Minor title changes

Change pie chart font for consistency
Simplify plot title by removing CAN ID
2026-07-24 08:53:40 +02:00 · 2026-07-24 08:53:29 +02:00 · 2026-07-23 16:16:12 +02:00 · 2026-07-23 16:03:47 +02:00 · 2026-07-23 16:01:34 +02:00 · 2026-07-23 15:37:50 +02:00
16 changed files with 2027 additions and 253 deletions
@@ -0,0 +1,9 @@
 # Copyright
 Copyright © 2026 Erick Ahmed
 The source code in this repository is licensed under the **GNU Affero General Public License v3.0 or later (AGPL-3.0-or-later)**.
 A copy of the license is provided in the `LICENSE` file. If any discrepancy exists between this notice and the `LICENSE` file, the `LICENSE` file shall prevail.
 Any third-party components included in this repository at any point during developement remain the property of their respective copyright holders and are subject to their own license terms.
@@ -1,106 +1,94 @@
-GNU GENERAL PUBLIC LICENSE
+GNU AFFERO GENERAL PUBLIC LICENSE
-                       Version 3, 29 June 2007
+   Version 3, 19 November 2007
- Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
+Copyright (C) 2007 Free Software Foundation, Inc. <http://fsf.org/>
- Everyone is permitted to copy and distribute verbatim copies
+Everyone is permitted to copy and distribute verbatim copies
- of this license document, but changing it is not allowed.
+of this license document, but changing it is not allowed.
-                            Preamble
+        Preamble
-  The GNU General Public License is a free, copyleft license for
+The GNU Affero General Public License is a free, copyleft license for
-software and other kinds of works.
+software and other kinds of works, specifically designed to ensure
 cooperation with the community in the case of network server software.
-  The licenses for most software and other practical works are designed
+The licenses for most software and other practical works are designed
 to take away your freedom to share and change the works.  By contrast,
-the GNU General Public License is intended to guarantee your freedom to
+our General Public Licenses are intended to guarantee your freedom to
 share and change all versions of a program--to make sure it remains free
-software for all its users.  We, the Free Software Foundation, use the
+software for all its users.
 GNU General Public License for most of our software; it applies also to
 any other work released this way by its authors.  You can apply it to
 your programs, too.
-  When we speak of free software, we are referring to freedom, not
+When we speak of free software, we are referring to freedom, not
 price.  Our General Public Licenses are designed to make sure that you
 have the freedom to distribute copies of free software (and charge for
 them if you wish), that you receive source code or can get it if you
 want it, that you can change the software or use pieces of it in new
 free programs, and that you know you can do these things.
-  To protect your rights, we need to prevent others from denying you
+Developers that use our General Public Licenses protect your rights
-these rights or asking you to surrender the rights.  Therefore, you have
+with two steps: (1) assert copyright on the software, and (2) offer
-certain responsibilities if you distribute copies of the software, or if
+you this License which gives you legal permission to copy, distribute
-you modify it: responsibilities to respect the freedom of others.
+and/or modify the software.
-  For example, if you distribute copies of such a program, whether
+A secondary benefit of defending all users' freedom is that
-gratis or for a fee, you must pass on to the recipients the same
+improvements made in alternate versions of the program, if they
-freedoms that you received.  You must make sure that they, too, receive
+receive widespread use, become available for other developers to
-or can get the source code.  And you must show them these terms so they
+incorporate.  Many developers of free software are heartened and
-know their rights.
+encouraged by the resulting cooperation.  However, in the case of
 software used on network servers, this result may fail to come about.
 The GNU General Public License permits making a modified version and
 letting the public access it on a server without ever releasing its
 source code to the public.
-  Developers that use the GNU GPL protect your rights with two steps:
+The GNU Affero General Public License is designed specifically to
-(1) assert copyright on the software, and (2) offer you this License
+ensure that, in such cases, the modified source code becomes available
-giving you legal permission to copy, distribute and/or modify it.
+to the community.  It requires the operator of a network server to
 provide the source code of the modified version running there to the
 users of that server.  Therefore, public use of a modified version, on
 a publicly accessible server, gives the public access to the source
 code of the modified version.
-  For the developers' and authors' protection, the GPL clearly explains
+An older license, called the Affero General Public License and
-that there is no warranty for this free software.  For both users' and
+published by Affero, was designed to accomplish similar goals.  This is
-authors' sake, the GPL requires that modified versions be marked as
+a different license, not a version of the Affero GPL, but Affero has
-changed, so that their problems will not be attributed erroneously to
+released a new version of the Affero GPL which permits relicensing under
-authors of previous versions.
+this license.
-  Some devices are designed to deny users access to install or run
+The precise terms and conditions for copying, distribution and
 modified versions of the software inside them, although the manufacturer
 can do so.  This is fundamentally incompatible with the aim of
 protecting users' freedom to change the software.  The systematic
 pattern of such abuse occurs in the area of products for individuals to
 use, which is precisely where it is most unacceptable.  Therefore, we
 have designed this version of the GPL to prohibit the practice for those
 products.  If such problems arise substantially in other domains, we
 stand ready to extend this provision to those domains in future versions
 of the GPL, as needed to protect the freedom of users.
  Finally, every program is threatened constantly by software patents.
 States should not allow patents to restrict development and use of
 software on general-purpose computers, but in those that do, we wish to
 avoid the special danger that patents applied to a free program could
 make it effectively proprietary.  To prevent this, the GPL assures that
 patents cannot be used to render the program non-free.
  The precise terms and conditions for copying, distribution and
 modification follow.
-                       TERMS AND CONDITIONS
+   TERMS AND CONDITIONS
-  0. Definitions.
+0. Definitions.
-  "This License" refers to version 3 of the GNU General Public License.
+"This License" refers to version 3 of the GNU Affero General Public License.
-  "Copyright" also means copyright-like laws that apply to other kinds of
+"Copyright" also means copyright-like laws that apply to other kinds of
 works, such as semiconductor masks.
-  "The Program" refers to any copyrightable work licensed under this
+"The Program" refers to any copyrightable work licensed under this
 License.  Each licensee is addressed as "you".  "Licensees" and
 "recipients" may be individuals or organizations.
-  To "modify" a work means to copy from or adapt all or part of the work
+To "modify" a work means to copy from or adapt all or part of the work
 in a fashion requiring copyright permission, other than the making of an
 exact copy.  The resulting work is called a "modified version" of the
 earlier work or a work "based on" the earlier work.
-  A "covered work" means either the unmodified Program or a work based
+A "covered work" means either the unmodified Program or a work based
 on the Program.
-  To "propagate" a work means to do anything with it that, without
+To "propagate" a work means to do anything with it that, without
 permission, would make you directly or secondarily liable for
 infringement under applicable copyright law, except executing it on a
 computer or modifying a private copy.  Propagation includes copying,
 distribution (with or without modification), making available to the
 public, and in some countries other activities as well.
-  To "convey" a work means any kind of propagation that enables other
+To "convey" a work means any kind of propagation that enables other
 parties to make or receive copies.  Mere interaction with a user through
 a computer network, with no transfer of a copy, is not conveying.
-  An interactive user interface displays "Appropriate Legal Notices"
+An interactive user interface displays "Appropriate Legal Notices"
 to the extent that it includes a convenient and prominently visible
 feature that (1) displays an appropriate copyright notice, and (2)
 tells the user that there is no warranty for the work (except to the
@@ -109,18 +97,18 @@ work under this License, and how to view a copy of this License.  If
 the interface presents a list of user commands or options, such as a
 menu, a prominent item in the list meets this criterion.
-  1. Source Code.
+1. Source Code.
-  The "source code" for a work means the preferred form of the work
+The "source code" for a work means the preferred form of the work
 for making modifications to it.  "Object code" means any non-source
 form of a work.
-  A "Standard Interface" means an interface that either is an official
+A "Standard Interface" means an interface that either is an official
 standard defined by a recognized standards body, or, in the case of
 interfaces specified for a particular programming language, one that
 is widely used among developers working in that language.
-  The "System Libraries" of an executable work include anything, other
+The "System Libraries" of an executable work include anything, other
 than the work as a whole, that (a) is included in the normal form of
 packaging a Major Component, but which is not part of that Major
 Component, and (b) serves only to enable use of the work with that
@@ -131,7 +119,7 @@ implementation is available to the public in source code form.  A
 (if any) on which the executable work runs, or a compiler used to
 produce the work, or an object code interpreter used to run it.
-  The "Corresponding Source" for a work in object code form means all
+The "Corresponding Source" for a work in object code form means all
 the source code needed to generate, install, and (for an executable
 work) run the object code and to modify the work, including scripts to
 control those activities.  However, it does not include the work's
@@ -144,16 +132,16 @@ linked subprograms that the work is specifically designed to require,
 such as by intimate data communication or control flow between those
 subprograms and other parts of the work.
-  The Corresponding Source need not include anything that users
+The Corresponding Source need not include anything that users
 can regenerate automatically from other parts of the Corresponding
 Source.
-  The Corresponding Source for a work in source code form is that
+The Corresponding Source for a work in source code form is that
 same work.
-  2. Basic Permissions.
+2. Basic Permissions.
-  All rights granted under this License are granted for the term of
+All rights granted under this License are granted for the term of
 copyright on the Program, and are irrevocable provided the stated
 conditions are met.  This License explicitly affirms your unlimited
 permission to run the unmodified Program.  The output from running a
@@ -161,7 +149,7 @@ covered work is covered by this License only if the output, given its
 content, constitutes a covered work.  This License acknowledges your
 rights of fair use or other equivalent, as provided by copyright law.
-  You may make, run and propagate covered works that you do not
+You may make, run and propagate covered works that you do not
 convey, without conditions so long as your license otherwise remains
 in force.  You may convey covered works to others for the sole purpose
 of having them make modifications exclusively for you, or provide you
@@ -172,19 +160,19 @@ for you must do so exclusively on your behalf, under your direction
 and control, on terms that prohibit them from making any copies of
 your copyrighted material outside their relationship with you.
-  Conveying under any other circumstances is permitted solely under
+Conveying under any other circumstances is permitted solely under
 the conditions stated below.  Sublicensing is not allowed; section 10
 makes it unnecessary.
-  3. Protecting Users' Legal Rights From Anti-Circumvention Law.
+3. Protecting Users' Legal Rights From Anti-Circumvention Law.
-  No covered work shall be deemed part of an effective technological
+No covered work shall be deemed part of an effective technological
 measure under any applicable law fulfilling obligations under article
 11 of the WIPO copyright treaty adopted on 20 December 1996, or
 similar laws prohibiting or restricting circumvention of such
 measures.
-  When you convey a covered work, you waive any legal power to forbid
+When you convey a covered work, you waive any legal power to forbid
 circumvention of technological measures to the extent such circumvention
 is effected by exercising rights under this License with respect to
 the covered work, and you disclaim any intention to limit operation or
@@ -192,9 +180,9 @@ modification of the work as a means of enforcing, against the work's
 users, your or third parties' legal rights to forbid circumvention of
 technological measures.
-  4. Conveying Verbatim Copies.
+4. Conveying Verbatim Copies.
-  You may convey verbatim copies of the Program's source code as you
+You may convey verbatim copies of the Program's source code as you
 receive it, in any medium, provided that you conspicuously and
 appropriately publish on each copy an appropriate copyright notice;
 keep intact all notices stating that this License and any
@@ -202,37 +190,37 @@ non-permissive terms added in accord with section 7 apply to the code;
 keep intact all notices of the absence of any warranty; and give all
 recipients a copy of this License along with the Program.
-  You may charge any price or no price for each copy that you convey,
+You may charge any price or no price for each copy that you convey,
 and you may offer support or warranty protection for a fee.
-  5. Conveying Modified Source Versions.
+5. Conveying Modified Source Versions.
-  You may convey a work based on the Program, or the modifications to
+You may convey a work based on the Program, or the modifications to
 produce it from the Program, in the form of source code under the
 terms of section 4, provided that you also meet all of these conditions:
-    a) The work must carry prominent notices stating that you modified
+a) The work must carry prominent notices stating that you modified
-    it, and giving a relevant date.
+it, and giving a relevant date.
-    b) The work must carry prominent notices stating that it is
+b) The work must carry prominent notices stating that it is
-    released under this License and any conditions added under section
+released under this License and any conditions added under section
-    7.  This requirement modifies the requirement in section 4 to
+7.  This requirement modifies the requirement in section 4 to
-    "keep intact all notices".
+"keep intact all notices".
-    c) You must license the entire work, as a whole, under this
+c) You must license the entire work, as a whole, under this
-    License to anyone who comes into possession of a copy.  This
+License to anyone who comes into possession of a copy.  This
-    License will therefore apply, along with any applicable section 7
+License will therefore apply, along with any applicable section 7
-    additional terms, to the whole of the work, and all its parts,
+additional terms, to the whole of the work, and all its parts,
-    regardless of how they are packaged.  This License gives no
+regardless of how they are packaged.  This License gives no
-    permission to license the work in any other way, but it does not
+permission to license the work in any other way, but it does not
-    invalidate such permission if you have separately received it.
+invalidate such permission if you have separately received it.
-    d) If the work has interactive user interfaces, each must display
+d) If the work has interactive user interfaces, each must display
-    Appropriate Legal Notices; however, if the Program has interactive
+Appropriate Legal Notices; however, if the Program has interactive
-    interfaces that do not display Appropriate Legal Notices, your
+interfaces that do not display Appropriate Legal Notices, your
-    work need not make them do so.
+work need not make them do so.
-  A compilation of a covered work with other separate and independent
+A compilation of a covered work with other separate and independent
 works, which are not by their nature extensions of the covered work,
 and which are not combined with it such as to form a larger program,
 in or on a volume of a storage or distribution medium, is called an
@@ -242,59 +230,59 @@ beyond what the individual works permit.  Inclusion of a covered work
 in an aggregate does not cause this License to apply to the other
 parts of the aggregate.
-  6. Conveying Non-Source Forms.
+6. Conveying Non-Source Forms.
-  You may convey a covered work in object code form under the terms
+You may convey a covered work in object code form under the terms
 of sections 4 and 5, provided that you also convey the
 machine-readable Corresponding Source under the terms of this License,
 in one of these ways:
-    a) Convey the object code in, or embodied in, a physical product
+a) Convey the object code in, or embodied in, a physical product
-    (including a physical distribution medium), accompanied by the
+(including a physical distribution medium), accompanied by the
-    Corresponding Source fixed on a durable physical medium
+Corresponding Source fixed on a durable physical medium
-    customarily used for software interchange.
+customarily used for software interchange.
-    b) Convey the object code in, or embodied in, a physical product
+b) Convey the object code in, or embodied in, a physical product
-    (including a physical distribution medium), accompanied by a
+(including a physical distribution medium), accompanied by a
-    written offer, valid for at least three years and valid for as
+written offer, valid for at least three years and valid for as
-    long as you offer spare parts or customer support for that product
+long as you offer spare parts or customer support for that product
-    model, to give anyone who possesses the object code either (1) a
+model, to give anyone who possesses the object code either (1) a
-    copy of the Corresponding Source for all the software in the
+copy of the Corresponding Source for all the software in the
-    product that is covered by this License, on a durable physical
+product that is covered by this License, on a durable physical
-    medium customarily used for software interchange, for a price no
+medium customarily used for software interchange, for a price no
-    more than your reasonable cost of physically performing this
+more than your reasonable cost of physically performing this
-    conveying of source, or (2) access to copy the
+conveying of source, or (2) access to copy the
-    Corresponding Source from a network server at no charge.
+Corresponding Source from a network server at no charge.
-    c) Convey individual copies of the object code with a copy of the
+c) Convey individual copies of the object code with a copy of the
-    written offer to provide the Corresponding Source.  This
+written offer to provide the Corresponding Source.  This
-    alternative is allowed only occasionally and noncommercially, and
+alternative is allowed only occasionally and noncommercially, and
-    only if you received the object code with such an offer, in accord
+only if you received the object code with such an offer, in accord
-    with subsection 6b.
+with subsection 6b.
-    d) Convey the object code by offering access from a designated
+d) Convey the object code by offering access from a designated
-    place (gratis or for a charge), and offer equivalent access to the
+place (gratis or for a charge), and offer equivalent access to the
-    Corresponding Source in the same way through the same place at no
+Corresponding Source in the same way through the same place at no
-    further charge.  You need not require recipients to copy the
+further charge.  You need not require recipients to copy the
-    Corresponding Source along with the object code.  If the place to
+Corresponding Source along with the object code.  If the place to
-    copy the object code is a network server, the Corresponding Source
+copy the object code is a network server, the Corresponding Source
-    may be on a different server (operated by you or a third party)
+may be on a different server (operated by you or a third party)
-    that supports equivalent copying facilities, provided you maintain
+that supports equivalent copying facilities, provided you maintain
-    clear directions next to the object code saying where to find the
+clear directions next to the object code saying where to find the
-    Corresponding Source.  Regardless of what server hosts the
+Corresponding Source.  Regardless of what server hosts the
-    Corresponding Source, you remain obligated to ensure that it is
+Corresponding Source, you remain obligated to ensure that it is
-    available for as long as needed to satisfy these requirements.
+available for as long as needed to satisfy these requirements.
-    e) Convey the object code using peer-to-peer transmission, provided
+e) Convey the object code using peer-to-peer transmission, provided
-    you inform other peers where the object code and Corresponding
+you inform other peers where the object code and Corresponding
-    Source of the work are being offered to the general public at no
+Source of the work are being offered to the general public at no
-    charge under subsection 6d.
+charge under subsection 6d.
-  A separable portion of the object code, whose source code is excluded
+A separable portion of the object code, whose source code is excluded
 from the Corresponding Source as a System Library, need not be
 included in conveying the object code work.
-  A "User Product" is either (1) a "consumer product", which means any
+A "User Product" is either (1) a "consumer product", which means any
 tangible personal property which is normally used for personal, family,
 or household purposes, or (2) anything designed or sold for incorporation
 into a dwelling.  In determining whether a product is a consumer product,
@@ -307,7 +295,7 @@ is a consumer product regardless of whether the product has substantial
 commercial, industrial or non-consumer uses, unless such uses represent
 the only significant mode of use of the product.
-  "Installation Information" for a User Product means any methods,
+"Installation Information" for a User Product means any methods,
 procedures, authorization keys, or other information required to install
 and execute modified versions of a covered work in that User Product from
 a modified version of its Corresponding Source.  The information must
@@ -315,7 +303,7 @@ suffice to ensure that the continued functioning of the modified object
 code is in no case prevented or interfered with solely because
 modification has been made.
-  If you convey an object code work under this section in, or with, or
+If you convey an object code work under this section in, or with, or
 specifically for use in, a User Product, and the conveying occurs as
 part of a transaction in which the right of possession and use of the
 User Product is transferred to the recipient in perpetuity or for a
@@ -326,7 +314,7 @@ if neither you nor any third party retains the ability to install
 modified object code on the User Product (for example, the work has
 been installed in ROM).
-  The requirement to provide Installation Information does not include a
+The requirement to provide Installation Information does not include a
 requirement to continue to provide support service, warranty, or updates
 for a work that has been modified or installed by the recipient, or for
 the User Product in which it has been modified or installed.  Access to a
@@ -334,15 +322,15 @@ network may be denied when the modification itself materially and
 adversely affects the operation of the network or violates the rules and
 protocols for communication across the network.
-  Corresponding Source conveyed, and Installation Information provided,
+Corresponding Source conveyed, and Installation Information provided,
 in accord with this section must be in a format that is publicly
 documented (and with an implementation available to the public in
 source code form), and must require no special password or key for
 unpacking, reading or copying.
-  7. Additional Terms.
+7. Additional Terms.
-  "Additional permissions" are terms that supplement the terms of this
+"Additional permissions" are terms that supplement the terms of this
 License by making exceptions from one or more of its conditions.
 Additional permissions that are applicable to the entire Program shall
 be treated as though they were included in this License, to the extent
@@ -351,41 +339,41 @@ apply only to part of the Program, that part may be used separately
 under those permissions, but the entire Program remains governed by
 this License without regard to the additional permissions.
-  When you convey a copy of a covered work, you may at your option
+When you convey a copy of a covered work, you may at your option
 remove any additional permissions from that copy, or from any part of
 it.  (Additional permissions may be written to require their own
 removal in certain cases when you modify the work.)  You may place
 additional permissions on material, added by you to a covered work,
 for which you have or can give appropriate copyright permission.
-  Notwithstanding any other provision of this License, for material you
+Notwithstanding any other provision of this License, for material you
 add to a covered work, you may (if authorized by the copyright holders of
 that material) supplement the terms of this License with terms:
-    a) Disclaiming warranty or limiting liability differently from the
+a) Disclaiming warranty or limiting liability differently from the
-    terms of sections 15 and 16 of this License; or
+terms of sections 15 and 16 of this License; or
-    b) Requiring preservation of specified reasonable legal notices or
+b) Requiring preservation of specified reasonable legal notices or
-    author attributions in that material or in the Appropriate Legal
+author attributions in that material or in the Appropriate Legal
-    Notices displayed by works containing it; or
+Notices displayed by works containing it; or
-    c) Prohibiting misrepresentation of the origin of that material, or
+c) Prohibiting misrepresentation of the origin of that material, or
-    requiring that modified versions of such material be marked in
+requiring that modified versions of such material be marked in
-    reasonable ways as different from the original version; or
+reasonable ways as different from the original version; or
-    d) Limiting the use for publicity purposes of names of licensors or
+d) Limiting the use for publicity purposes of names of licensors or
-    authors of the material; or
+authors of the material; or
-    e) Declining to grant rights under trademark law for use of some
+e) Declining to grant rights under trademark law for use of some
-    trade names, trademarks, or service marks; or
+trade names, trademarks, or service marks; or
-    f) Requiring indemnification of licensors and authors of that
+f) Requiring indemnification of licensors and authors of that
-    material by anyone who conveys the material (or modified versions of
+material by anyone who conveys the material (or modified versions of
-    it) with contractual assumptions of liability to the recipient, for
+it) with contractual assumptions of liability to the recipient, for
-    any liability that these contractual assumptions directly impose on
+any liability that these contractual assumptions directly impose on
-    those licensors and authors.
+those licensors and authors.
-  All other non-permissive additional terms are considered "further
+All other non-permissive additional terms are considered "further
 restrictions" within the meaning of section 10.  If the Program as you
 received it, or any part of it, contains a notice stating that it is
 governed by this License along with a term that is a further
@@ -395,46 +383,46 @@ License, you may add to a covered work material governed by the terms
 of that license document, provided that the further restriction does
 not survive such relicensing or conveying.
-  If you add terms to a covered work in accord with this section, you
+If you add terms to a covered work in accord with this section, you
 must place, in the relevant source files, a statement of the
 additional terms that apply to those files, or a notice indicating
 where to find the applicable terms.
-  Additional terms, permissive or non-permissive, may be stated in the
+Additional terms, permissive or non-permissive, may be stated in the
 form of a separately written license, or stated as exceptions;
 the above requirements apply either way.
-  8. Termination.
+8. Termination.
-  You may not propagate or modify a covered work except as expressly
+You may not propagate or modify a covered work except as expressly
 provided under this License.  Any attempt otherwise to propagate or
 modify it is void, and will automatically terminate your rights under
 this License (including any patent licenses granted under the third
 paragraph of section 11).
-  However, if you cease all violation of this License, then your
+However, if you cease all violation of this License, then your
 license from a particular copyright holder is reinstated (a)
 provisionally, unless and until the copyright holder explicitly and
 finally terminates your license, and (b) permanently, if the copyright
 holder fails to notify you of the violation by some reasonable means
 prior to 60 days after the cessation.
-  Moreover, your license from a particular copyright holder is
+Moreover, your license from a particular copyright holder is
 reinstated permanently if the copyright holder notifies you of the
 violation by some reasonable means, this is the first time you have
 received notice of violation of this License (for any work) from that
 copyright holder, and you cure the violation prior to 30 days after
 your receipt of the notice.
-  Termination of your rights under this section does not terminate the
+Termination of your rights under this section does not terminate the
 licenses of parties who have received copies or rights from you under
 this License.  If your rights have been terminated and not permanently
 reinstated, you do not qualify to receive new licenses for the same
 material under section 10.
-  9. Acceptance Not Required for Having Copies.
+9. Acceptance Not Required for Having Copies.
-  You are not required to accept this License in order to receive or
+You are not required to accept this License in order to receive or
 run a copy of the Program.  Ancillary propagation of a covered work
 occurring solely as a consequence of using peer-to-peer transmission
 to receive a copy likewise does not require acceptance.  However,
@@ -443,14 +431,14 @@ modify any covered work.  These actions infringe copyright if you do
 not accept this License.  Therefore, by modifying or propagating a
 covered work, you indicate your acceptance of this License to do so.
-  10. Automatic Licensing of Downstream Recipients.
+10. Automatic Licensing of Downstream Recipients.
-  Each time you convey a covered work, the recipient automatically
+Each time you convey a covered work, the recipient automatically
 receives a license from the original licensors, to run, modify and
 propagate that work, subject to this License.  You are not responsible
 for enforcing compliance by third parties with this License.
-  An "entity transaction" is a transaction transferring control of an
+An "entity transaction" is a transaction transferring control of an
 organization, or substantially all assets of one, or subdividing an
 organization, or merging organizations.  If propagation of a covered
 work results from an entity transaction, each party to that
@@ -460,7 +448,7 @@ give under the previous paragraph, plus a right to possession of the
 Corresponding Source of the work from the predecessor in interest, if
 the predecessor has it or can get it with reasonable efforts.
-  You may not impose any further restrictions on the exercise of the
+You may not impose any further restrictions on the exercise of the
 rights granted or affirmed under this License.  For example, you may
 not impose a license fee, royalty, or other charge for exercise of
 rights granted under this License, and you may not initiate litigation
@@ -468,13 +456,13 @@ rights granted under this License, and you may not initiate litigation
 any patent claim is infringed by making, using, selling, offering for
 sale, or importing the Program or any portion of it.
-  11. Patents.
+11. Patents.
-  A "contributor" is a copyright holder who authorizes use under this
+A "contributor" is a copyright holder who authorizes use under this
 License of the Program or a work on which the Program is based.  The
 work thus licensed is called the contributor's "contributor version".
-  A contributor's "essential patent claims" are all patent claims
+A contributor's "essential patent claims" are all patent claims
 owned or controlled by the contributor, whether already acquired or
 hereafter acquired, that would be infringed by some manner, permitted
 by this License, of making, using, or selling its contributor version,
@@ -484,19 +472,19 @@ purposes of this definition, "control" includes the right to grant
 patent sublicenses in a manner consistent with the requirements of
 this License.
-  Each contributor grants you a non-exclusive, worldwide, royalty-free
+Each contributor grants you a non-exclusive, worldwide, royalty-free
 patent license under the contributor's essential patent claims, to
 make, use, sell, offer for sale, import and otherwise run, modify and
 propagate the contents of its contributor version.
-  In the following three paragraphs, a "patent license" is any express
+In the following three paragraphs, a "patent license" is any express
 agreement or commitment, however denominated, not to enforce a patent
 (such as an express permission to practice a patent or covenant not to
 sue for patent infringement).  To "grant" such a patent license to a
 party means to make such an agreement or commitment not to enforce a
 patent against the party.
-  If you convey a covered work, knowingly relying on a patent license,
+If you convey a covered work, knowingly relying on a patent license,
 and the Corresponding Source of the work is not available for anyone
 to copy, free of charge and under the terms of this License, through a
 publicly available network server or other readily accessible means,
@@ -510,7 +498,7 @@ covered work in a country, or your recipient's use of the covered work
 in a country, would infringe one or more identifiable patents in that
 country that you have reason to believe are valid.
-  If, pursuant to or in connection with a single transaction or
+If, pursuant to or in connection with a single transaction or
 arrangement, you convey, or propagate by procuring conveyance of, a
 covered work, and grant a patent license to some of the parties
 receiving the covered work authorizing them to use, propagate, modify
@@ -518,7 +506,7 @@ or convey a specific copy of the covered work, then the patent license
 you grant is automatically extended to all recipients of the covered
 work and works based on it.
-  A patent license is "discriminatory" if it does not include within
+A patent license is "discriminatory" if it does not include within
 the scope of its coverage, prohibits the exercise of, or is
 conditioned on the non-exercise of one or more of the rights that are
 specifically granted under this License.  You may not convey a covered
@@ -533,13 +521,13 @@ for and in connection with specific products or compilations that
 contain the covered work, unless you entered into that arrangement,
 or that patent license was granted, prior to 28 March 2007.
-  Nothing in this License shall be construed as excluding or limiting
+Nothing in this License shall be construed as excluding or limiting
 any implied license or other defenses to infringement that may
 otherwise be available to you under applicable patent law.
-  12. No Surrender of Others' Freedom.
+12. No Surrender of Others' Freedom.
-  If conditions are imposed on you (whether by court order, agreement or
+If conditions are imposed on you (whether by court order, agreement or
 otherwise) that contradict the conditions of this License, they do not
 excuse you from the conditions of this License.  If you cannot convey a
 covered work so as to satisfy simultaneously your obligations under this
@@ -549,46 +537,56 @@ to collect a royalty for further conveying from those to whom you convey
 the Program, the only way you could satisfy both those terms and this
 License would be to refrain entirely from conveying the Program.
-  13. Use with the GNU Affero General Public License.
+13. Remote Network Interaction; Use with the GNU General Public License.
-  Notwithstanding any other provision of this License, you have
+Notwithstanding any other provision of this License, if you modify the
 Program, your modified version must prominently offer all users
 interacting with it remotely through a computer network (if your version
 supports such interaction) an opportunity to receive the Corresponding
 Source of your version by providing access to the Corresponding Source
 from a network server at no charge, through some standard or customary
 means of facilitating copying of software.  This Corresponding Source
 shall include the Corresponding Source for any work covered by version 3
 of the GNU General Public License that is incorporated pursuant to the
 following paragraph.
 Notwithstanding any other provision of this License, you have
 permission to link or combine any covered work with a work licensed
-under version 3 of the GNU Affero General Public License into a single
+under version 3 of the GNU General Public License into a single
 combined work, and to convey the resulting work.  The terms of this
 License will continue to apply to the part which is the covered work,
-but the special requirements of the GNU Affero General Public License,
+but the work with which it is combined will remain governed by version
-section 13, concerning interaction through a network will apply to the
+3 of the GNU General Public License.
 combination as such.
-  14. Revised Versions of this License.
+14. Revised Versions of this License.
-  The Free Software Foundation may publish revised and/or new versions of
+The Free Software Foundation may publish revised and/or new versions of
-the GNU General Public License from time to time.  Such new versions will
+the GNU Affero General Public License from time to time.  Such new versions
-be similar in spirit to the present version, but may differ in detail to
+will be similar in spirit to the present version, but may differ in detail to
 address new problems or concerns.
-  Each version is given a distinguishing version number.  If the
+Each version is given a distinguishing version number.  If the
-Program specifies that a certain numbered version of the GNU General
+Program specifies that a certain numbered version of the GNU Affero General
 Public License "or any later version" applies to it, you have the
 option of following the terms and conditions either of that numbered
 version or of any later version published by the Free Software
 Foundation.  If the Program does not specify a version number of the
-GNU General Public License, you may choose any version ever published
+GNU Affero General Public License, you may choose any version ever published
 by the Free Software Foundation.
-  If the Program specifies that a proxy can decide which future
+If the Program specifies that a proxy can decide which future
-versions of the GNU General Public License can be used, that proxy's
+versions of the GNU Affero General Public License can be used, that proxy's
 public statement of acceptance of a version permanently authorizes you
 to choose that version for the Program.
-  Later license versions may give you additional or different
+Later license versions may give you additional or different
 permissions.  However, no additional obligations are imposed on any
 author or copyright holder as a result of your choosing to follow a
 later version.
-  15. Disclaimer of Warranty.
+15. Disclaimer of Warranty.
-  THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
+THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
 APPLICABLE LAW.  EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
 HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
 OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
@@ -597,9 +595,9 @@ PURPOSE.  THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
 IS WITH YOU.  SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
 ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
-  16. Limitation of Liability.
+16. Limitation of Liability.
-  IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
+IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
 WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
 THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
 GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
@@ -609,66 +607,55 @@ PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
 EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
 SUCH DAMAGES.
-  17. Interpretation of Sections 15 and 16.
+17. Interpretation of Sections 15 and 16.
-  If the disclaimer of warranty and limitation of liability provided
+If the disclaimer of warranty and limitation of liability provided
 above cannot be given local legal effect according to their terms,
 reviewing courts shall apply local law that most closely approximates
 an absolute waiver of all civil liability in connection with the
 Program, unless a warranty or assumption of liability accompanies a
 copy of the Program in return for a fee.
-                     END OF TERMS AND CONDITIONS
+ END OF TERMS AND CONDITIONS
-            How to Apply These Terms to Your New Programs
+How to Apply These Terms to Your New Programs
-  If you develop a new program, and you want it to be of the greatest
+If you develop a new program, and you want it to be of the greatest
 possible use to the public, the best way to achieve this is to make it
 free software which everyone can redistribute and change under these terms.
-  To do so, attach the following notices to the program.  It is safest
+To do so, attach the following notices to the program.  It is safest
 to attach them to the start of each source file to most effectively
 state the exclusion of warranty; and each file should have at least
 the "copyright" line and a pointer to where the full notice is found.
-    <one line to give the program's name and a brief idea of what it does.>
+<one line to give the program's name and a brief idea of what it does.>
-    Copyright (C) <year>  <name of author>
+Copyright (C) <year>  <name of author>
-    This program is free software: you can redistribute it and/or modify
+This program is free software: you can redistribute it and/or modify
-    it under the terms of the GNU General Public License as published by
+it under the terms of the GNU Affero General Public License as published
-    the Free Software Foundation, either version 3 of the License, or
+by the Free Software Foundation, either version 3 of the License, or
-    (at your option) any later version.
+(at your option) any later version.
-    This program is distributed in the hope that it will be useful,
+This program is distributed in the hope that it will be useful,
-    but WITHOUT ANY WARRANTY; without even the implied warranty of
+but WITHOUT ANY WARRANTY; without even the implied warranty of
-    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
+MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
-    GNU General Public License for more details.
+GNU Affero General Public License for more details.
-    You should have received a copy of the GNU General Public License
+You should have received a copy of the GNU Affero General Public License
-    along with this program.  If not, see <https://www.gnu.org/licenses/>.
+along with this program.  If not, see <http://www.gnu.org/licenses/>.
 Also add information on how to contact you by electronic and paper mail.
-  If the program does terminal interaction, make it output a short
+If your software can interact with users remotely through a computer
-notice like this when it starts in an interactive mode:
+network, you should also make sure that it provides a way for users to
 get its source.  For example, if your program is a web application, its
 interface could display a "Source" link that leads users to an archive
 of the code.  There are many ways you could offer source, and different
 solutions will be better for different programs; see section 13 for the
 specific requirements.
-    <program>  Copyright (C) <year>  <name of author>
+You should also get your employer (if you work as a programmer) or school,
    This program comes with ABSOLUTELY NO WARRANTY; for details type `show w'.
    This is free software, and you are welcome to redistribute it
    under certain conditions; type `show c' for details.
 The hypothetical commands `show w' and `show c' should show the appropriate
 parts of the General Public License.  Of course, your program's commands
 might be different; for a GUI interface, you would use an "about box".
  You should also get your employer (if you work as a programmer) or school,
 if any, to sign a "copyright disclaimer" for the program, if necessary.
-For more information on this, and how to apply and follow the GNU GPL, see
+For more information on this, and how to apply and follow the GNU AGPL, see
-<https://www.gnu.org/licenses/>.
+<http://www.gnu.org/licenses/>.
  The GNU General Public License does not permit incorporating your program
 into proprietary programs.  If your program is a subroutine library, you
 may consider it more useful to permit linking proprietary applications with
 the library.  If this is what you want to do, use the GNU Lesser General
 Public License instead of this License.  But first, please read
 <https://www.gnu.org/licenses/why-not-lgpl.html>.
@@ -0,0 +1,86 @@
 # File: decoder.py
 # Copyright (C) 2026 Erick Ahmed
 # SPDX-License-Identifier: AGPL-3.0-or-later
 import argparse
 import polars as pl
 def get_j1939_mask() -> pl.Expr:
    """
    Returns a Polars expression representing the strict J1939 filtering rules.
    """
    id_int = pl.col("ID").str.to_integer(base=16).cast(pl.UInt32)
    return id_int > 0x7FF
 def decode_j1939_metadata(lf: pl.LazyFrame) -> pl.LazyFrame:
    """
    Decodes J1939 fields and bundles them into a Struct column.
    """
    id_int = pl.col("ID").str.to_integer(base=16).cast(pl.UInt32)
    priority = ((id_int // 67108864) % 8).cast(pl.UInt8)
    pf = ((id_int // 65536) % 256).cast(pl.UInt8)
    ps = ((id_int // 256) % 256).cast(pl.UInt8)
    sa = (id_int % 256).cast(pl.UInt8)
    da = pl.when(pf < 240).then(ps).otherwise(pl.lit(255, dtype=pl.UInt8)).cast(pl.UInt8)
    pgn = pl.when(pf < 240).then(
        ((id_int // 256) & 0x3FF00)
    ).otherwise(
        ((id_int // 256) & 0x3FFFF)
    ).cast(pl.UInt32)
    return lf.with_columns(
        pl.struct([
            priority.alias("Priority"),
            pf.alias("PF"),
            ps.alias("PS"),
            sa.alias("SA"),
            da.alias("DA"),
            pgn.alias("PGN")
        ]).alias("j1939_metadata")
    )
 def decode_j1939_frames(df: pl.DataFrame) -> pl.DataFrame:
    id_int = pl.col("ID").str.to_integer(base=16).cast(pl.UInt32)
    is_j1939 = id_int > 0x7FF
    priority = ((id_int // 67108864) % 8).cast(pl.UInt8)
    pf = ((id_int // 65536) % 256).cast(pl.UInt8)
    ps = ((id_int // 256) % 256).cast(pl.UInt8)
    sa = (id_int % 256).cast(pl.UInt8)
    da = pl.when(pf < 240).then(ps).otherwise(pl.lit(255, dtype=pl.UInt8)).cast(pl.UInt8)
    pgn = pl.when(pf < 240).then(
        ((id_int // 256) & 0x3FF00)
    ).otherwise(
        ((id_int // 256) & 0x3FFFF)
    ).cast(pl.UInt32)
    j1939_meta = pl.when(is_j1939).then(
        pl.struct([
            priority.alias("Priority"),
            pf.alias("PF"),
            ps.alias("PS"),
            sa.alias("SA"),
            da.alias("DA"),
            pgn.alias("PGN")
        ])
    ).otherwise(None)
    return df.with_columns(j1939_meta.alias("j1939_metadata"))
 if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="J1939 decoder")
    parser.add_argument("input_parquet", help="Path to the raw .parquet file")
    parser.add_argument("output_parquet", help="Path to save the decoded .parquet file")
    args = parser.parse_args()
    df = pl.scan_parquet(args.input_parquet).collect()
    decoded_df = decode_j1939_frames(df)
    decoded_df.write_parquet(args.output_parquet)
@@ -0,0 +1,83 @@
 # File: logs/view.py
 # Copyright (C) 2026 Erick Ahmed
 # SPDX-License-Identifier: AGPL-3.0-or-later
 import pandas as pd
 from dash import html, dash_table, dcc
 import dash_bootstrap_components as dbc
 PAGE_SIZE = 25000
 def prepare_logs_data(df: pd.DataFrame) -> pd.DataFrame:
    if df is None or df.empty:
        return pd.DataFrame()
    df = df.copy()
    if 'j1939_metadata' in df.columns:
        df['Priority'] = df['j1939_metadata'].apply(lambda x: x.get('Priority') if isinstance(x, dict) else None)
        df['PF'] = df['j1939_metadata'].apply(lambda x: x.get('PF') if isinstance(x, dict) else None)
        df['PS'] = df['j1939_metadata'].apply(lambda x: x.get('PS') if isinstance(x, dict) else None)
        df['SA'] = df['j1939_metadata'].apply(lambda x: x.get('SA') if isinstance(x, dict) else None)
        df['DA'] = df['j1939_metadata'].apply(lambda x: x.get('DA') if isinstance(x, dict) else None)
        df['PGN'] = df['j1939_metadata'].apply(lambda x: x.get('PGN') if isinstance(x, dict) else None)
    else:
        for col in ['Priority', 'PF', 'PS', 'SA', 'DA', 'PGN']:
            df[col] = None
    for i in range(8):
        col = f'b{i}'
        if col in df.columns:
            df[col] = df[col].apply(lambda x: f"{int(x):02X}" if pd.notna(x) else "")
        else:
            df[col] = ""
    if 'ID' in df.columns:
        df['ID'] = df['ID'].astype(str)
    display_cols = ['Timestamp', 'ID', 'DLC', 'b0', 'b1', 'b2', 'b3', 'b4', 'b5', 'b6', 'b7', 'Priority', 'PF', 'PS', 'SA', 'DA', 'PGN']
    display_df = df[[c for c in display_cols if c in df.columns]]
    return display_df.fillna("")
 def get_logs_table_component():
    return html.Div([
        html.Div(id='logs-info-text', className="text-muted mb-2"),
        dash_table.DataTable(
            id='logs-table',
            virtualization=True,
            page_action='none',
            style_table={'overflowX': 'auto', 'height': '70vh', 'overflowY': 'auto'},
            style_header={
                'backgroundColor': '#1a1a1a',
                'color': 'white',
                'fontWeight': 'bold',
                'textAlign': 'center',
                'position': 'sticky',
                'top': 0
            },
            style_data={
                'backgroundColor': '#f8f9fa',
                'color': '#2a2a2a',
                'textAlign': 'center'
            },
            style_data_conditional=[
                {
                    'if': {'row_index': 'odd'},
                    'backgroundColor': 'rgb(240, 240, 240)'
                }
            ],
            style_cell={
                'minWidth': '80px',
                'padding': '5px',
                'textAlign': 'center',
                'fontFamily': 'Segoe UI, Arial, sans-serif'
            }
        ),
        html.Div([
            dbc.Button("Prev", id='logs-prev-btn', color="secondary", outline=True, size="sm", className="me-2"),
            html.Div(id='logs-page-nav', className="d-inline-block", style={'verticalAlign': 'middle'}),
            dbc.Button("Next", id='logs-next-btn', color="secondary", outline=True, size="sm", className="ms-2"),
        ], className="d-flex justify-content-center align-items-center mt-3"),
        dcc.Store(id='logs-current-page', data=0),
    ])
@@ -0,0 +1,597 @@
 # File: main.py
 # Copyright (C) 2026 Erick Ahmed
 # SPDX-License-Identifier: AGPL-3.0-or-later
 """CANveyor dashboard entry point.
 Handles raw log ingestion, J1939 decoding, precomputation of
 statistical figures, and exposes a Dash application for browsing the
 processed data.
 """
 import os
 from concurrent.futures import ThreadPoolExecutor
 from pathlib import Path
 from typing import Dict, List, Tuple
 import dash
 import dash_bootstrap_components as dbc
 import numpy as np
 import pandas as pd
 import polars as pl
 from dash import dcc, html, Input, Output, State
 from decoder import decode_j1939_frames
 from logs.view import get_logs_table_component, prepare_logs_data
 from parser import parse_csv, parse_log
 from stats.correlation import calculate_correlation, plot_correlation_heatmap
 from stats.entropy import calculate_byte_entropy, plot_entropy_heatmap
 from stats.frequency import calculate_frequency, plot_frequency
 from stats.id_viewer import _format_can_id_vec, plot_bits
 from stats.utils.loader import load_data
 from vehicle import get_vehicle_module
 RAW_LOG_DIR = "data/logs"
 CSV_DIR = "data/csv"
 PARQUET_DIR = "data/parquet"
 PAGE_SIZE = 25_000
 BYTE_COLS = [f"b{i}" for i in range(8)]
 BUS_OPTIONS = [
    {"label": "Bus 1", "value": "Bus 1"},
    {"label": "Bus 2", "value": "Bus 2"},
 ]
 DATA: Dict[str, Dict[str, pd.DataFrame]] = {}
 VEHICLE_META: Dict[str, Dict[str, str]] = {}
 PRECOMPUTED_FIGURES: Dict[str, object] = {}
 DATA_BY_ID: Dict[Tuple[str, str], Dict[str, Tuple[pd.DataFrame, List[str]]]] = {}
 CORR_CACHE: Dict[Tuple, object] = {}
 PREPARED_LOGS_CACHE: Dict[Tuple[str, str], pd.DataFrame] = {}
 def parse_vehicle_from_filename(filename: str) -> Tuple[str, str, str]:
    """Derive (vehicle, brand, model) from a log file name."""
    stem = Path(filename).stem
    if "-" in stem:
        brand, model_part = stem.split("-", 1)
    else:
        brand, model_part = stem, "Unknown"
    model = model_part.replace("_", " ")
    vehicle = f"{brand} {model}".strip()
    return vehicle, brand, model
 def _vehicle_paths(vehicle: str) -> Dict[str, str]:
    """Return all intermediate file paths for a given vehicle."""
    return {
        "bus1_csv": f"{CSV_DIR}/{vehicle}_bus1.csv",
        "bus2_csv": f"{CSV_DIR}/{vehicle}_bus2.csv",
        "bus1_parquet": f"{PARQUET_DIR}/{vehicle}_bus1.parquet",
        "bus2_parquet": f"{PARQUET_DIR}/{vehicle}_bus2.parquet",
        "bus1_decoded": f"{PARQUET_DIR}/{vehicle}_bus1_decoded.parquet",
        "bus2_decoded": f"{PARQUET_DIR}/{vehicle}_bus2_decoded.parquet",
    }
 def run_pipeline() -> None:
    """Parse raw log files, convert to parquet, and decode J1939 frames."""
    for directory in (RAW_LOG_DIR, CSV_DIR, PARQUET_DIR):
        os.makedirs(directory, exist_ok=True)
    for log_file in Path(RAW_LOG_DIR).glob("*.txt"):
        vehicle, _, _ = parse_vehicle_from_filename(log_file.name)
        paths = _vehicle_paths(vehicle)
        if Path(paths["bus1_decoded"]).exists() and Path(paths["bus2_decoded"]).exists():
            continue
        print(f"Parsing raw log: {log_file.name}...")
        parse_log(str(log_file), paths["bus1_csv"], paths["bus2_csv"])
        print("Converting to parquet...")
        parse_csv(paths["bus1_csv"]).sink_parquet(paths["bus1_parquet"])
        parse_csv(paths["bus2_csv"]).sink_parquet(paths["bus2_parquet"])
        print("Decoding J1939...")
        df1 = pl.read_parquet(paths["bus1_parquet"])
        df2 = pl.read_parquet(paths["bus2_parquet"])
        decode_j1939_frames(df1).write_parquet(paths["bus1_decoded"])
        decode_j1939_frames(df2).write_parquet(paths["bus2_decoded"])
 def load_vehicle_data() -> None:
    """Load all decoded parquet files into the in-memory DATA store."""
    for log_file in Path(RAW_LOG_DIR).glob("*.txt"):
        vehicle, brand, model = parse_vehicle_from_filename(log_file.name)
        VEHICLE_META[vehicle] = {"brand": brand, "model": model}
        paths = _vehicle_paths(vehicle)
        if Path(paths["bus1_decoded"]).exists() and Path(paths["bus2_decoded"]).exists():
            DATA[vehicle] = {
                "Bus 1": load_data(paths["bus1_decoded"]),
                "Bus 2": load_data(paths["bus2_decoded"]),
            }
 def _can_id_column(df: pd.DataFrame) -> str:
    return "ID" if "ID" in df.columns else "Identifier"
 def _downsample_unchanged(group: pd.DataFrame, byte_cols: List[str]) -> pd.DataFrame:
    """Keep only rows where at least one byte changed vs. the previous row."""
    if group.empty or not byte_cols:
        return group
    arr = group[byte_cols].to_numpy(dtype=np.float32, copy=False)
    if len(arr) <= 1:
        return group
    changed = np.any(arr[1:] != arr[:-1], axis=1)
    keep = np.concatenate(([True], changed))
    return group.iloc[keep]
 def process_bus_data(
    vehicle: str, bus: str, df: pd.DataFrame
 ) -> Tuple[str, str, Dict[str, object], Dict[str, Tuple[pd.DataFrame, List[str]]]]:
    """Compute per-bus figures and ID-grouped, downsampled frames."""
    precomp = {
        f"{vehicle}_{bus}_freq": plot_frequency(
            calculate_frequency(df), title=f"{vehicle} {bus} Frequency"
        ),
        f"{vehicle}_{bus}_entropy": plot_entropy_heatmap(
            calculate_byte_entropy(df), title=f"{vehicle} {bus} Byte-Level Entropy"
        ),
    }
    df = df.assign(Formatted_ID=_format_can_id_vec(df[_can_id_column(df)]))
    df = df.sort_values(["Formatted_ID", "Timestamp"], kind="stable")
    grouped: Dict[str, Tuple[pd.DataFrame, List[str]]] = {}
    for can_id, group in df.groupby(by="Formatted_ID"):
        byte_cols = [c for c in BYTE_COLS if c in group.columns]
        group = _downsample_unchanged(group, byte_cols)
        grouped[can_id] = (group, byte_cols)
    return vehicle, bus, precomp, grouped
 def precompute_all() -> None:
    """Run :func:`process_bus_data` across every vehicle/bus pair in parallel."""
    with ThreadPoolExecutor() as executor:
        futures = [
            executor.submit(process_bus_data, vehicle, bus, df)
            for vehicle, buses in DATA.items()
            for bus, df in buses.items()
        ]
        for future in futures:
            v, b, precomp, grouped = future.result()
            PRECOMPUTED_FIGURES.update(precomp)
            DATA_BY_ID[(v, b)] = grouped
 run_pipeline()
 print("Loading data into memory...")
 load_vehicle_data()
 precompute_all()
 app = dash.Dash(__name__, external_stylesheets=[dbc.themes.BOOTSTRAP])
 app.config.suppress_callback_exceptions = True
 def _vehicle_dropdown(dropdown_id: str) -> dcc.Dropdown:
    return dcc.Dropdown(
        id=dropdown_id,
        options=[{"label": v, "value": v} for v in DATA.keys()],
        value=list(DATA.keys())[0] if DATA else None,
        clearable=False,
    )
 def _bus_dropdown(dropdown_id: str) -> dcc.Dropdown:
    return dcc.Dropdown(
        id=dropdown_id,
        options=BUS_OPTIONS,
        value="Bus 1",
        clearable=False,
    )
 def _label(text: str) -> html.Label:
    return html.Label(text, className="mt-2")
 app.layout = dbc.Container(
    [
        html.H1("CANveyor", className="my-4"),
        dbc.Tabs(
            [
                dbc.Tab(
                    label="Overview",
                    tab_id="overview",
                    children=[html.Div(id="overview-content")],
                ),
                dbc.Tab(
                    label="Vehicles",
                    tab_id="vehicles",
                    children=[
                        dbc.Row(
                            [
                                dbc.Col(_label("Vehicle:"), width="auto"),
                                dbc.Col(
                                    _vehicle_dropdown("vehicles-vehicle-selector"),
                                    width=3, className="me-4",
                                ),
                            ],
                            className="mb-3 mt-3", align="end",
                        ),
                        html.Div(id="vehicles-content", className="mt-3"),
                    ],
                ),
                dbc.Tab(
                    label="Logs",
                    tab_id="logs",
                    children=[
                        dbc.Row(
                            [
                                dbc.Col(_label("Vehicle:"), width="auto"),
                                dbc.Col(
                                    _vehicle_dropdown("logs-vehicle-selector"),
                                    width=3, className="me-4",
                                ),
                                dbc.Col(_label("Bus:"), width="auto"),
                                dbc.Col(
                                    _bus_dropdown("logs-bus-selector"),
                                    width=2,
                                ),
                            ],
                            className="mb-3 mt-3", align="end",
                        ),
                        get_logs_table_component(),
                    ],
                ),
                dbc.Tab(
                    label="Statistics",
                    tab_id="statistics",
                    children=[
                        dbc.Row(
                            [
                                dbc.Col(_label("Vehicle:"), width="auto"),
                                dbc.Col(
                                    _vehicle_dropdown("vehicle-selector"),
                                    width=3, className="me-4",
                                ),
                                dbc.Col(_label("Bus:"), width="auto"),
                                dbc.Col(
                                    _bus_dropdown("bus-selector"),
                                    width=2,
                                ),
                            ],
                            className="mb-3 mt-3", align="end",
                        ),
                        dbc.Tabs(
                            [
                                dbc.Tab(label="Frequency", tab_id="freq"),
                                dbc.Tab(label="ID Viewer", tab_id="id_viewer"),
                                dbc.Tab(label="Correlation", tab_id="corr"),
                                dbc.Tab(label="Entropy", tab_id="entropy"),
                            ],
                            id="tabs",
                            active_tab="freq",
                        ),
                        html.Div(id="tab-content", className="mt-3"),
                    ],
                ),
            ],
            id="main-tabs",
            active_tab="statistics",
        ),
    ],
    fluid=True,
 )
 def get_prepared_logs(vehicle: str, bus: str) -> pd.DataFrame:
    """Lazily prepare and cache log table data for a vehicle/bus pair."""
    cache_key = (vehicle, bus)
    if cache_key not in PREPARED_LOGS_CACHE:
        PREPARED_LOGS_CACHE[cache_key] = prepare_logs_data(DATA[vehicle][bus])
    return PREPARED_LOGS_CACHE[cache_key]
 def build_page_buttons(
    current_page: int, total_pages: int, max_buttons: int = 15
 ) -> List:
    """Build the pagination button list with ellipses where appropriate."""
    buttons: List = []
    if total_pages <= 1:
        return buttons
    half = max_buttons // 2
    start = max(0, current_page - half)
    end = min(total_pages, start + max_buttons)
    if end - start < max_buttons:
        start = max(0, end - max_buttons)
    if start > 0:
        buttons.append(
            dbc.Button(
                "1",
                id={"type": "page-btn", "index": 0},
                color="secondary", outline=True, size="sm", className="me-1",
            )
        )
        if start > 1:
            buttons.append(html.Span("…", className="mx-1 align-middle"))
    for i in range(start, end):
        is_current = i == current_page
        buttons.append(
            dbc.Button(
                str(i + 1),
                id={"type": "page-btn", "index": i},
                size="sm",
                color="primary" if is_current else "secondary",
                outline=not is_current,
                className="me-1",
                disabled=is_current,
            )
        )
    if end < total_pages:
        if end < total_pages - 1:
            buttons.append(html.Span("…", className="mx-1 align-middle"))
        buttons.append(
            dbc.Button(
                str(total_pages),
                id={"type": "page-btn", "index": total_pages - 1},
                color="secondary", outline=True, size="sm", className="me-1",
            )
        )
    return buttons
@app.callback(
    Output("logs-table", "data"),
    Output("logs-table", "columns"),
    Output("logs-info-text", "children"),
    Output("logs-page-nav", "children"),
    Output("logs-current-page", "data"),
    Input("logs-vehicle-selector", "value"),
    Input("logs-bus-selector", "value"),
    Input("logs-prev-btn", "n_clicks"),
    Input("logs-next-btn", "n_clicks"),
    Input({"type": "page-btn", "index": dash.ALL}, "n_clicks"),
    State("logs-current-page", "data"),
 )
 def update_logs_table(vehicle, bus, prev_clicks, next_clicks, page_btn_clicks, current_page):
    if not vehicle or not bus or vehicle not in DATA or bus not in DATA[vehicle]:
        return [], [], "No data available", [], 0
    prepared_df = get_prepared_logs(vehicle, bus)
    total_rows = len(prepared_df)
    if total_rows == 0:
        return [], [], "No data available", [], 0
    total_pages = max(1, (total_rows + PAGE_SIZE - 1) // PAGE_SIZE)
    ctx = dash.callback_context
    triggered_id = ctx.triggered_id
    current_page = current_page if current_page is not None else 0
    if triggered_id in ("logs-vehicle-selector", "logs-bus-selector"):
        current_page = 0
    elif triggered_id == "logs-prev-btn":
        current_page = max(0, current_page - 1)
    elif triggered_id == "logs-next-btn":
        current_page = current_page + 1
    elif isinstance(triggered_id, dict) and triggered_id.get("type") == "page-btn":
        if ctx.triggered and ctx.triggered[0]["value"]:
            current_page = triggered_id["index"]
    current_page = max(0, min(current_page, total_pages - 1))
    start_idx = current_page * PAGE_SIZE
    end_idx = min(start_idx + PAGE_SIZE, total_rows)
    page_data = prepared_df.iloc[start_idx:end_idx].to_dict("records")
    columns = [{"name": c, "id": c} for c in prepared_df.columns]
    info_text = (
        f"Page {current_page + 1} of {total_pages} | "
        f"Showing rows {start_idx + 1:,}–{end_idx:,} "
        f"of {total_rows:,} total frames"
    )
    page_buttons = build_page_buttons(current_page, total_pages)
    return page_data, columns, info_text, page_buttons, current_page
@app.callback(
    Output("tab-content", "children"),
    Input("tabs", "active_tab"),
    Input("vehicle-selector", "value"),
    Input("bus-selector", "value"),
 )
 def render_content(tab, vehicle, bus):
    if not vehicle or not bus or vehicle not in DATA or bus not in DATA[vehicle]:
        return html.Div("No data available")
    df = DATA[vehicle][bus]
    if tab == "freq":
        return dcc.Graph(
            figure=PRECOMPUTED_FIGURES[f"{vehicle}_{bus}_freq"],
            style={"height": "80vh"},
        )
    if tab == "id_viewer":
        ids = sorted(DATA_BY_ID.get((vehicle, bus), {}).keys())
        return html.Div(
            [
                html.Label("CAN ID:"),
                dcc.Dropdown(
                    id="id-selector",
                    options=[{"label": i, "value": i} for i in ids],
                    value=ids[0] if ids else None,
                    clearable=False,
                    style={"width": "50%", "marginBottom": "10px"},
                ),
                dcc.Graph(id="id-viewer-graph", style={"height": "70vh"}),
            ]
        )
    if tab == "corr":
        ids = sorted(DATA_BY_ID.get((vehicle, bus), {}).keys())
        return html.Div(
            [
                dbc.Row(
                    [
                        dbc.Col(html.Label("Method:"), width=1, className="mt-2"),
                        dbc.Col(
                            dcc.Dropdown(
                                id="corr-method",
                                options=[
                                    {"label": "Pearson", "value": "pearson"},
                                    {"label": "Spearman", "value": "spearman"},
                                ],
                                value="pearson",
                                clearable=False,
                            ),
                            width=2,
                        ),
                        dbc.Col(html.Label("Target ID:"), width=1, className="mt-2"),
                        dbc.Col(
                            dcc.Dropdown(
                                id="corr-target",
                                options=[{"label": "All IDs (Max Corr)", "value": "all"}]
                                + [{"label": i, "value": i} for i in ids],
                                value="all",
                                clearable=True,
                            ),
                            width=4,
                        ),
                    ],
                    className="mb-3",
                ),
                dcc.Graph(id="corr-graph", style={"height": "80vh"}),
            ]
        )
    if tab == "entropy":
        return dcc.Graph(
            figure=PRECOMPUTED_FIGURES[f"{vehicle}_{bus}_entropy"],
            style={"height": "80vh"},
        )
    return html.Div("Tab not found")
@app.callback(
    Output("id-viewer-graph", "figure"),
    Input("id-selector", "value"),
    Input("vehicle-selector", "value"),
    Input("bus-selector", "value"),
    Input("tabs", "active_tab"),
 )
 def update_id_viewer(selected_id, vehicle, bus, tab):
    if tab != "id_viewer" or not selected_id or not vehicle or not bus:
        return dash.no_update
    grouped_data = DATA_BY_ID.get((vehicle, bus), {})
    if selected_id not in grouped_data:
        return dash.no_update
    filtered_df, byte_cols = grouped_data[selected_id]
    return plot_bits(
        filtered_df, byte_cols, selected_id,
        title=f"{vehicle} {bus} Byte Visualization",
    )
@app.callback(
    Output("corr-graph", "figure"),
    Input("corr-method", "value"),
    Input("corr-target", "value"),
    Input("vehicle-selector", "value"),
    Input("bus-selector", "value"),
    Input("tabs", "active_tab"),
 )
 def update_corr(method, target, vehicle, bus, tab):
    if tab != "corr" or not vehicle or not bus:
        return dash.no_update
    target_id = None if target == "all" or not target else target
    cache_key = (vehicle, bus, method, target_id)
    if cache_key not in CORR_CACHE:
        df = DATA[vehicle][bus]
        CORR_CACHE[cache_key] = calculate_correlation(
            df, method=method, target_id=target_id
        )
    corr_df = CORR_CACHE[cache_key]
    title = f"{vehicle} {bus} Correlation"
    if target_id:
        title += f" ({target_id})"
    return plot_correlation_heatmap(corr_df, target_id=target_id, title=title)
@app.callback(
    Output("vehicles-content", "children"),
    Input("vehicles-vehicle-selector", "value"),
 )
 def render_vehicles(vehicle):
    if not vehicle or vehicle not in DATA:
        return html.Div("No data available", className="text-muted")
    brand = VEHICLE_META.get(vehicle, {}).get("brand", "")
    vehicle_module = get_vehicle_module(brand)
    dfs = list(DATA[vehicle].values())
    if not dfs:
        return html.Div("No data available", className="text-muted")
    df = pd.concat(dfs, ignore_index=True)
    if "Timestamp" in df.columns:
        df = df.sort_values("Timestamp", kind="stable").reset_index(drop=True)
    cards = []
    for nid, frame_def in vehicle_module.DECODER_RULES.items():
        decoded = vehicle_module.decode_dataframe(df, frame_def.can_id)
        for item in frame_def.signals:
            if hasattr(item, "plot_func") and callable(item.plot_func):
                title = f"{frame_def.can_id} - {item.name}"
                fig = item.plot_func(decoded, frame_def.color)
            else:
                sig = item
                if getattr(sig, "skip_plot", False):
                    continue
                unit_str = f" ({sig.unit})" if sig.unit else ""
                title = f"{sig.name}{unit_str}"
                fig = vehicle_module.plot_signal(
                    decoded, sig.name, title=title, color=frame_def.color
                )
            cards.append(
                dbc.Col(
                    dbc.Card(
                        [
                            dbc.CardBody(
                                [
                                    dcc.Graph(
                                        figure=fig,
                                        config={"displayModeBar": False},
                                        style={"height": "280px"},
                                    )
                                ],
                                className="p-2",
                            ),
                        ],
                        className="shadow-sm border-0 h-100",
                    ),
                    xs=12, sm=6, md=4, lg=3, className="mb-3",
                )
            )
    if not cards:
        return html.Div(
            "No decoded signals available. Add rules in the vehicle module.",
            className="text-muted",
        )
    return dbc.Row(cards)
 if __name__ == "__main__":
    app.run(debug=False)
@@ -1,3 +1,7 @@
 # File: parser.py
 # Copyright (C) 2026 Erick Ahmed
 # SPDX-License-Identifier: AGPL-3.0-or-later
 import re
 import csv
 import polars as pl
@@ -15,7 +19,7 @@ def parse_log(input_path: PathLike, out_bus1: PathLike, out_bus2: PathLike) -> N
    out1_file = Path(out_bus1)
    out2_file = Path(out_bus2)
-    start_pattern = re.compile(r'(C[12]):([0-9A-Fa-f]{1,8})\s+([0-9A-Fa-f]{1,2})\s+')
+    start_pattern = re.compile(r'(C[12]):([0-9A-Fa-f]{7,8})\s+([0-9A-Fa-f]{1,2})\s+')
    byte_pattern = re.compile(r'^[0-9A-Fa-f]{2}$')
    with input_file.open('r', encoding='utf-8') as f_in, \
@@ -31,7 +35,12 @@ def parse_log(input_path: PathLike, out_bus1: PathLike, out_bus2: PathLike) -> N
        for line in f_in:
            for match in start_pattern.finditer(line):
                bus = match.group(1)
-                can_id = match.group(2).upper()
+
                can_id = match.group(2).upper().zfill(8)
                if int(can_id, 16) > 0x1FFFFFFF:
                    continue
                dlc_str = match.group(3)
                try:
@@ -68,7 +77,7 @@ def parse_csv(csv_path: PathLike) -> pl.LazyFrame:
    """
    lf = pl.scan_csv(csv_path, schema_overrides={"ID": pl.String, "Data": pl.String})
-    if "Timestamp" not in lf.columns:
+    if "Timestamp" not in lf.collect_schema().names():
        lf = lf.with_row_index("Timestamp")
    byte_exprs = []
@@ -112,4 +121,3 @@ if __name__ == '__main__':
        print(f"[*] Processing {args.input_csv}...")
        lf = parse_csv(args.input_csv)
        lf.sink_parquet(args.output_parquet)
        print(f"[+] Saved parquet file to {args.output_parquet}")
@@ -3,5 +3,13 @@ name = "CANveyor"
 version = "0.1.0"
 description = "J1939 CAN bus parser that works in pair with CANdigger"
 readme = "README.md"
-requires-python = ">=3.14"
+requires-python = ">=3.10"
-dependencies = ["polars", "pathlib", "typing"]
+dependencies = [
    "polars",
    "dash",
    "dash-bootstrap-components",
    "numpy",
    "pandas",
    "plotly",
    "plotly-resampler"
 ]
@@ -0,0 +1,177 @@
 # File: stats/correlation.py
 # Copyright (C) 2026 Erick Ahmed
 # SPDX-License-Identifier: AGPL-3.0-or-later
 """CAN bus inter-byte correlation analyzer and plotter."""
 import argparse
 from pathlib import Path
 from concurrent.futures import ThreadPoolExecutor
 from typing import List
 import numpy as np
 import pandas as pd
 import plotly.graph_objects as go
 from stats.utils.converter import format_can_id_vec as _format_can_id_vec, to_int
 from stats.utils.loader import load_data
 def _ensure_int_bytes(df: pd.DataFrame, cols: List[str]) -> pd.DataFrame:
    needs = [c for c in cols if not pd.api.types.is_numeric_dtype(df[c])]
    if needs:
        df = df.copy()
        for c in needs:
            df[c] = df[c].apply(to_int)
    return df
 def calculate_correlation(df: pd.DataFrame, method: str, target_id: str | None = None) -> pd.DataFrame:
    available_cols = [f"b{i}" for i in range(8) if f"b{i}" in df.columns]
    if not available_cols:
        raise ValueError("No byte columns (b0-b7) found in the DataFrame")
    can_id_col = 'ID' if 'ID' in df.columns else 'Identifier'
    identifiers = _format_can_id_vec(df[can_id_col]).to_numpy()
    df_bytes = _ensure_int_bytes(df, available_cols)[available_cols]
    data = df_bytes.to_numpy(dtype=np.float64, copy=False)
    if target_id is not None:
        target_id = _format_can_id_vec(pd.Series([target_id])).iloc[0]
        mask = identifiers == target_id
        if not mask.any():
            raise ValueError(f"Identifier '{target_id}' not found in data")
        sub = data[mask]
        mask = ~np.isnan(sub).any(axis=1)
        sub = sub[mask]
        if method == 'spearman' and sub.shape[0] > 1:
            sub = pd.DataFrame(sub).rank().to_numpy()
        if sub.shape[0] > 1:
            with np.errstate(divide='ignore', invalid='ignore'):
                c = np.corrcoef(sub, rowvar=False)
            np.nan_to_num(c, copy=False, nan=0.0)
        else:
            c = np.zeros((len(available_cols), len(available_cols)))
        return pd.DataFrame(c, index=available_cols, columns=available_cols)
    unique_ids, inverse = np.unique(identifiers, return_inverse=True)
    n_cols = len(available_cols)
    sort_idx = np.argsort(inverse, kind='stable')
    data_sorted = data[sort_idx]
    inverse_sorted = inverse[sort_idx]
    if len(inverse_sorted) > 0:
        split_points = np.flatnonzero(np.diff(inverse_sorted)) + 1
        groups = np.split(data_sorted, split_points)
    else:
        groups = []
    def _process_group(sub: np.ndarray) -> np.ndarray:
        mask = ~np.isnan(sub).any(axis=1)
        sub = sub[mask]
        if len(sub) > 1:
            if method == 'spearman':
                sub = pd.DataFrame(sub).rank().to_numpy()
            with np.errstate(divide='ignore', invalid='ignore'):
                c = np.abs(np.corrcoef(sub, rowvar=False))
            np.nan_to_num(c, copy=False, nan=0.0)
            np.fill_diagonal(c, 0.0)
            return c.max(axis=0)
        return np.zeros(n_cols, dtype=np.float64)
    out = np.zeros((len(unique_ids), n_cols), dtype=np.float64)
    if len(groups) > 0:
        with ThreadPoolExecutor() as executor:
            results = list(executor.map(_process_group, groups))
            for i, res in enumerate(results):
                out[i] = res
    result = pd.DataFrame(out, index=unique_ids, columns=available_cols)
    result.index.name = 'Identifier'
    return result
 def plot_correlation_heatmap(corr_df: pd.DataFrame, target_id: str | None, title: str) -> go.Figure:
    is_8x8 = target_id is not None
    x = corr_df.columns.tolist()
    y = corr_df.index.tolist()
    z = corr_df.values
    if is_8x8:
        z_min, z_max = -1.0, 1.0
        colorscale = [[0.0, "#2c7bb6"], [0.25, "#abd9e9"], [0.5, "#ffffff"], [0.75, "#fdae61"], [1.0, "#d7191c"]]
        hover_template = "<b>%{y}</b> vs <b>%{x}</b><br>Correlation: %{z:.2f}<extra></extra>"
    else:
        z_min, z_max = 0.0, 1.0
        colorscale = [[0.0, "#ffffff"], [0.2, "#fff5f0"], [0.4, "#fecc5c"], [0.6, "#fd8d3c"], [0.8, "#e31a1c"], [1.0, "#800026"]]
        hover_template = "<b>%{y}</b><br>Byte %{x} max correlation: %{z:.2f}<extra></extra>"
    fig = go.Figure(
        data=go.Heatmap(
            z=z, x=x, y=y,
            zmin=z_min, zmax=z_max,
            colorscale=colorscale,
            xgap=3, ygap=3,
            text=np.round(z, 2),
            texttemplate="%{text}",
            textfont={"size": 11, "color": "#2a2a2a", "family": "Segoe UI, Arial, sans-serif"},
            hoverongaps=False,
            hovertemplate=hover_template,
            colorbar=dict(
                title=dict(text="Correlation", side="top", font=dict(size=13, color="#1a1a1a")),
                orientation="h", thickness=15, len=0.35,
                x=1.0, xanchor="right", y=1.02, yanchor="bottom",
                tickfont=dict(size=11, color="#2a2a2a"),
                tickformat=".1f", outlinewidth=0.5, outlinecolor="#cccccc",
            ),
        )
    )
    fig.update_layout(
        title=dict(text=title, font=dict(size=20, color="#1a1a1a"), x=0.5, xanchor="center", pad=dict(b=20)),
        height=600 if is_8x8 else max(600, len(y) * 28 + 150),
        autosize=True,
        template="plotly_white",
        xaxis=dict(
            title=dict(text="Byte Position", font=dict(size=13, color="#1a1a1a")),
            side="bottom" if is_8x8 else "top",
            dtick=1, showgrid=False, linecolor="#bdbdbd",
            tickfont=dict(size=12, color="#2a2a2a"), ticks="outside", ticklen=4, tickcolor="#cccccc",
        ),
        yaxis=dict(
            title=dict(text="Byte Position" if is_8x8 else "PGN or CAN ID", font=dict(size=13, color="#1a1a1a")),
            autorange="reversed", showgrid=False, linecolor="#bdbdbd",
            tickfont=dict(size=12, color="#2a2a2a"), ticks="outside", ticklen=4, tickcolor="#cccccc", automargin=True,
        ),
        font=dict(family="Segoe UI, Arial, sans-serif", size=12, color="#2a2a2a"),
        hoverlabel=dict(bgcolor="white", font_size=13, font_family="Segoe UI", bordercolor="#cccccc"),
        margin=dict(l=200, r=40, t=120, b=60),
    )
    return fig
 if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Analyze CAN bus inter-byte correlation")
    parser.add_argument("method", choices=["pearson", "spearman"], help="Correlation method to use")
    parser.add_argument("input", type=Path, help="Path to the input CAN log file")
    parser.add_argument("output", type=Path, nargs="?", default=Path("correlation_report.html"))
    parser.add_argument("title", nargs="?", default="CAN Bus Inter-Byte Correlation")
    parser.add_argument("--identifier", type=str, default=None)
    args = parser.parse_args()
    df = load_data(args.input)
    corr_df = calculate_correlation(df, method=args.method, target_id=args.identifier)
    display_title = f"{args.title} ({args.identifier})" if args.identifier else args.title
    fig = plot_correlation_heatmap(corr_df, target_id=args.identifier, title=display_title)
    config = {
        "responsive": True,
        "displaylogo": False,
        "scrollZoom": True,
        "modeBarButtonsToAdd": ["toggleSpikelines"],
        "toImageButtonOptions": {"format": "png", "scale": 2},
    }
    fig.write_html(str(args.output), include_plotlyjs="cdn", config=config)
@@ -0,0 +1,155 @@
 # File: stats/entropy.py
 # Copyright (C) 2026 Erick Ahmed
 # SPDX-License-Identifier: AGPL-3.0-or-later
 """CAN bus byte-level entropy analyzer and plotter."""
 import argparse
 from pathlib import Path
 from concurrent.futures import ThreadPoolExecutor
 from typing import List
 import numpy as np
 import pandas as pd
 import plotly.graph_objects as go
 from stats.utils.converter import format_can_id_vec as _format_can_id_vec, to_int
 from stats.utils.loader import load_data
 def _entropy_col(a: np.ndarray) -> float:
    a = a[~np.isnan(a)]
    if a.size == 0:
        return 0.0
    a = a.astype(np.int64)
    lo, hi = a.min(), a.max()
    span = hi - lo + 1
    if span <= 0:
        return 0.0
    if span > 1 << 20:
        _, counts = np.unique(a, return_counts=True)
    else:
        counts = np.bincount(a - lo, minlength=span)
        counts = counts[counts > 0]
    p = counts / counts.sum()
    return float(-np.sum(p * np.log2(p)))
 def calculate_byte_entropy(df: pd.DataFrame) -> pd.DataFrame:
    available_cols = [f"b{i}" for i in range(8) if f"b{i}" in df.columns]
    if not available_cols:
        raise ValueError("No byte columns (b0-b7) found in the DataFrame")
    can_id_col = 'ID' if 'ID' in df.columns else 'Identifier'
    identifiers = _format_can_id_vec(df[can_id_col]).to_numpy()
    needs = [c for c in available_cols if not pd.api.types.is_numeric_dtype(df[c])]
    if needs:
        df = df.copy()
        for c in needs:
            df[c] = df[c].apply(to_int)
    data = df[available_cols].to_numpy(dtype=np.float64, copy=False)
    unique_ids, inverse = np.unique(identifiers, return_inverse=True)
    n_cols = len(available_cols)
    sort_idx = np.argsort(inverse, kind='stable')
    data_sorted = data[sort_idx]
    inverse_sorted = inverse[sort_idx]
    if len(inverse_sorted) > 0:
        split_points = np.flatnonzero(np.diff(inverse_sorted)) + 1
        groups = np.split(data_sorted, split_points)
    else:
        groups = []
    def _process_group(sub: np.ndarray) -> np.ndarray:
        res = np.zeros(n_cols, dtype=np.float64)
        for ci in range(n_cols):
            res[ci] = _entropy_col(sub[:, ci])
        return res
    out = np.zeros((len(unique_ids), n_cols), dtype=np.float64)
    if len(groups) > 0:
        with ThreadPoolExecutor() as executor:
            results = list(executor.map(_process_group, groups))
            for i, res in enumerate(results):
                out[i] = res
    result = pd.DataFrame(out, index=unique_ids, columns=available_cols)
    result.index.name = 'Identifier'
    return result
 def plot_entropy_heatmap(entropy_df: pd.DataFrame, title: str) -> go.Figure:
    x = entropy_df.columns.tolist()
    y = entropy_df.index.tolist()
    z = entropy_df.values
    fig = go.Figure(
        data=go.Heatmap(
            z=z, x=x, y=y,
            colorscale=[
                [0.0, "#ffffff"],
                [0.15, "#fff7ec"],
                [0.35, "#fee8c8"],
                [0.55, "#fdd49e"],
                [0.75, "#fdbb84"],
                [1.0, "#ef6548"],
            ],
            xgap=3, ygap=3,
            text=np.round(z, 2),
            texttemplate="%{text}",
            textfont={"size": 11, "color": "#2a2a2a", "family": "Segoe UI, Arial, sans-serif"},
            hoverongaps=False,
            hovertemplate="<b>%{y}</b><br>Byte %{x}: %{z:.2f} bits<extra></extra>",
            colorbar=dict(
                title=dict(text="Entropy (bits)", side="top", font=dict(size=13, color="#1a1a1a")),
                orientation="h", thickness=15, len=0.35,
                x=1.0, xanchor="right", y=1.02, yanchor="bottom",
                tickfont=dict(size=11, color="#2a2a2a"),
                tickformat=".1f", outlinewidth=0.5, outlinecolor="#cccccc",
            ),
        )
    )
    fig.update_layout(
        title=dict(text=title, font=dict(size=20, color="#1a1a1a"), x=0.5, xanchor="center", pad=dict(b=20)),
        height=max(600, len(y) * 28 + 150),
        autosize=True,
        template="plotly_white",
        xaxis=dict(
            title=dict(text="Byte Position", font=dict(size=13, color="#1a1a1a")),
            side="top", dtick=1, showgrid=False, linecolor="#bdbdbd",
            tickfont=dict(size=12, color="#2a2a2a"), ticks="outside", ticklen=4, tickcolor="#cccccc",
        ),
        yaxis=dict(
            title=dict(text="PGN or CAN ID", font=dict(size=13, color="#1a1a1a")),
            autorange="reversed", showgrid=False, linecolor="#bdbdbd",
            tickfont=dict(size=12, color="#2a2a2a"), ticks="outside", ticklen=4, tickcolor="#cccccc", automargin=True,
        ),
        font=dict(family="Segoe UI, Arial, sans-serif", size=12, color="#2a2a2a"),
        hoverlabel=dict(bgcolor="white", font_size=13, font_family="Segoe UI", bordercolor="#cccccc"),
        margin=dict(l=200, r=40, t=120, b=60),
    )
    return fig
 if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Analyze CAN bus byte-level entropy")
    parser.add_argument("input", type=Path, help="Path to the input CAN log file")
    parser.add_argument("output", type=Path, nargs="?", default=Path("entropy_report.html"))
    parser.add_argument("title", nargs="?", default="CAN Bus Byte-Level Entropy")
    args = parser.parse_args()
    df = load_data(args.input)
    entropy_df = calculate_byte_entropy(df)
    fig = plot_entropy_heatmap(entropy_df, title=args.title)
    config = {
        "responsive": True,
        "displaylogo": False,
        "scrollZoom": True,
        "modeBarButtonsToAdd": ["toggleSpikelines"],
        "toImageButtonOptions": {"format": "png", "scale": 2},
    }
    fig.write_html(str(args.output), include_plotlyjs="cdn", config=config)
@@ -0,0 +1,128 @@
 # File: stats/frequency.py
 # Copyright (C) 2026 Erick Ahmed
 # SPDX-License-Identifier: AGPL-3.0-or-later
 """CAN bus message frequency analyzer and plotter."""
 import argparse
 from pathlib import Path
 import numpy as np
 import pandas as pd
 import plotly.graph_objects as go
 from stats.utils.converter import format_can_id_vec as _format_can_id_vec
 from stats.utils.loader import load_data
 def calculate_frequency(df: pd.DataFrame) -> pd.DataFrame:
    can_id_col = 'ID' if 'ID' in df.columns else 'Identifier'
    formatted = _format_can_id_vec(df[can_id_col])
    counts = formatted.value_counts()
    freq_df = pd.DataFrame({
        'Identifier': counts.index,
        'Count': counts.to_numpy(),
    })
    total = counts.sum()
    freq_df['Percentage'] = np.round(freq_df['Count'] / total * 100, 2) if total else 0.0
    return freq_df.sort_values('Count', ascending=True).reset_index(drop=True)
 def plot_frequency(stats_df: pd.DataFrame, title: str) -> go.Figure:
    n = len(stats_df)
    fig = go.Figure(go.Bar(
        y=stats_df['Identifier'],
        x=stats_df['Count'],
        orientation='h',
        marker=dict(
            color=stats_df['Count'],
            colorscale='Turbo',
            cmin=int(stats_df['Count'].min()) if n else 0,
            cmax=int(stats_df['Count'].max()) if n else 1,
            line_width=0,
        ),
        customdata=stats_df[['Percentage']].to_numpy(),
        hovertemplate="<b>%{y}</b><br>Count: %{x:,}<br>Share: %{customdata[0]}%<extra></extra>",
        texttemplate='%{x:,}',
        textposition='outside',
        cliponaxis=False,
    ))
    fig.update_layout(
        height=max(600, n * 18),
        autosize=True,
        template='plotly_white',
        xaxis=dict(
            type='log',
            title=dict(text="Message count [log scale]", font=dict(size=13, color="#1a1a1a")),
            side="top",
            dtick=1,
            showgrid=False,
            linecolor="#bdbdbd",
            tickfont=dict(size=12, color="#2a2a2a"),
            ticks="outside",
            ticklen=4,
            tickcolor="#cccccc",
        ),
        yaxis=dict(
            title=dict(text="PGN or CAN ID", font=dict(size=13, color="#1a1a1a")),
            showgrid=False,
            linecolor="#bdbdbd",
            tickfont=dict(size=12, color="#2a2a2a"),
            ticks="outside",
            ticklen=4,
            tickcolor="#cccccc",
            automargin=True,
            type='category',
        ),
        font=dict(family="Segoe UI, Arial, sans-serif", size=12, color='#2a2a2a'),
        hoverlabel=dict(bgcolor="white", font_size=13, font_family="Segoe UI", bordercolor='#cccccc'),
        margin=dict(l=200, r=40, t=120, b=60),
        bargap=0.35,
        coloraxis_colorbar=dict(
            title=dict(text='Message Count', side='top'),
            orientation='h',
            thickness=15,
            len=0.35,
            x=1.0,
            xanchor='right',
            y=1.02,
            yanchor='bottom',
            tickformat=',',
            outlinecolor='#cccccc',
            outlinewidth=0.5,
        ),
        title=dict(text=title, font=dict(size=20, color='#1a1a1a'), x=0.5, xanchor='center', pad=dict(b=20)),
    )
    fig.update_xaxes(
        showgrid=True, gridwidth=0.5, gridcolor='#e8e8e8',
        zeroline=False, linecolor='#bdbdbd', mirror=False,
        tickformat=',',
        minor=dict(showgrid=True, gridcolor='#f4f4f4', gridwidth=0.5),
    )
    fig.update_yaxes(
        showgrid=False, zeroline=False, linecolor='#bdbdbd',
        ticks='outside', ticklen=4, tickcolor='#cccccc', automargin=True,
    )
    return fig
 if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Analyze CAN bus message frequency")
    parser.add_argument("input", type=Path, help="Path to the input CAN log file")
    parser.add_argument("output", type=Path, nargs="?", default=Path("freq_report.html"))
    parser.add_argument("title", nargs="?", default="Frequency")
    args = parser.parse_args()
    df = load_data(args.input)
    stats = calculate_frequency(df)
    fig = plot_frequency(stats, title=args.title)
    config = {
        'responsive': True,
        'displaylogo': False,
        'scrollZoom': True,
        'modeBarButtonsToAdd': ['toggleSpikelines'],
        'toImageButtonOptions': {'format': 'png', 'scale': 2},
    }
    fig.write_html(str(args.output), include_plotlyjs='cdn', config=config)
@@ -0,0 +1,151 @@
 # File: stats/id_viewer.py
 # Copyright (C) 2026 Erick Ahmed
 # SPDX-License-Identifier: AGPL-3.0-or-later
 """Interactive CAN bus byte-change visualizer."""
 import argparse
 from pathlib import Path
 from typing import List, Tuple
 import numpy as np
 import pandas as pd
 import plotly.graph_objects as go
 from plotly_resampler import FigureResampler
 from stats.utils.converter import format_can_id_vec as _format_can_id_vec
 from stats.utils.loader import load_data
 _BYTE_COLORS = [
    '#e41a1c', '#377eb8', '#4daf4a', '#984ea3',
    '#ff7f00', '#ffff33', '#a65628', '#f781bf',
 ]
 def prepare_data(df: pd.DataFrame, target_id: str) -> Tuple[pd.DataFrame, List[str]]:
    can_id_col = 'ID' if 'ID' in df.columns else 'Identifier'
    df = df.assign(Formatted_ID=_format_can_id_vec(df[can_id_col]))
    target_id_clean = _format_can_id_vec(pd.Series([target_id])).iloc[0]
    filtered = df[df['Formatted_ID'] == target_id_clean]
    byte_cols = [f"b{i}" for i in range(8) if f"b{i}" in filtered.columns]
    if filtered.empty:
        return filtered, byte_cols
    for col in byte_cols:
        if not pd.api.types.is_numeric_dtype(filtered[col]):
            filtered = filtered.assign(
                **{col: pd.to_numeric(filtered[col], errors='coerce').astype('float32')}
            )
    filtered = filtered.sort_values('Timestamp', kind='stable')
    arr = filtered[byte_cols].to_numpy(dtype=np.float32, copy=False)
    if len(arr) > 1:
        changed = np.any(arr[1:] != arr[:-1], axis=1)
        keep = np.concatenate(([True], changed))
        filtered = filtered.iloc[keep]
    return filtered, byte_cols
 def plot_bits(df: pd.DataFrame, byte_cols: List[str], can_id: str, title: str) -> FigureResampler:
    fig = FigureResampler(
        resampled_trace_prefix_suffix=("", ""),
        show_mean_aggregation_size=False
    )
    n = len(byte_cols)
    x = df['Timestamp'].to_numpy() if not df.empty else np.array([])
    for i, col in enumerate(byte_cols):
        y = df[col].to_numpy(dtype=np.float32, copy=False) if not df.empty else np.array([])
        fig.add_trace(go.Scatter(
            mode='lines',
            line=dict(shape='hv', width=2, color=_BYTE_COLORS[i % len(_BYTE_COLORS)]),
            name=col.upper(),
            legendgroup=col.upper(),
            hovertemplate=f"<b>{col.upper()}</b><br>Time: %{{x}}<br>Value: %{{y}}<extra></extra>",
        ), hf_x=x, hf_y=y)
    all_button = dict(label='ALL', method='restyle', args=[{'visible': [True] * n}])
    none_button = dict(label='NONE', method='restyle', args=[{'visible': ['legendonly'] * n}])
    fig.update_layout(
        height=600,
        autosize=True,
        template='plotly_white',
        title=dict(
            text=f"{title} - ID: {can_id}",
            font=dict(size=20, color='#1a1a1a'),
            x=0.5, xanchor='center',
            pad=dict(b=20),
        ),
        font=dict(family="Segoe UI, Arial, sans-serif", size=12, color='#2a2a2a'),
        hoverlabel=dict(bgcolor="white", font_size=13, font_family="Segoe UI", bordercolor='#cccccc'),
        margin=dict(l=60, r=40, t=120, b=140),
        legend=dict(
            orientation='h',
            x=0.5, xanchor='center',
            y=-0.18, yanchor='top',
            title=None,
            bgcolor='white',
            bordercolor='#cccccc',
            borderwidth=1,
            font=dict(size=12, color="#2a2a2a"),
            itemsizing='constant',
            itemclick='toggle',
            itemdoubleclick='toggleothers',
        ),
        xaxis=dict(
            title=dict(text="Timestamp", font=dict(size=13, color="#1a1a1a")),
            showgrid=True, gridwidth=0.5, gridcolor='#e8e8e8',
            zeroline=False, linecolor="#bdbdbd",
            tickfont=dict(size=12, color="#2a2a2a"),
            ticks="outside", ticklen=4, tickcolor="#cccccc",
            minor=dict(showgrid=True, gridcolor='#f4f4f4', gridwidth=0.5),
        ),
        yaxis=dict(
            title=dict(text="Byte Value", font=dict(size=13, color="#1a1a1a")),
            showgrid=True, gridwidth=0.5, gridcolor='#e8e8e8',
            zeroline=False, linecolor="#bdbdbd",
            tickfont=dict(size=12, color="#2a2a2a"),
            ticks="outside", ticklen=4, tickcolor="#cccccc",
        ),
        updatemenus=[
            dict(
                type='buttons',
                direction='right',
                x=0.5, xanchor='center',
                y=-0.06, yanchor='top',
                buttons=[all_button, none_button],
                bgcolor='white',
                bordercolor='#cccccc',
                borderwidth=1,
                font=dict(size=11, color='#2a2a2a'),
                pad=dict(l=5, r=5, t=5, b=5),
            )
        ],
    )
    return fig
 if __name__ == "__main__":
    parser = argparse.ArgumentParser(description="Visualize CAN bus byte changes over time")
    parser.add_argument("input", type=Path, help="Path to the input CAN log file")
    parser.add_argument("can_id", type=str, help="CAN ID to visualize")
    parser.add_argument("output", type=Path, nargs="?", default=Path("bits_report.html"))
    parser.add_argument("title", nargs="?", default="Byte Visualization")
    args = parser.parse_args()
    df = load_data(args.input)
    filtered_df, byte_cols = prepare_data(df, args.can_id)
    fig = plot_bits(filtered_df, byte_cols, args.can_id, title=args.title)
    config = {
        'responsive': True,
        'displaylogo': False,
        'scrollZoom': True,
        'modeBarButtonsToAdd': ['toggleSpikelines'],
        'toImageButtonOptions': {'format': 'png', 'scale': 2},
    }
    fig.write_html(str(args.output), include_plotlyjs='cdn', config=config)
@@ -0,0 +1,19 @@
 # File: vehicle/__init__.py
 # Copyright (C) 2026 Erick Ahmed
 # SPDX-License-Identifier: AGPL-3.0-or-later
 import importlib
 def get_vehicle_module(brand: str):
    """
    Dynamically imports the correct decoder module based on the vehicle brand.
    Falls back to 'vehicle.generic' if a specific brand module is not found.
    """
    if not brand:
        return importlib.import_module("vehicle.generic")
    module_name = f"vehicle.{brand.lower().replace(' ', '_')}"
    try:
        return importlib.import_module(module_name)
    except ModuleNotFoundError:
        return importlib.import_module("vehicle.generic")
@@ -0,0 +1,186 @@
 # File: vehicle/base.py
 # Copyright (C) 2026 Erick Ahmed
 # SPDX-License-Identifier: AGPL-3.0-or-later
 """Core data structures and helpers for J1939/CAN signal decoding."""
 from dataclasses import dataclass, field
 from typing import Dict, List
 import numpy as np
 import pandas as pd
 import plotly.graph_objects as go
@dataclass
 class SignalDef:
    """Definition of a single signal within a CAN frame."""
    name: str
    bit_start: int
    bit_length: int
    factor: float = 1.0
    offset: float = 0.0
    is_signed: bool = False
    byte_order: str = "little"
    unit: str = ""
@dataclass
 class FrameDef:
    """Definition of a CAN frame and its contained signals."""
    can_id: str
    description: str = ""
    color: str = "#377eb8"
    signals: List[SignalDef] = field(default_factory=list)
 def normalize_id(can_id: str) -> str:
    """Normalize a CAN ID string to uppercase hex without leading zeros/0x."""
    s = str(can_id).strip().upper()
    if s.startswith("0X"):
        s = s[2:]
    return s.lstrip("0") or "0"
 def _byte_indices(sig: SignalDef) -> List[int]:
    """Return the in-range byte positions spanned by *sig*."""
    byte_lo = sig.bit_start // 8
    byte_hi = (sig.bit_start + sig.bit_length - 1) // 8
    return [i for i in range(byte_lo, byte_hi + 1) if 0 <= i < 8]
 def _extract_signal(bytes_arr: np.ndarray, sig: SignalDef) -> np.ndarray:
    """Extract raw signal values from an (N, 8) byte array and apply scaling."""
    if bytes_arr.size == 0:
        return np.zeros(0, dtype=np.float64)
    byte_indices = _byte_indices(sig)
    if not byte_indices:
        return np.full(bytes_arr.shape[0], np.nan, dtype=np.float64)
    raw = np.zeros(bytes_arr.shape[0], dtype=np.int64)
    if sig.byte_order == "little":
        for shift, bi in enumerate(byte_indices):
            raw += bytes_arr[:, bi].astype(np.int64) << (shift * 8)
    else:
        for shift, bi in enumerate(reversed(byte_indices)):
            raw += bytes_arr[:, bi].astype(np.int64) << (shift * 8)
    raw = raw >> (sig.bit_start % 8)
    raw = raw & ((1 << sig.bit_length) - 1)
    if sig.is_signed and sig.bit_length < 64:
        sign_bit = 1 << (sig.bit_length - 1)
        raw = (raw ^ sign_bit) - sign_bit
    return raw.astype(np.float64) * sig.factor + sig.offset
 def decode_dataframe(
    df: pd.DataFrame, can_id: str, decoder_rules: Dict[str, FrameDef]
 ) -> pd.DataFrame:
    """Decode all signals for *can_id* from *df* into a new DataFrame."""
    norm = normalize_id(can_id)
    if norm not in decoder_rules:
        return pd.DataFrame()
    frame_def = decoder_rules[norm]
    id_col = "ID" if "ID" in df.columns else "Identifier"
    df_ids = df[id_col].astype(str).map(normalize_id)
    sub = df.loc[df_ids == norm].copy()
    if sub.empty:
        return pd.DataFrame()
    byte_cols = [f"b{i}" for i in range(8) if f"b{i}" in sub.columns]
    if not byte_cols:
        return pd.DataFrame()
    arr = np.zeros((len(sub), 8), dtype=np.int64)
    for i, c in enumerate(byte_cols):
        arr[:, i] = (
            pd.to_numeric(sub[c], errors="coerce")
            .fillna(0)
            .astype(np.int64)
            .to_numpy()
        )
    out = pd.DataFrame()
    out["Timestamp"] = (
        sub["Timestamp"].to_numpy()
        if "Timestamp" in sub.columns
        else np.arange(len(sub))
    )
    for sig in frame_def.signals:
        out[sig.name] = _extract_signal(arr, sig)
    return out
 def plot_signal(
    df: pd.DataFrame,
    signal_name: str,
    title: str,
    color: str = "#377eb8",
    height: int = 280,
 ) -> go.Figure:
    """Plot a single signal over time as a line chart."""
    fig = go.Figure()
    if df.empty or signal_name not in df.columns:
        fig.update_layout(
            title=dict(text=title, font=dict(size=14)),
            annotations=[
                dict(
                    text="No data", showarrow=False, x=0.5, y=0.5,
                    font=dict(size=13, color="#888"),
                )
            ],
            height=height,
            template="plotly_white",
        )
        return fig
    fig.add_trace(
        go.Scatter(
            x=df["Timestamp"],
            y=df[signal_name],
            mode="lines",
            line=dict(width=2, color=color),
            name=signal_name,
            hovertemplate=(
                f"<b>{signal_name}</b><br>Time: %{{x}}<br>"
                f"Value: %{{y:.2f}}<extra></extra>"
            ),
        )
    )
    fig.update_layout(
        title=dict(
            text=title, font=dict(size=14, color="#1a1a1a"),
            x=0.5, xanchor="center", pad=dict(b=10),
        ),
        height=height,
        autosize=True,
        template="plotly_white",
        margin=dict(l=55, r=20, t=55, b=45),
        xaxis=dict(
            title=dict(text="Time", font=dict(size=11)),
            showgrid=True, gridwidth=0.5, gridcolor="#eee",
            zeroline=False, linecolor="#bdbdbd",
        ),
        yaxis=dict(
            title=dict(text=signal_name, font=dict(size=11)),
            showgrid=True, gridwidth=0.5, gridcolor="#eee",
            zeroline=False, linecolor="#bdbdbd",
        ),
        font=dict(family="Segoe UI, Arial, sans-serif", size=11, color="#2a2a2a"),
        hoverlabel=dict(
            bgcolor="white", font_size=12,
            font_family="Segoe UI", bordercolor="#cccccc",
        ),
    )
    return fig
@@ -0,0 +1,180 @@
 # File: vehicle/komatsu.py
 # Copyright (C) 2026 Erick Ahmed
 # SPDX-License-Identifier: AGPL-3.0-or-later
 """Komatsu-specific CAN frame decoder rules and custom plot definitions."""
 from copy import deepcopy
 from dataclasses import dataclass
 from typing import Callable, Dict
 import pandas as pd
 import plotly.express as px
 from vehicle.base import (
    FrameDef,
    SignalDef,
    decode_dataframe as _decode_dataframe,
    normalize_id,
    plot_signal,
 )
@dataclass
 class CustomPlotDef:
    """A non-signal entry in a FrameDef that carries its own plotting function."""
    name: str
    plot_func: Callable
 load_state_sig = SignalDef(
    name="Engine Load State",
    bit_start=24,
    bit_length=8,
    factor=1,
    offset=0.0,
    is_signed=False,
    byte_order="big",
    unit="",
 )
 load_state_sig.skip_plot = True
 DECODER_RULES: Dict[str, FrameDef] = {
    normalize_id("0x011F"): FrameDef(
        can_id="0x011F",
        description="ECM",
        color="#e41a1c",
        signals=[
            SignalDef(
                name="Engine",
                bit_start=0,
                bit_length=16,
                factor=0.125,
                offset=0.0,
                is_signed=False,
                byte_order="big",
                unit="RPM",
            ),
            SignalDef(
                name="Engine Load",
                bit_start=16,
                bit_length=16,
                factor=0.05,
                offset=0,
                is_signed=False,
                byte_order="little",
                unit="%",
            ),
        ],
    ),
    normalize_id("0x0CFF3300"): FrameDef(
        can_id="0x0CFF3300",
        description="Engine temperatures",
        color="#0080fe",
        signals=[
            SignalDef(
                name="Engine coolant temp",
                bit_start=8,
                bit_length=8,
                factor=1,
                offset=0.0,
                is_signed=False,
                byte_order="big",
                unit="℃",
            ),
            SignalDef(
                name="Engine oil temp",
                bit_start=40,
                bit_length=8,
                factor=1,
                offset=0.0,
                is_signed=False,
                byte_order="big",
                unit="℃",
            ),
            load_state_sig,
            CustomPlotDef(
                name="Engine Load",
                plot_func=lambda decoded, color: plot_load_state_pie(decoded, color),
            ),
        ],
    ),
 }
 LOAD_STATE_MAP = {
    0: "Boot up",
    16: "Normal load",
    32: "High load",
 }
 _LOAD_STATE_COLORS = {
    "Boot up": "#ff9900",
    "Normal load": "#00cc00",
    "High load": "#cc0000",
    "Unknown": "#808080",
 }
 def plot_load_state_pie(decoded_df, color):
    """Render a pie chart showing the distribution of engine load states."""
    if decoded_df is None or decoded_df.empty or "Engine Load State" not in decoded_df.columns:
        fig = px.pie()
        fig.update_layout(
            title=dict(
                text="Engine Load State",
                font=dict(size=14, color="#1a1a1a"),
                x=0.5, xanchor="center", pad=dict(b=10)
            ),
            height=280,
            template="plotly_white",
            annotations=[dict(text="No data", showarrow=False, x=0.5, y=0.5, font=dict(size=13, color="#888"))]
        )
        return fig
    states = pd.to_numeric(decoded_df["Engine Load State"], errors="coerce").dropna().astype(int)
    labels = states.map(LOAD_STATE_MAP).fillna("Unknown")
    counts = labels.value_counts().reset_index()
    counts.columns = ["State", "Count"]
    total = counts["Count"].sum()
    counts["Percentage"] = (counts["Count"] / total * 100).round(1)
    counts["Legend"] = counts["State"] + " (" + counts["Percentage"].astype(str) + "%)"
    fig = px.pie(
        counts,
        values="Count",
        names="Legend",
        color="State",
        color_discrete_map=_LOAD_STATE_COLORS,
    )
    fig.update_traces(
        textinfo="none",
        hoverinfo="label+percent+value",
        domain={"x": [0.05, 0.55], "y": [0.05, 0.95]},
    )
    fig.update_layout(
        title=dict(
            text="Engine Load State",
            font=dict(size=14, color="#1a1a1a"),
            x=0.5, xanchor="center", pad=dict(b=10)
        ),
        height=280,
        autosize=True,
        template="plotly_white",
        margin=dict(l=20, r=20, t=55, b=45),
        font=dict(family="Segoe UI, Arial, sans-serif", size=11, color="#2a2a2a"),
        legend=dict(x=0.6, y=0.5),
    )
    return fig
 def decode_dataframe(df, can_id):
    """Decode *can_id* from *df*, filtering out non-SignalDef entries first."""
    filtered_rules: Dict[str, FrameDef] = {}
    for nid, frame in DECODER_RULES.items():
        new_frame = deepcopy(frame)
        new_frame.signals = [s for s in frame.signals if isinstance(s, SignalDef)]
        filtered_rules[nid] = new_frame
    return _decode_dataframe(df, can_id, filtered_rules)
Author	SHA1	Message	Date
eeeck	d0141e821f	Minor title changes	2026-07-24 08:53:40 +02:00
eeeck	23d7696076	Change pie chart font for consistency	2026-07-24 08:53:29 +02:00
eeeck	92ff701dab	Simplify plot title by removing CAN ID	2026-07-23 16:16:12 +02:00
eeeck	1e5506de50	Merge pull request 'Refactor CANveyor dashboard architecture' (#8 ) from dev-cleanup into dev-dash Reviewed-on: erickahmed/CANveyor#8	2026-07-23 16:03:47 +02:00
eeeck	4f280da033	Refactor CANveyor dashboard architecture - Replace `stats.utils.extractor` with dedicated `loader` and `converter` modules to improve code organization. - Implement explicit pipeline stages for ingestion, decoding, and precomputation with caching. - Standardize data loading and J1939 parsing logic across sub-modules. - Enhance dashboard responsiveness by pre-calculating figures and downsampling ID-grouped data. - Enforce strict typing and add docstrings to public components.	2026-07-23 16:01:34 +02:00
eeeck	89a9124a83	Add custom plotting support for vehicle signal - Plot pie chart for engine load state	2026-07-23 15:37:50 +02:00
eeeck	0eac7a571f	Add color configuration and extra signals to vehicle frames	2026-07-23 13:26:37 +02:00
eeeck	be7cf9cb6a	Minor text box tweak	2026-07-23 00:39:52 +02:00
eeeck	9dbf50d1c5	Simplify UI labels for vehicle and bus selectors	2026-07-23 00:38:33 +02:00
eeeck	7da427dd09	Implement a modular vehicle decoding system - Add Komatsu specific rules - Possibility to expand to any brand	2026-07-23 00:34:18 +02:00
eeeck	fab448785b	Replace infinite scroll with paginated log view	2026-07-22 23:09:47 +02:00
eeeck	3b703e845f	Increase chunk size from 1000 to 50000	2026-07-22 22:00:39 +02:00
eeeck	54fd8ce74c	Implement infinite scroll for logs table	2026-07-22 21:39:47 +02:00
eeeck	e0a4d098d9	Replace Plotly graph-based tables with Dash DataTable	2026-07-22 21:23:58 +02:00
eeeck	42f8b844d9	Add log visualization tab to dashboard	2026-07-22 21:01:19 +02:00
eeeck	27998ff879	Add multi-vehicle support to dashboard and pipeline	2026-07-22 20:30:57 +02:00
eeeck	d8ca263c0d	Bump version and update project dependencies	2026-07-22 20:16:52 +02:00
eeeck	1463fa12ff	Parallelize data processing tasks with ThreadPoolExecutor	2026-07-22 20:13:19 +02:00
eeeck	6c198d83c5	Remove debug flag	2026-07-22 20:06:50 +02:00
eeeck	57505074cd	Change title to project name	2026-07-22 20:01:58 +02:00
eeeck	af8e916116	Create an Overview menu - To use as a sort of main menu	2026-07-22 20:00:59 +02:00
eeeck	d9262e365a	Put all CAN bus statistics submenus under a Statistics menu	2026-07-22 20:00:13 +02:00
eeeck	24ce8dad60	Explicitly specify grouping column in dataframe iteration	2026-07-22 19:47:11 +02:00
eeeck	22d4af292c	Refactor CSV to Parquet conversion logic	2026-07-22 19:47:05 +02:00
eeeck	5e01c3bb44	Ensure data directories exist before pipeline execution	2026-07-22 19:46:59 +02:00
eeeck	d6baaaa1fa	Remove redundant Formatted_ID column in frequency calculation	2026-07-22 19:46:51 +02:00
eeeck	9965bc761f	Simplify byte column selection in correlation calculation	2026-07-22 19:46:45 +02:00
eeeck	0a4dc5801e	Merge pull request 'Implement plotly resamper and precompute data' (#5 ) from dev-plotly-resampler into dev-dash Reviewed-on: erickahmed/CANveyor#5	2026-07-22 18:40:44 +02:00
eeeck	c06d813c26	Remove resampling information on legend	2026-07-22 18:39:03 +02:00
eeeck	2da646fa80	Precompute CAN data - Slower startup - Much faster visualization (from O(n) to O(1))	2026-07-22 18:20:18 +02:00
eeeck	93e0e3f648	Suppress callback exceptions	2026-07-22 18:16:43 +02:00
eeeck	02e46ddf0b	Implement plotly-resampler	2026-07-22 18:11:35 +02:00
eeeck	d274897cf3	Implement lttbc	2026-07-22 18:07:33 +02:00
eeeck	65591bbc6b	Refactor main application to use Polars pipeline - replaced the caching layer with a pre-processing pipeline that parses raw logs into decoded Parquet files	2026-07-15 00:48:51 +02:00
eeeck	c98563f541	Fix schema check and update import paths - Use `collect_schema` for accurate column validation in Polars and correct relative import paths for statistical modules.	2026-07-15 00:48:30 +02:00
eeeck	3df42fb497	Make subdirectories Python packages	2026-07-15 00:37:19 +02:00
eeeck	73e76d3adc	Rename to avoid conflict with Python stat module	2026-07-15 00:31:27 +02:00
eeeck	7a0e2efba1	Integrate Dash background callbacks to handle computations in async	2026-07-15 00:18:27 +02:00
eeeck	a2ac49c79f	Refactor statistical analysis modules for performance - Optimize data processing pipelines across files by replacing iterative pandas operations with vectorized NumPy routines	2026-07-15 00:17:59 +02:00
eeeck	0780a61d78	Improve bit selection	2026-07-14 23:46:09 +02:00
eeeck	fae85d1af9	Change title	2026-07-14 14:28:15 +02:00
eeeck	c9461868cc	Implement CAN ID visualization at the bit level	2026-07-14 14:14:09 +02:00
eeeck	2408c7a963	Use better function names	2026-07-14 00:37:47 +02:00
eeeck	179ec6e56b	Add header	2026-07-14 00:30:05 +02:00
eeeck	d8105e2da3	Normalize CAN IDs number of bits	2026-07-14 00:21:03 +02:00
eeeck	9ddc6ea0d5	Use utility function instead of internal	2026-07-13 22:36:31 +02:00
eeeck	df3e7b1f0e	Update software version	2026-07-13 22:12:44 +02:00
eeeck	fe4bc0e46a	Merge pull request 'Implement Pearson and Spearman per-bit correleration' (#3 ) from dev-inter-byte-correlation into main Reviewed-on: erickahmed/CANveyor#3	2026-07-13 21:54:38 +02:00
eeeck	c9ae482174	Add positional argument to choose correlation methods (Pearson or Spearman)	2026-07-13 21:53:20 +02:00
eeeck	5e6f81b50b	Add hex converter utility - To move to separate utility file in the future	2026-07-13 21:50:32 +02:00
eeeck	ce74c7fcd9	Treat undefined correlation as zero correlation	2026-07-13 21:43:24 +02:00
eeeck	0f25c0671b	Implement Pearson correlation	2026-07-13 21:43:17 +02:00
eeeck	d0e70dad2a	Remove leftovers	2026-07-13 21:20:07 +02:00
eeeck	f39d23fc64	Merge pull request 'Implement entropy heatmap for CAN frames' (#2 ) from dev-entropy-heatmap into main Reviewed-on: erickahmed/CANveyor#2	2026-07-13 21:17:33 +02:00
eeeck	7daf4c8e08	Add entropy heatmap analysis - Same style of frequency analysis for consistency	2026-07-13 21:16:18 +02:00
eeeck	8a3fc81d12	Use more consistent styling - X axis on top - Refactor figure generation logic	2026-07-13 21:15:36 +02:00
eeeck	db7e5eb40e	Add header informations	2026-07-13 20:08:29 +02:00
eeeck	8ccb97afae	Remove requirement for positional arguments	2026-07-13 20:07:10 +02:00
eeeck	13d91d566b	Move to subfolder - Makes python recognize it as a submodule	2026-07-13 20:06:45 +02:00
eeeck	118f1567a2	Merge pull request 'Add header with copyright and SPDX licensing information' (#1 ) from code-header into dev-entropy-heatmap Reviewed-on: erickahmed/CANveyor#1	2026-07-13 19:54:10 +02:00
eeeck	cbba800536	Merge branch 'dev-entropy-heatmap' into code-header	2026-07-13 19:53:59 +02:00
eeeck	17340746ce	Move data extraction functions to utility library	2026-07-13 19:51:22 +02:00
eeeck	ad8334c915	Add header with copyright and SPDX licensing information	2026-07-13 19:48:46 +02:00
eeeck	9a5a231841	Add simple CAN message frequency analyzer	2026-07-13 19:28:52 +02:00
eeeck	74b393934c	Fix NoneType error	2026-07-13 18:53:27 +02:00
eeeck	4a701e34c5	Remove unused variable	2026-07-13 18:48:45 +02:00
eeeck	c42afb34b3	Specify that code is licensed under AGPLv3-or-later	2026-07-13 15:24:52 +02:00
eeeck	70abf7b5ce	Use last pre-release tag version	2026-07-13 14:35:52 +02:00
eeeck	f975cba4f8	Directory restruture - Essential files in . - Analysis or utilities related scripts on respective directories	2026-07-13 14:31:27 +02:00
eeeck	663d75174e	Remove J1939 stub for data calculation - To be done separately	2026-07-13 14:17:12 +02:00
eeeck	324aa5652c	Use AGPLv3 license	2026-07-11 09:52:41 +02:00
eeeck	e27351aa28	Delete src/analyzer.py	2026-07-10 01:27:54 +02:00
eeeck	6e386fcb4b	Add stub to decode J1939 and calculate useful values	2026-07-10 01:27:21 +02:00
eeeck	ca670c9bb7	Fix issues with metadata not correctly computed	2026-07-10 00:46:42 +02:00
eeeck	725c9ccbc1	Use more clear function name	2026-07-10 00:03:47 +02:00
eeeck	9d5cd74ef7	Decode J1939 metadata for compliant frames and add a struct with J1939 metadata	2026-07-10 00:03:04 +02:00
eeeck	6ef0571e4e	Add J1939 decoder	2026-07-09 23:57:37 +02:00