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from healpy.pixelfunc import *
from healpy._query_disc import boundaries
from healpy._pixelfunc import pix2ring, isnsideok
import numpy as np
import unittest
from healpy._query_disc import query_strip
from healpy.pixelfunc import ring2nest
class TestPixelFunc(unittest.TestCase):
def setUp(self):
# data fixture
self.theta0 = [1.52911759, 0.78550497, 1.57079633, 0.05103658, 3.09055608]
self.phi0 = [0.0, 0.78539816, 1.61988371, 0.78539816, 0.78539816]
self.lon0 = np.degrees(self.phi0)
self.lat0 = 90.0 - np.degrees(self.theta0)
def test_nside2npix(self):
self.assertEqual(nside2npix(512), 3145728)
self.assertEqual(nside2npix(1024), 12582912)
def test_nside2resol(self):
self.assertAlmostEqual(nside2resol(512, arcmin=True), 6.87097282363)
self.assertAlmostEqual(nside2resol(1024, arcmin=True), 3.43548641181)
def test_max_pixrad(self):
self.assertAlmostEqual(max_pixrad(512), 2.0870552355e-03)
self.assertAlmostEqual(
max_pixrad(512, degrees=True), np.rad2deg(2.0870552355e-03)
)
def test_nside2pixarea(self):
self.assertAlmostEqual(nside2pixarea(512), 3.9947416351188569e-06)
def test_ang2pix_ring(self):
# ensure nside = 1 << 23 is correctly calculated
# by comparing the original theta phi are restored.
# NOTE: nside needs to be sufficiently large!
id = ang2pix(1048576 * 8, self.theta0, self.phi0, nest=False)
theta1, phi1 = pix2ang(1048576 * 8, id, nest=False)
np.testing.assert_array_almost_equal(theta1, self.theta0)
np.testing.assert_array_almost_equal(phi1, self.phi0)
def test_ang2pix_ring_outofrange(self):
# Healpy_Base2 works up to nside = 2**29.
# Check that a ValueError is raised for nside = 2**30.
self.assertRaises(
ValueError, ang2pix, 1 << 30, self.theta0, self.phi0, nest=False
)
def test_ang2pix_nest(self):
# ensure nside = 1 << 23 is correctly calculated
# by comparing the original theta phi are restored.
# NOTE: nside needs to be sufficiently large!
# NOTE: with Healpy_Base this will fail because nside
# is limited to 1 << 13 with Healpy_Base.
id = ang2pix(1048576 * 8, self.theta0, self.phi0, nest=True)
theta1, phi1 = pix2ang(1048576 * 8, id, nest=True)
np.testing.assert_array_almost_equal(theta1, self.theta0)
np.testing.assert_array_almost_equal(phi1, self.phi0)
self.assertTrue(np.allclose(theta1, self.theta0))
self.assertTrue(np.allclose(phi1, self.phi0))
def test_ang2pix_nest_outofrange_doesntcrash(self):
# Healpy_Base2 works up to nside = 2**29.
# Check that a ValueError is raised for nside = 2**30.
self.assertRaises(
ValueError, ang2pix, 1 << 30, self.theta0, self.phi0, nest=False
)
def test_ang2pix_negative_theta(self):
self.assertRaises(ValueError, ang2pix, 32, -1, 0)
def test_ang2pix_lonlat(self):
# Need to decrease the precision of the check because deg not radians
id = ang2pix(1048576 * 8, self.lon0, self.lat0, nest=False, lonlat=True)
lon1, lat1 = pix2ang(1048576 * 8, id, nest=False, lonlat=True)
np.testing.assert_array_almost_equal(lon1, self.lon0, decimal=5)
np.testing.assert_array_almost_equal(lat1, self.lat0, decimal=5)
# Now test nested
id = ang2pix(1048576 * 8, self.theta0, self.phi0, nest=True)
theta1, phi1 = pix2ang(1048576 * 8, id, nest=True)
np.testing.assert_array_almost_equal(theta1, self.theta0)
np.testing.assert_array_almost_equal(phi1, self.phi0)
def test_vec2pix_lonlat(self):
# Need to decrease the precision of the check because deg not radians
vec = ang2vec(self.lon0, self.lat0, lonlat=True)
lon1, lat1 = vec2ang(vec, lonlat=True)
np.testing.assert_array_almost_equal(lon1, self.lon0, decimal=5)
np.testing.assert_array_almost_equal(lat1, self.lat0, decimal=5)
def test_get_interp_val_lonlat(self):
m = np.arange(12.0)
val0 = get_interp_val(m, self.theta0, self.phi0)
val1 = get_interp_val(m, self.lon0, self.lat0, lonlat=True)
np.testing.assert_array_almost_equal(val0, val1)
def test_get_interp_weights(self):
p0, w0 = (np.array([0, 1, 4, 5]), np.array([1.0, 0.0, 0.0, 0.0]))
# phi not specified, theta assumed to be pixel
p1, w1 = get_interp_weights(1, 0)
np.testing.assert_array_almost_equal(p0, p1)
np.testing.assert_array_almost_equal(w0, w1)
# If phi is not specified, lonlat should do nothing
p1, w1 = get_interp_weights(1, 0, lonlat=True)
np.testing.assert_array_almost_equal(p0, p1)
np.testing.assert_array_almost_equal(w0, w1)
p0, w0 = (np.array([1, 2, 3, 0]), np.array([0.25, 0.25, 0.25, 0.25]))
p1, w1 = get_interp_weights(1, 0, 0)
np.testing.assert_array_almost_equal(p0, p1)
np.testing.assert_array_almost_equal(w0, w1)
p1, w1 = get_interp_weights(1, 0, 90, lonlat=True)
np.testing.assert_array_almost_equal(p0, p1)
np.testing.assert_array_almost_equal(w0, w1)
def test_get_all_neighbours(self):
ipix0 = np.array([8, 4, 0, -1, 1, 6, 9, -1])
ipix1 = get_all_neighbours(1, np.pi / 2, np.pi / 2)
ipix2 = get_all_neighbours(1, 90, 0, lonlat=True)
np.testing.assert_array_almost_equal(ipix0, ipix1)
np.testing.assert_array_almost_equal(ipix0, ipix2)
def test_fit_dipole(self):
nside = 32
npix = nside2npix(nside)
d = [0.3, 0.5, 0.2]
vec = np.transpose(pix2vec(nside, np.arange(npix)))
signal = np.dot(vec, d)
mono, dipole = fit_dipole(signal)
self.assertAlmostEqual(mono, 0.0)
self.assertAlmostEqual(d[0], dipole[0])
self.assertAlmostEqual(d[1], dipole[1])
self.assertAlmostEqual(d[2], dipole[2])
def test_boundaries(self):
"""Test whether the boundary shapes look sane"""
for lgNside in range(1, 5):
nside = 1 << lgNside
for pix in range(nside2npix(nside)):
for res in range(1, 50, 7):
num = 4 * res # Expected number of points
for nest in (True, False):
points = boundaries(nside, pix, res, nest=nest)
self.assertTrue(points.shape == (3, num))
dist = np.linalg.norm(
points[:, : num - 1] - points[:, 1:]
) # distance between points
self.assertTrue((dist != 0).all())
dmin = np.min(dist)
dmax = np.max(dist)
self.assertTrue(dmax / dmin <= 2.0)
def test_ring(self):
for lgNside in range(1, 5):
nside = 1 << lgNside
numPix = nside2npix(nside)
numRings = 4 * nside - 1 # Expected number of rings
for nest in (True, False):
pix = np.arange(numPix, dtype=np.int64)
ring = pix2ring(nside, pix, nest=nest)
self.assertTrue(pix.shape == ring.shape)
self.assertTrue(len(set(ring)) == numRings)
if not nest:
first = ring[: numPix - 1]
second = ring[1:]
self.assertTrue(
np.logical_or(first == second, first == second - 1).all()
)
def test_accept_ma_allows_only_keywords(self):
"""Test whether the accept_ma wrapper accepts calls using only keywords."""
ma = np.zeros(12 * 16 ** 2)
try:
ud_grade(map_in=ma, nside_out=32)
except IndexError:
self.fail("IndexError raised")
def test_isnsideok(self):
"""Test the isnsideok."""
self.assertTrue(isnsideok(nside=1, nest=False))
self.assertTrue(isnsideok(nside=16, nest=True))
self.assertTrue(not isnsideok(nside=-16, nest=True))
self.assertTrue(not isnsideok(nside=-16, nest=False))
self.assertTrue(not isnsideok(nside=13, nest=True))
def test_latauto_and_latbounce(self):
"""Test latauto and latbounce features in lonlat2thetaphi."""
# Test array input
lat = [-100, -90, 0, 90, 100]
lon = [0, 60, 90, 0, 180]
# Test with latauto=False (default)
theta, phi = lonlat2thetaphi(lon, lat)
self.assertTrue(
np.allclose(
theta,
[
np.pi / 2 - np.deg2rad(-100),
np.pi,
np.pi / 2,
0,
np.pi / 2 - np.deg2rad(100),
],
)
)
self.assertTrue(
np.allclose(phi, np.deg2rad([lon[0], lon[1], lon[2], lon[3], lon[4]]))
)
# Test with latauto=True and latbounce=True (default)
theta, phi = lonlat2thetaphi(lon, lat, latauto=True)
self.assertTrue(
np.allclose(
theta,
[
np.pi / 2 + np.deg2rad(80),
np.pi,
np.pi / 2,
0,
np.pi / 2 - np.deg2rad(80),
],
)
)
self.assertTrue(
np.allclose(phi, np.deg2rad([lon[0], lon[1], lon[2], lon[3], lon[4]]))
)
# Test with latauto=True and latbounce=False
theta, phi = lonlat2thetaphi(lon, lat, latauto=True, latbounce=False)
self.assertTrue(
np.allclose(
theta,
[
np.pi / 2 + np.deg2rad(80),
np.pi / 2 + np.pi / 2,
np.pi / 2,
0,
np.pi / 2 - np.deg2rad(80),
],
)
)
self.assertTrue(np.allclose(phi, np.deg2rad([180, 60, 90, 0, 180 + 180])))
# Test scalar input
lat_scalar = -100
lon_scalar = 10
# Test with latauto=False (default)
theta_scalar, phi_scalar = lonlat2thetaphi(lon_scalar, lat_scalar)
self.assertTrue(np.allclose(theta_scalar, np.pi / 2 + np.deg2rad(100)))
self.assertTrue(np.allclose(phi_scalar, np.deg2rad(lon_scalar)))
# Test with latauto=True and latbounce=True (default)
theta_scalar, phi_scalar = lonlat2thetaphi(lon_scalar, lat_scalar, latauto=True)
self.assertTrue(np.allclose(theta_scalar, np.pi / 2 + np.deg2rad(80)))
self.assertTrue(np.allclose(phi_scalar, np.radians(lon_scalar)))
# Test with latauto=True and latbounce=False
theta_scalar, phi_scalar = lonlat2thetaphi(
lon_scalar, lat_scalar, latauto=True, latbounce=False
)
self.assertTrue(np.allclose(theta_scalar, np.pi / 2 + np.deg2rad(80)))
self.assertTrue(np.allclose(phi_scalar, np.deg2rad(lon_scalar) + np.pi))
def test_query_strip_nest(self):
# Test query_strip with nest=True, which was previously crashing
nside = 2
theta1 = 1
theta2 = 2
# Expected result using the workaround from the issue description
expected_result = ring2nest(
nside, query_strip(nside, theta1, theta2, nest=False)
)
# Actual result with nest=True
actual_result = query_strip(nside, theta1, theta2, nest=True)
np.testing.assert_array_equal(actual_result, expected_result)
|
