Hi,
I have started learning artificial intelligence and currently going through
AIMA repository https://github.com/aimacode/aima-python but I am stucked at
model base reflex agent implementation in the 2D environment. Does anyone have
a good understanding of how model base agents work in 2D
Hello all,
Can anyone tell me how can I get the functional form of the fitted cubic spline
function on to my 2D array? For eg. when we fit the Gaussian on to an array so
we have the functional form with the parameters best fitted to my data likewise
how can we do for the cubic spline function
On 10 Dec 2015 14:46, "Heli" wrote:
>
> Thanks Peter,
>
> I will try to explain what I really need.
>
> I have a 3D numpy array of 100*100*100 (1M elements). Then I have another
numpy array of for example 10*2*10 (200 elements). I want to know if in the
bigger dataset of 100*100*100, there is anyw
Thanks Peter,
I will try to explain what I really need.
I have a 3D numpy array of 100*100*100 (1M elements). Then I have another numpy
array of for example 10*2*10 (200 elements). I want to know if in the bigger
dataset of 100*100*100, there is anywhere, where the second numpy array of 200
Heli wrote:
[Please don't open a new thread for the same problem]
> I need to check whether two 2d numpy arrays have intersections and if so I
> will need to have the cell indices of the intersection.
>
> By intersection, I exactly mean the intersection definition used in set
> theory.
>
> I w
Dear all,
I need to check whether two 2d numpy arrays have intersections and if so I will
need to have the cell indices of the intersection.
By intersection, I exactly mean the intersection definition used in set theory.
I will give an example of what I need to do:
a=[[0,1,2],[3,4,5],[6,7,8]]
Op dinsdag 25 maart 2014 20:15:27 UTC+1 schreef Joel Goldstick:
> Jean, be aware there is also python tutor list you might like. This is
> sometimes a tough crowd here. Don't be discouraged. It can be a badge of
> honor sometimes
thanks for the suggestions, I already subscribed to the python tu
Op dinsdag 25 maart 2014 20:58:10 UTC+1 schreef Dave Angel:
> Jean Dubois Wrote in message:
> > Op dinsdag 25 maart 2014 15:42:13 UTC+1 schreef Dave Angel:
>
> >> If your instructor wanted you to copy examples, he would have
> >> given you one.
> > please Dave leave that belittling tone behind,
Jean Dubois Wrote in message:
> Op dinsdag 25 maart 2014 15:42:13 UTC+1 schreef Dave Angel:
>> If your instructor wanted you to copy examples, he would have
>> given you one.
> please Dave leave that belittling tone behind, there's no instructor
> whatsoever involved here.
It wasn't my inten
Jean, be aware there is also python tutor list you might like. This is
sometimes a tough crowd here. Don't be discouraged. It can be a badge of
honor sometimes
--
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Op dinsdag 25 maart 2014 15:42:13 UTC+1 schreef Dave Angel:
> Jean Dubois Wrote in message:
> > Op dinsdag 25 maart 2014 12:01:37 UTC+1 schreef Steven D'Aprano:
> >>
> >> py> values = [float(s) for s in data.split()]
> >> py> print values
> >> [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]
> >> py>
s = [line.strip() for line in open("test.dat")]
> >>> lines
> ['1.0 2 3', '4 5 6.0', '7 8 9']
> As you can see lines is a list of three strings.
> Let's break these strings into parts:
> >>> cells = [line.split() for line in
On 3/25/14 9:42 AM, Dave Angel wrote:
All I need is a little python-example reading a file with e.g. three lines
with three numbers per line and putting those numbers as floats in a
3x3-numpy_array, then selecting an element from that numpy_array using
it's row and column-number.
If your instr
trings.
Let's break these strings into parts:
>>> cells = [line.split() for line in lines]
>>> cells
[['1.0', '2', '3'], ['4', '5', '6.0'], ['7', '8', '9']]
We now have a list of lists
On Tue, 25 Mar 2014 06:47:23 -0700, Jean Dubois wrote:
[...]
> Thanks for answering my question but unfortunately now I'm totally
> confused.
> Above I see parts from different programs which I can't assemble
> together to one working program (I really tried hard). Can I tell from
> your comment I
Jean Dubois Wrote in message:
> Op dinsdag 25 maart 2014 12:01:37 UTC+1 schreef Steven D'Aprano:
>>
>> py> values = [float(s) for s in data.split()]
>> py> print values
>> [1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 7.0, 8.0, 9.0]
>> py> array_lines = np.array(values)
>> py> array_lines = array_lines.reshape
Op dinsdag 25 maart 2014 12:01:37 UTC+1 schreef Steven D'Aprano:
> On Tue, 25 Mar 2014 03:26:26 -0700, Jean Dubois wrote:
>
> > I'm confused by the behaviour of the following python-script I wrote:
> >
> > #!/usr/bin/env python
> > #I first made a data file 'test.dat' with the following content
>
On Tue, 25 Mar 2014 03:26:26 -0700, Jean Dubois wrote:
> I'm confused by the behaviour of the following python-script I wrote:
>
> #!/usr/bin/env python
> #I first made a data file 'test.dat' with the following content
> #1.0 2 3
> #4 5 6.0
> #7 8 9
> import numpy as np
> lines=[line.strip() for
I'm confused by the behaviour of the following python-script I wrote:
#!/usr/bin/env python
#I first made a data file 'test.dat' with the following content
#1.0 2 3
#4 5 6.0
#7 8 9
import numpy as np
lines=[line.strip() for line in open('test.dat')]
#convert lines-list to numpy-array
array_lines=n
Great discussion started here
To answer some of the questions and to give more background:
- The grid resolution is 1x1cm. The problem starts when the distance of
the readings gets high. Then a 1° resolution doesn’t cover all cells anymore.
And cells get counted double on short distance
Gene Heskett wrote:
Your 1 degree assumption is, generally
speaking, an extremely coarse answer in terms of the accuracy needed, as we
need accuracies a lot closer to an arc-second than to a whole degree in
robotics.
That may be true for some applications, but somehow I doubt
that a sonar bea
ithin the arc for some
> > statistical calculations for an occupancy map.
> > So the target is a 2D array, not a picture.
> >
> > Robert
>
> If you go with one of the suggestions to use a graphics package to draw
> the arc, you can then take the resulting bitmap image
In article <1fc9a269-4847-4d29-a35e-5cf91731e...@googlegroups.com>,
Robert Voigtländer wrote:
> Thanks a lot for the links.
>
> I don't need it to be drawn. I need the fields within the arc for some
> statistical calculations for an occupancy map.
> So the target is
Thanks a lot for the links.
I don't need it to be drawn. I need the fields within the arc for some
statistical calculations for an occupancy map.
So the target is a 2D array, not a picture.
Robert
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Robert Voigtländer wrote:
> OK. Found a good one here:
> http://www.daniweb.com/software-development/python/threads/321181/python-
bresenham-circle-arc-algorithm
>
> Now only filling is needed.
> Any help is welcome ...
I think you shouldn't implement the algorithm directly. Rather look for a
l
OK. Found a good one here:
http://www.daniweb.com/software-development/python/threads/321181/python-bresenham-circle-arc-algorithm
Now only filling is needed.
Any help is welcome ...
Thanks
Robert
Am Montag, 25. November 2013 08:26:19 UTC+1 schrieb Robert Voigtländer:
> Hi,
>
>
>
> I wonder i
Hi,
I wonder if someone can help me with a function I need for programming my robot.
I want to update an 2D occupancy grid based on sonar data. The sonar “view
angle” is cone shaped. So I need to calculate all cells of a 30° slice of a
filled circle.
Something like this: http://www.intechopen.co
On 2009-07-27 06:24, Martin wrote:
Hi,
I am new to python and I was wondering if there was a way to speed up
the way I index 2D arrays when I need to check two arrays
simultaneously? My current implementations is (using numpy) something
like the following...
for i in range(numrows):
for j
On Jul 27, 4:12 pm, Peter Otten <__pete...@web.de> wrote:
> Martin wrote:
> > The statement works now, but it doesn't give the same results as my
> > original logic, strangely!?
>
> > in my logic:
>
> > data = np.zeros((numrows, numcols), dtype = np.uint8, order ='C')
>
> > for i in range(numrows):
Martin wrote:
> The statement works now, but it doesn't give the same results as my
> original logic, strangely!?
>
> in my logic:
>
> data = np.zeros((numrows, numcols), dtype = np.uint8, order ='C')
>
> for i in range(numrows):
> for j in range(numcols):
> if band3[i,j] == 255 or
On Jul 27, 2:17 pm, Peter Otten <__pete...@web.de> wrote:
> Martin wrote:
> > On Jul 27, 1:46 pm, Peter Otten <__pete...@web.de> wrote:
> >> Martin wrote:
> >> > On Jul 27, 12:42 pm, Peter Otten <__pete...@web.de> wrote:
> >> >> Martin wrote:
> >> >> > I am new to python and I was wondering if ther
Martin wrote:
> On Jul 27, 1:46 pm, Peter Otten <__pete...@web.de> wrote:
>> Martin wrote:
>> > On Jul 27, 12:42 pm, Peter Otten <__pete...@web.de> wrote:
>> >> Martin wrote:
>> >> > I am new to python and I was wondering if there was a way to speed
>> >> > up the way I index 2D arrays when I need
On Jul 27, 1:46 pm, Peter Otten <__pete...@web.de> wrote:
> Martin wrote:
> > On Jul 27, 12:42 pm, Peter Otten <__pete...@web.de> wrote:
> >> Martin wrote:
> >> > I am new to python and I was wondering if there was a way to speed up
> >> > the way I index 2D arrays when I need to check two arrays
>
Martin wrote:
> On Jul 27, 12:42 pm, Peter Otten <__pete...@web.de> wrote:
>> Martin wrote:
>> > I am new to python and I was wondering if there was a way to speed up
>> > the way I index 2D arrays when I need to check two arrays
>> > simultaneously? My current implementations is (using numpy) som
On Jul 27, 12:42 pm, Peter Otten <__pete...@web.de> wrote:
> Martin wrote:
> > I am new to python and I was wondering if there was a way to speed up
> > the way I index 2D arrays when I need to check two arrays
> > simultaneously? My current implementations is (using numpy) something
> > like the f
Martin wrote:
> I am new to python and I was wondering if there was a way to speed up
> the way I index 2D arrays when I need to check two arrays
> simultaneously? My current implementations is (using numpy) something
> like the following...
>
> for i in range(numrows):
> for j in range(numco
Hi,
I am new to python and I was wondering if there was a way to speed up
the way I index 2D arrays when I need to check two arrays
simultaneously? My current implementations is (using numpy) something
like the following...
for i in range(numrows):
for j in range(numcols):
if array_1
Thanks, everyone. All of your help solved at least my data storage
problem!
--
http://mail.python.org/mailman/listinfo/python-list
On Oct 11, 9:19 pm, Jillian Calderon <[EMAIL PROTECTED]>
wrote:
> How do I define a 2d list?
>
> For instance, to define a 4 by 5 list, I wanted to do this:
> n=4
> m=5
> world = [n][m]
> However, it gives me an invalid syntax error saying the index is out
> of range.
Here are some examples of how
Eric> I think you can do
Eric> mylist = [[]] or somesuch...
That won't do what you want. You've defined a list with a single element
(another list). You might have been thinking of something like this:
>>> N = 4
>>> M = 5
>>> mylist = [[0.0] * M] * N
While to the casual g
On Oct 12, 1:30 pm, [EMAIL PROTECTED] wrote:
> Jill> How do I define a 2d list?
>
> If you are looking to do numeric work with such multidimensional lists you
> should consider the builtin array object or the numpy package:
>
> http://docs.python.org/dev/library/array.html#module-array
The
On Oct 11, 9:30 pm, [EMAIL PROTECTED] wrote:
> Jill> How do I define a 2d list?
>
> Python doesn't truly have 2d lists in the way you might think of 2d arrays
> in C or Fortran. It has 1d lists which can contain any Python object,
> including other lists. If you wanted to create a 4x5 list yo
Jill> How do I define a 2d list?
Python doesn't truly have 2d lists in the way you might think of 2d arrays
in C or Fortran. It has 1d lists which can contain any Python object,
including other lists. If you wanted to create a 4x5 list you'd do
something like this:
N = 4
M = 5
Hi.
How do I define a 2d list?
For instance, to define a 4 by 5 list, I wanted to do this:
n=4
m=5
world = [n][m]
However, it gives me an invalid syntax error saying the index is out
of range.
I know this is a real newbie question, but if you could help me out,
I'd really appreciate it!
Thanks,
[EMAIL PROTECTED] wrote:
> I want to write an 2d array in an ascii file using numpy. There's the -
> tofile / fromfile - function but it doesn't work with nd array.
Is this good enough?
x = numpy.zeros( (10, 10) )
f = open('out.txt', 'w')
print
Hi,
I want to write an 2d array in an ascii file using numpy. There's the -
tofile / fromfile - function but it doesn't work with nd array.
Thanks,
CH.
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http://mail.python.org/mailman/listinfo/python-list
Tune Kamae (sent by Nabble.com) wrote:
> I am thinking to upgrade my desktop to 64bit cpu with 16GB memory to handle
> large astronomical images and data. I wonder if
> 1) the latest numarry (besides 2d slicing) has been tested with one or more
> 64 bit CPU and Linux distributions
Certainly.
I am thinking to upgrade my desktop to 64bit cpu with 16GB memory to handle
large astronomical images and data. I wonder if
1) the latest numarry (besides 2d slicing) has been tested with one or more
64 bit CPU and Linux distributions
2) with 64 bit address space, will numarray be able to h
thanks, i ran it -- the only difference i got was the numarray version:
1.1.1 on the 686, and 1.3.3 on the 64bit... but i wouldn't have thought
that would make too much difference.
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Do you have a simple program that demonstrates the problem?
I have an x86 machine with Python 2.3, and an x86_64 machine with Python 2.4
available. I wrote a simple test program which performs a slice operation,
but it behaves the same on both platforms.
Here's the program:
#
jeg wrote:
> dear all,
>
> i'm an astronomer working with 2d images -- 2d numarrays. i have a
> script which basically does some operations on some images, and one of
> the first steps is to find a galaxy on an image (at, say, a known x,y
> coord), and create a sub-image by slicing out part of the
dear all,
i'm an astronomer working with 2d images -- 2d numarrays. i have a
script which basically does some operations on some images, and one of
the first steps is to find a galaxy on an image (at, say, a known x,y
coord), and create a sub-image by slicing out part of the larger array
to create
On Wed, 2004-12-08 at 16:22, Steven Bethard wrote:
> Adam DePrince wrote:
> > The use of None as the default parameter was on purpose; the lack of
> > "magic" in python is often cited in religious wars between python and
> > perl aficionados. Use of get(something, None) was on purpose, the level
I am also not here to criticize style here, but I want to point
something out.
Something like a[1,2] might look wrong, but it's actually parsed
specially by Python to accommodate slicing of multidimensional arrays.
The difference is that, inside [], you can use slicing syntax, as in
a[1:2,3:4]. B
Adam DePrince wrote:
The use of None as the default parameter was on purpose; the lack of
"magic" in python is often cited in religious wars between python and
perl aficionados. Use of get(something, None) was on purpose, the level
of familiarity with the language implied by the original question
On Wed, 2004-12-08 at 15:06, Steven Bethard wrote:
> Adam DePrince wrote:
> > If your data is sparse you might want to consider using a dictionary
> > where the key is a tuple representing the coordinates.
> >
> > a = {}
> > a[(0,0)] = 0
> > a[(0,1)] = 1
> [snip]
> print a.get( (5,0), None )
>
Adam DePrince wrote:
If your data is sparse you might want to consider using a dictionary
where the key is a tuple representing the coordinates.
a = {}
a[(0,0)] = 0
a[(0,1)] = 1
[snip]
print a.get( (5,0), None )
Good point. Note that you don't need the parentheses in the assignments
or item acces
ment this in Python? thanks.
>
> If you're planning to do anything serious with a 2D array, you should
> probably look at numarray:
> http://www.stsci.edu/resources/software_hardware/numarray
>
> >>> import numarray as na
> >>> arr = na.array(range
LutherRevisited wrote:
I'm wanting to do something with a list that is basically a 2 dimensional
array. I'm not so good with lists so can someone give me an example of how I
might implement this in Python? thanks.
If you're planning to do anything serious with a 2D array, you s
I'm wanting to do something with a list that is basically a 2 dimensional
array. I'm not so good with lists so can someone give me an example of how I
might implement this in Python? thanks.
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