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#!/usr/bin/env bash
#: Name        : slides2pdf
#: Date        : 2020-10-05
#: Author      : Alexandre Boucaud
#: Version     : 1.0.0
#: Description : Convert HTML slides to PDF with decktape
#: Options     : See usage() function.

## Initialize defaults
WEBSITE="https://github.com/astefanutti/decktape"

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from my_service import config

def create_application():
    engine = Engine(url=config.get_config().DB_URL)
    ...

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import numpy as np
from scipy.ndimage import binary_dilation


def isolate_galaxy(image, seg_map, galaxy_value,
                   n_dilation = 5, 
                   use_background_pixels = False, 
                   noise_factor = 0.0):
    """
    Isolate a galaxy in an image by replacing its neighbors with background noise

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import tensorflow as tf

class GAN(tf.keras.model):
    def __init__(self, discriminator, generator, latent_dim):
        super(GAN, self).__init__()
	    self.discriminator = discriminator
	    self.generator = generator
	    self.latent_dim = latent_dim
    
  	def compile(self, d_optimizer, g_optimizer, loss_fn):

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git push -o ci.skip

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# https://github.com/sharkdp/hyperfine

hyperfine --warmup 3 'fd -e jpg -uu' 'find -iname "*.jpg"'

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# from https://bernd.dev/2020/04/trim-videos-instantly/

INFILE="video.mp4"
OUTFILE="shortenedclip.mp4"

START="00:00:12.35"     # Start Time in hh:mm:ss.msec format
DURATION="00:01:05.4"   # Duration in hh:mm:ss.msec format

################## Alternative format ##################
# START="12.35"      # Start time in s.msec format     #

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ffmpeg -f gif -i dancing-baby.gif dancing-baby.mp4

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# https://pandas.pydata.org/pandas-docs/stable/reference/style.html
# https://towardsdatascience.com/style-pandas-dataframe-like-a-master-6b02bf6468b0

import pandas as pd

# Option examples
pd.set_option('precision', 4)
pd.set_option('max_rows', 10)
pd.set_option('max_columns', 7)
pd.set_option("display.max_colwidth", -1)

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import numpy as np
import matplotlib.pyplot as plt

N = 10
colors = plt.cm.viridis(np.linspace(0.25, 1.0, N))

x = np.linspace(0, 1, 30)
powers = np.arange(N) + 1

for power, color in zip(powers, colors):