johnjosephhorton

library(ggplot2)
library(dplyr)
library(tidyr)
library(gridExtra)
library(purrr)

# Function to compute medians and bootstrap CIs for a single tau value
get_medians <- function(data, simtot = 150, tau = 0.5) {
  # Data without errors
  data0 <- subset(data, all_errors == 0)

johnjosephhorton

from edsl import QuestionList, ScenarioList, QuestionFreeText
import random 

q = QuestionList(question_text = "Generate a list of 10 fruits", question_name = "fruits")
fruits = q()

def list_to_pref(items):
    return  " > ".join(items)

preferences = [list_to_pref(random.sample(fruits, len(fruits))) for _ in range(20)]

johnjosephhorton

import textwrap
from edsl import QuestionMultipleChoice, Scenario

pay_offs = {
    ('red', 'red'):(1, -1),
    ('red', 'black'):(-1, 1),
    ('black', 'red'):(1, -1),
    ('black', 'black'): (-1, 1)
}
instructions = textwrap.dedent("""\

johnjosephhorton

"""
This gives some examples of how to use SQL and ggplot2 together in the Results class.
Note that rather than call LLMs, we are created an agent with a direct-answering capability. 
After we create the agent, we create a `Results` object. 

"""
import random

from edsl import QuestionNumerical, QuestionFreeText
from edsl import Agent

johnjosephhorton

(venv) john@Johns-MacBook-Air agent_dialog % python -i AgentDialog.py
John: Hello Robin, I was thinking about going hiking today. Are you interested in joining me?
Robin: Hello John, hiking sounds like a great idea! I was actually hoping to go biking today, but a hike could be a nice compromise. Where were you thinking of hiking?
John: That's great to hear, Robin! I was thinking of hitting the trails at the Green Mountain Forest. There are some fantastic views and the terrain is just right for a good day's hike. How does that sound to you?
Robin: Green Mountain Forest sounds wonderful, John! I've heard the trails there are quite scenic. And you're right, it seems like the perfect place for a good day's hike. Let's do it! What time were you thinking of starting?
John: I'm glad you're on board, Robin! How about we start early to make the most of the day? Meeting at 8:00 AM would give us plenty of time to enjoy the trails. Does that work for you?
Robin: That sounds like a plan, John! Meeting at 8:00 AM works for

johnjosephhorton

import aiohttp
import asyncio

http_status_codes = {
    100: "Continue",
    101: "Switching Protocols",
    102: "Processing",
    200: "OK",
    201: "Created",
    202: "Accepted",

johnjosephhorton

from jinja2 import Template
from jinja2 import Environment, meta

class Question:
    """This class reprsents a question sent to an LLM (or human).
    It uses the jinja2 templating language to generate the prompt.
    For details on jinja2: https://jinja.palletsprojects.com/en/3.0.x/
    This templating language gives us lots of flexibility in how we ask questions.
    """
    def __init__(self, template_string):

johnjosephhorton

# Find all your R files & get just the package names, uniquely 
find ../analysis/ -name *R -print0 | xargs -0 grep -h 'library*' | sed 's/library//g' | sed 's/#//g' | sed 's/ //g' | sort | uniq|\
 sed 's/(//g' | sed 's/)//g' > package_list.txt
 
# Install each package 
cat package_list.txt | xargs -I {} Rscript -e 'install.packages("{}")'

johnjosephhorton

#!/usr/bin/Rscript --vanilla

suppressPackageStartupMessages({
library(magrittr)
library(dplyr)
library(foreign)
library(plm)
library(reshape2)
library(stargazer)
library(ggplot2)

johnjosephhorton

project_name = hot_towel

ts := $(shell /bin/date "+%Y-%m-%d---%H-%M-%S")

params =
# DONE 
params += params_exp_details.tex
params_exp_details.tex: ../analysis/params_exp_details.R
	cd ../analysis && ./params_exp_details.R