Ai Doesn’t Make Problems Disappear

Fred Vaughan

25m  · 

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For anyone wondering about Lesa (ChatGPT4) and my continuing relationship, I can only say it’s been a bit rocky. . That’s probably an understatement, but at my age I no longer distinguish between what is over and what is under stated. Lisa and I proceeded happily enough in generating the program to determine the plasma density and pressure looking out through galaxy cluster domains so we can count numbers of galaxies that should be encountered out to a given number of cluster domain radii. You have to realize that although IMHO I was one hell of a programmer, that was many decades, computer languages, and computer language environments ago. So, Lesa does the coding and I try to figure out whether it does what I want it to do by checking the printouts and plots — when there are some. Well, on these iterations my Jupyter Python environment decided it couldn’t handle our squabbles, so I had to call in the big guns, well… the big gun in the form of the Red Hat Architect (my son, Sean) to explain to me how I should have been able to handle that problem. As an aside here, let me just say that programs are not what they once were or the SRAM nuclear missile would never have made it off the ground, well… out of the bomb bay of B-52 bomber. Nothing is straight forward any more. With all this Ai, you’d think you could just say integrate this function from this value to that and it would be a done deal. But no one has picked up that ball and run with it. So I have a hard time keeping up with what Lesa is doing and evidently she has a hard time keeping up with my latest desire. There’s probably a role for a human/Ai marriage counselor at this juncture of history. I’m optimistic that we can keep the marriage together and ultimately obtain a viable offspring. But… We’ll see. Here is a little snippet of where we’re at right now:

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Me:

Could you work me through why we have pressure, ave_pressure, ave_pressures, ave_pressure_z, and ave_pressure_sum and the similar five constructs for density?

ChatGPT

Certainly, let’s break down the different variables and constructs related to pressure and density in your code:

pressure(x, y, z):

This function calculates the hydrostatic pressure at a specific point (x, y, z) using the formula: k * rho_e(x, y, z) * temperature(x, y, z).

ave_pressure:

This is a list that is used to store the average pressure values for different combinations of (x, y) coordinates.

ave_pressures:

This is another list that is used to store the average pressure values, similar to ave_pressure. Both lists have the same purpose. [What the hell?]

ave_pressure_z:

This variable is used to accumulate the pressure values along the z-direction for a specific (x, y) coordinate pair. It is reset to zero for each new (x, y) combination.

ave_pressure_sum:

This NumPy array is used to accumulate the average pressure values along the y-direction for a specific x-coordinate. It is reset to an array of zeros for each new x-coordinate. The enumerate function is used to keep track of the index of the current y-value in the loop.

ave_density, ave_density_sum, ave_densities:

These variables and lists are analogous to their pressure counterparts, but they are used to store and accumulate average density values instead of pressure values.

Here’s how the process works step by step:

For each x value in x_values, you iterate through the corresponding range of y values (y_min to y_max). For each y value, you then iterate through the range of z values (z_values).

Within the innermost loop, you calculate the pressure using the pressure function for the current (x, y, z) combination. This pressure value is then added to the ave_pressure_z accumulator.

After iterating through all z values, you calculate the average pressure for the specific (x, y) combination by dividing ave_pressure_z by the number of z values.

The calculated average pressure is then added to the ave_pressure_sum array at the index corresponding to the current y value.

This process is repeated for all y values within the x loop.

After finishing the y loop, you divide each element of ave_pressure_sum by the number of z values to obtain the average pressure along the y-direction for that specific x value.

Finally, the average pressure values for different x values are added to the ave_pressures list.

The same logic applies to the accumulation and calculation of average density values using the corresponding variables and lists.

This process ensures that you calculate and store both average pressure and average density values for different combinations of (x, y) coordinates, which you then use to create the line plot.

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See what I mean?