joezuntz

import PIL.Image
import matplotlib
matplotlib.use("Agg")
import numpy as np
import pylab as pl

def make_color_maps():
	x=np.arange(0.,1.,0.01)
	z=np.zeros_like(x)
	R=list(zip(x,z,z))

joezuntz

#!/usr/bin/env python

print "This script has been moved to https://github.com/joezuntz/plot"

joezuntz

from numpy import sqrt,exp,log,pi
import numpy as np
import pymc

#Example script showing how to fit 


#Generate some fake data to fit.
#Use fixed mean and variance
true_mu = 2.4

joezuntz

import os
import pymc
database_file = "mc.pickle"
number_samples = 1000
a = pymc.Normal("a",mu=0, tau=1)
b = pymc.Normal("b",mu=0, tau=1)
mu = a+b
c = pymc.Normal("c", mu=mu, tau=1, observed=True, value=0.5)

joezuntz

Here are some short programming maxims for new science PhD students, to correct the most egregious errors made by people 
trained in science but not in programming.  Some from http://www.theexclusive.org/2012/08/principles-of-research-code.html and http://arkitus.com/PRML/


 - There is no tax on variable name length - make them as long as you like.

 - People will come to your code not knowing your nomenclature.

 - Don't write programs, write functions.

joezuntz

#Needs Python Wikipedia Robot Framework
import wikipedia
import sys

p=wikipedia.Page('en','List_of_towns_in_England')
town_pages=p.linkedPages()[7:-9]

class LatLonError(ValueError):
	pass

joezuntz

diff --git a/emcee/utils.py b/emcee/utils.py
index c5685d3..0aa63c7 100644
--- a/emcee/utils.py
+++ b/emcee/utils.py
@@ -163,19 +163,25 @@ if MPI is not None:
             F = _function_wrapper(function)
 
             # Tell all the workers what function to use.
+            requests = []
+

joezuntz

diff --git a/emcee/utils.py b/emcee/utils.py
index ca5fc30..0f33d2a 100644
--- a/emcee/utils.py
+++ b/emcee/utils.py
@@ -160,17 +160,23 @@ if MPI is not None:
                 self.wait()
                 return
 
-            F = _function_wrapper(function)
+            if function is not self.function:

joezuntz

int point_in_polygon(int n, float *vertx, float *verty, float testx, float testy)
{
    int i, j, c = 0;
    for (i = 0, j=n-1; i < n; j = i++) {
        if ( ((verty[i]>testy) != (verty[j]>testy)) &&
            (testx < (vertx[j]-vertx[i]) * (testy-verty[i]) / (verty[j]-verty[i]) + vertx[i]) )
            c = !c;
    }
    return c;
}

joezuntz

import numpy as np

def simulate_schechter_distribution(self, alpha, L_star, L_min, N):
		""" 
        Generate N samples from a Schechter distribution, which is like a gamma distribution 
        but with a negative alpha parameter and cut off on the left somewhere above zero so that
        it converges.
        
        If you pass in stupid enough parameters then it will get stuck in a loop forever, and it
        will be all your own fault.