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ID Date Author Subjectdown
  20   Wed Nov 20 00:40:49 2019 Julie RollaWeek 11/19/19 Update

Attendance for today's session: Cade, Julie, Alex M, Mitchell, Scott. 

 

Tasks/to-do list:

  1. ​Get loop to run up to the fitness function.
    • Right now we have the bash script setup to run AraSim by submitting them as parallel jobs. Today Cade added the "wait" function within the job in order to make sure the loop doesn't continue to the next step before the Arasim data is ready. Cade will give us an update on Thursday letting us know whether or not this completed or gave an error. 
  2. Fix error at fitness function. 
    • Currently, the loop stops at the fitness function calculation, and aborts (program fitnessFunction_ARA.cpp). We are unsure of why at the moment. Here are the things we are looking into. 
      • Run this outside of the loop-- ie compile the fitnessFunction_ARA.cpp (g++ -std=c++11 fitnessFunction_ARA.cpp -o fitnessFunction.exe), and run the executable(./fitnessFunction.exe). What happens?
        • Julie and Alex did this. It gave a segmentation fault. We need to look into this further. 
        • We double-checked that this .exe was properly created from compiling, and it was.
      • Double-check our AraSim output by checking:
        • Format
        • File type
      • Is there an error past the fitness function, and it's killing the loop after this runs?
        • Is his output not properly going into the gen alg?
        • Are the output files properly:
          • Filled
          • Formatted
          • Put in the right place
      • Look at how it's calculating the fitness score.

Since it seems like Alex and I may have found a problem at our first "test", this could be the issue. We will investigate it further. If (1) Cade's "wait" function works, and (2) we can fix this issue with the loop stopping at the fitness score calculation, ideally this means that the loop is then running. 

 

Today we also found that it is better to run on the terminal through an interactive job than a virtual desktop. This is MUCH faster -- ie we don't have to wait nearly as long as we do to get a node via a virtual desktop. This means that everyone with a PC needs to either (1) work out their issues with X11 forwarding crashing (Mitchell succeeded at this today by making sure Xquartz was set up to work via ssh to Pitzer in the settings), or (2) dual boot Linux. It seems that Mac users are not having issues, but that some of the Windows users are having their OS completely crash when XF GUI tries to forward. Users can test whether or not their X11 forwarding is working by doing the following:

  1.  Logging onto Pitzer
  2. Typing "module load xfdtd"
  3. Then typing "xfdtd"

This should successfully open the GUI for XF. If it crashes, users may have to do one of the things I mentioned above. Once we do succeed at having this setup, you can start an interactive job via the command: 

qsub -I -X -l walltime=1:00:00 -l nodes=1:ppn=10

You then have to wait until the node is free. This has taken about 1/3 of the time to get than when requesting a virtual desktop. Note that, however, we may need a higher ppn (maybe something like 40). This is not totally clear yet. 

  19   Fri Nov 15 09:59:27 2019 Julie RollaWeek 11/15/19 Update

Attendance for today's session: Cade, Julie, Alex M, Mitchell, Scott. 

 

Tasks worked on:

  • Continue to fix continuity of loop: Cade and Julie worked on fixing the following errors:
    1. In section D of the loop, it currently
      • Moves the output from the python conversion to $AraSimExec directory. 
      • Renames it as a .txt file (note the $i is renaming each in line with $NPOP). 

for i in `seq 1 $NPOP`

do

      mv evol_antenna_model_$i.dat $AraSimExec

done

for i in `seq 1 $NPOP`

do

      cp evol_antenna_model_$i.dat a_$i.txt

done

However, this wasn't working and it was only properly renaming individual 1. To check this,

  • We confirmed it is properly iterating the first loop by using the "echo" command. The second loop was not properly iterating, however.
  • We were able to fix it by combining these steps. This was confirmed to have worked. 

for i in `seq 1 $NPOP`

do

      mv evol_antenna_model_$i.dat $AraSimExec/a_$i.txt

done

              2. We got this iteration $i to work in the job script -- ie as an input file variable. The loop now successfully submits AraSim as a job with the proper input files. 

 

  • Clean bash script
    • Mitchell and Alex M worked again today on turning every function possible into functions (and putting them in their own .sh scripts that are being called by XF_Loop.sh). 
      • The loop runs the first generation "manually" -- ie each step was spelled out, and nothing is put into a loop. The second+ generations then run as a loop. This is because we need to initialize the first XF run -- which then has no problems in the later iterations.
        • Alex M. and Mitchell are now turning each section A-F into individual functions and put into their own .sh scripts. Thus section A would just be calling another .sh script. In gen 2+ we then loop over these SectionA.sh through SectionF.sh functions. All of these just got completed. He just needs to add the change Julie and Cade made today, and clean some things up. 
          • For example, he has an "if else" statement that tells it whether or not it's the first (XF initializes) generation, or in generation 2+. Cade has a few changes he would like Alex to make to clean up this part of the run. 
      • Idea: The loop used to run the first generation "manually" -- ie each step was spelled out, and nothing was put into a loop. The second+ generations then ran as a loop. Since we were able to get XF to import the xmacro scripts automatically -- as well as save the project with the correct name (matching the expected name initialize in the bash script)-- they've gotten rid of that first "manual" iteration, and are now fully running all generations as a loop. We haven't tested whether or not we can make this change yet, but it is worth looking into now that some changes have been successfully made with XF. 

 

Quick note from Julie:

I tried to run from the terminal once Cade left. I get the following output/error that we should make sure isn't happening for other users (since most of this is a permissions issue that I thought we fixed. I can look into the other errors and see if anyone else gets them). For whatever reason, Cade is not having the same output errors; he is able to run the same copy just fine. 

 

Roulette algorithm initialized.

./XF_Loop.sh: line 136: output.xmacro: Permission denied

./XF_Loop.sh: line 137: output.xmacro: Permission denied

./XF_Loop.sh: line 138: output.xmacro: Permission denied

./XF_Loop.sh: line 139: output.xmacro: Permission denied

./XF_Loop.sh: line 140: output.xmacro: Permission denied

./XF_Loop.sh: line 146: simulation_PEC.xmacro: Permission denied

./XF_Loop.sh: line 147: simulation_PEC.xmacro: Permission denied

./XF_Loop.sh: line 149: simulation_PEC.xmacro: Permission denied

./XF_Loop.sh: line 158: simulation_PEC.xmacro: Permission denied

 

Opening XF user interface...

*** Please remember to save the project with the same name as RunName! ***

 

1. Import and run simulation_PEC.xmacro

2. Import and run output.xmacro

3. Close XF

Lmod has detected the following error:  The following module(s) are unknown: "xfdtd"

 

Please check the spelling or version number. Also try "module spider ..."

It is also possible your cache file is out-of-date; it may help to try:

  $ module --ignore-cache load "xfdtd"

Also make sure that all modulefiles written in TCL start with the string #%Module

./XF_Loop.sh: line 172: xfdtd: command not found

./XF_Loop.sh: line 177: cd: /fs/project/PAS0654/BiconeEvolutionOSC/BiconeEvolution/current_antenna_evo_build/XF_Loop/Evolutionary_Loop/Run_Outputs/Julie/Julie.xf/Simulations/000001/Run0001/: No such file or directory

./XF_Loop.sh: line 178: xfsolver: command not found

./XF_Loop.sh: line 177: cd: /fs/project/PAS0654/BiconeEvolutionOSC/BiconeEvolution/current_antenna_evo_build/XF_Loop/Evolutionary_Loop/Run_Outputs/Julie/Julie.xf/Simulations/000002/Run0001/: No such file or directory

./XF_Loop.sh: line 178: xfsolver: command not found

./XF_Loop.sh: line 183: xfdtd: command not found

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Resuming...

 

chmod: changing permissions of ‘/fs/project/PAS0654/BiconeEvolutionOSC/BiconeEvolution/current_antenna_evo_build/XF_Loop/Evolutionary_Loop/AraSimTestJob.sh’: Operation not permitted

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Resuming...

NOTE:  You may want to change the following in your job for Owens

 

    nodes=1:ppn=1 defaulting to mem=4571MB

 

Please review the Owens documentation:

    https://www.osc.edu/supercomputing/computing/owens

 

Feel free to contact oschelp@osc.edu if you have any questions.

 

8485416.owens-batch.ten.osc.edu

rm: cannot remove ‘outputs/*.root’: No such file or directory

NOTE:  You may want to change the following in your job for Owens

 

    nodes=1:ppn=1 defaulting to mem=4571MB

 

Please review the Owens documentation:

    https://www.osc.edu/supercomputing/computing/owens

 

Feel free to contact oschelp@osc.edu if you have any questions.

 

8485417.owens-batch.ten.osc.edu

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mv: cannot stat ‘*.root’: No such file or directory

Fitness function initialized.

0 

Data successfully read. Data successfully written.

  18   Tue Nov 12 15:45:33 2019 Julie RollaWeek 11/12/19 Update

Attendance for today's session: Cade, Julie, Alex M, Alex P, Mitchell, Scott. 

Monday was a holiday, and we will be replaceing that meeting later this week. Today we worked on the following tasks:

Tasks:

  • Check continuity of loop
    • Alex M will try another run tonight, and has already requested a virtual desktop. 
  • Install Arasim to /fs/projects/PAS0654/BiconeEvolutionOCS to be edited and messed with
    • Cade is testing whether or not this is running within the loop. He had gotten a few errors, and it is not completing. It's submitting the job with the new bash script, but it is not actually running.
      • Found an error. The bash script was not grabbing the correct AraSim directory. More updates to come. 
  • Clean bash script
    • Mitchell and Alex M are putting all current functions hard-coded in into their own .sh scrips that are now being called in the main bash script.
  • Update Manual

Right now Elliot and Leo have decided to focus on working with Keith. They will not be contributing to this project for the remainder of the semester. Students have been posting individual updates here: https://www.dropbox.com/home/GP_Antennas/Updates

 

I've also attached the meeting minutes from the call last week, in order to keep track of updates. 

Attachment 1: GENETIS_meeting_minutes_11_|_7.pdf
  Draft   Sun Apr 19 15:27:42 2026 Julie RollaWeek 11/12/19 Update

 

Quote:

Attendance for today's session: Cade, Julie, Alex M, Alex P, Mitchell, Scott. 

Monday was a holiday, and we will be replaceing that meeting later this week. Today we worked on the following tasks:

Tasks:

  • Check continuity of loop
    • Alex M will try another run tonight, and has already requested a virtual desktop. 
  • Install Arasim to /fs/projects/PAS0654/BiconeEvolutionOCS to be edited and messed with
    • Cade is testing whether or not this is running within the loop. He had gotten a few errors, and it is not completing. It's submitting the job with the new bash script, but it is not actually running.
      • Found an error. The bash script was not grabbing the correct AraSim directory. More updates to come. 
  • Clean bash script
    • Mitchell and Alex M are putting all current functions hard-coded in into their own .sh scrips that are now being called in the main bash script.
  • Update Manual

Right now Elliot and Leo have decided to focus on working with Keith. They will not be contributing to this project for the remainder of the semester. Students have been posting individual updates here: https://www.dropbox.com/home/GP_Antennas/Updates

 

I've also attached the meeting minutes from the call last week, in order to keep track of updates. 

 

  134   Wed Jul 14 15:45:30 2021 Ethan FahimiWednesday Updates (7/14/2021)
Ethan Worked with Alex on fixing a few bugs with AREA. We are trying to solve an issue where the individuals are not finishing runs (around one in every four gens with 100 individuals). We believe some individuals may be too good and are then taking more than the wall time we have given them. Alex is testing this while I am working on a script that will add all the weights in the temp_{ind}.txt files. (See weightAdder.py for more)
   
   
   
   
   
   
  8   Fri Feb 22 17:09:28 2019 Suren GourapuraUpdates that need to be added to the manual

We are redesigning the way we simulate antennas in our loop. To do this, we changed our simulationPEC macro skeletons and our output skeleton. 

To make this easier, we changed the way we name the files, from i.uan where i is the simulation number, to i_j.uan where i is the antenna and j is the frequency.

We also rewrote XFintoARA.py so it's clean. Note that before there were comments from a previous author claiming it was VERY questionably written. This has now been cleaned up. We also changed the bash script relevant to the above changes.

This change needs to be added to the manual, and until we update this update, we have not done it.

 

  28   Thu Dec 5 16:58:55 2019 Julie RollaUpdated To-Do List:

Updated To-Do List:

  1. Add ARA constants in plotting code: ie add Veff, theta, R for ARA. This will sit as a constant line for us to compare each evolving parameter to. For example, in the plot Veff vs Generation, we will see a constant line for ARA's Veff to see how it is evolving in time. 

TASK 1: MAKE Veff PLOT. Note: One of our variables in this run is Energy. Unfortunately, we care about how Veff changes with Energy for ARAactualBicone. This means that before plotting "Veff versus Generation" we need to generate Veff for ARAactualBicone at the energy we are assigning the run. 

STEP 1: Make plotting code to plot "Veff vs Generation". 

  • You can follow the way we make LRPlot.py.
    • However, in this case, we will need to take the files /fs/project/PAS0654/BiconeEvolutionOSC/BiconeEvolution/current_antenna_evo_build/XF_Loop/Evolutionary_Loop/Run_Ouputs/$RunName/AraOut${gen}_${i}.txt -- ie the AraSim outputs for each individual in ALL generations. ie Gen 0 - ${gen}  -- INCLUDING the one we created in Gen 1 for ARAactualBicone -- and plot Veff from those. 
    • We also want to plot error bars with Veff. The error bars for each are labeled "and Veff (water eq)" at the bottom of these AraSim output files we are already reading in for Veff. 
      • Note, to know how to read in Veff, you can look at how we are reading that *exact* line from the AraSim output files in on the fitnessFunction_ARA.cpp code in the Antenna_Performance_Metric directory, since we are doing it there. 
      • Note that since we are plotting "Veff vs Generation", we will either have to read in all the files AraOut${gen}_${i}.txt (up to how may ${gen} we are in) every time -- including the ARAactualBicone one-- or we can append them all to one .txt file. It's your choice. 
    • Make sure you label the units for each axis every time, and that you have a key! If not, Amy will hate the plot!

STEP2: Add Veff for ARAactualBicone as a constat in the newly made "Veff vs Gen" plotting code. Remember, as I mentioned above, we must first put the ARAactualBicone through AraSim to see Veff at the same energy as the rest of the individuals. Here's what to do:

  •  Edit the Bash script to submit a job that runs the gain patterns of ARAactualBicone through AraSim in the initial gen (gen 0)! 
    • There's a current file that exits for ARAactualBicone that has the gain patterns of the current antenna, in the correct format for AraSim to run. In the bash script (XF_Loop.sh) we need to create ONE more AraSim job submission for this antenna (as a comparison to what we see with our genetically evolved ones) just in gen 0 (the first generation).
      • This current AraSim input file for ARAactualBicone exists in BiconeEvolutionOSC/AraSim/Ara_Bicone6in_output.txt
        • This needs to be the input for our .job script. 
  • Add lines to your newly made "Veff vs Gen" plotting code that reads in the Veff output for this ARAactualBicone AraSim output file (whatever you've chosen to name it when you wrote it into the job script. 

 STEP 3: Move the ARAactualBicone output file into the $Run_Name directory so it is not overwritten ever. 

  • We will want to make sure this is not overwritten after the run ends, and we start a new one. 
  • We will also be using it for plotting "Veff vs Generation". 

STEP 4: Correct the "wait" command for the AraSim job submissions. 

  • The "wait" command, on the first iteration, will have to wait for $NPOP+1 now-- not $NPOP.

 

TASK 2: MAKE "Theta vs Gen" Plot.  

STEP 1: Make plotting code to plot "Theta vs Generation". 

  • You can follow the way we make LRPlot.py; however, MAKE SURE YOU LABEL AXIS WITH UNITS, AND HAVE A KEY.
  • This will be exactly the same as this other code, except you will need to:
    1. Read in theta from your generation DNA files
    2. Add the ARAactualBicone constant to the code as a reference point

TASK 3: Fix "L vs Gen" and "R vs Gen" plot.  

STEP 1: Correct both plots to have labeled the units for each axis every time, and a key. This is plotted in the "LRPlot.py" code. 

STEP 2: Fix our 'R' values. I do believe we are plotting the incorrect "R". Here is what I think is happening:

 

 

  • We need to double-check and see what ARA defines "R" as on their current antennas. 
    • Check with Amy?
    • What does Brian Clark's thesis say?
    • Can you find a paper that shows a picture of how they define it?
  • If we are wrong, this means we need to change the "R vs Gen" part in the "LRPlot.py" code so that we:
    1. Read in R, L, and Theta for each generation.
      • See how this is already done for reading in R, and repeat it for L and theta. 
    2. Do trig to calculate the same "R" as ARAactualBicone defines. See picture below!
    3. Store that newly calculated "R" as an array, and plot THAT.
    4. Don't forget to add the ARAactualBicone Radius as a constant line. 

 

TASK 4: See PDF for other items!

Attachment 3: Proposal_To-Do_List.pdf
  7   Fri Feb 22 15:46:33 2019 Julie RollaUpdated To-Do List

We are getting to the stage where we would like to verify each step. It has been requested by Amy that we verify them visually. Here are the plots we need to make. 

  1. Add plotting for L & R parameters (note that we already have similar software to this from the dipole check. You can find this in the GitHub from the dipole test here: https://github.com/hchasan/XF-Scripts). This should be between A, and B in the loop drawing on the manual. (Done)
  2. Plot the distribution of theta and phi of incoming signal. This should be after D in the loop drawing on the manual. 
  3. Plot the distribution in cartesian coordinates of the neutrino interaction position. Maybe we can also plot the distance between the interaction point and the antenna. This should be after D in the loop drawing on the manual. 

 

Finally, as a tasks not to do with plotting, we need to make sure we don't lose any data as we go. We want to make sure that we keep tagged or labelled which individuals survive, and save the data flagged for those as we go. 

  175   Fri Aug 5 09:59:07 2022 Dennis CalderonUpdated Effective Volumes and Errors (Paper Run and Curved Sides)

Update to previous ELOG post for Effective Volumes and Errors for AraSim simulations for antennas from Paper_Run and Curved_Sides.

AraSim version compiled ~11/2021 and the (old) GENETIS version

 

Here are the column definitions:

  • The first column indicates the antenna being described. For example, XF_model_21_20 was the 20th individual in the 21st generation for the run discussed in the paper. Curved_side_1 was the best performing individual from the curved run done in February 2022. Curved_Side_1_Quad_Zero indicates the curved individual with its quadratic term set to 0. Curved_Side_1_Straightened indicates the curved individual with the quadratic term set to zero and the linear term modified so as to keep the outer radius the same as it originally was (that is, for Curved_Side_1).
  • The next three columns are the measurements for that individual.
    • The first one idicates the mean effective volume of the runs done for that individual. There were ~300 runs, each of 10,000 neutrinos.
    • The second column indicates the standard deviation of the mean (the previous column). This was measured by taking the standard deviation of the effective volumes (the line that says test Veff(ice) in the AraOut file) from all 300 runs (that is, Sigma(mean - x_i)/Sqrt(300)).
      • example of line:
        • Veff(ice) : 5.25337e+09 m3sr, 5.25337 km3sr
    • The final column indicates the average of the errors on the effective volume measurements from the AraOut files (the line that Veff(water eq.)) divided by Sqrt(300) for each of the 300 jobs (that is, Sigma(x_i/Sqrt(300))/300).
      • example of line:
        • And Veff(water eq.) error plus : 0.552722 and error minus : 0.552722
           

Note: Previously, the best curved individual (according to the run data) had been excluded (instead, we had the 2nd-6th best individuals). This has been corrected, with the order corrected. 

Also find attached a file called full_resimulate_DNA.csv . It contains the DNA for the top five curved individuals, the DNA for those same individuals with their quadratic term set to 0, and the DNA for those individuals with the quadratic term set to zero and the linear term modified to maintain the same outer radius as in the original run. 

Finally, the three images show the original best curved bicone (Curved_Side_1), the best curved bicone when its quadratic gene was set to 0 (Curved_Side_1_Quad_Zero), and the best curved bicone when its quadratic gene was set to 0 *and* its linear gene was changed to keep the same outer radius (Curved_Side_1_Straightened).

We have chosen XF_Model_23_08 to be the one actually built for testing. This was decided based on the data presented here. XF_Model_23_08 was the highest scoring individual in the paper run. Because the paper data was generated using the old version of AraSim, it was decided that using those results would make the most sense for which antenna to build. This would also mean that we can compare directly to the best individual in the paper. This individual was chosen over the curved sided inviduals because it has a higher fitness score, both when using the old version of AraSim and the new version.

Attachment 1: Effective_Volumes_Errors_2.pdf
Attachment 2: full_resimulate_DNA.csv 
Hybrid of Roulette and Tournament -- Thanks to Cal Poly / Jordan Potter
Author was David Liu
Notable contributors: Julie Rolla, Hannah Hasan, and Adam Blenk
Done at The Ohio State University
Working on behalf of Dr. Amy Connolly
And the ANITA project
Revision date: 21 March 2018 1800 EST
0.08333,0.1,0.11667,0.13334,0.15001,0.16668,0.18335,0.20002,0.21669,0.23336,0.25003,0.2667,0.28337,0.30004,0.31671,0.33338,0.35005,0.36672,0.38339,0.40006,0.41673,0.4334,0.45007,0.46674,0.48341,0.50008,0.51675,0.53342,0.55009,0.56676,0.58343,0.6001,0.61677,0.63344,0.65011,0.66678,0.68345,0.70012,0.71679,0.73346,0.75013,0.7668,0.78347,0.80014,0.81681,0.83348,0.85015,0.86682,0.88349,0.90016,0.91683,0.9335,0.95017,0.96684,0.98351,1.00018,1.01685,1.03352,1.05019,1.06686
Matrices for this Generation:
6.31483,77.6017,0.00260615,-0.197494
3.97024,40.9244,-0.0103313,0.36119
2.32499,79.663,-0.00224948,0.192602
0.308809,39.6742,-0.0084247,0.40629
2.32499,75.9855,-0.00224948,0.192602
0.966617,42.4246,-0.0084247,0.40629
5.83731,79.663,-0.000594616,0.0106887
2.316,38.0641,0.00166678,0.0135261
4.66148,79.663,-0.000594616,0.00582814
1.75822,39.9608,-0.000356019,0.0167485
6.31483,77.6017,0.0,-0.197494
3.97024,40.9244,0.0,0.36119
2.32499,79.663,0.0,0.192602
0.308809,39.6742,0.0,0.40629
2.32499,75.9855,0.0,0.192602
0.966617,42.4246,0.0,0.40629
5.83731,79.663,0.0,0.0106887
2.316,38.0641,0.0,0.0135261
4.66148,79.663,0.0,0.00582814
1.75822,39.9608,0.0,0.0167485
6.31483,77.6017,0.0,0.00474767
3.97024,40.9244,0.0,-0.0616123
2.32499,79.663,0.0,0.0134017
0.308809,39.6742,0.0,0.0720468
2.32499,75.9855,0.0,0.0216741
0.966617,42.4246,0.0,0.0488755
5.83731,79.663,0.0,-0.03668019
2.316,38.0641,0.0,0.0769706
4.66148,79.663,0.0,-0.0415408
1.75822,39.9608,0.0,0.00252170
Attachment 3: original_best_curved.png
original_best_curved.png
Attachment 4: best_curved_quad_zero.png
best_curved_quad_zero.png
Attachment 5: best_curved_same_radii.png
best_curved_same_radii.png
  Draft   Mon Oct 5 17:34:32 2020 Leo DeerUpdate Monday 10/5/2020
Name Update Plans for Monday
Alex M

 

  
Alex P   Finish up mutation function and then make sure it functions properly, currently our added functions all compile but we haven't tested if they are functioning as intended yet. Also have some questions about handling the standard deviations in mustations but first we want to get it functioning before applying more tweaks
Eliot Worked on learning about 3D plotting in python. Made a simple surface plot that can be expanded upon for our purposes.  
Leo Fixed the averge Fscore Plot so that it connects the mean values with a line instead of making them discrete points. Then I made Kai's plot suggestion. For that I copied the current FScore plotting software and made some edits so that it takes in 2 runs and plots the fitness scores of both in either red or green along with the average fitness score of both. I'll attach images of what these 2 plots look like. For Friday I'm going to look over the other plotting suggestions but most likely begin on fixing the random seperation in the RLTS plots.
Evelyn    
Ryan    
Ben    
Ethan    

 

Attachment 1: FixedFScore.png
FixedFScore.png
Attachment 2: RedPlot.png
RedPlot.png
  109   Fri Oct 2 17:11:25 2020 Ethan FahimiUpdate Friday 10/2/2020
Name Update Plans for Monday
Alex M

 

  
Alex P    
Eliot    
Leo Today I started working on improving the plots. I started with plotting the average fitness score for each generation on top of all the individuals data points. I made the average fitness score a star with higher contrast so it will stand out. Here is the plot of the first 26 generations of the "Machtay_20200914_Asymmetric_50_Individuals" run with the new averages. On monday I'm going to try and create the plot of  2 runs overlaid on top of eachother as Kai suggested.
Evelyn    
Ryan Worked with Ben and Alex P. on making the Bicone function modular on our copy. We finished writing a new roulette selection function, tournament selection function, and reproduction function.  Finish writing the mutation and crossover functions. After these are complete apply these functions in place of the existing function that is wrong and test to make sure the results are not producing errors. 
Ben    
Ethan Updated the AREA code with Alex M's help to work using SLURM. Began a trial run to see if our updates work. Begin making changes that allow the job to run faster as well as investigate what is causing some individuals to have fitness scores beyond what should be physically possible.
Attachment 1: Screen_Shot_2020-10-02_at_5.39.33_PM.png
Screen_Shot_2020-10-02_at_5.39.33_PM.png
  107   Wed Sep 9 17:28:54 2020 Alex MUpdate 9/9/20
Name Update Plans for tomorrow
Alex M

I've been working on readying the loop for the transition to slurm. OSC is switching from its current job managing software (torque/moab) to slurm, which uses some different commands but is functionally similar. Since we have places where jobs are called in the script, I've been changing them (with a backup copy of those files that we know works on torque). 

Right now I'm testing all of the changes I've made on the space OSC has set aside for playing with slurm. I have changes in all of the places I think they belong, but I need to make sure there aren't typos/different commands from what I've used. 

 I'll keep testing the changes I've made for slurm. I'll also try to organize some of the dfferences I've found in using slurm vs torque (for example, requesting an interactive job) so that everyone can see them and be able to find out what to use when OSC makes the switch (Pitzer changes on the 22nd, Owens is in November I think).
Alex P    
Eliot    
Leo    
Evelyn    
Ryan    
Ben    
Ethan    

 

  127   Tue Jan 26 17:17:41 2021 Ethan FahimiTuesday Updates 01/26/2021
Ethan F Continued implementing some solutions the OSC helpdesk gave me for fixing the unwanted extensions on the job output files.
   
   
   
   
   
   
  219   Mon May 22 20:34:59 2023 AmyThings to do before starting new PUEO run from 5/22/23 meeting

Here is a list of things we agreed to do before starting a new PUEO run.  Feel free to add notes here as things are done and we will revisit the list next week.

Change range of the height variable to 0.75-1.75m

Start with all bad individuals so that we can be sure and see growth - all at 0.75m?

Make sure we are using the ratios in the GA that we think we are

If we are using reproduction, are we combining results when individuals are resimulated to reduce errors?  I made a program to accomplish this and created a pull request on the PUEO Github (Dylan)

Investigate whether there are obvious places to speed up PUEOSim

Consolidate the GA to one branch

Understand what is happening with cross-pol, make sure we're not gettting Veff=0 when using XF-generated cross-pol response

Edit: Have the xmacros use the realized gain instead of the idealized gain, which allows for the design to build in matching

 

  233   Mon Jul 24 15:51:28 2023 Ryan DeboltTest Loop runs that need done.

Types of runs I need (May need some other people to help me run these):

  1. Optimization runs

    1. Non-error

      1. Search over combinations of selection methods and genetic operators

        1. Fix Sigma at 10%.

      2. Do this for 10 runs for each 

      3. Re-run the best run for 100 tests to see if the results agree with 10 test results

      4. This will be the main talking point

      5. Save the plot for the best combination (proxy and metric)

    2. Error

      1. Re-run the best run for 100 tests with 3 different error amounts (0.1, 0.2, 0.3)

      2. We will compare these results to the non-error run to talk about how errors may affect consistency/speed. 

      3. Save an example plot of an error test for each error (both metric and proxy score)

    3. Population

      1. Re-run the best run for 100 tests with 3 different population sizes (100, 500, 1000)

      2. We will compare these results to the non-error run to talk about how population size affects consistency/speed. 

      3. Save an example plot of a population test for each size (just proxy score)

  2. Demonstration runs (single runs, fitness score, no error population 100)

    1. Crossover only

    2. Mutation only

    3. Reproduction only

    4. Injection only

  241   Mon Oct 7 15:35:01 2024 Dylan WellsTemplate Run Results Slide Deck

Copy this slide deck to use when presenting on run updates!

https://docs.google.com/presentation/d/1Tk-B1QbFTP_5pQZovfn0_wbTswZTmOrJURpi374xJWo/edit?usp=sharing

  Draft   Sat Apr 18 02:21:30 2026 Dylan WellsTemplate Run Results Slide Deck

 

Quote:

Copy this slide deck to use when presenting on run updates!

https://docs.google.com/presentation/d/1Tk-B1QbFTP_5pQZovfn0_wbTswZTmOrJURpi374xJWo/edit?usp=sharing

 

  21   Wed Nov 20 15:05:14 2019 Julie RollaTask update 11/20/19

​Today I spent some time looking at task 1 from the update here: http://radiorm.physics.ohio-state.edu/elog/GENETIS/20. Below are my updates. 

 

Task-- Fix error at fitness function: 

Currently, the loop stops at the fitness function calculation, and aborts (program fitnessFunction_ARA.cpp). The following are the things I have tried.

1.Run this outside of the loop: Julie and Alex did this 11/19/19. It gave a segmentation fault. UPDATE: HERE'S WHAT I DID TO CHECK THIS TODAY:

(a) Checked using cout: I used some cout commands to print sections looking for errors. It seems we were not properly giving it arguments when running it outside of the loop. Since it's running outside of the loop, these variables are not initialized. Thus, to run you need to type: ./fitnessFunction.exe $NPOP $AraOut_i.txt

  • For example: ./fitnessFunction.exe 1 AraOut_1.txt

Status: The output file is verified! Running this way does properly generate our output file named fitnessScore.csv. I've double-checked this file, and it is properly being filled. At the moment it is giving a Veff of 0, thus no valid fitness score; however, this should be fixed automatically once we get real outputs from AraSim without a Veff of 0. 

 

 2. Check file location: See if fitnessScore.csv is being located in the correct place when the genetic algorithm initializes the next generation. 

(a) Searched bash script for the final location of fitnessScores.cvs: 

In lines 298, 299 of the bash script, it is doing the following 

cp fitnessScores.csv "$WorkingDir"/Run_Outputs/$RunName/0_fitnessScores.csv

mv fitnessScores.csv "$WorkingDir"

This is taking the .csv output generated from fitnessFunction_ARA.cpp, and is moving it to the run name directory and renaming it based on the generation -- ie first gen is 0_fitnessScores.csv-- so that data isn't overwritten. Then, for some reason, it moves the original copy -- ie fitnessScores.csv-- to the location /fs/project/PAS0654/BiconeEvolutionOSC/BiconeEvolution/current_antenna_evo_build/XF_Loop/Evolutionary_Loop

In line 374 we then run our genetic algorithm again. 

./roulette_algorithm.exe cont $NPOP

This does not seem to take in the input file as an argument.

 

(b) Checked roulette_algorithm.cpp for the location it accesses fitnessScores.csv:

I checked if it was hard-coded into the roulette_algorithm.cpp script. I found the following lines.

 // Now we need to read the fitness scores:                                                                                                                                                    

        ifstream fitnessScores;

        fitnessScores.open("fitnessScores.csv");

        string fitnessRead[NPOP+2];

        for(int i=0;i<(NPOP+2);i++)

    {

                getline(fitnessScores,fitnessRead[i]);

                if(i>=2)

                {

                        fitness[i-2] = atof(fitnessRead[i].c_str());

                        if (fitness[i-2]<0)

                        {

                                fitness[i-2] = 0; // If the fitness score is less than 0, we set it to 0 to not throw things off.                                                                     

                        }

                }

    }

        fitnessScores.close();

}

This means that our script roulette_algorithm.cpp is grabbing the fitnessScores.csv from its current directory-- which is accurate due to the line (mv fitnessScores.csv "$WorkingDir") referenced above in the bash script. Something we could verify here is to make sure this function is properly working by having it cout elements from the fitnessScores.csv within this function and to run the roulette algorithm separately. We could do this now, however, we don't have real outputs in fitnessScores.csv anyway, since we are getting a veff=0 for AraSim temporarily. 

In the meantime, I've added the following line after section E (the section that runs fitnessFunction_ARA.cpp, and generates/moves/copies fitnessScore.csv):

echo 'Congrats on getting a fitness score!'

This should check to be sure that it runs until after this point. I've also added the following line after section E (section that plots the fitness score versus gen):

echo 'Congrats on getting some nice plots!'

This should check to be sure that it runs until after this point. Note that I have added these lines to both our original bash script, and the one Alex M. is editing to turn every section into a function. I have added these lines to the .sh scripts containing the functions to be sure the function scripts for these tasks ran completely.  Once we have real AraSim outputs, we should be able to create some cout lines in the instructions highlighted in yellow above. 

 

3. Look at how it's calculating the fitness score.

I have not checked this yet. However, I do not think it is likely this is the issue. I will check later though. 

  13   Mon Jun 24 13:49:49 2019 Julie RollaSummer update

Right now the following people are working on this project:

Julie Rolla, Cade Sbrocco, Scott Janse, Alex Patton, Eliot Ferstl, Abassi Brown, Evelyn Shank, Sophie Dunlap

Today we met for our first working meeting. Scott, Alex, and Eliot were asked to speed up and optimize AraSim. Sophie and Evelyn are working on editing the .csv file with the beam patterns coming out of XF. Currently it's written in a different format than AraSim takes in. Abassi is helping Evelyn and Sophie by giving them a sample program helping reorganize the cells in a .csv file. Since there's confusion on how to optimize AraSim, we've started dissecting the software so we can understand how it works. The following are questions on the setup.txt document. 

 

 

Setup.txt

What is "timestep"? Could we increase the timestep? Is this timestep big or small compared to 2 GHz?

Answer: Timestep is the unit of discrete time the computer operates at. The timestep by default is set to 2 GHz, or 5 * 10^-10 seconds. We might be able to make up some cheap time by lowering that but would have to check if it makes the data less accurate.

What is "TRIG_WINDOW"? Is this a "coincidence"? Meaning if this signal is picked up within a certain time between stations it's considered the same event?

What is "V_MIMIC_MODE"? Comments in Setup.CC says "// default : 0 - write out all chs where global triggered bin is center of the window"

Answer: Not sure exactly what it does but we can't change it from default as the other values are for the test bed mode only.

Random Question from Setup.txt, but relevant for other things. What is "testbed mode"? Answer: The "testbed" is the original test station only 40m under. This mode is for if we do detector=3 in the first part of the setup.txt file; thus, we won't use this. 

What's the difference between "DETECTOR" and "DETECTOR_SIMULATION"? We found "DETECTOR_STATION" in Settings.h. The comments say "// for DETECTOR=4, indicates the single station to be simulated // 0 = testbed, 1 = A1, 2 = A2, 3 = A3"

In this file, there's an ANTENNA_MODE variable. You can look at what it does in Settings.h. In this file, it says that you can decide whether to use a bicone antenna response or "a different response for the top vpol antennas". How does this function work? What does it mean by "top vpol antennas"? Someone should look up the ARA antennas, and look into this function. 

 

Our goal is to meet and work as a group twice a week. Collaboration in work should help us progress faster. 

 

  229   Thu Jul 6 13:12:04 2023 Jack TillmanStraightened Sides AraSim Results

After discretizing and straightening the sides of the curved antenna that performed the best (Generation 13, individual 84) and running the antenna through AraSim, the following results and physics plots were generated. 

Attachment 1: Straightened_Sides_AraSim_Results.pdf
Attachment 2: Straightened_Sides_AraSim_Results.pptx
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