Thouis (Ray) Jones thouis

I hereby claim:

I am thouis on github.
I am thouis (https://keybase.io/thouis) on keybase.
I have a public key whose fingerprint is A4F6 3AF2 C0E4 8CAE 7501 2BDE 2904 0D09 3557 95A4

To claim this, I am signing this object:

	import requests
	import time

	# https://github.com/twitterdev/enterprise-scripts-python/blob/main/Engagement-API/generate_user_access_tokens.py
	from generate_user_access_tokens import request_token, get_user_authorization, get_user_access_tokens, CONSUMER_KEY, CONSUMER_SECRET

	MY_ID = "PUT_YOUR_TWITTER_ID_NUMBER_HERE"


	def create_url():

	import os
	from urllib import request
	import numpy as np
	import pandas as pd

	# grab a large corpus of words, sorted by usage counts (Peter Norvig)
	if not os.path.isfile('count_1w.txt'):
	request.urlretrieve("https://norvig.com/ngrams/count_1w.txt",
	"count_1w.txt")

	import sys
	import twitter
	import time

	# see https://python-twitter.readthedocs.io/en/latest/getting_started.html

	api = twitter.Api(consumer_key=CONSUMER_KEY,
	consumer_secret=CONSUMER_SECRET,
	access_token_key=ACCESS_TOKEN,
	access_token_secret=ACCESS_SECRET)

	def depth_to_space(x, blocksize=2):
	b, k, d, r, c = x.shape
	r1 = x.reshape((b, k // (blocksize ** 2), blocksize, blocksize, d, r, c))
	r2 = r1.transpose(0, 1, 4, 5, 2, 6, 3)
	return r2.reshape((b, k // (blocksize ** 2), d, r * blocksize, c * blocksize))

	# coding=utf-8

	import numpy as np
	import scipy.sparse as sparse

	# Evaluation code courtesy of Juan Nunez-Iglesias, taken from
	# https://github.com/janelia-flyem/gala/blob/master/gala/evaluate.py

	def adapted_rand(seg, gt, all_stats=False):
	"""Compute Adapted Rand error as defined by the SNEMI3D contest [1]

	import tensorflow as tf
	from tensorflow.python import control_flow_ops

	# from http://stackoverflow.com/a/34634291
	def batch_norm(x, n_out, phase_train, scope='bn', affine=True):
	"""
	Batch normalization on convolutional maps.
	Args:
	x: Tensor, 4D BHWD input maps
	n_out: integer, depth of input maps