marc-hanheide / bayesian-inference Goto Github PK
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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.
Original issue reported on code.google.com by [email protected]
on 30 Oct 2014 at 1:50
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]]
'''
Original issue reported on code.google.com by [email protected]
on 22 Nov 2010 at 6:21
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.
Original issue reported on code.google.com by [email protected]
on 25 Jul 2010 at 8:03
[deleted issue]
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.
Original issue reported on code.google.com by [email protected]
on 26 Aug 2010 at 11:09
Attachments:
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.
Original issue reported on code.google.com by [email protected]
on 8 Nov 2011 at 10:23
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
Original issue reported on code.google.com by [email protected]
on 16 Aug 2010 at 9:43
Attachments:
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