of the Vector:'
, magnitude(v))
chevron_rightfilter_noneOutput:
Vector: [0 1 2 3 4] Magnitude of the Vector: 5.477225575051661
Below is another example with the same approach:
# program to compute magnitude of a vector
# importing required libraries
import
numpy
import
math
# function defination to compute magnitude o f the vector
def
magnitude(vector):
return
math.sqrt(
sum
(
pow
(element,
2
)
for
element
in
vector))
# computing and displaying the magnitude of the vector
print
(
'Magnitude of the Vector:'
, magnitude(numpy.array([
1
,
2
,
3
])))
chevron_rightfilter_noneOutput:
Magnitude of the Vector: 3.7416573867739413
- By using the
norm()
method inlinalg
module ofNumPy
library. The Linear Algebra module ofNumPy
offers various methods to apply linear algebra on anyNumPy
array. Below are some programs which usenumpy.linalg.norm()
to compute the magnitude of a vector:# program to compute magnitude of a vector
# importing required libraries
import
numpy
# displaying the original vector
v
=
numpy.array([
1
,
2
,
3
])
print
(
'Vector:'
, v)
# computing and displaying the magnitude of
# the vector using norm() method
print
(
'Magnitude of the Vector:'
, numpy.linalg.norm(v))
chevron_rightfilter_noneOutput:
Vector: [1 2 3] Magnitude of the Vector: 3.7416573867739413
An additional argument
ord
can be used to compute the nth order of thenorm()
of a vector.# program to compute the nth order of the
# magnitude of a vector
# importing required libraries
import
numpy
# displaying the original vector
v
=
numpy.array([
0
,
1
,
2
,
3
,
4
])
print
(
'Vector:'
, v)
# computing and displaying the magnitude of the vector
print
(
'Magnitude of the Vector:'
, numpy.linalg.norm(v))
# Computing the nth order of the magnitude of vector
print
(
'ord is 0: '
, numpy.linalg.norm(v,
ord
=
0
))
print
(
'ord is 1: '
, numpy.linalg.norm(v,
ord
=
1
))
print
(
'ord is 2: '
, numpy.linalg.norm(v,
ord
=
2
))
print
(
'ord is 3: '
, numpy.linalg.norm(v,
ord
=
3
))
print
(
'ord is 4: '
, numpy.linalg.norm(v,
ord
=
4
))
chevron_rightfilter_noneOutput:
Vector: [0 1 2 3 4] Magnitude of the Vector: 5.477225575051661 ord is 0: 4.0 ord is 1: 10.0 ord is 2: 5.477225575051661 ord is 3: 4.641588833612778 ord is 4: 4.337613136533361
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