def test_error(self):
'''Test that using edges outside of x range raises ValueError'''
nx = 10
x = np.arange(nx)
y = np.ones(nx)
with self.assertRaises(ValueError):
yy = rebin.trapz_rebin(x, y, edges=np.arange(-1, nx - 1))
with self.assertRaises(ValueError):
yy = rebin.trapz_rebin(x, y, edges=np.arange(1, nx + 1))
def test_error(self):
'''Test that using edges outside of x range raises ValueError'''
nx = 10
x = np.arange(nx)
y = np.ones(nx)
with self.assertRaises(ValueError):
yy = rebin.trapz_rebin(x, y, edges=np.arange(-1, nx-1))
with self.assertRaises(ValueError):
yy = rebin.trapz_rebin(x, y, edges=np.arange(1, nx+1))
def test_nonuniform(self):
'''test rebinning a non-uniform density'''
for nx in range(5, 12):
x = np.linspace(0, 2 * np.pi, nx)
y = np.sin(x)
edges = [0, 2 * np.pi]
yy = rebin.trapz_rebin(x, y, edges=edges)
self.assertTrue(np.allclose(yy, 0.0))
x = np.linspace(0, 2 * np.pi, 100)
y = np.sin(x)
edges = [0, 0.5 * np.pi, np.pi, 1.5 * np.pi, 2 * np.pi]
yy = rebin.trapz_rebin(x, y, edges=edges)
self.assertTrue(np.allclose(yy[0:2], 2 / np.pi, atol=5e-4))
self.assertTrue(np.allclose(yy[2:4], -2 / np.pi, atol=5e-4))
def test_nonuniform(self):
'''test rebinning a non-uniform density'''
for nx in range(5,12):
x = np.linspace(0, 2*np.pi, nx)
y = np.sin(x)
edges = [0, 2*np.pi]
yy = rebin.trapz_rebin(x, y, edges=edges)
self.assertTrue(np.allclose(yy, 0.0))
x = np.linspace(0, 2*np.pi, 100)
y = np.sin(x)
edges = [0, 0.5*np.pi, np.pi, 1.5*np.pi, 2*np.pi]
yy = rebin.trapz_rebin(x, y, edges=edges)
self.assertTrue(np.allclose(yy[0:2], 2/np.pi, atol=5e-4))
self.assertTrue(np.allclose(yy[2:4], -2/np.pi, atol=5e-4))
def test_centers(self):
'''Test with centers instead of edges'''
nx = 10
x = np.arange(nx)
y = np.ones(nx)
xx = np.linspace(0.5, nx - 1.5)
yy = rebin.trapz_rebin(x, y, xx)
self.assertTrue(np.allclose(yy, 1.0), msg=str(yy))
def test_centers(self):
'''Test with centers instead of edges'''
nx = 10
x = np.arange(nx)
y = np.ones(nx)
xx = np.linspace(0.5, nx-1.5)
yy = rebin.trapz_rebin(x, y, xx)
self.assertTrue(np.allclose(yy, 1.0), msg=str(yy))
def test_trapzrebin(self):
'''Test constant flux density at various binnings'''
nx = 10
x = np.arange(nx) * 1.1
y = np.ones(nx)
#- test various binnings
for nedge in range(3, 10):
edges = np.linspace(min(x), max(x), nedge)
yy = rebin.trapz_rebin(x, y, edges=edges)
self.assertTrue(np.all(yy == 1.0), msg=str(yy))
#- edges starting/stopping in the interior
sum = rebin.trapz_rebin(x, y, edges=[0.5, 8.3])[0]
for nedge in range(3, 3 * nx):
edges = np.linspace(0.5, 8.3, nedge)
yy = rebin.trapz_rebin(x, y, edges=edges)
self.assertTrue(np.allclose(yy, 1.0), msg=str(yy))
def test_trapzrebin(self):
'''Test constant flux density at various binnings'''
nx = 10
x = np.arange(nx)*1.1
y = np.ones(nx)
#- test various binnings
for nedge in range(3,10):
edges = np.linspace(min(x), max(x), nedge)
yy = rebin.trapz_rebin(x, y, edges=edges)
self.assertTrue(np.all(yy == 1.0), msg=str(yy))
#- edges starting/stopping in the interior
sum = rebin.trapz_rebin(x, y, edges=[0.5, 8.3])[0]
for nedge in range(3, 3*nx):
edges = np.linspace(0.5, 8.3, nedge)
yy = rebin.trapz_rebin(x, y, edges=edges)
self.assertTrue(np.allclose(yy, 1.0), msg=str(yy))
def eval(self, coeff, wave, z):
'''
Return template for given coefficients, wavelengths, and redshift
Args:
coeff : array of coefficients length self.nbasis
wave : wavelengths at which to evaluate template flux
z : redshift at which to evaluate template flux
Returns:
template flux array
Notes:
A single factor of (1+z)^-1 is applied to the resampled flux
to conserve integrated flux after redshifting.
'''
assert len(coeff) == self.nbasis
flux = self.flux.T.dot(coeff).T / (1 + z)
return trapz_rebin(self.wave * (1 + z), flux, wave)
