henrik

tmux cheatsheet

As configured in my dotfiles.

start new:

tmux

start new with session name:

wolever

-- Functions to create and draw histograms with PostgreSQL.
--
-- psql# WITH email_lengths AS (
--    -#    SELECT length(email) AS length
--    -#    FROM auth_user
--    -#    LIMIT 100
--    -# )
--    -# SELECT * FROM show_histogram((SELECT histogram(length, 0, 32, 6) FROM email_lengths))
--  bucket |                range                | count |              bar               |             cumbar             | cumsum |         cumpct         
-- --------+-------------------------------------+-------+--------------------------------+--------------------------------+--------+------------------------

hellpanderrr

from scipy.spatial import Delaunay, ConvexHull
import networkx as nx
 
points = [ [0,0],[0,50],[50,50],[50,0],[0,400],[0,450],[50,400],[50,450],[700,300],[700,350],[750,300],[750,350],
          [900,600],[950,650],[950,600],[900,650]
]
def concave(points,alpha_x=150,alpha_y=250):
    points = [(i[0],i[1]) if type(i) <> tuple else i for i in points]
    de = Delaunay(points)

chantastic

Hi Nicholas,

I saw you tweet about JSX yesterday. It seemed like the discussion devolved pretty quickly but I wanted to share our experience over the last year. I understand your concerns. I've made similar remarks about JSX. When we started using it Planning Center, I led the charge to write React without it. I don't imagine I'd have much to say that you haven't considered but, if it's helpful, here's a pattern that changed my opinion:

The idea that "React is the V in MVC" is disingenuous. It's a good pitch but, for many of us, it feels like in invitation to repeat our history of coupled views. In practice, React is the V and the C. Dan Abramov describes the division as Smart and Dumb Components. At our office, we call them stateless and container components (view-controllers if we're Flux). The idea is pretty simple: components can't

jsanz

On this example I pass a vizjson object that defines a leaflet map with a layer, legend, tooltip and infowindows.

karpathy

"""
Minimal character-level Vanilla RNN model. Written by Andrej Karpathy (@karpathy)
BSD License
"""
import numpy as np

# data I/O
data = open('input.txt', 'r').read() # should be simple plain text file
chars = list(set(data))
data_size, vocab_size = len(data), len(chars)

CMCDragonkai

#!/usr/bin/env bash

typeofvar () {

    local type_signature=$(declare -p "$1" 2>/dev/null)

    if [[ "$type_signature" =~ "declare --" ]]; then
        printf "string"
    elif [[ "$type_signature" =~ "declare -a" ]]; then
        printf "array"

myme5261314

import tensorflow as tf
import numpy as np
import input_data
import Image
from util import tile_raster_images


def sample_prob(probs):
    return tf.nn.relu(
        tf.sign(

ottokart

# Tiny example of 3-layer nerual network with dropout in 2nd hidden layer
# Output layer is linear with L2 cost (regression model)
# Hidden layer activation is tanh

import numpy as np

n_epochs = 100
n_samples = 100
n_in = 10
n_hidden = 5

Cospel

#http://blog.echen.me/2011/07/18/introduction-to-restricted-boltzmann-machines/
#https://www.tensorflow.org/versions/r0.7/api_docs/python/constant_op.html#random_uniform

import tensorflow as tf
import numpy as np
import input_data
import Image
from util import tile_raster_images