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