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import numpy as np # Chapter 2 Beginning with NumPy fundamentals # # Demonstrates ndarray attributes. # # Run from the commandline with # # python arrayattributes2.py b = np.arange(24).reshape(2, 12) print "In: b" print b #Out: #array([[ 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11], # [12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23]]) print "In: b.ndim" print b.ndim #Out: 2 print "In: b.size" print b.size #Out: 24 print "In: b.itemsize" print b.itemsize #Out: 8 print "In: b.nbytes" print b.nbytes #Out: 192 print "In: b.size * b.itemsize" print b.size * b.itemsize #Out: 192 print "In: b.resize(6,4)" print b.resize(6,4) print "In: b" print b #Out: #array([[ 0, 1, 2, 3], # [ 4, 5, 6, 7], # [ 8, 9, 10, 11], # [12, 13, 14, 15], # [16, 17, 18, 19], # [20, 21, 22, 23]]) print "In: b.T" print b.T #Out: #array([[ 0, 4, 8, 12, 16, 20], # [ 1, 5, 9, 13, 17, 21], # [ 2, 6, 10, 14, 18, 22], # [ 3, 7, 11, 15, 19, 23]]) print "In: b.ndim" print b.ndim #Out: 1 print "In: b.T" print b.T #Out: array([0, 1, 2, 3, 4]) print "In: b = array([1.j + 1, 2.j + 3])" b = np.array([1.j + 1, 2.j + 3]) print "In: b" print b #Out: array([ 1.+1.j, 3.+2.j]) print "In: b.real" print b.real #Out: array([ 1., 3.]) print "In: b.imag" print b.imag #Out: array([ 1., 2.]) print "In: b.dtype" print b.dtype #Out: dtype('complex128') print "In: b.dtype.str" print b.dtype.str #Out: '<c16' print "In: b = arange(4).reshape(2,2)" b = np.arange(4).reshape(2,2) print "In: b" print b #Out: #array([[0, 1], # [2, 3]]) print "In: f = b.flat" f = b.flat print "In: f" print f #Out: <numpy.flatiter object at 0x103013e00> print "In: for it in f: print it" for it in f: print it #0 #1 #2 #3 print "In: b.flat[2]" print b.flat[2] #Out: 2 print "In: b.flat[[1,3]]" print b.flat[[1,3]] #Out: array([1, 3]) print "In: b" print b #Out: #array([[7, 7], # [7, 7]]) print "In: b.flat[[1,3]] = 1" b.flat[[1,3]] = 1 print "In: b" print b #Out: #array([[7, 1], # [7, 1]])