[Numpy-discussion] Replacing colours in numpy array

Fri Apr 10 10:18:52 EDT 2009

Hello

I have a numpy array that I obtained from a converted RGBA gif image. I have
tried to replace some colours with different ones using the where condition
but have a problem with dimensions.

If I use b=where(a==0,255,a) where a is a numpy array from an image it does
replace components of the RGB values in each pixel but it fails if I try
b=where(a==(0,0,0,255),(255,255,255,255),a) with incorrect dimension error.

Could you please help?

Thanks

Frank

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Today's Topics:

   1. Re: DVCS at PyCon (Ondrej Certik)
   2. Re: using reducing functions without	eliminating	dimensions?
      (Dan Lenski)
   3. Re: Another Array (Ian Mallett)
   4. Re: Another Array (Robert Kern)
   5. Re: Another Array (Ian Mallett)
   6. Re: Another Array (Robert Kern)
   7. Re: Another Array (Ian Mallett)
   8. Re: Another Array (Anne Archibald)

----------------------------------------------------------------------

Message: 1
Date: Thu, 9 Apr 2009 23:14:53 -0700
From: Ondrej Certik <ondrej at certik.cz>
Subject: Re: [Numpy-discussion] DVCS at PyCon
To: Discussion of Numerical Python <numpy-discussion at scipy.org>
Message-ID:
	<85b5c3130904092314o7512cdbfjd2f43b98e65f48cf at mail.gmail.com>
Content-Type: text/plain; charset=UTF-8

On Thu, Apr 9, 2009 at 10:45 PM, David Cournapeau
<david at ar.media.kyoto-u.ac.jp> wrote:
> Ondrej Certik wrote:
>>
>> It is maybe easier to learn how to work with different clones, but
>> once you start working with lots of patches and you need to reclone
>> all the time, then it's the wrong approach to work, as it takes lots
>> of time to copy the whole repository on the disk.
>
> Yes, *I* know how to use git, and I agree with you, I vastly prefer git
> branch handling to bzr branch handling. *I* find working with GUI for
> VCS a real PITA. But I am not the only numpy developer, that's why the
> feedback from people like Josef with a totally different workflow than
> me is valuable - much more than people like us who are unix geeks :)

Yes, definitely.

Ondrej

------------------------------

Message: 2
Date: Fri, 10 Apr 2009 06:36:08 +0000 (UTC)
From: Dan Lenski <dlenski at gmail.com>
Subject: Re: [Numpy-discussion] using reducing functions without
	eliminating	dimensions?
To: numpy-discussion at scipy.org
Message-ID: <grmpcn$2j4$1 at ger.gmane.org>
Content-Type: text/plain; charset=UTF-8

On Thu, 09 Apr 2009 01:31:33 -0500, Robert Kern wrote:

> On Thu, Apr 9, 2009 at 01:29, Anne Archibald <peridot.faceted at gmail.com>
> wrote:
> 
>> What's wrong with np.amin(a,axis=-1)[...,np.newaxis]?
> 
> It's cumbersome, particularly when you have axis=arbitrary_axis.

Quite right.  It would nice to be able to say:

np.amin(a, axiskeep=-1)
or
a.min(axiskeep=3)

... or something along those lines.

Dan

------------------------------

Message: 3
Date: Thu, 9 Apr 2009 23:42:03 -0700
From: Ian Mallett <geometrian at gmail.com>
Subject: Re: [Numpy-discussion] Another Array
To: Discussion of Numerical Python <numpy-discussion at scipy.org>
Message-ID:
	<a62fab400904092342y5509976bk927277d72730a095 at mail.gmail.com>
Content-Type: text/plain; charset="iso-8859-1"

It gives a perfect parabolic shape that looks very nice, but somewhat
unrealistic.  I'd like to scale the unit vectors by a random length (which
can just be a uniform distribution).  I tried scaling the unit vector n*n*3
array by a random n*n array, but that didn't work, obviously.  Help?
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Message: 4
Date: Fri, 10 Apr 2009 01:46:47 -0500
From: Robert Kern <robert.kern at gmail.com>
Subject: Re: [Numpy-discussion] Another Array
To: Discussion of Numerical Python <numpy-discussion at scipy.org>
Message-ID:
	<3d375d730904092346l6850c03chca1962915263e79c at mail.gmail.com>
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On Fri, Apr 10, 2009 at 01:42, Ian Mallett <geometrian at gmail.com> wrote:
> It gives a perfect parabolic shape that looks very nice, but somewhat
> unrealistic.

Parabolic? They should be spherical.

> I'd like to scale the unit vectors by a random length (which
> can just be a uniform distribution).? I tried scaling the unit vector
n*n*3
> array by a random n*n array, but that didn't work, obviously.

No, it's not obvious. Exactly what code did you try? What results did
you get? What results were you expecting?

> Help?

Let's take a step back. What kind of distribution are you trying to
achieve? You asked for uniformly distributed unit vectors. Now you are
asking for something else, but I'm really not sure what. What standard
are you comparing against when you say that the unit vectors look
"unrealistic"?

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
  -- Umberto Eco

------------------------------

Message: 5
Date: Thu, 9 Apr 2009 23:58:21 -0700
From: Ian Mallett <geometrian at gmail.com>
Subject: Re: [Numpy-discussion] Another Array
To: Discussion of Numerical Python <numpy-discussion at scipy.org>
Message-ID:
	<a62fab400904092358m60233289u73aba89a6bdad4b2 at mail.gmail.com>
Content-Type: text/plain; charset="iso-8859-1"

On Thu, Apr 9, 2009 at 11:46 PM, Robert Kern <robert.kern at gmail.com> wrote:

> Parabolic? They should be spherical.

The particle system in the last screenshot was affected by gravity.  In the
absence of gravity, the results should be spherical, yes.  All the vectors
are a unit length, which produces a perfectly smooth surface (unrealistic
for such an effect).

> No, it's not obvious. Exactly what code did you try? What results did
> you get? What results were you expecting?

It crashed.
I have this code:
vecs = Numeric.random.standard_normal(size=(self.size[0],self.size[1],3))
magnitudes = Numeric.sqrt((vecs*vecs).sum(axis=-1))
uvecs = vecs / magnitudes[...,Numeric.newaxis]
randlen = Numeric.random.random((self.size[0],self.size[1]))
randuvecs = uvecs*randlen #It crashes here with a dimension mismatch
rgb = ((randvecs+1.0)/2.0)*255.0

I also tried randlen = Numeric.random.random((self.size[0],self.size[1],3)),
but this does not scale each of the vector's components equally, producing
artifacts again.  Each needs to be scaled by the same random value for it to
make sense.

> Let's take a step back. What kind of distribution are you trying to
> achieve? You asked for uniformly distributed unit vectors. Now you are
> asking for something else, but I'm really not sure what. What standard
> are you comparing against when you say that the unit vectors look
> "unrealistic"?

The vectors are used to "jitter" each particle's initial speed, so that the
particles go in different directions instead of moving all as one.  Using
the unit vector causes the particles to make the smooth parabolic shape.
The jitter vectors much then be of a random length, so that the particles go
in all different directions at all different speeds, instead of just all in
different directions.

Ian
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Message: 6
Date: Fri, 10 Apr 2009 02:01:10 -0500
From: Robert Kern <robert.kern at gmail.com>
Subject: Re: [Numpy-discussion] Another Array
To: Discussion of Numerical Python <numpy-discussion at scipy.org>
Message-ID:
	<3d375d730904100001w4cdb7bedi2b36bca97731ef8c at mail.gmail.com>
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On Fri, Apr 10, 2009 at 01:58, Ian Mallett <geometrian at gmail.com> wrote:
> On Thu, Apr 9, 2009 at 11:46 PM, Robert Kern <robert.kern at gmail.com>
wrote:
>>
>> Parabolic? They should be spherical.
>
> The particle system in the last screenshot was affected by gravity.? In
the
> absence of gravity, the results should be spherical, yes.? All the vectors
> are a unit length, which produces a perfectly smooth surface (unrealistic
> for such an effect).
>>
>> No, it's not obvious. Exactly what code did you try? What results did
>> you get? What results were you expecting?
>
> It crashed.
> I have this code:
> vecs = Numeric.random.standard_normal(size=(self.size[0],self.size[1],3))
> magnitudes = Numeric.sqrt((vecs*vecs).sum(axis=-1))
> uvecs = vecs / magnitudes[...,Numeric.newaxis]
> randlen = Numeric.random.random((self.size[0],self.size[1]))
> randuvecs = uvecs*randlen #It crashes here with a dimension mismatch
> rgb = ((randvecs+1.0)/2.0)*255.0
>
> I also tried randlen =
Numeric.random.random((self.size[0],self.size[1],3)),
> but this does not scale each of the vector's components equally, producing
> artifacts again.? Each needs to be scaled by the same random value for it
to
> make sense.

See how I did magnitudes[...,numpy.newaxis]? You have to do the same.

>> Let's take a step back. What kind of distribution are you trying to
>> achieve? You asked for uniformly distributed unit vectors. Now you are
>> asking for something else, but I'm really not sure what. What standard
>> are you comparing against when you say that the unit vectors look
>> "unrealistic"?
>
> The vectors are used to "jitter" each particle's initial speed, so that
the
> particles go in different directions instead of moving all as one.? Using
> the unit vector causes the particles to make the smooth parabolic shape.
> The jitter vectors much then be of a random length, so that the particles
go
> in all different directions at all different speeds, instead of just all
in
> different directions.

Ah, okay. That makes sense.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless
enigma that is made terrible by our own mad attempt to interpret it as
though it had an underlying truth."
  -- Umberto Eco

------------------------------

Message: 7
Date: Fri, 10 Apr 2009 00:07:45 -0700
From: Ian Mallett <geometrian at gmail.com>
Subject: Re: [Numpy-discussion] Another Array
To: Discussion of Numerical Python <numpy-discussion at scipy.org>
Message-ID:
	<a62fab400904100007y185a80d5jfa4d62a850d1245 at mail.gmail.com>
Content-Type: text/plain; charset="iso-8859-1"

This seems to work:

vecs = Numeric.random.standard_normal(size=(self.size[0],self.size[1],3))
magnitudes = Numeric.sqrt((vecs*vecs).sum(axis=-1))
uvecs = vecs / magnitudes[...,Numeric.newaxis]
randlen = Numeric.random.random((self.size[0],self.size[1]))
randuvecs = uvecs*randlen[...,Numeric.newaxis]
rgb = ((randuvecs+1.0)/2.0)*255.0

(I have "import numpy as Numeric" for other reasons, that's why there's
Numeric there).

Thanks,
Ian
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Message: 8
Date: Fri, 10 Apr 2009 03:17:58 -0400
From: Anne Archibald <peridot.faceted at gmail.com>
Subject: Re: [Numpy-discussion] Another Array
To: Discussion of Numerical Python <numpy-discussion at scipy.org>
Message-ID:
	<ce557a360904100017l45019b89t32ce233226c4fae0 at mail.gmail.com>
Content-Type: text/plain; charset=UTF-8

2009/4/10 Ian Mallett <geometrian at gmail.com>:

> The vectors are used to "jitter" each particle's initial speed, so that
the
> particles go in different directions instead of moving all as one.? Using
> the unit vector causes the particles to make the smooth parabolic shape.
> The jitter vectors much then be of a random length, so that the particles
go
> in all different directions at all different speeds, instead of just all
in
> different directions.

Why not just skip the normalization? Then you'll get vectors with
random direction and a natural distribution of lengths. And it'll be
faster than tne unit vectors...

Anne

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