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The Matlab-like tools / library provided by PCDS

• matlabpymatlab.py
  ... a module implementing in python some of the tools written by Henrik/XPP for matlab
  

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  [ofte@psana0XXX myrelease]$ ipython Python 2.4.3 (#1, Nov 3 2010, 12:52:40) Type "copyright", "credits" or "license" for more information. IPython 0.9.1 -- An enhanced Interactive Python. ? -> Introduction and overview of IPython's features. %quickref -> Quick reference. help -> Python's own help system. object? -> Details about 'object'. ?object also works, ?? prints more.

  
  Loading the library. Normally 'import matlabpymatlab' would be recommended, but if you do 'from matlab pymatlab import *', all the functions defined in this module gets loaded in the current namespace, and you can see them in your workspace. This might be easier for interactive work.

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  In [1]: from matlabpymatlab import * Pretend this is matlab

  
  who gives you a short list of workspace contents

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  In [2]: who H5getobjnames ScanInput ScanOutput filtvec findmovingmotor getSTDMEANfrac_from_startpoint get_filter get_limits get_limits_automatic get_limits_channelhist get_limits_correlation get_limits_corrfrac h5py np plt rdXPPdata runexpNO2fina scan scaninput

  
  whos gives you a longer list of workspace contents

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  In [3]: whos Variable Type Data/Info -------------------------------------------------------- H5getobjnames function <function H5getobjnames at 0x2b57de8> ScanInput type <class 'matlabpymatlab.ScanInput'> ScanOutput type <class 'matlabpymatlab.ScanOutput'> filtvec function <function filtvec at 0x2b57f50> findmovingmotor function <function findmovingmotor at 0x2b57d70> getSTDMEANfrac_from_startpoint function <function getSTDMEANfrac_<...>_startpoint at 0x2b581b8> get_filter function <function get_filter at 0x2b57ed8> get_limits function <function get_limits at 0x2b58050> get_limits_automatic function <function get_limits_automatic at 0x2b58230> get_limits_channelhist function <function get_limits_channelhist at 0x2b582a8> get_limits_correlation function <function get_limits_correlation at 0x2b580c8> get_limits_corrfrac function <function get_limits_corrfrac at 0x2b58140> h5py module <module 'h5py' from '/reg<...>ython/h5py/__init__.pyc'> np module <module 'numpy' from '/re<...>thon/numpy/__init__.pyc'> plt module <module 'matplotlib.pyplo<...>n/matplotlib/pyplot.pyc'> rdXPPdata function <function rdXPPdata at 0x2b57c80> runexpNO2fina function <function runexpNO2fina at 0x2b57e60> scan ScanOutput <matlab<pymatlab.ScanOutput object at 0x2b60536bee90> scaninput ScanInput <matlab<pymatlab.ScanInput object at 0x2b60536b4e90>

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In [1]: from matlabpymatlab import *
Pretend this is matlab

In [2]: whos
Variable                         Type        Data/Info
------------------------------------------------------
H5getobjnames                    function    <function H5getobjnames at 0x1379fde8>
ScanInput                        type        <class 'matlabpymatlab.ScanInput'>
ScanOutput                       type        <class 'matlabpymatlab.ScanOutput'>
filtvec                          function    <function filtvec at 0x1379ff50>
findmovingmotor                  function    <function findmovingmotor at 0x1379fd70>
getSTDMEANfrac_from_startpoint   function    <function getSTDMEANfrac_<...>startpoint at 0x137a01b8>
get_filter                       function    <function get_filter at 0x1379fed8>
get_limits                       function    <function get_limits at 0x137a0050>
get_limits_automatic             function    <function get_limits_automatic at 0x137a0230>
get_limits_channelhist           function    <function get_limits_channelhist at 0x137a02a8>
get_limits_correlation           function    <function get_limits_correlation at 0x137a00c8>
get_limits_corrfrac              function    <function get_limits_corrfrac at 0x137a0140>
h5py                             module      <module 'h5py' from '/reg<...>ython/h5py/__init__.pyc'>
np                               module      <module 'numpy' from '/re<...>thon/numpy/__init__.pyc'>
plt                              module      <module 'matplotlib.pyplo<...>n/matplotlib/pyplot.pyc'>
rdXPPdata                        function    <function rdXPPdata at 0x1379fc80>
runexpNO2fina                    function    <function runexpNO2fina at 0x1379fe60>

In [3]: scaninput = ScanInput()

In [4]: scaninput.fina = "/reg/d/psdm/XPP/xpp23410/hdf5/xpp23410-r0107.h5"

In [5]: scan = rdXPPdata(scaninput)
Reading XPP data from  /reg/d/psdm/XPP/xpp23410/hdf5/xpp23410-r0107.h5
Found pv control object  fs2:ramp_angsft_target
Found scan vector  [ 2800120.  2800240.  2800360.  2800480.  2800600.  2800720.  2800840.
  2800960.  2801080.  2801200.  2801320.  2801440.  2801560.  2801680.
  2801800.  2801920.  2802040.  2802160.  2802280.  2802400.  2802520.
  2802640.  2802760.  2802880.  2803000.  2803120.  2803240.  2803360.
  2803480.  2803600.  2803720.  2803840.  2803960.  2804080.  2804200.
  2804320.  2804440.  2804560.  2804680.  2804800.  2804920.  2805040.
  2805160.  2805280.]
Fetching data to correlate with motor
['IPM1', 'IPM2']
(44, 120, 4)

In [6]: channels = np.concatenate(scan.scandata,axis=0)

In [7]: channels.shape
Out[7]: (5280, 4)

In [8]: get_limits(channels,1,"correlation")
4 channels a 5280 events
indexes that pass filter:  (array([   1,    5,    8, ..., 5266, 5272, 5273]),)
Out[8]:
array([[ 0.00086654,  0.01604564],
       [ 0.67172102,  0.71968567],
       [ 0.00194716,  0.01447819],
       [ 0.80365403,  0.73463468]])

In [9]: plt.draw()