Hello Henry,
This is one of the funny problems when you are working with Python and
forget to use a proper shebang*. I ran into this a couple of times already.
When you execute the Python script as you did (via ./python_API.py) and
it does not explicitly state with which interpreter it should be
executed, the current shell spawns a sub shell and executes the script.
The first statements in your Python script are import statements. When
you type 'man import' you see that this is command known to your
operating system. However, it does something one would not necessarily
expect:
"import - saves any visible window on an X server and outputs it as an
image file. You can capture a single window, the entire screen, or any
rectangular portion of the screen."
So the two import statements (importing sys and os) at the beginning of
your Python script were valid shell syntax and made your machine create
the 'sys' and 'os' files, containing screenshots of your desktop. Fun.
Of course, your shell does not understand Python syntax in general,
which is why you later on get these syntax errors:
> ./python_API.py: line 7: syntax error near unexpected token
`os.path.join'
> ./python_API.py: line 7:
> `sys.path.append(os.path.join(os.getenv(’AMBERHOME’), ’bin’))'
The solution is simple: put
#!/usr/bin/env python
at the top of your Python script. It should make your shell invoke the
Python interpreter when executing this script.
** The shebang is the first line in a script file stating which
interpreter should be used to interpret the script file. See
http://en.wikipedia.org/wiki/Shebang_%28Unix%29 for background info.
Cheers,
Jan-Philip
On 08/30/2013 05:19 AM, psu4.uic.edu wrote:
> Hi Jason,
>
> Thanks for your prompt reply. So we try to use the python API script in
> AmberTools 13 :
>
> #################################### Here is the python script, *
> python_API.py, * ######################
>
> import os
>
> import sys
>
> sys.path.append(os.path.join(os.getenv('AMBERHOME'),'bin'))
>
> from MMPBSA_mods import API as MMPBSA_API
>
> import matplotlib.pyplot as plt
>
> import numpy as np
>
> data = MMPBSA_API.load_mmpbsa_info('_MMPBSA_info')
>
> total = data['gb']['complex']['TOTAL'].copy()
>
> data = MMPBSA_API.load_mmpbsa_info('_MMPBSA_info')
>
> total_mut = data.mutant['gb']['complex']['TOTAL'].copy()
>
> total -= total.mean()
>
> total /= total.std()
>
> total2 = total.copy() / len(total)
>
> acor = np.correlate(total, total2, 'full')
>
> total_mut -= total_mut.mean()
>
> total_mut /= total_mut.std()
>
> total2_mut = total_mut.copy() / len(total_mut)
>
> acor_mut = np.correlate(total_mut, total2_mut, 'full')
>
> xdata = np.arrange(0, len(total))
>
> plt.plot(xdata, acor[len(acor)//2:], xdata, acor_mut[len(acor)//2:])
>
> plt.show()
>
> #################################################################3
>
> We have set up $AMBERHOME correctly and installed *python*,
> *numpy*<http://www.numpy.org/>,
> and *matplotlib* <http://matplotlib.org/index.html>
>
> login2$ python
>
> Python 2.7.2 |EPD 7.2-2 (64-bit)| (default, Jul 3 2011, 15:17:51)
>
> [GCC 4.1.2 20080704 (Red Hat 4.1.2-44)] on linux2
>
> Type "packages", "demo" or "enthought" for more information.
>
> >>> import numpy
>
>>>> print numpy.__version__
>
> 1.6.1
>
>>>> import matplotlib
>
>>>> print matplotlib.__version__
>
> 1.1.0
>
>
> Then we do *"./python_API.py" *in the directory where "_MMPBSA_info",
> related _MMPBSA* and topology files are. After waiting for about an
> hour, the following error messages will keep popping out:
>
> ./python_API.py: line 7: syntax error near unexpected token `os.path.join'
> ./python_API.py: line 7:
> `sys.path.append(os.path.join(os.getenv(’AMBERHOME’), ’bin’))'
>
> However, the script does generate two files: os and sys*. *Interestingly,
> if we open the "sys" file in the image software, it shows our Linux
> terminal (as attached). * *We do have X11 forwarding set up correctly by
> "ssh -X" and other images can be generated correctly in xmgrace remotely.
>
> Could you kindly offer some comments? Thanks.
>
>
> Cheers,
>
> Henry
>
>
>
>
> On Wed, Aug 28, 2013 at 6:59 AM, Jason Swails <jason.swails.gmail.com>wrote:
>
>> On Tue, Aug 27, 2013 at 7:57 PM, <psu4.uic.edu> wrote:
>>
>>> Dear Amber,
>>>
>>> We have a question about calculating correlation time of mmP(G)BSA dG
>>> values. After consulting the amberTools 13 manual, old mailing
>>> list<http://archive.ambermd.org/200712/0070.html>and the manuscripts
>>> using the statistical inefficiency method (J. Chem.
>>> Phys. 120, 2618 (2004); doi: 10.1063/1.1638996 & J Comput Chem 31:
>>> 837–846, 2010 ), we assume the following way is correct to calculate
>>> correlation time of dG in mmP(G)BSA?
>>>
>>> 1. Run MD simulation and save the trajectory in every picosecond (ps).
>>>
>>> 2. Calculate mmP(G)BSA dGbind using every ps snapshot from the MD
>>> trajectory. Save the .csv file during mmP(G)BSA (Activate -eo flag).
>>>
>>> 3. Write a script to calculate the dGbind correlation time using dGbind
>>> of each snapshot from the .csv file by the statistical inefficiency
>> method.
>>>
>>> * statistical inefficiency method: correlation time= (block length) *
>>> (the variance of the block average of X) / (the variance of the
>>> distribution (X))
>>>
>>
>> This way will work, but there is an easier method if you plan to use Python
>> to analyze your data (with, e.g., numpy, scipy, pandas, etc.). See pages
>> 376--377 of the AmberTools 13 manual where it describes using the Python
>> API giving an example where the autocorrelation function is printed.
>>
>> The binding energy can be computed pretty easily by just subtracting the
>> receptor and ligand TOTALs from the complex TOTAL (numpy arrays follow
>> standard vector add/subtract rules). This approach prevents you from
>> having to write a separate script to parse the CSV file. The example in
>> the manual demonstrates how you would calculate the normalized
>> autocorrelation function (which can also be used to estimate the
>> statistical inefficiency in which the function becomes zero within some
>> range of tolerance) and plots the resulting autocorrelation function with
>> matplotlib, but you can adapt it for your own purposes.
>>
>> HTH,
>> Jason
>>
>> --
>> Jason M. Swails
>> BioMaPS,
>> Rutgers University
>> Postdoctoral Researcher
>> _______________________________________________
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>>
>>
>>
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Received on Fri Aug 30 2013 - 01:00:02 PDT
