JobShopModels.py/plot_gantt.py at master · thj3a/JobShopModels.py · GitHub

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import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
import colorcet as cc
import numpy as np
import os
import math
import plotly.express as px
from matplotlib.patches import Patch

def plot_gantt(timestamp, instance_name, path):
    # plt.style.use('seaborn-whitegrid')
    # plt.style.use('seaborn-pastel')
    # color_map = plt.get_cmap('Pastel1')

    ##### STYLE #####
    plt.style.use('ggplot')
    color_map = sns.color_palette(cc.glasbey_hv, n_colors=100)

    ##### DATA #####
    timestamp.sort_values(by=['Resource', 'Job', 'Start_f'], inplace=True)

    ##### PLOT #####
    fig, ax = plt.subplots()
    jobs = list(map(int, timestamp.Job))
    Ws = list(map(int, (timestamp.Finish_f-timestamp.Start_f)))
    Ls = list(map(int, timestamp.Start_f))
    bars = ax.barh(y = timestamp.Resource,
            width = Ws,
            left = Ls,
            color = [color_map[job] for job in jobs],
            label = timestamp['Job'].values,
            edgecolor='k')

    ##### LEGEND #####
    legend_elements = [Patch(facecolor=color_map[int(job)], edgecolor='k', label=f'Job {job}') for job in sorted([str(v).rjust(2, '0') for v in timestamp.Job.unique()])]
    ax.legend(handles=legend_elements, ncol=math.ceil(len(timestamp.Job.unique())/20), bbox_to_anchor=(1.05, 1), loc='upper left')

    ## uncomment this piece of code below to label the bars with the number of operation of each job ##
    # for bars in ax.containers:
    #     ax.bar_label(bars, timestamp.Op)

    ##### TICKS #####
    # n_ranges = int(timestamp.Finish_f.max()/(timestamp.Finish_f - timestamp.Start_f).max())
    # xticks = np.arange(0, timestamp.Finish_f.max(), n_ranges)
    # xticks_labels = np.arange(0, int(timestamp.Finish_f.max()))[::n_ranges]
    # ax.set_xticks(xticks)
    # ax.set_xticklabels(xticks_labels)

    # xticks_minor = np.arange(0, df.Finish_f.max()+1, 1)
    # ax.set_xticks(xticks_minor, minor=True)

    ##### LABELS #####
    ax.set_xlabel('Time (min)')
    ax.set_ylabel('Resource')
    # ax.set_title(f'{instance_name} - Timestamp')
    ax.autoscale(enable=True, axis='both', tight=False)
    # ax.set_xlim(xmax=35000)
    # plt.show()
    plt.savefig(
                os.path.join(path, f'{instance_name}'),
                dpi=300,
                bbox_inches='tight'
                )
    plt.close()

def old_gantt_plot(timestamp, instance_name, path):

    timestamp.sort_values(by=['Resource','Start'], ascending=True, inplace=True)
    timestamp.Job = list(map(str, timestamp.Job))
    fig = px.timeline(timestamp, x_start="Start", x_end="Finish", y="Resource", color="Job")
    fig.update_layout(xaxis=dict(
                        title='Timestamp',
                        tickformat = '%H:%M:%S',
                    ))
    fig.update_yaxes(categoryorder='array', categoryarray=timestamp.Resource.unique())
    fig.update_layout(
    autosize=True,)
    # width=1000,
    # height=1000,)

    fig.write_image(os.path.join(path, f"{instance_name}_gantt.jpg"))