Hello,

WOW, that looks fantastic (Nupic Studio) As one that has not try the new
Nupic because of the complications of installing it, I am very happy that
you come up with the Nupic Studio. I will be able to finally dive into
Nupic and HTM! Now my problem! I downloaded the Nupic Studio but now what?
I am not even sure how to start it! It seems that it needs bunch of other
software to work. The doc says:


Dependencies:

   - Python (2.7 or later) (with development headers)
   - PIP
   - Nupic
   - NumPy
   - SciPy
   - PyOpenGL
   - PyOpenGL-accelerate
   - PyQt4
   - PyQtGraph

*Note*: Except Python, PIP and NuPIC, all dependencies above already are
automatically installed by PIP package.

I am not really familiar with any of these software. Do I need to install
each of them (PIP, Python 2.7 and NUPIC)?


Thanks a lot for any info/suggestions. Maybe all this install is probably
above my pay grade but I REALLY would like to start using NUPIC (especially
since there is Nupic Studio now)

Mo








On Wed, Sep 10, 2014 at 9:00 AM, <[email protected]> wrote:

> Send nupic mailing list submissions to
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>
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> When replying, please edit your Subject line so it is more specific
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>
>
> Today's Topics:
>
>    1. Re: Introducing NuPIC Studio! (Jim Bridgewater)
>    2. Re: Introducing NuPIC Studio! (Michael Neale)
>    3. Re: Introducing NuPIC Studio! (Ajay Ramanathan)
>    4. Re: Introducing NuPIC Studio! (Kevin Martin)
>    5. Re: Introducing NuPIC Studio! (Fergal Byrne)
>    6. Re: Understanding Hello_TP.py (Nicholas Mitri)
>    7. Re: Introducing NuPIC Studio! (David Ragazzi)
>    8. Re: Introducing NuPIC Studio! (Joseph Skippings)
>    9. Re: Introducing NuPIC Studio! (Marek Otahal)
>
>
> ----------------------------------------------------------------------
>
> Message: 1
> Date: Tue, 9 Sep 2014 20:51:52 -0700
> From: Jim Bridgewater <[email protected]>
> To: "NuPIC general mailing list." <[email protected]>
> Subject: Re: Introducing NuPIC Studio!
> Message-ID:
>         <CAMma+TjRKPsG22L9FRLti+RyCc=
> [email protected]>
> Content-Type: text/plain; charset=UTF-8
>
> Looks great, David.  Nice work!
>
> On Tue, Sep 9, 2014 at 7:39 PM, Daniel Bell
> <[email protected]> wrote:
> > How difficult would it be for an intermediate developer to create a
> similar
> > application for Nupic.core c++?
> >
> > On Wed, Sep 10, 2014 at 2:12 PM, David Ragazzi <[email protected]>
> > wrote:
> >>
> >> Daniel, I tried leave it as intuitive as possible just for discard
> >> tutorials.. But if anyone still believe it needs a tutorial, please feel
> >> free to create an issue there and share your thoughts..
> >>
> >> On 9 September 2014 22:59, Daniel Bell <
> [email protected]>
> >> wrote:
> >>>
> >>> This looks pretty cool. Any tutorials to go with it?
> >>>
> >>> On Wed, Sep 10, 2014 at 1:17 PM, David Ragazzi <[email protected]
> >
> >>> wrote:
> >>>>
> >>>> Hi guys, don't forget that if you click with the left mouse button on
> >>>> simulation painel, it will be showed a context menu with several
> options
> >>>> like camera positions and customization of views (you can define what
> kind
> >>>> of elements should be shown or not and save this configuration for
> use it
> >>>> always that you want, etc).
> >>>>
> >>>> On 9 September 2014 22:01, Mika Schiller <[email protected]>
> wrote:
> >>>>>
> >>>>> Can't wait to look through this David. Looks super neat!
> >>>>>
> >>>>> On Tue, Sep 9, 2014 at 8:21 PM, David Ragazzi <
> [email protected]>
> >>>>> wrote:
> >>>>>>
> >>>>>> Thanks guys, Matt also is helping me to find potential issues..
> >>>>>>
> >>>>>> As Mr. Ray said me in private:
> >>>>>> "I think this could become the goto interface for nupic!"
> >>>>>>
> >>>>>> On 9 September 2014 20:45, David Ray <[email protected]>
> >>>>>> wrote:
> >>>>>>>
> >>>>>>> This is Awesome! I look forward to checking it out!
> >>>>>>>
> >>>>>>> David Ray
> >>>>>>>
> >>>>>>> Sent from my iPhone
> >>>>>>>
> >>>>>>> On Sep 9, 2014, at 6:39 PM, David Ragazzi <[email protected]>
> >>>>>>> wrote:
> >>>>>>>
> >>>>>>> Hello NuPICers!
> >>>>>>>
> >>>>>>> Just for inform that in all these days I was out, I was creating
> an a
> >>>>>>> tool that I believe will be a breakthrough for the community. This
> tool
> >>>>>>> calls "NuPIC Studio", or just NuStudio. NuStudio is an
> all?-in-?one tool
> >>>>>>> that allows users create a HTM neural network from scratch, train
> it,
> >>>>>>> collect statistics, and share it among the members of the
> community. It is
> >>>>>>> not just a visualization tool but an HTM builder, debugger and
> laboratory
> >>>>>>> for experiments. It is ideal for newbies with little intimacy with
> NuPIC
> >>>>>>> code as well as experts that wish a better productivity. Among its
> features
> >>>>>>> and advantages I list:
> >>>>>>> - Users can open, save, or change their "HTM projects" or of other
> >>>>>>> developers. A typical project contains data to be trained, neural
> network
> >>>>>>> configuration, statistics, etc, which can be shared to be analysed
> or
> >>>>>>> integrated with other projects.
> >>>>>>> - The HTM engine is the own original NuPIC libray (Python
> >>>>>>> distribution). This means no port, no bindings, no
> re-implementation, etc.
> >>>>>>> So any changes in the original nupic source can be immediatedly
> viewed. This
> >>>>>>> helps users that wish test improvements like new encoders or even
> hierarchy,
> >>>>>>> attention, and motor integration.
> >>>>>>> - The project is pip-installable and for desktop use.
> >>>>>>>
> >>>>>>> Project details:
> >>>>>>> - All code is implemented in Python. When I say "all code", I
> really
> >>>>>>> mean that code like GUI, 3d simulation, etc, are writen in Python
> and use
> >>>>>>> open-source and cross platform components.
> >>>>>>> - All GUI stuff (forms, controls, etc) is implemented in PyQT. PyQT
> >>>>>>> is the version of the famous QT adapted for python apps, which is
> >>>>>>> open-source, cross-platform, complete, and very easy to code and
> change.
> >>>>>>> - All utilities like XML serialization, canvas 2d, etc, also are
> >>>>>>> implemented in PyQT.
> >>>>>>> - A front-end object-oriented layer also written in Python is
> >>>>>>> provided in order to ease the understanding of the NuPIC code and
> keep
> >>>>>>> backwards compatibility. This means that someone with less
> experience in
> >>>>>>> NuPIC could re-use this front-end in her projects.
> >>>>>>>
> >>>>>>> The project's site is:
> >>>>>>> https://github.com/DavidRagazzi/nupic.studio
> >>>>>>>
> >>>>>>> and you can see some screen-shots attached to this message.
> >>>>>>>
> >>>>>>> Surely it still is not 100%, and it's expected that some
> installation
> >>>>>>> issues arise, but I hope optimize the process as soon as possible.
> By the
> >>>>>>> way, it works reasonably well and any people is welcome to try it
> or even
> >>>>>>> improve it.
> >>>>>>>
> >>>>>>> I look forward for your feedback, it is very important!
> >>>>>>>
> >>>>>>> Cheers,
> >>>>>>> David
> >>>>>>>
> >>>>>>> --
> >>>>>>> David Ragazzi
> >>>>>>> MSc in Sofware Engineer (University of Liverpool)
> >>>>>>> Try NuPIC Studio! https://github.com/DavidRagazzi/nupic.studio
> >>>>>>> --
> >>>>>>> "I think James Connolly, the Irish revolutionary, is right when he
> >>>>>>> says that the only prophets are those who make their future. So
> we're not
> >>>>>>> anticipating, we're working for it."
> >>>>>>>
> >>>>>>> <splash.png>
> >>>>>>>
> >>>>>>> <screenshot.png>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>>
> >>>>>> --
> >>>>>> David Ragazzi
> >>>>>> MSc in Sofware Engineer (University of Liverpool)
> >>>>>> OS Community Commiter at Numenta.org
> >>>>>> --
> >>>>>> "I think James Connolly, the Irish revolutionary, is right when he
> >>>>>> says that the only prophets are those who make their future. So
> we're not
> >>>>>> anticipating, we're working for it."
> >>>>>
> >>>>>
> >>>>
> >>>>
> >>>>
> >>>> --
> >>>> David Ragazzi
> >>>> MSc in Sofware Engineer (University of Liverpool)
> >>>> OS Community Commiter at Numenta.org
> >>>> --
> >>>> "I think James Connolly, the Irish revolutionary, is right when he
> says
> >>>> that the only prophets are those who make their future. So we're not
> >>>> anticipating, we're working for it."
> >>>
> >>>
> >>
> >>
> >>
> >> --
> >> David Ragazzi
> >> MSc in Sofware Engineer (University of Liverpool)
> >> OS Community Commiter at Numenta.org
> >> --
> >> "I think James Connolly, the Irish revolutionary, is right when he says
> >> that the only prophets are those who make their future. So we're not
> >> anticipating, we're working for it."
> >
> >
>
>
>
> --
> James Bridgewater, PhD
> Arizona State University
> 480-227-9592
>
>
>
> ------------------------------
>
> Message: 2
> Date: Wed, 10 Sep 2014 14:18:15 +1000
> From: Michael Neale <[email protected]>
> To: "NuPIC general mailing list." <[email protected]>
> Subject: Re: Introducing NuPIC Studio!
> Message-ID:
>         <CAKVMTi7WbP3KnuFu6ACzc1PHmc=
> [email protected]>
> Content-Type: text/plain; charset="utf-8"
>
> This looks incredible - what a great tool. The connections visualisation
> looks like a great explanatory tool too!
>
> On Wed, Sep 10, 2014 at 9:39 AM, David Ragazzi <[email protected]>
> wrote:
>
> > Hello NuPICers!
> >
> > Just for inform that in all these days I was out, I was creating an a
> tool that
> > I believe will be a breakthrough for the community. This tool calls
> > "NuPIC Studio", or just NuStudio. NuStudio is an all?-in-?one tool that
> > allows users create a HTM neural network from scratch, train it, collect
> > statistics, and share it among the members of the community. It is not
> just
> > a visualization tool but an HTM builder, debugger and laboratory for
> > experiments. It is ideal for newbies with little intimacy with NuPIC code
> > as well as experts that wish a better productivity. Among its features
> and
> > advantages I list:
> > - Users can open, save, or change their "HTM projects" or of other
> > developers. A typical project contains data to be trained, neural network
> > configuration, statistics, etc, which can be shared to be analysed or
> > integrated with other projects.
> > - The HTM engine is the own original NuPIC libray (Python distribution).
> > This means no port, no bindings, no re-implementation, etc. So any
> changes
> > in the original nupic source can be immediatedly viewed. This helps users
> > that wish test improvements like new encoders or even hierarchy,
> attention,
> > and motor integration.
> > - The project is pip-installable and for desktop use.
> >
> > Project details:
> > - All code is implemented in Python. When I say "all code", I really mean
> > that code like GUI, 3d simulation, etc, are writen in Python and use
> > open-source and cross platform components.
> > - All GUI stuff (forms, controls, etc) is implemented in PyQT. PyQT is
> the
> > version of the famous QT adapted for python apps, which is open-source,
> > cross-platform, complete, and very easy to code and change.
> > - All utilities like XML serialization, canvas 2d, etc, also are
> > implemented in PyQT.
> > - A front-end object-oriented layer also written in Python is provided in
> > order to ease the understanding of the NuPIC code and keep backwards
> > compatibility. This means that someone with less experience in NuPIC
> could
> > re-use this front-end in her projects.
> >
> > The project's site is:
> > https://github.com/DavidRagazzi/nupic.studio
> >
> > and you can see some screen-shots attached to this message.
> >
> > Surely it still is not 100%, and it's expected that some installation
> > issues arise, but I hope optimize the process as soon as possible. By the
> > way, it works reasonably well and any people is welcome to try it or even
> > improve it.
> >
> > I look forward for your feedback, it is very important!
> >
> > Cheers,
> > David
> >
> > --
> > David Ragazzi
> > MSc in Sofware Engineer (University of Liverpool)
> > Try NuPIC Studio! https://github.com/DavidRagazzi/nupic.studio
> > --
> > "I think James Connolly, the Irish revolutionary, is right when he says
> that
> > the only prophets are those who make their future. So we're not
> > anticipating, we're working for it."
> >
>
>
>
> --
> Michael D Neale
> home: www.michaelneale.net
> blog: michaelneale.blogspot.com
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>
> ------------------------------
>
> Message: 3
> Date: Wed, 10 Sep 2014 11:08:57 +0530
> From: Ajay Ramanathan <[email protected]>
> To: "NuPIC general mailing list." <[email protected]>
> Subject: Re: Introducing NuPIC Studio!
> Message-ID:
>         <
> caglh-rszzy9kf_1eyocymqvswajtblatfkwg93bhp+s_pqf...@mail.gmail.com>
> Content-Type: text/plain; charset="utf-8"
>
> It looks really cool; looking forward to it :D
>
> On Wed, Sep 10, 2014 at 9:48 AM, Michael Neale <[email protected]>
> wrote:
>
> > This looks incredible - what a great tool. The connections visualisation
> > looks like a great explanatory tool too!
> >
> > On Wed, Sep 10, 2014 at 9:39 AM, David Ragazzi <[email protected]>
> > wrote:
> >
> >> Hello NuPICers!
> >>
> >> Just for inform that in all these days I was out, I was creating an a
> >> tool that I believe will be a breakthrough for the community. This tool
> >> calls "NuPIC Studio", or just NuStudio. NuStudio is an all?-in-?one tool
> >> that allows users create a HTM neural network from scratch, train it,
> >> collect statistics, and share it among the members of the community. It
> is
> >> not just a visualization tool but an HTM builder, debugger and
> laboratory
> >> for experiments. It is ideal for newbies with little intimacy with NuPIC
> >> code as well as experts that wish a better productivity. Among its
> features
> >> and advantages I list:
> >> - Users can open, save, or change their "HTM projects" or of other
> >> developers. A typical project contains data to be trained, neural
> network
> >> configuration, statistics, etc, which can be shared to be analysed or
> >> integrated with other projects.
> >> - The HTM engine is the own original NuPIC libray (Python distribution).
> >> This means no port, no bindings, no re-implementation, etc. So any
> changes
> >> in the original nupic source can be immediatedly viewed. This helps
> users
> >> that wish test improvements like new encoders or even hierarchy,
> attention,
> >> and motor integration.
> >> - The project is pip-installable and for desktop use.
> >>
> >> Project details:
> >> - All code is implemented in Python. When I say "all code", I really
> mean
> >> that code like GUI, 3d simulation, etc, are writen in Python and use
> >> open-source and cross platform components.
> >> - All GUI stuff (forms, controls, etc) is implemented in PyQT. PyQT is
> >> the version of the famous QT adapted for python apps, which is
> open-source,
> >> cross-platform, complete, and very easy to code and change.
> >> - All utilities like XML serialization, canvas 2d, etc, also are
> >> implemented in PyQT.
> >> - A front-end object-oriented layer also written in Python is provided
> in
> >> order to ease the understanding of the NuPIC code and keep backwards
> >> compatibility. This means that someone with less experience in NuPIC
> could
> >> re-use this front-end in her projects.
> >>
> >> The project's site is:
> >> https://github.com/DavidRagazzi/nupic.studio
> >>
> >> and you can see some screen-shots attached to this message.
> >>
> >> Surely it still is not 100%, and it's expected that some installation
> >> issues arise, but I hope optimize the process as soon as possible. By
> the
> >> way, it works reasonably well and any people is welcome to try it or
> even
> >> improve it.
> >>
> >> I look forward for your feedback, it is very important!
> >>
> >> Cheers,
> >> David
> >>
> >> --
> >> David Ragazzi
> >> MSc in Sofware Engineer (University of Liverpool)
> >> Try NuPIC Studio! https://github.com/DavidRagazzi/nupic.studio
> >> --
> >> "I think James Connolly, the Irish revolutionary, is right when he says
> that
> >> the only prophets are those who make their future. So we're not
> >> anticipating, we're working for it."
> >>
> >
> >
> >
> > --
> > Michael D Neale
> > home: www.michaelneale.net
> > blog: michaelneale.blogspot.com
> >
> -------------- next part --------------
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> URL: <
> http://lists.numenta.org/pipermail/nupic_lists.numenta.org/attachments/20140910/f534f99e/attachment-0001.html
> >
>
> ------------------------------
>
> Message: 4
> Date: Wed, 10 Sep 2014 11:27:33 +0530
> From: Kevin Martin <[email protected]>
> To: "NuPIC general mailing list." <[email protected]>
> Subject: Re: Introducing NuPIC Studio!
> Message-ID:
>         <CAJisb+=GzehLYd441=0+tyMn0OKVZVpzX5v0UB0MdrFu=
> [email protected]>
> Content-Type: text/plain; charset="utf-8"
>
> Awesome! One more cool thing to do when I get time. Great work!
>
> On Wed, Sep 10, 2014 at 11:08 AM, Ajay Ramanathan <[email protected]>
> wrote:
>
> > It looks really cool; looking forward to it :D
> >
> > On Wed, Sep 10, 2014 at 9:48 AM, Michael Neale <[email protected]>
> > wrote:
> >
> >> This looks incredible - what a great tool. The connections visualisation
> >> looks like a great explanatory tool too!
> >>
> >> On Wed, Sep 10, 2014 at 9:39 AM, David Ragazzi <[email protected]>
> >> wrote:
> >>
> >>> Hello NuPICers!
> >>>
> >>> Just for inform that in all these days I was out, I was creating an a
> >>> tool that I believe will be a breakthrough for the community. This tool
> >>> calls "NuPIC Studio", or just NuStudio. NuStudio is an all?-in-?one
> >>> tool that allows users create a HTM neural network from scratch, train
> it,
> >>> collect statistics, and share it among the members of the community.
> It is
> >>> not just a visualization tool but an HTM builder, debugger and
> laboratory
> >>> for experiments. It is ideal for newbies with little intimacy with
> NuPIC
> >>> code as well as experts that wish a better productivity. Among its
> features
> >>> and advantages I list:
> >>> - Users can open, save, or change their "HTM projects" or of other
> >>> developers. A typical project contains data to be trained, neural
> network
> >>> configuration, statistics, etc, which can be shared to be analysed or
> >>> integrated with other projects.
> >>> - The HTM engine is the own original NuPIC libray (Python
> distribution).
> >>> This means no port, no bindings, no re-implementation, etc. So any
> changes
> >>> in the original nupic source can be immediatedly viewed. This helps
> users
> >>> that wish test improvements like new encoders or even hierarchy,
> attention,
> >>> and motor integration.
> >>> - The project is pip-installable and for desktop use.
> >>>
> >>> Project details:
> >>> - All code is implemented in Python. When I say "all code", I really
> >>> mean that code like GUI, 3d simulation, etc, are writen in Python and
> use
> >>> open-source and cross platform components.
> >>> - All GUI stuff (forms, controls, etc) is implemented in PyQT. PyQT is
> >>> the version of the famous QT adapted for python apps, which is
> open-source,
> >>> cross-platform, complete, and very easy to code and change.
> >>> - All utilities like XML serialization, canvas 2d, etc, also are
> >>> implemented in PyQT.
> >>> - A front-end object-oriented layer also written in Python is provided
> >>> in order to ease the understanding of the NuPIC code and keep backwards
> >>> compatibility. This means that someone with less experience in NuPIC
> could
> >>> re-use this front-end in her projects.
> >>>
> >>> The project's site is:
> >>> https://github.com/DavidRagazzi/nupic.studio
> >>>
> >>> and you can see some screen-shots attached to this message.
> >>>
> >>> Surely it still is not 100%, and it's expected that some installation
> >>> issues arise, but I hope optimize the process as soon as possible. By
> the
> >>> way, it works reasonably well and any people is welcome to try it or
> even
> >>> improve it.
> >>>
> >>> I look forward for your feedback, it is very important!
> >>>
> >>> Cheers,
> >>> David
> >>>
> >>> --
> >>> David Ragazzi
> >>> MSc in Sofware Engineer (University of Liverpool)
> >>> Try NuPIC Studio! https://github.com/DavidRagazzi/nupic.studio
> >>> --
> >>> "I think James Connolly, the Irish revolutionary, is right when he
> says that
> >>> the only prophets are those who make their future. So we're not
> >>> anticipating, we're working for it."
> >>>
> >>
> >>
> >>
> >> --
> >> Michael D Neale
> >> home: www.michaelneale.net
> >> blog: michaelneale.blogspot.com
> >>
> >
> >
> -------------- next part --------------
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> http://lists.numenta.org/pipermail/nupic_lists.numenta.org/attachments/20140910/5b5232d0/attachment-0001.html
> >
>
> ------------------------------
>
> Message: 5
> Date: Wed, 10 Sep 2014 08:01:23 +0100
> From: Fergal Byrne <[email protected]>
> To: "NuPIC general mailing list." <[email protected]>
> Subject: Re: Introducing NuPIC Studio!
> Message-ID:
>         <CAD2Q5Yf_erPWjYRMGJ-0M3cQL4LgzoU6=
> [email protected]>
> Content-Type: text/plain; charset="utf-8"
>
> Hi David,
>
> Wow, that looks and sounds like a great new addition to the NuPIC
> ecosystem. I'll have time to take a proper look at it this evening, but it
> already looks like you've pulled off yet another Ragazzi-quality
> production! Well done and thanks for sharing this - I think having great
> tools like this is hugely important for spreading the word about NuPIC and
> HTM.
>
> Cheers,
>
> Fergal Byrne
>
> On Wed, Sep 10, 2014 at 6:57 AM, Kevin Martin <[email protected]
> >
> wrote:
>
> > Awesome! One more cool thing to do when I get time. Great work!
> >
> > On Wed, Sep 10, 2014 at 11:08 AM, Ajay Ramanathan <[email protected]
> >
> > wrote:
> >
> >> It looks really cool; looking forward to it :D
> >>
> >> On Wed, Sep 10, 2014 at 9:48 AM, Michael Neale <[email protected]
> >
> >> wrote:
> >>
> >>> This looks incredible - what a great tool. The connections
> visualisation
> >>> looks like a great explanatory tool too!
> >>>
> >>> On Wed, Sep 10, 2014 at 9:39 AM, David Ragazzi <[email protected]
> >
> >>> wrote:
> >>>
> >>>> Hello NuPICers!
> >>>>
> >>>> Just for inform that in all these days I was out, I was creating an a
> >>>> tool that I believe will be a breakthrough for the community. This
> >>>> tool calls "NuPIC Studio", or just NuStudio. NuStudio is an
> >>>> all?-in-?one tool that allows users create a HTM neural network from
> >>>> scratch, train it, collect statistics, and share it among the members
> of
> >>>> the community. It is not just a visualization tool but an HTM builder,
> >>>> debugger and laboratory for experiments. It is ideal for newbies with
> >>>> little intimacy with NuPIC code as well as experts that wish a better
> >>>> productivity. Among its features and advantages I list:
> >>>> - Users can open, save, or change their "HTM projects" or of other
> >>>> developers. A typical project contains data to be trained, neural
> network
> >>>> configuration, statistics, etc, which can be shared to be analysed or
> >>>> integrated with other projects.
> >>>> - The HTM engine is the own original NuPIC libray (Python
> >>>> distribution). This means no port, no bindings, no re-implementation,
> etc.
> >>>> So any changes in the original nupic source can be immediatedly
> viewed.
> >>>> This helps users that wish test improvements like new encoders or even
> >>>> hierarchy, attention, and motor integration.
> >>>> - The project is pip-installable and for desktop use.
> >>>>
> >>>> Project details:
> >>>> - All code is implemented in Python. When I say "all code", I really
> >>>> mean that code like GUI, 3d simulation, etc, are writen in Python and
> use
> >>>> open-source and cross platform components.
> >>>> - All GUI stuff (forms, controls, etc) is implemented in PyQT. PyQT is
> >>>> the version of the famous QT adapted for python apps, which is
> open-source,
> >>>> cross-platform, complete, and very easy to code and change.
> >>>> - All utilities like XML serialization, canvas 2d, etc, also are
> >>>> implemented in PyQT.
> >>>> - A front-end object-oriented layer also written in Python is provided
> >>>> in order to ease the understanding of the NuPIC code and keep
> backwards
> >>>> compatibility. This means that someone with less experience in NuPIC
> could
> >>>> re-use this front-end in her projects.
> >>>>
> >>>> The project's site is:
> >>>> https://github.com/DavidRagazzi/nupic.studio
> >>>>
> >>>> and you can see some screen-shots attached to this message.
> >>>>
> >>>> Surely it still is not 100%, and it's expected that some installation
> >>>> issues arise, but I hope optimize the process as soon as possible. By
> the
> >>>> way, it works reasonably well and any people is welcome to try it or
> even
> >>>> improve it.
> >>>>
> >>>> I look forward for your feedback, it is very important!
> >>>>
> >>>> Cheers,
> >>>> David
> >>>>
> >>>> --
> >>>> David Ragazzi
> >>>> MSc in Sofware Engineer (University of Liverpool)
> >>>> Try NuPIC Studio! https://github.com/DavidRagazzi/nupic.studio
> >>>> --
> >>>> "I think James Connolly, the Irish revolutionary, is right when he
> says that
> >>>> the only prophets are those who make their future. So we're not
> >>>> anticipating, we're working for it."
> >>>>
> >>>
> >>>
> >>>
> >>> --
> >>> Michael D Neale
> >>> home: www.michaelneale.net
> >>> blog: michaelneale.blogspot.com
> >>>
> >>
> >>
> >
>
>
> --
>
> Fergal Byrne, Brenter IT
>
> http://inbits.com - Better Living through Thoughtful Technology
> http://ie.linkedin.com/in/fergbyrne/ - https://github.com/fergalbyrne
>
> Author, Real Machine Intelligence with Clortex and NuPIC
> Read for free or buy the book at https://leanpub.com/realsmartmachines
>
> Speaking on Clortex and HTM/CLA at euroClojure Krakow, June 2014:
> http://euroclojure.com/2014/
> and at LambdaJam Chicago, July 2014: http://www.lambdajam.com
>
> e:[email protected] t:+353 83 4214179
> Join the quest for Machine Intelligence at http://numenta.org
> Formerly of Adnet [email protected] http://www.adnet.ie
> -------------- next part --------------
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> http://lists.numenta.org/pipermail/nupic_lists.numenta.org/attachments/20140910/953e6ef8/attachment-0001.html
> >
>
> ------------------------------
>
> Message: 6
> Date: Wed, 10 Sep 2014 12:58:39 +0300
> From: Nicholas Mitri <[email protected]>
> To: "NuPIC general mailing list." <[email protected]>
> Subject: Re: Understanding Hello_TP.py
> Message-ID: <[email protected]>
> Content-Type: text/plain; charset="windows-1252"
>
> Thanks Chetan! I?ll take a look at the files you recommended.
>
> Any hints as to why the classifier is performing so poorly?
> Considering that the classifier learns by building probability
> distributions, I thought higher training passes would make it perform
> better. Even at 1000 passes though, it?s performing no better.
>
> Nick
>
>
> On Sep 10, 2014, at 1:39 AM, Chetan Surpur <[email protected]> wrote:
>
> > Also, if you play with extensive_temporal_memory_test.py, try adding
> VERBOSITY = 2 at the class level.
> >
> > On Tue, Sep 9, 2014 at 3:20 PM, Chetan Surpur <[email protected]>
> wrote:
> >
> > Hi Nick,
> >
> > >> 1) Why are there no predictive states being seen for the first
> training pass (i.e. seeing the entire sequence once)? Even if
> activationThreshold and minThreshold are set sufficiently low to make
> segments sensitive, no lateral activation happens. Are cells initialized
> with no segments?
> >
> > That's right, cells are initialized with no segments. The segments are
> formed when a pattern is shown, and newly active cells form connections to
> previously active cells.
> >
> > >> 3) in the second training pass, we go from no predictive cells to
> perfectly predictive cells associated with the next character. I would
> typically expect the network to show scattered predictive cells before it
> hones in on the right prediction (consecutive 10 on-bits in this example).
> Why the abrupt shift in predictive behavior?
> >
> > That's because in this example, initialPerm == connectedPerm, so any
> synapses that are formed are immediately "connected". This allows the
> sequence to be learned in one pass.
> >
> > >> 4) finally, the printCells() function outputs the following. Can you
> please explain what each entry means?
> >
> > I'm not sure what the entries mean. However, I would recommend that if
> you're trying to understand the behavior of the temporal memory, take a
> look at the new implementation (temporal_memory.py) and tests for it
> (tutorial_temporal_memory_test.py and extensive_temporal_memory_test.py).
> They are easier to read and understand, and the implementation is closer to
> the pure white paper description.
> >
> > - Chetan
> >
> > On Thursday, Sep 4, 2014 at 1:37 PM, Nicholas Mitri <[email protected]>,
> wrote:
> > Hey all,
> >
> > I?d like to dedicate this thread for discussing some TP implementation
> and practical questions, namely those associated with the introductory file
> to the TP, hello-tp.py.
> >
> > Below is the print out of a TP with 50 columns, 1 cell per column being
> trained as described in the py file for 2 iterations on the sequence
> A->B->C->D->E. Each pattern is fed directly into the TP as an active
> network state.
> >
> > I?ve been playing around with the configurations and have a few
> questions.
> >
> > 1) Why are there no predictive states being seen for the first training
> pass (i.e. seeing the entire sequence once)? Even if activationThreshold
> and minThreshold are set sufficiently low to make segments sensitive, no
> lateral activation happens. Are cells initialized with no segments?
> > 2) if segments are created during initialization, how is their
> connectivity to the cells of the region configured? How are permanence
> values allocated? Same as proximal synapses in the TP?
> > 3) in the second training pass, we go from no predictive cells to
> perfectly predictive cells associated with the next character. I would
> typically expect the network to show scattered predictive cells before it
> hones in on the right prediction (consecutive 10 on-bits in this example).
> Why the abrupt shift in predictive behavior? Is this related to
> getBestMatchingCell()?
> > 4) finally, the printCells() function outputs the following. Can you
> please explain what each entry means?
> >
> > Column 41 Cell 0 : 1 segment(s)
> > Seg #0 ID:41 True 0.2000000 ( 3/3 ) 0 [30,0]1.00 [31,0]1.00 [32,0]1.00
> [33,0]1.00 [34,0]1.00 [35,0]1.00 [36,0]1.00 [37,0]1.00 [38,0]1.00 [39,0]1.00
> >
> > Thanks,
> > Nick
> > ????????????? PRINT OUT???????????? ?????
> >
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 1111111111 0000000000 0000000000 0000000000 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 1111111111 0000000000 0000000000 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 0000000000 1111111111 0000000000 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 0000000000 0000000000 1111111111 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 0000000000 0000000000 0000000000 1111111111
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 0000000000
> >
> > ############ Training Pass #1 Complete ############
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 1111111111 0000000000 0000000000 0000000000 0000000000
> > Inference Predicted state
> > 0000000000 1111111111 0000000000 0000000000 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 1111111111 0000000000 0000000000 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 1111111111 0000000000 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 0000000000 1111111111 0000000000 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 1111111111 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 0000000000 0000000000 1111111111 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 1111111111
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 0000000000 0000000000 0000000000 1111111111
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 0000000000
> >
> > ############ Training Pass #2 Complete ############
> > Hey all,
> >
> > I?d like to dedicate this thread for discussing some TP implementation
> and practical questions, namely those associated with the introductory file
> to the TP, hello-tp.py.
> >
> > Below is the print out of a TP with 50 columns, 1 cell per column being
> trained as described in the py file for 2 iterations on the sequence
> A->B->C->D->E. Each pattern is fed directly into the TP as an active
> network state.
> >
> > I?ve been playing around with the configurations and have a few
> questions.
> >
> > 1) Why are there no predictive states being seen for the first training
> pass (i.e. seeing the entire sequence once)? Even if activationThreshold
> and minThreshold are set sufficiently low to make segments sensitive, no
> lateral activation happens. Are cells initialized with no segments?
> > 2) if segments are created during initialization, how is their
> connectivity to the cells of the region configured? How are permanence
> values allocated? Same as proximal synapses in the TP?
> > 3) in the second training pass, we go from no predictive cells to
> perfectly predictive cells associated with the next character. I would
> typically expect the network to show scattered predictive cells before it
> hones in on the right prediction (consecutive 10 on-bits in this example).
> Why the abrupt shift in predictive behavior? Is this related to
> getBestMatchingCell()?
> > 4) finally, the printCells() function outputs the following. Can you
> please explain what each entry means?
> >
> > Column 41 Cell 0 : 1 segment(s)
> > Seg #0 ID:41 True 0.2000000 ( 3/3 ) 0 [30,0]1.00 [31,0]1.00 [32,0]1.00
> [33,0]1.00 [34,0]1.00 [35,0]1.00 [36,0]1.00 [37,0]1.00 [38,0]1.00 [39,0]1.00
> >
> > Thanks,
> > Nick
> > ????????????? PRINT OUT???????????? ?????
> >
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 1111111111 0000000000 0000000000 0000000000 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 1111111111 0000000000 0000000000 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 0000000000 1111111111 0000000000 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 0000000000 0000000000 1111111111 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 0000000000 0000000000 0000000000 1111111111
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 0000000000
> >
> > ############ Training Pass #1 Complete ############
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 1111111111 0000000000 0000000000 0000000000 0000000000
> > Inference Predicted state
> > 0000000000 1111111111 0000000000 0000000000 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 1111111111 0000000000 0000000000 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 1111111111 0000000000 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 0000000000 1111111111 0000000000 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 1111111111 0000000000
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 0000000000 0000000000 1111111111 0000000000
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 1111111111
> >
> > All the active and predicted cells:
> >
> > Inference Active state
> > 0000000000 0000000000 0000000000 0000000000 1111111111
> > Inference Predicted state
> > 0000000000 0000000000 0000000000 0000000000 0000000000
> >
> > ############ Training Pass #2 Complete ############
> >
>
> -------------- next part --------------
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> http://lists.numenta.org/pipermail/nupic_lists.numenta.org/attachments/20140910/a2ad9853/attachment-0001.html
> >
>
> ------------------------------
>
> Message: 7
> Date: Wed, 10 Sep 2014 08:20:04 -0300
> From: David Ragazzi <[email protected]>
> To: "NuPIC general mailing list." <[email protected]>
> Subject: Re: Introducing NuPIC Studio!
> Message-ID:
>         <CAB-x0C=
> [email protected]>
> Content-Type: text/plain; charset="utf-8"
>
> Thank you, guys!
>
> > The connections visualisation looks like a great *explanatory tool* too!
>
> This is other objective, I remember that Jeff Hawkins commented about the
> need of tool that allow visualize a HTM in 3D to check what changed along
> the time.. For this, NuStudio keeps the history of states (max=5, but you
> can increase), so you might slide the "step bar" for check if the columns
> are active at moment, were predicted or not, or if the input is unexpected
> which cells were chosen as learning cells, or what new synapses were
> created or removed, etc.
>
> > How difficult would it be for an intermediate developer to create a
> similar application for Nupic.core c++?
>
> Daniel, you don't need re-invent the wheel, you could change NuStudio to
> handle NuPIC C++ instead of NuPIC Python. It's because NuPIC Python dist
> has some bindings to handle NuPIC C++. Theorically, you just need change
> some "headers imports" and voil?.. But in the pratice, this is not
> possible, because NuStudio uses the new TM (implemented on Python but not
> on C++).. So I advise you wait a little until TM is implemented on C++..
> But once this done, a few changes will be need..
>
> > another Ragazzi-quality production!
>
> Thanks for this, Fergal! :-D
>
> David
>
> On 10 September 2014 04:01, Fergal Byrne <[email protected]>
> wrote:
>
> > Hi David,
> >
> > Wow, that looks and sounds like a great new addition to the NuPIC
> > ecosystem. I'll have time to take a proper look at it this evening, but
> it
> > already looks like you've pulled off yet another Ragazzi-quality
> > production! Well done and thanks for sharing this - I think having great
> > tools like this is hugely important for spreading the word about NuPIC
> and
> > HTM.
> >
> > Cheers,
> >
> > Fergal Byrne
> >
> > On Wed, Sep 10, 2014 at 6:57 AM, Kevin Martin <
> [email protected]
> > > wrote:
> >
> >> Awesome! One more cool thing to do when I get time. Great work!
> >>
> >> On Wed, Sep 10, 2014 at 11:08 AM, Ajay Ramanathan <
> [email protected]>
> >> wrote:
> >>
> >>> It looks really cool; looking forward to it :D
> >>>
> >>> On Wed, Sep 10, 2014 at 9:48 AM, Michael Neale <
> [email protected]>
> >>> wrote:
> >>>
> >>>> This looks incredible - what a great tool. The connections
> >>>> visualisation looks like a great explanatory tool too!
> >>>>
> >>>> On Wed, Sep 10, 2014 at 9:39 AM, David Ragazzi <
> [email protected]>
> >>>> wrote:
> >>>>
> >>>>> Hello NuPICers!
> >>>>>
> >>>>> Just for inform that in all these days I was out, I was creating an a
> >>>>> tool that I believe will be a breakthrough for the community. This
> >>>>> tool calls "NuPIC Studio", or just NuStudio. NuStudio is an
> >>>>> all?-in-?one tool that allows users create a HTM neural network from
> >>>>> scratch, train it, collect statistics, and share it among the
> members of
> >>>>> the community. It is not just a visualization tool but an HTM
> builder,
> >>>>> debugger and laboratory for experiments. It is ideal for newbies with
> >>>>> little intimacy with NuPIC code as well as experts that wish a better
> >>>>> productivity. Among its features and advantages I list:
> >>>>> - Users can open, save, or change their "HTM projects" or of other
> >>>>> developers. A typical project contains data to be trained, neural
> network
> >>>>> configuration, statistics, etc, which can be shared to be analysed or
> >>>>> integrated with other projects.
> >>>>> - The HTM engine is the own original NuPIC libray (Python
> >>>>> distribution). This means no port, no bindings, no
> re-implementation, etc.
> >>>>> So any changes in the original nupic source can be immediatedly
> viewed.
> >>>>> This helps users that wish test improvements like new encoders or
> even
> >>>>> hierarchy, attention, and motor integration.
> >>>>> - The project is pip-installable and for desktop use.
> >>>>>
> >>>>> Project details:
> >>>>> - All code is implemented in Python. When I say "all code", I really
> >>>>> mean that code like GUI, 3d simulation, etc, are writen in Python
> and use
> >>>>> open-source and cross platform components.
> >>>>> - All GUI stuff (forms, controls, etc) is implemented in PyQT. PyQT
> is
> >>>>> the version of the famous QT adapted for python apps, which is
> open-source,
> >>>>> cross-platform, complete, and very easy to code and change.
> >>>>> - All utilities like XML serialization, canvas 2d, etc, also are
> >>>>> implemented in PyQT.
> >>>>> - A front-end object-oriented layer also written in Python is
> provided
> >>>>> in order to ease the understanding of the NuPIC code and keep
> backwards
> >>>>> compatibility. This means that someone with less experience in NuPIC
> could
> >>>>> re-use this front-end in her projects.
> >>>>>
> >>>>> The project's site is:
> >>>>> https://github.com/DavidRagazzi/nupic.studio
> >>>>>
> >>>>> and you can see some screen-shots attached to this message.
> >>>>>
> >>>>> Surely it still is not 100%, and it's expected that some installation
> >>>>> issues arise, but I hope optimize the process as soon as possible.
> By the
> >>>>> way, it works reasonably well and any people is welcome to try it or
> even
> >>>>> improve it.
> >>>>>
> >>>>> I look forward for your feedback, it is very important!
> >>>>>
> >>>>> Cheers,
> >>>>> David
> >>>>>
> >>>>> --
> >>>>> David Ragazzi
> >>>>> MSc in Sofware Engineer (University of Liverpool)
> >>>>> Try NuPIC Studio! https://github.com/DavidRagazzi/nupic.studio
> >>>>> --
> >>>>> "I think James Connolly, the Irish revolutionary, is right when he
> >>>>> says that the only prophets are those who make their future. So we're
> >>>>> not anticipating, we're working for it."
> >>>>>
> >>>>
> >>>>
> >>>>
> >>>> --
> >>>> Michael D Neale
> >>>> home: www.michaelneale.net
> >>>> blog: michaelneale.blogspot.com
> >>>>
> >>>
> >>>
> >>
> >
> >
> > --
> >
> > Fergal Byrne, Brenter IT
> >
> > http://inbits.com - Better Living through Thoughtful Technology
> > http://ie.linkedin.com/in/fergbyrne/ - https://github.com/fergalbyrne
> >
> > Author, Real Machine Intelligence with Clortex and NuPIC
> > Read for free or buy the book at https://leanpub.com/realsmartmachines
> >
> > Speaking on Clortex and HTM/CLA at euroClojure Krakow, June 2014:
> > http://euroclojure.com/2014/
> > and at LambdaJam Chicago, July 2014: http://www.lambdajam.com
> >
> > e:[email protected] t:+353 83 4214179
> > Join the quest for Machine Intelligence at http://numenta.org
> > Formerly of Adnet [email protected] http://www.adnet.ie
> >
>
>
>
> --
> David Ragazzi
> MSc in Sofware Engineer (University of Liverpool)
> OS Community Commiter at Numenta.org
> --
> "I think James Connolly, the Irish revolutionary, is right when he says
> that
> the only prophets are those who make their future. So we're not
> anticipating
> , we're working for it."
> -------------- next part --------------
> An HTML attachment was scrubbed...
> URL: <
> http://lists.numenta.org/pipermail/nupic_lists.numenta.org/attachments/20140910/8f91e914/attachment-0001.html
> >
>
> ------------------------------
>
> Message: 8
> Date: Wed, 10 Sep 2014 07:51:28 -0400
> From: Joseph Skippings <[email protected]>
> To: "NuPIC general mailing list." <[email protected]>
> Subject: Re: Introducing NuPIC Studio!
> Message-ID: <[email protected]>
> Content-Type: text/plain; charset="utf-8"
>
> Wow that is awesome!!!
>
> Sent from my iPhone
>
> > On Sep 10, 2014, at 7:20 AM, David Ragazzi <[email protected]>
> wrote:
> >
> > Thank you, guys!
> >
> > > The connections visualisation looks like a great explanatory tool too!
> >
> > This is other objective, I remember that Jeff Hawkins commented about
> the need of tool that allow visualize a HTM in 3D to check what changed
> along the time.. For this, NuStudio keeps the history of states (max=5, but
> you can increase), so you might slide the "step bar" for check if the
> columns are active at moment, were predicted or not, or if the input is
> unexpected which cells were chosen as learning cells, or what new synapses
> were created or removed, etc.
> >
> > > How difficult would it be for an intermediate developer to create a
> similar application for Nupic.core c++?
> >
> > Daniel, you don't need re-invent the wheel, you could change NuStudio to
> handle NuPIC C++ instead of NuPIC Python. It's because NuPIC Python dist
> has some bindings to handle NuPIC C++. Theorically, you just need change
> some "headers imports" and voil?.. But in the pratice, this is not
> possible, because NuStudio uses the new TM (implemented on Python but not
> on C++).. So I advise you wait a little until TM is implemented on C++..
> But once this done, a few changes will be need..
> >
> > > another Ragazzi-quality production!
> >
> > Thanks for this, Fergal! :-D
> >
> > David
> >
> >> On 10 September 2014 04:01, Fergal Byrne <[email protected]>
> wrote:
> >> Hi David,
> >>
> >> Wow, that looks and sounds like a great new addition to the NuPIC
> ecosystem. I'll have time to take a proper look at it this evening, but it
> already looks like you've pulled off yet another Ragazzi-quality
> production! Well done and thanks for sharing this - I think having great
> tools like this is hugely important for spreading the word about NuPIC and
> HTM.
> >>
> >> Cheers,
> >>
> >> Fergal Byrne
> >>
> >>> On Wed, Sep 10, 2014 at 6:57 AM, Kevin Martin <
> [email protected]> wrote:
> >>> Awesome! One more cool thing to do when I get time. Great work!
> >>>
> >>>> On Wed, Sep 10, 2014 at 11:08 AM, Ajay Ramanathan <
> [email protected]> wrote:
> >>>> It looks really cool; looking forward to it :D
> >>>>
> >>>>> On Wed, Sep 10, 2014 at 9:48 AM, Michael Neale <
> [email protected]> wrote:
> >>>>> This looks incredible - what a great tool. The connections
> visualisation looks like a great explanatory tool too!
> >>>>>
> >>>>>> On Wed, Sep 10, 2014 at 9:39 AM, David Ragazzi <
> [email protected]> wrote:
> >>>>>> Hello NuPICers!
> >>>>>>
> >>>>>> Just for inform that in all these days I was out, I was creating an
> a tool that I believe will be a breakthrough for the community. This tool
> calls "NuPIC Studio", or just NuStudio. NuStudio is an all?-in-?one tool
> that allows users create a HTM neural network from scratch, train it,
> collect statistics, and share it among the members of the community. It is
> not just a visualization tool but an HTM builder, debugger and laboratory
> for experiments. It is ideal for newbies with little intimacy with NuPIC
> code as well as experts that wish a better productivity. Among its features
> and advantages I list:
> >>>>>> - Users can open, save, or change their "HTM projects" or of other
> developers. A typical project contains data to be trained, neural network
> configuration, statistics, etc, which can be shared to be analysed or
> integrated with other projects.
> >>>>>> - The HTM engine is the own original NuPIC libray (Python
> distribution). This means no port, no bindings, no re-implementation, etc.
> So any changes in the original nupic source can be immediatedly viewed.
> This helps users that wish test improvements like new encoders or even
> hierarchy, attention, and motor integration.
> >>>>>> - The project is pip-installable and for desktop use.
> >>>>>>
> >>>>>> Project details:
> >>>>>> - All code is implemented in Python. When I say "all code", I
> really mean that code like GUI, 3d simulation, etc, are writen in Python
> and use open-source and cross platform components.
> >>>>>> - All GUI stuff (forms, controls, etc) is implemented in PyQT. PyQT
> is the version of the famous QT adapted for python apps, which is
> open-source, cross-platform, complete, and very easy to code and change.
> >>>>>> - All utilities like XML serialization, canvas 2d, etc, also are
> implemented in PyQT.
> >>>>>> - A front-end object-oriented layer also written in Python is
> provided in order to ease the understanding of the NuPIC code and keep
> backwards compatibility. This means that someone with less experience in
> NuPIC could re-use this front-end in her projects.
> >>>>>>
> >>>>>> The project's site is:
> >>>>>> https://github.com/DavidRagazzi/nupic.studio
> >>>>>>
> >>>>>> and you can see some screen-shots attached to this message.
> >>>>>>
> >>>>>> Surely it still is not 100%, and it's expected that some
> installation issues arise, but I hope optimize the process as soon as
> possible. By the way, it works reasonably well and any people is welcome to
> try it or even improve it.
> >>>>>>
> >>>>>> I look forward for your feedback, it is very important!
> >>>>>>
> >>>>>> Cheers,
> >>>>>> David
> >>>>>>
> >>>>>> --
> >>>>>> David Ragazzi
> >>>>>> MSc in Sofware Engineer (University of Liverpool)
> >>>>>> Try NuPIC Studio! https://github.com/DavidRagazzi/nupic.studio
> >>>>>> --
> >>>>>> "I think James Connolly, the Irish revolutionary, is right when he
> says that the only prophets are those who make their future. So we're not
> anticipating, we're working for it."
> >>>>>
> >>>>>
> >>>>>
> >>>>> --
> >>>>> Michael D Neale
> >>>>> home: www.michaelneale.net
> >>>>> blog: michaelneale.blogspot.com
> >>
> >>
> >>
> >> --
> >>
> >> Fergal Byrne, Brenter IT
> >>
> >> http://inbits.com - Better Living through Thoughtful Technology
> >> http://ie.linkedin.com/in/fergbyrne/ - https://github.com/fergalbyrne
> >>
> >> Author, Real Machine Intelligence with Clortex and NuPIC
> >> Read for free or buy the book at https://leanpub.com/realsmartmachines
> >>
> >> Speaking on Clortex and HTM/CLA at euroClojure Krakow, June 2014:
> http://euroclojure.com/2014/
> >> and at LambdaJam Chicago, July 2014: http://www.lambdajam.com
> >>
> >> e:[email protected] t:+353 83 4214179
> >> Join the quest for Machine Intelligence at http://numenta.org
> >> Formerly of Adnet [email protected] http://www.adnet.ie
> >
> >
> >
> > --
> > David Ragazzi
> > MSc in Sofware Engineer (University of Liverpool)
> > OS Community Commiter at Numenta.org
> > --
> > "I think James Connolly, the Irish revolutionary, is right when he says
> that the only prophets are those who make their future. So we're not
> anticipating, we're working for it."
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> Message: 9
> Date: Wed, 10 Sep 2014 13:57:32 +0200
> From: Marek Otahal <[email protected]>
> To: "NuPIC general mailing list." <[email protected]>
> Subject: Re: Introducing NuPIC Studio!
> Message-ID:
>         <CACh1_Rr4o_6C7nHMFOUxSXP5QEs=dn=v_bx=
> [email protected]>
> Content-Type: text/plain; charset="utf-8"
>
> Wow David!
> this looks awesome!
> Can't wait to get home and play with it.
> KUDOS!!
>
> On Wed, Sep 10, 2014 at 1:51 PM, Joseph Skippings <[email protected]
> >
> wrote:
>
> > Wow that is awesome!!!
> >
> > Sent from my iPhone
> >
> > On Sep 10, 2014, at 7:20 AM, David Ragazzi <[email protected]>
> wrote:
> >
> > Thank you, guys!
> >
> > > The connections visualisation looks like a great *explanatory tool*
> > too!
> >
> > This is other objective, I remember that Jeff Hawkins commented about the
> > need of tool that allow visualize a HTM in 3D to check what changed along
> > the time.. For this, NuStudio keeps the history of states (max=5, but you
> > can increase), so you might slide the "step bar" for check if the columns
> > are active at moment, were predicted or not, or if the input is
> unexpected
> > which cells were chosen as learning cells, or what new synapses were
> > created or removed, etc.
> >
> > > How difficult would it be for an intermediate developer to create a
> > similar application for Nupic.core c++?
> >
> > Daniel, you don't need re-invent the wheel, you could change NuStudio to
> > handle NuPIC C++ instead of NuPIC Python. It's because NuPIC Python dist
> > has some bindings to handle NuPIC C++. Theorically, you just need change
> > some "headers imports" and voil?.. But in the pratice, this is not
> > possible, because NuStudio uses the new TM (implemented on Python but not
> > on C++).. So I advise you wait a little until TM is implemented on C++..
> > But once this done, a few changes will be need..
> >
> > > another Ragazzi-quality production!
> >
> > Thanks for this, Fergal! :-D
> >
> > David
> >
> > On 10 September 2014 04:01, Fergal Byrne <[email protected]>
> > wrote:
> >
> >> Hi David,
> >>
> >> Wow, that looks and sounds like a great new addition to the NuPIC
> >> ecosystem. I'll have time to take a proper look at it this evening, but
> it
> >> already looks like you've pulled off yet another Ragazzi-quality
> >> production! Well done and thanks for sharing this - I think having great
> >> tools like this is hugely important for spreading the word about NuPIC
> and
> >> HTM.
> >>
> >> Cheers,
> >>
> >> Fergal Byrne
> >>
> >> On Wed, Sep 10, 2014 at 6:57 AM, Kevin Martin <
> >> [email protected]> wrote:
> >>
> >>> Awesome! One more cool thing to do when I get time. Great work!
> >>>
> >>> On Wed, Sep 10, 2014 at 11:08 AM, Ajay Ramanathan <
> [email protected]
> >>> > wrote:
> >>>
> >>>> It looks really cool; looking forward to it :D
> >>>>
> >>>> On Wed, Sep 10, 2014 at 9:48 AM, Michael Neale <
> [email protected]
> >>>> > wrote:
> >>>>
> >>>>> This looks incredible - what a great tool. The connections
> >>>>> visualisation looks like a great explanatory tool too!
> >>>>>
> >>>>> On Wed, Sep 10, 2014 at 9:39 AM, David Ragazzi <
> [email protected]
> >>>>> > wrote:
> >>>>>
> >>>>>> Hello NuPICers!
> >>>>>>
> >>>>>> Just for inform that in all these days I was out, I was creating an
> a
> >>>>>> tool that I believe will be a breakthrough for the community. This
> >>>>>> tool calls "NuPIC Studio", or just NuStudio. NuStudio is an
> >>>>>> all?-in-?one tool that allows users create a HTM neural network from
> >>>>>> scratch, train it, collect statistics, and share it among the
> members of
> >>>>>> the community. It is not just a visualization tool but an HTM
> builder,
> >>>>>> debugger and laboratory for experiments. It is ideal for newbies
> with
> >>>>>> little intimacy with NuPIC code as well as experts that wish a
> better
> >>>>>> productivity. Among its features and advantages I list:
> >>>>>> - Users can open, save, or change their "HTM projects" or of other
> >>>>>> developers. A typical project contains data to be trained, neural
> network
> >>>>>> configuration, statistics, etc, which can be shared to be analysed
> or
> >>>>>> integrated with other projects.
> >>>>>> - The HTM engine is the own original NuPIC libray (Python
> >>>>>> distribution). This means no port, no bindings, no
> re-implementation, etc.
> >>>>>> So any changes in the original nupic source can be immediatedly
> viewed.
> >>>>>> This helps users that wish test improvements like new encoders or
> even
> >>>>>> hierarchy, attention, and motor integration.
> >>>>>> - The project is pip-installable and for desktop use.
> >>>>>>
> >>>>>> Project details:
> >>>>>> - All code is implemented in Python. When I say "all code", I really
> >>>>>> mean that code like GUI, 3d simulation, etc, are writen in Python
> and use
> >>>>>> open-source and cross platform components.
> >>>>>> - All GUI stuff (forms, controls, etc) is implemented in PyQT. PyQT
> >>>>>> is the version of the famous QT adapted for python apps, which is
> >>>>>> open-source, cross-platform, complete, and very easy to code and
> change.
> >>>>>> - All utilities like XML serialization, canvas 2d, etc, also are
> >>>>>> implemented in PyQT.
> >>>>>> - A front-end object-oriented layer also written in Python is
> >>>>>> provided in order to ease the understanding of the NuPIC code and
> keep
> >>>>>> backwards compatibility. This means that someone with less
> experience in
> >>>>>> NuPIC could re-use this front-end in her projects.
> >>>>>>
> >>>>>> The project's site is:
> >>>>>> https://github.com/DavidRagazzi/nupic.studio
> >>>>>>
> >>>>>> and you can see some screen-shots attached to this message.
> >>>>>>
> >>>>>> Surely it still is not 100%, and it's expected that some
> installation
> >>>>>> issues arise, but I hope optimize the process as soon as possible.
> By the
> >>>>>> way, it works reasonably well and any people is welcome to try it
> or even
> >>>>>> improve it.
> >>>>>>
> >>>>>> I look forward for your feedback, it is very important!
> >>>>>>
> >>>>>> Cheers,
> >>>>>> David
> >>>>>>
> >>>>>> --
> >>>>>> David Ragazzi
> >>>>>> MSc in Sofware Engineer (University of Liverpool)
> >>>>>> Try NuPIC Studio! https://github.com/DavidRagazzi/nupic.studio
> >>>>>> --
> >>>>>> "I think James Connolly, the Irish revolutionary, is right when he
> >>>>>> says that the only prophets are those who make their future. So
> we're
> >>>>>> not anticipating, we're working for it."
> >>>>>>
> >>>>>
> >>>>>
> >>>>>
> >>>>> --
> >>>>> Michael D Neale
> >>>>> home: www.michaelneale.net
> >>>>> blog: michaelneale.blogspot.com
> >>>>>
> >>>>
> >>>>
> >>>
> >>
> >>
> >> --
> >>
> >> Fergal Byrne, Brenter IT
> >>
> >> http://inbits.com - Better Living through Thoughtful Technology
> >> http://ie.linkedin.com/in/fergbyrne/ - https://github.com/fergalbyrne
> >>
> >> Author, Real Machine Intelligence with Clortex and NuPIC
> >> Read for free or buy the book at https://leanpub.com/realsmartmachines
> >>
> >> Speaking on Clortex and HTM/CLA at euroClojure Krakow, June 2014:
> >> http://euroclojure.com/2014/
> >> and at LambdaJam Chicago, July 2014: http://www.lambdajam.com
> >>
> >> e:[email protected] t:+353 83 4214179
> >> Join the quest for Machine Intelligence at http://numenta.org
> >> Formerly of Adnet [email protected] http://www.adnet.ie
> >>
> >
> >
> >
> > --
> > David Ragazzi
> > MSc in Sofware Engineer (University of Liverpool)
> > OS Community Commiter at Numenta.org
> > --
> > "I think James Connolly, the Irish revolutionary, is right when he says
> that
> > the only prophets are those who make their future. So we're not
> > anticipating, we're working for it."
> >
> >
>
>
> --
> Marek Otahal :o)
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