add recommender to repository

vis.py

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+import matplotlib.pyplot as plt
+import pandas as pd
+import os
+
+def setAxLinesBW(ax):
+    """
+    Take each Line2D in the axes, ax, and convert the line style to be 
+    suitable for black and white viewing.
+    """
+    MARKERSIZE = 3
+
+    COLORMAP = {
+        '#1f77b4': {'marker': None, 'dash': [5,2]},
+        '#ff7f0e': {'marker': None, 'dash': [3,4]},
+        '#2ca02c': {'marker': None, 'dash': [1,1]},
+        'k': {'marker': None, 'dash': (None,None)},
+        "#d62728": {'marker': None, 'dash': (None,None)},
+        }
+
+
+    lines_to_adjust = ax.get_lines()
+    try:
+        lines_to_adjust += ax.get_legend().get_lines()
+    except AttributeError:
+        pass
+
+    for line in lines_to_adjust:
+        origColor = line.get_color()
+        line.set_color('black')
+        line.set_dashes(COLORMAP[origColor]['dash'])
+        line.set_marker(COLORMAP[origColor]['marker'])
+        line.set_markersize(MARKERSIZE)
+
+def setFigLinesBW(fig):
+    """
+    Take each axes in the figure, and for each line in the axes, make the
+    line viewable in black and white.
+    """
+    for ax in fig.get_axes():
+        setAxLinesBW(ax)
+
+
+def save_figs(folder):
+    happiness_diff = load_data_frame("{}/data/{}".format(folder, "_happy_increase.csv"))
+    unhappiness_diff = load_data_frame("{}/data/{}".format(folder, "_unhappy_increase.csv"))
+
+    happiness_diff['dictator'] = 0
+    unhappiness_diff['dictator'] = 0
+
+    happiness_total_all = load_data_frame("{}/data/{}".format(folder, "_happy_total_all.csv"))
+    unhappiness_total_all = load_data_frame("{}/data/{}".format(folder, "_unhappy_total_all.csv"))
+
+    column = happiness_total_all.columns[0]
+    index = happiness_total_all.index[0]
+    dictator_y_happy = happiness_total_all[column][index] - happiness_diff[column][index]
+    dictator_y_unhappy = unhappiness_total_all[column][index] - unhappiness_diff[column][index]
+
+
+    figure, axes = new_fig(title="{} Figure 2".format(folder))
+
+    x_lim=[0,150]
+
+    axes[0].set_title("satisfaction")
+    axes[0].set_xlim(x_lim)
+    axes[0].set_xlabel("number of stored configurations")
+    axes[0].set_ylabel("number of people")
+    axes[0].axhline(y=dictator_y_happy,linewidth=1, color='k')
+
+    happiness_total_all.plot(ax=axes[0])
+    y_labels_happy_total =axes[0].get_yticks().tolist()
+
+    axes[1].set_title("dissatisfaction")
+    axes[1].set_xlabel("number of stored configurations")
+    axes[1].set_ylabel("number of people")
+    axes[1].set_xlim(x_lim)
+    axes[1].axhline(y=dictator_y_unhappy,linewidth=1, color='k')
+
+    unhappiness_total_all.plot(ax=axes[1])
+    y_labels_unhappy_total =axes[1].get_yticks().tolist()
+
+    setFigLinesBW(figure)
+
+    #plt.savefig("{}/fig/vis_happy_unhappy_number.pdf".format(folder),format="pdf")
+    plt.close()
+
+    figure, axes = new_fig(title="{} Figure 1".format(folder))
+
+    x_lim=[0,150]
+
+    left_y_label = "change in number of people"
+    rigt_y_label = "number of people"
+    x_label = "number of stored configurations"
+
+    axes[0].set_title("satisfaction")
+    axes[0].set_xlim(x_lim)
+    axes[0].set_xlabel(x_label)
+    axes[0].set_ylabel(left_y_label)
+    #axes[0].axhline(y=0, linewidth=1, color='k')
+    twin0 = axes[0].twinx()
+    twin0.set_ylabel(rigt_y_label)
+
+    happiness_diff.plot(ax=axes[0])
+
+    axes[1].set_title("dissatisfaction")
+    axes[1].set_xlabel(x_label)
+    axes[1].set_ylabel(left_y_label)
+    axes[1].set_xlim(x_lim)
+    #axes[1].axhline(y=0, linewidth=1, color='k')
+    twin1 = axes[1].twinx()
+    twin1.set_ylabel(rigt_y_label)
+
+
+    unhappiness_diff.plot(ax=axes[1])
+
+    y_labels_happy = list(map(lambda x: process_label(x, show_plus=True), axes[0].get_yticks().tolist()))
+    y_labels_unhappy = list(map(lambda x: process_label(x, show_plus=True), axes[1].get_yticks().tolist()))
+
+    y_labels_secondary_happy = list(map(lambda x: process_label(x + dictator_y_happy), axes[0].get_yticks().tolist()))
+    y_labels_secondary_unhappy = list(map(lambda x: process_label(x + dictator_y_unhappy), axes[1].get_yticks().tolist()))
+    
+    align_labels(axes[0], twin0)
+    align_labels(axes[1], twin1)
+
+    axes[0].set_yticklabels(y_labels_happy)
+    twin0.set_yticklabels(y_labels_secondary_happy)
+
+    axes[1].set_yticklabels(y_labels_unhappy)
+    twin1.set_yticklabels(y_labels_secondary_unhappy)
+
+
+    setFigLinesBW(figure)
+
+    #plt.show()
+
+    plt.savefig("{}/fig/vis_happy_unhappy_combined.pdf".format(folder),format="pdf")
+    plt.close()
+
+def process_label(label, show_plus=False, round_digits = 2):
+    n_label = round(label, round_digits)
+    if label > 0 and show_plus:
+        n_label = "+{}".format(n_label)
+    else:
+        n_label = "{}".format(n_label)
+    return n_label
+
+def align_labels(origin, to_align):
+    y_low, y_high =  origin.get_ylim()
+    to_align.set_ylim(y_low, y_high)
+    to_align.set_yticklabels(origin.get_yticks().tolist())
+
+
+def load_data_frame(path):
+    frame = pd.read_csv(path, index_col=0).T
+    frame.index = frame.index.astype(int)
+    return frame
+
+def new_fig(subplot_row=1, subplot_column=2,aspect_ratio=1.3 ,dpi=300, title="Untitled"):
+    figure, axes = plt.subplots(subplot_row, subplot_column, sharey=False)
+    figure.canvas.set_window_title(title)
+    figure.dpi = dpi
+    figure.set_figwidth(4 * subplot_column * aspect_ratio)
+    figure.set_figheight(4 * subplot_row)
+    plt.subplots_adjust(wspace=0.45)
+
+    return figure, axes
+
+
+def main(dir = "./out"):
+    for subdir in os.listdir(dir):
+        path = "{}/{}".format(dir,subdir)
+        if os.path.isdir(path):
+            try: 
+                save_figs(path)
+                print("Generated Figures for: {}".format(subdir))
+            except OSError as e:
+                print("Files Not Found in: {}".format(subdir))
+
+if __name__ == "__main__":
+    main()