├── FINALM_1.pdf ├── LICENSE ├── QFERNv4.py ├── README.md ├── barabassialbertmodel.py ├── classicaltoquantumbehavior.py ├── diffusion.py ├── epidemicmodel.py ├── firefly-kuramoto-v2.py ├── net-kuramoto.py ├── netsyncanalysis.py ├── netsyncanalysisQuantumDAGmodel.py ├── netsyncanalysisv2eigen.py ├── netsyncanalysisv2eigenwigner.py ├── perioddoublingbifurcation.py ├── pycxsimulator.py ├── qoppav2.py ├── qoppav4.py ├── scalefreequantum.py └── votermodel.py /FINALM_1.pdf: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/MuonRay/QuantumNetworkSimulations/8c03a05a936b98102667e2ce7f5829229e7516cf/FINALM_1.pdf -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | GNU GENERAL PUBLIC LICENSE 2 | Version 3, 29 June 2007 3 | 4 | Copyright (C) 2007 Free Software Foundation, Inc. 5 | Everyone is permitted to copy and distribute verbatim copies 6 | of this license document, but changing it is not allowed. 7 | 8 | Preamble 9 | 10 | The GNU General Public License is a free, copyleft license for 11 | software and other kinds of works. 12 | 13 | The licenses for most software and other practical works are designed 14 | to take away your freedom to share and change the works. By contrast, 15 | the GNU General Public License is intended to guarantee your freedom to 16 | share and change all versions of a program--to make sure it remains free 17 | software for all its users. We, the Free Software Foundation, use the 18 | GNU General Public License for most of our software; it applies also to 19 | any other work released this way by its authors. You can apply it to 20 | your programs, too. 21 | 22 | When we speak of free software, we are referring to freedom, not 23 | price. Our General Public Licenses are designed to make sure that you 24 | have the freedom to distribute copies of free software (and charge for 25 | them if you wish), that you receive source code or can get it if you 26 | want it, that you can change the software or use pieces of it in new 27 | free programs, and that you know you can do these things. 28 | 29 | To protect your rights, we need to prevent others from denying you 30 | these rights or asking you to surrender the rights. Therefore, you have 31 | certain responsibilities if you distribute copies of the software, or if 32 | you modify it: responsibilities to respect the freedom of others. 33 | 34 | For example, if you distribute copies of such a program, whether 35 | gratis or for a fee, you must pass on to the recipients the same 36 | freedoms that you received. You must make sure that they, too, receive 37 | or can get the source code. And you must show them these terms so they 38 | know their rights. 39 | 40 | Developers that use the GNU GPL protect your rights with two steps: 41 | (1) assert copyright on the software, and (2) offer you this License 42 | giving you legal permission to copy, distribute and/or modify it. 43 | 44 | For the developers' and authors' protection, the GPL clearly explains 45 | that there is no warranty for this free software. For both users' and 46 | authors' sake, the GPL requires that modified versions be marked as 47 | changed, so that their problems will not be attributed erroneously to 48 | authors of previous versions. 49 | 50 | Some devices are designed to deny users access to install or run 51 | modified versions of the software inside them, although the manufacturer 52 | can do so. This is fundamentally incompatible with the aim of 53 | protecting users' freedom to change the software. The systematic 54 | pattern of such abuse occurs in the area of products for individuals to 55 | use, which is precisely where it is most unacceptable. Therefore, we 56 | have designed this version of the GPL to prohibit the practice for those 57 | products. If such problems arise substantially in other domains, we 58 | stand ready to extend this provision to those domains in future versions 59 | of the GPL, as needed to protect the freedom of users. 60 | 61 | Finally, every program is threatened constantly by software patents. 62 | States should not allow patents to restrict development and use of 63 | software on general-purpose computers, but in those that do, we wish to 64 | avoid the special danger that patents applied to a free program could 65 | make it effectively proprietary. To prevent this, the GPL assures that 66 | patents cannot be used to render the program non-free. 67 | 68 | The precise terms and conditions for copying, distribution and 69 | modification follow. 70 | 71 | TERMS AND CONDITIONS 72 | 73 | 0. Definitions. 74 | 75 | "This License" refers to version 3 of the GNU General Public License. 76 | 77 | "Copyright" also means copyright-like laws that apply to other kinds of 78 | works, such as semiconductor masks. 79 | 80 | "The Program" refers to any copyrightable work licensed under this 81 | License. Each licensee is addressed as "you". "Licensees" and 82 | "recipients" may be individuals or organizations. 83 | 84 | To "modify" a work means to copy from or adapt all or part of the work 85 | in a fashion requiring copyright permission, other than the making of an 86 | exact copy. The resulting work is called a "modified version" of the 87 | earlier work or a work "based on" the earlier work. 88 | 89 | A "covered work" means either the unmodified Program or a work based 90 | on the Program. 91 | 92 | To "propagate" a work means to do anything with it that, without 93 | permission, would make you directly or secondarily liable for 94 | infringement under applicable copyright law, except executing it on a 95 | computer or modifying a private copy. Propagation includes copying, 96 | distribution (with or without modification), making available to the 97 | public, and in some countries other activities as well. 98 | 99 | To "convey" a work means any kind of propagation that enables other 100 | parties to make or receive copies. Mere interaction with a user through 101 | a computer network, with no transfer of a copy, is not conveying. 102 | 103 | An interactive user interface displays "Appropriate Legal Notices" 104 | to the extent that it includes a convenient and prominently visible 105 | feature that (1) displays an appropriate copyright notice, and (2) 106 | tells the user that there is no warranty for the work (except to the 107 | extent that warranties are provided), that licensees may convey the 108 | work under this License, and how to view a copy of this License. If 109 | the interface presents a list of user commands or options, such as a 110 | menu, a prominent item in the list meets this criterion. 111 | 112 | 1. Source Code. 113 | 114 | The "source code" for a work means the preferred form of the work 115 | for making modifications to it. "Object code" means any non-source 116 | form of a work. 117 | 118 | A "Standard Interface" means an interface that either is an official 119 | standard defined by a recognized standards body, or, in the case of 120 | interfaces specified for a particular programming language, one that 121 | is widely used among developers working in that language. 122 | 123 | The "System Libraries" of an executable work include anything, other 124 | than the work as a whole, that (a) is included in the normal form of 125 | packaging a Major Component, but which is not part of that Major 126 | Component, and (b) serves only to enable use of the work with that 127 | Major Component, or to implement a Standard Interface for which an 128 | implementation is available to the public in source code form. A 129 | "Major Component", in this context, means a major essential component 130 | (kernel, window system, and so on) of the specific operating system 131 | (if any) on which the executable work runs, or a compiler used to 132 | produce the work, or an object code interpreter used to run it. 133 | 134 | The "Corresponding Source" for a work in object code form means all 135 | the source code needed to generate, install, and (for an executable 136 | work) run the object code and to modify the work, including scripts to 137 | control those activities. However, it does not include the work's 138 | System Libraries, or general-purpose tools or generally available free 139 | programs which are used unmodified in performing those activities but 140 | which are not part of the work. For example, Corresponding Source 141 | includes interface definition files associated with source files for 142 | the work, and the source code for shared libraries and dynamically 143 | linked subprograms that the work is specifically designed to require, 144 | such as by intimate data communication or control flow between those 145 | subprograms and other parts of the work. 146 | 147 | The Corresponding Source need not include anything that users 148 | can regenerate automatically from other parts of the Corresponding 149 | Source. 150 | 151 | The Corresponding Source for a work in source code form is that 152 | same work. 153 | 154 | 2. Basic Permissions. 155 | 156 | All rights granted under this License are granted for the term of 157 | copyright on the Program, and are irrevocable provided the stated 158 | conditions are met. This License explicitly affirms your unlimited 159 | permission to run the unmodified Program. The output from running a 160 | covered work is covered by this License only if the output, given its 161 | content, constitutes a covered work. This License acknowledges your 162 | rights of fair use or other equivalent, as provided by copyright law. 163 | 164 | You may make, run and propagate covered works that you do not 165 | convey, without conditions so long as your license otherwise remains 166 | in force. You may convey covered works to others for the sole purpose 167 | of having them make modifications exclusively for you, or provide you 168 | with facilities for running those works, provided that you comply with 169 | the terms of this License in conveying all material for which you do 170 | not control copyright. Those thus making or running the covered works 171 | for you must do so exclusively on your behalf, under your direction 172 | and control, on terms that prohibit them from making any copies of 173 | your copyrighted material outside their relationship with you. 174 | 175 | Conveying under any other circumstances is permitted solely under 176 | the conditions stated below. Sublicensing is not allowed; section 10 177 | makes it unnecessary. 178 | 179 | 3. Protecting Users' Legal Rights From Anti-Circumvention Law. 180 | 181 | No covered work shall be deemed part of an effective technological 182 | measure under any applicable law fulfilling obligations under article 183 | 11 of the WIPO copyright treaty adopted on 20 December 1996, or 184 | similar laws prohibiting or restricting circumvention of such 185 | measures. 186 | 187 | When you convey a covered work, you waive any legal power to forbid 188 | circumvention of technological measures to the extent such circumvention 189 | is effected by exercising rights under this License with respect to 190 | the covered work, and you disclaim any intention to limit operation or 191 | modification of the work as a means of enforcing, against the work's 192 | users, your or third parties' legal rights to forbid circumvention of 193 | technological measures. 194 | 195 | 4. Conveying Verbatim Copies. 196 | 197 | You may convey verbatim copies of the Program's source code as you 198 | receive it, in any medium, provided that you conspicuously and 199 | appropriately publish on each copy an appropriate copyright notice; 200 | keep intact all notices stating that this License and any 201 | non-permissive terms added in accord with section 7 apply to the code; 202 | keep intact all notices of the absence of any warranty; and give all 203 | recipients a copy of this License along with the Program. 204 | 205 | You may charge any price or no price for each copy that you convey, 206 | and you may offer support or warranty protection for a fee. 207 | 208 | 5. Conveying Modified Source Versions. 209 | 210 | You may convey a work based on the Program, or the modifications to 211 | produce it from the Program, in the form of source code under the 212 | terms of section 4, provided that you also meet all of these conditions: 213 | 214 | a) The work must carry prominent notices stating that you modified 215 | it, and giving a relevant date. 216 | 217 | b) The work must carry prominent notices stating that it is 218 | released under this License and any conditions added under section 219 | 7. This requirement modifies the requirement in section 4 to 220 | "keep intact all notices". 221 | 222 | c) You must license the entire work, as a whole, under this 223 | License to anyone who comes into possession of a copy. This 224 | License will therefore apply, along with any applicable section 7 225 | additional terms, to the whole of the work, and all its parts, 226 | regardless of how they are packaged. This License gives no 227 | permission to license the work in any other way, but it does not 228 | invalidate such permission if you have separately received it. 229 | 230 | d) If the work has interactive user interfaces, each must display 231 | Appropriate Legal Notices; however, if the Program has interactive 232 | interfaces that do not display Appropriate Legal Notices, your 233 | work need not make them do so. 234 | 235 | A compilation of a covered work with other separate and independent 236 | works, which are not by their nature extensions of the covered work, 237 | and which are not combined with it such as to form a larger program, 238 | in or on a volume of a storage or distribution medium, is called an 239 | "aggregate" if the compilation and its resulting copyright are not 240 | used to limit the access or legal rights of the compilation's users 241 | beyond what the individual works permit. Inclusion of a covered work 242 | in an aggregate does not cause this License to apply to the other 243 | parts of the aggregate. 244 | 245 | 6. Conveying Non-Source Forms. 246 | 247 | You may convey a covered work in object code form under the terms 248 | of sections 4 and 5, provided that you also convey the 249 | machine-readable Corresponding Source under the terms of this License, 250 | in one of these ways: 251 | 252 | a) Convey the object code in, or embodied in, a physical product 253 | (including a physical distribution medium), accompanied by the 254 | Corresponding Source fixed on a durable physical medium 255 | customarily used for software interchange. 256 | 257 | b) Convey the object code in, or embodied in, a physical product 258 | (including a physical distribution medium), accompanied by a 259 | written offer, valid for at least three years and valid for as 260 | long as you offer spare parts or customer support for that product 261 | model, to give anyone who possesses the object code either (1) a 262 | copy of the Corresponding Source for all the software in the 263 | product that is covered by this License, on a durable physical 264 | medium customarily used for software interchange, for a price no 265 | more than your reasonable cost of physically performing this 266 | conveying of source, or (2) access to copy the 267 | Corresponding Source from a network server at no charge. 268 | 269 | c) Convey individual copies of the object code with a copy of the 270 | written offer to provide the Corresponding Source. This 271 | alternative is allowed only occasionally and noncommercially, and 272 | only if you received the object code with such an offer, in accord 273 | with subsection 6b. 274 | 275 | d) Convey the object code by offering access from a designated 276 | place (gratis or for a charge), and offer equivalent access to the 277 | Corresponding Source in the same way through the same place at no 278 | further charge. You need not require recipients to copy the 279 | Corresponding Source along with the object code. If the place to 280 | copy the object code is a network server, the Corresponding Source 281 | may be on a different server (operated by you or a third party) 282 | that supports equivalent copying facilities, provided you maintain 283 | clear directions next to the object code saying where to find the 284 | Corresponding Source. Regardless of what server hosts the 285 | Corresponding Source, you remain obligated to ensure that it is 286 | available for as long as needed to satisfy these requirements. 287 | 288 | e) Convey the object code using peer-to-peer transmission, provided 289 | you inform other peers where the object code and Corresponding 290 | Source of the work are being offered to the general public at no 291 | charge under subsection 6d. 292 | 293 | A separable portion of the object code, whose source code is excluded 294 | from the Corresponding Source as a System Library, need not be 295 | included in conveying the object code work. 296 | 297 | A "User Product" is either (1) a "consumer product", which means any 298 | tangible personal property which is normally used for personal, family, 299 | or household purposes, or (2) anything designed or sold for incorporation 300 | into a dwelling. In determining whether a product is a consumer product, 301 | doubtful cases shall be resolved in favor of coverage. For a particular 302 | product received by a particular user, "normally used" refers to a 303 | typical or common use of that class of product, regardless of the status 304 | of the particular user or of the way in which the particular user 305 | actually uses, or expects or is expected to use, the product. A product 306 | is a consumer product regardless of whether the product has substantial 307 | commercial, industrial or non-consumer uses, unless such uses represent 308 | the only significant mode of use of the product. 309 | 310 | "Installation Information" for a User Product means any methods, 311 | procedures, authorization keys, or other information required to install 312 | and execute modified versions of a covered work in that User Product from 313 | a modified version of its Corresponding Source. The information must 314 | suffice to ensure that the continued functioning of the modified object 315 | code is in no case prevented or interfered with solely because 316 | modification has been made. 317 | 318 | If you convey an object code work under this section in, or with, or 319 | specifically for use in, a User Product, and the conveying occurs as 320 | part of a transaction in which the right of possession and use of the 321 | User Product is transferred to the recipient in perpetuity or for a 322 | fixed term (regardless of how the transaction is characterized), the 323 | Corresponding Source conveyed under this section must be accompanied 324 | by the Installation Information. But this requirement does not apply 325 | if neither you nor any third party retains the ability to install 326 | modified object code on the User Product (for example, the work has 327 | been installed in ROM). 328 | 329 | The requirement to provide Installation Information does not include a 330 | requirement to continue to provide support service, warranty, or updates 331 | for a work that has been modified or installed by the recipient, or for 332 | the User Product in which it has been modified or installed. Access to a 333 | network may be denied when the modification itself materially and 334 | adversely affects the operation of the network or violates the rules and 335 | protocols for communication across the network. 336 | 337 | Corresponding Source conveyed, and Installation Information provided, 338 | in accord with this section must be in a format that is publicly 339 | documented (and with an implementation available to the public in 340 | source code form), and must require no special password or key for 341 | unpacking, reading or copying. 342 | 343 | 7. Additional Terms. 344 | 345 | "Additional permissions" are terms that supplement the terms of this 346 | License by making exceptions from one or more of its conditions. 347 | Additional permissions that are applicable to the entire Program shall 348 | be treated as though they were included in this License, to the extent 349 | that they are valid under applicable law. If additional permissions 350 | apply only to part of the Program, that part may be used separately 351 | under those permissions, but the entire Program remains governed by 352 | this License without regard to the additional permissions. 353 | 354 | When you convey a copy of a covered work, you may at your option 355 | remove any additional permissions from that copy, or from any part of 356 | it. (Additional permissions may be written to require their own 357 | removal in certain cases when you modify the work.) You may place 358 | additional permissions on material, added by you to a covered work, 359 | for which you have or can give appropriate copyright permission. 360 | 361 | Notwithstanding any other provision of this License, for material you 362 | add to a covered work, you may (if authorized by the copyright holders of 363 | that material) supplement the terms of this License with terms: 364 | 365 | a) Disclaiming warranty or limiting liability differently from the 366 | terms of sections 15 and 16 of this License; or 367 | 368 | b) Requiring preservation of specified reasonable legal notices or 369 | author attributions in that material or in the Appropriate Legal 370 | Notices displayed by works containing it; or 371 | 372 | c) Prohibiting misrepresentation of the origin of that material, or 373 | requiring that modified versions of such material be marked in 374 | reasonable ways as different from the original version; or 375 | 376 | d) Limiting the use for publicity purposes of names of licensors or 377 | authors of the material; or 378 | 379 | e) Declining to grant rights under trademark law for use of some 380 | trade names, trademarks, or service marks; or 381 | 382 | f) Requiring indemnification of licensors and authors of that 383 | material by anyone who conveys the material (or modified versions of 384 | it) with contractual assumptions of liability to the recipient, for 385 | any liability that these contractual assumptions directly impose on 386 | those licensors and authors. 387 | 388 | All other non-permissive additional terms are considered "further 389 | restrictions" within the meaning of section 10. If the Program as you 390 | received it, or any part of it, contains a notice stating that it is 391 | governed by this License along with a term that is a further 392 | restriction, you may remove that term. If a license document contains 393 | a further restriction but permits relicensing or conveying under this 394 | License, you may add to a covered work material governed by the terms 395 | of that license document, provided that the further restriction does 396 | not survive such relicensing or conveying. 397 | 398 | If you add terms to a covered work in accord with this section, you 399 | must place, in the relevant source files, a statement of the 400 | additional terms that apply to those files, or a notice indicating 401 | where to find the applicable terms. 402 | 403 | Additional terms, permissive or non-permissive, may be stated in the 404 | form of a separately written license, or stated as exceptions; 405 | the above requirements apply either way. 406 | 407 | 8. Termination. 408 | 409 | You may not propagate or modify a covered work except as expressly 410 | provided under this License. Any attempt otherwise to propagate or 411 | modify it is void, and will automatically terminate your rights under 412 | this License (including any patent licenses granted under the third 413 | paragraph of section 11). 414 | 415 | However, if you cease all violation of this License, then your 416 | license from a particular copyright holder is reinstated (a) 417 | provisionally, unless and until the copyright holder explicitly and 418 | finally terminates your license, and (b) permanently, if the copyright 419 | holder fails to notify you of the violation by some reasonable means 420 | prior to 60 days after the cessation. 421 | 422 | Moreover, your license from a particular copyright holder is 423 | reinstated permanently if the copyright holder notifies you of the 424 | violation by some reasonable means, this is the first time you have 425 | received notice of violation of this License (for any work) from that 426 | copyright holder, and you cure the violation prior to 30 days after 427 | your receipt of the notice. 428 | 429 | Termination of your rights under this section does not terminate the 430 | licenses of parties who have received copies or rights from you under 431 | this License. If your rights have been terminated and not permanently 432 | reinstated, you do not qualify to receive new licenses for the same 433 | material under section 10. 434 | 435 | 9. Acceptance Not Required for Having Copies. 436 | 437 | You are not required to accept this License in order to receive or 438 | run a copy of the Program. Ancillary propagation of a covered work 439 | occurring solely as a consequence of using peer-to-peer transmission 440 | to receive a copy likewise does not require acceptance. However, 441 | nothing other than this License grants you permission to propagate or 442 | modify any covered work. These actions infringe copyright if you do 443 | not accept this License. Therefore, by modifying or propagating a 444 | covered work, you indicate your acceptance of this License to do so. 445 | 446 | 10. Automatic Licensing of Downstream Recipients. 447 | 448 | Each time you convey a covered work, the recipient automatically 449 | receives a license from the original licensors, to run, modify and 450 | propagate that work, subject to this License. You are not responsible 451 | for enforcing compliance by third parties with this License. 452 | 453 | An "entity transaction" is a transaction transferring control of an 454 | organization, or substantially all assets of one, or subdividing an 455 | organization, or merging organizations. If propagation of a covered 456 | work results from an entity transaction, each party to that 457 | transaction who receives a copy of the work also receives whatever 458 | licenses to the work the party's predecessor in interest had or could 459 | give under the previous paragraph, plus a right to possession of the 460 | Corresponding Source of the work from the predecessor in interest, if 461 | the predecessor has it or can get it with reasonable efforts. 462 | 463 | You may not impose any further restrictions on the exercise of the 464 | rights granted or affirmed under this License. For example, you may 465 | not impose a license fee, royalty, or other charge for exercise of 466 | rights granted under this License, and you may not initiate litigation 467 | (including a cross-claim or counterclaim in a lawsuit) alleging that 468 | any patent claim is infringed by making, using, selling, offering for 469 | sale, or importing the Program or any portion of it. 470 | 471 | 11. Patents. 472 | 473 | A "contributor" is a copyright holder who authorizes use under this 474 | License of the Program or a work on which the Program is based. The 475 | work thus licensed is called the contributor's "contributor version". 476 | 477 | A contributor's "essential patent claims" are all patent claims 478 | owned or controlled by the contributor, whether already acquired or 479 | hereafter acquired, that would be infringed by some manner, permitted 480 | by this License, of making, using, or selling its contributor version, 481 | but do not include claims that would be infringed only as a 482 | consequence of further modification of the contributor version. For 483 | purposes of this definition, "control" includes the right to grant 484 | patent sublicenses in a manner consistent with the requirements of 485 | this License. 486 | 487 | Each contributor grants you a non-exclusive, worldwide, royalty-free 488 | patent license under the contributor's essential patent claims, to 489 | make, use, sell, offer for sale, import and otherwise run, modify and 490 | propagate the contents of its contributor version. 491 | 492 | In the following three paragraphs, a "patent license" is any express 493 | agreement or commitment, however denominated, not to enforce a patent 494 | (such as an express permission to practice a patent or covenant not to 495 | sue for patent infringement). To "grant" such a patent license to a 496 | party means to make such an agreement or commitment not to enforce a 497 | patent against the party. 498 | 499 | If you convey a covered work, knowingly relying on a patent license, 500 | and the Corresponding Source of the work is not available for anyone 501 | to copy, free of charge and under the terms of this License, through a 502 | publicly available network server or other readily accessible means, 503 | then you must either (1) cause the Corresponding Source to be so 504 | available, or (2) arrange to deprive yourself of the benefit of the 505 | patent license for this particular work, or (3) arrange, in a manner 506 | consistent with the requirements of this License, to extend the patent 507 | license to downstream recipients. "Knowingly relying" means you have 508 | actual knowledge that, but for the patent license, your conveying the 509 | covered work in a country, or your recipient's use of the covered work 510 | in a country, would infringe one or more identifiable patents in that 511 | country that you have reason to believe are valid. 512 | 513 | If, pursuant to or in connection with a single transaction or 514 | arrangement, you convey, or propagate by procuring conveyance of, a 515 | covered work, and grant a patent license to some of the parties 516 | receiving the covered work authorizing them to use, propagate, modify 517 | or convey a specific copy of the covered work, then the patent license 518 | you grant is automatically extended to all recipients of the covered 519 | work and works based on it. 520 | 521 | A patent license is "discriminatory" if it does not include within 522 | the scope of its coverage, prohibits the exercise of, or is 523 | conditioned on the non-exercise of one or more of the rights that are 524 | specifically granted under this License. You may not convey a covered 525 | work if you are a party to an arrangement with a third party that is 526 | in the business of distributing software, under which you make payment 527 | to the third party based on the extent of your activity of conveying 528 | the work, and under which the third party grants, to any of the 529 | parties who would receive the covered work from you, a discriminatory 530 | patent license (a) in connection with copies of the covered work 531 | conveyed by you (or copies made from those copies), or (b) primarily 532 | for and in connection with specific products or compilations that 533 | contain the covered work, unless you entered into that arrangement, 534 | or that patent license was granted, prior to 28 March 2007. 535 | 536 | Nothing in this License shall be construed as excluding or limiting 537 | any implied license or other defenses to infringement that may 538 | otherwise be available to you under applicable patent law. 539 | 540 | 12. No Surrender of Others' Freedom. 541 | 542 | If conditions are imposed on you (whether by court order, agreement or 543 | otherwise) that contradict the conditions of this License, they do not 544 | excuse you from the conditions of this License. If you cannot convey a 545 | covered work so as to satisfy simultaneously your obligations under this 546 | License and any other pertinent obligations, then as a consequence you may 547 | not convey it at all. For example, if you agree to terms that obligate you 548 | to collect a royalty for further conveying from those to whom you convey 549 | the Program, the only way you could satisfy both those terms and this 550 | License would be to refrain entirely from conveying the Program. 551 | 552 | 13. Use with the GNU Affero General Public License. 553 | 554 | Notwithstanding any other provision of this License, you have 555 | permission to link or combine any covered work with a work licensed 556 | under version 3 of the GNU Affero General Public License into a single 557 | combined work, and to convey the resulting work. The terms of this 558 | License will continue to apply to the part which is the covered work, 559 | but the special requirements of the GNU Affero General Public License, 560 | section 13, concerning interaction through a network will apply to the 561 | combination as such. 562 | 563 | 14. Revised Versions of this License. 564 | 565 | The Free Software Foundation may publish revised and/or new versions of 566 | the GNU General Public License from time to time. Such new versions will 567 | be similar in spirit to the present version, but may differ in detail to 568 | address new problems or concerns. 569 | 570 | Each version is given a distinguishing version number. If the 571 | Program specifies that a certain numbered version of the GNU General 572 | Public License "or any later version" applies to it, you have the 573 | option of following the terms and conditions either of that numbered 574 | version or of any later version published by the Free Software 575 | Foundation. If the Program does not specify a version number of the 576 | GNU General Public License, you may choose any version ever published 577 | by the Free Software Foundation. 578 | 579 | If the Program specifies that a proxy can decide which future 580 | versions of the GNU General Public License can be used, that proxy's 581 | public statement of acceptance of a version permanently authorizes you 582 | to choose that version for the Program. 583 | 584 | Later license versions may give you additional or different 585 | permissions. However, no additional obligations are imposed on any 586 | author or copyright holder as a result of your choosing to follow a 587 | later version. 588 | 589 | 15. Disclaimer of Warranty. 590 | 591 | THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY 592 | APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT 593 | HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY 594 | OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO, 595 | THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR 596 | PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM 597 | IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF 598 | ALL NECESSARY SERVICING, REPAIR OR CORRECTION. 599 | 600 | 16. Limitation of Liability. 601 | 602 | IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING 603 | WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS 604 | THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY 605 | GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE 606 | USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF 607 | DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD 608 | PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS), 609 | EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF 610 | SUCH DAMAGES. 611 | 612 | 17. Interpretation of Sections 15 and 16. 613 | 614 | If the disclaimer of warranty and limitation of liability provided 615 | above cannot be given local legal effect according to their terms, 616 | reviewing courts shall apply local law that most closely approximates 617 | an absolute waiver of all civil liability in connection with the 618 | Program, unless a warranty or assumption of liability accompanies a 619 | copy of the Program in return for a fee. 620 | 621 | END OF TERMS AND CONDITIONS 622 | 623 | How to Apply These Terms to Your New Programs 624 | 625 | If you develop a new program, and you want it to be of the greatest 626 | possible use to the public, the best way to achieve this is to make it 627 | free software which everyone can redistribute and change under these terms. 628 | 629 | To do so, attach the following notices to the program. It is safest 630 | to attach them to the start of each source file to most effectively 631 | state the exclusion of warranty; and each file should have at least 632 | the "copyright" line and a pointer to where the full notice is found. 633 | 634 | 635 | Copyright (C) 636 | 637 | This program is free software: you can redistribute it and/or modify 638 | it under the terms of the GNU General Public License as published by 639 | the Free Software Foundation, either version 3 of the License, or 640 | (at your option) any later version. 641 | 642 | This program is distributed in the hope that it will be useful, 643 | but WITHOUT ANY WARRANTY; without even the implied warranty of 644 | MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the 645 | GNU General Public License for more details. 646 | 647 | You should have received a copy of the GNU General Public License 648 | along with this program. If not, see . 649 | 650 | Also add information on how to contact you by electronic and paper mail. 651 | 652 | If the program does terminal interaction, make it output a short 653 | notice like this when it starts in an interactive mode: 654 | 655 | Copyright (C) 656 | This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'. 657 | This is free software, and you are welcome to redistribute it 658 | under certain conditions; type `show c' for details. 659 | 660 | The hypothetical commands `show w' and `show c' should show the appropriate 661 | parts of the General Public License. Of course, your program's commands 662 | might be different; for a GUI interface, you would use an "about box". 663 | 664 | You should also get your employer (if you work as a programmer) or school, 665 | if any, to sign a "copyright disclaimer" for the program, if necessary. 666 | For more information on this, and how to apply and follow the GNU GPL, see 667 | . 668 | 669 | The GNU General Public License does not permit incorporating your program 670 | into proprietary programs. If your program is a subroutine library, you 671 | may consider it more useful to permit linking proprietary applications with 672 | the library. If this is what you want to do, use the GNU Lesser General 673 | Public License instead of this License. But first, please read 674 | . 675 | -------------------------------------------------------------------------------- /QFERNv4.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Sat Jan 18 19:59:18 2025 4 | 5 | @author: ektop 6 | """ 7 | 8 | # -*- coding: utf-8 -*- 9 | """ 10 | Created on Wed Sep 25 18:26:44 2024 11 | 12 | @author: ektop 13 | """ 14 | 15 | import numpy as np 16 | import matplotlib.pyplot as plt 17 | import networkx as nx 18 | import random 19 | from itertools import combinations 20 | 21 | # Define the number of nodes in each component 22 | NUM_NODES_A = 10 # Number of nodes in group A 23 | NUM_NODES_B = 10 # Number of nodes in group B 24 | 25 | # Create a structured directed acyclic graph (DAG) 26 | dag = nx.DiGraph() 27 | 28 | def create_random_bipartite_structure(num_nodes_a, num_nodes_b): 29 | """Create a random bipartite-like structure.""" 30 | edges = [(i, num_nodes_a + j) for i in range(num_nodes_a) for j in range(num_nodes_b)] 31 | random.shuffle(edges) 32 | selected_edges = random.sample(edges, k=random.randint(1, len(edges))) 33 | return selected_edges 34 | 35 | # Add random edges to the graph 36 | dag.add_edges_from(create_random_bipartite_structure(NUM_NODES_A, NUM_NODES_B)) 37 | dag.add_edges_from(create_random_bipartite_structure(NUM_NODES_A, NUM_NODES_B)) 38 | 39 | # Generate connections between the nodes 40 | component_connections = [] 41 | connections_from_first_to_second = random.sample( 42 | [(i, NUM_NODES_A + j) for i in range(NUM_NODES_A) for j in range(NUM_NODES_B)], 43 | k=random.randint(1, 2)) 44 | component_connections.extend(connections_from_first_to_second) 45 | 46 | # Create additional connections for the second section of nodes 47 | second_section_nodes = list(range(NUM_NODES_A, NUM_NODES_A + NUM_NODES_B)) 48 | new_node = NUM_NODES_A + NUM_NODES_B 49 | for node in second_section_nodes: 50 | additional_connections = random.sample([new_node] + second_section_nodes, 51 | k=random.randint(1, len(second_section_nodes))) 52 | component_connections += [(node, conn) for conn in additional_connections if conn != node] 53 | 54 | dag.add_edges_from(component_connections) 55 | 56 | def compute_cheeger_constant(G): 57 | """Calculate the Cheeger constant of the graph.""" 58 | n = len(G.nodes) 59 | cuts = [] 60 | for cut_nodes in combinations(range(n), n // 2): 61 | cut_size = len([edge for edge in G.edges if (edge[0] in cut_nodes) ^ (edge[1] in cut_nodes)]) 62 | cuts.append(cut_size) 63 | return min(cuts) / min(sum(1 for node in cut_nodes), sum(1 for node in G.nodes if node not in cut_nodes)) 64 | 65 | # Calculate the initial Cheeger constant 66 | initial_cheeger_constant = compute_cheeger_constant(dag) 67 | print(f"Initial Cheeger Constant: {initial_cheeger_constant}") 68 | 69 | def laplacian_matrix(A): 70 | """Compute the normalized Laplacian matrix.""" 71 | D = np.diag(np.sum(A, axis=1)) 72 | return D - A 73 | 74 | def effective_resistance(u, v, eigenvalues, fiedler_vector): 75 | """Calculate the effective resistance between two nodes.""" 76 | if len(eigenvalues) == 0 or len(fiedler_vector) == 0: 77 | return np.inf 78 | sum_term = 0 79 | for i in range(len(eigenvalues)): 80 | if eigenvalues[i] > 0: 81 | sum_term += (fiedler_vector[u] * fiedler_vector[v]) / eigenvalues[i] 82 | return sum_term 83 | 84 | def optimize_graph(g, iterations=100): 85 | """Optimize the graph to minimize effective resistance and maximize Cheeger constant.""" 86 | previous_cheeger_constant = compute_cheeger_constant(g) 87 | 88 | for _ in range(iterations): 89 | # Step 1: Remove a random edge 90 | if len(g.edges) > 0: 91 | edge = random.choice(list(g.edges)) 92 | g.remove_edge(*edge) 93 | 94 | # Step 2: Add a new random edge 95 | possible_edges = [(i, j) for i in range(len(g.nodes)) for j in range(len(g.nodes)) 96 | if i != j and not g.has_edge(i, j)] 97 | if possible_edges: 98 | new_edge = random.choice(possible_edges) 99 | g.add_edge(*new_edge) 100 | 101 | # Step 3: Calculate the new Cheeger constant 102 | new_cheeger_constant = compute_cheeger_constant(g) 103 | print(f"Current Cheeger Constant: {new_cheeger_constant}") 104 | 105 | # Check for convergence 106 | if new_cheeger_constant == previous_cheeger_constant: 107 | break 108 | 109 | previous_cheeger_constant = new_cheeger_constant 110 | 111 | # Run the optimization process 112 | optimize_graph(dag) 113 | 114 | # Final graph attributes and effective resistance calculation 115 | num_nodes = dag.number_of_nodes() 116 | adjacency = nx.to_numpy_array(dag) 117 | normalized_laplacian = laplacian_matrix(adjacency) 118 | 119 | # Eigenvalue decomposition for effective resistance calculation 120 | eigenvalues, eigenvectors = np.linalg.eig(normalized_laplacian) 121 | order = np.argsort(eigenvalues) 122 | fiedler_vector = np.real(eigenvectors[:, order[1]]) 123 | 124 | # Compute effective resistances for all node pairs 125 | effective_resistances = np.zeros((num_nodes, num_nodes)) 126 | for u, v in combinations(range(num_nodes), 2): 127 | effective_resistances[u, v] = effective_resistance(u, v, eigenvalues[order[1:]], fiedler_vector) 128 | effective_resistances[v, u] = effective_resistances[u, v] 129 | 130 | # Visualization of effective resistances 131 | plt.figure(figsize=(10, 8)) 132 | pos = nx.spring_layout(dag) # Positioning for the nodes 133 | node_color = [np.mean(effective_resistances[node]) for node in range(num_nodes)] 134 | 135 | # Draw the graph with effective resistances represented as colors 136 | nodes = nx.draw(dag, pos, node_color=node_color, with_labels=True, cmap=plt.cm.viridis, node_size=500) 137 | 138 | # Create the ScalarMappable for color representation 139 | sm = plt.cm.ScalarMappable(cmap=plt.cm.viridis) 140 | sm.set_array(node_color) 141 | 142 | # Add colorbar to the plot 143 | plt.colorbar(sm, label='Effective Resistance Level') 144 | plt.title('Graph Visualization of Effective Resistances') 145 | plt.show() 146 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | # QuantumNetworkSimulations 2 | A series of simulation codes used to emulate quantum-like networks in the simulation of emergent adaptive behavior, such as network synchronization, and relate the nature of the coupled harmonic oscillators with non-local behavior and chimera states in systems of quantum particles. A full showcase of this project is discussed in the following videos:https://www.youtube.com/watch?v=OqJP6EatbFo 3 | -------------------------------------------------------------------------------- /barabassialbertmodel.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Tue Mar 2 19:01:57 2021 4 | 5 | @author: cosmi 6 | """ 7 | 8 | import matplotlib 9 | matplotlib.use('TkAgg') 10 | from pylab import * 11 | import networkx as nx 12 | 13 | m0 = 5 # number of nodes in initial condition 14 | m = 2 # number of edges per new node 15 | 16 | def initialize(): 17 | global g, nextg, counter 18 | g = nx.complete_graph(m0) 19 | g.pos = nx.spring_layout(g) 20 | nextg = g.copy() 21 | 22 | 23 | xdata = [] 24 | ydata = [] 25 | 26 | def observe(): 27 | global g, nextg, counter 28 | subplot(1,2,1) 29 | cla() 30 | nx.draw(g) 31 | 32 | subplot(1,2,2) 33 | cla() 34 | plot(xdata, ydata,'o',alpha = 0.05) 35 | axis('image') 36 | # for percolation search 37 | 38 | 39 | def pref_select(nds): 40 | global g 41 | r = uniform(0, sum(g.degree(i) for i in nds)) 42 | x = 0 43 | for i in nds: 44 | x += g.degree(i) 45 | if r <= x: 46 | return i 47 | 48 | 49 | def update(): 50 | global g, nextg, counter 51 | counter += 1 52 | if counter % 20 == 0: 53 | nds = g.nodes() 54 | newcomer = max(nds) + 1 55 | 56 | for i in range(m): 57 | j = pref_select(nds) 58 | g.add_edge(newcomer, j) 59 | unsaturated_b = g.nodes() 60 | list(unsaturated_b).remove(j) 61 | 62 | xdata.append(g.degree(i)) 63 | ccs = nx.connected_components(g) 64 | ydata.append(max(len(cc) for cc in ccs)) 65 | #xdata.append(g.degree(i)); ydata.append(g.degree(j)) 66 | #xdata.append(g.degree(j)); ydata.append(g.degree(i)) 67 | #g.pos[newcomer] = (0, 0) # simulation of node movement 68 | g, nextg = nextg, g 69 | 70 | #g.pos = nx.spring_layout(pos = g.pos, iterations = 5) 71 | 72 | import pycxsimulator 73 | 74 | pycxsimulator.GUI().start(func=[initialize, observe, update]) 75 | 76 | 77 | -------------------------------------------------------------------------------- /classicaltoquantumbehavior.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Sat Feb 13 13:30:10 2021 4 | 5 | @author: cosmi 6 | """ 7 | 8 | 9 | import matplotlib 10 | matplotlib.use('TkAgg') 11 | from pylab import * 12 | import networkx as nx 13 | from math import pi 14 | import numpy as np 15 | 16 | import time # for steptime 17 | 18 | # for space vs time plotting (chimera search) 19 | 20 | import scipy 21 | import numpy as np 22 | from scipy import misc 23 | 24 | from matplotlib import pyplot as plt # For image viewing 25 | 26 | from matplotlib import colors 27 | from matplotlib import ticker 28 | from matplotlib.colors import LinearSegmentedColormap 29 | 30 | 31 | 32 | 33 | 34 | from random import random as rand 35 | from random import uniform 36 | 37 | def initialize(): 38 | global g, nextg, counter 39 | s = 5 40 | g = nx.grid_graph(dim=[s,s]) 41 | #nodes = list(G.nodes) 42 | #edges = list(G.edges) 43 | 44 | #g = nx.karate_club_graph() 45 | counter = 0 46 | for i in list(g.nodes()): 47 | g.node[i]['theta'] = 2 * pi * random() 48 | #rows, cols = (-0.05, 0.05) 49 | #arr = [[rand.randrange(10) for i in range(int(cols))] for j in range(int(rows))] 50 | #a = numpy.asarray(arr) 51 | #g.node[i]['omega'] = 1. + rand.uniform(-0.05, 0.05) 52 | g.node[i]['omega'] = 1. + uniform(-0.05, 0.05) 53 | nextg = g.copy() 54 | counter = +1 55 | 56 | def observe(): 57 | global g, nextg 58 | cla() 59 | nx.draw(g, cmap = cm.hsv, vmin = -1, vmax = 1, 60 | node_color = [np.sin(g.node[i]['theta']) for i in list(g.nodes())], 61 | pos = nx.spring_layout(g) ) 62 | 63 | 64 | alpha = 1 # coupling strength 65 | Dt = 0.01 # Delta t 66 | 67 | def update(): 68 | global g, nextg 69 | for i in list(g.nodes()): 70 | theta_i = g.node[i]['theta'] 71 | nextg.node[i]['theta'] = theta_i + (g.node[i]['omega'] + alpha * ( \ 72 | sum(np.sin(g.node[j]['theta'] - theta_i) for j in g.neighbors(i)) \ 73 | / g.degree(i))) * Dt 74 | g, nextg = nextg, g 75 | 76 | agents = theta_i 77 | """ 78 | environment 79 | """ 80 | 81 | # empty numpy array for environmental state 82 | plot_time_stamp = [] 83 | plot_agent = [] 84 | 85 | # save for figure 86 | plot_time_stamp.append(counter) 87 | plot_agent.append(agents) 88 | 89 | 90 | 91 | 92 | 93 | 94 | import pycxsimulator 95 | 96 | pycxsimulator.GUI().start(func=[initialize, observe, update]) 97 | 98 | 99 | plt.figure(1) 100 | #compare red and blue pixel data 101 | nbins = 20 102 | plt.hexbin(x=plot_time_stamp, y=plot_agent, gridsize=nbins, cmap=plt.cm.jet) 103 | plt.xlabel('Blue Reflectance') 104 | plt.ylabel('NIR Reflectance') 105 | # Add a title 106 | plt.title('NIR vs Blue Spectral Data') 107 | plt.show() 108 | -------------------------------------------------------------------------------- /diffusion.py: -------------------------------------------------------------------------------- 1 | 2 | import matplotlib 3 | matplotlib.use('TkAgg') 4 | from pylab import * 5 | import networkx as nx 6 | import random as rd 7 | 8 | def initialize(): 9 | global g, nextg 10 | g = nx.karate_club_graph() 11 | for i in g.nodes(): 12 | g.node[i]['state'] = 1 if random() < .5 else 0 13 | nextg = g.copy() 14 | 15 | 16 | 17 | def observe(): 18 | global g, nextg 19 | cla() 20 | nx.draw(g, cmap = cm.hsv, vmin = -1, vmax = 1, 21 | node_color = [g.node[i]['state'] for i in g.nodes()], 22 | pos = nx.spring_layout(g) ) 23 | 24 | alpha = 1 # coupling strength 25 | Dt = 0.01 # Delta t 26 | 27 | def update(): 28 | global g, nextg 29 | for i in list(g.nodes()): 30 | ci = g.node[i]['state'] 31 | nextg.node[i]['state'] = ci + alpha * ( \ 32 | np.sum(g.node[j]['state'] for j in g.neighbors(i)) \ 33 | -ci * g.degree(i)) * Dt 34 | g, nextg = nextg, g 35 | 36 | 37 | 38 | g.add_edge(0,1) 39 | g[0]['visited'] = True 40 | g.neighbors(0) 41 | ['visited', 1] 42 | 43 | 44 | import pycxsimulator 45 | 46 | pycxsimulator.GUI().start(func=[initialize, observe, update]) 47 | 48 | -------------------------------------------------------------------------------- /epidemicmodel.py: -------------------------------------------------------------------------------- 1 | # Epidemic model 2 | 3 | import matplotlib 4 | matplotlib.use('TkAgg') 5 | from pylab import * 6 | import networkx as nx 7 | import random as rd 8 | 9 | def initialize(): 10 | global g, nextg 11 | g = nx.karate_club_graph() 12 | for i in g.nodes(): 13 | g.node[i]['state'] = 1 if random() < .5 else 0 14 | nextg = g.copy() 15 | 16 | 17 | 18 | def observe(): 19 | global g, nextg 20 | cla() 21 | nx.draw(g, cmap = cm.hsv, vmin = -1, vmax = 1, 22 | node_color = [g.node[i]['state'] for i in g.nodes()], 23 | pos = nx.spring_layout(g) ) 24 | 25 | p_i = 0.5 # infection probability 26 | p_r = 0.5 # recovery probability 27 | 28 | def update(): 29 | global g, nextg 30 | a = rd.choice(g.nodes()) 31 | if g.node[a]['state'] == 0: # if susceptable to infection 32 | b = rd.choice(g.neighbors(a)) 33 | if g.node[b]['state'] == 1: # if neighbor b is infected 34 | g.node[a]['state'] = 1 if random() < p_i else 0 35 | 36 | else: # if infected 37 | g.node[a]['state'] = 1 if random() < p_r else 1 38 | 39 | 40 | 41 | 42 | 43 | #g.add_edge(0,1) 44 | #g[0]['visited'] = True 45 | #g.neighbors(0) 46 | #['visited', 1] 47 | 48 | 49 | import pycxsimulator 50 | 51 | pycxsimulator.GUI().start(func=[initialize, observe, update]) 52 | 53 | -------------------------------------------------------------------------------- /firefly-kuramoto-v2.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Sat Feb 13 13:30:10 2021 4 | 5 | @author: cosmi 6 | """ 7 | 8 | 9 | import matplotlib 10 | matplotlib.use('TkAgg') 11 | from pylab import * 12 | import networkx as nx 13 | from math import pi 14 | import numpy as np 15 | 16 | from random import random as rand 17 | from random import uniform 18 | 19 | def initialize(): 20 | global g, nextg 21 | g = nx.karate_club_graph() 22 | for i in list(g.nodes()): 23 | g.node[i]['theta'] = 2 * pi * random() 24 | #rows, cols = (-0.05, 0.05) 25 | #arr = [[rand.randrange(10) for i in range(int(cols))] for j in range(int(rows))] 26 | #a = numpy.asarray(arr) 27 | #g.node[i]['omega'] = 1. + rand.uniform(-0.05, 0.05) 28 | g.node[i]['omega'] = 1. + uniform(-0.05, 0.05) 29 | nextg = g.copy() 30 | 31 | def observe(): 32 | global g, nextg 33 | cla() 34 | nx.draw(g, cmap = cm.hsv, vmin = -1, vmax = 1, 35 | node_color = [np.sin(g.node[i]['theta']) for i in list(g.nodes())], 36 | pos = nx.spring_layout(g) ) 37 | 38 | fig = go.Figure(data=go.Scatter(x=plot_time_stamp, y=plot_agent, mode='markers', 39 | marker=dict(size=4.5, color="Blue", opacity=0.6))) 40 | fig.show() 41 | 42 | alpha = 1 # coupling strength 43 | Dt = 0.01 # Delta t 44 | 45 | def update(): 46 | global g, nextg 47 | for i in list(g.nodes()): 48 | theta_i = g.node[i]['theta'] 49 | nextg.node[i]['theta'] = theta_i + (g.node[i]['omega'] + alpha * ( \ 50 | np.sum(np.sin(g.node[j]['theta'] - theta_i) for j in g.neighbors(i)) \ 51 | / g.degree(i))) * Dt 52 | g, nextg = nextg, g 53 | 54 | 55 | import pycxsimulator 56 | 57 | pycxsimulator.GUI().start(func=[initialize, observe, update]) 58 | 59 | 60 | 61 | -------------------------------------------------------------------------------- /net-kuramoto.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Sat Feb 13 13:30:10 2021 4 | 5 | @author: cosmi 6 | """ 7 | 8 | 9 | import matplotlib 10 | matplotlib.use('TkAgg') 11 | from pylab import * 12 | import networkx as nx 13 | from math import sin, pi 14 | import numpy 15 | 16 | from random import random as rand 17 | 18 | 19 | def initialize(): 20 | global g, nextg 21 | g = nx.karate_club_graph() 22 | g.pos = nx.spring_layout(g) 23 | 24 | 25 | for i in list(g.nodes()): 26 | 27 | #for i in g.nodes_iter(): 28 | g.node[i]['theta'] = 2*pi*rand() 29 | 30 | rows, cols = (-0.05, 0.05) 31 | arr = [[rand.randrange(10) for i in range(int(cols))] for j in range(int(rows))] 32 | a = numpy.asarray(arr) 33 | #g.node[i]['omega'] = 1. + rand.uniform(-0.05, 0.05) 34 | g.node[i]['omega'] = 1. + a 35 | 36 | nextg = g.copy() 37 | 38 | def observe(): 39 | global g, nextg 40 | nx.draw(g, cmap = cm.hsv, vmin = -1, vmax = 1, 41 | node_color = [sin(g.node[i]['theta']) for i in list(g.nodes())], 42 | pos = g.pos) 43 | 44 | alpha = 1 # coupling strength 45 | Dt = 0.01 # Delta t 46 | 47 | def update(): 48 | global g, nextg 49 | for i in list(g.nodes()): 50 | theta_i = g.node[i]['theta'] 51 | nextg.node[i]['theta'] = theta_i + (g.node[i]['omega'] + alpha * ( \ 52 | sum(sin(g.node[j]['theta'] - theta_i) for j in g.neighbors(i)) 53 | /g.degree(i))) * Dt 54 | g, nextg = nextg, g 55 | 56 | 57 | import pycxsimulator 58 | 59 | pycxsimulator.GUI().start(func=[initialize, observe, update]) 60 | -------------------------------------------------------------------------------- /netsyncanalysis.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Sat Feb 13 13:30:10 2021 4 | 5 | @author: cosmi 6 | """ 7 | 8 | 9 | import matplotlib 10 | matplotlib.use('TkAgg') 11 | from pylab import * 12 | import networkx as nx 13 | from math import pi 14 | import numpy as np 15 | 16 | 17 | 18 | import scipy 19 | import numpy as np 20 | from scipy import misc 21 | import numpy as np 22 | import scipy.linalg as la 23 | 24 | from matplotlib import pyplot as plt # For image viewing 25 | 26 | from matplotlib import colors 27 | from matplotlib import ticker 28 | from matplotlib.colors import LinearSegmentedColormap 29 | 30 | from matplotlib.collections import LineCollection 31 | from matplotlib.colors import ListedColormap, BoundaryNorm 32 | 33 | 34 | 35 | from random import random as rand 36 | from random import uniform 37 | 38 | from qutip.visualization import plot_wigner, hinton 39 | 40 | from pygsp import graphs 41 | 42 | #def gridsize(val): 43 | # ''' 44 | # Number Of Particles in a Grid Shall Be Entered such that gridsize 4 = 4 x 4 i.e. 16 45 | # Particles in Total. Note: this can only be changed at the start of a new 46 | # Simulation Run - In This Version Do Note Change While Running the Simulation! 47 | # ''' 48 | # global n 49 | 50 | # n = int(val) 51 | # return val 52 | 53 | 54 | 55 | def initialize(): 56 | global g, nextg 57 | 58 | n = 3 59 | g = nx.grid_graph(dim=[n,n]) 60 | 61 | #g = nx.karate_club_graph() 62 | 63 | for i in list(g.nodes()): 64 | g.node[i]['theta'] = 2 * pi * random() 65 | #rows, cols = (-0.05, 0.05) 66 | #arr = [[rand.randrange(10) for i in range(int(cols))] for j in range(int(rows))] 67 | #a = numpy.asarray(arr) 68 | #g.node[i]['omega'] = 1. + rand.uniform(-0.05, 0.05) 69 | g.node[i]['omega'] = 1. + uniform(-0.05, 0.05) 70 | nextg = g.copy() 71 | 72 | 73 | for i in list(g.nodes()): 74 | g.node[i]['theta'] = random() 75 | nextg = g.copy() 76 | 77 | 78 | 79 | 80 | 81 | 82 | 83 | 84 | grid2d = graphs.Graph.from_networkx(nextg) 85 | 86 | print(grid2d.W.toarray()) 87 | print(grid2d.signals) 88 | print(grid2d) 89 | 90 | grid2d.compute_fourier_basis() 91 | 92 | grid2d.set_coordinates() 93 | 94 | 95 | 96 | 97 | 98 | # plot spectrum 99 | fig, ax = plt.subplots(1, 1, figsize=(7,7)) 100 | ax.plot(grid2d.e) 101 | ax.set_xlabel('eigenvalue index (i)') 102 | ax.set_ylabel('eigenvalue ($\lambda_{i}$)') 103 | ax.set_title('2D-grid spectrum'); 104 | #fiedler vector highlighted graph 105 | grid2d.plot_signal(grid2d.U[:,1]) 106 | 107 | #plot all eigenvectors as network graph frames 108 | 109 | fig, axes = plt.subplots(2, 3, figsize=(10, 6.6)) 110 | count = 0 111 | for j in range(2): 112 | for i in range(3): 113 | grid2d.plot_signal(grid2d.U[:, count*1], ax=axes[j,i],colorbar=False) 114 | axes[j,i].set_xticks([]) 115 | axes[j,i].set_yticks([]) 116 | axes[j,i].set_title(f'Eigvec {count*1+1}') 117 | count+=1 118 | fig.tight_layout() 119 | 120 | 121 | #for space vs time graph 122 | 123 | xdata = [] 124 | ydata = [] 125 | 126 | 127 | def observe(): 128 | global g, nextg, grid2d 129 | subplot(1,2,1) 130 | cla() 131 | nx.draw(g, cmap = cm.hsv, vmin = -1, vmax = 1, 132 | node_color = [np.sin(g.node[i]['theta']) for i in list(g.nodes())], 133 | pos = nx.spring_layout(g) ) 134 | axis('image') 135 | 136 | subplot(1,2,2) 137 | cla() 138 | 139 | plot([np.cos(g.node[i]['theta']) for i in list(g.nodes())], 140 | [np.sin(g.node[i]['theta']) for i in list(g.nodes())], '.') 141 | axis('image') 142 | 143 | axis([-1.1,1.1,-1.1,1.1]) 144 | 145 | 146 | 147 | 148 | 149 | 150 | #subplot(1,2,2) 151 | #cla() 152 | #plot(xdata, ydata,'o',alpha = 0.05) 153 | #axis('image') 154 | # for space vs time plotting (chimera search) 155 | 156 | 157 | 158 | 159 | alpha = 2 # coupling strength 160 | beta = 1 # acceleration rate 161 | Dt = 0.01 # Delta t 162 | 163 | #def update(): 164 | # global g, nextg 165 | # for i in list(g.nodes()): 166 | # theta_i = g.node[i]['theta'] 167 | # nextg.node[i]['theta'] = theta_i + (beta * theta_i + alpha * (np.sum(sin(g.node[j]['theta'] - theta_i) for j in g.neighbors(i))) * Dt) 168 | # g, nextg = nextg, g 169 | 170 | def update(): 171 | global g, nextg, eig_values, eig_vectors, rho, grid2d 172 | for i in list(g.nodes()): 173 | theta_i = g.node[i]['theta'] 174 | nextg.node[i]['theta'] = theta_i + (g.node[i]['omega'] + alpha * ( \ 175 | sum(np.sin(g.node[j]['theta'] - theta_i) for j in g.neighbors(i)) \ 176 | / g.degree(i))) * Dt 177 | g, nextg = nextg, g 178 | 179 | 180 | #for i, j in list(g.nodes()): 181 | #xdata.append(g.degree(i)) 182 | #ccs = nx.connected_components(g) 183 | #ydata.append(max(len(cc) for cc in ccs)) 184 | #xdata.append(g.degree(i)); ydata.append(g.degree(j)) 185 | #xdata.append(g.degree(j)); ydata.append(g.degree(i)) 186 | 187 | 188 | A = nx.adjacency_matrix(nextg) 189 | print(A) 190 | n, m = A.shape 191 | diags = A.sum(axis=0) # 1 = outdegree, 0 = indegree 192 | D = scipy.sparse.spdiags(diags.flatten(), [0], m, n, format="csr") 193 | L = (A-D) 194 | Lap = L.todense() 195 | print(Lap) 196 | 197 | eig_values, eig_vectors = la.eig(Lap) 198 | fiedler_pos = np.where(eig_values.real == np.sort(eig_values.real)[1])[0][0] 199 | fiedler_vector = np.transpose(eig_vectors)[fiedler_pos] 200 | 201 | print("Fiedler value: " + str(fiedler_pos.real)) 202 | 203 | print("Fiedler vector: " + str(fiedler_vector.real)) 204 | #nx.laplacian_matrix(nextg).toarray() 205 | 206 | 207 | # applying matrix.trace() method 208 | LTrace = np.matrix.trace(Lap) 209 | print(LTrace) 210 | 211 | #print density matrix 212 | rho = np.divide(Lap,LTrace) 213 | print(rho) 214 | 215 | 216 | 217 | 218 | 219 | 220 | 221 | 222 | 223 | #note you can calculate the trace faster using the hadamard product (element-wise multiplication) 224 | # using the fiedler vector as the basis for the emergent density matrix 225 | 226 | 227 | 228 | 229 | import pycxsimulator 230 | 231 | pycxsimulator.GUI().start(func=[initialize, observe, update]) 232 | 233 | 234 | 235 | 236 | #plt.figure(1) 237 | #compare red and blue pixel data 238 | #nbins = 20 239 | #plt.hexbin(x=plot_time_stamp, y=plot_agent, gridsize=nbins, cmap=plt.cm.jet) 240 | #plt.xlabel('Blue Reflectance') 241 | #plt.ylabel('NIR Reflectance') 242 | # Add a title 243 | #plt.title('NIR vs Blue Spectral Data') 244 | #plt.show() 245 | -------------------------------------------------------------------------------- /netsyncanalysisQuantumDAGmodel.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Sat Feb 13 13:30:10 2021 4 | 5 | @author: cosmi 6 | """ 7 | 8 | 9 | import matplotlib 10 | matplotlib.use('TkAgg') 11 | from pylab import * 12 | import networkx as nx 13 | from math import pi 14 | import numpy as np 15 | 16 | 17 | 18 | import scipy 19 | import numpy as np 20 | from scipy import misc 21 | 22 | from matplotlib import pyplot as plt # For image viewing 23 | 24 | from matplotlib import colors 25 | from matplotlib import ticker 26 | from matplotlib.colors import LinearSegmentedColormap 27 | 28 | #new feature 2022 29 | from qutip.visualization import plot_wigner, hinton 30 | 31 | 32 | import operator 33 | 34 | from random import random as rand 35 | from random import uniform 36 | 37 | import rustworkx as rx 38 | 39 | from rustworkx.visualization import mpl_draw 40 | 41 | 42 | #def gridsize(val): 43 | # ''' 44 | # Number Of Particles in a Grid Shall Be Entered such that gridsize 4 = 4 x 4 i.e. 16 45 | # Particles in Total. Note: this can only be changed at the start of a new 46 | # Simulation Run - In This Version Do Note Change While Running the Simulation! 47 | # ''' 48 | # global n 49 | 50 | # n = int(val) 51 | # return val 52 | 53 | 54 | 55 | 56 | 57 | def initialize(): 58 | global g, nextg, A, nextA 59 | 60 | n = 3 61 | #g = nx.grid_graph(dim=[n,n]) 62 | 63 | #using dag 64 | #g = nx.from_edgelist([dag], create_using=nx.DiGraph) 65 | #construct classical network graph g from adjacency matrix 66 | g = nx.scale_free_graph(n) #obtain a directed acyclic graph 67 | #remove self loops 68 | g.remove_edges_from(nx.selfloop_edges(g)) 69 | 70 | 71 | 72 | #g = nx.karate_club_graph() 73 | 74 | for i in list(g.nodes()): 75 | g.node[i]['theta'] = 2 * pi * random() 76 | #rows, cols = (-0.05, 0.05) 77 | #arr = [[rand.randrange(10) for i in range(int(cols))] for j in range(int(rows))] 78 | #a = numpy.asarray(arr) 79 | #g.node[i]['omega'] = 1. + rand.uniform(-0.05, 0.05) 80 | g.node[i]['omega'] = 1. + uniform(-0.05, 0.05) 81 | nextg = g.copy() 82 | 83 | 84 | for i in list(g.nodes()): 85 | g.node[i]['theta'] = random() 86 | nextg = g.copy() 87 | 88 | 89 | #for space vs time graph 90 | 91 | xdata = [] 92 | ydata = [] 93 | 94 | 95 | def observe(): 96 | global g, nextg 97 | subplot(1,2,1) 98 | cla() 99 | nx.draw(g, cmap = cm.hsv, vmin = -1, vmax = 1, 100 | node_color = [np.sin(g.node[i]['theta']) for i in list(g.nodes())], 101 | pos = nx.spring_layout(g) ) 102 | axis('image') 103 | 104 | subplot(1,2,2) 105 | cla() 106 | 107 | plot([np.cos(g.node[i]['theta']) for i in list(g.nodes())], 108 | [np.sin(g.node[i]['theta']) for i in list(g.nodes())], '.') 109 | axis('image') 110 | 111 | axis([-1.1,1.1,-1.1,1.1]) 112 | 113 | 114 | #subplot(1,2,2) 115 | #cla() 116 | #plot(xdata, ydata,'o',alpha = 0.05) 117 | #axis('image') 118 | # for space vs time plotting (chimera search) 119 | 120 | 121 | alpha = 2 # coupling strength 122 | beta = 1 # acceleration rate 123 | Dt = 0.01 # Delta t 124 | 125 | #def update(): 126 | # global g, nextg 127 | # for i in list(g.nodes()): 128 | # theta_i = g.node[i]['theta'] 129 | # nextg.node[i]['theta'] = theta_i + (beta * theta_i + alpha * (np.sum(sin(g.node[j]['theta'] - theta_i) for j in g.neighbors(i))) * Dt) 130 | # g, nextg = nextg, g 131 | 132 | def update(): 133 | global g, nextg, A, k_in, L 134 | for i in list(g.nodes()): 135 | theta_i = g.node[i]['theta'] 136 | nextg.node[i]['theta'] = theta_i + (g.node[i]['omega'] + alpha * ( \ 137 | sum(np.sin(g.node[j]['theta'] - theta_i) for j in g.neighbors(i)) \ 138 | / g.degree(i))) * Dt 139 | g, nextg = nextg, g 140 | A = nx.adj_matrix(nextg).todense() 141 | k_in = np.zeros(nextg.number_of_nodes()) 142 | 143 | L = np.diag(k_in) - A 144 | 145 | 146 | 147 | #for i, j in list(g.nodes()): 148 | #xdata.append(g.degree(i)) 149 | #ccs = nx.connected_components(g) 150 | #ydata.append(max(len(cc) for cc in ccs)) 151 | #xdata.append(g.degree(i)); ydata.append(g.degree(j)) 152 | #xdata.append(g.degree(j)); ydata.append(g.degree(i)) 153 | 154 | 155 | 156 | import pycxsimulator 157 | 158 | pycxsimulator.GUI().start(func=[initialize, observe, update]) 159 | 160 | 161 | 162 | #plt.figure(1) 163 | #compare red and blue pixel data 164 | #nbins = 20 165 | #plt.hexbin(x=plot_time_stamp, y=plot_agent, gridsize=nbins, cmap=plt.cm.jet) 166 | #plt.xlabel('Blue Reflectance') 167 | #plt.ylabel('NIR Reflectance') 168 | # Add a title 169 | #plt.title('NIR vs Blue Spectral Data') 170 | #plt.show() 171 | -------------------------------------------------------------------------------- /netsyncanalysisv2eigen.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Sat Feb 13 13:30:10 2021 4 | 5 | @author: cosmi 6 | """ 7 | 8 | 9 | import matplotlib 10 | matplotlib.use('TkAgg') 11 | from pylab import * 12 | import networkx as nx 13 | from math import pi 14 | import numpy as np 15 | 16 | 17 | 18 | import scipy 19 | import numpy as np 20 | from scipy import misc 21 | import numpy as np 22 | import scipy.linalg as la 23 | 24 | from matplotlib import pyplot as plt # For image viewing 25 | 26 | from matplotlib import colors 27 | from matplotlib import ticker 28 | from matplotlib.colors import LinearSegmentedColormap 29 | 30 | from matplotlib.collections import LineCollection 31 | from matplotlib.colors import ListedColormap, BoundaryNorm 32 | 33 | 34 | 35 | from random import random as rand 36 | from random import uniform 37 | 38 | from qutip.visualization import plot_wigner, hinton 39 | 40 | #qutip star imports 41 | from qutip import * 42 | 43 | from qutip import Qobj, rand_dm, fidelity, displace, qdiags, qeye, expect 44 | from qutip.states import coherent, coherent_dm, thermal_dm, fock_dm 45 | from qutip.wigner import qfunc 46 | 47 | 48 | from pygsp import graphs 49 | 50 | #def gridsize(val): 51 | # ''' 52 | # Number Of Particles in a Grid Shall Be Entered such that gridsize 4 = 4 x 4 i.e. 16 53 | # Particles in Total. Note: this can only be changed at the start of a new 54 | # Simulation Run - In This Version Do Note Change While Running the Simulation! 55 | # ''' 56 | # global n 57 | 58 | # n = int(val) 59 | # return val 60 | 61 | 62 | 63 | def initialize(): 64 | global g, nextg, hilbert_size 65 | 66 | 67 | 68 | 69 | n = 2 70 | g = nx.grid_graph(dim=[n,n]) 71 | 72 | #g = nx.karate_club_graph() 73 | 74 | for i in list(g.nodes()): 75 | g.node[i]['theta'] = 2 * pi * random() 76 | #rows, cols = (-0.05, 0.05) 77 | #arr = [[rand.randrange(10) for i in range(int(cols))] for j in range(int(rows))] 78 | #a = numpy.asarray(arr) 79 | #g.node[i]['omega'] = 1. + rand.uniform(-0.05, 0.05) 80 | g.node[i]['omega'] = 1. + uniform(-0.05, 0.05) 81 | nextg = g.copy() 82 | 83 | 84 | for i in list(g.nodes()): 85 | g.node[i]['theta'] = random() 86 | nextg = g.copy() 87 | 88 | 89 | 90 | 91 | 92 | 93 | 94 | 95 | grid2d = graphs.Graph.from_networkx(nextg) 96 | 97 | #print(grid2d.W.toarray()) 98 | #print(grid2d.signals) 99 | #print(grid2d) 100 | 101 | grid2d.compute_fourier_basis() 102 | 103 | grid2d.set_coordinates() 104 | 105 | 106 | 107 | 108 | 109 | # plot spectrum 110 | fig, ax = plt.subplots(1, 1, figsize=(7,7)) 111 | ax.plot(grid2d.e) 112 | ax.set_xlabel('eigenvalue index (i)') 113 | ax.set_ylabel('eigenvalue ($\lambda_{i}$)') 114 | ax.set_title('2D-grid spectrum'); 115 | #fiedler vector highlighted graph 116 | grid2d.plot_signal(grid2d.U[:,1]) 117 | 118 | #plot all eigenvectors as network graph frames 119 | 120 | fig, axes = plt.subplots(2, 3, figsize=(10, 6.6)) 121 | count = 0 122 | for j in range(2): 123 | for i in range(2): 124 | grid2d.plot_signal(grid2d.U[:, count*1], ax=axes[j,i],colorbar=False) 125 | axes[j,i].set_xticks([]) 126 | axes[j,i].set_yticks([]) 127 | axes[j,i].set_title(f'Eigvec {count*1+1}') 128 | count+=1 129 | fig.tight_layout() 130 | 131 | 132 | 133 | #hilbert space must be the same as the network size for this to make sense 134 | 135 | 136 | alphas = grid2d.signals['omega'] 137 | 138 | 139 | print(alphas) 140 | 141 | betas = grid2d.signals['theta'] 142 | 143 | print(betas) 144 | 145 | hilbert_size = n 146 | 147 | 148 | 149 | 150 | psi = coherent(hilbert_size, 0) 151 | 152 | rho = coherent_dm(hilbert_size, 1-1j) 153 | 154 | d = displace(hilbert_size, 2+2j) 155 | 156 | 157 | 158 | #psi = sum([coherent_dm(hilbert_size, a) for a in alphas]) 159 | psi = psi.unit() 160 | rho = psi*psi.dag() 161 | 162 | fig, ax = plt.subplots(1, 4, figsize=(19, 4)) 163 | 164 | plot_wigner_fock_distribution(psi, fig=fig, axes=[ax[0], ax[1]]) 165 | plot_wigner_fock_distribution(d*psi, fig=fig, axes=[ax[2], ax[3]]) 166 | 167 | ax[0].set_title(r"Initial state, $\psi_{vac} = |0 \rangle$") 168 | ax[2].set_title(r"Displaced state, $D(\alpha=2+2i )\psi_{vac}$") 169 | plt.show() 170 | 171 | fig, ax = plot_wigner_fock_distribution(rho, figsize=(9, 4)) 172 | ax[0].set_title("Superposition of three coherent states") 173 | plt.show() 174 | 175 | 176 | measured_populations = [measure_population(b, rho) for b in betas] 177 | 178 | 179 | 180 | 181 | 182 | 183 | 184 | 185 | 186 | def observe(): 187 | global g, nextg, grid2d 188 | subplot(1,2,1) 189 | cla() 190 | nx.draw(g, cmap = cm.hsv, vmin = -1, vmax = 1, 191 | node_color = [np.sin(g.node[i]['theta']) for i in list(g.nodes())], 192 | pos = nx.spring_layout(g) ) 193 | axis('image') 194 | 195 | subplot(1,2,2) 196 | cla() 197 | 198 | plot([np.cos(g.node[i]['theta']) for i in list(g.nodes())], 199 | [np.sin(g.node[i]['theta']) for i in list(g.nodes())], '.') 200 | axis('image') 201 | 202 | axis([-1.1,1.1,-1.1,1.1]) 203 | 204 | 205 | 206 | 207 | 208 | 209 | #subplot(1,2,2) 210 | #cla() 211 | #plot(xdata, ydata,'o',alpha = 0.05) 212 | #axis('image') 213 | # for space vs time plotting (chimera search) 214 | 215 | 216 | 217 | 218 | alpha = 2 # coupling strength 219 | beta = 1 # acceleration rate 220 | Dt = 0.01 # Delta t 221 | 222 | #def update(): 223 | # global g, nextg 224 | # for i in list(g.nodes()): 225 | # theta_i = g.node[i]['theta'] 226 | # nextg.node[i]['theta'] = theta_i + (beta * theta_i + alpha * (np.sum(sin(g.node[j]['theta'] - theta_i) for j in g.neighbors(i))) * Dt) 227 | # g, nextg = nextg, g 228 | 229 | def measure_population(beta, rho): 230 | """ 231 | Measures the photon number statistics for state rho when displaced 232 | by angle alpha. 233 | 234 | Parameters 235 | ---------- 236 | alpha: np.complex 237 | A complex displacement. 238 | 239 | rho: 240 | The density matrix as a QuTiP Qobj (`qutip.Qobj`) 241 | 242 | Returns 243 | ------- 244 | population: ndarray 245 | A 1D array for the probabilities for populations. 246 | """ 247 | hilbertsize = rho.shape[0] 248 | # Apply a displacement to the state and then measure the diagonals. 249 | 250 | D = displace(hilbertsize, beta) 251 | rho_disp = D*rho*D.dag() 252 | populations = np.real(np.diagonal(rho_disp.full())) 253 | return populations 254 | 255 | 256 | 257 | 258 | 259 | def update(): 260 | global g, nextg, eig_values, eig_vectors, rho, grid2d, theta_i 261 | for i in list(g.nodes()): 262 | theta_i = g.node[i]['theta'] 263 | omega_i = g.node[i]['omega'] 264 | nextg.node[i]['theta'] = theta_i + (g.node[i]['omega'] + alpha * ( \ 265 | sum(np.sin(g.node[j]['theta'] - theta_i) for j in g.neighbors(i)) \ 266 | / g.degree(i))) * Dt 267 | g, nextg = nextg, g 268 | 269 | 270 | #for i, j in list(g.nodes()): 271 | #xdata.append(g.degree(i)) 272 | #ccs = nx.connected_components(g) 273 | #ydata.append(max(len(cc) for cc in ccs)) 274 | #xdata.append(g.degree(i)); ydata.append(g.degree(j)) 275 | #xdata.append(g.degree(j)); ydata.append(g.degree(i)) 276 | 277 | 278 | A = nx.adjacency_matrix(nextg) 279 | print(A) 280 | n, m = A.shape 281 | diags = A.sum(axis=0) # 1 = outdegree, 0 = indegree 282 | D = scipy.sparse.spdiags(diags.flatten(), [0], m, n, format="csr") 283 | L = (A-D) 284 | Lap = L.todense() 285 | print(Lap) 286 | 287 | eig_values, eig_vectors = la.eig(Lap) 288 | fiedler_pos = np.where(eig_values.real == np.sort(eig_values.real)[1])[0][0] 289 | fiedler_vector = np.transpose(eig_vectors)[fiedler_pos] 290 | 291 | #print("Fiedler value: " + str(fiedler_pos.real)) 292 | 293 | # this will be an eigenbra version 294 | print("Fiedler vector: " + str(fiedler_vector.real)) 295 | 296 | 297 | #nx.laplacian_matrix(nextg).toarray() 298 | 299 | 300 | # applying matrix.trace() method 301 | LTrace = np.matrix.trace(Lap) 302 | #print(LTrace) 303 | 304 | #print density matrix from graph laplacian 305 | 306 | rho = np.divide(Lap,LTrace) 307 | 308 | #we need to represent this graph density matrix as a cavity reduced density matrix to make physical sense 309 | 310 | #print(rho) 311 | 312 | 313 | 314 | 315 | 316 | print(theta_i) 317 | 318 | print(omega_i) 319 | 320 | 321 | 322 | 323 | #note you can calculate the trace faster using the hadamard product (element-wise multiplication) 324 | # using the fiedler vector as the basis for the emergent density matrix 325 | 326 | 327 | 328 | 329 | import pycxsimulator 330 | 331 | pycxsimulator.GUI().start(func=[initialize, observe, update]) 332 | 333 | 334 | 335 | #plt.figure(1) 336 | #compare red and blue pixel data 337 | #nbins = 20 338 | #plt.hexbin(x=plot_time_stamp, y=plot_agent, gridsize=nbins, cmap=plt.cm.jet) 339 | #plt.xlabel('Blue Reflectance') 340 | #plt.ylabel('NIR Reflectance') 341 | # Add a title 342 | #plt.title('NIR vs Blue Spectral Data') 343 | #plt.show() 344 | -------------------------------------------------------------------------------- /netsyncanalysisv2eigenwigner.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Sat Feb 13 13:30:10 2021 4 | 5 | @author: cosmi 6 | """ 7 | 8 | 9 | import matplotlib 10 | matplotlib.use('TkAgg') 11 | from pylab import * 12 | import networkx as nx 13 | from math import pi 14 | import numpy as np 15 | 16 | 17 | 18 | import scipy 19 | import numpy as np 20 | from scipy import misc 21 | import numpy as np 22 | import scipy.linalg as la 23 | 24 | from matplotlib import pyplot as plt # For image viewing 25 | 26 | from matplotlib import colors 27 | from matplotlib import ticker 28 | from matplotlib.colors import LinearSegmentedColormap 29 | 30 | from matplotlib.collections import LineCollection 31 | from matplotlib.colors import ListedColormap, BoundaryNorm 32 | 33 | 34 | 35 | from random import random as rand 36 | from random import uniform 37 | 38 | from qutip.visualization import plot_wigner, hinton 39 | 40 | #qutip star imports 41 | from qutip import * 42 | 43 | from qutip import Qobj, rand_dm, fidelity, displace, qdiags, qeye, expect 44 | from qutip.states import coherent, coherent_dm, thermal_dm, fock_dm 45 | from qutip.wigner import qfunc 46 | 47 | 48 | from pygsp import graphs 49 | 50 | #def gridsize(val): 51 | # ''' 52 | # Number Of Particles in a Grid Shall Be Entered such that gridsize 4 = 4 x 4 i.e. 16 53 | # Particles in Total. Note: this can only be changed at the start of a new 54 | # Simulation Run - In This Version Do Note Change While Running the Simulation! 55 | # ''' 56 | # global n 57 | 58 | # n = int(val) 59 | # return val 60 | 61 | 62 | 63 | def initialize(): 64 | global g, nextg, hilbert_size 65 | 66 | 67 | 68 | 69 | n = 2 70 | g = nx.grid_graph(dim=[n,n]) 71 | 72 | #g = nx.karate_club_graph() 73 | 74 | for i in list(g.nodes()): 75 | g.node[i]['theta'] = 2 * pi * random() 76 | #rows, cols = (-0.05, 0.05) 77 | #arr = [[rand.randrange(10) for i in range(int(cols))] for j in range(int(rows))] 78 | #a = numpy.asarray(arr) 79 | #g.node[i]['omega'] = 1. + rand.uniform(-0.05, 0.05) 80 | g.node[i]['omega'] = 1. + uniform(-0.05, 0.05) 81 | nextg = g.copy() 82 | 83 | 84 | for i in list(g.nodes()): 85 | g.node[i]['theta'] = random() 86 | nextg = g.copy() 87 | 88 | 89 | 90 | 91 | 92 | 93 | 94 | 95 | grid2d = graphs.Graph.from_networkx(nextg) 96 | 97 | #print(grid2d.W.toarray()) 98 | #print(grid2d.signals) 99 | #print(grid2d) 100 | 101 | grid2d.compute_fourier_basis() 102 | 103 | grid2d.set_coordinates() 104 | 105 | 106 | 107 | 108 | 109 | # plot spectrum 110 | fig, ax = plt.subplots(1, 1, figsize=(7,7)) 111 | ax.plot(grid2d.e) 112 | ax.set_xlabel('eigenvalue index (i)') 113 | ax.set_ylabel('eigenvalue ($\lambda_{i}$)') 114 | ax.set_title('2D-grid spectrum'); 115 | #fiedler vector highlighted graph 116 | grid2d.plot_signal(grid2d.U[:,1]) 117 | 118 | #plot all eigenvectors as network graph frames 119 | 120 | fig, axes = plt.subplots(2, 3, figsize=(10, 6.6)) 121 | count = 0 122 | for j in range(2): 123 | for i in range(2): 124 | grid2d.plot_signal(grid2d.U[:, count*1], ax=axes[j,i],colorbar=False) 125 | axes[j,i].set_xticks([]) 126 | axes[j,i].set_yticks([]) 127 | axes[j,i].set_title(f'Eigvec {count*1+1}') 128 | count+=1 129 | fig.tight_layout() 130 | 131 | 132 | 133 | #hilbert space must be the same as the network size for this to make sense 134 | 135 | 136 | alphas = grid2d.signals['omega'] 137 | 138 | 139 | print(alphas) 140 | 141 | betas = grid2d.signals['theta'] 142 | 143 | print(betas) 144 | 145 | hilbert_size = n 146 | 147 | 148 | 149 | 150 | psi = coherent(hilbert_size, 0) 151 | 152 | rho = coherent_dm(hilbert_size, 1-1j) 153 | 154 | d = displace(hilbert_size, 2+2j) 155 | 156 | 157 | 158 | #psi = sum([coherent_dm(hilbert_size, a) for a in alphas]) 159 | psi = psi.unit() 160 | rho = psi*psi.dag() 161 | 162 | fig, ax = plt.subplots(1, 4, figsize=(19, 4)) 163 | 164 | plot_wigner_fock_distribution(psi, fig=fig, axes=[ax[0], ax[1]]) 165 | plot_wigner_fock_distribution(d*psi, fig=fig, axes=[ax[2], ax[3]]) 166 | 167 | ax[0].set_title(r"Initial state, $\psi_{vac} = |0 \rangle$") 168 | ax[2].set_title(r"Displaced state, $D(\alpha=2+2i )\psi_{vac}$") 169 | plt.show() 170 | 171 | fig, ax = plot_wigner_fock_distribution(rho, figsize=(9, 4)) 172 | ax[0].set_title("Superposition of three coherent states") 173 | plt.show() 174 | 175 | 176 | measured_populations = [measure_population(b, rho) for b in betas] 177 | 178 | 179 | 180 | 181 | 182 | 183 | 184 | 185 | 186 | def observe(): 187 | global g, nextg, grid2d 188 | subplot(1,2,1) 189 | cla() 190 | nx.draw(g, cmap = cm.hsv, vmin = -1, vmax = 1, 191 | node_color = [np.sin(g.node[i]['theta']) for i in list(g.nodes())], 192 | pos = nx.spring_layout(g) ) 193 | axis('image') 194 | 195 | subplot(1,2,2) 196 | cla() 197 | 198 | plot([np.cos(g.node[i]['theta']) for i in list(g.nodes())], 199 | [np.sin(g.node[i]['theta']) for i in list(g.nodes())], '.') 200 | axis('image') 201 | 202 | axis([-1.1,1.1,-1.1,1.1]) 203 | 204 | 205 | 206 | 207 | 208 | 209 | #subplot(1,2,2) 210 | #cla() 211 | #plot(xdata, ydata,'o',alpha = 0.05) 212 | #axis('image') 213 | # for space vs time plotting (chimera search) 214 | 215 | 216 | 217 | 218 | alpha = 2 # coupling strength 219 | beta = 1 # acceleration rate 220 | 221 | 222 | #beta could a delay for simulating memory. 223 | 224 | Dt = 0.01 # Delta t 225 | 226 | #def update(): 227 | # global g, nextg 228 | # for i in list(g.nodes()): 229 | # theta_i = g.node[i]['theta'] 230 | # nextg.node[i]['theta'] = theta_i + (beta * theta_i + alpha * (np.sum(sin(g.node[j]['theta'] - theta_i) for j in g.neighbors(i))) * Dt) 231 | # g, nextg = nextg, g 232 | 233 | def measure_population(beta, rho): 234 | """ 235 | Measures the photon number statistics for state rho when displaced 236 | by angle alpha. 237 | 238 | Parameters 239 | ---------- 240 | alpha: np.complex 241 | A complex displacement. 242 | 243 | rho: 244 | The density matrix as a QuTiP Qobj (`qutip.Qobj`) 245 | 246 | Returns 247 | ------- 248 | population: ndarray 249 | A 1D array for the probabilities for populations. 250 | """ 251 | hilbertsize = rho.shape[0] 252 | # Apply a displacement to the state and then measure the diagonals. 253 | 254 | D = displace(hilbertsize, beta) 255 | rho_disp = D*rho*D.dag() 256 | populations = np.real(np.diagonal(rho_disp.full())) 257 | return populations 258 | 259 | 260 | 261 | 262 | 263 | def update(): 264 | global g, nextg, eig_values, eig_vectors, rho, grid2d, theta_i 265 | for i in list(g.nodes()): 266 | theta_i = g.node[i]['theta'] 267 | omega_i = g.node[i]['omega'] 268 | nextg.node[i]['theta'] = theta_i + (g.node[i]['omega'] + alpha * ( \ 269 | sum(np.sin(g.node[j]['theta'] - theta_i) for j in g.neighbors(i)) \ 270 | / g.degree(i))) * Dt 271 | g, nextg = nextg, g 272 | 273 | 274 | #for i, j in list(g.nodes()): 275 | #xdata.append(g.degree(i)) 276 | #ccs = nx.connected_components(g) 277 | #ydata.append(max(len(cc) for cc in ccs)) 278 | #xdata.append(g.degree(i)); ydata.append(g.degree(j)) 279 | #xdata.append(g.degree(j)); ydata.append(g.degree(i)) 280 | 281 | 282 | A = nx.adjacency_matrix(nextg) 283 | print(A) 284 | n, m = A.shape 285 | diags = A.sum(axis=0) # 1 = outdegree, 0 = indegree 286 | D = scipy.sparse.spdiags(diags.flatten(), [0], m, n, format="csr") 287 | L = (A-D) 288 | Lap = L.todense() 289 | print(Lap) 290 | 291 | eig_values, eig_vectors = la.eig(Lap) 292 | fiedler_pos = np.where(eig_values.real == np.sort(eig_values.real)[1])[0][0] 293 | fiedler_vector = np.transpose(eig_vectors)[fiedler_pos] 294 | 295 | #print("Fiedler value: " + str(fiedler_pos.real)) 296 | 297 | # this will be an eigenbra version 298 | print("Fiedler vector: " + str(fiedler_vector.real)) 299 | 300 | 301 | #nx.laplacian_matrix(nextg).toarray() 302 | 303 | 304 | # applying matrix.trace() method 305 | LTrace = np.matrix.trace(Lap) 306 | #print(LTrace) 307 | 308 | #print density matrix from graph laplacian 309 | 310 | rho = np.divide(Lap,LTrace) 311 | 312 | #we need to represent this graph density matrix as a cavity reduced density matrix to make physical sense 313 | 314 | #print(rho) 315 | 316 | 317 | 318 | 319 | 320 | print(theta_i) 321 | 322 | print(omega_i) 323 | 324 | 325 | 326 | 327 | #note you can calculate the trace faster using the hadamard product (element-wise multiplication) 328 | # using the fiedler vector as the basis for the emergent density matrix 329 | 330 | 331 | 332 | 333 | import pycxsimulator 334 | 335 | pycxsimulator.GUI().start(func=[initialize, observe, update]) 336 | 337 | 338 | 339 | #plt.figure(1) 340 | #compare red and blue pixel data 341 | #nbins = 20 342 | #plt.hexbin(x=plot_time_stamp, y=plot_agent, gridsize=nbins, cmap=plt.cm.jet) 343 | #plt.xlabel('Blue Reflectance') 344 | #plt.ylabel('NIR Reflectance') 345 | # Add a title 346 | #plt.title('NIR vs Blue Spectral Data') 347 | #plt.show() 348 | -------------------------------------------------------------------------------- /perioddoublingbifurcation.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Wed Mar 3 18:28:58 2021 4 | 5 | @author: cosmi 6 | """ 7 | 8 | from pylab import * 9 | def initialize(): 10 | global x, result 11 | x = 0.1 12 | result = [x] 13 | 14 | 15 | def observe(): 16 | global x, result 17 | result.append(x) 18 | 19 | def update(): 20 | global x, result 21 | x = x + r - x**2 22 | 23 | #def plot_asymptotic_states(): 24 | def plot_phase_space(): 25 | initialize() 26 | for t in range(30): 27 | update() 28 | observe() 29 | plot(result) 30 | ylim(0, 2) 31 | title('r = ' + str(r)) 32 | rs = [0.1, 0.5, 1.0, 1.1, 1.5, 1.6] 33 | 34 | for i in range(len(rs)): 35 | subplot(2, 3, i + 1) 36 | r = rs[i] 37 | plot_phase_space() 38 | show() 39 | -------------------------------------------------------------------------------- /pycxsimulator.py: -------------------------------------------------------------------------------- 1 | ## "pycxsimulator.py" 2 | ## Dynamic, interactive simulation GUI for PyCX 3 | ## 4 | ## Project website: 5 | ## https://github.com/hsayama/PyCX 6 | ## 7 | ## Initial development by: 8 | ## Chun Wong 9 | ## email@chunwong.net 10 | ## 11 | ## Revisions by: 12 | ## Hiroki Sayama 13 | ## sayama@binghamton.edu 14 | ## 15 | ## Copyright 2012 Chun Wong 16 | ## Copyright 2012-2019 Hiroki Sayama 17 | ## 18 | ## Simulation control & GUI extensions 19 | ## Copyright 2013 Przemyslaw Szufel & Bogumil Kaminski 20 | ## {pszufe, bkamins}@sgh.waw.pl 21 | ## 22 | ## Fixing errors due to "the grid and pack problem" by: 23 | ## Toshihiro Tanizawa 24 | ## tanizawa@ee.kochi-ct.ac.jp 25 | ## began at 2016-06-15(Wed) 17:10:17 26 | ## fixed grid() and pack() problem on 2016-06-21(Tue) 18:29:40 27 | ## 28 | ## various bug fixes and updates by Steve Morgan on 3/28/2020 29 | 30 | import matplotlib 31 | 32 | #System check added by Steve Morgan 33 | import platform #SM 3/28/2020 34 | if platform.system() == 'Windows': #SM 3/28/2020 35 | backend = 'TkAgg' #SM 3/28/2020 36 | else: #SM 3/28/2020 37 | backend = 'Qt5Agg' #SM 3/28/2020 38 | matplotlib.use(backend) #SM 3/28/2020 39 | 40 | import matplotlib.pyplot as plt #SM 3/28/2020 41 | 42 | ## version check added by Hiroki Sayama on 01/08/2019 43 | import sys 44 | if sys.version_info[0] == 3: # Python 3 45 | from tkinter import * 46 | from tkinter.ttk import Notebook 47 | else: # Python 2 48 | from Tkinter import * 49 | from ttk import Notebook 50 | 51 | ## suppressing matplotlib deprecation warnings (especially with subplot) by Hiroki Sayama on 06/29/2020 52 | import warnings 53 | warnings.filterwarnings("ignore", category = matplotlib.cbook.MatplotlibDeprecationWarning) 54 | 55 | class GUI: 56 | 57 | # Constructor 58 | def __init__(self, title='PyCX Simulator', interval=0, stepSize=1, parameterSetters=[]): 59 | 60 | ## all GUI variables moved to inside constructor by Hiroki Sayama 10/09/2018 61 | 62 | self.titleText = title 63 | self.timeInterval = interval 64 | self.stepSize = stepSize 65 | self.parameterSetters = parameterSetters 66 | self.varEntries = {} 67 | self.statusStr = "" 68 | 69 | self.running = False 70 | self.modelFigure = None 71 | self.currentStep = 0 72 | 73 | # initGUI() removed by Hiroki Sayama 10/09/2018 74 | 75 | #create root window 76 | self.rootWindow = Tk() 77 | self.statusText = StringVar(self.rootWindow, value=self.statusStr) # at this point, statusStr = "" 78 | # added "self.rootWindow" above by Hiroki Sayama 10/09/2018 79 | self.setStatusStr("Simulation not yet started") 80 | 81 | self.rootWindow.wm_title(self.titleText) # titleText = 'PyCX Simulator' 82 | self.rootWindow.protocol('WM_DELETE_WINDOW', self.quitGUI) 83 | self.rootWindow.geometry('450x300') 84 | self.rootWindow.columnconfigure(0, weight=1) 85 | self.rootWindow.rowconfigure(0, weight=1) 86 | 87 | self.notebook = Notebook(self.rootWindow) 88 | # self.notebook.grid(row=0,column=0,padx=2,pady=2,sticky='nswe') # commented out by toshi on 2016-06-21(Tue) 18:30:25 89 | self.notebook.pack(side=TOP, padx=2, pady=2) 90 | 91 | # added "self.rootWindow" by Hiroki Sayama 10/09/2018 92 | self.frameRun = Frame(self.rootWindow) 93 | self.frameSettings = Frame(self.rootWindow) 94 | self.frameParameters = Frame(self.rootWindow) 95 | self.frameInformation = Frame(self.rootWindow) 96 | 97 | self.notebook.add(self.frameRun,text="Run") 98 | self.notebook.add(self.frameSettings,text="Settings") 99 | self.notebook.add(self.frameParameters,text="Parameters") 100 | self.notebook.add(self.frameInformation,text="Info") 101 | self.notebook.pack(expand=NO, fill=BOTH, padx=5, pady=5 ,side=TOP) 102 | # self.notebook.grid(row=0, column=0, padx=5, pady=5, sticky='nswe') # commented out by toshi on 2016-06-21(Tue) 18:31:02 103 | 104 | self.status = Label(self.rootWindow, width=40,height=3, relief=SUNKEN, bd=1, textvariable=self.statusText) 105 | # self.status.grid(row=1,column=0,padx=5,pady=5,sticky='nswe') # commented out by toshi on 2016-06-21(Tue) 18:31:17 106 | self.status.pack(side=TOP, fill=X, padx=5, pady=5, expand=NO) 107 | 108 | # ----------------------------------- 109 | # frameRun 110 | # ----------------------------------- 111 | # buttonRun 112 | self.runPauseString = StringVar(self.rootWindow) # added "self.rootWindow" by Hiroki Sayama 10/09/2018 113 | self.runPauseString.set("Run") 114 | self.buttonRun = Button(self.frameRun,width=30,height=2,textvariable=self.runPauseString,command=self.runEvent) 115 | self.buttonRun.pack(side=TOP, padx=5, pady=5) 116 | self.showHelp(self.buttonRun,"Runs the simulation (or pauses the running simulation)") 117 | 118 | # buttonStep 119 | self.buttonStep = Button(self.frameRun,width=30,height=2,text='Step Once',command=self.stepOnce) 120 | self.buttonStep.pack(side=TOP, padx=5, pady=5) 121 | self.showHelp(self.buttonStep,"Steps the simulation only once") 122 | 123 | # buttonReset 124 | self.buttonReset = Button(self.frameRun,width=30,height=2,text='Reset',command=self.resetModel) 125 | self.buttonReset.pack(side=TOP, padx=5, pady=5) 126 | self.showHelp(self.buttonReset,"Resets the simulation") 127 | 128 | # ----------------------------------- 129 | # frameSettings 130 | # ----------------------------------- 131 | can = Canvas(self.frameSettings) 132 | 133 | lab = Label(can, width=25,height=1,text="Step size ", justify=LEFT, anchor=W,takefocus=0) 134 | lab.pack(side='left') 135 | 136 | self.stepScale = Scale(can,from_=1, to=50, resolution=1,command=self.changeStepSize,orient=HORIZONTAL, width=25,length=150) 137 | self.stepScale.set(self.stepSize) 138 | self.showHelp(self.stepScale,"Skips model redraw during every [n] simulation steps\nResults in a faster model run.") 139 | self.stepScale.pack(side='left') 140 | 141 | can.pack(side='top') 142 | 143 | can = Canvas(self.frameSettings) 144 | lab = Label(can, width=25,height=1,text="Step visualization delay in ms ", justify=LEFT, anchor=W,takefocus=0) 145 | lab.pack(side='left') 146 | self.stepDelay = Scale(can,from_=0, to=max(2000,self.timeInterval), 147 | resolution=10,command=self.changeStepDelay,orient=HORIZONTAL, width=25,length=150) 148 | self.stepDelay.set(self.timeInterval) 149 | self.showHelp(self.stepDelay,"The visualization of each step is delays by the given number of milliseconds.") 150 | self.stepDelay.pack(side='left') 151 | 152 | can.pack(side='top') 153 | 154 | # -------------------------------------------- 155 | # frameInformation 156 | # -------------------------------------------- 157 | scrollInfo = Scrollbar(self.frameInformation) 158 | self.textInformation = Text(self.frameInformation, width=45,height=13,bg='lightgray',wrap=WORD,font=("Courier",10)) 159 | scrollInfo.pack(side=RIGHT, fill=Y) 160 | self.textInformation.pack(side=LEFT,fill=BOTH,expand=YES) 161 | scrollInfo.config(command=self.textInformation.yview) 162 | self.textInformation.config(yscrollcommand=scrollInfo.set) 163 | 164 | # -------------------------------------------- 165 | # ParameterSetters 166 | # -------------------------------------------- 167 | for variableSetter in self.parameterSetters: 168 | can = Canvas(self.frameParameters) 169 | 170 | lab = Label(can, width=25,height=1,text=variableSetter.__name__+" ",anchor=W,takefocus=0) 171 | lab.pack(side='left') 172 | 173 | ent = Entry(can, width=11) 174 | ent.insert(0, str(variableSetter())) 175 | 176 | if variableSetter.__doc__ != None and len(variableSetter.__doc__) > 0: 177 | self.showHelp(ent,variableSetter.__doc__.strip()) 178 | 179 | ent.pack(side='left') 180 | 181 | can.pack(side='top') 182 | 183 | self.varEntries[variableSetter]=ent 184 | 185 | if len(self.parameterSetters) > 0: 186 | self.buttonSaveParameters = Button(self.frameParameters,width=50,height=1, 187 | command=self.saveParametersCmd,text="Save parameters to the running model",state=DISABLED) 188 | self.showHelp(self.buttonSaveParameters, 189 | "Saves the parameter values.\nNot all values may take effect on a running model\nA model reset might be required.") 190 | self.buttonSaveParameters.pack(side='top',padx=5,pady=5) 191 | self.buttonSaveParametersAndReset = Button(self.frameParameters,width=50,height=1, 192 | command=self.saveParametersAndResetCmd,text="Save parameters to the model and reset the model") 193 | self.showHelp(self.buttonSaveParametersAndReset,"Saves the given parameter values and resets the model") 194 | self.buttonSaveParametersAndReset.pack(side='top',padx=5,pady=5) 195 | 196 | # <<<<< Init >>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>> 197 | 198 | def setStatusStr(self,newStatus): 199 | self.statusStr = newStatus 200 | self.statusText.set(self.statusStr) 201 | 202 | # model control functions for changing parameters 203 | def changeStepSize(self,val): 204 | self.stepSize = int(val) 205 | 206 | def changeStepDelay(self,val): 207 | self.timeInterval= int(val) 208 | 209 | def saveParametersCmd(self): 210 | for variableSetter in self.parameterSetters: 211 | variableSetter(float(self.varEntries[variableSetter].get())) 212 | self.setStatusStr("New parameter values have been set") 213 | 214 | def saveParametersAndResetCmd(self): 215 | self.saveParametersCmd() 216 | self.resetModel() 217 | 218 | # <<<< runEvent >>>>> 219 | # This event is envoked when "Run" button is clicked. 220 | def runEvent(self): 221 | self.running = not self.running 222 | if self.running: 223 | self.rootWindow.after(self.timeInterval,self.stepModel) 224 | self.runPauseString.set("Pause") 225 | self.buttonStep.configure(state=DISABLED) 226 | self.buttonReset.configure(state=DISABLED) 227 | if len(self.parameterSetters) > 0: 228 | self.buttonSaveParameters.configure(state=NORMAL) 229 | self.buttonSaveParametersAndReset.configure(state=DISABLED) 230 | else: 231 | self.runPauseString.set("Continue Run") 232 | self.buttonStep.configure(state=NORMAL) 233 | self.buttonReset.configure(state=NORMAL) 234 | if len(self.parameterSetters) > 0: 235 | self.buttonSaveParameters.configure(state=NORMAL) 236 | self.buttonSaveParametersAndReset.configure(state=NORMAL) 237 | 238 | def stepModel(self): 239 | if self.running: 240 | self.modelStepFunc() 241 | self.currentStep += 1 242 | self.setStatusStr("Step "+str(self.currentStep)) 243 | self.status.configure(foreground='black') 244 | if (self.currentStep) % self.stepSize == 0: 245 | self.drawModel() 246 | self.rootWindow.after(int(self.timeInterval*1.0/self.stepSize),self.stepModel) 247 | 248 | def stepOnce(self): 249 | self.running = False 250 | self.runPauseString.set("Continue Run") 251 | self.modelStepFunc() 252 | self.currentStep += 1 253 | self.setStatusStr("Step "+str(self.currentStep)) 254 | self.drawModel() 255 | if len(self.parameterSetters) > 0: 256 | self.buttonSaveParameters.configure(state=NORMAL) 257 | 258 | def resetModel(self): 259 | self.running = False 260 | self.runPauseString.set("Run") 261 | self.modelInitFunc() 262 | self.currentStep = 0; 263 | self.setStatusStr("Model has been reset") 264 | self.drawModel() 265 | 266 | def drawModel(self): 267 | plt.ion() #SM 3/26/2020 268 | if self.modelFigure == None or self.modelFigure.canvas.manager.window == None: 269 | self.modelFigure = plt.figure() #SM 3/26/2020 270 | self.modelDrawFunc() 271 | self.modelFigure.canvas.manager.window.update() 272 | plt.show() # bug fix by Hiroki Sayama in 2016 #SM 3/26/2020 273 | 274 | def start(self,func=[]): 275 | if len(func)==3: 276 | self.modelInitFunc = func[0] 277 | self.modelDrawFunc = func[1] 278 | self.modelStepFunc = func[2] 279 | if (self.modelStepFunc.__doc__ != None and len(self.modelStepFunc.__doc__)>0): 280 | self.showHelp(self.buttonStep,self.modelStepFunc.__doc__.strip()) 281 | if (self.modelInitFunc.__doc__ != None and len(self.modelInitFunc.__doc__)>0): 282 | self.textInformation.config(state=NORMAL) 283 | self.textInformation.delete(1.0, END) 284 | self.textInformation.insert(END, self.modelInitFunc.__doc__.strip()) 285 | self.textInformation.config(state=DISABLED) 286 | 287 | self.modelInitFunc() 288 | self.drawModel() 289 | self.rootWindow.mainloop() 290 | 291 | def quitGUI(self): 292 | self.running = False # HS 06/29/2020 293 | self.rootWindow.quit() 294 | plt.close('all') # HS 06/29/2020 295 | self.rootWindow.destroy() 296 | 297 | def showHelp(self, widget,text): 298 | def setText(self): 299 | self.statusText.set(text) 300 | self.status.configure(foreground='blue') 301 | def showHelpLeave(self): 302 | self.statusText.set(self.statusStr) 303 | self.status.configure(foreground='black') 304 | widget.bind("", lambda e : setText(self)) 305 | widget.bind("", lambda e : showHelpLeave(self)) -------------------------------------------------------------------------------- /qoppav2.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Wed Jul 31 16:51:21 2024 4 | 5 | @author: ektop 6 | """ 7 | 8 | 9 | import matplotlib 10 | matplotlib.use('TkAgg') 11 | from pylab import * 12 | import networkx as nx 13 | from math import pi 14 | import numpy as np 15 | 16 | 17 | 18 | import scipy 19 | import numpy as np 20 | from scipy import misc 21 | import numpy as np 22 | import scipy.linalg as la 23 | 24 | from matplotlib import pyplot as plt # For image viewing 25 | 26 | from matplotlib import colors 27 | from matplotlib import ticker 28 | from matplotlib.colors import LinearSegmentedColormap 29 | 30 | from matplotlib.collections import LineCollection 31 | from matplotlib.colors import ListedColormap, BoundaryNorm 32 | 33 | 34 | 35 | from random import random as rand 36 | from random import uniform 37 | 38 | alpha = 1 # coupling strength 39 | Dt = 0.01 # Delta t 40 | 41 | # Define constants for the mass (m) of the oscillators if relevant 42 | m = 1 # Assume mass as 1 for simplicity 43 | 44 | # Initialize the network and the next network state 45 | 46 | def initialize(): 47 | global g, nextg, hilbert_size 48 | 49 | 50 | 51 | 52 | n = 3 53 | g = nx.grid_graph(dim=[n,n]) 54 | 55 | 56 | 57 | # g = nx.karate_club_graph() 58 | for i in list(g.nodes()): 59 | g.node[i]['theta'] = 2 * pi * np.random.random() 60 | g.node[i]['omega'] = 1. + uniform(-0.05, 0.05) 61 | nextg = g.copy() 62 | 63 | # Visualize the network 64 | def observe(): 65 | global g, nextg, grid2d 66 | subplot(1,2,1) 67 | cla() 68 | nx.draw(g, cmap = cm.hsv, vmin = -1, vmax = 1, 69 | node_color = [np.sin(g.node[i]['theta']) for i in list(g.nodes())], 70 | pos = nx.spring_layout(g) ) 71 | axis('image') 72 | 73 | subplot(1,2,2) 74 | cla() 75 | 76 | plot([np.cos(g.node[i]['theta']) for i in list(g.nodes())], 77 | [np.sin(g.node[i]['theta']) for i in list(g.nodes())], '.') 78 | axis('image') 79 | 80 | axis([-1.1,1.1,-1.1,1.1]) 81 | # Define the Gauss/Mouse map transformation 82 | def gauss_mouse_map(phase): 83 | return np.sin(phase) 84 | 85 | 86 | 87 | # Update the network state 88 | def update(): 89 | global g, nextg, chaotic_numbers_data, timestamps, frequency_shifts, koppa_values, action_derivative_values 90 | chaotic_numbers = [] 91 | 92 | num_nodes = len(g.nodes()) 93 | angular_accelerations = np.zeros(num_nodes) 94 | action_derivative = 0 # Initialize action derivative for this timestep 95 | 96 | # Store previous angular velocities 97 | previous_angular_velocities = np.array([g.nodes[i]['omega'] for i in g.nodes()]) 98 | 99 | # Create a node to index mapping 100 | node_to_index = {node: idx for idx, node in enumerate(g.nodes())} 101 | 102 | for i in g.nodes(): 103 | idx = node_to_index[i] # Get the index for the current node 104 | theta_i = g.nodes[i]['theta'] 105 | omega_i = g.nodes[i]['omega'] 106 | 107 | # Calculate next angular momentum using Euler's method 108 | nextg.nodes[i]['theta'] = theta_i + omega_i * Dt + (alpha * ( 109 | np.sum(np.sin(g.nodes[j]['theta'] - theta_i) for j in g.neighbors(i)) 110 | / g.degree(i))) * Dt 111 | 112 | # Update angular acceleration 113 | angular_accelerations[idx] = (nextg.nodes[i]['theta'] - theta_i) / Dt # This is a simple approximation 114 | 115 | chaotic_number = gauss_mouse_map(g.nodes[i]['theta']) 116 | chaotic_numbers.append(chaotic_number) 117 | 118 | # Now compute the derivative of action 119 | for i in range(num_nodes): 120 | action_derivative += 0.5 * m * previous_angular_velocities[i] * angular_accelerations[i] 121 | 122 | action_derivative_values.append(action_derivative) # Store action derivative over time 123 | 124 | # Calculate frequency shifts 125 | if len(chaotic_numbers_data) > 0: 126 | previous_chaotic_numbers = chaotic_numbers_data[-1] 127 | frequency_shift = [chaotic_numbers[j] - previous_chaotic_numbers[j] for j in range(len(chaotic_numbers))] 128 | frequency_shifts.append(np.mean(frequency_shift)) # Store the average frequency shift over time 129 | else: 130 | frequency_shifts.append(0) # No shift initially 131 | 132 | # Calculate algebraic connectivity (koppa) 133 | laplacian = nx.laplacian_matrix(g).toarray() 134 | eigenvalues = np.linalg.eigvals(laplacian) 135 | koppa = np.sort(eigenvalues)[1] # Second smallest eigenvalue 136 | koppa_values.append(koppa) 137 | 138 | g, nextg = nextg, g 139 | chaotic_numbers_data.append(chaotic_numbers) 140 | timestamps.append(len(chaotic_numbers_data)) 141 | 142 | # Initialize and update the network state 143 | def initialize_and_update(): 144 | initialize() 145 | update() 146 | 147 | import pycxsimulator 148 | 149 | # Run the simulation 150 | chaotic_numbers_data = [] 151 | frequency_shifts = [] 152 | timestamps = [] 153 | koppa_values = [] 154 | action_derivative_values = [] # List to store action derivatives over time 155 | pycxsimulator.GUI().start(func=[initialize, observe, update]) 156 | 157 | # Create scatter plot of chaotic number values vs timestamps 158 | plt.figure(figsize=(12, 5)) 159 | for i, chaotic_numbers in enumerate(chaotic_numbers_data): 160 | colors = ['r' if num >= 0 else 'b' for num in chaotic_numbers] 161 | plt.scatter([timestamps[i]] * len(chaotic_numbers), chaotic_numbers, color=colors, alpha=0.5) 162 | 163 | plt.xlabel('Timestamp') 164 | plt.ylabel('Chaotic Number Value') 165 | plt.title('Scatter Plot of Chaotic Number Values vs Timestamp') 166 | plt.show() 167 | 168 | # Create scatter plot of frequency shifts 169 | plt.figure(figsize=(12, 5)) 170 | for i, shift in enumerate(frequency_shifts): 171 | plt.scatter(timestamps[i], shift, color='g', alpha=0.5) # Use just `timestamps[i]` for y values 172 | 173 | plt.xlabel('Timestamp') 174 | plt.ylabel('Average Frequency Shift') 175 | plt.title('Scatter Plot of Frequency Shifts vs Timestamp') 176 | plt.show() 177 | 178 | # Plot the trend of wavelength shifts vs koppa 179 | plt.figure(figsize=(12, 5)) 180 | plt.plot(timestamps, koppa_values, marker='o', linestyle='-') 181 | plt.title('Algebraic Connectivity Koppa over Time') 182 | plt.xlabel('Timestamp') 183 | plt.ylabel('Algebraic Connectivity (Koppa)') 184 | plt.grid() 185 | plt.show() 186 | 187 | plt.figure(figsize=(12, 5)) 188 | plt.scatter(koppa_values, frequency_shifts, color='purple', alpha=0.5) 189 | plt.title('Wavelength Shifts vs Algebraic Connectivity Koppa') 190 | plt.xlabel('Algebraic Connectivity (Koppa)') 191 | plt.ylabel('Average Frequency Shift') 192 | plt.grid() 193 | plt.show() 194 | 195 | # New: Plot action derivatives over time 196 | plt.figure(figsize=(12, 5)) 197 | plt.plot(timestamps, action_derivative_values, marker='o', linestyle='-') 198 | plt.title('Action Derivative over Time') 199 | plt.xlabel('Timestamp') 200 | plt.ylabel('Action Derivative') 201 | plt.grid() 202 | plt.show() 203 | 204 | # New: Plot frequency shifts vs action derivatives 205 | plt.figure(figsize=(12, 5)) 206 | plt.scatter(action_derivative_values, frequency_shifts, color='orange', alpha=0.5) 207 | plt.title('Frequency Shifts vs Action Derivative') 208 | plt.xlabel('Action Derivative') 209 | plt.ylabel('Average Frequency Shift') 210 | plt.grid() 211 | plt.show() -------------------------------------------------------------------------------- /qoppav4.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Wed Jul 31 17:15:19 2024 4 | 5 | @author: ektop 6 | """ 7 | 8 | import networkx as nx 9 | import numpy as np 10 | from random import uniform 11 | from math import pi 12 | import matplotlib.pyplot as plt 13 | from mpl_toolkits.mplot3d import Axes3D 14 | 15 | alpha = 1 # coupling strength 16 | Dt = 0.01 # Delta t 17 | m = 1 # Assume mass as 1 for simplicity 18 | 19 | def initialize(): 20 | global g, nextg 21 | g = nx.karate_club_graph() 22 | for i in list(g.nodes()): 23 | g.node[i]['theta'] = 2 * pi * np.random.random() 24 | g.node[i]['omega'] = 1. + uniform(-0.05, 0.05) 25 | nextg = g.copy() 26 | 27 | def observe(): 28 | global g 29 | plt.clf() 30 | nx.draw(g, cmap=plt.cm.hsv, vmin=-1, vmax=1, 31 | node_color=[np.sin(g.node[i]['theta']) for i in list(g.nodes())], 32 | pos=nx.spring_layout(g)) 33 | plt.title('Network Visualization') 34 | plt.show() 35 | 36 | def gauss_mouse_map(phase): 37 | return np.sin(phase) 38 | 39 | def update(): 40 | global g, nextg, chaotic_numbers_data, timestamps, frequency_shifts, action_derivative_values 41 | chaotic_numbers = [] 42 | angular_accelerations = np.zeros(len(g.nodes())) 43 | action_derivative = 0 # Initialize action derivative for this timestep 44 | previous_angular_velocities = np.array([g.node[i]['omega'] for i in g.nodes()]) 45 | 46 | for i in list(g.nodes()): 47 | theta_i = g.node[i]['theta'] 48 | omega_i = g.node[i]['omega'] 49 | 50 | # Update angular position using Euler's method 51 | nextg.node[i]['theta'] = theta_i + omega_i * Dt + (alpha * ( 52 | np.sum(np.sin(g.node[j]['theta'] - theta_i) for j in g.neighbors(i)) 53 | / g.degree(i))) * Dt 54 | 55 | angular_accelerations[i] = (nextg.node[i]['theta'] - theta_i) / Dt 56 | 57 | chaotic_number = gauss_mouse_map(g.node[i]['theta']) 58 | chaotic_numbers.append(chaotic_number) 59 | 60 | # Compute derivative of action 61 | for i in range(len(g.nodes())): 62 | action_derivative += 0.5 * m * previous_angular_velocities[i] * angular_accelerations[i] 63 | 64 | action_derivative_values.append(action_derivative) # Store action derivative over time 65 | # Calculate frequency shifts 66 | if len(chaotic_numbers_data) > 0: 67 | previous_chaotic_numbers = chaotic_numbers_data[-1] 68 | frequency_shift = [chaotic_numbers[j] - previous_chaotic_numbers[j] for j in range(len(chaotic_numbers))] 69 | frequency_shifts.append(np.mean(frequency_shift)) # Store the average frequency shift over time 70 | else: 71 | frequency_shifts.append(0) # No shift initially 72 | 73 | 74 | # Update the states 75 | g, nextg = nextg, g 76 | chaotic_numbers_data.append(chaotic_numbers) 77 | timestamps.append(len(chaotic_numbers_data)) 78 | 79 | def initialize_and_update(): 80 | initialize() 81 | update() 82 | 83 | import pycxsimulator 84 | 85 | # Initialize lists to store data 86 | chaotic_numbers_data = [] 87 | frequency_shifts = [] 88 | action_derivative_values = [] # List to store action derivatives over time 89 | timestamps = [] # Initialize timestamps 90 | 91 | # Run the simulation 92 | pycxsimulator.GUI().start(func=[initialize, observe, update]) 93 | 94 | 95 | # Create scatter plot of chaotic number values vs timestamps 96 | plt.figure(figsize=(12, 5)) 97 | for i, chaotic_numbers in enumerate(chaotic_numbers_data): 98 | colors = ['r' if num >= 0 else 'b' for num in chaotic_numbers] 99 | plt.scatter([timestamps[i]] * len(chaotic_numbers), chaotic_numbers, color=colors, alpha=0.5) 100 | 101 | plt.xlabel('Timestamp') 102 | plt.ylabel('Chaotic Number Value') 103 | plt.title('Scatter Plot of Chaotic Number Values vs Timestamp') 104 | plt.show() 105 | 106 | 107 | # Create scatter plot of frequency shifts 108 | plt.figure(figsize=(12, 5)) 109 | for i, shift in enumerate(frequency_shifts): 110 | plt.scatter(timestamps[i], shift, color='g', alpha=0.5) 111 | 112 | plt.xlabel('Timestamp') 113 | plt.ylabel('Average Frequency Shift') 114 | plt.title('Scatter Plot of Frequency Shifts vs Timestamp') 115 | plt.show() 116 | 117 | 118 | # New: Plot action derivatives over time 119 | plt.figure(figsize=(12, 5)) 120 | plt.plot(timestamps, action_derivative_values, marker='o', linestyle='-') 121 | plt.title('Action Derivative over Time') 122 | plt.xlabel('Timestamp') 123 | plt.ylabel('Action Derivative') 124 | plt.grid() 125 | plt.show() 126 | 127 | # New: Create scatter plot of action derivative vs chaotic numbers 128 | plt.figure(figsize=(12, 5)) 129 | for i, chaotic_numbers in enumerate(chaotic_numbers_data): 130 | for j in range(len(chaotic_numbers)): 131 | plt.scatter(action_derivative_values[i], chaotic_numbers[j], color='red', alpha=0.5) 132 | 133 | plt.title('Chaotic Numbers vs Action Derivative') 134 | plt.xlabel('Action Derivative') 135 | plt.ylabel('Chaotic Number Value') 136 | plt.grid() 137 | plt.show() 138 | 139 | 140 | # New: Plot frequency shifts vs actions 141 | plt.figure(figsize=(12, 5)) 142 | plt.scatter(action_derivative_values, frequency_shifts, color='orange', alpha=0.5) 143 | plt.title('Frequency Shifts vs Action Derivative') 144 | plt.xlabel('Action Derivative') 145 | plt.ylabel('Average Frequency Shift') 146 | plt.grid() 147 | plt.show() 148 | 149 | 150 | 151 | 152 | 153 | # Assuming you have the following variables defined 154 | # timestamps, action_derivative_values, frequency_shifts 155 | 156 | # Create a figure 157 | fig = plt.figure(figsize=(12, 8)) 158 | 159 | # Create a 3D scatter plot 160 | ax = fig.add_subplot(111, projection='3d') 161 | 162 | # Create a scatter plot, using timestamps, action derivatives, and chaotic numbers 163 | scatter = ax.scatter(timestamps, action_derivative_values, frequency_shifts, 164 | c=action_derivative_values, cmap='viridis', alpha=0.5) 165 | 166 | # Add titles and labels 167 | ax.set_title('3D Visualization of Action Derivative, Frequency Shift, va Timestamps') 168 | ax.set_xlabel('Timestamp') 169 | ax.set_ylabel('Action Derivative') 170 | ax.set_zlabel('Frequency Shift Value') 171 | 172 | # Show color bar for reference 173 | plt.colorbar(scatter, label='Action Derivative') 174 | 175 | # Show the plot 176 | plt.show() 177 | 178 | 179 | 180 | 181 | -------------------------------------------------------------------------------- /scalefreequantum.py: -------------------------------------------------------------------------------- 1 | # -*- coding: utf-8 -*- 2 | """ 3 | Created on Sun May 28 01:18:22 2023 4 | 5 | @author: ektop 6 | """ 7 | 8 | # -*- coding: utf-8 -*- 9 | """ 10 | Created on Tue Mar 2 19:01:57 2021 11 | 12 | @author: cosmi 13 | """ 14 | 15 | import matplotlib 16 | matplotlib.use('TkAgg') 17 | from pylab import * 18 | import networkx as nx 19 | 20 | import numpy as np 21 | 22 | from pygsp import graphs 23 | import matplotlib.pyplot as plt 24 | 25 | m0 = 4 # number of nodes in initial condition 26 | m = 2 # number of edges per new node 27 | 28 | global grid2d 29 | 30 | counter = 0 31 | 32 | def initialize(): 33 | global g, nextg, counter, grid2d 34 | g = nx.complete_graph(m0) 35 | g.pos = nx.spring_layout(g) 36 | nextg = g.copy() 37 | 38 | 39 | xdata = [] 40 | ydata = [] 41 | 42 | grid2d = [] 43 | 44 | def observe1(): 45 | global g, nextg, counter, grid2d 46 | 47 | 48 | 49 | subplot(1,2,1) 50 | cla() 51 | nx.draw(g) 52 | 53 | #subplot(1,2,2) 54 | #cla() 55 | #plot(xdata, ydata,'o',alpha = 0.05) 56 | #axis('image') 57 | 58 | 59 | def observe2(): 60 | global g, nextg, counter, grid2d 61 | 62 | subplot(1,2,2) 63 | grid2d = graphs.Graph.from_networkx(g) 64 | 65 | plt.imshow(grid2d.A.todense()) 66 | axis('image') 67 | 68 | 69 | 70 | 71 | def pref_select(nds): 72 | global g 73 | r = uniform(0, sum(g.degree(i) for i in nds)) 74 | x = 0 75 | for i in nds: 76 | x += g.degree(i) 77 | if r <= x: 78 | return i 79 | 80 | 81 | def update(): 82 | global g, nextg, counter, grid2d 83 | counter += 1 84 | if counter % 20 == 0: 85 | nds = g.nodes() 86 | newcomer = max(nds) + 1 87 | 88 | for i in range(m): 89 | j = pref_select(nds) 90 | g.add_edge(newcomer, j) 91 | unsaturated_b = g.nodes() 92 | list(unsaturated_b).remove(j) 93 | 94 | xdata.append(g.degree(i)) 95 | ccs = nx.connected_components(g) 96 | ydata.append(max(len(cc) for cc in ccs)) 97 | #xdata.append(g.degree(i)); ydata.append(g.degree(j)) 98 | #xdata.append(g.degree(j)); ydata.append(g.degree(i)) 99 | #g.pos[newcomer] = (0, 0) # simulation of node movement 100 | g, nextg = nextg, g 101 | 102 | grid2d = graphs.Graph.from_networkx(g) 103 | 104 | 105 | 106 | #g.pos = nx.spring_layout(pos = g.pos, iterations = 5) 107 | 108 | import pycxsimulator2plots 109 | 110 | pycxsimulator2plots.GUI().start(func=[initialize, observe1, observe2, update]) 111 | 112 | 113 | 114 | 115 | 116 | 117 | # for percolation search at end of run 118 | pycxsimulator2plots.GUI().quitGUI 119 | 120 | 121 | print(grid2d.W.toarray()) 122 | print(grid2d.signals) 123 | 124 | print(grid2d) 125 | 126 | 127 | 128 | grid2d.compute_fourier_basis() 129 | 130 | grid2d.set_coordinates() 131 | grid2d.plot() 132 | 133 | plt.imshow(grid2d.A.todense()) 134 | 135 | 136 | 137 | # plot spectrum 138 | fig, ax = plt.subplots(1, 1, figsize=(7,7)) 139 | ax.plot(grid2d.e) 140 | ax.set_xlabel('eigenvalue index (i)') 141 | ax.set_ylabel('eigenvalue ($\lambda_{i}$)') 142 | ax.set_title('2D-grid spectrum'); 143 | 144 | 145 | #fiedler vector highlighted graph 146 | grid2d.plot_signal(grid2d.U[:,1]) 147 | 148 | 149 | #plot all eigenvectors as network graph frames 150 | 151 | fig, axes = plt.subplots(2, 3, figsize=(10, 6.6)) 152 | count = 0 153 | for j in range(2): 154 | for i in range(3): 155 | grid2d.plot_signal(grid2d.U[:, count*1], ax=axes[j,i],colorbar=False) 156 | axes[j,i].set_xticks([]) 157 | axes[j,i].set_yticks([]) 158 | axes[j,i].set_title(f'Eigvec {count*1+1}') 159 | count+=1 160 | fig.tight_layout() 161 | 162 | 163 | 164 | 165 | 166 | -------------------------------------------------------------------------------- /votermodel.py: -------------------------------------------------------------------------------- 1 | 2 | import matplotlib 3 | matplotlib.use('TkAgg') 4 | from pylab import * 5 | import networkx as nx 6 | import random as rd 7 | 8 | def initialize(): 9 | global g 10 | g = nx.karate_club_graph() 11 | for i in g.nodes(): 12 | g.node[i]['state'] = 1 if random() < .5 else 0 13 | 14 | 15 | def observe(): 16 | global g 17 | cla() 18 | nx.draw(g, cmap = cm.hsv, vmin = -1, vmax = 1, 19 | node_color = [g.node[i]['state'] for i in g.nodes()], 20 | pos = nx.spring_layout(g) ) 21 | 22 | 23 | def update(): 24 | global g 25 | listener = rd.choice(g.nodes()) 26 | speaker = rd.choice(g.neighbors(listener)) 27 | g.node[listener]['state'] = g.node[speaker]['state'] 28 | g.add_edge(0,1) 29 | g[0]['visited'] = True 30 | g.neighbors(0) 31 | ['visited', 1] 32 | 33 | 34 | import pycxsimulator 35 | 36 | pycxsimulator.GUI().start(func=[initialize, observe, update]) 37 | 38 | --------------------------------------------------------------------------------