E+PlotResults.py

from textwrap import wrap

import matplotlib.pyplot as plt
import pandas as pd


def plot(base_path: str, mod_path: str, plot_vars=None):
    """
    Plots the results from two eplusout.csv files. Attempts to match the columns names and plot these series together.

    :param base_path: Path to the base simulation eplusout.csv file.
                      Typically this is the results from the 'develop' branch.
    :param mod_path: Path to the modified simulation eplusout.csv file.
    :param plot_vars: Python dict object containing mis-matched columns names to be plotted together.
                      Base columns names are the dict keys, and mod columns names are the values.

    Example 1:
    >>> base_path = "/path/to/base/eplusout.csv"
    >>> mod_path = "/path/to/mod/eplusout.csv"
    >>> plot(base_path, mod_path)


    Example 2:
    cols_to_plot = {"Base Col_1 Name": "Mod Col_1 Name", "Base Col_2 Name": "Mod Col_2 Name"}
    >>> plot(base_path, mod_path, cols_to_plot)
    """

    df_base = pd.read_csv(base_path)
    df_mod = pd.read_csv(mod_path)

    plot_vars_present = True

    if plot_vars is None:
        plot_vars_present = False

    # strip whitespace
    df_base.rename(columns=lambda x: x.strip(), inplace=True)
    df_mod.rename(columns=lambda x: x.strip(), inplace=True)

    # drop Date/Time
    df_base.drop(labels="Date/Time", axis=1, inplace=True)
    df_mod.drop(labels="Date/Time", axis=1, inplace=True)

    if plot_vars is None:
        base_cols = df_base.columns.to_list()
        mod_cols = df_mod.columns.to_list()

        plot_vars = dict()
        base_skipped = list()
        mod_skipped = list()

        for col in base_cols:
            if col in mod_cols:
                plot_vars[col] = col
            else:
                base_skipped.append(col)

        for col in mod_cols:
            if col not in base_cols:
                mod_skipped.append(col)

        print(f"Columns Skipped from Base: {base_skipped}")
        print(f"Columns Skpped from Mod: {mod_skipped}")

    for idx, (base_col, mod_col) in enumerate(plot_vars.items()):
        base = df_base[base_col]
        mod = df_mod[mod_col]
        diff = base - mod
        fig, (ax1, ax2) = plt.subplots(2, sharex=True)

        if plot_vars_present:
            ax1.plot(base, label=base_col)
            ax1.plot(mod, label=mod_col, linestyle='--')
        else:
            ax1.plot(base, label='EMS')
            ax1.plot(mod, label='Python', linestyle='--')

        ax1.legend()
        ax1.grid()
        ax2.plot(diff)
        ax2.set_ylabel("Delta (EMS - Python)")
        ax2.grid()

        if not plot_vars_present:
            plt.suptitle("\n".join(wrap(base_col)))

        plt.show()