Valentine Svensson vals

## gist:2541ea899810eb561ce1

      
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                vals
                / gist:2541ea899810eb561ce1
            
            
              Created
              May 5, 2015 23:09
            
              
                us state map
              
          
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## measles.ipynb

      
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                / measles.ipynb
            
            
              Created
              April 13, 2015 14:57
            
              
                Time series plot for measles incidence
              
          
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## gist:fa2aa17c1fc349598527
{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {

## Clusters from dendrograms.ipynb

      
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                vals
                / Clusters from dendrograms.ipynb
            
            
              Created
              June 28, 2014 23:37
            
              
                IPython notebook illustrating how to extract cluster elements in Python Dendrograms
              
          
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## stacked by factor.ipynb

      
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                / stacked by factor.ipynb
            
            
              Last active
              August 29, 2015 14:02
            
              
                Stacked by factor
              
          
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## estimate_size_factors.py
def estimate_size_factor(counts):

    #COUNTS = GENES (rows) x CELLS (columns)
    genes = counts[:, 0]
    #ONLY COUNTS WITHOUT HEADER NOR GENES
    counts = numpy.array(counts[1:, 1:], dtype = int)

    #DONT REMOVE INFITE VALUES AS IT CAUSES PROBLEMS
    log_counts = numpy.log(counts)


## readroi.py
# Copyright: Luis Pedro Coelho <luis@luispedro.org>, 2012
# License: MIT
import numpy as np


def read_roi(fileobj):
    """
    points = read_roi(fileobj)

    Read ImageJ's ROI format

## dev_null.ipynb

      
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              Created
              April 3, 2013 11:21
            
              
                Escape from /dev/null IPython Notebook
              
          
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## number1.py
from random import shuffle

slices = [1,2,3] * 4 + [20, 25, 30] * 2
shuffle(slices)

fig = plt.figure(figsize=[10, 10])
ax = fig.add_subplot(111)

cmap = plt.cm.prism
colors = cmap(np.linspace(0., 1., len(slices)))

## Lab 1 IPython Notebook
{
 "metadata": {
  "name": "Lab 1"
 },
 "nbformat": 3,
 "nbformat_minor": 0,
 "worksheets": [
  {
   "cells": [
    {
	{
	"cells": [
	{
	"cell_type": "code",
	"execution_count": 2,
	"metadata": {
	"collapsed": false
	},
	"outputs": [
	{
	def estimate_size_factor(counts):

	#COUNTS = GENES (rows) x CELLS (columns)
	genes = counts[:, 0]
	#ONLY COUNTS WITHOUT HEADER NOR GENES
	counts = numpy.array(counts[1:, 1:], dtype = int)

	#DONT REMOVE INFITE VALUES AS IT CAUSES PROBLEMS
	log_counts = numpy.log(counts)
	# Copyright: Luis Pedro Coelho <luis@luispedro.org>, 2012
	# License: MIT
	import numpy as np


	def read_roi(fileobj):
	"""
	points = read_roi(fileobj)

	Read ImageJ's ROI format
	from random import shuffle

	slices = [1,2,3] * 4 + [20, 25, 30] * 2
	shuffle(slices)

	fig = plt.figure(figsize=[10, 10])
	ax = fig.add_subplot(111)

	cmap = plt.cm.prism
	colors = cmap(np.linspace(0., 1., len(slices)))
	{
	"metadata": {
	"name": "Lab 1"
	},
	"nbformat": 3,
	"nbformat_minor": 0,
	"worksheets": [
	{
	"cells": [
	{