w2v_vis

Complexity

Total Complexity

3

Size/Duplication

Total Lines	43
Duplicated Lines	0 %

Importance

Changes

0

2 Methods

Rating	Name	Duplication	Size	Complexity
A	tracking_policy_agendas.word2vec.w2v_vis.reduce_dimensions()	11	11	1
A	tracking_policy_agendas.word2vec.w2v_vis.plot_with_matplotlib()	11	11	2

from sklearn.manifold import TSNE

Missing module docstring

import matplotlib.pyplot as plt
import numpy as np
import random

standard import "import random" should be placed before "from sklearn.manifold import TSNE"

def reduce_dimensions(w2v_model):

Missing function or method docstring

This code seems to be duplicated in your project.

    num_dimensions = 2
    vectors = np.asarray(w2v_model.wv.vectors)
    labels = np.asarray(w2v_model.wv.index_to_key)

labels is re-defining a name which is already available in the outer-scope (previously defined on line 41).

    tsne = TSNE(n_components=num_dimensions, random_state=42)
    vectors = tsne.fit_transform(vectors)

    x_evals = [v[0] for v in vectors]

x_evals is re-defining a name which is already available in the outer-scope (previously defined on line 41).

    y_evals = [v[1] for v in vectors]

y_evals is re-defining a name which is already available in the outer-scope (previously defined on line 41).

    return x_evals, y_evals, labels


def plot_with_matplotlib(x_evals, y_evals, labels):

y_evals is re-defining a name which is already available in the outer-scope (previously defined on line 41).

Missing function or method docstring

This code seems to be duplicated in your project.

labels is re-defining a name which is already available in the outer-scope (previously defined on line 41).

x_evals is re-defining a name which is already available in the outer-scope (previously defined on line 41).

    random.seed(0)

    plt.figure(figsize=(12, 12))
    plt.scatter(x_evals, y_evals)
    indices = list(range(len(labels)))
    selected_indices = random.sample(indices, 25)
    for i in selected_indices:
        plt.annotate(labels[i], (x_evals[i], y_evals[i]))
    plt.savefig('w2v_plot.png')
    plt.show()


if __name__ == '__main__':

This code seems to be duplicated in your project.

    from .w2v_corpus import W2VCorpus
    import pandas as pd
    import gensim.models
    corpus = pd.read_excel('test_corpus.xlsx')
    print(corpus.head())
    corpus = W2VCorpus(list(corpus[0]))
    model = gensim.models.Word2Vec(sentences=corpus)
    x_evals, y_evals, labels = reduce_dimensions(model)
    plot_with_matplotlib(x_evals, y_evals, labels)