|
7 | 7 | "name": "", |
8 | 8 | "published": true |
9 | 9 | }, |
10 | | - "signature": "sha256:6730dbab487e985094dbfb0c0ef5cf8308a9c1d0578c38bf873c7ed721a48b67" |
| 10 | + "signature": "sha256:9e029d61f0feea4f4d19511b44579e113ef088bc23c9fcc0a05ebcd3093a8821" |
11 | 11 | }, |
12 | 12 | "nbformat": 3, |
13 | 13 | "nbformat_minor": 0, |
|
130 | 130 | "cell_type": "code", |
131 | 131 | "collapsed": false, |
132 | 132 | "input": [ |
133 | | - "print type(image_data)\n", |
134 | | - "print image_data.shape" |
| 133 | + "print(type(image_data))\n", |
| 134 | + "print(image_data.shape)" |
135 | 135 | ], |
136 | 136 | "language": "python", |
137 | 137 | "metadata": {}, |
|
174 | 174 | "collapsed": false, |
175 | 175 | "input": [ |
176 | 176 | "image_data = fits.getdata(image_file)\n", |
177 | | - "print type(image_data)\n", |
178 | | - "print image_data.shape" |
| 177 | + "print(type(image_data))\n", |
| 178 | + "print(image_data.shape)" |
179 | 179 | ], |
180 | 180 | "language": "python", |
181 | 181 | "metadata": {}, |
|
214 | 214 | "cell_type": "code", |
215 | 215 | "collapsed": false, |
216 | 216 | "input": [ |
217 | | - "print 'Min:', np.min(image_data)\n", |
218 | | - "print 'Max:', np.max(image_data)\n", |
219 | | - "print 'Mean:', np.mean(image_data)\n", |
220 | | - "print 'Stdev:', np.std(image_data)" |
| 217 | + "print('Min:', np.min(image_data))\n", |
| 218 | + "print('Max:', np.max(image_data))\n", |
| 219 | + "print('Mean:', np.mean(image_data))\n", |
| 220 | + "print('Stdev:', np.std(image_data))" |
221 | 221 | ], |
222 | 222 | "language": "python", |
223 | 223 | "metadata": {}, |
|
249 | 249 | "cell_type": "code", |
250 | 250 | "collapsed": false, |
251 | 251 | "input": [ |
252 | | - "print type(image_data.flat)" |
| 252 | + "print(type(image_data.flat))" |
253 | 253 | ], |
254 | 254 | "language": "python", |
255 | 255 | "metadata": {}, |
|
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