def make_LC_map():
LCmap = np.zeros((len(xlocs), len(ylocs), num_chunks * num_ints))
for i in range(num_chunks):
start = i * max_photons
# print start, start+max_photons
packets = pipe.read_obs(max_photons=max_photons, start=start)
# newpackets = pipe.isolate_interval(packets,[0,0.1])
# print np.shape(newpackets)
# cube = pipe.arange_into_cube(newpackets)
# image = pipe.make_intensity_map(cube)
# image = pipe.make_intensity_map_packets(packets)
# # loop_frames
# quicklook_im(image)
# print image[58,67]
# xloc, yloc = 58., 67.
# xloc, yloc = 60., 60.
# xloc, yloc = 60., 60.
start = packets[0, 2]
end = packets[-1, 2]
# print start, end
for ix, xloc in enumerate(xlocs):
for iy, yloc in enumerate(ylocs):
print np.shape(packets)
LC, packets = pipe.get_lightcurve(packets,
xloc,
yloc,
start,
end + cp.frame_time,
bin_time=bin_time,
speed_up=True)
# print LC['intensity']
LCmap[ix, iy,
i * num_ints:(i + 1) * num_ints] = LC['intensity']
if (ix * len(ylocs) + iy) % 10 == 0:
misc.progressBar(value=(ix * len(ylocs) + iy),
endvalue=len(xlocs) * len(ylocs))
with open(LCmapFile, 'wb') as handle:
pickle.dump(LCmap, handle, protocol=pickle.HIGHEST_PROTOCOL)
def run():
packets = pipe.read_obs(max_photons=max_photons)
print packets[:50], packets.shape
# tp.packets = packets
print sp.num_processes, 'NUM_PROCESSES'
p = multiprocessing.Pool(sp.num_processes)
LCmap = np.zeros((len(xlocs), len(ylocs), num_ints))
print num_ints, num_chunks
for i in range(num_chunks):
packets_chunk = packets[i * max_photons:(i + 1) * max_photons]
print debprint((i, packets_chunk.shape))
prod_x = partial(mp_worker, packets=packets_chunk
) # prod_x has only one argument x (y is fixed to 10)
# idxs = range(tp.grid_size**2)
idxs = range(len(xlocs) * len(ylocs))
print debprint(idxs)
LClist = p.map(prod_x, idxs)
# LClist = mp_worker(idxs[0])
# LClist = p.map(mp_worker, idxs)
# LClist = []
# for idx in idxs:
# ints = p.apply_async(mp_worker, (idx, packets)).get()
# print ints
# LClist.append(ints)
# print LClist
binned_chunk = num_ints / num_chunks
print debprint((len(LClist[0]), binned_chunk))
for idx in idxs:
ix = idx / len(xlocs)
iy = idx % len(xlocs)
LCmap[ix, iy,
i * binned_chunk:(i + 1) * binned_chunk] = LClist[idx]
plt.imshow(LCmap[:, :, 0])
plt.show()
return LCmap
def LCmap_speedup_colors():
allpackets = pipe.read_obs()
# packets = packets[:,2:]
phases = allpackets[:, 1] - allpackets[:, 0]
# packets = np.vstack((phases,packets[:,2:]))
print phases[:50]
print np.shape(allpackets)
wsamples = np.linspace(tp.band[0], tp.band[1], tp.nwsamp)
print wsamples
phasebins = spec.phase_cal(wsamples)
print phasebins
binnedphase = np.digitize(phases, phasebins)
print binnedphase[:20]
LCmaps = np.zeros((len(phasebins), len(xlocs), len(ylocs), num_ints))
for col in range(len(phasebins)):
locs = np.where(binnedphase == col)[0]
packets = allpackets[locs]
# cube = pipe.arange_into_cube(packets)
# image = pipe.make_intensity_map(cube)
# quicklook_im(image)
print 'Sorting packets (takes a while)'
ind = np.lexsort((packets[:, 3], packets[:, 4]))
packets = packets[ind]
print packets.shape, sp.num_processes
# exit()
LCmap = np.zeros((len(xlocs), len(ylocs), num_ints))
# for i in range(num_chunks):
# packets_chunk = packets[i * max_photons:(i + 1) * max_photons]
output = multiprocessing.Queue()
inqueue = multiprocessing.Queue()
packqueue = multiprocessing.Queue()
jobs = []
for i in range(sp.num_processes):
p = multiprocessing.Process(target=LCmap_worker,
args=(inqueue, output, packqueue))
jobs.append(p)
p.start()
# print 'ip', i
for idx in range(len(xlocs) * len(ylocs)):
# print 'idx', idx
inqueue.put(idx)
lower = 0
# for ix, iy in zip(xlocs,ylocs):
for ix, iy in list(itertools.product(xlocs, ylocs)):
print ix, iy, 'ix iy' #'idx', idx
# print inqueue.qsize(), output.qsize(), packqueue.qsize(), ' 3queues'
diff = 0
span = lower
while diff == 0:
diff = packets[span, 3] - iy
span += 1
if span == len(packets):
break
# print 'lower and span', lower, span
upper = span - 1
packets_chunk = packets[lower:upper]
lower = upper
packqueue.put(packets_chunk)
LClist = output.get()
# if ix == 1 and iy == 1:
# exit()
# print LClist, 'LClist'
# binned_chunk = num_ints / num_chunks
# print debprint((len(LClist[0]), binned_chunk))
# for idx in idxs:
# ix = idx / len(xlocs)
# iy = idx % len(xlocs)
# LCmap[ix, iy, i * binned_chunk:(i + 1) * binned_chunk] = LClist # [idx]
LCmap[ix, iy] = LClist # [idx]
# print LClist
print inqueue.qsize(), output.qsize(), packqueue.qsize(
), 'line380 3queues'
output.put(None)
# packqueue.put(None)
print inqueue.qsize(), output.qsize(), packqueue.qsize(
), 'line383 3queues'
for i in range(sp.num_processes):
# Send the sentinal to tell Simulation to end
inqueue.put(sentinel)
print 'second i', i
print 'line 205', tp.detector
print inqueue.qsize(), output.qsize(), packqueue.qsize(
), 'line389 3queues'
for i, p in enumerate(jobs):
p.join()
print 'third i', i
print col, type(col)
LCmaps[col] = LCmap
return LCmaps
def LCmap_speedup():
packets = pipe.read_obs()
packets = packets[:,2:]
print('Sorting packets (takes a while)')
ind = np.lexsort((packets[:, 1], packets[:, 2]))
packets = packets[ind]
print(packets.shape, sp.num_processes)
# exit()
num_ints = int(cp.frame_time * ap.numframes / mp.bin_time)
LCmap = np.zeros((len(xlocs), len(ylocs), num_ints))
# for i in range(num_chunks):
# packets_chunk = packets[i * max_photons:(i + 1) * max_photons]
output = multiprocessing.Queue()
inqueue = multiprocessing.Queue()
packqueue = multiprocessing.Queue()
jobs = []
for i in range(sp.num_processes):
p = multiprocessing.Process(target=LCmap_worker, args=(inqueue, output, packqueue))
jobs.append(p)
p.start()
# print 'ip', i
for idx in range(len(xlocs) * len(ylocs)):
# print 'idx', idx
inqueue.put(idx)
lower=0
# for ix, iy in zip(xlocs,ylocs):
for ix, iy in list(itertools.product(xlocs, ylocs)):
print(ix, iy, 'ix iy')#'idx', idx
# print inqueue.qsize(), output.qsize(), packqueue.qsize(), ' 3queues'
diff = 0
span = lower
while diff == 0:
# print diff, packets[span,1], iy, span
diff = packets[span,1] - iy
span += 1
if span == ap.star_photons*ap.numframes:
break
print('lower and span', lower, span)
upper = span -1
packets_chunk = packets[lower:upper]
lower=upper
packqueue.put(packets_chunk)
LClist = output.get()
# if ix == 1 and iy == 1:
# exit()
# print LClist, 'LClist'
# binned_chunk = num_ints / num_chunks
# print debprint((len(LClist[0]), binned_chunk))
# for idx in idxs:
# ix = idx / len(xlocs)
# iy = idx % len(xlocs)
# LCmap[ix, iy, i * binned_chunk:(i + 1) * binned_chunk] = LClist # [idx]
LCmap[ix, iy] = LClist # [idx]
print(inqueue.qsize(), output.qsize(), packqueue.qsize(), 'line380 3queues')
output.put(None)
# packqueue.put(None)
print(inqueue.qsize(), output.qsize(), packqueue.qsize(), 'line383 3queues')
for i in range(sp.num_processes):
# Send the sentinal to tell Simulation to end
inqueue.put(sentinel)
print('second i', i)
print('line 205', tp.detector)
print(inqueue.qsize(), output.qsize(), packqueue.qsize(), 'line389 3queues')
for i, p in enumerate(jobs):
p.join()
print('third i', i)
return LCmap
sys.path.append('D:/dodkins/MEDIS/MEDIS')
import numpy as np
import matplotlib.pylab as plt
from params import ap, cp, tp, mp
# import Detector.readout as read
import Detector.pipeline as pipe
# import Detector.temporal as temp
from Utils.plot_tools import view_datacube, quicklook_im, loop_frames
import cPickle as pickle
framesFile = 'backup/frames.pkl'
if os.path.isfile(framesFile):
with open(framesFile, 'rb') as handle:
frames = pickle.load(handle)
else:
frames = []
max_photons = 1e6
for i in range(10):
start = i * max_photons
print start, start + max_photons
packets = pipe.read_obs(max_photons=max_photons, start=start)
image = pipe.make_intensity_map_packets(packets)
# quicklook_im(image)
frames.append(image)
frames = np.array(frames)
with open(framesFile, 'wb') as handle:
pickle.dump(frames, handle, protocol=pickle.HIGHEST_PROTOCOL)
loop_frames(frames)
