Comments (3)
Hey @drewmee - yes, please! I think in terms of how it's implemented, it should take place at OPC definition stage - in other words, when you create an OPC, you should be able to set a parameter for how you allocate particles to bins. We can brainstorm some ideas for what this parameter should be called, but should default to what is used now. If there are other arguments/parameters that need to be set in order to make it work, then we can just add another kwarg such as prob_kwargs
or something like that...make sense?
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Thanks that makes sense. From my understanding the probability distribution used for bin assignment should bake in uncertainties in particle properties as well as the instrument-specific relationship between scattering signal amplitude and particle scattering cross section. The latter seems like the easiest place to start. As for the former, have you thought about how one might assign probability distributions for particle density, hygroscopic growth, and refractive index to each lognormal mode within an aerosol distribution, for example for an externally mixed sample? Correct me if I'm wrong but those properties are currently held constant for each mode in opcsim? Perhaps implementing a way to represent modes with heterogeneous properties should be addressed prior to any attempt at a bin-assignment algorithm. Maybe that should be raised/tracked in a whole different GH issue...
Please let me know if any of that made sense.
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Hey @drewmee I don't think that is necessarily the case, though I could see that being useful. I think the first step would be to just assign them probabilities based on whether the Cscat value was in a region where there is large uncertainty in the correct bin assignment. I think the composition and other uncertainty is next level!
You are correct that currently, each mode is treated separately, though you could create two identical modes of different composition. It shouldn't be too hard to build in core-shell model functionality, and there are examples (py-mie) that do this already and can be looked to for inspiration/code examples.
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Related Issues (20)
- Mention that the diameter we use in each bin is the geometric mean
- Take a look at how much we are over or underestimating each bin
- Verify the non-linear differences are real
- Figure out why the OPC isn't reporting large particles
- Add volume-weighted plots when we show number-weighted plots
- Lookup Roshan Gao's paper for calibration details
- Generate a method for bin mis-classification
- Provide method for multi-line fits (i.e., high and low-gain)
- Instead of squashing dips, use spline interpolation
- Fix home page text
- Write Nephelometer Tutorial
- Add Nephelometer example to gallery
- Write unittests for Nephelometer
- Correct bin diameter to use?
- Stop returning all bin params on .histogram()
- Fix examples in all code blocks - many are outdated
- Fix the gallery examples
- Add citation information HOT 1
- 2023 Updates!
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