cs224

import math
import pyjags
import numpy as np
import pandas as pd

np.random.seed(0)
np.set_printoptions(precision=3)

def pyjags_trace():

buo

#!/bin/bash

sudo pip install jupyter
jupyter notebook --generate-config
sed -i "s/# c.NotebookApp.port = 8888/c.NotebookApp.port = $PORT/" ~/.jupyter/jupyter_notebook_config.py
sed -i "s/# c.NotebookApp.ip = 'localhost'/c.NotebookApp.ip = '0.0.0.0'/" ~/.jupyter/jupyter_notebook_config.py

brandonwillard

from scipy import stats
from theano.tensor.nlinalg import det, matrix_inverse, trace, eigh

from pymc3 import transforms
from pymc3.distributions.distribution import Continuous, Discrete, draw_values, generate_samples
from pymc3.distributions.special import gammaln, multigammaln
from pymc3.distributions.dist_math import bound, logpow, factln

class MvNormal(Continuous):
    r"""

MatsuuraKentaro

data {
  int N;
  int M;
  real<lower=0> Y[N];
}

parameters {
  real<lower=0> mu;
  real<lower=0> phi;
  real<lower=1, upper=2> theta;

johnpauljanecek

f0k

# -*- coding: utf-8 -*-

"""
Preliminary implementation of batch normalization for Lasagne.
Does not include a way to properly compute the normalization factors over the
full training set for testing, but can be used as a drop-in for training and
validation.

Author: Jan Schlüter
"""

ramhiser

from datetime import datetime, timedelta

def date_range(start, end, step=7, date_format="%m-%d-%Y"):
    """
    Creates generator with a range of dates.
    The dates occur every 7th day (default).
    
    :param start: the start date of the date range
    :param end: the end date of the date range
    :param step: the step size of the dates

jseabold

import os
import calendar

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.ticker import FixedLocator, FixedFormatter
import pandas as pd
import seaborn as sns

to_colors = lambda x : x/255.

minrk

a=1

takluyver

Copy nbflatten.py to somewhere on $PATH. Then, in the root of a git repository, run these commands:

echo "*.ipynb diff=ipynb" >> .gitattributes 
git config diff.ipynb.textconv nbflatten.py

When you change a notebook and run git diff, you'll see the diff of flattened, simplified notebooks, rather than the full JSON. This does lose some information (metadata, non-text output), but it makes it easier to see simple changes in the notebook.

This doesn't help with merging conflicting changes in notebooks. For that, see nbdiff.org.