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October 29, 2019 00:32
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Demonstrates that evaluating wcs.pixel_to_world is efficient for large vectors but very inefficient for single calls.
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from time import sleep, time | |
import numpy as np | |
from astropy import wcs | |
w = wcs.WCS(naxis=2) | |
w.wcs.ctype = ["RA---SIN","DEC--SIN"] | |
w.wcs.cdelt = (6.2/3600, 6.2/3600) | |
w.wcs.crval = (30, 60) | |
w.wcs.crota = (0, 15) | |
# ---------------------------------------- | |
N = 100 | |
xs=np.random.randint(0, 128, N) | |
ys=np.random.randint(0, 128, N) | |
t1 = time() | |
M = 100 | |
for i in range(M): | |
coord = w.pixel_to_world(xs, ys) | |
t2 = time() | |
print('I. Process duration for array of size N = {}: {:.3f} ms per iteration'.format(N, (t2-t1)/M*1000)) | |
# ---------------------------------------- | |
N = 1000 | |
xs=np.random.randint(0, 128, N) | |
ys=np.random.randint(0, 128, N) | |
t1 = time() | |
for i in range(M): | |
coord = w.pixel_to_world(xs, ys) | |
t2 = time() | |
print('II. Process duration for array of size N = {}: {:.3f} ms per iteration'.format(N, (t2-t1)/M*1000)) |
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