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NumPy IPython Notebook - 31 May, 2012
{
"metadata": {
"name": "NumpyLesson"
},
"nbformat": 2,
"worksheets": [
{
"cells": [
{
"cell_type": "markdown",
"source": [
"# NumPy Lesson - May 31, 2012 #"
]
},
{
"cell_type": "markdown",
"source": [
"NumPy Docs: http://docs.scipy.org/doc/numpy/reference/"
]
},
{
"cell_type": "code",
"collapsed": true,
"input": [
"import numpy as np"
],
"language": "python",
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "markdown",
"source": [
"## 1. Building Arrays ##",
"",
"### From Other Sequences ###",
"dtypes: http://docs.scipy.org/doc/numpy/reference/arrays.scalars.html#arrays-scalars-built-in"
]
},
{
"cell_type": "code",
"collapsed": true,
"input": [
"a = np.array([1, 2, 3, 10])"
],
"language": "python",
"outputs": [],
"prompt_number": 8
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print a"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[ 1 2 3 10]"
]
}
],
"prompt_number": 9
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"b = np.array([[1, 2, 3, 4], [5, 6, 7, 10.0]], dtype=np.float32)"
],
"language": "python",
"outputs": [],
"prompt_number": 15
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"b"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 16,
"text": [
"array([[ 1., 2., 3., 4.],",
" [ 5., 6., 7., 10.]], dtype=float32)"
]
}
],
"prompt_number": 16
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"b.dtype"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 17,
"text": [
"dtype('float32')"
]
}
],
"prompt_number": 17
},
{
"cell_type": "markdown",
"source": [
"### NumPy Generation Functions ###",
"http://docs.scipy.org/doc/numpy/reference/routines.array-creation.html"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"z = np.zeros((3, 3),dtype=np.int32)",
"print z"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[[0 0 0]",
" [0 0 0]",
" [0 0 0]]"
]
}
],
"prompt_number": 19
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"o = np.ones((3, 3))",
"print o"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[[ 1. 1. 1.]",
" [ 1. 1. 1.]",
" [ 1. 1. 1.]]"
]
}
],
"prompt_number": 21
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a = np.arange(1, 2, 0.01)",
"print a"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[ 1. 1.01 1.02 1.03 1.04 1.05 1.06 1.07 1.08 1.09 1.1 1.11",
" 1.12 1.13 1.14 1.15 1.16 1.17 1.18 1.19 1.2 1.21 1.22 1.23",
" 1.24 1.25 1.26 1.27 1.28 1.29 1.3 1.31 1.32 1.33 1.34 1.35",
" 1.36 1.37 1.38 1.39 1.4 1.41 1.42 1.43 1.44 1.45 1.46 1.47",
" 1.48 1.49 1.5 1.51 1.52 1.53 1.54 1.55 1.56 1.57 1.58 1.59",
" 1.6 1.61 1.62 1.63 1.64 1.65 1.66 1.67 1.68 1.69 1.7 1.71",
" 1.72 1.73 1.74 1.75 1.76 1.77 1.78 1.79 1.8 1.81 1.82 1.83",
" 1.84 1.85 1.86 1.87 1.88 1.89 1.9 1.91 1.92 1.93 1.94 1.95",
" 1.96 1.97 1.98 1.99]"
]
}
],
"prompt_number": 22
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"np.linspace(1, 2, num=50, endpoint=False)"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 25,
"text": [
"array([ 1. , 1.02, 1.04, 1.06, 1.08, 1.1 , 1.12, 1.14, 1.16,",
" 1.18, 1.2 , 1.22, 1.24, 1.26, 1.28, 1.3 , 1.32, 1.34,",
" 1.36, 1.38, 1.4 , 1.42, 1.44, 1.46, 1.48, 1.5 , 1.52,",
" 1.54, 1.56, 1.58, 1.6 , 1.62, 1.64, 1.66, 1.68, 1.7 ,",
" 1.72, 1.74, 1.76, 1.78, 1.8 , 1.82, 1.84, 1.86, 1.88,",
" 1.9 , 1.92, 1.94, 1.96, 1.98])"
]
}
],
"prompt_number": 25
},
{
"cell_type": "markdown",
"source": [
"## 2. Indexing Arrays ##",
"http://docs.scipy.org/doc/numpy/reference/arrays.indexing.html"
]
},
{
"cell_type": "code",
"collapsed": true,
"input": [
"a = np.arange(10)"
],
"language": "python",
"outputs": [],
"prompt_number": 26
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 27,
"text": [
"array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9])"
]
}
],
"prompt_number": 27
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a[5:8]"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 29,
"text": [
"array([5, 6, 7])"
]
}
],
"prompt_number": 29
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a = np.arange(10).reshape((2, 5))",
"print a"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[[0 1 2 3 4]",
" [5 6 7 8 9]]"
]
}
],
"prompt_number": 30
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a[1, :]"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 33,
"text": [
"array([5, 6, 7, 8, 9])"
]
}
],
"prompt_number": 33
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a[(a < 3) & (a > 1)]"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 36,
"text": [
"array([2])"
]
}
],
"prompt_number": 36
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"b = np.arange(10, 20).reshape((2, 5))",
"print b"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[[10 11 12 13 14]",
" [15 16 17 18 19]]"
]
}
],
"prompt_number": 38
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"b[a > 5]"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 40,
"text": [
"array([16, 17, 18, 19])"
]
}
],
"prompt_number": 40
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a > 5"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 41,
"text": [
"array([[False, False, False, False, False],",
" [False, True, True, True, True]], dtype=bool)"
]
}
],
"prompt_number": 41
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a[a > 5] *= 2",
"print a"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[[ 0 1 2 3 4]",
" [ 5 12 14 16 18]]"
]
}
],
"prompt_number": 42
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"np.where(a > 5)"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 43,
"text": [
"(array([1, 1, 1, 1]), array([1, 2, 3, 4]))"
]
}
],
"prompt_number": 43
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"b[np.where(a > 5)]"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 44,
"text": [
"array([16, 17, 18, 19])"
]
}
],
"prompt_number": 44
},
{
"cell_type": "markdown",
"source": [
"## 3. Array Math ##"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a = np.arange(10)",
"a = a * 2",
"print a"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[ 0 2 4 6 8 10 12 14 16 18]"
]
}
],
"prompt_number": 46
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"np.arange(10) * np.arange(10, 20)"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 47,
"text": [
"array([ 0, 11, 24, 39, 56, 75, 96, 119, 144, 171])"
]
}
],
"prompt_number": 47
},
{
"cell_type": "code",
"collapsed": true,
"input": [
"a = np.arange(8).reshape((4, 2))"
],
"language": "python",
"outputs": [],
"prompt_number": 107
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 108,
"text": [
"array([[0, 1],",
" [2, 3],",
" [4, 5],",
" [6, 7]])"
]
}
],
"prompt_number": 108
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a * np.array([2, 3])"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 109,
"text": [
"array([[ 0, 3],",
" [ 4, 9],",
" [ 8, 15],",
" [12, 21]])"
]
}
],
"prompt_number": 109
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a * np.array([[2], [3], [5], [6]])"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 52,
"text": [
"array([[ 0, 2],",
" [ 6, 9],",
" [20, 25],",
" [36, 42]])"
]
}
],
"prompt_number": 52
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a * np.array([[1, 2], [3, 4]])"
],
"language": "python",
"outputs": [
{
"ename": "ValueError",
"evalue": "shape mismatch: objects cannot be broadcast to a single shape",
"output_type": "pyerr",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mValueError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/Users/mrdavis/projects/numpy_tutorial_2012-05-31/<ipython-input-53-b5bd2537fe31>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0ma\u001b[0m \u001b[0;34m*\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0marray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;36m3\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;36m4\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;31mValueError\u001b[0m: shape mismatch: objects cannot be broadcast to a single shape"
]
}
],
"prompt_number": 53
},
{
"cell_type": "markdown",
"source": [
"## 4. NumPy Functions ##",
"http://docs.scipy.org/doc/numpy/reference/ufuncs.html#available-ufuncs"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 54,
"text": [
"array([[0, 1],",
" [2, 3],",
" [4, 5],",
" [6, 7]])"
]
}
],
"prompt_number": 54
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"np.sin(a)"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 56,
"text": [
"array([[ 0. , 0.84147098],",
" [ 0.90929743, 0.14112001],",
" [-0.7568025 , -0.95892427],",
" [-0.2794155 , 0.6569866 ]])"
]
}
],
"prompt_number": 56
},
{
"cell_type": "markdown",
"source": [
"## 5. Array Attributes & Methods ##",
"http://docs.scipy.org/doc/numpy/reference/arrays.ndarray.html#array-attributes",
"",
"http://docs.scipy.org/doc/numpy/reference/arrays.ndarray.html#array-methods"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 57,
"text": [
"array([[0, 1],",
" [2, 3],",
" [4, 5],",
" [6, 7]])"
]
}
],
"prompt_number": 57
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a.shape"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 58,
"text": [
"(4, 2)"
]
}
],
"prompt_number": 58
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a.size"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 59,
"text": [
"8"
]
}
],
"prompt_number": 59
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a.dtype"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 60,
"text": [
"dtype('int64')"
]
}
],
"prompt_number": 60
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a.nbytes"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 61,
"text": [
"64"
]
}
],
"prompt_number": 61
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a.reshape((2,4))"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 62,
"text": [
"array([[0, 1, 2, 3],",
" [4, 5, 6, 7]])"
]
}
],
"prompt_number": 62
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a.argsort()"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 63,
"text": [
"array([[0, 1],",
" [0, 1],",
" [0, 1],",
" [0, 1]])"
]
}
],
"prompt_number": 63
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a.min()"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 67,
"text": [
"0"
]
}
],
"prompt_number": 67
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a.max()"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 68,
"text": [
"9"
]
}
],
"prompt_number": 68
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print a.mean(), a.sum(), a.std(), a.prod()"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"4.5 45 2.87228132327 0"
]
}
],
"prompt_number": 69
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"np.mean([1, 2, 3, 4])"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 71,
"text": [
"2.5"
]
}
],
"prompt_number": 71
},
{
"cell_type": "markdown",
"source": [
"## 6. numpy.random ##",
"http://docs.scipy.org/doc/numpy/reference/routines.random.html"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"np.random.permutation(np.arange(10))"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 110,
"text": [
"array([2, 3, 5, 6, 8, 1, 0, 7, 9, 4])"
]
}
],
"prompt_number": 110
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"np.random.random((2, 2))"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 77,
"text": [
"array([[ 0.50411342, 0.10708051],",
" [ 0.7061658 , 0.87775115]])"
]
}
],
"prompt_number": 77
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"np.random.random_integers(5, 10, 5)"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 79,
"text": [
"array([7, 7, 5, 8, 9])"
]
}
],
"prompt_number": 79
},
{
"cell_type": "markdown",
"source": [
"## 7. Masked Arrays ##",
"http://docs.scipy.org/doc/numpy/reference/maskedarray.html",
"",
"http://docs.scipy.org/doc/numpy/reference/routines.ma.html"
]
},
{
"cell_type": "code",
"collapsed": true,
"input": [
"import numpy.ma as ma"
],
"language": "python",
"outputs": [],
"prompt_number": 80
},
{
"cell_type": "code",
"collapsed": true,
"input": [
"a = ma.masked_greater(np.random.random(10), 0.5)"
],
"language": "python",
"outputs": [],
"prompt_number": 81
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 82,
"text": [
"masked_array(data = [0.126459538933 -- -- 0.382754789138 0.0975191738884 0.182983512924",
" 0.367432667685 -- 0.0585601591978 --],",
" mask = [False True True False False False False True False True],",
" fill_value = 1e+20)"
]
}
],
"prompt_number": 82
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print a.mean(), a.max()"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"0.202618306961 0.382754789138"
]
}
],
"prompt_number": 84
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a[0] = ma.masked",
"print a"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[-- -- -- 0.382754789138 0.0975191738884 0.182983512924 0.367432667685 --",
" 0.0585601591978 --]"
]
}
],
"prompt_number": 85
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a[0] = 1.0",
"print a"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[1.0 -- -- 0.382754789138 0.0975191738884 0.182983512924 0.367432667685 --",
" 0.0585601591978 --]"
]
}
],
"prompt_number": 87
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a.filled()"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 88,
"text": [
"array([ 1.00000000e+00, 1.00000000e+20, 1.00000000e+20,",
" 3.82754789e-01, 9.75191739e-02, 1.82983513e-01,",
" 3.67432668e-01, 1.00000000e+20, 5.85601592e-02,",
" 1.00000000e+20])"
]
}
],
"prompt_number": 88
},
{
"cell_type": "markdown",
"source": [
"## 8. Array Comparison ##",
"http://docs.scipy.org/doc/numpy/reference/routines.testing.html"
]
},
{
"cell_type": "code",
"collapsed": true,
"input": [
"a = np.arange(10)",
"b = np.arange(5, 25, 2)"
],
"language": "python",
"outputs": [],
"prompt_number": 89
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"b.shape"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 90,
"text": [
"(10,)"
]
}
],
"prompt_number": 90
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"print a",
"print b"
],
"language": "python",
"outputs": [
{
"output_type": "stream",
"stream": "stdout",
"text": [
"[0 1 2 3 4 5 6 7 8 9]",
"[ 5 7 9 11 13 15 17 19 21 23]"
]
}
],
"prompt_number": 91
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"a == b"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 93,
"text": [
"array([False, False, False, False, False, False, False, False, False, False], dtype=bool)"
]
}
],
"prompt_number": 93
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"np.allclose(a, b)"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 94,
"text": [
"False"
]
}
],
"prompt_number": 94
},
{
"cell_type": "code",
"collapsed": true,
"input": [
"a[1] = 7"
],
"language": "python",
"outputs": [],
"prompt_number": 95
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"(a == b).any()"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 97,
"text": [
"True"
]
}
],
"prompt_number": 97
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"(a == b).all()"
],
"language": "python",
"outputs": [
{
"output_type": "pyout",
"prompt_number": 98,
"text": [
"False"
]
}
],
"prompt_number": 98
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"np.testing.assert_allclose(a, b)"
],
"language": "python",
"outputs": [
{
"ename": "AssertionError",
"evalue": "\nNot equal to tolerance rtol=1e-07, atol=0\n\n(mismatch 100.0%)\n x: array([0, 7, 2, 3, 4, 5, 6, 7, 8, 9])\n y: array([ 5, 7, 9, 11, 13, 15, 17, 19, 21, 23])",
"output_type": "pyerr",
"traceback": [
"\u001b[0;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[0;31mAssertionError\u001b[0m Traceback (most recent call last)",
"\u001b[0;32m/Users/mrdavis/projects/numpy_tutorial_2012-05-31/<ipython-input-99-b55a17f72509>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtesting\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0massert_allclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[0;32m/usr/stsci/pyssgdev/2.7/numpy/testing/utils.pyc\u001b[0m in \u001b[0;36massert_allclose\u001b[0;34m(actual, desired, rtol, atol, err_msg, verbose)\u001b[0m\n\u001b[1;32m 1128\u001b[0m \u001b[0mheader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m'Not equal to tolerance rtol=%g, atol=%g'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0mrtol\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0matol\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1129\u001b[0m assert_array_compare(compare, actual, desired, err_msg=str(err_msg),\n\u001b[0;32m-> 1130\u001b[0;31m verbose=verbose, header=header)\n\u001b[0m\u001b[1;32m 1131\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 1132\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0massert_array_almost_equal_nulp\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnulp\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/usr/stsci/pyssgdev/2.7/numpy/testing/utils.pyc\u001b[0m in \u001b[0;36massert_array_compare\u001b[0;34m(comparison, x, y, err_msg, verbose, header)\u001b[0m\n\u001b[1;32m 616\u001b[0m names=('x', 'y'))\n\u001b[1;32m 617\u001b[0m \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mcond\u001b[0m \u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 618\u001b[0;31m \u001b[0;32mraise\u001b[0m \u001b[0mAssertionError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mmsg\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 619\u001b[0m \u001b[0;32mexcept\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 620\u001b[0m msg = build_err_msg([x, y], err_msg, verbose=verbose, header=header,\n",
"\u001b[0;31mAssertionError\u001b[0m: \nNot equal to tolerance rtol=1e-07, atol=0\n\n(mismatch 100.0%)\n x: array([0, 7, 2, 3, 4, 5, 6, 7, 8, 9])\n y: array([ 5, 7, 9, 11, 13, 15, 17, 19, 21, 23])"
]
}
],
"prompt_number": 99
},
{
"cell_type": "code",
"collapsed": true,
"input": [],
"language": "python",
"outputs": []
}
]
}
]
}
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