np.logspace(2.0, 3.0, num=4)
# array([  100.        ,   215.443469  ,   464.15888336,  1000.        ])
np.logspace(2.0, 3.0, num=4, endpoint=False)
# array([ 100.        ,  177.827941  ,  316.22776602,  562.34132519])
np.logspace(2.0, 3.0, num=4, base=2.0)
# array([ 4.        ,  5.0396842 ,  6.34960421,  8.        ])

# Graphical illustration:

import matplotlib.pyplot as plt
N = 10
x1 = np.logspace(0.1, 1, N, endpoint=True)
x2 = np.logspace(0.1, 1, N, endpoint=False)
y = np.zeros(N)
plt.plot(x1, y, 'o')
# [<matplotlib.lines.Line2D object at 0x...>]
plt.plot(x2, y + 0.5, 'o')
# [<matplotlib.lines.Line2D object at 0x...>]
plt.ylim([-0.5, 1])
# (-0.5, 1)
plt.show()