In [1]:

    

from kbmodpy import kbmod as kb
import numpy
import matplotlib.pyplot as plt
import os
%matplotlib inline


    

In [2]:

    

path = '../../HITS/test_35/4,6tempExp/new_header/'


    

In [7]:

    

files = os.listdir(path)


    

In [8]:

    

files.sort()
files = [path+f for f in files]
files = files[:4]
files


    

    
Out[8]:





['../../HITS/test_35/4,6tempExp/new_header/v410913-fg.fits',
 '../../HITS/test_35/4,6tempExp/new_header/v410969-fg.fits',
 '../../HITS/test_35/4,6tempExp/new_header/v411019-fg.fits',
 '../../HITS/test_35/4,6tempExp/new_header/v411053-fg.fits']

In [169]:

    

images = [kb.layered_image(f) for f in files]


    

In [170]:

    

p = kb.psf(1.0)


    

In [171]:

    

ix = 3000
iy = 3200
xv = 2300
yv = 800
flux = 1500
init_time = images[0].get_time()
for i in images:
    t = i.get_time()-init_time
    print('x: '+str(ix+xv*t) + ' y: ' + str(iy+yv*t) )
    i.add_object( ix+xv*t, iy+yv*t, flux, p )


    

    




x: 3000.0 y: 3200.0
x: 3196.7949000012595 y: 3268.450400000438
x: 3354.7439499969187 y: 3323.3891999989282
x: 3462.822329996561 y: 3360.981679998804

In [172]:

    

stack = kb.image_stack(images)


    

In [173]:

    

flags = ~0 # mask a pixel with any flag
flag_exceptions = [32,39]#int('100000', 2) # unless it also has this flag
master_flags = int('100111', 2) # mask any pixels which have any of 
# these more than two times


    

In [174]:

    

stack.apply_mask_flags(flags, flag_exceptions)


    

In [175]:

    

stack.apply_master_mask(master_flags, 2)


    

In [176]:

    

images = stack.get_images()


    

In [177]:

    

img = images[1] #kb.layered_image("test",4096, 4096, 20.0, 400.0, 0.0)#


    

In [178]:

    

sub = img.science()


    

In [179]:

    

sub = sub[ 2400:3900,2800:4000]


    

In [ ]:

    




    

In [180]:

    

fig = plt.figure(figsize=(12,12))
plt.imshow(sub, origin='lower',  vmin=-50, vmax=500)#cmap=plt.cm.Greys_r,
plt.xlabel('X Pixels')
plt.ylabel('Y Pixels')
plt.colorbar()


    

    
Out[180]:





<matplotlib.colorbar.Colorbar at 0x7fd4282a0860>






    

In [183]:

    

search = kb.stack_search(stack, p)


    

In [184]:

    

search.gpu(50,50, 0.15, 0.9, 2300.0, 3200.0)


    

In [185]:

    

#search.filter_min_obs(3)


    

In [186]:

    

res = search.get_results(0, 10000)


    

In [187]:

    

res = [t for t in res if t.obs_count>2]


    

In [188]:

    

#search.save_results("filtered.txt")


    

In [189]:

    

len(res)


    

    
Out[189]:





21

In [52]:

    

res


    

    
Out[52]:





[lh: 138.453003 flux: 9873.385742 x: 2255 y: 1275 x_v: 1976.203735 y_v: 2014.522949 obs_count: 3,
 lh: 135.394699 flux: 8691.991211 x: 432 y: 2974 x_v: 2793.225342 y_v: 1148.168945 obs_count: 3,
 lh: 126.149994 flux: 3451.456055 x: 3123 y: 3043 x_v: 2428.268555 y_v: 1040.997559 obs_count: 3,
 lh: 122.266182 flux: 3240.961182 x: 3126 y: 3045 x_v: 2411.724609 y_v: 1033.905273 obs_count: 3,
 lh: 122.152214 flux: 3267.580078 x: 3123 y: 3044 x_v: 2428.268555 y_v: 1040.997559 obs_count: 3,
 lh: 122.138527 flux: 3335.924805 x: 3124 y: 3044 x_v: 2428.268555 y_v: 1040.997559 obs_count: 3,
 lh: 119.428062 flux: 3203.938477 x: 3121 y: 3042 x_v: 2444.812256 y_v: 1048.089966 obs_count: 3,
 lh: 117.922615 flux: 3094.543457 x: 3127 y: 3045 x_v: 2411.724609 y_v: 1033.905273 obs_count: 3,
 lh: 117.387085 flux: 3164.751221 x: 3124 y: 3043 x_v: 2428.268555 y_v: 1040.997559 obs_count: 3,
 lh: 117.085182 flux: 7836.525879 x: 2253 y: 1275 x_v: 1988.808838 y_v: 2027.372559 obs_count: 3,
 lh: 114.757835 flux: 2972.942383 x: 3126 y: 3044 x_v: 2411.724609 y_v: 1033.905273 obs_count: 3,
 lh: 113.998955 flux: 3091.735107 x: 3122 y: 3042 x_v: 2444.812256 y_v: 1048.089966 obs_count: 3,
 lh: 109.307732 flux: 5111.617676 x: 432 y: 2975 x_v: 2793.225342 y_v: 1148.168945 obs_count: 3,
 lh: 108.604225 flux: 2963.837402 x: 3122 y: 3043 x_v: 2444.812256 y_v: 1048.089966 obs_count: 3,
 lh: 107.615211 flux: 6042.180664 x: 430 y: 2973 x_v: 2809.873779 y_v: 1155.012329 obs_count: 3,
 lh: 105.710472 flux: 11258.163086 x: 2245 y: 1275 x_v: 2031.790894 y_v: 2009.972534 obs_count: 3,
 lh: 105.433083 flux: 2751.723877 x: 3121 y: 3043 x_v: 2444.812256 y_v: 1048.089966 obs_count: 3,
 lh: 104.576538 flux: 2646.500732 x: 3122 y: 3043 x_v: 2428.268555 y_v: 1040.997559 obs_count: 3,
 lh: 103.962524 flux: 10063.449219 x: 2254 y: 1275 x_v: 1988.808838 y_v: 2027.372559 obs_count: 3,
 lh: 102.395012 flux: 2553.401611 x: 3127 y: 3044 x_v: 2411.724609 y_v: 1033.905273 obs_count: 3,
 lh: 102.179001 flux: 2703.235840 x: 3119 y: 3042 x_v: 2461.356201 y_v: 1055.182251 obs_count: 3]

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