Rev 4429 Rev 4666
1 { 1 {
2 "metadata": { 2 "metadata": {
3 "name": "", 3 "name": "",
4 "signature": "sha256:c35f5f2963a30c62e2bc2437fc0d2422404aec0dbc3c5526df0be8cecdef27ee" 4 "signature": "sha256:9453f2d297004717b7b0ab5bb80d8d05d3ff319f7e609fa9565e753aa36cef87"
5 }, 5 },
6 "nbformat": 3, 6 "nbformat": 3,
7 "nbformat_minor": 0, 7 "nbformat_minor": 0,
8 "worksheets": [ 8 "worksheets": [
9 { 9 {
10 "cells": [ 10 "cells": [
11 { 11 {
12 "cell_type": "code", 12 "cell_type": "code",
13 "collapsed": false, 13 "collapsed": false,
14 "input": [ 14 "input": [
15 "import h5py\n", 15 "import h5py\n",
16 "import numpy as np\n", 16 "import numpy as np\n",
17 "import matplotlib.pyplot as plt" 17 "import matplotlib.pyplot as plt"
18 ], 18 ],
19 "language": "python", 19 "language": "python",
20 "metadata": {}, 20 "metadata": {},
21 "outputs": [], 21 "outputs": [],
22 "prompt_number": 1 22 "prompt_number": 1
23 }, 23 },
24 { 24 {
25 "cell_type": "code", 25 "cell_type": "code",
26 "collapsed": false, 26 "collapsed": false,
27 "input": [ 27 "input": [
28 "file = h5py.File('test_rps.hdf5', 'r') # 'r' means that hdf5 file is open in read-only mode\n", 28 "file = h5py.File('test_rps.hdf5', 'r') # 'r' means that hdf5 file is open in read-only mode\n",
29 "dataset = file['RPS01']" 29 "dataset = file['RPS01']"
30 ], 30 ],
31 "language": "python", 31 "language": "python",
32 "metadata": {}, 32 "metadata": {},
33 "outputs": [], 33 "outputs": [],
34 "prompt_number": 2 34 "prompt_number": 2
35 }, 35 },
36 { 36 {
37 "cell_type": "code", 37 "cell_type": "code",
38 "collapsed": false, 38 "collapsed": false,
39 "input": [ 39 "input": [
40 "print dataset.value[4,2]" 40 "print dataset.value[4,2]"
41 ], 41 ],
42 "language": "python", 42 "language": "python",
43 "metadata": {}, 43 "metadata": {},
44 "outputs": [ 44 "outputs": [
45 { 45 {
46 "output_type": "stream", 46 "output_type": "stream",
47 "stream": "stdout", 47 "stream": "stdout",
48 "text": [ 48 "text": [
49 "36.7822\n" 49 "36.7822\n"
50 ] 50 ]
51 } 51 }
52 ], 52 ],
53 "prompt_number": 24 53 "prompt_number": 3
54 }, 54 },
55 { 55 {
56 "cell_type": "code", 56 "cell_type": "code",
57 "collapsed": false, 57 "collapsed": false,
58 "input": [ 58 "input": [
59 "plt.plot( dataset.value[:,0], dataset.value[:,2], color = 'r')\n", 59 "plt.plot( dataset.value[:,0], dataset.value[:,2], color = 'r')\n",
60 "#plt.xlim([1.45415117E9,1.4541513E9])\n", 60 "#plt.xlim([1.45415117E9,1.4541513E9])\n",
61 "plt.show()" 61 "plt.show()"
62 ], 62 ],
63 "language": "python", 63 "language": "python",
64 "metadata": {}, 64 "metadata": {},
65 "outputs": [], 65 "outputs": [],
66 "prompt_number": 14 66 "prompt_number": 4
67 }, 67 },
68 { 68 {
69 "cell_type": "code", 69 "cell_type": "code",
70 "collapsed": false, 70 "collapsed": false,
71 "input": [ 71 "input": [
72 "prev_val= dataset.value[0,2]\n", 72 "prev_val= dataset.value[0,2]\n",
73 "n = 0\n", 73 "n = 0\n",
74 "angle = np.zeros_like(dataset.value)\n", 74 "angle = np.zeros((dataset.shape[0]))\n",
75 "for i in range(dataset.value.shape[0]):\n", 75 "for i in range(dataset.value.shape[0]):\n",
76 " if (dataset.value[i,2] - prev_val) > 300: \n", 76 " if (dataset.value[i,2] - prev_val) > 300:\n",
-   77 " n -= 1\n",
-   78 " angle[i] = dataset.value[i,2] + n*360\n",
-   79 " prev_val = dataset.value[i,2]\n",
-   80 " elif -(dataset.value[i,2] - prev_val) > 300: # compute angular speed in backward direction.\n",
77 " n += 1\n", 81 " n += 1\n",
-   82 " angle[i] = dataset.value[i,2] - n*360\n",
-   83 " prev_val = dataset.value[i,2]\n",
-   84 " else:\n",
78 " angle[i] = dataset.value[i,2] + n*360\n", 85 " angle[i] = dataset.value[i,2] + n*360\n",
79 " prev_val = dataset.value[i,2]" 86 " prev_val = dataset.value[i,2]\n",
-   87 " "
80 ], 88 ],
81 "language": "python", 89 "language": "python",
82 "metadata": {}, 90 "metadata": {},
83 "outputs": [], 91 "outputs": [],
84 "prompt_number": 19 92 "prompt_number": 6
-   93 },
-   94 {
-   95 "cell_type": "markdown",
-   96 "metadata": {},
-   97 "source": [
-   98 "Five point difference numerical calculation. Source: http://mathfun528.blogspot.cz/2011/07/numerical-differentiation.html"
-   99 ]
85 }, 100 },
86 { 101 {
87 "cell_type": "code", 102 "cell_type": "code",
88 "collapsed": false, 103 "collapsed": false,
89 "input": [ 104 "input": [
-   105 "angle_speed = np.zeros_like(angle)\n",
90 "angle" 106 "\n",
-   107 "for i in range(2,angle.shape[0]-2):\n",
-   108 " angle_speed[i] = (-angle[i + 2] + 8*angle[i + 1] - 8*angle[i - 1] + angle[i - 2])/12"
91 ], 109 ],
92 "language": "python", 110 "language": "python",
93 "metadata": {}, 111 "metadata": {},
94 "outputs": [ 112 "outputs": [],
-   113 "prompt_number": 7
-   114 },
-   115 {
-   116 "cell_type": "code",
-   117 "collapsed": false,
-   118 "input": [
-   119 "fig, ax1 = plt.subplots()\n",
-   120 "\n",
-   121 "ax2 = ax1.twinx()\n",
-   122 "ax1.set_xlabel('Sample #')\n",
-   123 "ax1.set_ylabel('Angle')\n",
-   124 "ax2.set_ylabel('Angular speed')\n",
-   125 "\n",
-   126 "ax1.plot(dataset.value[:,0], angle,'b',dataset.value[:,0], dataset.value[:,2],'r')\n",
-   127 "ax2.plot(dataset.value[:,0], angle_speed,'g')\n",
-   128 "\n",
-   129 "plt.show()"
-   130 ],
-   131 "language": "python",
-   132 "metadata": {},
-   133 "outputs": [],
-   134 "prompt_number": 8
-   135 },
95 { 136 {
-   137 "cell_type": "code",
-   138 "collapsed": false,
-   139 "input": [
-   140 "print angle"
-   141 ],
-   142 "language": "python",
96 "metadata": {}, 143 "metadata": {},
-   144 "outputs": [
-   145 {
97 "output_type": "pyout", 146 "output_type": "stream",
98 "prompt_number": 20, 147 "stream": "stdout",
99 "text": [ 148 "text": [
100 "array([[ 0., 0., 0.],\n", -  
101 " [ 0., 0., 0.],\n", -  
102 " [ 0., 0., 0.],\n", -  
103 " ..., \n", -  
104 " [ 0., 0., 0.],\n", 149 "[ 3.64746094e+01 3.65405273e+01 3.77929688e+01 ..., -1.31529551e+05\n",
105 " [ 0., 0., 0.],\n", -  
106 " [ 0., 0., 0.]], dtype=float32)" 150 " -1.31530452e+05 -1.31528452e+05]\n"
107 ] 151 ]
108 } 152 }
109 ], 153 ],
110 "prompt_number": 20 154 "prompt_number": 10
-   155 },
-   156 {
-   157 "cell_type": "code",
-   158 "collapsed": false,
-   159 "input": [],
-   160 "language": "python",
-   161 "metadata": {},
-   162 "outputs": [],
-   163 "prompt_number": 4
-   164 },
-   165 {
-   166 "cell_type": "markdown",
-   167 "metadata": {},
-   168 "source": []
-   169 },
-   170 {
-   171 "cell_type": "code",
-   172 "collapsed": false,
-   173 "input": [],
-   174 "language": "python",
-   175 "metadata": {},
-   176 "outputs": [],
-   177 "prompt_number": 45
-   178 },
-   179 {
-   180 "cell_type": "code",
-   181 "collapsed": false,
-   182 "input": [],
-   183 "language": "python",
-   184 "metadata": {},
-   185 "outputs": [],
-   186 "prompt_number": 45
111 }, 187 },
112 { 188 {
113 "cell_type": "code", 189 "cell_type": "code",
114 "collapsed": false, 190 "collapsed": false,
115 "input": [], 191 "input": [],
116 "language": "python", 192 "language": "python",
117 "metadata": {}, 193 "metadata": {},
118 "outputs": [] 194 "outputs": []
119 } 195 }
120 ], 196 ],
121 "metadata": {} 197 "metadata": {}
122 } 198 }
123 ] 199 ]
124 } 200 }