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c8603a2b | 1 | /************************************************************************** |
2 | * Copyright(c) 1998-1999, ALICE Experiment at CERN, All rights reserved. * | |
3 | * * | |
4 | * Author: The ALICE Off-line Project. * | |
5 | * Contributors are mentioned in the code where appropriate. * | |
6 | * * | |
7 | * Permission to use, copy, modify and distribute this software and its * | |
8 | * documentation strictly for non-commercial purposes is hereby granted * | |
9 | * without fee, provided that the above copyright notice appears in all * | |
10 | * copies and that both the copyright notice and this permission notice * | |
11 | * appear in the supporting documentation. The authors make no claims * | |
12 | * about the suitability of this software for any purpose. It is * | |
13 | * provided "as is" without express or implied warranty. * | |
14 | **************************************************************************/ | |
15 | ||
16 | /* $Id: $ */ | |
17 | ||
18 | //_________________________________________________________________________ | |
19 | // Utility Class for Neural Network fit | |
20 | // | |
21 | // currently uses 5 input neurons | |
22 | // network configured via TMultiLayerPerceptron | |
23 | // | |
24 | //*-- Author: Paola La Rocca (Catania) | |
25 | // | |
26 | ||
27 | #include "AliCaloNeuralFit.h" | |
28 | #include <cmath> | |
29 | ||
30 | ||
31 | Double_t AliCaloNeuralFit::Value | |
32 | (int index, Double_t in0, Double_t in1, Double_t in2, Double_t in3, Double_t in4) | |
33 | { | |
34 | // | |
35 | // Compute the neural network answer, | |
36 | // given the input values (taken from the signal TGraph) | |
37 | // | |
38 | ||
39 | fInput0 = in0; | |
40 | fInput1 = in1; | |
41 | fInput2 = in2; | |
42 | fInput3 = in3; | |
43 | fInput4 = in4; | |
41539981 | 44 | switch(index) |
45 | { | |
c8603a2b | 46 | case 0: |
ceda081b | 47 | return Neuron0x93bc708(); |
c8603a2b | 48 | case 1: |
ceda081b | 49 | return Neuron0x93be5d0(); |
c8603a2b | 50 | default: |
51 | return 0.; | |
52 | } | |
53 | } | |
54 | ||
ceda081b | 55 | Double_t AliCaloNeuralFit::Neuron0x8ceb770() const |
c8603a2b | 56 | { |
57 | // | |
58 | // Input neuron. | |
59 | // Just return activation value externally setted. | |
60 | // | |
61 | ||
62 | return fInput0; | |
63 | } | |
64 | ||
ceda081b | 65 | Double_t AliCaloNeuralFit::Neuron0x8ceb900() const |
c8603a2b | 66 | { |
67 | // | |
68 | // Input neuron. | |
69 | // Just return activation value externally setted. | |
70 | // | |
71 | ||
72 | return fInput1; | |
73 | } | |
74 | ||
ceda081b | 75 | Double_t AliCaloNeuralFit::Neuron0x8cebad8() const |
c8603a2b | 76 | { |
77 | // | |
78 | // Input neuron. | |
79 | // Just return activation value externally setted. | |
80 | // | |
81 | ||
82 | return fInput2; | |
83 | } | |
84 | ||
ceda081b | 85 | Double_t AliCaloNeuralFit::Neuron0x8cebcb0() const |
c8603a2b | 86 | { |
87 | // | |
88 | // Input neuron. | |
89 | // Just return activation value externally setted. | |
90 | // | |
91 | ||
92 | return fInput3; | |
93 | } | |
94 | ||
ceda081b | 95 | Double_t AliCaloNeuralFit::Neuron0x93bc518() const |
c8603a2b | 96 | { |
97 | // | |
98 | // Input neuron. | |
99 | // Just return activation value externally setted. | |
100 | // | |
101 | ||
102 | return fInput4; | |
103 | } | |
104 | ||
ceda081b | 105 | Double_t AliCaloNeuralFit::Input0x93bc838() const |
c8603a2b | 106 | { |
107 | // | |
108 | // Hidden/Output neuron | |
109 | // Compute the activation from linear combination of | |
110 | // all neurons going into this, each one times its synaptic weight | |
111 | // | |
ceda081b | 112 | Double_t input = -0.097207; |
113 | input += Synapse0x93bc9e8(); | |
114 | input += Synapse0x93bca10(); | |
115 | input += Synapse0x93bca38(); | |
116 | input += Synapse0x93bca60(); | |
117 | input += Synapse0x93bca88(); | |
c8603a2b | 118 | return input; |
119 | } | |
120 | ||
ceda081b | 121 | Double_t AliCaloNeuralFit::Neuron0x93bc838() const |
c8603a2b | 122 | { |
123 | // | |
124 | // Hidden/Output neuron | |
125 | // Return computed activation | |
126 | // | |
ceda081b | 127 | Double_t input = Input0x93bc838(); |
c8603a2b | 128 | return (tanh(input) * 1)+0; |
129 | } | |
130 | ||
ceda081b | 131 | Double_t AliCaloNeuralFit::Input0x93bcab0() const |
c8603a2b | 132 | { |
133 | // | |
134 | // Hidden/Output neuron | |
135 | // Compute the activation from linear combination of | |
136 | // all neurons going into this, each one times its synaptic weight | |
137 | // | |
ceda081b | 138 | Double_t input = 0.0466086; |
139 | input += Synapse0x93bcca8(); | |
140 | input += Synapse0x93bccd0(); | |
141 | input += Synapse0x93bccf8(); | |
142 | input += Synapse0x93bcd20(); | |
143 | input += Synapse0x93bcd48(); | |
c8603a2b | 144 | return input; |
145 | } | |
146 | ||
ceda081b | 147 | Double_t AliCaloNeuralFit::Neuron0x93bcab0() const |
c8603a2b | 148 | { |
149 | // | |
150 | // Hidden/Output neuron | |
151 | // Return computed activation | |
152 | // | |
ceda081b | 153 | Double_t input = Input0x93bcab0(); |
c8603a2b | 154 | return (tanh(input) * 1)+0; |
155 | } | |
156 | ||
ceda081b | 157 | Double_t AliCaloNeuralFit::Input0x93bcd70() const |
c8603a2b | 158 | { |
159 | // | |
160 | // Hidden/Output neuron | |
161 | // Compute the activation from linear combination of | |
162 | // all neurons going into this, each one times its synaptic weight | |
163 | // | |
ceda081b | 164 | Double_t input = 0.617042; |
165 | input += Synapse0x93bcf68(); | |
166 | input += Synapse0x93bcf90(); | |
167 | input += Synapse0x93bcfb8(); | |
168 | input += Synapse0x93bcfe0(); | |
169 | input += Synapse0x93bd008(); | |
c8603a2b | 170 | return input; |
171 | } | |
172 | ||
ceda081b | 173 | Double_t AliCaloNeuralFit::Neuron0x93bcd70() const |
c8603a2b | 174 | { |
175 | // | |
176 | // Hidden/Output neuron | |
177 | // Return computed activation | |
178 | // | |
ceda081b | 179 | Double_t input = Input0x93bcd70(); |
c8603a2b | 180 | return (tanh(input) * 1)+0; |
181 | } | |
182 | ||
ceda081b | 183 | Double_t AliCaloNeuralFit::Input0x93bd030() const |
c8603a2b | 184 | { |
185 | // | |
186 | // Hidden/Output neuron | |
187 | // Compute the activation from linear combination of | |
188 | // all neurons going into this, each one times its synaptic weight | |
189 | // | |
ceda081b | 190 | Double_t input = -0.519529; |
191 | input += Synapse0x93bd228(); | |
192 | input += Synapse0x93bd250(); | |
193 | input += Synapse0x93bd300(); | |
194 | input += Synapse0x93bd328(); | |
195 | input += Synapse0x93bd350(); | |
c8603a2b | 196 | return input; |
197 | } | |
198 | ||
ceda081b | 199 | Double_t AliCaloNeuralFit::Neuron0x93bd030() const |
c8603a2b | 200 | { |
201 | // | |
202 | // Hidden/Output neuron | |
203 | // Return computed activation | |
204 | // | |
ceda081b | 205 | Double_t input = Input0x93bd030(); |
c8603a2b | 206 | return (tanh(input) * 1)+0; |
207 | } | |
208 | ||
ceda081b | 209 | Double_t AliCaloNeuralFit::Input0x93bd378() const |
c8603a2b | 210 | { |
211 | // | |
212 | // Hidden/Output neuron | |
213 | // Compute the activation from linear combination of | |
214 | // all neurons going into this, each one times its synaptic weight | |
215 | // | |
ceda081b | 216 | Double_t input = -0.405186; |
217 | input += Synapse0x93bd528(); | |
218 | input += Synapse0x93bd550(); | |
219 | input += Synapse0x93bd578(); | |
220 | input += Synapse0x93bd5a0(); | |
221 | input += Synapse0x93bd5c8(); | |
c8603a2b | 222 | return input; |
223 | } | |
224 | ||
ceda081b | 225 | Double_t AliCaloNeuralFit::Neuron0x93bd378() const |
c8603a2b | 226 | { |
227 | // | |
228 | // Hidden/Output neuron | |
229 | // Return computed activation | |
230 | // | |
ceda081b | 231 | Double_t input = Input0x93bd378(); |
c8603a2b | 232 | return (tanh(input) * 1)+0; |
233 | } | |
234 | ||
ceda081b | 235 | Double_t AliCaloNeuralFit::Input0x93bd5f0() const |
c8603a2b | 236 | { |
237 | // | |
238 | // Hidden/Output neuron | |
239 | // Compute the activation from linear combination of | |
240 | // all neurons going into this, each one times its synaptic weight | |
241 | // | |
ceda081b | 242 | Double_t input = -0.253465; |
243 | input += Synapse0x93bd7e8(); | |
244 | input += Synapse0x93bd810(); | |
245 | input += Synapse0x93bd838(); | |
246 | input += Synapse0x93bd860(); | |
247 | input += Synapse0x93bd888(); | |
c8603a2b | 248 | return input; |
249 | } | |
250 | ||
ceda081b | 251 | Double_t AliCaloNeuralFit::Neuron0x93bd5f0() const |
c8603a2b | 252 | { |
253 | // | |
254 | // Hidden/Output neuron | |
255 | // Return computed activation | |
256 | // | |
ceda081b | 257 | Double_t input = Input0x93bd5f0(); |
c8603a2b | 258 | return (tanh(input) * 1)+0; |
259 | } | |
260 | ||
ceda081b | 261 | Double_t AliCaloNeuralFit::Input0x93bd8b0() const |
c8603a2b | 262 | { |
263 | // | |
264 | // Hidden/Output neuron | |
265 | // Compute the activation from linear combination of | |
266 | // all neurons going into this, each one times its synaptic weight | |
267 | // | |
ceda081b | 268 | Double_t input = 0.0340672; |
269 | input += Synapse0x93bdaa8(); | |
270 | input += Synapse0x93bdad0(); | |
271 | input += Synapse0x93bdaf8(); | |
272 | input += Synapse0x8ce7098(); | |
273 | input += Synapse0x8ce70c0(); | |
c8603a2b | 274 | return input; |
275 | } | |
276 | ||
ceda081b | 277 | Double_t AliCaloNeuralFit::Neuron0x93bd8b0() const |
c8603a2b | 278 | { |
279 | // | |
280 | // Hidden/Output neuron | |
281 | // Return computed activation | |
282 | // | |
ceda081b | 283 | Double_t input = Input0x93bd8b0(); |
c8603a2b | 284 | return (tanh(input) * 1)+0; |
285 | } | |
286 | ||
ceda081b | 287 | Double_t AliCaloNeuralFit::Input0x93bdc28() const |
c8603a2b | 288 | { |
289 | // | |
290 | // Hidden/Output neuron | |
291 | // Compute the activation from linear combination of | |
292 | // all neurons going into this, each one times its synaptic weight | |
293 | // | |
ceda081b | 294 | Double_t input = 0.231599; |
295 | input += Synapse0x93bde20(); | |
296 | input += Synapse0x93bde48(); | |
297 | input += Synapse0x93bde70(); | |
298 | input += Synapse0x93bde98(); | |
299 | input += Synapse0x93bdec0(); | |
c8603a2b | 300 | return input; |
301 | } | |
302 | ||
ceda081b | 303 | Double_t AliCaloNeuralFit::Neuron0x93bdc28() const |
c8603a2b | 304 | { |
305 | // | |
306 | // Hidden/Output neuron | |
307 | // Return computed activation | |
308 | // | |
ceda081b | 309 | Double_t input = Input0x93bdc28(); |
c8603a2b | 310 | return (tanh(input) * 1)+0; |
311 | } | |
312 | ||
ceda081b | 313 | Double_t AliCaloNeuralFit::Input0x93bdee8() const |
c8603a2b | 314 | { |
315 | // | |
316 | // Hidden/Output neuron | |
317 | // Compute the activation from linear combination of | |
318 | // all neurons going into this, each one times its synaptic weight | |
319 | // | |
ceda081b | 320 | Double_t input = 0.56831; |
321 | input += Synapse0x93be0e0(); | |
322 | input += Synapse0x93be108(); | |
323 | input += Synapse0x93be130(); | |
324 | input += Synapse0x93be158(); | |
325 | input += Synapse0x93be180(); | |
c8603a2b | 326 | return input; |
327 | } | |
328 | ||
ceda081b | 329 | Double_t AliCaloNeuralFit::Neuron0x93bdee8() const |
c8603a2b | 330 | { |
331 | // | |
332 | // Hidden/Output neuron | |
333 | // Return computed activation | |
334 | // | |
ceda081b | 335 | Double_t input = Input0x93bdee8(); |
c8603a2b | 336 | return (tanh(input) * 1)+0; |
337 | } | |
338 | ||
ceda081b | 339 | Double_t AliCaloNeuralFit::Input0x93be1a8() const |
c8603a2b | 340 | { |
341 | // | |
342 | // Hidden/Output neuron | |
343 | // Compute the activation from linear combination of | |
344 | // all neurons going into this, each one times its synaptic weight | |
345 | // | |
ceda081b | 346 | Double_t input = 0.223889; |
347 | input += Synapse0x93be3a0(); | |
348 | input += Synapse0x93be3c8(); | |
349 | input += Synapse0x93be3f0(); | |
350 | input += Synapse0x93be418(); | |
351 | input += Synapse0x93be440(); | |
c8603a2b | 352 | return input; |
353 | } | |
354 | ||
ceda081b | 355 | Double_t AliCaloNeuralFit::Neuron0x93be1a8() const |
c8603a2b | 356 | { |
357 | // | |
358 | // Hidden/Output neuron | |
359 | // Return computed activation | |
360 | // | |
ceda081b | 361 | Double_t input = Input0x93be1a8(); |
c8603a2b | 362 | return (tanh(input) * 1)+0; |
363 | } | |
364 | ||
ceda081b | 365 | Double_t AliCaloNeuralFit::Input0x93bc708() const |
c8603a2b | 366 | { |
367 | // | |
368 | // Hidden/Output neuron | |
369 | // Compute the activation from linear combination of | |
370 | // all neurons going into this, each one times its synaptic weight | |
371 | // | |
ceda081b | 372 | Double_t input = 0.565736; |
373 | input += Synapse0x93bd2c0(); | |
374 | input += Synapse0x93be468(); | |
375 | input += Synapse0x93be490(); | |
376 | input += Synapse0x93be4b8(); | |
377 | input += Synapse0x93be4e0(); | |
378 | input += Synapse0x93be508(); | |
379 | input += Synapse0x93be530(); | |
380 | input += Synapse0x93be558(); | |
381 | input += Synapse0x93be580(); | |
382 | input += Synapse0x93be5a8(); | |
c8603a2b | 383 | return input; |
384 | } | |
385 | ||
ceda081b | 386 | Double_t AliCaloNeuralFit::Neuron0x93bc708() const |
c8603a2b | 387 | { |
388 | // | |
389 | // Hidden/Output neuron | |
390 | // Return computed activation | |
391 | // | |
ceda081b | 392 | Double_t input = Input0x93bc708(); |
c8603a2b | 393 | return (input * 1)+0; |
394 | } | |
395 | ||
ceda081b | 396 | Double_t AliCaloNeuralFit::Input0x93be5d0() const |
c8603a2b | 397 | { |
398 | // | |
399 | // Hidden/Output neuron | |
400 | // Compute the activation from linear combination of | |
401 | // all neurons going into this, each one times its synaptic weight | |
402 | // | |
ceda081b | 403 | Double_t input = 0.311772; |
404 | input += Synapse0x93be7d0(); | |
405 | input += Synapse0x93be7f8(); | |
406 | input += Synapse0x93be820(); | |
407 | input += Synapse0x93be848(); | |
408 | input += Synapse0x93be870(); | |
409 | input += Synapse0x934a7c8(); | |
410 | input += Synapse0x93605e0(); | |
411 | input += Synapse0x9360608(); | |
412 | input += Synapse0x8ce6fe8(); | |
413 | input += Synapse0x8ce7010(); | |
c8603a2b | 414 | return input; |
415 | } | |
416 | ||
ceda081b | 417 | Double_t AliCaloNeuralFit::Neuron0x93be5d0() const |
c8603a2b | 418 | { |
419 | // | |
420 | // Hidden/Output neuron | |
421 | // Return computed activation | |
422 | // | |
ceda081b | 423 | Double_t input = Input0x93be5d0(); |
c8603a2b | 424 | return (input * 1)+0; |
425 | } | |
426 | ||
ceda081b | 427 | Double_t AliCaloNeuralFit::Synapse0x93bc9e8() const |
c8603a2b | 428 | { |
429 | // | |
430 | // Synaptic connection | |
431 | // Multiplies input times synaptic weight | |
432 | // | |
ceda081b | 433 | return (Neuron0x8ceb770()*-0.173079); |
c8603a2b | 434 | } |
435 | ||
ceda081b | 436 | Double_t AliCaloNeuralFit::Synapse0x93bca10() const |
c8603a2b | 437 | { |
438 | // | |
439 | // Synaptic connection | |
440 | // Multiplies input times synaptic weight | |
441 | // | |
ceda081b | 442 | return (Neuron0x8ceb900()*-0.356515); |
c8603a2b | 443 | } |
444 | ||
ceda081b | 445 | Double_t AliCaloNeuralFit::Synapse0x93bca38() const |
c8603a2b | 446 | { |
447 | // | |
448 | // Synaptic connection | |
449 | // Multiplies input times synaptic weight | |
450 | // | |
ceda081b | 451 | return (Neuron0x8cebad8()*0.116333); |
c8603a2b | 452 | } |
453 | ||
ceda081b | 454 | Double_t AliCaloNeuralFit::Synapse0x93bca60() const |
c8603a2b | 455 | { |
456 | // | |
457 | // Synaptic connection | |
458 | // Multiplies input times synaptic weight | |
459 | // | |
ceda081b | 460 | return (Neuron0x8cebcb0()*-0.0647334); |
c8603a2b | 461 | } |
462 | ||
ceda081b | 463 | Double_t AliCaloNeuralFit::Synapse0x93bca88() const |
c8603a2b | 464 | { |
465 | // | |
466 | // Synaptic connection | |
467 | // Multiplies input times synaptic weight | |
468 | // | |
ceda081b | 469 | return (Neuron0x93bc518()*0.135181); |
c8603a2b | 470 | } |
471 | ||
ceda081b | 472 | Double_t AliCaloNeuralFit::Synapse0x93bcca8() const |
c8603a2b | 473 | { |
474 | // | |
475 | // Synaptic connection | |
476 | // Multiplies input times synaptic weight | |
477 | // | |
ceda081b | 478 | return (Neuron0x8ceb770()*-0.00703734); |
c8603a2b | 479 | } |
480 | ||
ceda081b | 481 | Double_t AliCaloNeuralFit::Synapse0x93bccd0() const |
c8603a2b | 482 | { |
483 | // | |
484 | // Synaptic connection | |
485 | // Multiplies input times synaptic weight | |
486 | // | |
ceda081b | 487 | return (Neuron0x8ceb900()*1.04245); |
c8603a2b | 488 | } |
489 | ||
ceda081b | 490 | Double_t AliCaloNeuralFit::Synapse0x93bccf8() const |
c8603a2b | 491 | { |
492 | // | |
493 | // Synaptic connection | |
494 | // Multiplies input times synaptic weight | |
495 | // | |
ceda081b | 496 | return (Neuron0x8cebad8()*0.70812); |
c8603a2b | 497 | } |
498 | ||
ceda081b | 499 | Double_t AliCaloNeuralFit::Synapse0x93bcd20() const |
c8603a2b | 500 | { |
501 | // | |
502 | // Synaptic connection | |
503 | // Multiplies input times synaptic weight | |
504 | // | |
ceda081b | 505 | return (Neuron0x8cebcb0()*-0.486738); |
c8603a2b | 506 | } |
507 | ||
ceda081b | 508 | Double_t AliCaloNeuralFit::Synapse0x93bcd48() const |
c8603a2b | 509 | { |
510 | // | |
511 | // Synaptic connection | |
512 | // Multiplies input times synaptic weight | |
513 | // | |
ceda081b | 514 | return (Neuron0x93bc518()*-0.623982); |
c8603a2b | 515 | } |
516 | ||
ceda081b | 517 | Double_t AliCaloNeuralFit::Synapse0x93bcf68() const |
c8603a2b | 518 | { |
519 | // | |
520 | // Synaptic connection | |
521 | // Multiplies input times synaptic weight | |
522 | // | |
ceda081b | 523 | return (Neuron0x8ceb770()*0.0557636); |
c8603a2b | 524 | } |
525 | ||
ceda081b | 526 | Double_t AliCaloNeuralFit::Synapse0x93bcf90() const |
c8603a2b | 527 | { |
528 | // | |
529 | // Synaptic connection | |
530 | // Multiplies input times synaptic weight | |
531 | // | |
ceda081b | 532 | return (Neuron0x8ceb900()*0.503374); |
c8603a2b | 533 | } |
534 | ||
ceda081b | 535 | Double_t AliCaloNeuralFit::Synapse0x93bcfb8() const |
c8603a2b | 536 | { |
537 | // | |
538 | // Synaptic connection | |
539 | // Multiplies input times synaptic weight | |
540 | // | |
ceda081b | 541 | return (Neuron0x8cebad8()*-0.0500216); |
c8603a2b | 542 | } |
543 | ||
ceda081b | 544 | Double_t AliCaloNeuralFit::Synapse0x93bcfe0() const |
c8603a2b | 545 | { |
546 | // | |
547 | // Synaptic connection | |
548 | // Multiplies input times synaptic weight | |
549 | // | |
ceda081b | 550 | return (Neuron0x8cebcb0()*0.0561266); |
c8603a2b | 551 | } |
552 | ||
ceda081b | 553 | Double_t AliCaloNeuralFit::Synapse0x93bd008() const |
c8603a2b | 554 | { |
555 | // | |
556 | // Synaptic connection | |
557 | // Multiplies input times synaptic weight | |
558 | // | |
ceda081b | 559 | return (Neuron0x93bc518()*-0.403885); |
c8603a2b | 560 | } |
561 | ||
ceda081b | 562 | Double_t AliCaloNeuralFit::Synapse0x93bd228() const |
c8603a2b | 563 | { |
564 | // | |
565 | // Synaptic connection | |
566 | // Multiplies input times synaptic weight | |
567 | // | |
ceda081b | 568 | return (Neuron0x8ceb770()*-0.0649038); |
c8603a2b | 569 | } |
570 | ||
ceda081b | 571 | Double_t AliCaloNeuralFit::Synapse0x93bd250() const |
c8603a2b | 572 | { |
573 | // | |
574 | // Synaptic connection | |
575 | // Multiplies input times synaptic weight | |
576 | // | |
ceda081b | 577 | return (Neuron0x8ceb900()*-0.164437); |
c8603a2b | 578 | } |
579 | ||
ceda081b | 580 | Double_t AliCaloNeuralFit::Synapse0x93bd300() const |
c8603a2b | 581 | { |
582 | // | |
583 | // Synaptic connection | |
584 | // Multiplies input times synaptic weight | |
585 | // | |
ceda081b | 586 | return (Neuron0x8cebad8()*-0.657412); |
c8603a2b | 587 | } |
588 | ||
ceda081b | 589 | Double_t AliCaloNeuralFit::Synapse0x93bd328() const |
c8603a2b | 590 | { |
591 | // | |
592 | // Synaptic connection | |
593 | // Multiplies input times synaptic weight | |
594 | // | |
ceda081b | 595 | return (Neuron0x8cebcb0()*0.175571); |
c8603a2b | 596 | } |
597 | ||
ceda081b | 598 | Double_t AliCaloNeuralFit::Synapse0x93bd350() const |
c8603a2b | 599 | { |
600 | // | |
601 | // Synaptic connection | |
602 | // Multiplies input times synaptic weight | |
603 | // | |
ceda081b | 604 | return (Neuron0x93bc518()*0.588896); |
c8603a2b | 605 | } |
606 | ||
ceda081b | 607 | Double_t AliCaloNeuralFit::Synapse0x93bd528() const |
c8603a2b | 608 | { |
609 | // | |
610 | // Synaptic connection | |
611 | // Multiplies input times synaptic weight | |
612 | // | |
ceda081b | 613 | return (Neuron0x8ceb770()*-0.00361627); |
c8603a2b | 614 | } |
615 | ||
ceda081b | 616 | Double_t AliCaloNeuralFit::Synapse0x93bd550() const |
c8603a2b | 617 | { |
618 | // | |
619 | // Synaptic connection | |
620 | // Multiplies input times synaptic weight | |
621 | // | |
ceda081b | 622 | return (Neuron0x8ceb900()*0.398821); |
c8603a2b | 623 | } |
624 | ||
ceda081b | 625 | Double_t AliCaloNeuralFit::Synapse0x93bd578() const |
c8603a2b | 626 | { |
627 | // | |
628 | // Synaptic connection | |
629 | // Multiplies input times synaptic weight | |
630 | // | |
ceda081b | 631 | return (Neuron0x8cebad8()*0.38779); |
c8603a2b | 632 | } |
633 | ||
ceda081b | 634 | Double_t AliCaloNeuralFit::Synapse0x93bd5a0() const |
c8603a2b | 635 | { |
636 | // | |
637 | // Synaptic connection | |
638 | // Multiplies input times synaptic weight | |
639 | // | |
ceda081b | 640 | return (Neuron0x8cebcb0()*0.341009); |
c8603a2b | 641 | } |
642 | ||
ceda081b | 643 | Double_t AliCaloNeuralFit::Synapse0x93bd5c8() const |
c8603a2b | 644 | { |
645 | // | |
646 | // Synaptic connection | |
647 | // Multiplies input times synaptic weight | |
648 | // | |
ceda081b | 649 | return (Neuron0x93bc518()*0.290214); |
c8603a2b | 650 | } |
651 | ||
ceda081b | 652 | Double_t AliCaloNeuralFit::Synapse0x93bd7e8() const |
c8603a2b | 653 | { |
654 | // | |
655 | // Synaptic connection | |
656 | // Multiplies input times synaptic weight | |
657 | // | |
ceda081b | 658 | return (Neuron0x8ceb770()*-0.238609); |
c8603a2b | 659 | } |
660 | ||
ceda081b | 661 | Double_t AliCaloNeuralFit::Synapse0x93bd810() const |
c8603a2b | 662 | { |
663 | // | |
664 | // Synaptic connection | |
665 | // Multiplies input times synaptic weight | |
666 | // | |
ceda081b | 667 | return (Neuron0x8ceb900()*-0.193207); |
c8603a2b | 668 | } |
669 | ||
ceda081b | 670 | Double_t AliCaloNeuralFit::Synapse0x93bd838() const |
c8603a2b | 671 | { |
672 | // | |
673 | // Synaptic connection | |
674 | // Multiplies input times synaptic weight | |
675 | // | |
ceda081b | 676 | return (Neuron0x8cebad8()*0.304672); |
c8603a2b | 677 | } |
678 | ||
ceda081b | 679 | Double_t AliCaloNeuralFit::Synapse0x93bd860() const |
c8603a2b | 680 | { |
681 | // | |
682 | // Synaptic connection | |
683 | // Multiplies input times synaptic weight | |
684 | // | |
ceda081b | 685 | return (Neuron0x8cebcb0()*-0.327625); |
c8603a2b | 686 | } |
687 | ||
ceda081b | 688 | Double_t AliCaloNeuralFit::Synapse0x93bd888() const |
c8603a2b | 689 | { |
690 | // | |
691 | // Synaptic connection | |
692 | // Multiplies input times synaptic weight | |
693 | // | |
ceda081b | 694 | return (Neuron0x93bc518()*-0.268996); |
c8603a2b | 695 | } |
696 | ||
ceda081b | 697 | Double_t AliCaloNeuralFit::Synapse0x93bdaa8() const |
c8603a2b | 698 | { |
699 | // | |
700 | // Synaptic connection | |
701 | // Multiplies input times synaptic weight | |
702 | // | |
ceda081b | 703 | return (Neuron0x8ceb770()*0.725989); |
c8603a2b | 704 | } |
705 | ||
ceda081b | 706 | Double_t AliCaloNeuralFit::Synapse0x93bdad0() const |
c8603a2b | 707 | { |
708 | // | |
709 | // Synaptic connection | |
710 | // Multiplies input times synaptic weight | |
711 | // | |
ceda081b | 712 | return (Neuron0x8ceb900()*-0.217538); |
c8603a2b | 713 | } |
714 | ||
ceda081b | 715 | Double_t AliCaloNeuralFit::Synapse0x93bdaf8() const |
c8603a2b | 716 | { |
717 | // | |
718 | // Synaptic connection | |
719 | // Multiplies input times synaptic weight | |
720 | // | |
ceda081b | 721 | return (Neuron0x8cebad8()*-0.603975); |
c8603a2b | 722 | } |
723 | ||
ceda081b | 724 | Double_t AliCaloNeuralFit::Synapse0x8ce7098() const |
c8603a2b | 725 | { |
726 | // | |
727 | // Synaptic connection | |
728 | // Multiplies input times synaptic weight | |
729 | // | |
ceda081b | 730 | return (Neuron0x8cebcb0()*0.175658); |
c8603a2b | 731 | } |
732 | ||
ceda081b | 733 | Double_t AliCaloNeuralFit::Synapse0x8ce70c0() const |
c8603a2b | 734 | { |
735 | // | |
736 | // Synaptic connection | |
737 | // Multiplies input times synaptic weight | |
738 | // | |
ceda081b | 739 | return (Neuron0x93bc518()*-0.262399); |
c8603a2b | 740 | } |
741 | ||
ceda081b | 742 | Double_t AliCaloNeuralFit::Synapse0x93bde20() const |
c8603a2b | 743 | { |
744 | // | |
745 | // Synaptic connection | |
746 | // Multiplies input times synaptic weight | |
747 | // | |
ceda081b | 748 | return (Neuron0x8ceb770()*-1.08242); |
c8603a2b | 749 | } |
750 | ||
ceda081b | 751 | Double_t AliCaloNeuralFit::Synapse0x93bde48() const |
c8603a2b | 752 | { |
753 | // | |
754 | // Synaptic connection | |
755 | // Multiplies input times synaptic weight | |
756 | // | |
ceda081b | 757 | return (Neuron0x8ceb900()*0.41456); |
c8603a2b | 758 | } |
759 | ||
ceda081b | 760 | Double_t AliCaloNeuralFit::Synapse0x93bde70() const |
c8603a2b | 761 | { |
762 | // | |
763 | // Synaptic connection | |
764 | // Multiplies input times synaptic weight | |
765 | // | |
ceda081b | 766 | return (Neuron0x8cebad8()*0.117809); |
c8603a2b | 767 | } |
768 | ||
ceda081b | 769 | Double_t AliCaloNeuralFit::Synapse0x93bde98() const |
c8603a2b | 770 | { |
771 | // | |
772 | // Synaptic connection | |
773 | // Multiplies input times synaptic weight | |
774 | // | |
ceda081b | 775 | return (Neuron0x8cebcb0()*0.514938); |
c8603a2b | 776 | } |
777 | ||
ceda081b | 778 | Double_t AliCaloNeuralFit::Synapse0x93bdec0() const |
c8603a2b | 779 | { |
780 | // | |
781 | // Synaptic connection | |
782 | // Multiplies input times synaptic weight | |
783 | // | |
ceda081b | 784 | return (Neuron0x93bc518()*-0.193678); |
c8603a2b | 785 | } |
786 | ||
ceda081b | 787 | Double_t AliCaloNeuralFit::Synapse0x93be0e0() const |
c8603a2b | 788 | { |
789 | // | |
790 | // Synaptic connection | |
791 | // Multiplies input times synaptic weight | |
792 | // | |
ceda081b | 793 | return (Neuron0x8ceb770()*0.580561); |
c8603a2b | 794 | } |
795 | ||
ceda081b | 796 | Double_t AliCaloNeuralFit::Synapse0x93be108() const |
c8603a2b | 797 | { |
798 | // | |
799 | // Synaptic connection | |
800 | // Multiplies input times synaptic weight | |
801 | // | |
ceda081b | 802 | return (Neuron0x8ceb900()*0.610453); |
c8603a2b | 803 | } |
804 | ||
ceda081b | 805 | Double_t AliCaloNeuralFit::Synapse0x93be130() const |
c8603a2b | 806 | { |
807 | // | |
808 | // Synaptic connection | |
809 | // Multiplies input times synaptic weight | |
810 | // | |
ceda081b | 811 | return (Neuron0x8cebad8()*0.4977); |
c8603a2b | 812 | } |
813 | ||
ceda081b | 814 | Double_t AliCaloNeuralFit::Synapse0x93be158() const |
c8603a2b | 815 | { |
816 | // | |
817 | // Synaptic connection | |
818 | // Multiplies input times synaptic weight | |
819 | // | |
ceda081b | 820 | return (Neuron0x8cebcb0()*-0.328315); |
c8603a2b | 821 | } |
822 | ||
ceda081b | 823 | Double_t AliCaloNeuralFit::Synapse0x93be180() const |
c8603a2b | 824 | { |
825 | // | |
826 | // Synaptic connection | |
827 | // Multiplies input times synaptic weight | |
828 | // | |
ceda081b | 829 | return (Neuron0x93bc518()*-0.729094); |
c8603a2b | 830 | } |
831 | ||
ceda081b | 832 | Double_t AliCaloNeuralFit::Synapse0x93be3a0() const |
c8603a2b | 833 | { |
834 | // | |
835 | // Synaptic connection | |
836 | // Multiplies input times synaptic weight | |
837 | // | |
ceda081b | 838 | return (Neuron0x8ceb770()*0.172817); |
c8603a2b | 839 | } |
840 | ||
ceda081b | 841 | Double_t AliCaloNeuralFit::Synapse0x93be3c8() const |
c8603a2b | 842 | { |
843 | // | |
844 | // Synaptic connection | |
845 | // Multiplies input times synaptic weight | |
846 | // | |
ceda081b | 847 | return (Neuron0x8ceb900()*0.288833); |
c8603a2b | 848 | } |
849 | ||
ceda081b | 850 | Double_t AliCaloNeuralFit::Synapse0x93be3f0() const |
c8603a2b | 851 | { |
852 | // | |
853 | // Synaptic connection | |
854 | // Multiplies input times synaptic weight | |
855 | // | |
ceda081b | 856 | return (Neuron0x8cebad8()*0.0242409); |
c8603a2b | 857 | } |
858 | ||
ceda081b | 859 | Double_t AliCaloNeuralFit::Synapse0x93be418() const |
c8603a2b | 860 | { |
861 | // | |
862 | // Synaptic connection | |
863 | // Multiplies input times synaptic weight | |
864 | // | |
ceda081b | 865 | return (Neuron0x8cebcb0()*0.273568); |
c8603a2b | 866 | } |
867 | ||
ceda081b | 868 | Double_t AliCaloNeuralFit::Synapse0x93be440() const |
c8603a2b | 869 | { |
870 | // | |
871 | // Synaptic connection | |
872 | // Multiplies input times synaptic weight | |
873 | // | |
ceda081b | 874 | return (Neuron0x93bc518()*0.261816); |
c8603a2b | 875 | } |
876 | ||
ceda081b | 877 | Double_t AliCaloNeuralFit::Synapse0x93bd2c0() const |
c8603a2b | 878 | { |
879 | // | |
880 | // Synaptic connection | |
881 | // Multiplies input times synaptic weight | |
882 | // | |
ceda081b | 883 | return (Neuron0x93bc838()*-0.332154); |
c8603a2b | 884 | } |
885 | ||
ceda081b | 886 | Double_t AliCaloNeuralFit::Synapse0x93be468() const |
c8603a2b | 887 | { |
888 | // | |
889 | // Synaptic connection | |
890 | // Multiplies input times synaptic weight | |
891 | // | |
ceda081b | 892 | return (Neuron0x93bcab0()*0.175458); |
c8603a2b | 893 | } |
894 | ||
ceda081b | 895 | Double_t AliCaloNeuralFit::Synapse0x93be490() const |
c8603a2b | 896 | { |
897 | // | |
898 | // Synaptic connection | |
899 | // Multiplies input times synaptic weight | |
900 | // | |
ceda081b | 901 | return (Neuron0x93bcd70()*0.211775); |
c8603a2b | 902 | } |
903 | ||
ceda081b | 904 | Double_t AliCaloNeuralFit::Synapse0x93be4b8() const |
c8603a2b | 905 | { |
906 | // | |
907 | // Synaptic connection | |
908 | // Multiplies input times synaptic weight | |
909 | // | |
ceda081b | 910 | return (Neuron0x93bd030()*0.335443); |
c8603a2b | 911 | } |
912 | ||
ceda081b | 913 | Double_t AliCaloNeuralFit::Synapse0x93be4e0() const |
c8603a2b | 914 | { |
915 | // | |
916 | // Synaptic connection | |
917 | // Multiplies input times synaptic weight | |
918 | // | |
ceda081b | 919 | return (Neuron0x93bd378()*0.341079); |
c8603a2b | 920 | } |
921 | ||
ceda081b | 922 | Double_t AliCaloNeuralFit::Synapse0x93be508() const |
c8603a2b | 923 | { |
924 | // | |
925 | // Synaptic connection | |
926 | // Multiplies input times synaptic weight | |
927 | // | |
ceda081b | 928 | return (Neuron0x93bd5f0()*-0.324381); |
c8603a2b | 929 | } |
930 | ||
ceda081b | 931 | Double_t AliCaloNeuralFit::Synapse0x93be530() const |
c8603a2b | 932 | { |
933 | // | |
934 | // Synaptic connection | |
935 | // Multiplies input times synaptic weight | |
936 | // | |
ceda081b | 937 | return (Neuron0x93bd8b0()*0.135666); |
c8603a2b | 938 | } |
939 | ||
ceda081b | 940 | Double_t AliCaloNeuralFit::Synapse0x93be558() const |
c8603a2b | 941 | { |
942 | // | |
943 | // Synaptic connection | |
944 | // Multiplies input times synaptic weight | |
945 | // | |
ceda081b | 946 | return (Neuron0x93bdc28()*-0.0213577); |
c8603a2b | 947 | } |
948 | ||
ceda081b | 949 | Double_t AliCaloNeuralFit::Synapse0x93be580() const |
c8603a2b | 950 | { |
951 | // | |
952 | // Synaptic connection | |
953 | // Multiplies input times synaptic weight | |
954 | // | |
ceda081b | 955 | return (Neuron0x93bdee8()*-0.598335); |
c8603a2b | 956 | } |
957 | ||
ceda081b | 958 | Double_t AliCaloNeuralFit::Synapse0x93be5a8() const |
c8603a2b | 959 | { |
960 | // | |
961 | // Synaptic connection | |
962 | // Multiplies input times synaptic weight | |
963 | // | |
ceda081b | 964 | return (Neuron0x93be1a8()*0.636813); |
c8603a2b | 965 | } |
966 | ||
ceda081b | 967 | Double_t AliCaloNeuralFit::Synapse0x93be7d0() const |
c8603a2b | 968 | { |
969 | // | |
970 | // Synaptic connection | |
971 | // Multiplies input times synaptic weight | |
972 | // | |
ceda081b | 973 | return (Neuron0x93bc838()*0.173357); |
c8603a2b | 974 | } |
975 | ||
ceda081b | 976 | Double_t AliCaloNeuralFit::Synapse0x93be7f8() const |
c8603a2b | 977 | { |
978 | // | |
979 | // Synaptic connection | |
980 | // Multiplies input times synaptic weight | |
981 | // | |
ceda081b | 982 | return (Neuron0x93bcab0()*-0.971616); |
c8603a2b | 983 | } |
984 | ||
ceda081b | 985 | Double_t AliCaloNeuralFit::Synapse0x93be820() const |
c8603a2b | 986 | { |
987 | // | |
988 | // Synaptic connection | |
989 | // Multiplies input times synaptic weight | |
990 | // | |
ceda081b | 991 | return (Neuron0x93bcd70()*-0.38099); |
c8603a2b | 992 | } |
993 | ||
ceda081b | 994 | Double_t AliCaloNeuralFit::Synapse0x93be848() const |
c8603a2b | 995 | { |
996 | // | |
997 | // Synaptic connection | |
998 | // Multiplies input times synaptic weight | |
999 | // | |
ceda081b | 1000 | return (Neuron0x93bd030()*0.351755); |
c8603a2b | 1001 | } |
1002 | ||
ceda081b | 1003 | Double_t AliCaloNeuralFit::Synapse0x93be870() const |
c8603a2b | 1004 | { |
1005 | // | |
1006 | // Synaptic connection | |
1007 | // Multiplies input times synaptic weight | |
1008 | // | |
ceda081b | 1009 | return (Neuron0x93bd378()*0.106307); |
c8603a2b | 1010 | } |
1011 | ||
ceda081b | 1012 | Double_t AliCaloNeuralFit::Synapse0x934a7c8() const |
c8603a2b | 1013 | { |
1014 | // | |
1015 | // Synaptic connection | |
1016 | // Multiplies input times synaptic weight | |
1017 | // | |
ceda081b | 1018 | return (Neuron0x93bd5f0()*0.118656); |
c8603a2b | 1019 | } |
1020 | ||
ceda081b | 1021 | Double_t AliCaloNeuralFit::Synapse0x93605e0() const |
c8603a2b | 1022 | { |
1023 | // | |
1024 | // Synaptic connection | |
1025 | // Multiplies input times synaptic weight | |
1026 | // | |
ceda081b | 1027 | return (Neuron0x93bd8b0()*-0.447119); |
c8603a2b | 1028 | } |
1029 | ||
ceda081b | 1030 | Double_t AliCaloNeuralFit::Synapse0x9360608() const |
c8603a2b | 1031 | { |
1032 | // | |
1033 | // Synaptic connection | |
1034 | // Multiplies input times synaptic weight | |
1035 | // | |
ceda081b | 1036 | return (Neuron0x93bdc28()*0.677259); |
c8603a2b | 1037 | } |
1038 | ||
ceda081b | 1039 | Double_t AliCaloNeuralFit::Synapse0x8ce6fe8() const |
c8603a2b | 1040 | { |
1041 | // | |
1042 | // Synaptic connection | |
1043 | // Multiplies input times synaptic weight | |
1044 | // | |
ceda081b | 1045 | return (Neuron0x93bdee8()*-0.246138); |
c8603a2b | 1046 | } |
1047 | ||
ceda081b | 1048 | Double_t AliCaloNeuralFit::Synapse0x8ce7010() const |
c8603a2b | 1049 | { |
1050 | // | |
1051 | // Synaptic connection | |
1052 | // Multiplies input times synaptic weight | |
1053 | // | |
ceda081b | 1054 | return (Neuron0x93be1a8()*-0.117442); |
c8603a2b | 1055 | } |