def parallelize_single_file(filename, output_file):
"""This function analyzes a single file in parallel.
64 FITS images are spread across our available ranks
This implementation would be distinct from the parallelize_file_set function
This breaks a single file's analysis into steps, but parallelize_file_set function spreads a set of files
Beware: this function will fail on a system that has less than 2 threads
"""
print '(' + str(comm.Get_rank()) + ')', "Entered parallelizer."
rank = comm.Get_rank()
hdulist = fits.open(filename)
frame_list = hdulist[0].data
# Responsibilities for process 0, the file distributor
if rank == 0:
if size > NUM_FITS_IMAGES:
print "You have more threads than images in a FITS file."
print "Suggestion: revise your functions to take advantage of all threads."
remainder = (NUM_FITS_IMAGES) % size
imgs_per_rank = NUM_FITS_IMAGES / size
print "(0) Assigned imgs ", 0, " through ", imgs_per_rank, " to process ", rank
for process in range(1, size):
#Distribute image numbers to each process
if process != (size - 1):
upper_bound = (process+1) * imgs_per_rank
else:
upper_bound = (process+1) * imgs_per_rank + remainder
comm.send(range(process*imgs_per_rank, upper_bound), dest=process, tag=process)
print "(0) Assigned imgs ", process*imgs_per_rank, " through ", upper_bound, " to process ", process
# Responsibilities for all processes
if rank != 0:
my_range = comm.recv(source=0, tag=rank)
if rank == 0:
my_range = range(0, imgs_per_rank)
sumA = 0
sumB = 0
for i in my_range:
max_pixel = AC.brightest_region(frame_list[i])
tmp = AC.frame_aperture(frame_list[i], max_pixel)
sumA += tmp[0]
sumB += tmp[1]
print '(' + str(comm.Get_rank()) + ')', "Intermediate sum: ", (sumA, sumB)
if rank != 0:
comm.send((sumA, sumB), dest=0, tag=rank)
if rank == 0:
totalA = sumA
totalB = sumB
for process in range(1, size):
z = comm.recv(source=process, tag=process)
totalA += z[0]
totalB += z[1]
avg_apertureA = float(totalA) / (float(NUM_FITS_IMAGES))
avg_apertureB = float(totalB) / (float(NUM_FITS_IMAGES))
f = open(output_file, 'a')
f.write(filename + '\t' + str((avg_apertureA, avg_apertureB)) + '\n')
print "Final aperture val:", filename + '\t' + str((avg_apertureA, avg_apertureB))
f.close()
return
from astropy.io import fits FOCAL_LENGTH = 10.2 # In meters DIAMETER = 0.85 # In meters F_NUM = FOCAL_LENGTH/DIAMETER WAVELENGTH = 3.6 # In microns NUM_ROWS = 32 # The dimensions of a FITS image NUM_COLS = 32 fits_file = "prototype_data/SPITZER_I1_41629440_0000_0000_1_bcd.fits" hdulist = fits.open(fits_file) frame_list = hdulist[0].data avg_frame = ac.mk_avg_frame(frame_list) max_pixel = ac.brightest_region(avg_frame) rv = ac.frame_aperture(avg_frame, max_pixel) s_n = [0.154547861818, 0.403526244264, 0.772498520473, 1.33493102866, 2.11287033914, 3.44958935702, 5.5838167695, 9.28302033016, 15.7997153381, 27.0342961138, 49.8872234858, 95.2443001898, 199.353286902, 454.247471923, 1366.3357413] #for i in range(len(s_n)): # s_n[i] = s_n[i]/s_n[-1] an_sum = [18560.9447522, 21859.9067966, 22793.8054371, 23751.4771974, 22396.5774943, 25454.3094973, 25498.6133756, 26717.4479049, 27129.5026967, 26564.0617414, 29080.7097892, 28853.3001293, 30392.3182606, 29923.7592573, 31420.1164373, 33063.7496585] an_weight = [18560.9447522, 21304.8352603, 20565.3608689, 18843.4098908, 14840.8798195, 13381.6042331, 10101.6436409, 7576.32888009, 5230.62754907, 3307.61010714, 2221.22445384, 1284.13386742, 748.627449789, 387.493955085, 203.171683728, 101.40838172] #for i in range(len(an_weight)) x = (range(NUM_ROWS/2)) y = [] p = [] flux = []
