# source:sasmodels/sasmodels/models/porod.py@cc3fac6

core_shell_microgelscostrafo411magnetic_modelrelease_v0.94release_v0.95ticket-1257-vesicle-productticket_1156ticket_1265_superballticket_822_more_unit_tests
Last change on this file since cc3fac6 was cc3fac6, checked in by Doucet, Mathieu <doucetm@…>, 8 years ago

Convert Guinier-Porod model

• Property mode set to 100644
File size: 1.2 KB
Line
1r"""
2This model fits the Porod function
3
4.. math::
5
6    I(q) = C/q^4
7    \\
8    C = 2\pi (\Delta\rho)^2 S_v
9
10to the data directly without any need for linearisation (cf. Log I(q) vs Log q).
11
12Here $C$ is the scale factor and $S_v$ is the specific surface area (ie, surface area / volume)
13of the sample, and $\Delta\rho$ is the contrast factor.
14
15For 2D data: The 2D scattering intensity is calculated in the same way as 1D,
16where the q vector is defined as
17
18.. math::
19    q = \sqrt{q_x^2+q_y^2}
20
21"""
22
23from numpy import sqrt, power
24
25name = "porod"
26title = "Porod function"
27description = """\
28          I(q) = scale/q^4 + background
29"""
30
31category = "shape-independent"
32
33parameters = []
34
35def Iq(q):
36    """
37    @param q: Input q-value
38    """
39    return 1.0/power(q, 4)
40
41Iq.vectorized = True  # Iq accepts an array of q values
42
43def Iqxy(qx, qy, *args):
44    """
45    @param qx:   Input q_x-value
46    @param qy:   Input q_y-value
47    @param args: Remaining arguments
48    """
49    return Iq(sqrt(qx ** 2 + qy ** 2), *args)
50
51Iqxy.vectorized = True # Iqxy accepts an array of qx, qy values
52
53demo = dict(scale=1.5, background=0.5)
54
55oldname = "PorodModel"
56oldpars = dict(scale='scale', background='background')
57
58tests = [[{'scale': 0.00001, 'background':0.01}, 0.04, 3.916250]]
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