add recommender to repository

data_gen/gen.bat

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+python gen_diagram.py

data_gen/gen_diagram.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 = {
+        '#ff7f0e': {'marker': None, 'dash': [3,4]},
+        '#1f77b4': {'marker': None, 'dash': [1,1]},
+        '#2ca02c': {'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 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, dpi=300, title="Untitled"):
+    figure, axes = plt.subplots(subplot_row, subplot_column, sharey=True)
+    #figure.tight_layout(pad=1.5)
+    for axis in axes:
+        axis.tick_params(
+            axis="y",       # both major and minor ticks are affected
+            left=True,
+            labelleft=True,
+            labelright=True)
+    figure.canvas.set_window_title(title)
+    figure.dpi = dpi
+    figure.set_figwidth(4 * subplot_column)
+    figure.set_figheight(4 * subplot_row)
+
+    return axes
+
+
+happy_dictator = load_data_frame("./{}".format("happy_dictator.csv"))
+unhappy_dictator = load_data_frame("./{}".format("unhappy_dictator.csv"))
+
+axes = new_fig()
+
+axes[0].set_title("satisfaction")
+#axes[0].set_xlim(x_lim)
+axes[0].set_xlabel("tc")
+axes[0].set_ylabel("number of people")
+
+happy_dictator.plot(ax=axes[0])
+
+setAxLinesBW(axes[0])
+
+axes[1].set_title("dissatisfaction")
+axes[1].set_xlabel("tc")
+axes[1].set_ylabel("number of people")
+#axes[1].set_xlim(x_lim)
+unhappy_dictator.plot(ax=axes[1])
+
+setAxLinesBW(axes[1])
+
+plt.savefig("./dictator.pdf",format="pdf")
+
+
+happy_change = load_data_frame("./{}".format("happy_change.csv"))
+unhappy_change = load_data_frame("./{}".format("unhappy_change.csv"))
+
+axes = new_fig()
+
+axes[0].set_title("satisfaction change")
+#axes[0].set_xlim(x_lim)
+axes[0].set_xlabel("tc")
+axes[0].set_ylabel("number of people")
+
+happy_change.plot(ax=axes[0])
+
+setAxLinesBW(axes[0])
+
+axes[1].set_title("dissatisfaction change")
+axes[1].set_xlabel("tc")
+axes[1].set_ylabel("number of people")
+#axes[1].set_xlim(x_lim)
+unhappy_change.plot(ax=axes[1])
+
+setAxLinesBW(axes[1])
+
+plt.savefig("./change.pdf",format="pdf")
+
+
+
+
+plt.show()
+plt.close()

data_gen/happy_change.csv

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+,10,20,30,40,50,60,63,65,67,70,73,75,77,80,81,82,83,84,85,87,90,91,92,93,94
+heterogenous,0.079,0.166,0.256,0.232,0.375,0.631,0.625,0.605,0.561,0.501,0.427,0.351,0.255,0.153,0.083,0.062,-0.002,-0.048,-0.14,-0.282,-0.442,-0.568,-0.633,-0.802,-0.895
+random,0.01,0.05,0.099,0.153,0.266,0.533,0.611,0.668,0.716,0.773,0.831,0.858,0.869,0.853,0.848,0.83,0.804,0.769,0.737,0.643,0.405,0.243,0.137,-0.155,-0.337
+homogenous,0,0,0,0,0,0,0,0,0,0,0.004,0.005,0.006,0.011,0.011,0.014,0.026,0.031,0.048,0.078,0.164,0.21,0.267,0.303,0.271

data_gen/happy_dictator.csv

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+,10,20,30,40,50,60,63,65,67,70,73,75,77,80,81,82,83,84,85,87,90,91,92,93,94
+heterogenous,3.7541875,3.805,3.654,3.594,3.343,2.807,2.683,2.61,2.535,2.387,2.263,2.192,2.136,2.014,1.948,1.916,1.837,1.814,1.746,1.638,1.448,1.352,1.312,1.235,1.186
+random,3.989,3.945,3.878,3.8,3.655,3.262,3.138,3.041,2.938,2.781,2.618,2.51,2.404,2.229,2.141,2.102,2.024,1.992,1.88,1.727,1.513,1.396,1.324,1.183,1.121
+homogenous,4,4,4,4,4,4,4,4,4,4,3.996,3.995,3.994,3.989,3.988,3.985,3.971,3.963,3.944,3.905,3.756,3.596,3.443,3.025,2.674

data_gen/unhappy_change.csv

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+,10,20,30,40,50,60,63,65,67,70,73,75,77,80,81,82,83,84,85,87,90,91,92,93,94
+heterogenous,0,-0.079,-0.166,-0.256,-0.232,-0.375,-0.417,-0.474,-0.589,-0.631,-0.625,-0.605,-0.561,-0.501,-0.501,-0.464,-0.427,-0.377,-0.351,-0.255,-0.153,-0.083,-0.062,0.002,0.048
+random,0,-0.01,-0.05,-0.099,-0.153,-0.266,-0.336,-0.377,-0.441,-0.533,-0.611,-0.668,-0.716,-0.773,-0.783,-0.818,-0.831,-0.841,-0.858,-0.869,-0.853,-0.848,-0.83,-0.804,-0.769
+homogenous,0,0,0,0,0,0,0,0,0,0,0,0,0,-0.002,-0.002,-0.003,-0.004,-0.004,-0.005,-0.006,-0.011,-0.011,-0.014,-0.026,-0.031

data_gen/unhappy_dictator.csv

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+,10,20,30,40,50,60,63,65,67,70,73,75,77,80,81,82,83,84,85,87,90,91,92,93,94
+heterogenous,0,0.081,0.195,0.346,0.406,0.657,0.762,0.859,1.052,1.193,1.317,1.39,1.465,1.613,1.65,1.71,1.737,1.793,1.808,1.864,1.986,2.052,2.084,2.163,2.186
+random,0,0.011,0.055,0.122,0.2,0.345,0.448,0.513,0.604,0.738,0.862,0.959,1.062,1.219,1.253,1.34,1.382,1.451,1.49,1.596,1.771,1.859,1.898,1.976,2.008
+homogenous,0,0,0,0,0,0,0,0,0,0,0,0,0,0.002,0.002,0.003,0.004,0.004,0.005,0.006,0.011,0.012,0.015,0.029,0.037