Plot room heat balance
======================

This script:

- Asks the user to open an IES-VE result file.
- Plots the room heat balances for each room.

This was originally published as an article here: https://www.stevenfirth.com/how-to-plot-room-heat-balance-results-in-ies-using-python/

.. image:: ../images/figure_how_to_plot_room_heat_balances.png

.. code-block:: python

   # PlotRoomHeatBalance

   # - This script creates a plot of the (annual) heat gains and losses for all rooms in the building.
   # - The heat gains and losses are plotted as a horizontal stacked bars for each room.

   # 1. Setup

   # - import packages
   import iesve
   import os
   import math
   from tkinter import Tk, messagebox
   from tkinter.filedialog import askopenfilename
   import matplotlib.pyplot as plt
   import matplotlib.ticker

   # - instances
   current_project = iesve.VEProject.get_current_project()

   # - directories
   dir_current_project = current_project.path.replace('\\','/')
   print('dir_current_project: ', dir_current_project)
   if not os.path.exists(dir_current_project):
      root = Tk()
      root.withdraw()
      messagebox.showinfo('Error', 'No IESVE project folder found.', parent = root)
      root.destroy()
      quit()
   dir_vista = os.path.join(dir_current_project, 'vista')

   # 2. Select results file
   # - Select file
   root = Tk()
   root.withdraw()
   fp_in = askopenfilename(title = 'Select IES results file', parent = root, initialdir = dir_vista, filetypes = [("APS files","*.aps")])
   root.destroy()
   print('fp_in: ', fp_in)
   # - Exit if filepath is empty string
   if fp_in == '': 
      root = Tk()
      root.withdraw()
      messagebox.showinfo('User input needed', 'Please select a .aps results file.', parent = root)
      root.destroy()
      quit()
   # - Exit if filepath is not in project filepath
   elif not dir_current_project in fp_in:
      root = Tk()
      root.withdraw()
      messagebox.showinfo('User input needed', 'Please select a .aps results file in the current IES project.', parent = root)
      root.destroy()
      quit()
      
   # 3. Get room data
   # - a dictionary {room_id: room_general_data_dict}
   realmodel = current_project.models[0]
   bodies = realmodel.get_bodies(False)  # False means get all bodies
   room_data_dict = {body.id: body.get_room_data().get_general() for body in bodies}
      
   # 4. Load gain data
   # - a dictionary {variable_name: {room_id: annual_total_heat_gain}}
   # - this selects only room variables which have 'units_type' as "Gain"
   data = {}
   with iesve.ResultsReader.open(fp_in) as f:
      vars = f.get_variables() 
      for var in vars:
         d = {}
         if var['model_level'] == 'z' and var['units_type'] == 'Gain':
               for room_id in list(room_data_dict):
                  x = f.get_room_results(room_id, var['aps_varname'], var['display_name'], 'z')
                  x = sum(x) if x is not None else 0
                  d[room_id] = x/1000000  # convert to MWh/year
               data[var['display_name']] = d
               
   #for k,v in data.items(): print(k, v)


   # 5. Plot figure
   #
   height = (0.4 * len(room_data_dict))
   if height < 2: height = 2
   if height > 4: height = 4
   #
   #height = 6 / 1920 * 1080  # fixed aspect ratio for publishing figure
   #
   fig, ax = plt.subplots(
      figsize = (
         6, 
         height
         ), 
      dpi = 200
      )
   positive_lefts = [0] * len(room_data_dict)
   negative_lefts = [0] * len(room_data_dict)
   #
   def plot_row(name, data, **kwargs):
      ""
      for i, (room_id, height) in enumerate(data.items()):
         if height > 0:
               left = positive_lefts[i]
               positive_lefts[i] += height
         else:
               left = negative_lefts[i]
               negative_lefts[i] += height
         line = ax.barh(
               i, 
               height, 
               left = left, 
               label = name if i == 0 else None,
               edgecolor = 'black',
               linewidth = 0.5,
               **kwargs)
      return line
   #
   color_i = 0
   for i, (k,v) in enumerate(data.items()):
      for x in v.values():
         if not math.isclose(x,0):  # plot variable provided at least one annual total is non-zero
               plot_row(
                  k,
                  v, 
                  color = f'C{color_i}',
                  alpha = 0.5
                  )
               color_i += 1
               break
   
   ax.legend(
      loc='center left', 
      bbox_to_anchor=(1, 0.5),
      fontsize=6
      )
   ax.set_xlabel('Annual heat gain (MWh/year)')
   ax.get_xaxis().set_major_formatter(matplotlib.ticker.FuncFormatter(lambda x, p: format(int(x), ',')))  # thousands separator
   ax.set_xlim(min(negative_lefts) - (max(positive_lefts) - min(negative_lefts)) * 0.05, max(positive_lefts) + (max(positive_lefts) - min(negative_lefts)) * 0.05)  # 5% margin on either side
   ax.set_yticks(range(len(room_data_dict)))
   ax.set_yticklabels([x['name'] for x in room_data_dict.values()])
   ax.set_ylabel('Room')
   ax.yaxis.set_tick_params(labelsize=10 - len(room_data_dict) * 3 / 30)    # reduces room name font size based on nmber of rooms
   fig.tight_layout()
   plt.show()