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Update show_azure.py #54

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170 changes: 102 additions & 68 deletions scripts/show_azure.py
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Original file line number Diff line number Diff line change
@@ -1,94 +1,128 @@
import os
import json
import pandas as pd
import argparse
import logging
import numpy as np
from tqdm import tqdm
from concurrent.futures import ThreadPoolExecutor
from io import StringIO

# Set up logging
logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")

# Validate the experiment configuration
def validate_config(config):
required_keys = ["exp_name", "a11y_backend", "som_origin", "model_name"]
for exp_name, exp_details in config.items():
for key in required_keys:
if key not in exp_details:
raise ValueError(f"Missing '{key}' in experiment '{exp_name}'")

# Process each experiment and gather results
def process_experiment(exp_name, exp_details, result_dir, columns):
row = {col: None for col in columns}
row["exp_name"] = exp_name
row["uia_value"] = "✅" if exp_details.get("a11y_backend", "") == "uia" else "❌"
row["som_origin"] = exp_details.get("som_origin", "N/A")
row["model"] = exp_details.get("model_name", "Unknown")

path_kwargs = {
"result_dir": result_dir,
"exp_name": exp_name,
"action_space": "pyautogui",
"observation_type": "a11y_tree",
"model": exp_details["model_name"],
"trial_id": "0"
}

path_args = [path_kwargs[k] for k in [
"result_dir", "exp_name", "action_space", "observation_type", "model", "trial_id"
]]

results_path = os.path.join(*path_args)
errs = 0

for domain in ["chrome", "libreoffice_calc", "libreoffice_writer",
"vlc", "vs_code", "settings", "windows_calc",
"clock", "msedge", "file_explorer", "microsoft_paint", "notepad"]:
domain_path = os.path.join(results_path, domain)
if os.path.isdir(domain_path):
task_results = []
for task in os.listdir(domain_path):
task_path = os.path.join(domain_path, task, "result.txt")
if os.path.isfile(task_path):
try:
with open(task_path, "r") as f:
result = float(f.read().strip())
task_results.append(result)
except ValueError:
logging.error(f"Invalid result.txt in {exp_name}, {domain}/{task}")
errs += 1
task_results.append(np.nan)
else:
logging.warning(f"Missing result.txt in {exp_name}, {domain}/{task}")
errs += 1
task_results.append(np.nan)

# Calculate the percentage of valid results
if task_results:
valid_results = [res for res in task_results if not np.isnan(res)]
row[domain] = sum(valid_results) / len(valid_results) * 100 if valid_results else None
else:
row[domain] = None
else:
row[domain] = None

row["*errors*"] = errs
return row

# Main function to generate results table from experiments
def get_results_from_json(result_dir, config, output_file):
columns = ["exp_name", "uia_value", "som_origin", "model",
"chrome", "libreoffice_calc", "libreoffice_writer",
"vlc", "vs_code", "settings", "windows_calc",
"clock", "msedge", "file_explorer", "microsoft_paint", "notepad", "*errors*"]

# Start the markdown file and write the headers
# Prepare markdown headers
output = StringIO()
output.write("| " + " | ".join(columns) + " |\n")
output.write("|" + " | ".join(["---"] * len(columns)) + "|\n")

# Process each experiment in parallel
with ThreadPoolExecutor() as executor:
results = list(executor.map(lambda exp: process_experiment(exp[0], exp[1], result_dir, columns), config.items()))

# Write results to output file in one go
for row in results:
row_markdown = "| " + " | ".join([str(row[col]) if row[col] is not None else "" for col in columns]) + " |\n"
output.write(row_markdown)

with open(output_file, "w") as f:
f.write("| " + " | ".join(columns) + " |\n")
f.write("|" + " | ".join(["---"] * len(columns)) + "|\n")

# Iterate through each experiment configuration
for exp_name, exp_details in tqdm(config.items(), desc="Processing Experiments"):
row = {col: None for col in columns}
row["exp_name"] = exp_name
row["uia_value"] = "✅" if exp_details.get("a11y_backend", "") == "uia" else "❌"
row["som_origin"] = exp_details.get("som_origin", "")
row["model"] = exp_details.get("model_name", "")

path_kwargs = {
"result_dir": result_dir,
"exp_name": exp_name,
"action_space": "pyautogui",
"observation_type": "a11y_tree",
"model": exp_details["model_name"],
"trial_id": "0"
}

path_args = [path_kwargs[k] for k in [
"result_dir", "exp_name", "action_space", "observation_type", "model", "trial_id"
]]

results_path = os.path.join(*path_args)
errs = 0

for domain in ["chrome", "libreoffice_calc", "libreoffice_writer",
"vlc", "vs_code", "settings", "windows_calc",
"clock", "msedge", "file_explorer", "microsoft_paint", "notepad"]:
domain_path = os.path.join(results_path, domain)
if os.path.isdir(domain_path):
task_results = []
for task in os.listdir(domain_path):
task_path = os.path.join(domain_path, task, "result.txt")
if os.path.isfile(task_path):
try:
with open(task_path, "r") as f:
result = float(f.read().strip())
task_results.append(result)
except ValueError:
print(f"Invalid result.txt in {exp_name}, {domain}/{task}")
errs += 1
task_results.append(np.nan)
else:
print(f"Missing result.txt in {exp_name}, {domain}/{task}")
errs += 1

# Calculate the percentage of valid results
if task_results:
valid_results = [res for res in task_results if not np.isnan(res)]
row[domain] = sum(valid_results) / len(valid_results) * 100 if valid_results else None
else:
row[domain] = None
else:
row[domain] = None
f.write(output.getvalue())

row["*errors*"] = errs

# Convert row to markdown format and append to file
with open(output_file, "a") as f:
row_markdown = "| " + " | ".join([str(row[col]) if row[col] is not None else "" for col in columns]) + " |\n"
f.write(row_markdown)

print(f"Results table saved to {output_file}")
logging.info(f"Results table saved to {output_file}")

if __name__ == "__main__":
import argparse

# Set up argument parser
parser = argparse.ArgumentParser(description="Generate results table from JSON config.")
parser.add_argument("--result_dir", type=str, required=True, help="Directory containing result files.")
parser.add_argument("--json_config", type=str, required=True, help="Path to JSON config file.")
parser.add_argument("--output_file", type=str, default="results_table.md", help="Output markdown file.")

# Parse arguments
args = parser.parse_args()

# Load the JSON configuration
with open(args.json_config, "r") as f:
config = json.load(f)

get_results_from_json(args.result_dir, config, args.output_file)
# Validate the configuration
try:
validate_config(config)
except ValueError as e:
logging.error(f"Configuration error: {e}")
exit(1)

# Process and generate the results table
get_results_from_json(args.result_dir, config, args.output_file)