I just installed mvpa2 module on my ubuntu 14.04, Python 2.7.6. following the instruction at http://www.pymvpa.org/installation.html using sudo aptitude install python-mvpa2
Command import mvpa2 works well, but when I run from mvpa2.suite import * , I get the followin warning in my terminal:
/usr/local/lib/python2.7/dist-packages/sklearn/pls.py:7: DeprecationWarning: This module has been moved to cross_decomposition and will be removed in 0.16
"removed in 0.16", DeprecationWarning)
And also fallowing error:
TypeError: __init__() got an unexpected keyword argument 'rho'
Appreciate your help!
actually this warning comes from the import done by mdp, which PyMVPA optionally uses... you can safely ignore it (no upgrade of PyMVPA would help anyhow), because even if it gets completely removed, then mdp would simply skip that import and you would remain 'golden'.
That problem is due to an incompatibility of the python-mvpa2 and scikit-learn versions. You can check more details on that in this page, because depends on which scikit-learn version you have what will be the parameters to call a given function.
A short solution is to uninstall your python-mvpa2 and scikit-learn, and install them directly from their github repos:
[python-mvpa2] https://github.com/PyMVPA
[scikit-learn] https://github.com/scikit-learn/scikit-learn
I just did it and now the example doc/examples/som.py (for my case) is working perfectly.
Related
I am trying to import win32api in python 2.7.9. i did the "pip install pypiwin32" and made sure all the files were intalled correctly (i have the win32api.pyd under ${PYTHON_HOME}\Lib\site-packages\win32). i also tried coping the files from C:\Python27\Lib\site-packages\pywin32_system32 to C:\Python27\Lib\site-packages\win32. I also tried restarting my pc after each of these steps but nothing seems to work! i still get the error 'No module named 'win32api''
Well, turns out the answer is upgrading my python to 3.6.
python 2.7 seems to old to work with outside imports (I'm just guessing here, because its not the first time I'm having an import problem)
hope it helps :)
I would like to have a script invoke numpy from a c++ embedded python runtime by setting the runtime path to know about the numpy module located within site-packages.
However I get the error:
cannot import name 'multiarray'
from \Lib\site-packages\numpy\core__init_.py on the line
from . import multiarrray
I have tried to set the os.path to be xxx\numpy\core but it still cannot seem to find the multiarray.pyd file during the import statement
I have read through similar questions posed but none of the answers seem relevant to my case.
I am using Python 3.4.4 (32 bit) and have installed Numpy 1.11.1 using the wheel
numpy-1.11.1-cp34-none-win32.whl
python -m pip install numpy-1.11.1-cp34-none-win32.whl
Completed without any errors.
Seems like the failure message maybe more general than just an incomplete PYTHONPATH?
Also think it might be broader than Numpy in that ANY .pyd based package that is imported from the embedded environment will have this problem?
Any help appreciated.
Did you ensure all your NumPy includes: \numpy\core\include\numpy\ were present during the build? That's the only time I get those types of errors was if the build couldn't find all the NumPy includes... although during embedding I found that the numpy entire directory (already built on your build machine) has to be inside a directory under Py_SetPath(python35.lib;importlibs); assuming importlibs is a directory with NumPy inside and anything else you want to bundle.
Seems like the answer was to install python 3.4.1 to match the python34.dll version of 3.4.1.
After I installed BeautifulSoup, whenever I run my Python in from the command line, this warning comes out:
D:\Application\python\lib\site-packages\beautifulsoup4-4.4.1-py3.4.egg\bs4\__init__.py:166:
UserWarning: No parser was explicitly specified, so I'm using the best
available HTML parser for this system ("html.parser"). This usually isn't a
problem, but if you run this code on another system, or in a different
virtual environment, it may use a different parser and behave differently.
To get rid of this warning, change this:
BeautifulSoup([your markup])
to this:
BeautifulSoup([your markup], "html.parser")
I have no idea why it comes out and how to solve it.
The solution to your problem is clearly stated in the error message. Code like the below does not specify an XML/HTML/etc. parser.
BeautifulSoup( ... )
In order to fix the error, you'll need to specify which parser you'd like to use, like so:
BeautifulSoup( ..., "html.parser" )
You can also install a 3rd party parser if you'd like.
Documentation recommends that you install and use lxml for speed.
BeautifulSoup(html, "lxml")
If you’re using a version of Python 2 earlier than 2.7.3, or a version
of Python 3 earlier than 3.2.2, it’s essential that you install lxml
or html5lib–Python’s built-in HTML parser is just not very good in
older versions.
Installing LXML parser
On Ubuntu (debian)
apt-get install python-lxml
Fedora (RHEL based)
dnf install python-lxml
Using PIP
pip install lxml
In my opinion, the previous posts did not answer the question.
Yes, as everyone said, you can remove the warning by specifying the parser.
And as pointed by the documentation, it is a best-practice for performances 1 and for consistency 2.
But in some cases, you want to silence the warning... Hence this post.
since BeautifulSoup 4 rev 460, the warning message does not appear in interactive (REPL) mode
there are more generalist answers at: How to disable Python warnings? to control Python warnings (TL;DL: PYTHONWARNINGS=ignore or -Wignore)
suppressing the warning explicitly (bs4 ≥ rev 569) by adding to your code:
import warnings
from bs4 import GuessedAtParserWarning
warnings.filterwarnings('ignore', category=GuessedAtParserWarning)
cheating by letting bs4 think you provided the parser, i.e.:
bs4.BeautifulSoup(
your_markup,
builder=bs4.builder_registry.lookup(*bs4.BeautifulSoup.DEFAULT_BUILDER_FEATURES)
)
For HTML parser, you need to install html5lib, run:
pip install html5lib
then add html5lib in the BeautifulSoup method:
htmlDoc = bs4.BeautifulSoup(req1.text, 'html5lib')
print(htmlDoc)
I'm running Python 2.7.11 under Anaconda 2.0.0 (x86_64) on a MacBook.
Some weeks ago, as part of a process of getting OpenCV working, I downgraded numpy from wherever it was (unfortunately/stupidly I have no record) to 1.7.1. I seem to remember this was necessary, and I do not want OpenCV to stop working, so I'm pretty sure I should now leave numpy where it is.
However, today I discovered that this has broken my matplotlib/pylab. When I do import pylab I get the following:
---------------------------------------------------------------------------
RuntimeError Traceback (most recent call last)
RuntimeError: module compiled against API version 9 but this version of numpy is 7
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
...
...
ImportError: numpy.core.multiarray failed to import
My question, therefore, is: how do I install (or roll back to) a version of matplotlib that's compatible with my existing numpy, without disturbing my existing numpy?
Here's where I've got so far: based on related conda questions on SO, I looked at the output of conda list --revisions matplotlib which includes:
...
2016-03-28 17:16:36 (rev 6)
conda {3.8.3 -> 4.0.5}
conda-env {2.0.1 -> 2.4.5}
numpy {1.8.1 -> 1.7.1}
...
Now I'm not sure how to interpret this but given the numpy version number looks like it's actually falling in contrast to all the other entries here, this sounds to me like a promising, "in March 2016 matplotlib realized it could fall back to an earlier version of its numpy dependency". However, when I ask for this revision:
conda install --revision=6 matplotlib
I'm told I already have it, and that its dependency is numpy 1.8:
Fetching package metadata: ....
# All requested packages already installed.
# packages in environment at /Users/jez/anaconda:
#
matplotlib 1.3.1 np18py27_1 <unknown>
So from here I'm not sure how to proceed. I've tentatively played with some variations on conda install matplotlib, but it clearly wants to mess with my numpy at the same time, so I have never pressed y. Equally clearly, I'm out of my depth in conda, so would really appreciate your help.
You can specify the exact versions of any libraries you want in the conda install command. For example:
$ conda install numpy=1.7.1 matplotlib=1.3
If the versions are incompatible, the command will give you an error specifying exactly what the incompatibility is.
this is my first stack overflow question so please pardon any ignorance about the forum on my part.
I am using python 2.7.6 64 bit and pandas 0.13.1-1 from Enthought Canopy 1.3.0.1715 on a win 7 machine. I have numpy 1.8.0-1 and numexpr 2.2.2-2.
I have inconsistent error behviour running the following on a pandas series of 10,000 numpy.float64 loaded from hdf:
import python
s = pandas.read_hdf(r'C:\test\test.h5', 'test')
s/2.
This gives me inconsistent behaviour, it sometimes works and sometimes throws:
OMP: Error #134: Cannot set thread affinity mask.
OMP: System error #87: The parameter is incorrect.
I have replicated this error on other machines, and the test case is derived from a unit test failure (with the above error) which was replicted on several machines and from a server. This has come up in an upgrade from pandas 0.12 to pandas 0.13.
The following consistantly runs with no error:
import python
s = pandas.read_hdf(r'C:\test\test.h5', 'test')
s.apply(lambda x: x/2.)
and,
import python
s = pandas.read_hdf(r'C:\test\test.h5', 'test')
pandas.computation.expressions.set_use_numexpr(False)
s/2.
Thanks for the help.
This is a very similar problem to as described in this issue, and the linked issue
It seems that only canopy is experiencing these issues. I think it has to do with the canopy numpy MKL build, but that is a guess as I have not been able to reproduce this. So here are some work-arounds:
try to upgrade numexpr to 2.4 (current version), or downgrade to 2.1
try to use numpy 1.8.1 via canopy
try to install numpy/numexpr from the posted binaries here; I don't know exactly how canopy works so not sure if this is possible
uninstall numexpr
you can also disable numexpr support via pandas.computation.expressions.set_use_numexpr(False). Note that numexpr is REQUIRED in order to read/use HDF5 files via PyTables. However the expressions disabling of numexpr should just disable it for 'computations' (and not the HDF access).