Marc Laugharn mlaugharn

## gist:31656564a35509a17295ae2e7695a068
algebraic data types
- adt
- opeltre/fp

typechecking:
- mypy
- dry-python/returns
- life4/deal

typeclasses:

## State 2018 populations.csv

          
            State
            2018 Population

            
              California
              39776830

            
              Texas
              28704330

            
              Florida
              21312211

            
              New York
              19862512

            
              Pennsylvania
              12823989

            
              Illinois
              12768320

            
              Ohio
              11694664

            
              Georgia
              10545138

            
              North Carolina
              10390149

## .tmux.conf
set -g default-shell /usr/bin/zsh
set -g default-command /usr/bin/zsh
set -g default-terminal "screen-256color"

# act like GNU screen
unbind C-b
set -g prefix C-a

set -g base-index 1
set -s escape-time 0

## filters.py
# much (some) of this code isn't mine
import PIL.Image, numpy, scipy.misc, scipy.ndimage, scipy.spatial
import time, sys, random, math, functools, collections

# image = PIL.Image.open("4.2.06.tiff") # sailboat on lake
# image = PIL.Image.open("lena.tiff") # lena
pixel_definition = ["r", "g", "b"] # definition of pixel

# neighborhood_kernel = numpy.array([[1, 1, 1],
#    					             [1, 1, 1],
	algebraic data types
	- adt
	- opeltre/fp

	typechecking:
	- mypy
	- dry-python/returns
	- life4/deal

	typeclasses:
	State	2018 Population
	California	39776830
	Texas	28704330
	Florida	21312211
	New York	19862512
	Pennsylvania	12823989
	Illinois	12768320
	Ohio	11694664
	Georgia	10545138
	North Carolina	10390149
	set -g default-shell /usr/bin/zsh
	set -g default-command /usr/bin/zsh
	set -g default-terminal "screen-256color"

	# act like GNU screen
	unbind C-b
	set -g prefix C-a

	set -g base-index 1
	set -s escape-time 0
	# much (some) of this code isn't mine
	import PIL.Image, numpy, scipy.misc, scipy.ndimage, scipy.spatial
	import time, sys, random, math, functools, collections

	# image = PIL.Image.open("4.2.06.tiff") # sailboat on lake
	# image = PIL.Image.open("lena.tiff") # lena
	pixel_definition = ["r", "g", "b"] # definition of pixel

	# neighborhood_kernel = numpy.array([[1, 1, 1],
	# [1, 1, 1],