|
19 | 19 | "outputs": [], |
20 | 20 | "source": [ |
21 | 21 | "#install the newest version of fvgp\n", |
22 | | - "#!pip install fvgp~=4.7.9" |
| 22 | + "#!pip install fvgp~=4.8.0" |
23 | 23 | ] |
24 | 24 | }, |
25 | 25 | { |
|
55 | 55 | "name": "stderr", |
56 | 56 | "output_type": "stream", |
57 | 57 | "text": [ |
58 | | - "/home/marcus/Coding/fvGP/fvgp/gp.py:310: UserWarning: No noise function or measurement noise provided. Noise variances will be set to (0.01 * mean(|y_data|))^2.\n", |
| 58 | + "/home/marcus/Coding/fvGP/fvgp/gp.py:329: UserWarning: No noise function or measurement noise provided. Noise variances will be set to (0.01 * mean(|y_data|))^2.\n", |
59 | 59 | " self.likelihood = GPlikelihood(self.data,\n" |
60 | 60 | ] |
61 | 61 | }, |
62 | 62 | { |
63 | 63 | "name": "stdout", |
64 | 64 | "output_type": "stream", |
65 | 65 | "text": [ |
66 | | - "hyperparameters: [12.12847202 10.6867904 ]\n", |
67 | | - "prediction : 3.2944069811247743\n", |
68 | | - "uncertainty: [0.93214154]\n" |
| 66 | + "hyperparameters: [28.85710592 28.97643312]\n", |
| 67 | + "prediction : 3.3575135028855434\n", |
| 68 | + "uncertainty: [0.5369167]\n" |
69 | 69 | ] |
70 | 70 | } |
71 | 71 | ], |
|
232 | 232 | { |
233 | 233 | "data": { |
234 | 234 | "text/plain": [ |
235 | | - "array([ 0.9038004 , 10.03596858])" |
| 235 | + "array([1.69625485, 3.96570178])" |
236 | 236 | ] |
237 | 237 | }, |
238 | 238 | "execution_count": 7, |
|
259 | 259 | "data": { |
260 | 260 | "text/plain": [ |
261 | 261 | "{'x': ['dwed', 'dwe'],\n", |
262 | | - " 'm(x)': array([[0.76525193, 0.76525193, 0.76525193, 0.76525193, 0.76525193],\n", |
263 | | - " [0.59857919, 0.59857919, 0.59857919, 0.59857919, 0.59857919]]),\n", |
264 | | - " 'm(x)_flat': array([0.76525193, 0.59857919, 0.76525193, 0.59857919, 0.76525193,\n", |
265 | | - " 0.59857919, 0.76525193, 0.59857919, 0.76525193, 0.59857919]),\n", |
| 262 | + " 'm(x)': array([[0.49867421, 0.49867421, 0.49867421, 0.49867421, 0.49867421],\n", |
| 263 | + " [0.53123029, 0.53123029, 0.53123029, 0.53123029, 0.53123029]]),\n", |
| 264 | + " 'm(x)_flat': array([0.49867421, 0.53123029, 0.49867421, 0.53123029, 0.49867421,\n", |
| 265 | + " 0.53123029, 0.49867421, 0.53123029, 0.49867421, 0.53123029]),\n", |
266 | 266 | " 'x_pred': [['dwed', np.int64(0)],\n", |
267 | 267 | " ['dwe', np.int64(0)],\n", |
268 | 268 | " ['dwed', np.int64(1)],\n", |
|
327 | 327 | "name": "python", |
328 | 328 | "nbconvert_exporter": "python", |
329 | 329 | "pygments_lexer": "ipython3", |
330 | | - "version": "3.11.14" |
| 330 | + "version": "3.11.15" |
331 | 331 | } |
332 | 332 | }, |
333 | 333 | "nbformat": 4, |
|
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