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Do other Python GUI toolkits require this?

P: n/a
From the introduction to PyObjC, the Python-Objective-C bridge on Mac OS X:

"As described in Objective-C for PyObjC users the creation of
Objective-C objects is a two-stage process. To initialize objects, first
call a class method to allocate the memory (typically alloc), and then
call an initializer (typically starts with init). Some classes have
class methods which perform this behind the scenes, especially classes
that create cached, immutable, or singleton instances."

An example:

myObject = NSObject.alloc().init()

I know Tkinter doesn't require any manual memory allocation of this
sort. Does wxPython, PyQt, PyGtk require anything like this when
creating objects?

--
Kevin Walzer
Code by Kevin
http://www.codebykevin.com
Apr 18 '07 #1
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P: n/a
Kevin Walzer wrote:
From the introduction to PyObjC, the Python-Objective-C bridge on Mac
OS X:

"As described in Objective-C for PyObjC users the creation of
Objective-C objects is a two-stage process. To initialize objects, first
call a class method to allocate the memory (typically alloc), and then
call an initializer (typically starts with init). Some classes have
class methods which perform this behind the scenes, especially classes
that create cached, immutable, or singleton instances."

An example:

myObject = NSObject.alloc().init()

I know Tkinter doesn't require any manual memory allocation of this
sort. Does wxPython, PyQt, PyGtk require anything like this when
creating objects?
This appears more or less unique to Objective C. It looks that with
PyObjC, you have to interact with the Objective C runtime to manage
memory. This is not required, thankfully, with any other GUI tookits
I've seen.

I think the main difference is that PyObjC is not a GUI toolkit per se,
but is simply a means to make the Objective C runtime (and hence Cocoa)
available via a python layer.

James
Apr 18 '07 #2

P: n/a
James Stroud wrote:
This appears more or less unique to Objective C. It looks that with
PyObjC, you have to interact with the Objective C runtime to manage
memory. This is not required, thankfully, with any other GUI tookits
I've seen.

I think the main difference is that PyObjC is not a GUI toolkit per se,
but is simply a means to make the Objective C runtime (and hence Cocoa)
available via a python layer.

James
That's kind of what I thought. Memory management? In Python? *shudder*

I'm a Mac-only developer, and I keep telling myself I should drink the
Mac-only Kool-aid of PyObjC. But Tk is burned into my brain, and
anything else looks and feels weird to me. Tk is so flexible that it's
fairly easy to tweak it to look Mac-like, and it's simpler to do that
than learn a new tookit.

--
Kevin Walzer
Code by Kevin
http://www.codebykevin.com
Apr 18 '07 #3

P: n/a

On Apr 18, 2007, at 5:11 PM, Kevin Walzer wrote:
James Stroud wrote:
>This appears more or less unique to Objective C. It looks that with
PyObjC, you have to interact with the Objective C runtime to manage
memory. This is not required, thankfully, with any other GUI tookits
I've seen.

I think the main difference is that PyObjC is not a GUI toolkit
per se,
but is simply a means to make the Objective C runtime (and hence
Cocoa)
available via a python layer.

James

That's kind of what I thought. Memory management? In Python? *shudder*

I'm a Mac-only developer, and I keep telling myself I should drink the
Mac-only Kool-aid of PyObjC. But Tk is burned into my brain, and
anything else looks and feels weird to me. Tk is so flexible that it's
fairly easy to tweak it to look Mac-like, and it's simpler to do that
than learn a new tookit.
PyObjC is pretty slick (and since Ronald hasn't made any commits in a
while I'm nearly certain it'll show up in the next official
distribution of the devtools). About the time you gave up on PyQt on
the Mac and switched over to Tkinter, I switched to PyObjC. The
learning curve is rather steep IMO, but worth it. One thing I think
I should mention though is that if you move to PyObjC -- do some
projects in Objective C first. Otherwise your brain will implode.

hth,
Michael

Apr 19 '07 #4

P: n/a
On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:
>
On Apr 18, 2007, at 5:11 PM, Kevin Walzer wrote:
>James Stroud wrote:
>>This appears more or less unique to Objective C. It looks that with
PyObjC, you have to interact with the Objective C runtime to manage
memory. This is not required, thankfully, with any other GUI tookits
I've seen.

I think the main difference is that PyObjC is not a GUI toolkit
per se,
but is simply a means to make the Objective C runtime (and hence
Cocoa)
available via a python layer.

James

That's kind of what I thought. Memory management? In Python? *shudder*

I'm a Mac-only developer, and I keep telling myself I should drink the
Mac-only Kool-aid of PyObjC. But Tk is burned into my brain, and
anything else looks and feels weird to me. Tk is so flexible that it's
fairly easy to tweak it to look Mac-like, and it's simpler to do that
than learn a new tookit.

PyObjC is pretty slick (and since Ronald hasn't made any commits in a
while I'm nearly certain it'll show up in the next official
distribution of the devtools). About the time you gave up on PyQt on
the Mac and switched over to Tkinter, I switched to PyObjC. The
learning curve is rather steep IMO, but worth it.
Just a throw in remark, that you may ignore if you wish, but a steep
learning curve means that the subject is easily familiarized and that
the learning period is short.

You seem to use it as if it is the opposite.

--
Antoon Pardon
Apr 19 '07 #5

P: n/a

On Apr 19, 2007, at 4:11 AM, Antoon Pardon wrote:
On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:
>>
On Apr 18, 2007, at 5:11 PM, Kevin Walzer wrote:
>>James Stroud wrote:

This appears more or less unique to Objective C. It looks that with
PyObjC, you have to interact with the Objective C runtime to manage
memory. This is not required, thankfully, with any other GUI
tookits
I've seen.

I think the main difference is that PyObjC is not a GUI toolkit
per se,
but is simply a means to make the Objective C runtime (and hence
Cocoa)
available via a python layer.

James

That's kind of what I thought. Memory management? In Python?
*shudder*

I'm a Mac-only developer, and I keep telling myself I should
drink the
Mac-only Kool-aid of PyObjC. But Tk is burned into my brain, and
anything else looks and feels weird to me. Tk is so flexible that
it's
fairly easy to tweak it to look Mac-like, and it's simpler to do
that
than learn a new tookit.

PyObjC is pretty slick (and since Ronald hasn't made any commits in a
while I'm nearly certain it'll show up in the next official
distribution of the devtools). About the time you gave up on PyQt on
the Mac and switched over to Tkinter, I switched to PyObjC. The
learning curve is rather steep IMO, but worth it.

Just a throw in remark, that you may ignore if you wish, but a steep
learning curve means that the subject is easily familiarized and that
the learning period is short.

You seem to use it as if it is the opposite.
Mathematical absurdities aside, it's the common usage -- but perhaps
you knew that.
Apr 19 '07 #6

P: n/a
On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:
>
On Apr 19, 2007, at 4:11 AM, Antoon Pardon wrote:
>On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:
>>>
PyObjC is pretty slick (and since Ronald hasn't made any commits in a
while I'm nearly certain it'll show up in the next official
distribution of the devtools). About the time you gave up on PyQt on
the Mac and switched over to Tkinter, I switched to PyObjC. The
learning curve is rather steep IMO, but worth it.

Just a throw in remark, that you may ignore if you wish, but a steep
learning curve means that the subject is easily familiarized and that
the learning period is short.

You seem to use it as if it is the opposite.

Mathematical absurdities aside, it's the common usage -- but perhaps
you knew that.
I don't know how you come to the conclusion that it is a mathematical
absurdity but consider this: If you find that common usage propagates
something that is incorrect, should we just shrug it off or should we
attemp a correction? There is always a chance that one day you find
yourself exposed to a learning curve while going through a document.
If you just depend on common usage you will probably draw the wrong
conclusion.

--
Antoon Pardon
Apr 19 '07 #7

P: n/a
*plonk*
Apr 19 '07 #8

P: n/a
Michael Bentley wrote:
On Apr 19, 2007, at 4:11 AM, Antoon Pardon wrote:
>On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:
[...] The
>>learning curve is rather steep IMO, but worth it.
Just a throw in remark, that you may ignore if you wish, but a steep
learning curve means that the subject is easily familiarized and that
the learning period is short.

You seem to use it as if it is the opposite.

Mathematical absurdities aside, it's the common usage -- but perhaps
you knew that.

Perhaps in Belgium they prefer climbing mountains over walking up and
down gentle hills? Or possibly they will simply pick any nit that is
carelessly left within range?

http://home.earthlink.net/~macrakis/...ew_Recipe.html

Don't forget the salt, Antoon!

regards
Steve
--
Steve Holden +44 150 684 7255 +1 800 494 3119
Holden Web LLC/Ltd http://www.holdenweb.com
Skype: holdenweb http://del.icio.us/steve.holden
Recent Ramblings http://holdenweb.blogspot.com

Apr 19 '07 #9

P: n/a
On 2007-04-19, Steve Holden <st***@holdenweb.comwrote:
Michael Bentley wrote:
>On Apr 19, 2007, at 4:11 AM, Antoon Pardon wrote:
>>On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:
[...] The
>>>learning curve is rather steep IMO, but worth it.
Just a throw in remark, that you may ignore if you wish, but a steep
learning curve means that the subject is easily familiarized and that
the learning period is short.

You seem to use it as if it is the opposite.

Mathematical absurdities aside, it's the common usage -- but perhaps
you knew that.

Perhaps in Belgium they prefer climbing mountains over walking up and
down gentle hills? Or possibly they will simply pick any nit that is
carelessly left within range?
If it is just a nit, why don't you ignore my remark as I suggested?

Now suppose I give you a graph that shows you how different people
are making progress. Would you prefer the rather flat curves instead
of the steep curves because the latter gives you the idea of someone
having to conquer huge obstacles or would you choose the steep curve
because they show you someone is getting results fast?

--
Antoon Pardon
Apr 19 '07 #10

P: n/a
Antoon Pardon wrote:
On 2007-04-19, Steve Holden <st***@holdenweb.comwrote:
>Michael Bentley wrote:
>>On Apr 19, 2007, at 4:11 AM, Antoon Pardon wrote:

On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:
[...] The
>>>>learning curve is rather steep IMO, but worth it.
Just a throw in remark, that you may ignore if you wish, but a steep
learning curve means that the subject is easily familiarized and that
the learning period is short.

You seem to use it as if it is the opposite.
Mathematical absurdities aside, it's the common usage -- but perhaps
you knew that.

Perhaps in Belgium they prefer climbing mountains over walking up and
down gentle hills? Or possibly they will simply pick any nit that is
carelessly left within range?

If it is just a nit, why don't you ignore my remark as I suggested?
Because I suffer from the quixotic urge to help stamp out obsessive
compulsive behavior on c.l.py? This is self-defeating, of course, since
it makes me appear obsessive compulsive in my own right ...
Now suppose I give you a graph that shows you how different people
are making progress. Would you prefer the rather flat curves instead
of the steep curves because the latter gives you the idea of someone
having to conquer huge obstacles or would you choose the steep curve
because they show you someone is getting results fast?
Suppose I should you a hill you have to climb? Would you rather don
mountain boots and crampons to climb 3,000 feet up a vertical cliff or
would you rather amble up, say, Ben Lomond with the other tourists?

Clearly you have no wish to bow before common usage. be careful this
doesn't put you in a universe with only one inhabitant. We all have to
get along.

obsessive-compulsive-ly y'rs - steve
--
Steve Holden +44 150 684 7255 +1 800 494 3119
Holden Web LLC/Ltd http://www.holdenweb.com
Skype: holdenweb http://del.icio.us/steve.holden
Recent Ramblings http://holdenweb.blogspot.com

Apr 19 '07 #11

P: n/a
I don't know how this whole things started,

But it is funny on both sides. And hilarious from the outside. It sounds
like university Banter really. And who can avoid getting their 2 cents
in. Honestly

And people say computers are all about science. You guys prove that we
are all as much tech geeks and semantic geeks.
>From my own experiential education background, and currently trying to
learn python I would say my exposure to python as a scripting language
is a logical extension to my knowledge of DOS and BASH scripting so in
that respect I am on a shallow learning curve. That is little effort
(say 5 on the X axis) over a given time (say 10 y).

Now, my goal is to take what I had learn about VB6 over the last number
of months to modify a chunk of in-house software My learning curve was
steeper. That is I had the same amount of time (10 y) but I had to put
in some more effort, so a moderate curve using 10 X as my peak, or point
where I plateau.

However where I as a newbie am having a hard time is programming a GUI
and full application using python (hence why I saw the topic), and
understanding OOP. Therefore right now I feel as though I am on a steep
learning curve. So maybe 20 or 30 on the X and I still have the same
amount of time.

To further support this I took the first result of google (of course the
worlds most authoritative resource on randomness) and went to this BLOG
(worlds best phenomena of random and unsubstantiated opinions).
http://createwhatmattersmost.blogspo...-curve-explain
ed.html

And found this

I guess I'm approaching the "knee" of the learning curve, that magical
transition point on the learning at which you begin to generate results
far out of proportion to time and energy expended.

This tells me my understanding is the common accepted one of X= Effort,
Y= time or productivity ... But really productivity is a function of
time.
C'mon now folks, if this is university banter the least I should see is
some referencing.

Thanks for demonstrating my own lack of will power and propensity to
engage in both of your OCB.

Now I must get back to my steep learning curve or else I will be back on
the street.

Cheers
-----Original Message-----
From: py**************************************@python.or g
[mailto:py**************************************@py thon.org] On Behalf
Of Steve Holden
Sent: April 19, 2007 08:25
To: py*********@python.org
Subject: Re: Do other Python GUI toolkits require this?

Antoon Pardon wrote:
On 2007-04-19, Steve Holden <st***@holdenweb.comwrote:
>Michael Bentley wrote:
>>On Apr 19, 2007, at 4:11 AM, Antoon Pardon wrote:

On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:
[...] The
>>>>learning curve is rather steep IMO, but worth it.
Just a throw in remark, that you may ignore if you wish, but a
steep learning curve means that the subject is easily familiarized
and that the learning period is short.

You seem to use it as if it is the opposite.
Mathematical absurdities aside, it's the common usage -- but perhaps
>>you knew that.

Perhaps in Belgium they prefer climbing mountains over walking up and
>down gentle hills? Or possibly they will simply pick any nit that is
carelessly left within range?
If it is just a nit, why don't you ignore my remark as I suggested?
Because I suffer from the quixotic urge to help stamp out obsessive
compulsive behavior on c.l.py? This is self-defeating, of course, since
it makes me appear obsessive compulsive in my own right ...
Now suppose I give you a graph that shows you how different people are
making progress. Would you prefer the rather flat curves instead of
the steep curves because the latter gives you the idea of someone
having to conquer huge obstacles or would you choose the steep curve
because they show you someone is getting results fast?
Suppose I should you a hill you have to climb? Would you rather don
mountain boots and crampons to climb 3,000 feet up a vertical cliff or
would you rather amble up, say, Ben Lomond with the other tourists?

Clearly you have no wish to bow before common usage. be careful this
doesn't put you in a universe with only one inhabitant. We all have to
get along.

obsessive-compulsive-ly y'rs - steve
--
Steve Holden +44 150 684 7255 +1 800 494 3119
Holden Web LLC/Ltd http://www.holdenweb.com
Skype: holdenweb http://del.icio.us/steve.holden
Recent Ramblings http://holdenweb.blogspot.com

--
http://mail.python.org/mailman/listinfo/python-list
Apr 19 '07 #12

P: n/a
On Apr 19, 6:54 am, Antoon Pardon <apar...@forel.vub.ac.bewrote:
I don't know how you come to the conclusion that it is a mathematical
absurdity but consider this: If you find that common usage propagates
something that is incorrect, should we just shrug it off or should we
attemp a correction?
a) In English, "learning curve" is not restricted to a mathematical
plot--Webster's also defines it as "the course of progress made in
learning something". In that context, adding the adjective steep
("extremely or excessively high...STEEP implies such sharpness of
pitch that ascent or descent is very difficult") makes sense.

Trying to apply a mathematical definition to an English-language
phrase is prone to incorrect outcomes.

b) The purpose of language is to communicate. In English, if a phrase
now means something in common usage, then that is (one of) its current
definition(s)--this is possibly different from some other languages
where there is an attempt to have an "officially sanctioned" set of
definitions and spellings that may differ from common usage. If you
find that everyone else means something when they say a phrase, you'd
best learn what they mean if you want to be speaking the same language
(and hence be able to communicate with them).

Apr 19 '07 #13

P: n/a
On Thu, 19 Apr 2007 19:11, Antoon Pardon wrote in comp.lang.python:
On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:
<snip type="various irrelevances to my comment below" />
>The learning curve is rather steep IMO, but worth it.

Just a throw in remark, that you may ignore if you wish, but a steep
learning curve means that the subject is easily familiarized and that
the learning period is short.

You seem to use it as if it is the opposite.
Who says the axes are labeled "familiarity" and "learning period"? I
just assume they are labeled (y-axis) "Effort" and (x-axis) "Knowledge"
(or "skill" or ....).

Which means that something with a 'steep learning curve' requires a lot
of effort to achieve a small amount of knowledge (or skill or ...).

--
Nigel Rowe
A pox upon the spammers that make me write my address like..
rho (snail) swiftdsl (stop) com (stop) au
Apr 20 '07 #14

P: n/a
On 2007-04-19, Steve Holden <st***@holdenweb.comwrote:
Antoon Pardon wrote:
>On 2007-04-19, Steve Holden <st***@holdenweb.comwrote:
>>Michael Bentley wrote:
On Apr 19, 2007, at 4:11 AM, Antoon Pardon wrote:

On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:
[...] The
>learning curve is rather steep IMO, but worth it.
Just a throw in remark, that you may ignore if you wish, but a steep
learning curve means that the subject is easily familiarized and that
the learning period is short.
>
You seem to use it as if it is the opposite.
Mathematical absurdities aside, it's the common usage -- but perhaps
you knew that.
Perhaps in Belgium they prefer climbing mountains over walking up and
down gentle hills? Or possibly they will simply pick any nit that is
carelessly left within range?

If it is just a nit, why don't you ignore my remark as I suggested?
Because I suffer from the quixotic urge to help stamp out obsessive
compulsive behavior on c.l.py? This is self-defeating, of course, since
it makes me appear obsessive compulsive in my own right ...
>Now suppose I give you a graph that shows you how different people
are making progress. Would you prefer the rather flat curves instead
of the steep curves because the latter gives you the idea of someone
having to conquer huge obstacles or would you choose the steep curve
because they show you someone is getting results fast?
Suppose I should you a hill you have to climb? Would you rather don
mountain boots and crampons to climb 3,000 feet up a vertical cliff or
would you rather amble up, say, Ben Lomond with the other tourists?
So if you have the choice between a steep or a shalow income curve
you will prefer the shalow curve because a steep curve makes you
think about verticale clifs and such?

The analogy with a walk is just silly because curves are not like walks.
Nobody will say something like: I won't invest in that company because
it has a steep profit curve or the reverse: I'll invest in this company
because it has an easy looking downhill going profit curve.
Clearly you have no wish to bow before common usage. be careful this
doesn't put you in a universe with only one inhabitant. We all have to
get along.
Indeed I have no wish to bow before common usage. I prefer to think
about things and dare to speak out when they don't seem to make sense.

Just repeating common usage propagates a lot of nonsense.
Apr 20 '07 #15

P: n/a
On 2007-04-19, Wayne Brehaut <wb******@mcsnet.cawrote:
On 19 Apr 2007 10:54:20 GMT, Antoon Pardon <ap*****@forel.vub.ac.be>
wrote:
>>On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:
>>>
On Apr 19, 2007, at 4:11 AM, Antoon Pardon wrote:

On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:
>
PyObjC is pretty slick (and since Ronald hasn't made any commits in a
while I'm nearly certain it'll show up in the next official
distribution of the devtools). About the time you gave up on PyQt on
the Mac and switched over to Tkinter, I switched to PyObjC. The
learning curve is rather steep IMO, but worth it.

Just a throw in remark, that you may ignore if you wish, but a steep
learning curve means that the subject is easily familiarized and that
the learning period is short.

You seem to use it as if it is the opposite.

Mathematical absurdities aside, it's the common usage -- but perhaps
you knew that.

I don't know how you come to the conclusion that it is a mathematical
absurdity but consider this: If you find that common usage propagates
something that is incorrect, should we just shrug it off or should we
attemp a correction? There is always a chance that one day you find
yourself exposed to a learning curve while going through a document.
If you just depend on common usage you will probably draw the wrong
conclusion.

The only way one could assume the "common usage" to be a mathematical
absurdity would be not to think about it or not to have much
mathematical insight or "maturity". Is a vertical cliff not steep no
matter how high it is? And is a gentle grade (say <= 10%) not
un-steep no matter how long it is? Is the slope of a curve dependent
on its length?

So the remark that " a steep learning curve means that the subject is
easily familiarized and that the learning period is short" is
completely incorrect on two points (i.e., all points that are
relevant): first, steep always implies much to learn in a relatively
short time (what else could the slope of a curve possibly mean
"mathematicallY" or logically?);
No it doesn't imply that at all. A learning curve doesn't show some
goal of a person who was given just so much time to familiarize himself
with some material. A learning curve shows the progres that is made
in familiarizing one self while studying. A steep curve means a
lot of actual learning in a short time.
second, steepness is independent of
length, so "steep" has no implication in general about how long the
learning curve will be--on the contrary, in fact, it's quite possible
that a learning curve will never have any great challenges (steep
portions) but be only a very long gradual process--as the learning of
many natural languages is.
That doesn't contradict that if one language has a steeper curve to
learn than a second. Familiarisation with the first language will
be faster and easier than with the second.
A learning curve is conventionally the graph of a function of
"quantity to be learned" vs. time,
No it doesn't. A learning curve is the graph that somehow quantifies
what is actually learned vs time.

--
Antoon Pardon
Apr 20 '07 #16

P: n/a
On 2007-04-19, sj*******@yahoo.com <sj*******@yahoo.comwrote:
On Apr 19, 6:54 am, Antoon Pardon <apar...@forel.vub.ac.bewrote:
>I don't know how you come to the conclusion that it is a mathematical
absurdity but consider this: If you find that common usage propagates
something that is incorrect, should we just shrug it off or should we
attemp a correction?

a) In English, "learning curve" is not restricted to a mathematical
plot--Webster's also defines it as "the course of progress made in
learning something". In that context, adding the adjective steep
("extremely or excessively high...STEEP implies such sharpness of
pitch that ascent or descent is very difficult") makes sense.
How much sense does it really make? Suppose we would talk about
an income curve. Would you not prefer a steep curve over a shalow
one? What about a productivity curve? It is all about the progress
made in something.

So how much sense does it make that a steep curve in earnings and
productivity is good but a steep curve in learning is bad?
Trying to apply a mathematical definition to an English-language
phrase is prone to incorrect outcomes.

b) The purpose of language is to communicate. In English, if a phrase
now means something in common usage, then that is (one of) its current
definition(s)--this is possibly different from some other languages
where there is an attempt to have an "officially sanctioned" set of
definitions and spellings that may differ from common usage. If you
find that everyone else means something when they say a phrase, you'd
best learn what they mean if you want to be speaking the same language
(and hence be able to communicate with them).
But the problem is that even if this would be only a way to communicate
in englishi, a lot of people get the wrong idea about real curves from
this idiom, as this thread shows. So even if you only want to communicate
one specific idea that comes accross as intended, you also propagate
a lot of nonsense with it.

--
Antoon Pardon
Apr 20 '07 #17

P: n/a
On 2007-04-20, Nigel Rowe <se*@signature.invalidwrote:
On Thu, 19 Apr 2007 19:11, Antoon Pardon wrote in comp.lang.python:
>On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:

<snip type="various irrelevances to my comment below" />
>>The learning curve is rather steep IMO, but worth it.

Just a throw in remark, that you may ignore if you wish, but a steep
learning curve means that the subject is easily familiarized and that
the learning period is short.

You seem to use it as if it is the opposite.

Who says the axes are labeled "familiarity" and "learning period"? I
just assume they are labeled (y-axis) "Effort" and (x-axis) "Knowledge"
(or "skill" or ....).
You can assume all you want, but no serious person processing numbers
would choose axes like that.

--
Antoon Pardon
Apr 20 '07 #18

P: n/a
Antoon Pardon schreef:
On 2007-04-19, Wayne Brehaut <wb******@mcsnet.cawrote:
>So the remark that " a steep learning curve means that the subject is
easily familiarized and that the learning period is short" is
completely incorrect on two points (i.e., all points that are
relevant): first, steep always implies much to learn in a relatively
short time (what else could the slope of a curve possibly mean
"mathematicallY" or logically?);

No it doesn't imply that at all. A learning curve doesn't show some
goal of a person who was given just so much time to familiarize himself
with some material. A learning curve shows the progres that is made
in familiarizing one self while studying. A steep curve means a
lot of actual learning in a short time.
>A learning curve is conventionally the graph of a function of
"quantity to be learned" vs. time,
No it doesn't. A learning curve is the graph that somehow quantifies
what is actually learned vs time.
Do you have any reference to back that up?

As I understand it, a learning curve plots the learning effort vs. the
progress made. A steep learning curve means you need to learn a lot in
order to make a little progress.

--
If I have been able to see further, it was only because I stood
on the shoulders of giants. -- Isaac Newton

Roel Schroeven
Apr 20 '07 #19

P: n/a
Antoon Pardon wrote:
>a) In English, "learning curve" is not restricted to a mathematical
plot--Webster's also defines it as "the course of progress made in
learning something". In that context, adding the adjective steep
("extremely or excessively high...STEEP implies such sharpness of
pitch that ascent or descent is very difficult") makes sense.

How much sense does it really make? Suppose we would talk about
an income curve. Would you not prefer a steep curve over a shalow
one? What about a productivity curve? It is all about the progress
made in something.
I don't think I have seen "steep learning curve" used in that sense
prior to reading your post. I have seen it being used as "what a steep
cliff to climb!" (i.e. would would have been much easier with a
"flatter" one). OTOH, I just went to an (Am.) English school my first
school year, and language is not one of my fields of interest. So I'll
just shut up and go away.
--
Kind regards,
Jan Danielsson
Apr 20 '07 #20

P: n/a
Antoon Pardon wrote:
On 2007-04-19, sj*******@yahoo.com <sj*******@yahoo.comwrote:
>On Apr 19, 6:54 am, Antoon Pardon <apar...@forel.vub.ac.bewrote:
>>I don't know how you come to the conclusion that it is a mathematical
absurdity but consider this: If you find that common usage propagates
something that is incorrect, should we just shrug it off or should we
attemp a correction?
a) In English, "learning curve" is not restricted to a mathematical
plot--Webster's also defines it as "the course of progress made in
learning something". In that context, adding the adjective steep
("extremely or excessively high...STEEP implies such sharpness of
pitch that ascent or descent is very difficult") makes sense.

How much sense does it really make? Suppose we would talk about
an income curve. Would you not prefer a steep curve over a shalow
one? What about a productivity curve? It is all about the progress
made in something.

So how much sense does it make that a steep curve in earnings and
productivity is good but a steep curve in learning is bad?
Just as much sense as that a motor car is great for driving around in
but bad for being run over by. Context is everything. Do *all* steep
curves have to be good or all bad? What the hell happened to common sense?
>Trying to apply a mathematical definition to an English-language
phrase is prone to incorrect outcomes.

b) The purpose of language is to communicate. In English, if a phrase
now means something in common usage, then that is (one of) its current
definition(s)--this is possibly different from some other languages
where there is an attempt to have an "officially sanctioned" set of
definitions and spellings that may differ from common usage. If you
find that everyone else means something when they say a phrase, you'd
best learn what they mean if you want to be speaking the same language
(and hence be able to communicate with them).

But the problem is that even if this would be only a way to communicate
in englishi, a lot of people get the wrong idea about real curves from
this idiom, as this thread shows. So even if you only want to communicate
one specific idea that comes accross as intended, you also propagate
a lot of nonsense with it.
Well, I have to bow to your expertise when it comes to propagating nonsense.

regards
Steve
--
Steve Holden +44 150 684 7255 +1 800 494 3119
Holden Web LLC/Ltd http://www.holdenweb.com
Skype: holdenweb http://del.icio.us/steve.holden
Recent Ramblings http://holdenweb.blogspot.com

Apr 20 '07 #21

P: n/a
On 2007-04-20, Roel Schroeven <rs****************@fastmail.fmwrote:
Antoon Pardon schreef:
>On 2007-04-19, Wayne Brehaut <wb******@mcsnet.cawrote:
>>So the remark that " a steep learning curve means that the subject is
easily familiarized and that the learning period is short" is
completely incorrect on two points (i.e., all points that are
relevant): first, steep always implies much to learn in a relatively
short time (what else could the slope of a curve possibly mean
"mathematicallY" or logically?);

No it doesn't imply that at all. A learning curve doesn't show some
goal of a person who was given just so much time to familiarize himself
with some material. A learning curve shows the progres that is made
in familiarizing one self while studying. A steep curve means a
lot of actual learning in a short time.
A learning curve is conventionally the graph of a function of
"quantity to be learned" vs. time,
No it doesn't. A learning curve is the graph that somehow quantifies
what is actually learned vs time.

Do you have any reference to back that up?
http://en.wikipedia.org/wiki/Experience_curve_effects

Where you will also learn that learning curves by what values
are generally plotted go downwards.

--
Antoon Pardon
Apr 20 '07 #22

P: n/a
On 2007-04-20, Steve Holden <st***@holdenweb.comwrote:
Antoon Pardon wrote:
>On 2007-04-19, sj*******@yahoo.com <sj*******@yahoo.comwrote:
>>On Apr 19, 6:54 am, Antoon Pardon <apar...@forel.vub.ac.bewrote:
I don't know how you come to the conclusion that it is a mathematical
absurdity but consider this: If you find that common usage propagates
something that is incorrect, should we just shrug it off or should we
attemp a correction?
a) In English, "learning curve" is not restricted to a mathematical
plot--Webster's also defines it as "the course of progress made in
learning something". In that context, adding the adjective steep
("extremely or excessively high...STEEP implies such sharpness of
pitch that ascent or descent is very difficult") makes sense.

How much sense does it really make? Suppose we would talk about
an income curve. Would you not prefer a steep curve over a shalow
one? What about a productivity curve? It is all about the progress
made in something.

So how much sense does it make that a steep curve in earnings and
productivity is good but a steep curve in learning is bad?
Just as much sense as that a motor car is great for driving around in
but bad for being run over by. Context is everything. Do *all* steep
curves have to be good or all bad? What the hell happened to common sense?
You are just grabbing for straws. Sure context is everything. But you
don't make a case that the context makes a difference here. Are you
suggesting progres in productivity is good but progres in learning is bad?

Just asserting how something can make a difference withouth arguing
how in the particular case it actucally makes a difference is just
a divertion tactic without real merrit.

--
Antoon Pardon
Apr 20 '07 #23

P: n/a
Nigel Rowe a écrit :
On Thu, 19 Apr 2007 19:11, Antoon Pardon wrote in comp.lang.python:
>On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:

<snip type="various irrelevances to my comment below" />
>>The learning curve is rather steep IMO, but worth it.
Just a throw in remark, that you may ignore if you wish, but a steep
learning curve means that the subject is easily familiarized and that
the learning period is short.

You seem to use it as if it is the opposite.

Who says the axes are labeled "familiarity" and "learning period"? I
just assume they are labeled (y-axis) "Effort" and (x-axis) "Knowledge"
(or "skill" or ....).

Which means that something with a 'steep learning curve' requires a lot
of effort to achieve a small amount of knowledge (or skill or ...).
Funny, I would have placed on the x axis the time, and on the y axis
"Knowledge". And Effort = lambda*time where lambda is the amount of
effort per minute you are able to produce. Thus I always found it weird
to call a steep learning curve something hard to learn.

Disclaimer: I have never made any study in that field, never read any
reports or anything like that. It just feels much more natural for me to
place the time on the x axis.
Apr 20 '07 #24

P: n/a
On 20 Apr, 09:21, Antoon Pardon <apar...@forel.vub.ac.bewrote:
>
Indeed I have no wish to bow before common usage.
Then nobody will understand you properly if you start referring to a
"steep learning curve" when in their terminology you actually mean a
"shallow learning curve". Certainly, this discussion has alerted me to
a level of ambiguity with the term that would dissuade me from using
it, but then it's a hand-waving kind of term, anyway, which would be
better replaced with a proper description of whatever effect is
supposed to be observable.

It seems to me that the original term isn't directly applicable to
most situations where it is applied in general usage. For example,
someone talking about the learning curve involved in riding a bicycle
is taking a term originally used to describe effects observed when
people carry out the same task repeatedly and applying it to an
activity which involves a number of different cooperating tasks or
processes.
I prefer to think about things and dare to speak out when they don't seem to make sense.

Just repeating common usage propagates a lot of nonsense.
Languages and their constituent parts change over time. Here's a
relevant article on the topic:

http://groups.google.com/group/alt.u...ce58f687589a6c

Paul

Apr 20 '07 #25

P: n/a
Antoon Pardon wrote:
On 2007-04-20, Steve Holden <st***@holdenweb.comwrote:
>Antoon Pardon wrote:
>>On 2007-04-19, sj*******@yahoo.com <sj*******@yahoo.comwrote:
On Apr 19, 6:54 am, Antoon Pardon <apar...@forel.vub.ac.bewrote:
I don't know how you come to the conclusion that it is a mathematical
absurdity but consider this: If you find that common usage propagates
something that is incorrect, should we just shrug it off or should we
attemp a correction?
a) In English, "learning curve" is not restricted to a mathematical
plot--Webster's also defines it as "the course of progress made in
learning something". In that context, adding the adjective steep
("extremely or excessively high...STEEP implies such sharpness of
pitch that ascent or descent is very difficult") makes sense.
How much sense does it really make? Suppose we would talk about
an income curve. Would you not prefer a steep curve over a shalow
one? What about a productivity curve? It is all about the progress
made in something.

So how much sense does it make that a steep curve in earnings and
productivity is good but a steep curve in learning is bad?
Just as much sense as that a motor car is great for driving around in
but bad for being run over by. Context is everything. Do *all* steep
curves have to be good or all bad? What the hell happened to common sense?

You are just grabbing for straws. Sure context is everything. But you
don't make a case that the context makes a difference here. Are you
suggesting progres in productivity is good but progres in learning is bad?
No, I'm suggesting that in the company of thousands of people, most of
whom agree that a "steep learning curve" means, in the face of all
logic, that something is difficult to learn, you stop banging your head
against the wall and trying to "prove" them "wrong" (presumably because
it's important to you to be "right").

As has been said already at least twice in this thread, language is
about communication. Human beings aren't always entirely rational no
matter how much we may individually strive for correctness, and
sometimes our only options are to either go with the flow or stand
valiantly, pissing into the wind.
Just asserting how something can make a difference withouth arguing
how in the particular case it actucally makes a difference is just
a divertion tactic without real merrit.
In the face of a notion that all steep curves determining "progress made
in something" must be good I stand with my mouth agape. I am aware that
common usage does not concur with academic rigor, but in this particular
instance I'm with the common herd.

regards
Steve
--
Steve Holden +44 150 684 7255 +1 800 494 3119
Holden Web LLC/Ltd http://www.holdenweb.com
Skype: holdenweb http://del.icio.us/steve.holden
Recent Ramblings http://holdenweb.blogspot.com

Apr 20 '07 #26

P: n/a
"Steve Holden" <s..e@holdenweb.comwrote:

Perhaps in Belgium they prefer climbing mountains over walking up and
down gentle hills?
Mountains ? Hills ? In Belgium ??

Its not called the battlefield of Europe for nothing...

- Hendrik

Apr 20 '07 #27

P: n/a
On 2007-04-20, Steve Holden <st***@holdenweb.comwrote:
Antoon Pardon wrote:
>On 2007-04-20, Steve Holden <st***@holdenweb.comwrote:
>>Antoon Pardon wrote:
On 2007-04-19, sj*******@yahoo.com <sj*******@yahoo.comwrote:
On Apr 19, 6:54 am, Antoon Pardon <apar...@forel.vub.ac.bewrote:
>I don't know how you come to the conclusion that it is a mathematical
>absurdity but consider this: If you find that common usage propagates
>something that is incorrect, should we just shrug it off or should we
>attemp a correction?
a) In English, "learning curve" is not restricted to a mathematical
plot--Webster's also defines it as "the course of progress made in
learning something". In that context, adding the adjective steep
("extremely or excessively high...STEEP implies such sharpness of
pitch that ascent or descent is very difficult") makes sense.
How much sense does it really make? Suppose we would talk about
an income curve. Would you not prefer a steep curve over a shalow
one? What about a productivity curve? It is all about the progress
made in something.

So how much sense does it make that a steep curve in earnings and
productivity is good but a steep curve in learning is bad?

Just as much sense as that a motor car is great for driving around in
but bad for being run over by. Context is everything. Do *all* steep
curves have to be good or all bad? What the hell happened to common sense?

You are just grabbing for straws. Sure context is everything. But you
don't make a case that the context makes a difference here. Are you
suggesting progres in productivity is good but progres in learning is bad?
No, I'm suggesting that in the company of thousands of people, most of
whom agree that a "steep learning curve" means, in the face of all
logic, that something is difficult to learn, you stop banging your head
against the wall and trying to "prove" them "wrong" (presumably because
it's important to you to be "right").
Thousands of people can be wrong. Now I don't particularly want
to prove them wrong. But if instead of ignoring the remark as
I suggested, they start trying to prove they are right, I will
point out where their thinking is wrong.
As has been said already at least twice in this thread, language is
about communication. Human beings aren't always entirely rational no
matter how much we may individually strive for correctness, and
sometimes our only options are to either go with the flow or stand
valiantly, pissing into the wind.
But if a wrong idea is circulating and nobody ever tries to correct it,
people will continue with the wrong idea. All I did was make a simple
remark, that as I suggested anyone could ignore, but that would allow
those willing to learn, to further investigate.

But what a terrible thing that seems to be.
>Just asserting how something can make a difference withouth arguing
how in the particular case it actucally makes a difference is just
a divertion tactic without real merrit.
In the face of a notion that all steep curves determining "progress made
in something" must be good I stand with my mouth agape. I am aware that
common usage does not concur with academic rigor, but in this particular
instance I'm with the common herd.
Well that notion is entirely yours. My notion was only that progres in
productivity, earnings and learning was good and thus that curves that
are to be prefered tend to be the same shape for those three subjects.

--
Antoon Pardon
Apr 20 '07 #28

P: n/a
Antoon Pardon schrieb:
On 2007-04-19, Steve Holden <st***@holdenweb.comwrote:
>Antoon Pardon wrote:
>>On 2007-04-19, Steve Holden <st***@holdenweb.comwrote:
Michael Bentley wrote:
On Apr 19, 2007, at 4:11 AM, Antoon Pardon wrote:
>
>On 2007-04-19, Michael Bentley <mi*****@jedimindworks.comwrote:
[...] The
>>learning curve is rather steep IMO, but worth it.
>Just a throw in remark, that you may ignore if you wish, but a steep
>learning curve means that the subject is easily familiarized and that
>the learning period is short.
>>
>You seem to use it as if it is the opposite.
Mathematical absurdities aside, it's the common usage -- but perhaps
you knew that.
>
>
Perhaps in Belgium they prefer climbing mountains over walking up and
down gentle hills? Or possibly they will simply pick any nit that is
carelessly left within range?
If it is just a nit, why don't you ignore my remark as I suggested?
Because I suffer from the quixotic urge to help stamp out obsessive
compulsive behavior on c.l.py? This is self-defeating, of course, since
it makes me appear obsessive compulsive in my own right ...
>>Now suppose I give you a graph that shows you how different people
are making progress. Would you prefer the rather flat curves instead
of the steep curves because the latter gives you the idea of someone
having to conquer huge obstacles or would you choose the steep curve
because they show you someone is getting results fast?
Suppose I should you a hill you have to climb? Would you rather don
mountain boots and crampons to climb 3,000 feet up a vertical cliff or
would you rather amble up, say, Ben Lomond with the other tourists?

So if you have the choice between a steep or a shalow income curve
you will prefer the shalow curve because a steep curve makes you
think about verticale clifs and such?

The analogy with a walk is just silly because curves are not like walks.
Nobody will say something like: I won't invest in that company because
it has a steep profit curve or the reverse: I'll invest in this company
because it has an easy looking downhill going profit curve.
Your whole argumentation bases on the fact that the result of the
learning process, and the success of it, has something to do with the
reached height - or y-axis-value - of your climb.

Which is nonsense. The goal is to go from A - ignorance - to B -
knowledge - which both lie on the X-Axis.

And you really argue that having to go 2 miles OVER THE GROUND on a
shallow slope is worse than walking 2 miles OVER GROUND with the mount
everest between you and your goal?

Diez
Apr 20 '07 #29

P: n/a
On 2007-04-20, Paul Boddie <pa**@boddie.org.ukwrote:
On 20 Apr, 09:21, Antoon Pardon <apar...@forel.vub.ac.bewrote:
>>
Indeed I have no wish to bow before common usage.

Then nobody will understand you properly if you start referring to a
"steep learning curve" when in their terminology you actually mean a
"shallow learning curve". Certainly, this discussion has alerted me to
a level of ambiguity with the term that would dissuade me from using
it, but then it's a hand-waving kind of term, anyway, which would be
better replaced with a proper description of whatever effect is
supposed to be observable.
Well that I made some people aware was all I intended. Personaly
I don't use the term either unless I have an actual curve to
show which I can use to explain how to interpret it.

--
Antoon Pardon
Apr 20 '07 #30

P: n/a
On 2007-04-20, Diez B. Roggisch <de***@nospam.web.dewrote:
>So if you have the choice between a steep or a shalow income curve
you will prefer the shalow curve because a steep curve makes you
think about verticale clifs and such?

The analogy with a walk is just silly because curves are not like walks.
Nobody will say something like: I won't invest in that company because
it has a steep profit curve or the reverse: I'll invest in this company
because it has an easy looking downhill going profit curve.

Your whole argumentation bases on the fact that the result of the
learning process, and the success of it, has something to do with the
reached height - or y-axis-value - of your climb.

Which is nonsense. The goal is to go from A - ignorance - to B -
knowledge - which both lie on the X-Axis.
Well if you want to do it that way, nobody can stop you, but people
in the habit of processing numbers usually put the time on the X-axis
like in time spend learning or exercising and put the other value
on the Y-axis.

That is because people prefer a curve going up and down while moving
to the right instead of going left and right while moving up.

--
Antoon Pardon

Apr 20 '07 #31

P: n/a
Hendrik van Rooyen schreef:
"Steve Holden" <s..e@holdenweb.comwrote:

>Perhaps in Belgium they prefer climbing mountains over walking up and
down gentle hills?

Mountains ? Hills ? In Belgium ??

Its not called the battlefield of Europe for nothing...
I'm not sure if this adds anything of interest (well actually I'm pretty
sure it doesn't), but our king Albert I was a fanatic mountain climber,
until he died from a fall in 1934.

--
If I have been able to see further, it was only because I stood
on the shoulders of giants. -- Isaac Newton

Roel Schroeven
Apr 20 '07 #32

P: n/a

On Apr 20, 2007, at 9:22 AM, Antoon Pardon wrote:
Well if you want to do it that way, nobody can stop you, but people
in the habit of processing numbers usually put the time on the X-axis
like in time spend learning or exercising and put the other value
on the Y-axis.

That is because people prefer a curve going up and down while moving
to the right instead of going left and right while moving up.
That depends all on what you are plotting. If you are after the
amount of
work it was to go from uneducated to educated then a shallow slope is
preferable (with amount of work on the y axis, and degree of educated
on the x axis). Wether a shallow or steep slope is preferable is all
dependent
on what one is actually measuring.

Cheers
Tommy
Apr 20 '07 #33

P: n/a
On 20 Apr, 15:22, Antoon Pardon <apar...@forel.vub.ac.bewrote:
On 2007-04-20, Diez B. Roggisch <d...@nospam.web.dewrote:
Which is nonsense. The goal is to go from A - ignorance - to B -
knowledge - which both lie on the X-Axis.

Well if you want to do it that way, nobody can stop you, but people
in the habit of processing numbers usually put the time on the X-axis
like in time spend learning or exercising and put the other value
on the Y-axis.
But time wasn't mentioned. You could have knowledge or accomplishment
on the X axis and effort or work on the Y axis. Subjects with more
material to learn could be said to have a "long learning curve"; an
example of such usage can be found here:

http://www.linuxplanet.com/linuxplanet/reviews/3207/5/

But if the nature of the material is not particularly challenging, you
could say that a "shallow learning curve" is involved: you don't need
to think very hard about the material. Conversely, a "steep learning
curve" in the popular sense suggests more effort being expended for a
given measure of material.

Paul

Apr 20 '07 #34

P: n/a
Antoon Pardon <ap*****@forel.vub.ac.bewrote:
>>Just asserting how something can make a difference withouth
arguing how in the particular case it actucally makes a
difference is just a divertion tactic without real merrit.
In the face of a notion that all steep curves determining
"progress made in something" must be good I stand with my mouth
agape. I am aware that common usage does not concur with
academic rigor, but in this particular instance I'm with the
common herd.

Well that notion is entirely yours. My notion was only that
progres in productivity, earnings and learning was good and thus
that curves that are to be prefered tend to be the same shape for
those three subjects.
If we are being pedantic about describing a curve that shows the
progress of a person in learning a topic, there is no arguing with
you, a steep curve describes fast uptake and is a good thing.

If we are being pedantic about what a learning curve describes, it
seems possible that it describes the rate of knowledge uptake
required to master a given topic, and that such a learning curve
could exclude people that were unable to take in knowledge at that
rate(for whatever reason) from mastering that topic, making it
reasonable to describe such a topic as both 'hard' and 'having a
steep learning curve'.
max

Apr 20 '07 #35

P: n/a
On 2007-04-20, Paul Boddie <pa**@boddie.org.ukwrote:
On 20 Apr, 15:22, Antoon Pardon <apar...@forel.vub.ac.bewrote:
>On 2007-04-20, Diez B. Roggisch <d...@nospam.web.dewrote:
Which is nonsense. The goal is to go from A - ignorance - to B -
knowledge - which both lie on the X-Axis.

Well if you want to do it that way, nobody can stop you, but people
in the habit of processing numbers usually put the time on the X-axis
like in time spend learning or exercising and put the other value
on the Y-axis.

But time wasn't mentioned.
Wel what is the second variable then?
You could have knowledge or accomplishment
on the X axis and effort or work on the Y axis.
What else is effort than the time you spent on it?

And yes you could do that, but in general it is not done because such an
organisation would make your curve no longer a function. Situations could
occur where more effort will result in less knowledge; where new material
seem to conflict with older material resulting in confusion. With an
arrangement of axes like you proposed that would result in an inverted
c like curve.

So you no longer have the familiar up and down movement but a movement
going left and right.

--
Antoon Pardon
Apr 20 '07 #36

P: n/a
On 2007-04-20, Max Erickson <ma*********@gmail.comwrote:
>
If we are being pedantic about describing a curve that shows the
progress of a person in learning a topic, there is no arguing with
you, a steep curve describes fast uptake and is a good thing.

If we are being pedantic about what a learning curve describes, it
seems possible that it describes the rate of knowledge uptake
required to master a given topic, and that such a learning curve
could exclude people that were unable to take in knowledge at that
rate(for whatever reason) from mastering that topic, making it
reasonable to describe such a topic as both 'hard' and 'having a
steep learning curve'.
I must confess I don't follow you here. A rate is a single number.
Now some second variable can be a function of this rate or vice
versa but I can't make out what this second variable is supposed
to be from your explanation.

--
Antoon Pardon
Apr 20 '07 #37

P: n/a
Antoon Pardon <ap*****@forel.vub.ac.bewrote:
On 2007-04-20, Max Erickson <ma*********@gmail.comwrote:
>>
If we are being pedantic about describing a curve that shows the
progress of a person in learning a topic, there is no arguing
with you, a steep curve describes fast uptake and is a good
thing.

If we are being pedantic about what a learning curve describes,
it seems possible that it describes the rate of knowledge uptake
required to master a given topic, and that such a learning curve
could exclude people that were unable to take in knowledge at
that rate(for whatever reason) from mastering that topic, making
it reasonable to describe such a topic as both 'hard' and
'having a steep learning curve'.

I must confess I don't follow you here. A rate is a single
number. Now some second variable can be a function of this rate
or vice versa but I can't make out what this second variable is
supposed to be from your explanation.
I'm stopping after this because it is offtopic noise, but take a
graph of position vs time for an object; the slope of that graph
happens to be related to the velocity of the object, so you can
'see' the velocity of the object even though the graph is of
position and time. The slope of the graph can be said to describe a
rate.

(and a graph that showed the movement of the world around that
object would be quite different, and similar lines on those
different graphs would thus elecit rather different descriptions,
which is the point, pretending that all graphs of learning curves
only describe what you assume they describe and then being pedantic
about what information can be inferred from the graphs isn't going
to get you anywhere, hence this thread)

My english is full of colloquialisms and idioms and I am not
interested in learning "Antoon Pardon's Dictionary of Exact Usage",
so I fear that further explanation will be fruitless.
max

Apr 20 '07 #38

P: n/a
On 20 Apr, 16:34, Antoon Pardon <apar...@forel.vub.ac.bewrote:
On 2007-04-20, Paul Boddie <p...@boddie.org.ukwrote:
You could have knowledge or accomplishment
on the X axis and effort or work on the Y axis.

What else is effort than the time you spent on it?
What's the difference between watching a television programme called
"Useless Celebrity Factoids" for half an hour and spending the same
amount of time studying for an exam involving useful information where
you might also need to show some level of understanding of the subject
matter?

If that's not comparing similar measures of information, what's the
difference between studying for an exam in a subject whose
prerequisites are familiar to you and studying for one in an
unfamiliar field, both for the same amount of time?

Paul

Apr 20 '07 #39

P: n/a
En Thu, 19 Apr 2007 17:33:19 -0300, sj*******@yahoo.com
<sj*******@yahoo.comescribió:
On Apr 19, 6:54 am, Antoon Pardon <apar...@forel.vub.ac.bewrote:
>I don't know how you come to the conclusion that it is a mathematical
absurdity but consider this: If you find that common usage propagates
something that is incorrect, should we just shrug it off or should we
attemp a correction?

a) In English, "learning curve" is not restricted to a mathematical
plot--Webster's also defines it as "the course of progress made in
learning something". In that context, adding the adjective steep
("extremely or excessively high...STEEP implies such sharpness of
pitch that ascent or descent is very difficult") makes sense.

Trying to apply a mathematical definition to an English-language
phrase is prone to incorrect outcomes.
I don't know if it's used in English, but my uncle says "open the light"
and "close the light". From an electrician point of view, that's wrong: to
turn the light on you have to close the circuit, and the light is off when
the circuit is open.
A biologyst won't aggree on the common usage of "crocodrile tears". Such
expressions should not be understood technically (I think they're known as
idioms).
As English is not my native language, I sometimes got puzzled by some
idioms. How much Python can be put in a nutshell? Almost nothing, so for
me, the famous book starts diminished from the title.
Or, I would not consider "sleepping tight" a good thing, I prefer big and
comfortable beds...

This is getting close to win the "longest off topic thread" award.

--
Gabriel Genellina
Apr 20 '07 #40

P: n/a
Dennis Lee Bieber <wl*****@ix.netcom.comwrites:
But is it a "wrong idea" if 999 people interpret the phrase one way,
and just 1 insists upon an interpretation that, while correct in a small
technical area, results in misunderstanding when speaking with the other
999?
You remind me of my grandpa: if all soldiers but one are marching with
the "wrong" foot ahead, who's wrong?

--
Jorge Godoy <jg****@gmail.com>
Apr 20 '07 #41

P: n/a
hg
Roel Schroeven wrote:
Hendrik van Rooyen schreef:
> "Steve Holden" <s..e@holdenweb.comwrote:

>>Perhaps in Belgium they prefer climbing mountains over walking up and
down gentle hills?

Mountains ? Hills ? In Belgium ??

Its not called the battlefield of Europe for nothing...

I'm not sure if this adds anything of interest (well actually I'm pretty
sure it doesn't), but our king Albert I was a fanatic mountain climber,
until he died from a fall in 1934.

--
If I have been able to see further, it was only because I stood
on the shoulders of giants. -- Isaac Newton

Roel Schroeven
You never know ... was it a 'steep curve' ?

hg

Apr 20 '07 #42

P: n/a
hg schreef:
Roel Schroeven wrote:
>Hendrik van Rooyen schreef:
>> "Steve Holden" <s..e@holdenweb.comwrote:
Perhaps in Belgium they prefer climbing mountains over walking up and
down gentle hills?
Mountains ? Hills ? In Belgium ??

Its not called the battlefield of Europe for nothing...
I'm not sure if this adds anything of interest (well actually I'm pretty
sure it doesn't), but our king Albert I was a fanatic mountain climber,
until he died from a fall in 1934.
You never know ... was it a 'steep curve' ?
To stay in the general style of this thread, that largely depends on how
you interpret that expression :-) I would say yes, but judge for
yourself; this is the rock he was climbing when he fell:
http://nl.wikipedia.org/wiki/Afbeeld...%C3%A5tche.jpg

It's completely true that Belgium is a pretty flat country, but there
are some regions featuring a somewhat more pronounced differences in height.

--
If I have been able to see further, it was only because I stood
on the shoulders of giants. -- Isaac Newton

Roel Schroeven
Apr 20 '07 #43

P: n/a
"Roel Schroeven" <rs..v_nospam_ml@f..l.fmwrote:
Hendrik van Rooyen schreef:
"Steve Holden" <s..e@holdenweb.comwrote:

Perhaps in Belgium they prefer climbing mountains over walking up and
down gentle hills?
Mountains ? Hills ? In Belgium ??

Its not called the battlefield of Europe for nothing...

I'm not sure if this adds anything of interest (well actually I'm pretty
sure it doesn't), but our king Albert I was a fanatic mountain climber,
until he died from a fall in 1934.
Thanks - I was not aware of that.
Adds a whole new dimension to the phrase:

"The Fall of a King"

What was he climbing when he fell, btw?

- Hendrik

Apr 21 '07 #44

P: n/a
Hendrik van Rooyen schreef:
"Roel Schroeven" <rs..v_nospam_ml@f..l.fmwrote:
>Hendrik van Rooyen schreef:
>> "Steve Holden" <s..e@holdenweb.comwrote:
Perhaps in Belgium they prefer climbing mountains over walking up and
down gentle hills?
Mountains ? Hills ? In Belgium ??

Its not called the battlefield of Europe for nothing...
I'm not sure if this adds anything of interest (well actually I'm pretty
sure it doesn't), but our king Albert I was a fanatic mountain climber,
until he died from a fall in 1934.

Thanks - I was not aware of that.
Adds a whole new dimension to the phrase:

"The Fall of a King"

What was he climbing when he fell, btw?
A rock in Marche-les-Dames, see the picture at
http://nl.wikipedia.org/wiki/Afbeeld...%C3%A5tche.jpg

That's in the Walloon region; Flanders is of course much more flat than
that.

--
If I have been able to see further, it was only because I stood
on the shoulders of giants. -- Isaac Newton

Roel Schroeven
Apr 21 '07 #45

P: n/a
Antoon Pardon schrieb:
On 2007-04-20, Diez B. Roggisch <de***@nospam.web.dewrote:
>>So if you have the choice between a steep or a shalow income curve
you will prefer the shalow curve because a steep curve makes you
think about verticale clifs and such?

The analogy with a walk is just silly because curves are not like walks.
Nobody will say something like: I won't invest in that company because
it has a steep profit curve or the reverse: I'll invest in this company
because it has an easy looking downhill going profit curve.
Your whole argumentation bases on the fact that the result of the
learning process, and the success of it, has something to do with the
reached height - or y-axis-value - of your climb.

Which is nonsense. The goal is to go from A - ignorance - to B -
knowledge - which both lie on the X-Axis.

Well if you want to do it that way, nobody can stop you, but people
in the habit of processing numbers usually put the time on the X-axis
like in time spend learning or exercising and put the other value
on the Y-axis.

You seem to live in a very limited world, where bezier-curves (note the
name...)
are parametrized over t, but rendered on the x/y-axis happily going
forth and back and whatnot.

If using knowledge as the x-axis and effort on the y-axis, the figure of
speech makes perfect sense.

That is because people prefer a curve going up and down while moving
to the right instead of going left and right while moving up.
Which is obviously something people don't want to do in this context,
because "going down" doesn't make too much sense here, doesn't it? Or do
you want to cram the process of unlearning in the little figure of
speech as well?
But even a perfectly sense-making explanation can be found, I doubt that
you will ever acknowledge that you did make a mistake on this one - as
you always (or better never) do...
Apr 21 '07 #46

P: n/a
Kevin Walzer wrote:
From the introduction to PyObjC, the Python-Objective-C bridge on Mac
OS X:

"As described in Objective-C for PyObjC users the creation of
Objective-C objects is a two-stage process. To initialize objects, first
call a class method to allocate the memory (typically alloc), and then
call an initializer (typically starts with init). Some classes have
class methods which perform this behind the scenes, especially classes
that create cached, immutable, or singleton instances."

An example:

myObject = NSObject.alloc().init()

I know Tkinter doesn't require any manual memory allocation of this
sort. Does wxPython, PyQt, PyGtk require anything like this when
creating objects?

Thanks to all for an illuminating thread on the mathematical
implications of "learning curve" and other aspects. This thread has
wandered pretty far from my original question (above) but I got at least
one useful answer, so I am grateful.

--
Kevin Walzer
Code by Kevin
http://www.codebykevin.com
Apr 21 '07 #47

P: n/a
Kevin Walzer a écrit :
(snip)
Thanks to all for an illuminating thread on the mathematical
implications of "learning curve" and other aspects. This thread has
wandered pretty far from my original question (above)
Noticed this too ?-)
Apr 21 '07 #48

P: n/a
Kevin Walzer a écrit :
From the introduction to PyObjC, the Python-Objective-C bridge on Mac
OS X:

"As described in Objective-C for PyObjC users the creation of
Objective-C objects is a two-stage process. To initialize objects, first
call a class method to allocate the memory (typically alloc), and then
call an initializer (typically starts with init). Some classes have
class methods which perform this behind the scenes, especially classes
that create cached, immutable, or singleton instances."

An example:

myObject = NSObject.alloc().init()

I know Tkinter doesn't require any manual memory allocation of this
sort. Does wxPython, PyQt, PyGtk require anything like this when
creating objects?
PyObjC is not a GUI toolkit, it's a bridge between Python and
Objective-C (a smalltalk-inspired OO superset of ansi C).

And FWIW, under the hood, Python also uses this 2-stages
instanciation/initialisation scheme (methods __new__ and __init__), even
if it doesn't requires you to call them both explicitly.
Apr 21 '07 #49

P: n/a
Antoon Pardon schrieb:
>Who says the axes are labeled "familiarity" and "learning period"? I
just assume they are labeled (y-axis) "Effort" and (x-axis) "Knowledge"
(or "skill" or ....).

You can assume all you want, but no serious person processing numbers
would choose axes like that.
The vast majority of world population is not into "processing numbers",
so why should they care?

--
René
Apr 22 '07 #50

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