Changeset 14821 for fact


Ignore:
Timestamp:
02/01/13 08:11:45 (12 years ago)
Author:
neise
Message:
new full photon table added to Run object after reading the entire file.
File:
1 edited

Legend:

Unmodified
Added
Removed
  • fact/tools/pyscripts/simulation/readcorsika.py

    r14805 r14821  
    33import struct
    44import sys
    5 import numpy as np
     5
    66from pprint import pprint
    77
     
    1010readline.parse_and_bind('tab: complete')
    1111
    12 import matplotlib.pyplot as plt
     12#import matplotlib.pyplot as plt
     13
     14import numpy as np
     15
     16
     17
     18
     19def add_all_photon_table( run ):
     20    ##########################################################################
     21    #
     22    # At this point I have (hopefully) successfully read the entire file.
     23    # But the corsika coordinate system is not quite what I like.
     24    # In corsika the x-axis points north
     25    # and the y-axis points north.
     26    # And so are the direction cosines.
     27    # In addition I later found, that I would like to loop over all photons
     28    # in a corsika file, without respect to the event in order to delete all
     29    # those which are absorbed or which definitely do not hit the detector,
     30    # because they are to far away.
     31    # This should reduce computation time a bit...
     32    #
     33    # So what I do now, Is setting up a np.ndarray with two dimensions
     34    # ( photon_id , parameters ) so I can use nice numpy array operations.
     35    #
     36    # the former array contained:
     37    #        the *photon_definition_array* pda contains:
     38    #        pda[0] - encoded info
     39    #        pda[1:3] - x,y position in cm. x:north; y:west; z:down
     40    #        pda[3:5] - u,v cosines to x,y axis  --> so called direction cosines
     41    #        pda[5] - time since first interaction [ns]
     42    #        pda[6] - height of production in cm
     43    #        pda[7] - j ??
     44    #        pda[8] - imov ??
     45    #        pda[9] - wavelength [nm]
     46    #
     47    #
     48    # the new parameters will be:
     49    # 0 - x-position in [cm] - x-axis points north
     50    # 1 - y-position in [cm] - y-axis points east
     51    # 2 - z-position in [cm] - z-axis points up
     52    #
     53    # 3 - now the direction cosine to x-axis: was formerly u
     54    # 4 - now the direction cosine to y-axis: was formerly -v
     55    # 5 - now the direction cosine to z-axis: is 1-[3]-[4]
     56    #
     57    # the next two are in radians:
     58    # 6 - theta (angle between photon path and z-axis): computed from 3, 4, and 5
     59    # 7 - phi   (angle between photon path projected into x-y-plane and x-axis)
     60    #
     61    # 8 - height of production in cm
     62    # 9 - wavelength in nm
     63    # 10- time since 1st interaction in ns
     64    # 11- core_location distance in cm
     65    # 12- event id
     66    # 13- photon id
     67    #
     68    # in order to find the length of the array I loop ever the events and count the photons
     69    #
     70    # we directly take care for the so called core_location
     71   
     72    num_photons = 0
     73    for event in run.events:
     74        num_photons += event.info_dict['num_photons']
     75        if num_photons == 0:
     76            continue
     77    run.table = np.zeros((num_photons,14))
     78   
     79    n = 0
     80    for event_id, event in enumerate(run.events):
     81        this_event_photons = event.info_dict['num_photons']
     82        if this_event_photons == 0:
     83            continue
     84        core_loc = event.info_dict['core_loc']
     85        if core_loc is None:
     86            print "core_loc is None!:", event_id
     87        if event.photons is None:
     88            print "event.photons is None", event_id
     89            print "event.photons is None", num_photons
     90           
     91        shape = (this_event_photons,)
     92        # new x(north)   <--- old x(north)
     93        run.table[n:n+this_event_photons,0] = event.photons[:,1]-core_loc[0]
     94        # new y(east)  <--- old -y(west)
     95        run.table[n:n+this_event_photons,1] = -1. * (event.photons[:,2]-core_loc[1])
     96        # new z is zero anyway.
     97        run.table[n:n+this_event_photons,2] = np.zeros(shape)
     98       
     99        # new direct. cos to north-axis    <--- old u
     100        run.table[n:n+this_event_photons,3] = event.photons[:,3]
     101        # new direct. cos to east-axis   <--- old -v
     102        run.table[n:n+this_event_photons,4] = -1. * event.photons[:,4]
     103
     104        # new 3rd direction cosine         <--- old sqrt(1-u^2-v^2)
     105        u = run.table[n:n+this_event_photons,3]
     106        v = run.table[n:n+this_event_photons,4]
     107        run.table[n:n+this_event_photons,5] = np.sqrt(1-u**2-v**2)
     108       
     109        # new theta
     110        run.table[n:n+this_event_photons,6] = np.arccos(run.table[n:n+this_event_photons,5])
     111        # new phi
     112        run.table[n:n+this_event_photons,7] = np.arctan2( run.table[n:n+this_event_photons,4], run.table[n:n+this_event_photons,3])
     113       
     114        # production height in cm
     115        run.table[n:n+this_event_photons,8] = event.photons[:,6]
     116        # wavelength
     117        run.table[n:n+this_event_photons,9] = event.photons[:,9]
     118        # time since 1st interaction
     119        run.table[n:n+this_event_photons,10] = event.photons[:,5]
     120        # core_loc distance
     121        run.table[n:n+this_event_photons,11] = np.ones(shape) * np.linalg.norm(core_loc)
     122       
     123        # event_id
     124        run.table[n:n+this_event_photons,12] = np.ones(shape) * event_id
     125        # photon_id
     126        run.table[n:n+this_event_photons,13] = np.arange(this_event_photons)
     127       
     128        n += this_event_photons
     129   
     130    return run
     131
     132
     133
     134
    13135
    14136class Run(object):
     
    444566    plt.colorbar()
    445567    return Hsum
     568
     569
     570
    446571
    447572
     
    609734   
    610735    f.close()
     736       
     737    run = add_all_photon_table(run)
    611738
    612739    return run
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