Test the background caching mechanism

Load software and data



In [1]:

    
%run ../../load_fretbursts.py









    



C:\Data\Antonio\software\src\fretbursts
 - Optimized (cython) burst search loaded.
 - Optimized (cython) photon counting loaded.

FRETBursts revision:
 2014-08-04 9c0d8b2 Fix bg_cache (broken since ph_sel refactor)

Load and process the data:



In [2]:

    
data_dir = 'C:\Data\Antonio\data/'



In [3]:

    
fname = data_dir + u'/manta/2014-04-11/17d_200p_2_600mW_reall_steer_20.dat'



In [4]:

    
d1 = loader.multispot48(fname)
d2 = loader.multispot48(fname)









    



 - Loading HDF5 file: C:\Data\Antonio\data//manta/2014-04-11/17d_200p_2_600mW_reall_steer_20.hdf5 ... DONE.
 - Loading HDF5 file: C:\Data\Antonio\data//manta/2014-04-11/17d_200p_2_600mW_reall_steer_20.hdf5 ... DONE.



In [5]:

    
def compare_data_bg(d1, d2):
    mch_arrays = ['bg', 'bg_dd', 'bg_ad', 'bg_aa', 'Lim', 'Ph_p']
    scalars = ['nperiods', 'bg_time_s', 'bg_auto_th', 'bg_fun_name']
    for name in mch_arrays:
        for ich, arr in enumerate(d1[name]):
            assert np.allclose(arr, d2[name][ich])
    for name in scalars:
        assert d1[name] == d2[name]



In [6]:

    
#reload(bg_cache)

Manual threshold



In [7]:

    
bg_cache.remove_cache(d2)









    



 * Removing all the cached background data ... [DONE]



In [8]:

    
d1.calc_bg(bg.exp_fit, time_s=20, tail_min_us=300)
d2.calc_bg_cache(bg.exp_fit, time_s=20, tail_min_us=300)









    



 - Calculating BG rates ... [DONE]
 * No cached BG rates, recomputing:
 - Calculating BG rates ... [DONE]
 * Storing BG  to disk ... 
 - Saving arrays/scalars: bg, bg_time_s, Ph_p, Lim, nperiods, bg_dd, bg_auto_th, bg_da, bg_th_us_user, bg_aa, bg_ad, 
 - Saving HDF5 attributes: bg_fun, bg_fun_name, 
 [DONE]



In [9]:

    
compare_data_bg(d1, d2)



In [10]:

    
d2.calc_bg_cache(bg.exp_fit, time_s=20, tail_min_us=300)









    



 * Loading BG rates from cache ... 
 - Loading arrays/scalars: Lim, Ph_p, bg, bg_aa, bg_ad, bg_auto_th, bg_da, bg_dd, bg_th_us_user, bg_time_s, nperiods, 
 - Loading HDF5 attributes: bg_fun, bg_fun_name, signature, 
 - Generating additional fields: bg, bg_dd, bg_ad, bg_da, bg_aa, 
 [DONE]



In [11]:

    
compare_data_bg(d1, d2)

Auto threshold



In [12]:

    
d1.calc_bg(bg.exp_fit, time_s=20, tail_min_us='auto', F_bg=1.7)
d2.calc_bg_cache(bg.exp_fit, time_s=20, tail_min_us='auto', F_bg=1.7)









    



 - Calculating BG rates ... [DONE]
 * No cached BG rates, recomputing:
 - Calculating BG rates ... [DONE]
 * Storing BG  to disk ... 
 - Saving arrays/scalars: bg_auto_F_bg, bg, bg_time_s, Ph_p, Lim, nperiods, bg_dd, bg_auto_th, bg_da, bg_auto_th_us0, bg_aa, bg_ad, 
 - Saving HDF5 attributes: bg_fun, bg_fun_name, 
 [DONE]



In [13]:

    
compare_data_bg(d1, d2)



In [14]:

    
d2.calc_bg_cache(bg.exp_fit, time_s=20, tail_min_us='auto', F_bg=1.7)









    



 * Loading BG rates from cache ... 
 - Loading arrays/scalars: Lim, Ph_p, bg, bg_aa, bg_ad, bg_auto_F_bg, bg_auto_th, bg_auto_th_us0, bg_da, bg_dd, bg_time_s, nperiods, 
 - Loading HDF5 attributes: bg_fun, bg_fun_name, signature, 
 - Generating additional fields: bg, bg_dd, bg_ad, bg_da, bg_aa, 
 [DONE]



In [15]:

    
compare_data_bg(d1, d2)

Direct test of bg_cache function



In [16]:

    
bg_cache.remove_cache(d2)









    



 * Removing all the cached background data ... [DONE]



In [17]:

    
d1.calc_bg(bg.exp_fit, time_s=20, tail_min_us=300)
bg_cache.calc_bg_cache(d2, fun=bg.exp_fit, time_s=20, tail_min_us=300)









    



 - Calculating BG rates ... [DONE]
 * No cached BG rates, recomputing:
 - Calculating BG rates ... [DONE]
 * Storing BG  to disk ... 
 - Saving arrays/scalars: bg, bg_time_s, Ph_p, Lim, nperiods, bg_dd, bg_auto_th, bg_da, bg_th_us_user, bg_aa, bg_ad, 
 - Saving HDF5 attributes: bg_fun, bg_fun_name, 
 [DONE]



In [18]:

    
compare_data_bg(d1, d2)



In [19]:

    
bg_cache.calc_bg_cache(d2, fun=bg.exp_fit, time_s=20, tail_min_us=300)









    



 * Loading BG rates from cache ... 
 - Loading arrays/scalars: Lim, Ph_p, bg, bg_aa, bg_ad, bg_auto_th, bg_da, bg_dd, bg_th_us_user, bg_time_s, nperiods, 
 - Loading HDF5 attributes: bg_fun, bg_fun_name, signature, 
 - Generating additional fields: bg, bg_dd, bg_ad, bg_da, bg_aa, 
 [DONE]



In [20]:

    
compare_data_bg(d1, d2)



In [21]:

    
d1.calc_bg(bg.exp_fit, time_s=20, tail_min_us='auto', F_bg=1.7)
bg_cache.calc_bg_cache(d2, fun=bg.exp_fit, time_s=20, tail_min_us='auto', F_bg=1.7)









    



 - Calculating BG rates ... [DONE]
 * No cached BG rates, recomputing:
 - Calculating BG rates ... [DONE]
 * Storing BG  to disk ... 
 - Saving arrays/scalars: bg_auto_F_bg, bg, bg_time_s, Ph_p, Lim, nperiods, bg_dd, bg_auto_th, bg_da, bg_auto_th_us0, bg_aa, bg_ad, 
 - Saving HDF5 attributes: bg_fun, bg_fun_name, 
 [DONE]



In [22]:

    
compare_data_bg(d1, d2)



In [23]:

    
bg_cache.calc_bg_cache(d2, fun=bg.exp_fit, time_s=20, tail_min_us='auto', F_bg=1.7)









    



 * Loading BG rates from cache ... 
 - Loading arrays/scalars: Lim, Ph_p, bg, bg_aa, bg_ad, bg_auto_F_bg, bg_auto_th, bg_auto_th_us0, bg_da, bg_dd, bg_time_s, nperiods, 
 - Loading HDF5 attributes: bg_fun, bg_fun_name, signature, 
 - Generating additional fields: bg, bg_dd, bg_ad, bg_da, bg_aa, 
 [DONE]



In [24]:

    
compare_data_bg(d1, d2)



In [25]:

    
print 'OK'

OK



In [25]: