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SciPy - Quiz(MCQ)
A)
source library
B)
science library
C)
scientific library
D)
significant library

Correct Answer :   scientific library


Explanation : SciPy, a scientific library for Python is an open source, BSD-licensed library for mathematics, science and engineering.

A)
scipy.cluster
B)
scipy.source
C)
scipy.signal
D)
scipy.interpolate

Correct Answer :   scipy.source


Explanation : scipy.source is not correct sub-packages of SciPy.

A)
Planck constant
B)
Elementary charge
C)
Molar gas constant
D)
Newton's gravitational constant

Correct Answer :   Planck constant


Explanation : h : Planck constant

A)
Jim Hugunin
B)
Wes McKinney
C)
Guido van Rossum
D)
Travis Oliphant

Correct Answer :   Travis Oliphant

A)
top
B)
high
C)
slope
D)
maxima

Correct Answer :   maxima

A)
SciPy is built on top of NumPy arrays
B)
There is no need to import the NumPy functions explicitly, when SciPy is imported.
C)
By default, all the NumPy functions have been available through the SciPy namespace
D)
All of the above

Correct Answer :   All of the above


Explanation : scipy.source is not correct sub-packages of SciPy.

A)
Up
B)
low
C)
minima
D)
bottom

Correct Answer :   minima

A)
global maxima
B)
maxima
C)
maximo dutti
D)
None of the above

Correct Answer :   global maxima

A)
R
B)
k
C)
G
D)
e

Correct Answer :   k


Explanation : k : Boltzmann constant

A)
A data set where most of the item values are zero
B)
A data set with only negative values
C)
A data set where all numbers are higher than the previous number
D)
None of the above

Correct Answer :   A data set where most of the item values are zero.

A)
det()
B)
SciPy.det()
C)
determinant()
D)
SciPy.determinant()

Correct Answer :   det()


Explanation : In SciPy, this is computed using the det() function.

A)
Full Array
B)
Lower Data
C)
Dense Array
D)
All of the above

Correct Answer :   Dense Array

A)
Duval()
B)
Delaunay()
C)
Dmitri()
D)
None of the above

Correct Answer :   Delaunay()

A)
2
B)
1
C)
-1
D)
0

Correct Answer :   0

A)
connections()
B)
connected_components()
C)
comp_connections()
D)
None of the above

Correct Answer :   connected_components()

A)
The level of significance.
B)
The highest possible number.
C)
The distance from the lowest to the highest number.
D)
All of the above

Correct Answer :   The level of significance.

A)
Av != lambda*v
B)
Av =10 * lambda*v
C)
Av = lambda*v
D)
Av =Constant * lambda*v

Correct Answer :   Av = lambda*v


Explanation :

We can find the Eigen values (lambda) and the corresponding Eigen vectors (v) of a square matrix (A) by considering the following relation.

A)
matrices
B)
object
C)
rank
D)
Vectors

Correct Answer :   rank


Explanation : Dimensions are called as axes. The number of axes is called as rank.

A)
The values are sorted ascending
B)
Most of the values are not zero
C)
The values are all positive
D)
None of the above

Correct Answer :   Most of the values are not zero

A)
nozeros()
B)
nonzeros()
C)
no_zeros()
D)
count_nonzeros()

Correct Answer :   count_nonzeros()

A)
data = whiten(data)
B)
data = data.whiten()
C)
data =SciPy.whiten(data)
D)
data = numpy.whiten(data)

Correct Answer :   data = whiten(data)

A)
0.11
B)
0.1
C)
0.01
D)
0.001

Correct Answer :   0.001

A)
blocks()
B)
block_distance()
C)
cityblock()
D)
None of the above

Correct Answer :   cityblock()

A)
The data is skewed right
B)
The data is skewed left
C)
Both (a) and (b) are True
D)
Both (a) and (b) are False

Correct Answer :   The data is skewed left

A)
BLAS/Linalg support
B)
BLAS/LAPACK support
C)
Linalg/LAPACK support
D)
None of the above

Correct Answer :   BLAS/LAPACK support


Explanation : SciPy.linalg is always compiled with BLAS/LAPACK support, while for NumPy this is optional.

A)
linear equation
B)
integration problem
C)
differentiation problem
D)
All of the above

Correct Answer :   linear equation


Explanation : The scipy.linalg.solve feature solves the linear equation a * x + b * y = Z, for the unknown x, y values.

A)
ford()
B)
bellmann()
C)
dijkstra()
D)
All of the above

Correct Answer :   dijkstra()

A)
A convex hull is the smallest polygon that covers all of the given points.
B)
A convex hull is the smallest square that covers four given points.
C)
A convex hull is the smallest triangle that covers all of the given points.
D)
None of the above

Correct Answer :   A convex hull is the smallest polygon that covers all of the given points.

A)
amputation
B)
samputation
C)
adoptation
D)
imputation

Correct Answer :   imputation

A)
to_matlab()
B)
savemat()
C)
save_to_mat()
D)
None of the above

Correct Answer :   savemat()

A)
matlab()
B)
loadmat()
C)
matlab.get()
D)
None of the above

Correct Answer :   loadmat()

32 .
What is a correct syntax to return the mathematical number PI from the constants module, if the module is imported like this :
 
from scipy import constants
A)
PI
B)
constants.pi_int
C)
constants.pi
D)
All of the above

Correct Answer :   constants.pi

33 .
What is a correct syntax to a list of all units under the constants module, if the module is imported like this:
 
from scipy import constants
A)
dir(constants)
B)
 constants
C)
constants.list
D)
None of the above

Correct Answer :   dir(constants)

34 .
What will be output for the following code?
 
import numpy as np
print np.linspace(1., 4., 6)
A)
array([ 1. , 1.6, 2.8, 3.4, 4. ])
B)
array([ 1. , 2.2, 2.8, 3.4, 4. ])
C)
array([ 1. , 1.6, 2.2, 2.8, 4. ])
D)
array([ 1. , 1.6, 2.2, 2.8, 3.4, 4. ])

Correct Answer :   array([ 1. , 1.6, 2.2, 2.8, 3.4, 4. ])

35 .
What will be output for the following code?
 
from scipy import linalg
import numpy as np
a = np.array([[3, 2, 0], [1, -1, 0], [0, 5, 1]])
b = np.array([2, 4, -1])
x = linalg.solve(a, b)
print x
A)
array([ 2., -2.])
B)
array([ 2., -2., 9., 6.])
C)
array([ 2., -2., 9.])
D)
 array([ 2., -2., 9., -9.])

Correct Answer :   array([ 2., -2., 9.])


Explaination : The above program will generate the following output : array([ 2., -2., 9.])

36 .
What is a correct syntax to return the speed of sound (in meters per seconds), if the module is imported like this:
 
from scipy import constants
A)
constants.kmh
B)
constants.speed_of_sound
C)
constants.mph
D)

Correct Answer :   constants.speed_of_sound

37 .
What will be output for the following code?
 
import numpy as np
print np.arange(7)
A)
[0, 1, 2, 3, 4, 5, 6]
B)
[[0, 1, 2, 3, 4, 5, 6]]
C)
array(0, 1, 2, 3, 4, 5, 6)
D)
array([0, 1, 2, 3, 4, 5, 6])

Correct Answer :   array([0, 1, 2, 3, 4, 5, 6])

38 .
What will be output for the following code?
 
from scipy.special import logsumexp
import numpy as np
a = np.arange(10)
res = logsumexp(a)
print res
A)
9.45862974443
B)
9.46
C)
9.637
D)
10

Correct Answer :   9.45862974443

39 .
When working with constanst, what would be the result of the following:
 
constants.kilo
A)
1.0
B)
10.0
C)
100.0
D)
1000.0

Correct Answer :   1000.0

40 .
When working with constanst, what would be the result of the following:
 
constants.gram
A)
0.1
B)
0.01
C)
0.001
D)
All of the above

Correct Answer :   0.001

41 .
When working with constanst, what would be the result of the following:
 
constants.hour
A)
24.0
B)
3600.0
C)
12.0
D)
1.0

Correct Answer :   3600.0

42 .
What will be output for the following code?
 
from scipy import linalg
import numpy as np
A = np.array([[1,2],[3,4]])
x = linalg.det(A)
print x
A)
-2
B)
-1
C)
1
D)
2

Correct Answer :   -2

A)
SciPy version might be faster depending on how NumPy was installed.
B)
scipy.linalg also has some other advanced functions that are not in numpy.linalg
C)
Both (a) and (b)
D)
None of the above

Correct Answer :   Both (a) and (b)