76 lines
2.6 KiB
Python
76 lines
2.6 KiB
Python
import pandas as pd
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import plotly.graph_objects as go
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# Load the data
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data = pd.read_csv('06-25_07-07.csv')
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# Convert 'Date/Time (--4:0:0)' column to datetime
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data['Date/Time (--4:0:0)'] = pd.to_datetime(data['Date/Time (--4:0:0)'])
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# Calculate the time difference between consecutive points in minutes
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data['Time Diff (min)'] = data['Date/Time (--4:0:0)'].diff().dt.total_seconds() / 60
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# Set flow rate and specific heat capacity
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flow_rate_gpm = 10
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density_water = 62.4 # lbm/ft^3
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flow_rate_lbm_min = flow_rate_gpm * 0.133681 * density_water # Convert GPM to lbm/min
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# Calculate Q (BTU)
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cp_water = 1 # BTU/lbm°F
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data['Delta T (F)'] = data['Sewer Water Out'] - data['Sewer Water In']
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data['Q (BTU)'] = flow_rate_lbm_min * cp_water * data['Delta T (F)'] * data['Time Diff (min)']
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# Set the datetime column as the index
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data.set_index('Date/Time (--4:0:0)', inplace=True)
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# Apply a smoothing function (moving average)
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window_size = 10
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data['Q Smooth'] = data['Q (BTU)'].rolling(window=window_size, center=True).mean()
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# Ensure index is a datetime index for ease of filtering
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data.index = pd.to_datetime(data.index)
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# Create the plot
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fig = go.Figure()
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# Add traces for each line with spline smoothing and increased visibility
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fig.add_trace(go.Scatter(x=data.index, y=data['Q Smooth'], mode='lines', name='Transferred Heat (BTU/lb)',
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line=dict(shape='spline', color='blue', width=2, dash='solid')))
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# Add shading to separate days
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for i in range((data.index[-1] - data.index[0]).days + 1):
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start = data.index[0] + pd.Timedelta(days=i)
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end = start + pd.Timedelta(days=1)
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fig.add_vrect(
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x0=start, x1=end,
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fillcolor='grey' if i % 2 == 0 else 'white',
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opacity=0.1,
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line_width=0
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)
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# Update layout for better styling and to set figure size
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fig.update_layout(
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title=dict(
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text='Transferred Heat',
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font=dict(size=20, family='Arial', color='black', weight='bold')
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),
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xaxis_title=dict(
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text='Date/Time',
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font=dict(size=18, family='Arial', color='black', weight='bold')
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),
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yaxis_title=dict(
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text='Energy (BTU)',
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font=dict(size=18, family='Arial', color='black', weight='bold')
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),
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legend=dict(
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title=dict(font=dict(size=15, family='Arial', color='black', weight='bold')),
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font=dict(size=14, family='Arial', color='black', weight='bold')
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),
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font=dict(size=14),
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width=1400, # Set the width of the figure
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height=800 # Set the height of the figure
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)
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# Save the plot (requires kaleido package)
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fig.write_image('heat.png')
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# Display the plot
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fig.show()
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