87 lines
3.7 KiB
Python
87 lines
3.7 KiB
Python
import json
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from pathlib import Path
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import matplotlib.pyplot as plt
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import numpy as np
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from matplotlib.ticker import MaxNLocator
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output_path = (Path(__file__).parent / 'out_files').resolve()
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# File paths for the three JSON files
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file1 = output_path / 'base_case_buildings_data.json'
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file2 = output_path / 'air_to_air_hp_buildings_data.json'
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file3 = output_path / 'air_to_water_hp_buildings_data.json'
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# Opening and reading all three JSON files at the same time
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with open(file1) as f1, open(file2) as f2, open(file3) as f3:
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base_case = json.load(f1)
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air = json.load(f2)
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water = json.load(f3)
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month_names = ['Jan', 'Feb', 'Mar', 'Apr', 'May', 'Jun', 'Jul', 'Aug', 'Sep', 'Oct', 'Nov', 'Dec']
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x = np.arange(len(month_names)) # the label locations
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width = 0.25 # the width of the bars
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# Prettier colors for each scenario
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colors = ['#66B2FF', '#e74c3c', '#2ecc71'] # Blue, Red, Green
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# Plotting heating data for all buildings in a 2x5 grid
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fig, axes = plt.subplots(2, 5, figsize=(20, 10), dpi=96)
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fig.suptitle('Monthly Heating Consumption Comparison Across Buildings', fontsize=16, weight='bold', alpha=0.8)
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axes = axes.flatten()
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for idx, building_name in enumerate(base_case.keys()):
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heating_data = [list(data["monthly_heating_consumption_kWh"].values()) for data in
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[base_case[building_name], air[building_name], water[building_name]]]
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ax = axes[idx]
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for i, data in enumerate(heating_data):
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ax.bar(x + (i - 1) * width, data, width, label=f'Scenario {i+1}', color=colors[i], zorder=2)
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# Grid settings
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ax.grid(which="major", axis='x', color='#DAD8D7', alpha=0.5, zorder=1)
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ax.grid(which="major", axis='y', color='#DAD8D7', alpha=0.5, zorder=1)
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# Axis labels and title
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ax.set_title(building_name, fontsize=14, weight='bold', alpha=0.8, pad=10)
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ax.set_xticks(x)
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ax.set_xticklabels(month_names, rotation=45, ha='right')
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ax.xaxis.set_major_locator(MaxNLocator(integer=True))
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ax.yaxis.set_major_locator(MaxNLocator(integer=True))
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if idx % 5 == 0:
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ax.set_ylabel('Heating Consumption (kWh)', fontsize=12, labelpad=10)
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fig.legend(['Base Case', 'Scenario 1', 'Scenario 2'], loc='upper right', ncol=3)
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plt.tight_layout(rect=[0, 0.03, 1, 0.95])
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plt.savefig(output_path / 'monthly_heating.png')
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# Plotting cooling data for all buildings in a 2x5 grid
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# Plotting cooling data for all buildings in a 2x5 grid
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fig, axes = plt.subplots(2, 5, figsize=(20, 10), dpi=96)
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fig.suptitle('Monthly Cooling Consumption Comparison Across Buildings', fontsize=16, weight='bold', alpha=0.8)
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axes = axes.flatten()
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for idx, building_name in enumerate(base_case.keys()):
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cooling_data = [list(data["monthly_cooling_consumption_kWh"].values()) for data in
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[base_case[building_name], air[building_name], water[building_name]]]
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ax = axes[idx]
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for i, data in enumerate(cooling_data):
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ax.bar(x + (i - 1) * width, data, width, label=f'Scenario {i+1}', color=colors[i], zorder=2)
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# Grid settings
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ax.grid(which="major", axis='x', color='#DAD8D7', alpha=0.5, zorder=1)
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ax.grid(which="major", axis='y', color='#DAD8D7', alpha=0.5, zorder=1)
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# Axis labels and title
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ax.set_title(building_name, fontsize=14, weight='bold', alpha=0.8, pad=10)
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ax.set_xticks(x)
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ax.set_xticklabels(month_names, rotation=45, ha='right')
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ax.xaxis.set_major_locator(MaxNLocator(integer=True))
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ax.yaxis.set_major_locator(MaxNLocator(integer=True))
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if idx % 5 == 0:
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ax.set_ylabel('Cooling Consumption (kWh)', fontsize=12, labelpad=10)
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fig.legend(['Base Case', 'Scenario 1', 'Scenario 2'], loc='upper right', ncol=3)
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plt.tight_layout(rect=[0, 0.03, 1, 0.95])
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plt.savefig(output_path / 'monthly_cooling.png') |