mattbierbaum

from distutils.core import setup, Extension
import numpy
import os

os.environ['CC'] = 'g++';
setup(name='matt_simple_test', version='1.0', ext_modules =[Extension('_simple',
 ['simple.cc', 'simple.i'], include_dirs = [numpy.get_include(),'.'])])

mattbierbaum

# standard compile options for the c++ executable
FLAGS = -fPIC

# the python interface through swig
PYTHONI = -I/usr/include/python2.6/
PYTHONL = -Xlinker -export-dynamic

# default super-target
all: 
	g++ -fPIC -c kitty.cc -o kitty.o

mattbierbaum

import sys
import time
import numpy as np

#=============================================================================
# Progress bar
#=============================================================================
class ProgressBar(object):
    def __init__(self, num, label='Progress', value=0, screen=79,
            time_remaining=True, bar=True, bar_symbol='=', bar_caps='[]',

mattbierbaum

import pylab as pl
import numpy as np

from matplotlib.colors import Normalize
from matplotlib.collections import LineCollection

def plot_colored_curve(x, y, t=None, linewidth=2, drawpoints=False, cmap=pl.cm.copper):
    """
    Plot a curve that is colored based on index or 'time' value at each point
    in that curve. [x,y,t] are the values y(x, t) which will be plotted. They

mattbierbaum

import os
import uuid
from celery import signals
from celery import Celery, Task
from celery.utils.log import get_task_logger

app = Celery('simple_celery')
logger = get_task_logger(__name__)

class Worker(object):

mattbierbaum

import numpy as np
import matplotlib.pylab as pl

class Encirculator(object):
    def __init__(self, image, cmap='bone', size=14, max_number_circles=100):
        """
        A class which builds a matplotlib interface to facilitate the drawing
        of circles on an image (typically to measure the sizes and positions of
        objects). To create the circles, you label the edges with points via
        mouse clicks, and a fitted circle is drawn over the image to guide

mattbierbaum

import numpy as np
import matplotlib.pyplot as pl
from matplotlib import cm
from matplotlib.colors import Normalize
from matplotlib.widgets import Slider

def rescale(xs, ys, params, values):
    """
    An example scaling_func that can be provided to interactive_collapse.  This
    scales the zombie data by the variables alphac, sigma, tau for curves at