t_SNE_plot.py

%matplotlib inline
import plotly.offline as py
py.init_notebook_mode(connected=True)
import plotly.graph_objs as go
import plotly.tools as tls

from sklearn.manifold import TSNE
tsne = TSNE(
    n_components=3,
    init='random', # pca
    random_state=101,
    method='barnes_hut',
    n_iter=500,
    verbose=2
).fit_transform(img_mat)

trace1 = go.Scatter3d(
    x=tsne[:,0],
    y=tsne[:,1],
    z=tsne[:,2],
    mode='markers',
    marker=dict(
        sizemode='diameter',
        #color = preprocessing.LabelEncoder().fit_transform(all_image_types),
        #colorscale = 'Portland',
        #colorbar = dict(title = 'images'),
        line=dict(color='rgb(255, 255, 255)'),
        opacity=0.9
    )
)

data=[trace1]
layout=dict(height=800, width=800, title='3D embedding of images')
fig=dict(data=data, layout=layout)
py.iplot(fig, filename='3DBubble')