Introduction

This module provides tools to simulate scattering intensities detected by POPS as a function of particle size, refractive index, and some more less obvious parameters. Simulations are based on mie scattering, which gives the module the name. The only function that is worth mentioning is the one below. Its worth exploring all the optional parameters.

Imports



In [1]:

    
from atmPy.aerosols.instruments.POPS import mie
%matplotlib inline



In [2]:

    
import matplotlib.pylab as plt
plt.rcParams['figure.dpi'] = 200

standard settings



In [6]:

    
d,amp = mie.makeMie_diameter(noOfdiameters=1000)



In [7]:

    
f,a = plt.subplots()
a.plot(d,amp)
a.loglog()
a.set_xlim((0.1,3))
a.set_ylabel('Signal intensity (arb. u.)')
a.set_xlabel('Diameter ($\mu$m)')









    Out[7]:





Text(0.5, 0, 'Diameter ($\\mu$m)')

Wavelength dependence

as an example what would it mean to use a 445nm instead of a 405nm laser



In [35]:

    
noofpoints = 1000
d,amp405 = mie.makeMie_diameter(noOfdiameters=noofpoints, WavelengthInUm=0.405)
d,amp445 = mie.makeMie_diameter(noOfdiameters=noofpoints, WavelengthInUm=0.445)



In [36]:

    
f,a = plt.subplots()
a.plot(d, amp405, label = '405')
a.plot(d, amp445, label = '445')
a.loglog()









    Out[36]:





[]



In [38]:

    
lim = [0.14, 3]
arglim = [abs(d - lim[0]).argmin(), abs(d - lim[1]).argmin()]
# arglim

scs_at_lim_405= amp405[arglim]
# scs_at_lim_405

#w the lower detection limit will go up to 
d[abs(amp445 - scs_at_lim_405[0]).argmin()]









    Out[38]:





0.15409274138061216

refractive index dependence



In [75]:

    
nop = 1000
dI,ampI = mie.makeMie_diameter(noOfdiameters=nop, IOR=1.4)
dII,ampII = mie.makeMie_diameter(noOfdiameters=nop, IOR=1.5)
dIII,ampIII = mie.makeMie_diameter(noOfdiameters=nop, IOR=1.6)



In [ ]:



In [76]:

    
f,a = plt.subplots()
a.plot(dI,ampI)
a.plot(dII,ampII)
a.plot(dIII,ampIII)

a.loglog()
a.set_xlim((0.1,3))
a.set_ylabel('Signal intensity (arb. u.)')
a.set_xlabel('Diameter ($\mu$m)')









    














    











    Out[76]:





<matplotlib.text.Text at 0x10d980390>