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patrmccormack opened this issue Mar 4, 2017 · 2 comments
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Dependencies under Anaconda #136

patrmccormack opened this issue Mar 4, 2017 · 2 comments

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@patrmccormack
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Folks,
Trying to install control 0.7.0 under Python 2.7 with conda gives me considerable number of downgrades as shown below. System is Ubuntu 64 bit 1604.
Particularly, control seems to want Numpy 1.9 whereas conda's latest build is 1.12.0
I don't think conda-forge's mismatching is the problem as I've nuked conda-forge on a different workstation and gotten the same problem.
Any ideas?
regards
pat

pat@pat-cuda:~/anaconda2$ conda install -c python-control control=0.7.0
Fetching package metadata .............
Solving package specifications: .

Package plan for installation in environment /home/pat/anaconda2:

The following NEW packages will be INSTALLED:

control:      0.7.0-np19py27_0      python-control      
llvm:         3.3-0                                     
llvmpy:       0.12.7-py27_0                             
olefile:      0.44-py27_0                               
py2cairo:     1.10.0-py27_2                             
system:       5.8-2

The following packages will be UPDATED:

fontconfig:   2.11.1-6              conda-forge          --> 2.11.1-6                     
pillow:       3.4.2-py27_0          conda-forge          --> 4.0.0-py27_1                 
qt:           4.8.7-3               conda-forge          --> 4.8.7-4                      
tensorflow:   0.10.0rc0-np111py27_0                      --> 0.10.0-py27_0     conda-forge

The following packages will be SUPERCEDED by a higher-priority channel:

cairo:        1.14.6-0              conda-forge          --> 1.12.18-6                    
freetype:     2.6.3-1               conda-forge          --> 2.5.5-1                      
matplotlib:   2.0.0rc2-np111py27_2  conda-forge/label/rc --> 1.4.3-np19py27_2             
pango:        1.40.1-0              conda-forge          --> 1.39.0-0

The following packages will be DOWNGRADED due to dependency conflicts:

astropy:      1.3-np111py27_0                            --> 1.0.4-np19py27_0             
bottleneck:   1.1.0-np111py27_0                          --> 1.0.0-np19py27_0             
dask:         0.13.0-py27_0                              --> 0.11.1-py27_0                
h5py:         2.6.0-np111py27_2                          --> 2.5.0-np19py27_3             
hdf5:         1.8.17-1                                   --> 1.8.15.1-3                   
libpng:       1.6.27-0                                   --> 1.6.17-0                     
numba:        0.30.0-np111py27_0                         --> 0.15.1-np19py27_0            
numexpr:      2.6.1-np111py27_1                          --> 2.4.4-np19py27_0             
numpy:        1.11.2-py27_0                              --> 1.9.3-py27_3                 
pandas:       0.19.2-np111py27_0                         --> 0.17.1-np19py27_0            
pixman:       0.34.0-0                                   --> 0.32.6-0                     
protobuf:     3.0.0-py27_1                               --> 3.0.0b2-py27_0    conda-forge
pyparsing:    2.1.4-py27_0                               --> 2.0.3-py27_0                 
pytables:     3.3.0-np111py27_0                          --> 3.2.2-np19py27_0             
scikit-image: 0.12.3-np111py27_1                         --> 0.11.3-np19py27_0            
scikit-learn: 0.18.1-np111py27_0                         --> 0.16.1-np19py27_0            
scipy:        0.18.1-np111py27_0                         --> 0.17.1-np19py27_1            
statsmodels:  0.6.1-np111py27_1                          --> 0.6.1-np19py27_0
@murrayrm
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murrayrm commented Mar 4, 2017

Looks to me like we have a hard dependence on numpy 1.9 in the conda files sitting on the Anaconda cloud. These were generated by @cwrowley quite some time ago and probably need to be updated.

@patrmccormack: Although it is not as handy, you might try installing python-control using pip instead of conda. Here are the commands (from the python-control README file):

pip install slycot   # optional
pip install control

If you do this within your conda environment, it should install using whatever version of numpy is installed.

@patrmccormack
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That works... in 2.7 and 3.5. Thanks.

@murrayrm murrayrm mentioned this issue Mar 29, 2017
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