CODEWITHSUNDEEP
pythonseaborn
eneko valero
eneko valero

Reputation: 459

Plotting VAE predicted data using seaborn

I am trying to plot in a scatter format some data I have predicted with the decoder of a VAE I've developed.

This might be very basic. However, I would like to know how should I plot the array I've predicted with a scatterplot.

new_data = vae.decoder.predict(np.random.normal(0,1,size=(1, latent_dim, 1)))

array([[[0.4776226 ],
    [0.47153735],
    [0.4817254 ],
    [0.48054865],
    [0.45594737],
    [0.48623624],
    [0.47953185],
    [0.47151   ],
    [0.4822226 ],
    [0.46702865],
    [0.50809085]]], dtype=float32)

I am using this question. However when I do: df = pd.DataFrame(new_data) I get: ValueError: Must pass 2-d input. shape=(1, 11, 1) Which is the proper way to plot this using Seaborn?

Upvotes: 0

Views: 52

Answers (1)

DPM
DPM

Reputation: 945

Your data is currently a 3d array and it requires a 2d array, so you will need to reshape your array:

new_data = vae.decoder.predict(np.random.normal(0,1,size=(1, latent_dim, 1)))
reshaped_data = new_data.reshape((1, 11))

Upvotes: 1

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