def testBalance1(self):
ts = [just_sleep(0.5) for i in range(LocalExecutor.NUM_THREADS)]
start = time.time()
res = resultset(ts)
for r in res:
pass
end = time.time()
print "Took %f" % (end - start)
self.assertTrue(end - start < 1.0)
def testBalance1(self):
ts = [just_sleep(0.5) for i in range(LocalExecutor.NUM_THREADS)]
start = time.time()
res = resultset(ts)
for r in res:
pass
end = time.time()
print "Took %f" % (end - start)
self.assertTrue(end - start < 1.0)
def testResultBag(self):
COUNT = 10
res1 = (py_ivar(i) for i in range(COUNT))
res2 = (inc(i - 1) for i in range(COUNT))
res2b = (inc(i - 1) for i in range(COUNT))
exp = [(x, x) for x in range(COUNT)]
# with max-running at 1 should be in order
self.checkSequential((item for i, item in resultset(res2b, max_ready=1)), COUNT)
# Check that all of the expected results turn up
act1 = [(i, x.get()) for i, x in list(resultset(res1))]
print act1
self.assertEquals(sorted(act1), exp)
act2 = [(i, x.get()) for i, x in list(resultset(res2))]
print act2
self.assertEquals(sorted(act2), exp)
def testResultBag(self):
COUNT = 10
res1 = (py_ivar(i) for i in range(COUNT))
res2 = (inc(i - 1) for i in range(COUNT))
res2b = (inc(i - 1) for i in range(COUNT))
exp = [(x, x) for x in range(COUNT)]
# with max-running at 1 should be in order
self.checkSequential(
(item for i, item in resultset(res2b, max_ready=1)), COUNT)
# Check that all of the expected results turn up
act1 = [(i, x.get()) for i, x in list(resultset(res1))]
print act1
self.assertEquals(sorted(act1), exp)
act2 = [(i, x.get()) for i, x in list(resultset(res2))]
print act2
self.assertEquals(sorted(act2), exp)
proj << mProjectPP(raw_img, header)
# Generate a temporary table with info about images
proj_table = MTable(path.join(bands, 'proj', 'pimages.tbl'))
proj_table << mImgtbl(*projected)
# Now combine the projected images into a montage
band_img = MImage(path.join(bands, bands + ".fits"))
band_img << mAdd(proj_table, header, *projected)
return band_img
# Get info for the three bands we are interested in
allbands = ['DSS2B', 'DSS2R', 'DSS2IR']
img_tables = [archive_fetch(bands) for bands in allbands]
# For each of the three bands, stitch together the different
# images into a grayscale image.
# Use of resultset sparks all futures in img_tables
# , and allows to process the results out of order as
# soon as data is ready.
band_imgs = [
process_one_band(bands, tbl, header)
for bands, tbl in resultset(img_tables, allbands)
]
# Make a false-color JPEG image out of the three bands
res = JPEG("DSS2_BRIR.jpeg") << mJPEGrgb(band_imgs[2], band_imgs[1],
band_imgs[0])
res.get() # Calling get triggers execution
for proj, raw_img in zip(projected, raw_images):
proj << mProjectPP(raw_img, header)
# Generate a temporary table with info about images
proj_table = MTable(path.join(bands, 'proj', 'pimages.tbl'))
proj_table << mImgtbl(*projected)
# Now combine the projected images into a montage
band_img = MImage(path.join(bands, bands+".fits"))
band_img << mAdd(proj_table, header, *projected)
return band_img
# Get info for the three bands we are interested in
allbands = ['DSS2B', 'DSS2R', 'DSS2IR']
img_tables = [archive_fetch(bands)
for bands in allbands]
# For each of the three bands, stitch together the different
# images into a grayscale image.
# Use of resultset sparks all futures in img_tables
# , and allows to process the results out of order as
# soon as data is ready.
band_imgs = [process_one_band(bands, tbl, header)
for bands, tbl
in resultset(img_tables, allbands)]
# Make a false-color JPEG image out of the three bands
res = JPEG("DSS2_BRIR.jpeg") << mJPEGrgb(band_imgs[2],
band_imgs[1], band_imgs[0])
res.get() # Calling get triggers execution