IES-VE User Forum

import sys
import iesve
from ies_file_picker import IesFilePicker
import pandas as pd
import os
from datetime import datetime

# Pick an aps file name
aps_name = IesFilePicker.pick_vista_file([("APS files", "*.aps")], "Select an APS file")
# Open the aps file for reading
aps_file = iesve.ResultsReader.open(aps_name)

# Get a list of real model bodies
project = iesve.VEProject.get_current_project()
realmodel = project.models[0]
bodies = realmodel.get_bodies(False)

# Initialize a list to store the results
results = []

# Iterate through the bodies
for body in bodies:
# Setup a list of body types we do not want to query
unwanted_subtypes = [iesve.VEBody_subtype.void, iesve.VEBody_subtype.ra_plenum, iesve.VEBody_subtype.sa_plenum]
# Now avoid the body types we do not want
if (body.type != iesve.VEBody_type.room or body.subtype in unwanted_subtypes):
continue

# Get the body data object
bodydata = body.get_room_data(0)

# Get room data
room_data = bodydata.get_general()
room_name = room_data['name']
room_id = room_data['id']

# Get operative temperature data using room id
try:
operative_temp_data = aps_file.get_room_results(room_id, 'Room air temperature&Room radiant temperature', 'Operative temperature (TM 52/CIBSE)', 'z', start_day=-1, end_day=-1)
except Exception as e:
print(f"No data returned for room: {room_name} (ID: {room_id}) - {str(e)}")
continue

if operative_temp_data is None:
print(f"No data returned for room: {room_name} (ID: {room_id})")
continue

# Store the results
for hour, temp in enumerate(operative_temp_data, start=1):
results.append({"Hour": hour, "Room Name": room_name, "Operative Temperature (C)": temp})

# Close results file
aps_file.close()

# Create a DataFrame
df = pd.DataFrame(results)

# Pivot the DataFrame
pivot_df = df.pivot(index="Hour", columns="Room Name", values="Operative Temperature (C)")

# Extract the base name of the aps file without extension
aps_base_name = os.path.splitext(os.path.basename(aps_name))[0]

# Get the current time
current_time = datetime.now().strftime("%H%M")

# Construct the output file name
output_file_name = f"{aps_base_name}_{current_time}.xlsx"

# Save to an Excel file
pivot_df.to_excel(output_file_name)

print(f"Hourly operative temperature data extracted and saved to {output_file_name}")