flowtron_plotting_utils.py

###############################################################################
#
#  Copyright (c) 2020, NVIDIA CORPORATION. All rights reserved.
#  Licensed under the Apache License, Version 2.0 (the "License");
#  you may not use this file except in compliance with the License.
#  You may obtain a copy of the License at
#
#      http://www.apache.org/licenses/LICENSE-2.0
#
#  Unless required by applicable law or agreed to in writing, software
#  distributed under the License is distributed on an "AS IS" BASIS,
#  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
#  See the License for the specific language governing permissions and
#  limitations under the License.
#
###############################################################################
import matplotlib
matplotlib.use("Agg")
import matplotlib.pylab as plt
import numpy as np


def save_figure_to_numpy(fig):
    # save it to a numpy array.
    data = np.fromstring(fig.canvas.tostring_rgb(), dtype=np.uint8, sep='')
    data = data.reshape(fig.canvas.get_width_height()[::-1] + (3,))
    return data


def plot_alignment_to_numpy(alignment, info=None):
    fig, ax = plt.subplots(figsize=(6, 4))
    im = ax.imshow(alignment, aspect='auto', origin='lower',
                   interpolation='none')
    fig.colorbar(im, ax=ax)
    xlabel = 'Decoder timestep'
    if info is not None:
        xlabel += '\n\n' + info
    plt.xlabel(xlabel)
    plt.ylabel('Encoder timestep')
    plt.tight_layout()

    fig.canvas.draw()
    data = save_figure_to_numpy(fig)
    plt.close()
    return data


def plot_gate_outputs_to_numpy(gate_targets, gate_outputs):
    fig, ax = plt.subplots(figsize=(12, 3))
    ax.scatter(range(len(gate_targets)), gate_targets, alpha=0.5,
               color='green', marker='+', s=1, label='target')
    ax.scatter(range(len(gate_outputs)), gate_outputs, alpha=0.5,
               color='red', marker='.', s=1, label='predicted')

    plt.xlabel("Frames (Green target, Red predicted)")
    plt.ylabel("Gate State")
    plt.tight_layout()

    fig.canvas.draw()
    data = save_figure_to_numpy(fig)
    plt.close()
    return data