coniston/daily_plots.py

import pandas as pd
import plotly.graph_objects as go

# Load the data (assuming you've already loaded and processed it as shown)
data = pd.read_csv('06-25_07-07.csv')

# Convert 'Date/Time (--4:0:0)' column to datetime
data['Date/Time (--4:0:0)'] = pd.to_datetime(data['Date/Time (--4:0:0)'])

# Set the datetime column as the index
data.set_index('Date/Time (--4:0:0)', inplace=True)

# Apply a smoothing function (moving average)
window_size = 10
data['Sewer Water In Smooth'] = data['Sewer Water In'].rolling(window=window_size, center=True).mean()
data['Sewer Water Out Smooth'] = data['Sewer Water Out'].rolling(window=window_size, center=True).mean()
data['Return Air Smooth'] = data['Return Air'].rolling(window=window_size, center=True).mean()
data['Supply Air Smooth'] = data['Supply Air'].rolling(window=window_size, center=True).mean()

# Ensure index is a datetime index for ease of filtering
data.index = pd.to_datetime(data.index)

# Loop through each calendar day and create separate plots
for day in pd.Index(data.index.date).unique():
    # Filter data for the current day
    day_data = data[data.index.date == day]

    # Create the plot for the current day
    fig = go.Figure()

    fig.add_trace(go.Scatter(x=day_data.index, y=day_data['Sewer Water In Smooth'], mode='lines', name='Sewer Water In',
                             line=dict(shape='spline', color='blue', width=2, dash='solid')))
    fig.add_trace(go.Scatter(x=day_data.index, y=day_data['Sewer Water Out Smooth'], mode='lines', name='Sewer Water Out',
                             line=dict(shape='spline', color='red', width=2, dash='solid')))
    fig.add_trace(go.Scatter(x=day_data.index, y=day_data['Return Air Smooth'], mode='lines', name='Return Air',
                             line=dict(shape='spline', color='orange', width=2, dash='solid')))
    fig.add_trace(go.Scatter(x=day_data.index, y=day_data['Supply Air Smooth'], mode='lines', name='Supply Air',
                             line=dict(shape='spline', color='green', width=2, dash='solid')))

    fig.update_layout(
        title=dict(
            text=f'Temperature at Inlets and Outlets of the Heat Exchanger - {day}',
            font=dict(size=20, family='Arial', color='black', weight='bold')
        ),
        xaxis_title=dict(
            text='Date/Time',
            font=dict(size=18, family='Arial', color='black', weight='bold')
        ),
        yaxis_title=dict(
            text='Temperature (F)',
            font=dict(size=18, family='Arial', color='black', weight='bold'),
        ),
        legend=dict(
            title=dict(font=dict(size=15, family='Arial', color='black', weight='bold')),
            font=dict(size=14, family='Arial', color='black', weight='bold')
        ),
        font=dict(size=14),
        width=1400,
        height=800
    )

    # Save the plot (requires kaleido package)
    fig.write_image(f'temperature_variations_without_Q_{day}.png')