import random
import time
import unittest

import numpy as np


def add_scalar(writer, mode, tag, num_steps, skip):
    my_writer = writer.as_mode(mode)
    scalar = my_writer.scalar(tag)
    for i in range(num_steps):
        if i % skip == 0:
            scalar.add_record(i, random.random())


def add_image(writer,
              mode,
              tag,
              num_samples,
              num_passes,
              step_cycle,
              shape=[50, 50, 3]):
    writer_ = writer.as_mode(mode)
    image_writer = writer_.image(tag, num_samples, step_cycle)

    for pass_ in xrange(num_passes):
        image_writer.start_sampling()
        for ins in xrange(2 * num_samples):
            print '.',
            index = image_writer.is_sample_taken()
            if index != -1:
                data = np.random.random(shape) * 256
                data = np.ndarray.flatten(data)
                image_writer.set_sample(index, shape, list(data))
        image_writer.finish_sampling()


if __name__ == '__main__':
    add_scalar("train", "layer/scalar0/min", 1000, 1)
    add_scalar("test", "layer/scalar0/min", 1000, 10)
    add_scalar("valid", "layer/scalar0/min", 1000, 10)

    add_scalar("train", "layer/scalar0/max", 1000, 1)
    add_scalar("test", "layer/scalar0/max", 1000, 10)
    add_scalar("valid", "layer/scalar0/max", 1000, 10)

    add_image("train", "layer/image0", 7, 10, 1)
    add_image("test", "layer/image0", 7, 10, 3)