- Timestamp:
- Feb 8, 2018 5:17:59 PM (7 years ago)
- Branches:
- master, core_shell_microgels, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests
- Children:
- e309e23
- Parents:
- a09d55d
- File:
-
- 1 edited
Legend:
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- Added
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-
explore/multiscat.py
ra09d55d r54a5024 170 170 171 171 def scattering_power(Iq, n): 172 """ 173 Calculate the nth scattering power as a distribution. To get the 174 weighted contribution, scale by $\lambda^k e^{-\lambda}/k!$. 175 """ 172 176 scale = np.sum(Iq) 173 177 F = _forward_fft(Iq/scale) 174 result = scale *_inverse_fft(F**n)178 result = _inverse_fft(F**n) 175 179 return result 176 180 … … 181 185 Given a probability p of scattering with the thickness, the expected 182 186 number of scattering events, $\lambda$ is $-\log(1 - p)$, giving a 183 Poisson weighted sum of single, double, triple, ... scattering patterns. 184 The number of patterns used is based on coverage (default 99%). If 185 return_poi 187 Poisson weighted sum of single, double, triple, etc. scattering patterns. 188 The number of patterns used is based on coverage (default 99%). 186 189 """ 187 190 L = -np.log(1-p)
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