def test_testOddFeatures(self):
# Test of other odd features
x = arange(20)
x = x.reshape(4, 5)
x.flat[5] = 12
assert_(x[1, 0] == 12)
z = x + 10j * x
assert_(eq(z.real, x))
assert_(eq(z.imag, 10 * x))
assert_(eq((z * conjugate(z)).real, 101 * x * x))
z.imag[...] = 0.0
x = arange(10)
x[3] = masked
assert_(str(x[3]) == str(masked))
c = x >= 8
assert_(count(where(c, masked, masked)) == 0)
assert_(shape(where(c, masked, masked)) == c.shape)
z = where(c, x, masked)
assert_(z.dtype is x.dtype)
assert_(z[3] is masked)
assert_(z[4] is masked)
assert_(z[7] is masked)
assert_(z[8] is not masked)
assert_(z[9] is not masked)
assert_(eq(x, z))
z = where(c, masked, x)
assert_(z.dtype is x.dtype)
assert_(z[3] is masked)
assert_(z[4] is not masked)
assert_(z[7] is not masked)
assert_(z[8] is masked)
assert_(z[9] is masked)
z = masked_where(c, x)
assert_(z.dtype is x.dtype)
assert_(z[3] is masked)
assert_(z[4] is not masked)
assert_(z[7] is not masked)
assert_(z[8] is masked)
assert_(z[9] is masked)
assert_(eq(x, z))
x = array([1., 2., 3., 4., 5.])
c = array([1, 1, 1, 0, 0])
x[2] = masked
z = where(c, x, -x)
assert_(eq(z, [1., 2., 0., -4., -5]))
c[0] = masked
z = where(c, x, -x)
assert_(eq(z, [1., 2., 0., -4., -5]))
assert_(z[0] is masked)
assert_(z[1] is not masked)
assert_(z[2] is masked)
assert_(eq(masked_where(greater(x, 2), x), masked_greater(x, 2)))
assert_(eq(masked_where(greater_equal(x, 2), x),
masked_greater_equal(x, 2)))
assert_(eq(masked_where(less(x, 2), x), masked_less(x, 2)))
assert_(eq(masked_where(less_equal(x, 2), x), masked_less_equal(x, 2)))
assert_(eq(masked_where(not_equal(x, 2), x), masked_not_equal(x, 2)))
assert_(eq(masked_where(equal(x, 2), x), masked_equal(x, 2)))
assert_(eq(masked_where(not_equal(x, 2), x), masked_not_equal(x, 2)))
assert_(eq(masked_inside(list(range(5)), 1, 3), [0, 199, 199, 199, 4]))
assert_(eq(masked_outside(list(range(5)), 1, 3), [199, 1, 2, 3, 199]))
assert_(eq(masked_inside(array(list(range(5)),
mask=[1, 0, 0, 0, 0]), 1, 3).mask,
[1, 1, 1, 1, 0]))
assert_(eq(masked_outside(array(list(range(5)),
mask=[0, 1, 0, 0, 0]), 1, 3).mask,
[1, 1, 0, 0, 1]))
assert_(eq(masked_equal(array(list(range(5)),
mask=[1, 0, 0, 0, 0]), 2).mask,
[1, 0, 1, 0, 0]))
assert_(eq(masked_not_equal(array([2, 2, 1, 2, 1],
mask=[1, 0, 0, 0, 0]), 2).mask,
[1, 0, 1, 0, 1]))
assert_(eq(masked_where([1, 1, 0, 0, 0], [1, 2, 3, 4, 5]),
[99, 99, 3, 4, 5]))
atest = ones((10, 10, 10), dtype=np.float32)
btest = zeros(atest.shape, MaskType)
ctest = masked_where(btest, atest)
assert_(eq(atest, ctest))
z = choose(c, (-x, x))
assert_(eq(z, [1., 2., 0., -4., -5]))
assert_(z[0] is masked)
assert_(z[1] is not masked)
assert_(z[2] is masked)
x = arange(6)
x[5] = masked
y = arange(6) * 10
y[2] = masked
c = array([1, 1, 1, 0, 0, 0], mask=[1, 0, 0, 0, 0, 0])
cm = c.filled(1)
z = where(c, x, y)
zm = where(cm, x, y)
assert_(eq(z, zm))
assert_(getmask(zm) is nomask)
assert_(eq(zm, [0, 1, 2, 30, 40, 50]))
z = where(c, masked, 1)
assert_(eq(z, [99, 99, 99, 1, 1, 1]))
z = where(c, 1, masked)
assert_(eq(z, [99, 1, 1, 99, 99, 99]))
dc1 = 0.
c1 = np.mean(group['c2'][f1])
color = np.divide(m0 - m1 + z0 - z1, 1 - c0 + c1)
dcolor = np.abs(color) * np.sqrt(
np.divide(dm0**2 + dm1**2 + dz0**2 + dz1**2, (m0 - m1 + z0 - z1)**2)
+ np.divide(dc0**2 + dc1**2, (1 - c0 + c1)**2)
)
for row in group:
colors.append(color)
dcolors.append(dcolor)
targets[filters] = np.array(colors)
targets['d'+filters] = np.array(dcolors)
# calibrate all the instrumental magnitudes
zcol = [color_to_use[row['filter']][0] if color_to_use[row['filter']] else row['filter']*2 for row in targets]
zeropoint = np.choose(zcol == targets['zcol1'], [targets['z2'], targets['z1']])
dzeropoint = np.choose(zcol == targets['zcol1'], [targets['dz2'], targets['dz1']])
colorterm = np.choose(zcol == targets['zcol1'], [targets['c2'], targets['c1']])
dcolorterm = np.choose(zcol == targets['zcol1'], [targets['dc2'], targets['dc1']])
uzcol, izcol = np.unique(zcol, return_inverse=True)
color_used = np.choose(izcol, [targets[col].T if col in targets.colnames else 0. for col in uzcol]).filled(0.) # if no other filter, skip color correction
dcolor_used = np.choose(izcol, [targets['d'+col].T if col in targets.colnames else 0. for col in uzcol]).filled(0.)
targets['mag'] = (targets['instmag_amcorr'].T + zeropoint + colorterm * color_used).T
targets['dmag'] = np.sqrt(targets['dinstmag'].T**2 + dzeropoint**2 + dcolorterm**2 * color_used**2 + colorterm**2 * dcolor_used**2).T
if args.stage == 'mag':
# write mag & dmag to database
targets['dmag'].mask = targets['mag'].mask
query = 'INSERT INTO photlco (filename, mag, dmag) VALUES\n'
query += ',\n'.join(['("{}", {}, {})'.format(row['filename'], row['mag'], row['dmag']) for row in targets.filled(9999.)])
query += '\nON DUPLICATE KEY UPDATE mag=VALUES(mag), dmag=VALUES(dmag)'
def test_testOddFeatures(self):
# Test of other odd features
x = arange(20)
x = x.reshape(4, 5)
x.flat[5] = 12
assert_(x[1, 0] == 12)
z = x + 10j * x
assert_(eq(z.real, x))
assert_(eq(z.imag, 10 * x))
assert_(eq((z * conjugate(z)).real, 101 * x * x))
z.imag[...] = 0.0
x = arange(10)
x[3] = masked
assert_(str(x[3]) == str(masked))
c = x >= 8
assert_(count(where(c, masked, masked)) == 0)
assert_(shape(where(c, masked, masked)) == c.shape)
z = where(c, x, masked)
assert_(z.dtype is x.dtype)
assert_(z[3] is masked)
assert_(z[4] is masked)
assert_(z[7] is masked)
assert_(z[8] is not masked)
assert_(z[9] is not masked)
assert_(eq(x, z))
z = where(c, masked, x)
assert_(z.dtype is x.dtype)
assert_(z[3] is masked)
assert_(z[4] is not masked)
assert_(z[7] is not masked)
assert_(z[8] is masked)
assert_(z[9] is masked)
z = masked_where(c, x)
assert_(z.dtype is x.dtype)
assert_(z[3] is masked)
assert_(z[4] is not masked)
assert_(z[7] is not masked)
assert_(z[8] is masked)
assert_(z[9] is masked)
assert_(eq(x, z))
x = array([1., 2., 3., 4., 5.])
c = array([1, 1, 1, 0, 0])
x[2] = masked
z = where(c, x, -x)
assert_(eq(z, [1., 2., 0., -4., -5]))
c[0] = masked
z = where(c, x, -x)
assert_(eq(z, [1., 2., 0., -4., -5]))
assert_(z[0] is masked)
assert_(z[1] is not masked)
assert_(z[2] is masked)
assert_(eq(masked_where(greater(x, 2), x), masked_greater(x, 2)))
assert_(eq(masked_where(greater_equal(x, 2), x),
masked_greater_equal(x, 2)))
assert_(eq(masked_where(less(x, 2), x), masked_less(x, 2)))
assert_(eq(masked_where(less_equal(x, 2), x), masked_less_equal(x, 2)))
assert_(eq(masked_where(not_equal(x, 2), x), masked_not_equal(x, 2)))
assert_(eq(masked_where(equal(x, 2), x), masked_equal(x, 2)))
assert_(eq(masked_where(not_equal(x, 2), x), masked_not_equal(x, 2)))
assert_(eq(masked_inside(list(range(5)), 1, 3), [0, 199, 199, 199, 4]))
assert_(eq(masked_outside(list(range(5)), 1, 3), [199, 1, 2, 3, 199]))
assert_(eq(masked_inside(array(list(range(5)),
mask=[1, 0, 0, 0, 0]), 1, 3).mask,
[1, 1, 1, 1, 0]))
assert_(eq(masked_outside(array(list(range(5)),
mask=[0, 1, 0, 0, 0]), 1, 3).mask,
[1, 1, 0, 0, 1]))
assert_(eq(masked_equal(array(list(range(5)),
mask=[1, 0, 0, 0, 0]), 2).mask,
[1, 0, 1, 0, 0]))
assert_(eq(masked_not_equal(array([2, 2, 1, 2, 1],
mask=[1, 0, 0, 0, 0]), 2).mask,
[1, 0, 1, 0, 1]))
assert_(eq(masked_where([1, 1, 0, 0, 0], [1, 2, 3, 4, 5]),
[99, 99, 3, 4, 5]))
atest = ones((10, 10, 10), dtype=np.float32)
btest = zeros(atest.shape, MaskType)
ctest = masked_where(btest, atest)
assert_(eq(atest, ctest))
z = choose(c, (-x, x))
assert_(eq(z, [1., 2., 0., -4., -5]))
assert_(z[0] is masked)
assert_(z[1] is not masked)
assert_(z[2] is masked)
x = arange(6)
x[5] = masked
y = arange(6) * 10
y[2] = masked
c = array([1, 1, 1, 0, 0, 0], mask=[1, 0, 0, 0, 0, 0])
cm = c.filled(1)
z = where(c, x, y)
zm = where(cm, x, y)
assert_(eq(z, zm))
assert_(getmask(zm) is nomask)
assert_(eq(zm, [0, 1, 2, 30, 40, 50]))
z = where(c, masked, 1)
assert_(eq(z, [99, 99, 99, 1, 1, 1]))
z = where(c, 1, masked)
assert_(eq(z, [99, 1, 1, 99, 99, 99]))
np.divide(dm0**2 + dm1**2 + dz0**2 + dz1**2,
(m0 - m1 + z0 - z1)**2) +
np.divide(dc0**2 + dc1**2, (1 - c0 + c1)**2))
for row in group:
colors.append(color)
dcolors.append(dcolor)
targets[filters] = np.array(colors)
targets['d' + filters] = np.array(dcolors)
# calibrate all the instrumental magnitudes
zcol = [
color_to_use[row['filter']][0]
if color_to_use[row['filter']] else row['filter'] * 2
for row in targets
]
zeropoint = np.choose(zcol == targets['zcol1'],
[targets['z2'], targets['z1']])
dzeropoint = np.choose(zcol == targets['zcol1'],
[targets['dz2'], targets['dz1']])
colorterm = np.choose(zcol == targets['zcol1'],
[targets['c2'], targets['c1']])
dcolorterm = np.choose(zcol == targets['zcol1'],
[targets['dc2'], targets['dc1']])
uzcol, izcol = np.unique(zcol, return_inverse=True)
color_used = np.choose(
izcol,
[targets[col].T if col in targets.colnames else 0.
for col in uzcol]).filled(
0.) # if no other filter, skip color correction
dcolor_used = np.choose(izcol, [
targets['d' + col].T if col in targets.colnames else 0.
for col in uzcol
