You can use the [`pyplot.suptitle`](http://matplotlib.sourceforge.net/api/pyplot_api.html#matplotlib.pyplot.suptitle) command to add a *centered title to the figure* in addition to sub plot titles.

How to copy contents from a directory and not symbolic link?

I&#39;m using django-gunicorn-nginx setup by following this tutorial http://ijcdigital.com/blog/django-gunicorn-and-nginx-setup/ Upto nginx setup, it is working. Then I installed supervisor, configured it and then I reboot my server and checked, it shows 502 bad gateway. I&#39;m using Ubuntu 12.04 LTS

/etc/supervisor/conf.d/qlimp.conf

    [program: qlimp]
    directory = /home/nirmal/project/qlimp/qlimp.sh
    user = nirmal
    command = /home/nirmal/project/qlimp/qlimp.sh
    stdout_logfile = /path/to/supervisor/log/file/logfile.log
    stderr_logfile = /path/to/supervisor/log/file/error-logfile.log

Then I restarted supervisor and I run this command `$ supervisorctl start qlimp` and I&#39;m getting this error

    unix:///var/run/supervisor.sock no such file

Is there any problem in my supervisor setup?

Thanks!


nginx and supervisor setup in Ubuntu

I am making a chart in matplotlib and I have many subplots in it each of them with a different title, but on the top I also want to a put a title to the whole chart. How this can be done?

Common title to many subplots in Matplotlib

<p>I am making a chart in matplotlib and I have many subplots in it each of them with a different title, but on the top I also want to a put a title to the whole chart. How this can be done?</p>


I have a project hosted on GitHub. For this I have written my README using the Markdown syntax in order to have it nicely formatted on GitHub.

As my project is in Python I also plan to upload it to [PyPi][1]. The syntax used for READMEs on PyPi is reStructuredText. 

I would like to avoid having to handle two READMEs containing roughly the same content; so I searched for a markdown to RST (or the other way around) translator, but couldn&#39;t find any. 

The other solution I see is to perform a markdown/HTML and then a HTML/RST translation. I found some ressources for this [here][2] and [here][3] so I guess it should be possible.

Would you have any idea that could fit better with what I want to do?

  [1]: http://pypi.python.org/pypi
  [2]: http://www.siafoo.net/tools/html
  [3]: http://net.tutsplus.com/tutorials/other/vim-essential-plugin-markdown-to-html/

Have the same README both in Markdown and reStructuredText

Why does the json serialization not work for datetime objects . As I understand json serialization the basic idea for any object can be call the  `__str__` builtin function and then urlencode the object that you get as a response. But in case of datetime i get the following error 

    TypeError: datetime.datetime(2012, 5, 23, 18, 38, 23, 37566) is not JSON serializable

while there is a `__str__` i.e a way of stringifying the object already available , But it seems like a conscious decision to not do it , why would that be the case? 

Why does json serialization of datetime objects in python not work out of the box for datetime objects

Suppose I have a large in memory numpy array, I have a function `func` that takes in this giant array as input (together with some other parameters). `func` with different parameters can be run in parallel. For example:

    def func(arr, param):
        # do stuff to arr, param
    
    # build array arr
    
    pool = Pool(processes = 6)
    results = [pool.apply_async(func, [arr, param]) for param in all_params]
    output = [res.get() for res in results]
        
If I use multiprocessing library, then that giant array will be copied for multiple times into different processes. 

Is there a way to let different processes share the same array? This array object is read-only and will never be modified. 

What&#39;s more complicated, if arr is not an array, but an arbitrary python object, is there a way to share it? 

[EDITED]

I read the answer but I am still a bit confused. Since fork() is copy-on-write, we should not invoke any additional cost when spawning new processes in python multiprocessing library. But the following code suggests there is a huge overhead: 

    from multiprocessing import Pool, Manager
    import numpy as np; 
    import time
    
    def f(arr):
        return len(arr)
    
    t = time.time()
    arr = np.arange(10000000)
    print &quot;construct array = &quot;, time.time() - t;
    
    
    pool = Pool(processes = 6)
    
    t = time.time()
    res = pool.apply_async(f, [arr,])
    res.get()
    print &quot;multiprocessing overhead = &quot;, time.time() - t;

output (and by the way, the cost increases as the size of the array increases, so I suspect there is still overhead related to memory copying): 

&lt;!-- language: lang-none --&gt;

    construct array =  0.0178790092468
    multiprocessing overhead =  0.252444982529

Why is there such huge overhead, if we didn&#39;t copy the array? And what part does the shared memory save me? 


Shared-memory objects in multiprocessing

I have a Python function, `fetch_data`, that goes and hits a remote API, grabs some data, and returns it wrapped in a response object. It looks a bit like the below:

    def fetch_data(self, foo, bar, baz, **kwargs):
        response = Response()
        # Do various things, get some data
        return response

Now, it&#39;s possible that the response data says &quot;I have more data, call me with an incremented `page` parameter to get more&quot;. Thus, I&#39;d essentially like to store &quot;The Method Call&quot; (function, parameters) in the response object, so I can then have a `Response.get_more()` which looks at the stored function and parameters, and calls the function again with (almost) the same parameters, returning a new `Response`

Now if `fetch_data` were defined as `fetch_data(*args, **kwargs)` I could just store `(fetch_data, args, kwargs)` in `response`. However I have `self`, `foo`, `bar` and `baz` to worry about - I could just store `(fetch_data, foo, bar, baz, kwargs)` but that&#39;s a highly undesirable amount of repetition.

Essentially, I&#39;m trying to work out how to, from within a function, get a completely populated `*args` and `**kwargs`, including the function&#39;s named parameters.


Getting all arguments and values passed to a function

Is it possible to decorator a function conditionally.  For example, I want to decorate the function `foo()` with a timer function (`timeit`) only doing_performance_analysis is `True` (see the psuedo-code below).

    if doing_performance_analysis:
      @timeit
      def foo():
        &quot;&quot;&quot;
        do something, timeit function will return the time it takes
        &quot;&quot;&quot;
        time.sleep(2)
    else:
      def foo():
        time.sleep(2)  

how to do a conditional decorator in python

I am making an application in Python which collects data from a serial port and plots a graph of the collected data against arrival time. The time of arrival for the data is uncertain. I want the plot to be updated when data is received. I searched on how to do this and found two methods:

 1. Clear the plot and re-draw the plot with all the points again.
 2. Animate the plot by changing it after a particular interval.

I do not prefer the first one as the program runs and collects data for a long time (a day for example), and redrawing the plot will be pretty slow.
The second one is also not preferable as time of arrival of data is uncertain and I want the plot to update only when the data is received.

Is there a way in which I can update the plot just by adding more points to it only when the data is received?

Dynamically updating plot in matplotlib

I am new to Python and want to use its `plot` functionality to create graphs. I am using ubuntu 12.04. I followed the Python installation steps from http://eli.thegreenplace.net/2011/10/10/installing-python-2-7-on-ubuntu/ but when I do 

    from pylab import *

I am getting this error

    &gt;&gt;&gt; from pylab import *
    Traceback (most recent call last):
      File &quot;&lt;stdin&gt;&quot;, line 1, in &lt;module&gt;
    ImportError: No module named pylab

My Python version is `python 2.7`. Can anybody tell me what I am missing here?


python error: no module named pylab

I have a simple problem, but I cannot find a good solution to it.

I want to take a NumPy 2D array which represents a grayscale image, and convert it to an RGB PIL image while applying some of the matplotlib colormaps.

I can get a reasonable PNG output by using the `pyplot.figure.figimage` command:

    dpi = 100.0
    w, h = myarray.shape[1]/dpi, myarray.shape[0]/dpi
    fig = plt.figure(figsize=(w,h), dpi=dpi)
    fig.figimage(sub, cmap=cm.gist_earth)
    plt.savefig(&#39;out.png&#39;)

Although I could adapt this to get what I want (probably using StringIO do get the PIL image), I wonder if there is not a simpler way to do that, since it seems to be a very natural problem of image visualization. Let&#39;s say, something like this:

    colored_PIL_image = magic_function(array, cmap)


How to convert a NumPy array to PIL image applying matplotlib colormap

I&#39;m plotting data in Python using matplotlib. I am updating the data of the plot based upon some calculations and want the ylim and xlim to be rescaled automatically. Instead what happens is the scale is set based upon the limits of the initial plot. A MWE is

    import random
    import matplotlib.pyplot as pyplot

    pyplot.ion()

    x = range(10)
    y = lambda m: [m*random.random() for i in range(10)]
    
    pLine, = pyplot.plot(x, y(1))

    for i in range(10):
        pLine.set_ydata(y(i+1))
        pyplot.draw()

The first plot command generates a plot from `[0,1]` and I can see everything just fine. At the end, the y-data array goes from `[0,10)` with most of it greater than `1`, but the y-limits of the figure remain `[0,1]`. 

I know I can manually change the limits using `pyplot.ylim(...)`, but I don&#39;t know what to change them to. In the `for` loop, can I tell pyplot to scale the limits as if it was the first time being plotted?

Automatically Rescale ylim and xlim in Matplotlib

I can&#39;t figure out how to rotate the text on the X Axis.  Its a time stamp, so as the number of samples increase, they get closer and closer until they overlap.  I&#39;d like to rotate the text 90 degrees so as the samples get closer together, they aren&#39;t overlapping.

Below is what I have, it works fine with the exception that I can&#39;t figure out how to rotate the X axis text.

    import sys
    
    import matplotlib
    matplotlib.use(&#39;Agg&#39;)
    import matplotlib.pyplot as plt
    import datetime
    
    font = {&#39;family&#39; : &#39;normal&#39;,
            &#39;weight&#39; : &#39;bold&#39;,
            &#39;size&#39;   : 8}
    
    matplotlib.rc(&#39;font&#39;, **font)
    
    values = open(&#39;stats.csv&#39;, &#39;r&#39;).readlines()
    
    time = [datetime.datetime.fromtimestamp(float(i.split(&#39;,&#39;)[0].strip())) for i in values[1:]]
    delay = [float(i.split(&#39;,&#39;)[1].strip()) for i in values[1:]]
    
    plt.plot(time, delay)
    plt.grid(b=&#39;on&#39;)
    
    plt.savefig(&#39;test.png&#39;)



Content Type	Original Author	Original Content on Stackoverflow
Question	lovespeed	View Question on Stackoverflow
Solution 1 - Python	Chris	View Answer on Stackoverflow

Common title to many subplots in Matplotlib

Python Problem Overview

Python Solutions

Solution 1 - Python

nginx and supervisor setup in Ubuntu

How to copy contents from a directory and not symbolic link?

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