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Annoying creationists

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Annoying Creationists

The image for the hyperbolic paraboloid looks like this:
180px-HyperbolicParaboloid.png
 
Kleinman said:
Well this is a little change of pace. No evolutionists have responded this weekend. Have I bored you?
Belz… said:
No, it's just that watching paint dry is a more enjoyable experience.
There must be a lot of people who enjoy watching paint dry since there were 500 views of this thread since I last posted.

Hey Belz, were you one of the kids in math class who whined “how does all this stuff relate to reality”? Well, I’m going to show you how all this abstract mathematics relates to the reality of the mutation and selection sorting/optimization process.
 
There must be a lot of people who enjoy watching paint dry since there were 500 views of this thread since I last posted.

Hey Belz, were you one of the kids in math class who whined “how does all this stuff relate to reality”? Well, I’m going to show you how all this abstract mathematics relates to the reality of the mutation and selection sorting/optimization process.
:jaw-dropp:shocked::gasp::eye-poppi:crowded::eek::drool::rolleyes:
 
There must be a lot of people who enjoy watching paint dry since there were 500 views of this thread since I last posted.

View <> enjoyment.

Hey Belz, were you one of the kids in math class who whined “how does all this stuff relate to reality”?

No, because I already knew that mathematics was an abstract language, nothing else.

Well, I’m going to show you how all this abstract mathematics relates to the reality of the mutation and selection sorting/optimization process.

Somehow, I expect you won't.
 
Annoying Creationists

Kleinman said:
There must be a lot of people who enjoy watching paint dry since there were 500 views of this thread since I last posted.
Belz… said:
View <> enjoyment.
Especially if you are a legal beagle who believes in the theory of evolution.
Kleinman said:
Hey Belz, were you one of the kids in math class who whined “how does all this stuff relate to reality”?
Belz… said:
No, because I already knew that mathematics was an abstract language, nothing else.
It’s the abstract language of science, something which evolutionists need many lessons.
Kleinman said:
Well, I’m going to show you how all this abstract mathematics relates to the reality of the mutation and selection sorting/optimization process.
Belz… said:
Somehow, I expect you won't.
Prepare yourself for unmet expectations unless your expectation is that you won’t understand this abstract mathematics relates to reality. You evolutionists only have a superficial training in mathematics, let’s see if we can bring you up to speed on the mathematics of the mutation and selection sorting/optimization process.
 
Prepare yourself for unmet expectations unless your expectation is that you won’t understand this abstract mathematics relates to reality. You evolutionists only have a superficial training in mathematics, let’s see if we can bring you up to speed on the mathematics of the mutation and selection sorting/optimization process.

I have a feeling I'll be preparing for a long, long time.
 
Annoying Creationists

Kleinman said:
Prepare yourself for unmet expectations unless your expectation is that you won’t understand this abstract mathematics relates to reality. You evolutionists only have a superficial training in mathematics, let’s see if we can bring you up to speed on the mathematics of the mutation and selection sorting/optimization process.
Belz… said:
I have a feeling I'll be preparing for a long, long time.
It won’t be that long; it surely won’t be eternity. Did you understand what I said about analytic geometry and functionals above?
 
Annoying Creationists

So we have the functional expression:

F(n,G,g,mr,nsp) = gfc

Where,

n = population size
G = genome length
g = number of sites
mr = mutation rate
nsp = number of selection pressures
gfc = generations for convergence.

We have no explicit algebraic expression in which to plug in values in order to map out this functional surface as we have with the hyperbolic paraboloid equation or other explicitly defined functions such as trigonometric and logarithmic functions. In fact, this situation is much more complex because we are working in six dimensions with the above functional equation and only three dimensions for the hyperbolic paraboloid function. The only thing we know about this function is that the generations for convergence is dependent on population size, genome length, gamma, mutation rate and number of selection pressures.

There are two ways to obtain data points necessary to map out the defined by the functional equation F(n,G,g,mr,nsp) = gfc. One way to try to attempt to construct this surface would be experimentally and the other way is to use simulations like Dr Schneider’s computer model to generate points on this surface. The former method is extremely arduous, costly and slow while the latter can much more quickly give data to generate the function surface.

When doing such a study, I suggest you be systematic and study the behavior of one parameter at a time. This is done by holding 4 of the 5 independent variables (n, G, g, mr and nsp are the independent variables) to a fixed value and compute the effect on the dependent variable (gfc, the generations for convergence) from the variation of the remaining independent variable. What you obtain are sets of points on the 6-dimensional functional surface which are equivalent to views of the hyperbolic paraboloid when you take cuts along the axis. This is like taking a mathematical CT scan of the 6-dimensionsal surface which enables you to start picturing how the surface appears.

Tomorrow, I’ll walk you through the generation of some tabular data (which could be plotted graphically but I’ll leave that to you) which describes this 6-dimensional surface using Dr Schneider’s ev computer simulation.
 
Tomorrow, I’ll walk you through the generation of some tabular data (which could be plotted graphically but I’ll leave that to you) which describes this 6-dimensional surface using Dr Schneider’s ev computer simulation.

I am sure your "walk through" will include the few sets of parameters you repeat over and over.

I am sure it will also conveniently not include all the rest of the parameter combinations that show how much of a liar you are.

I am sure you will tell us "if you want to see what happens when you use those parameters, then try it yourself, I have no time for such nonsense."

Finally, I am absolutely sure that when people do try it themselves, you will accuse them of being mathematically incompetent (as if the mere act of plugging in parameters on a Java applet, exactly like you told us, could be an indicator of such a thing).
 
Although I took this thread off of my regular updates, I did check and based on what I've just seen, here's a couple thoughts that should and could be easily dispelled by a resoundingly truthful-seeming mathematical explanation of something.

As I recall, dimensions are easily visualized up to about 3. Three axes, xyz, can be understood as up/down, back/forward, and right/left. By throwing an object straight up on a moving train, we introduce the 4th, which is time. The object appears to go up and down, but if we put it "in time" (view it from beside the train track) it then describes a curve where its position is described as something like "xyz at time T" and then "xyz at time T plus one millisecond" and the overall impression is a curve. Imagine that this moment-by-moment structure is done by many things on many parallel trains, at one moment, and you now get what Fourier was trying to think about in the 1700s. Can we capture complex periodic behavior in equations? Blasphemous and odd thought, that, but he was right. We can model acoustical phenomena in just the ways he imagined.

So I'm not at all put off by the idea that complex systems can be modeled with complex mathematics. The calculus allows us to even predict higher-order things, like "rates of change" (slope of curve) and relative maxima and minima.

You fill your tub of 30 gallons for a bath at 2 gallons per hour and the plug drains it at 1 gallon per hour, the hot water is 70 degrees C and you can account for turbulence in the water. Thermal loss is say anything, 5 degrees per hour. What is the temperature of the water in the bath after 7 hours? Has it overflowed? Is it too cold? Will you burn yourself? Now let's make an equation for all the bathtubs in the town.

OK, I admit I made this up but a decent model would give us a good equation for it to be, shall I say, "figure-out-able". And this doesn't bother me in the least.

I'm a simple non-mathematician. Without one accounting for Time (t) in terms of whether time is allowed to be approaching infinity (a limit) it seems like the elegances of calculus are not being approached.

Thanks for listening, I had to get that off my chest.
 
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Annoying Creationists

Kleinman said:
Tomorrow, I’ll walk you through the generation of some tabular data (which could be plotted graphically but I’ll leave that to you) which describes this 6-dimensional surface using Dr Schneider’s ev computer simulation.
rocketdodger said:
I am sure your "walk through" will include the few sets of parameters you repeat over and over.
I’ve already asked what parameters you want to include. Include any parameters you want and produce the data that you think will support your irrational and illogical theory. What Dr Schneider’s model shows is that the more complex the selection conditions become the much, much slower the mutation and selection sorting/optimization process becomes. Now rocketdodger, if you think that you can find a set of parameters that will contradict this, produce the data. In the mean time I’ll show those who are interested how to analyze Dr Schneider’s model and why it shows the theory of evolution to be mathematically impossible.
BPScooter said:
As I recall, dimensions are easily visualized up to about 3. Three axes, xyz, can be understood as up/down, back/forward, and right/left. By throwing an object straight up on a moving train, we introduce the 4th, which is time. The object appears to go up and down, but if we put it "in time" (view it from beside the train track) it then describes a curve where its position is described as something like "xyz at time T" and then "xyz at time T plus one millisecond" and the overall impression is a curve. Imagine that this moment-by-moment structure is done by many things on many parallel trains, at one moment, and you now get what Fourier was trying to think about in the 1700s. Can we capture complex periodic behavior in equations? Blasphemous and odd thought, that, but he was right. We can model acoustical phenomena in just the ways he imagined.
It isn’t really that difficult to visualize systems with more than 3 or 4 dimensions, it just takes a little practice. Visualizing higher dimensional system simply requires multiple 2 dimensional images (or tabular data) to get an idea what these higher dimensional systems look like. You can think of it this way, a three dimensional object requires 3 2-dimensional blue prints to completely visualize the three dimensional object. A shape in a 4-dimensional space requires 4 3-dimensional projections to completely visualize the four dimensional shape and so on. Each of those three dimensional images can be described by a series of 2-dimensional images. You can think of it this way, the hyperbolic paraboloid can be visualized by looking at 2-dimensional projections (slices) done along each axis. Cuts along one axis looks like parabolas opening up, along another axis the slices look like parabolas opening down and along the third axis, the cuts look like lines or hyperbolas. You can think of this as views taken by a multidimensional CT or MRI scan.

So let’s get to how you describe the shape of the 6-dimensional surface generated by Dr Schneider’s computer simulation. We all know how impatient Belz is. This 6-dimensional surface is defined by the functional equation:

F(n,G,g,mr,nsp) = gfc

Where,

n = population size
G = genome length
g = number of sites
mr = mutation rate
nsp = number of selection pressures
gfc = generations for convergence.

We will generate the data points using Dr Schneider’s ev computer simulation of random point mutations and natural selection. You can access the online version of this computer simulation (written by James Randi Educational Forum moderator Paul C. Anagnostopoulos) at http://www.ccrnp.ncifcrf.gov/~toms/paper/ev/ . On this web page there is a hot spot that looks like this:
Click Here to Start the Evj Model

Note that you must have your browser Java enabled. If you don’t have Java for your browser, you can download the software free at http://www.java.com/en/ .

I will now assume you have been able to bring up the start-up screen for ev. Here is a brief description of this screen. At the top of the screen it says “Evj 2.37 Evolution of DNA binding sites, Java version”. Directly below this are four buttons, Restart, New, Help and about. Restart starts the model from the beginning. New brings up a window which allows the user to set parameters for the model at other values. Help is not implemented yet but you can let the mouse point linger over fields and get descriptions of their properties. About gives general information about the program. Below these buttons on the left are several user definable options and buttons. The Pause/Run button starts and stops the computation. The Step button allows the user to step through the computation one generation at the time. The speed spinner allows the user to set the rate at which the computer does the computation. I set this to the maximum value of 21 usually (this control does not affect the mathematical results obtained). Generation displays the number of generations computed. Cycles to run allow the user to set the maximum number of generations to be computed. To the right of this area is a display of the parameters used in the particular case being computed and a check box which tells the model whether to do selection or not. To the right of this area is some pretty graphics and to the right of this area is more display information and some check boxes which allow the user to determine when the program should stop executing. These check boxes include Pause on perfect creature, Pause on Rseq ≥ Rfreq and Pause on both. There is also a spin entry field which allows the user to change the rate at which the screen updates data. I tend to set this to a large value since it does not affect the computation and lots of screen updates slow the execution of the model. The bottom of the screen contains lots of pretty graphics.

If you left click on the New button you will see a window which allows you to set parameters in the model. In the left upper you will see a spin field that lets you set population, below that is Potential sites (this is G, the genome length), Binding sites (this is g, the number of binding sites), in the lower left are fields which allow you to set the binding site width and the weight width (the size of the array which determines if a selection condition is met) and a Placement field. In the upper right are fields for setting the mutation rate. One field allows the user to set the mutation rate per genome and the other field allow you to set the mutation rate per number of bases. Below these controls are check boxes that allow the user to stop execution for the two convergence conditions, perform selection and so on. The bottom two fields allow the user to set the maximum number of generations for the program to compute and to set the seed value for the random number generator. Below these fields are a row of buttons. The two important buttons are the OK button and the Advanced>> button. The OK button accepts the input parameters and returns the user to the start-up screen so you can run the computation. I will discuss the Advanced>> button later.

In order to get you started on running ev, go to the startup screen, without changing anything on the screen other than click the Pause on perfect creature check box and then click the Run button. You should see the colors and numbers on the screen change and the number of generations show 662 and the progress bar should be red and the words “perfect creature” should show in the progress bar.

Now click the New button and on the parameter screen, under mutation parameters, change “1” mutation(s) per genome to “2” and then click the OK button. Again click the Run button. In this case you should get 572 generations to evolve the “perfect creature”.

If you continue this process for 3 and 4 mutations per genome you will obtain a table of data which show for G=256, population=64, g=16, nsp=3 like this:
mr/gfc to perfect creature
1|662
2|572
3|12890
4|>1,000,000 did not converge

If you are so inclined to plot this data, it might appear paraboloid.

This data give our first glimpse at what the 6-dimensional surface looks like that is defined by Dr Schneider’s computer simulation of random point mutations and natural selection. What do you think will happen when we change the G value to a new value and then again vary the mutation rate?
 
I’ve already asked what parameters you want to include. Include any parameters you want and produce the data that you think will support your irrational and illogical theory. What Dr Schneider’s model shows is that the more complex the selection conditions become the much, much slower the mutation and selection sorting/optimization process becomes. Now rocketdodger, if you think that you can find a set of parameters that will contradict this, produce the data. In the mean time I’ll show those who are interested how to analyze Dr Schneider’s model and why it shows the theory of evolution to be mathematically impossible. (clip)
Fascinating. Do go on, won't you?
 
Annoying Creationists

Kleinman said:
I’ve already asked what parameters you want to include. Include any parameters you want and produce the data that you think will support your irrational and illogical theory. What Dr Schneider’s model shows is that the more complex the selection conditions become the much, much slower the mutation and selection sorting/optimization process becomes. Now rocketdodger, if you think that you can find a set of parameters that will contradict this, produce the data. In the mean time I’ll show those who are interested how to analyze Dr Schneider’s model and why it shows the theory of evolution to be mathematically impossible. (clip)
kjkent1 said:
Fascinating. Do go on, won't you?
Of course I will, just for you, well, you and Dr Schneider and Paul, I think their work deserves to be recognized and understood. Aren’t you going to tell us what you think will happen when we change the G value to a new value and then again vary the mutation rate?
 
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Annoying Creationists

Kleinman said:
I’ve already asked what parameters you want to include. Include any parameters you want and produce the data that you think will support your irrational and illogical theory. What Dr Schneider’s model shows is that the more complex the selection conditions become the much, much slower the mutation and selection sorting/optimization process becomes. Now rocketdodger, if you think that you can find a set of parameters that will contradict this, produce the data. In the mean time I’ll show those who are interested how to analyze Dr Schneider’s model and why it shows the theory of evolution to be mathematically impossible.
rocketdodger said:
I already did, you blind, stupid, ignorant, lying, fraudulent fool of a man. In fact, multiple people asked you to respond to my "data," which you of course are outright ignoring because it shows you to be plainly wrong.
Rocket who fizzles, is this the data you want me to respond to?
rocketdodger said:
I found a combination of parameters last night that led to over 100 pressures being faster than a single one, but I forgot what it was
frown.gif
Sorry, I thought I responded to this. Let me respond again.
doglaugh.gif

rocketdodger said:
In case you missed the post, here:
rocketdodger quoting himself said:
What is Rfreq and Rseq?
You missed this post rocket that travels slower than a speeding snail: http://www.internationalskeptics.com/forums/showpost.php?p=3323249&postcount=7732
Kleinman said:
Of course I will, just for you, well, you and Dr Schneider and Paul, I think their work deserves to be recognized and understood. Aren’t you going to tell us what you think will happen when we change the G value to a new value and then again vary the mutation rate?
Kleinman said:
rocketdodger said:
My guess is that the graph will shift to the right, I.E. the "optimal" mutation rate will increase.
Here’s the data for G=512, all other parameters the same for the G=256 base case the same, G=512, population=64, g=16, nsp=3 like this:
mr/gfc to perfect creature
1|2412
2|1251
3|973
4|13251
5|22790
6|>1,000,000 did not converge

Care to hazard a guess what the results will show for G=1024?
 
Annoying Creationists

I guess rocketdodger did not want to hazard a guess for the G=1024 series. For G=1024, population=64, g=16, nsp=3 like this:
mr/gfc to perfect creature
1|18030
2|9701
3|4679
4|2991
5|1299
6|1979
7|3782
8|7254
9|16243
10|>1,000,000 did not converge

These series which investigate the mutation rate all show a paraboloid appearance. Rocketdodger is the graph shifting to the right? I’ll post the data for G=2048 tomorrow and will see if rocketdodger’s guess is correct.
 
Of course I will, just for you, well, you and Dr Schneider and Paul, I think their work deserves to be recognized and understood. Aren’t you going to tell us what you think will happen when we change the G value to a new value and then again vary the mutation rate?
Nope. I'm rather more interested in the behavior science experiment currently underway. It appears that failing to maintain combination selective pressure on the kleinman virus, even for one day, causes the kleinman virus to spread quickly to other forum threads.

Anyway, don't let me interrupt. Keep on telling us how evolution doesn't work. We're all a twitter!
 
Annoying Creationists

Kleinman said:
Of course I will, just for you, well, you and Dr Schneider and Paul, I think their work deserves to be recognized and understood. Aren’t you going to tell us what you think will happen when we change the G value to a new value and then again vary the mutation rate?
kjkent1 said:
Nope. I'm rather more interested in the behavior science experiment currently underway. It appears that failing to maintain combination selective pressure on the kleinman virus, even for one day, causes the kleinman virus to spread quickly to other forum threads.
The only problem you have is that you don’t have any selection pressures. For example, I just won my malpractice case that you so much enjoyed trying to discredit me with. It only took 6 years to win the case. Now you watch the web carefully because the Superior Court only posts their decisions for a week or so.
kjkent1 said:
Anyway, don't let me interrupt. Keep on telling us how evolution doesn't work. We're all a twitter!
I do enjoy making evolutionists twitter.
 
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