Correct Answer : scientific library
Explanation : SciPy, a scientific library for Python is an open source, BSD-licensed library for mathematics, science and engineering.
Correct Answer : scipy.source
Explanation : scipy.source is not correct sub-packages of SciPy.
Correct Answer : Planck constant
Explanation : h : Planck constant
Correct Answer : Travis Oliphant
Correct Answer : maxima
Correct Answer : All of the above
Correct Answer : minima
Correct Answer : global maxima
Correct Answer : k
Explanation : k : Boltzmann constant
Correct Answer : A data set where most of the item values are zero.
Correct Answer : det()
Explanation : In SciPy, this is computed using the det() function.
Correct Answer : Dense Array
Correct Answer : Delaunay()
Correct Answer : 0
Correct Answer : connected_components()
Correct Answer : The level of significance.
Correct Answer : Av = lambda*v
Explanation :
Correct Answer : rank
Explanation : Dimensions are called as axes. The number of axes is called as rank.
Correct Answer : Most of the values are not zero
Correct Answer : count_nonzeros()
Correct Answer : data = whiten(data)
Correct Answer : 0.001
Correct Answer : cityblock()
Correct Answer : The data is skewed left
Correct Answer : BLAS/LAPACK support
Explanation : SciPy.linalg is always compiled with BLAS/LAPACK support, while for NumPy this is optional.
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.
Correct Answer : dijkstra()
Correct Answer : A convex hull is the smallest polygon that covers all of the given points.
Correct Answer : imputation
Correct Answer : savemat()
Correct Answer : loadmat()
from scipy import constants
Correct Answer : constants.pi
Correct Answer : dir(constants)
import numpy as np print np.linspace(1., 4., 6)
Correct Answer : array([ 1. , 1.6, 2.2, 2.8, 3.4, 4. ])
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
Correct Answer : array([ 2., -2., 9.])
Explaination : The above program will generate the following output : array([ 2., -2., 9.])
array([ 2., -2., 9.])
Correct Answer : constants.speed_of_sound
import numpy as np print np.arange(7)
Correct Answer : array([0, 1, 2, 3, 4, 5, 6])
from scipy.special import logsumexp import numpy as np a = np.arange(10) res = logsumexp(a) print res
Correct Answer : 9.45862974443
constants.kilo
Correct Answer : 1000.0
constants.gram
constants.hour
Correct Answer : 3600.0
from scipy import linalg import numpy as np A = np.array([[1,2],[3,4]]) x = linalg.det(A) print x
Correct Answer : -2
Correct Answer : Both (a) and (b)