Question-and-Answer Resource for the Building Energy Modeling Community
 | 1 | initial version |
Hi Jack. I use the measure "CreateCSVOutput" in the BLC library to get a .csv file which is placed in the run folder after every simulationrun with all the variable data output. Then I use a python script to graph the data in my webbrowser.
Use ChatGPT or Google AIstudio to edit the script to your liking. I hope this helps you somewhat. Good luck.
import pandas as pd import plotly.graph_objs as go import plotly.io as pio import tempfile import webbrowser import os
csv_file = 'report_variables_ZoneTimestep.csv'
df = pd.read_csv(csv_file, parse_dates=['Zone Timestep'], index_col='Zone Timestep')
exclude_cols = [ 'e:Electricity:Facility[J]' ]
def is_power_variable(col_name: str) -> bool: keywords = ['[w]', '(w)', ' watt', 'power', 'rate', 'elec'] return any(k.lower() in col_name.lower() for k in keywords)
available_cols = [c for c in df.columns if c not in exclude_cols]
left_cols = [c for c in available_cols if not is_power_variable(c)] right_cols = [c for c in available_cols if is_power_variable(c)]
fig = go.Figure()
for col in left_cols: fig.add_trace(go.Scatter(x=df.index, y=df[col], mode='lines', name=col, yaxis='y1'))
for col in right_cols: fig.add_trace(go.Scatter(x=df.index, y=df[col], mode='lines', name=col, yaxis='y2'))
fig.update_layout( title='All Variables from CSV', xaxis_title='Time', yaxis=dict( title='Temperature [Celsius]', side='left', showgrid=False, autorange=True ), yaxis2=dict( title='Power [Watt]', overlaying='y', side='right', showgrid=False, autorange=True ), hovermode='x unified', xaxis=dict( rangeselector=dict( buttons=list([ dict(count=1, label='1 day', step='day', stepmode='backward'), dict(count=7, label='1 week', step='day', stepmode='backward'), dict(count=1, label='1 month', step='month', stepmode='backward'), dict(step='all') ]) ), rangeslider=dict(visible=True), type='date' ) )
with tempfile.NamedTemporaryFile('w', delete=False, suffix='.html', encoding='utf-8') as f: html_str = pio.to_html(fig, include_plotlyjs='cdn', full_html=True, config={'displaylogo': False}) f.write(html_str) temp_path = f.name
webbrowser.open('file://' + os.path.realpath(temp_path)) print("Base plot opened in browser. Axis scaling now uses default Plotly autorange.")
