louiskirsch

import tensorflow as tf
import tensorflow.contrib as tfc
import numpy as np
import matplotlib.pyplot as plt
import observations
from functools import lru_cache

tf.reset_default_graph()

train_data, test_data = observations.cifar10('data/cifar',)

louiskirsch

class RingBuffer:

    def __init__(self, scope_name, components, size):
        """
        Create a new ring buffer of size `size`.
        Each item in the ring buffer is a tuple of variables of size `len(components)`.
        
        :param scope_name: A scope name for the newly created variables
        :param components: Defines the type of items in the buffer. An iterable of tuples (name: str, shape: Iterable, dtype)
        :param size: The maximum size of the buffer

louiskirsch

#!/bin/bash

name=${1:-slides}
replace='s/^([^ ].*)/# \1§/g; s/^ {8}([^ ].*)/§### \1§/g; s/^ {4}([^ ].*)/§## \1§/g; s/ +(\![[])/\1/g; s/ {12}([^ ]+)/- \1/g; s/\![(]([0-9-]+)[)]/\1/g'

sed -E "$replace" <&0 | tr "§" "\n"  > $name.md
markdown-to-slides -d $name.md -o $name.html
open $name.html

louiskirsch

fig, ax = plt.subplots()
ax.set_title('Figure 2 - Progressing samples')
ax.set_xlabel('Erruption length')
ax.set_ylabel('Time since last erruption')
ax.set_xlim((np.min(x[:, 0]), np.max(x[:, 0])))
ax.set_ylim((np.min(x[:, 1]), np.max(x[:, 1])))
line, = ax.plot([], [])

def init():
    line.set_data([], [])

louiskirsch

import matplotlib.pyplot as plt
import numpy as np
import time

plt.rcParams['toolbar'] = 'None'

fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)

def draw():