fccoelho / bayesian-inference Goto Github PK

What steps will reproduce the problem?
1. Run runspy_test (with spy in the same folder)

What is the expected output? What do you see instead?
The two graphs and the two lists should be the same. Time 0 is the same for 
both list and is equal to the initial population.

The population of series changes before the event happens: series[1:] is 
already different from series[0] even when the first event happens later.

What version of the product are you using? On what operating system?
v0.4.12

Please provide any additional information below.

[deleted issue]

Just downloaded and installed version 0.5.7 on Windows 7 Pro 32-bit with Python 
2.6.5 installed (from the Enthought EPD 6.2-2).
I am aiming to test the lhs capability so in a Python session I tried...

import BIP.Bayes

resulting in...

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "C:\Python26\lib\site-packages\bip-0.5.7-py2.6.egg\BIP\__init__.py", line 28, in <module>
    fh = RotatingFileHandler("/tmp/BIP.log", maxBytes=500000, backupCount=2)
  File "C:\Python26\lib\logging\handlers.py", line 107, in __init__
    BaseRotatingHandler.__init__(self, filename, mode, encoding, delay)
  File "C:\Python26\lib\logging\handlers.py", line 59, in __init__
    logging.FileHandler.__init__(self, filename, mode, encoding, delay)
  File "C:\Python26\lib\logging\__init__.py", line 819, in __init__
    StreamHandler.__init__(self, self._open())
  File "C:\Python26\lib\logging\__init__.py", line 838, in _open
    stream = open(self.baseFilename, self.mode)
IOError: [Errno 2] No such file or directory: 'H:\\tmp\\BIP.log'

I did this in a cmd window in directory h:\
If I create a tmp directory on h: then the problem goes away but that really 
isn't a solution.

This is just an idea: couldn't the gillespie function use a dictionnary instead 
of a list of values?

This would allow the transition functions to be more readable (and avoid wrong 
results from switching two indexes by accident):

'''
rates = [.001,.1]
prop=[lambda r, ini:r[0]*ini[0]*ini[1],lambda r,ini:r[0]*ini[1]]
'''
(as a side matter, I think one of those r[] should be one, so that people 
recover - see line 117 of gillespie.py)

Would become

'''
rates = {'inf':.001, 'rec':.1}
#prop=[lambda r, ini:r['inf']*ini[0]*ini[1],lambda r,ini:r['rec']*ini[1]]
'''

What steps will reproduce the problem?
1. Call lhs with params > size


What is the expected output? What do you see instead?

Expected: The output matrix of samples
See:...

File "/usr/local/lib/python2.6/dist-packages/BIP/Bayes/lhs.py", line 81, in lhs
    indices=rank_restr(nvars=len(dists), smp=siz, noCorrRestr=noCorrRestr, Corrmat=corrmat)
  File "/usr/local/lib/python2.6/dist-packages/BIP/Bayes/lhs.py", line 136, in rank_restr
    Q=cholesky(numpy.corrcoef(S))
  File "/usr/lib/python2.6/dist-packages/numpy/linalg/linalg.py", line 423, in cholesky
    Cholesky decomposition cannot be computed'
numpy.linalg.linalg.LinAlgError: Matrix is not positive definite -         
Cholesky decomposition cannot be computed



What version of the product are you using? On what operating system?
Python 2.65 
NumPy 1.3
SciPy 0.7.0-2
Ubuntu 10.04
BIP 0.5.0


Please provide any additional information below.
I'm trying to create a sample size of 40, where each sample has 256 parameters. 
Should this be possible? I would imagine so. I am running a large scale 
optimization problem.

Hi,

I like your ascii histogram:-)

I have added range functionality to it.

  h=asciihist.Histogram(turns,bins=8,range=(int_mean-4,int_mean+4))
  print h.vertical(20)

The output can be reduced to interesting part only:

5.00 : ||||||||||
6.00 : |||||||||||||||||
7.00 : |||||||||||||||||||
8.00 : ||||||||||||||||||||
9.00 : |||||||||||||||||
10.00: ||||||||||||||
11.00: |||||||||||
12.00: ||||||||||||||


I have changed following lines:
class Histogram(object):
    """
    Ascii histogram
    """
    def __init__(self, data, bins=10,range=None):  <== added range 
        """
        Class constructor

        :Parameters:
            - `data`: array like object
        """
        self.data = data
        self.bins = bins
        self.range = range   <== new line
        self.h = histogram(self.data, bins=self.bins, range=self.range) <==added range here

I have attached updated asciihist.py file. Could you please consider to update 
it in the repository?

Thanks
Jirka

What steps will reproduce the problem?
1. Tried install BIP.

What is the expected output? What do you see instead?
Error message: 
inotify is not available on macosx-10.5-x86_64
error: Setup script exited with 1


What version of the product are you using? On what operating system?
Mac OS X 10.10

Please provide any additional information below.