コード例 #1
0
ファイル: scatter_plots.py プロジェクト: slyfocks/congress
def make_scatter(congress_num):
    fig = plt.figure(1)
    arr = hs.make_similarity_array(congress_num)
    cls, means, steps = mlpy.kmeans(arr, k=2, plus=True)
    members = hs.members(congress_num)
    extreme_index1 = members.index(most_least.most_extreme(congress_num, 10)[0])
    extreme_index2 = list(arr[extreme_index1]).index(min(arr[extreme_index1]))
    if members[extreme_index1].split(' ')[1] == 'R':
        #change color so Democrats are blue and Republicans are red
        for i in range(len(cls)):
            if cls[i] == 0:
                cls[i] = 1
            else:
                cls[i] = 0
        plot = plt.scatter(arr[:, extreme_index1], arr[:, extreme_index2], c=cls, alpha=0.75)
        plt.xlabel("Conservatism (Cosine similarity to most conservative member, "
                   + members[extreme_index1].split(' ')[0] + ")")
        plt.ylabel("Liberalism (Cosine similarity to most liberal member, "
                   + members[extreme_index2].split(' ')[0] + ")")
    else:
        plot = plt.scatter(arr[:, extreme_index2], arr[:, extreme_index1], c=cls, alpha=0.75)
        plt.ylabel("Liberalism (Cosine similarity to most liberal member, "
                   + members[extreme_index1].split(' ')[0] + ")")
        plt.xlabel("Conservatism (Cosine similarity to most conservative member, "
                   + members[extreme_index2].split(' ')[0] + ")")
    return
コード例 #2
0
ファイル: most_least.py プロジェクト: slyfocks/congress
def most_unique(congress_num, knn):
    arr = hs.make_similarity_array(congress_num)
    congresspeople = hs.members(congress_num)
    #takes k-nearest members in cos similarity
    sorted_similarity = [sorted(arr[i])[-knn:] for i in range(len(arr[0]))]
    sums = [sum(sorted_similarity[i]) for i in range(len(sorted_similarity))]
    sorted_unique = sorted(range(len(sums)), key=lambda k: sums[k])
    unique_rank = [(congresspeople[index]) for index in sorted_unique]
    return unique_rank
コード例 #3
0
ファイル: most_least.py プロジェクト: slyfocks/congress
def most_extreme(congress_num, knn):
    arr = hs.make_similarity_array(congress_num)
    congresspeople = hs.members(congress_num)
    #takes k-furthest members in cos similarity
    sorted_similarity = [sorted(arr[i])[:knn] for i in range(len(arr[0]))]
    #sums those similarities
    sums = [sum(sorted_similarity[i]) for i in range(len(sorted_similarity))]
    #sorts members from lowest to highest
    sorted_extreme = sorted(range(len(sums)), key=lambda k: sums[k])
    extreme_rank = [(congresspeople[index]) for index in sorted_extreme]
    return extreme_rank