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solver.py
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solver.py
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"""
This module defines an `RTE` object which sets up an SHDOM solution to the
RTE equation through calls to fortran subroutines. See src/polarized/shdomsub1.f etc.
xr.Datasets prepared from sensor, source, surface, medium/mie/size_distribution are
used here.
containers.py contains a `SolversDict` object which stores multiple solver.RTE
objects and can be used for parallelization of solving the RTE etc.
"""
import sys
import warnings
import copy
import typing
from collections import OrderedDict
import psutil
import xarray as xr
import numpy as np
import at3d.core
import at3d.util
import at3d.checks
class ShdomPropertyArrays(object):
"""
Shdom property array module.
Contains the parameters that were in the original SHDOM_PROPERTY_ARRAYS module
in shdom90.f90.
This contains arrays that have been formatted for input to SHDOM routines
but have not yet been fully preprocessed through delta scaling etc. In the
original SHDOM, the arrays here are formed by PROPGEN and associated routines.
In our case, the data is simply rearranged from python inputs as those are
already defined on 'SHDOM-like' grids (see grid.py).
Parameters
----------
npx: int
Number of x grid points
npy: int
Number of y grid points
npz: int
Number of z grid points
numphase: int
Number of phase function enteries in the table
delx: float32
Delta-x spacing
dely: float32
Delta-y spacing
xstart: float32
Starting position of x coordinates
ystart: float32
Starting position of y coordinates
zlevels: np.ndarray(shape=(npz,), dtype=np.float32))
Altitude grid points
tempp: np.ndarray
Temperatures at grid points
extinctp: np.ndarray
Extinction on grid
albedop: np.ndarray
Single scattering albedo grid
legenp: np.ndarray
legendre phase function table
extdirp: np.ndarray
Delta-M scaled extinction on grid, used for calculating direct beam.
iphasep: np.ndarray, dtype=np.int32
pointer to phase function table
nzckd: int
Number of correlated-k distribution points
zckd: np.ndarray
correlated-k distribution z levels.
gasabs: np.ndarray, shape=(npz,)
Gas absorption extinction on vertical levels.
nlegp: int
Number of legendre moments in full phase functio expansions (legenp)
max_num_micro: int
The maximum number of phase functions to mix per grid point across
all scattering species.
phasewtp: np.ndarray
interpolation weights for mixtures of phase functions.
"""
def __init__(self):
self.npx = None
self.npy = None
self.npz = None
self.numphase = None
self.delx = None
self.dely = None
self.xstart = None
self.ystart = None
self.zlevels = None
self.tempp = None
self.extinctp = None
self.albedop = None
self.legenp = None
self.extdirp = None
self.iphasep = None
self.nzckd = None
self.zckd = None
self.gasabs = None
self.nlegp = None
self.max_num_micro = None
self.phasewtp = None
class RTE:
"""
Radiative Transfer solver object.
This object contains the interface to SHDOM's internal structures and methods.
Rather than reading inputs from files, the xr.Datasets are directly passed to
instantiate this class.
Parameters
----------
medium: list or xr.dataset
A list or dataset containing the optical properties of the different scatter types within the medium
numerical_params: xr.dataset
A dataset containing the numerical parameters requiered for the RTE solution. These can be loaded
from a config file (see ancillary_data/config.cfg).
num_stokes: int, default=1
The number of stokes for which to solve the RTE can be 1, 3, or 4.
num_stokes=1 means unpolarized.
num_stokes=3 means linear polarization.
num_stokes=4 means full polarization.
name: str, optional
The name for the solver. Will be used when printing solution iteration messages.
If non specified a default <type> <wavelength> is given, where <type> is Radiance for num_stokes=1 and
Polarized for num_stokes>1
Notes
-----
k-distribution not supported.
"""
def __init__(self, numerical_params, medium, source, surface, num_stokes=1, name=None,
atmosphere=None):
# Check number of stokes and setup type of solver
if num_stokes not in (1, 3, 4):
raise ValueError("num_stokes should be in (1, 3, 4) not '{}'".format(num_stokes))
self._type = 'Radiance' if num_stokes == 1 else 'Polarization'
self._nstokes = num_stokes
self._nstleg = 1 if num_stokes == 1 else 6
# If the second character is 'O' then 'max scattering' interpolation
# of phase functions occurs. If the second character is 'N' then
# linear mixing of phase functions occurs.
self._interpmethod = 'ON'
# phasemax is only used for linear mixing of phase functions
# and is the threshold for the weight for neglecting the
# contributions of other phase functions.
self._phasemax = 0.999
self._adjflag = False # Used for testing the adjoint source.
self._newmethod = True # Used for testing the fast multi-species source computation
# vs the slow multi-species source computation.
self._longest_path_pts = 1
# Set this to 1 by default as it is used for solar direct beam derivatives
# and isn't necessarily needed for thermal.
self._correctinterpolate = True
# Flag for switching between the 'Radiance' and 'Visualization'
# methods for calculating radiances in original SHDOM.
# This is added for verification against original SHDOM.
# The methods only differ in calculations when line integrations
# pass through a region with varying grid resolution.
# `True` corresponds to the 'Visualization' method which utilizes
# a more accurate interpolation for the source-extinction
# product than the 'Radiance' method.
self.source = self._setup_source(source)
self.medium, self._grid = self._setup_medium(medium)
# Setup a name for the solver
self._name = '{} {:1.3f} micron'.format(self._type, self.wavelength) if name is None else name
#Start mpi (if available). This is a dummy routine. MPI is not currently supported.
self._masterproc = at3d.core.start_mpi()
# Link to the properties array module.
self._pa = ShdomPropertyArrays()
# k-distribution not supported yet
self._kdist = False
self._ng = 1
self._delg = np.ones(1, order='F')
self._pa.nzckd = 0
self._baseout = False
self._npart = 1
# No iterations have taken place
self._iters = 0
self.numerical_params = self._setup_numerical_params(numerical_params)
self._setup_grid(self._grid)
self.surface = self._setup_surface(surface)
# atmosphere includes temperature for thermal radiation
self.atmosphere = self._setup_atmosphere(atmosphere)
#these warnings can only be done after both surface and numerical params.
flux = 0.0
if self._srctype in ('T', 'B'):
#Surface flux is typically the warmest and therefore largest flux
#so it is used as guidance for the splitting accuracy.
flux = np.pi*at3d.util.planck_function(self._gndtemp, self.wavelength)
if self._srctype != 'T':
flux += self._solarflux
if (self._splitacc > 0.0) & ((self._splitacc < 0.001*flux) | (self._splitacc > 0.1*flux)):
warnings.warn("Splitting accuracy parameter is not a fraction but scales with fluxes."
" splitacc/nominal flux = {}".format(self._splitacc/flux))
if (self._shacc > 0.0) & (self._shacc > 0.03*flux):
warnings.warn("spherical_harmonics_accuracy is not a fraction but scales with fluxes."
" SHACC/nominal flux = {}".format(self._shacc/flux))
#this is called at initialization so that warnings about the optical
#thickness across cells in the medium can be called to warn a user
#before they try to run RTE.solve().
self._prepare_optical_properties()
#here is where an xr.Dataset containing a solved solution will go
#if it is loaded (self.load_solution.) in preparation to be read into
#memory for the self.solve method. (in self._init_solution.)
self._restore_data = None
self._setup_grid_flag = True
#set the cached spherical_harmonics and net flux divergence to None
self._netfluxdiv = None
self._shterms = None
#Initialize solution criterion here so that we can use it to check
#if RTE is 'solved'.
self._solcrit = None
#initialize these attributes that are only filled with the
#true memory-related numerical parameters after an SHDOM solution.
self._maxmb_out = None
self._adapt_grid_factor_out = None
self._shterm_fac_out = None
self._cell_point_out = None
@property
def final_maxmb(self):
return self._maxmb_out
@property
def final_adapt_grid_factor(self):
return self._adapt_grid_factor_out
@property
def final_shterm_factor(self):
return self._shterm_fac_out
@property
def final_cell_point_ratio(self):
return self._cell_point_out
@property
def solution_accuracy(self):
return self._solacc
def set_solution_accuracy(self, val):
"""
Update the solution accuracy to allow a more accurate solution to
be iterated towards without reinitializing the solver.
"""
self._solacc = val
self.numerical_params['solacc'] = val
#important to update both consistently.
def solve(self, maxiter, init_solution=True, setup_grid=True, verbose=True,
solve=True):
"""
Main solver routine. This routine is comprised of two parts:
1. Initialization, optional
2. Solution iterations
Parameters
----------
maxiter: integer
Maximum number of iterations for the iterative solution to SHDOM.
setup_grid: boolean
If True then a new grid is initialized. If False then the grid
(including adaptive grid points)
init_solution: boolean, default=True
If False then a solution is initialized. This is overwritten
to True if no existing Radiance/Source function fields exist.
The solution initialization will use a Radiance/Source field provided
by RTE.load_solution or use a 1D two-stream model.
verbose: boolean
True will output solution iteration information into stdout.
"""
if not isinstance(verbose, bool):
raise TypeError("`verbose` should be a boolean.")
if not isinstance(init_solution, bool):
raise TypeError("`init_solution` should be a boolean.")
if not isinstance(setup_grid, bool):
raise TypeError("`setup_grid` should be a boolean.")
# Part 1: Initialize solution (from a 1D layered model)
# or from a loaded solution if available.
if np.any([not hasattr(self, attr) for attr in ('_radiance', '_source', '_fluxes')]) \
and (not init_solution):
warnings.warn(
"RTE object does not have initialized Radiance/Source fields as such, the"
" `init_solution` flag has been overwritten and a solution will be initialized.")
init_solution = True
if init_solution:
self._init_solution(
setup_grid=setup_grid,
)
if not self.check_solved(verbose=False):
if maxiter <= self._iters:
warnings.warn(
"The solver is not converged to the specified accuracy but maxiter "
"has already been exceeded. Please increase `maxiter`."
)
#set the cached spherical_harmonics and net flux divergence to None
#as a new solution has been formed. This is also done in ._init_solution
#AND here as either could be done without the other and either way the
#cached values are no longer representative.
self._netfluxdiv = None
self._shterms = None
# Part 2: Solution itertaions
# This is the time consuming part, equivalent to SOLVE_RTE in SHDOM.
# All of these arrays are initialized in _init_solution or _setup_grid.
# And are modified in-place to reflect the solved RTE.
self._sfcgridparms, self._solcrit, self._iters, self._temp, self._planck, \
self._extinct, self._albedo, self._legen, self._iphase, self._ntoppts, \
self._nbotpts, self._bcptr, self._bcrad, self._npts, self._gridpos, \
self._ncells, self._gridptr, self._neighptr, self._treeptr, self._cellflags, \
self._rshptr, self._shptr, self._oshptr, self._source, self._delsource, \
self._radiance, self._fluxes, self._dirflux, self._uniformzlev, \
self._pa.extdirp, self._oldnpts, self._total_ext, self._deljdot, \
self._deljold, self._deljnew, self._jnorm, self._work, self._work1, \
self._work2, ierr, errmsg, self._phaseinterpwt, self._cpu_time \
= at3d.core.solution_iterations(
transmin=self._transmin,
newmethod=self._newmethod,
verbose=verbose,
solve=solve,
maxnmicro=self._pa.max_num_micro,
phasewtp=self._pa.phasewtp,
nlegp=self._pa.nlegp,
phasemax=self._phasemax,
phaseinterpwt=self._phaseinterpwt,
interpmethod=self._interpmethod,
iterfixsh=self._iterfixsh,
iter=self._iters,
uniform_sfc_brdf=self._uniform_sfc_brdf,
sfc_brdf_do=self._sfc_brdf_do,
work=self._work,
work1=self._work1,
work2=self._work2,
bcrad=self._bcrad,
fluxes=self._fluxes,
nang=self._nang,
nphi0=self._nphi0,
maxnbc=self._maxnbc,
ntoppts=self._ntoppts,
nbotpts=self._nbotpts,
uniformzlev=self._uniformzlev,
extmin=self._extmin,
scatmin=self._scatmin,
cx=self._cx,
cy=self._cy,
cz=self._cz,
cxinv=self._cxinv,
cyinv=self._cyinv,
czinv=self._czinv,
ipdirect=self._ipdirect,
di=self._di,
dj=self._dj,
dk=self._dk,
nphi0max=self._nphi0max,
epss=self._epss,
epsz=self._epsz,
xdomain=self._xdomain,
ydomain=self._ydomain,
delxd=self._delxd,
delyd=self._delyd,
albmax=self._albmax,
deljdot=self._deljdot,
deljold=self._deljold,
deljnew=self._deljnew,
jnorm=self._jnorm,
fftflag=self._fftflag,
cmu1=self._cmu1,
cmu2=self._cmu2,
wtmu=self._wtmu,
cphi1=self._cphi1,
cphi2=self._cphi2,
wphisave=self._wphisave,
nbpts=self._nbpts,
npart=self._npart,
extinct=self._extinct,
albedo=self._albedo,
legen=self._legen,
total_ext=self._total_ext,
extinctp=self._pa.extinctp,
albedop=self._pa.albedop,
planck=self._planck,
iphase=self._iphase,
iphasep=self._pa.iphasep,
nstokes=self._nstokes,
nstleg=self._nstleg,
npx=self._pa.npx,
npy=self._pa.npy,
npz=self._pa.npz,
delx=self._pa.delx,
dely=self._pa.dely,
xstart=self._pa.xstart,
ystart=self._pa.ystart,
zlevels=self._pa.zlevels,
tempp=self._pa.tempp,
legenp=self._pa.legenp,
extdirp=self._pa.extdirp,
nzckd=self._pa.nzckd,
zckd=self._pa.zckd,
gasabs=self._pa.gasabs,
solcrit=self._solcrit,
nx=self._nx,
ny=self._ny,
nx1=self._nx1,
ny1=self._ny1,
nz=self._nz,
ml=self._ml,
mm=self._mm,
ncs=self._ncs,
nlm=self._nlm,
nmu=self._nmu,
nphi=self._nphi,
numphase=self._pa.numphase,
mu=self._mu,
phi=self._phi,
wtdo=self._wtdo,
bcflag=self._bcflag,
ipflag=self._ipflag,
deltam=self._deltam,
srctype=self._srctype,
highorderrad=self._highorderrad,
solarflux=self._solarflux,
solarmu=self._solarmu,
solaraz=self._solaraz,
skyrad=self._skyrad,
sfctype=self._sfctype,
gndtemp=self._gndtemp,
gndalbedo=self._gndalbedo,
nxsfc=self._nxsfc,
nysfc=self._nysfc,
delxsfc=self._delxsfc,
delysfc=self._delysfc,
nsfcpar=self._nsfcpar,
sfcparms=self._sfcparms,
sfcgridparms=self._sfcgridparms,
units=self._units,
waveno=self._waveno,
wavelen=self.wavelength,
accelflag=self._accelflag,
solacc=self._solacc,
maxiter=maxiter,
splitacc=self._splitacc,
shacc=self._shacc,
xgrid=self._xgrid,
ygrid=self._ygrid,
zgrid=self._zgrid,
temp=self._temp,
maxbcrad=self._maxbcrad,
bcptr=self._bcptr,
npts=self._npts,
gridpos=self._gridpos,
ncells=self._ncells,
gridptr=self._gridptr,
neighptr=self._neighptr,
treeptr=self._treeptr,
cellflags=self._cellflags,
rshptr=self._rshptr,
shptr=self._shptr,
oshptr=self._oshptr,
source=self._source,
delsource=self._delsource,
radiance=self._radiance,
dirflux=self._dirflux,
nleg=self._nleg,
maxiv=self._maxiv,
maxic=self._maxic,
maxig=self._maxig,
maxido=self._maxido,
oldnpts=self._oldnpts,
ylmsun=self._ylmsun,
runname=self._name
)
at3d.checks.check_errcode(ierr, errmsg)
nsh = self._shptr[self._npts]
self._maxmb_out = 4*(self._nmu*(2+2*self._nphi + 2*self._nlm+2*33*32) \
+ 4.5*self._maxpg + self._maxpgl + self._nstleg*self._pa.numphase*(self._nleg + 1) \
+ 16.5*self._ncells + self._npts*(28+self._nphi0max*self._nstokes) \
+ self._nstokes*nsh*self._big_arrays)/(1024**2)
self._adapt_grid_factor_out = self._npts/self._nbpts
self._shterm_fac_out = nsh/(self._nlm*self._npts)
self._cell_point_out = self._ncells/self._npts
# if verbose:
# warnings.warn("Actual MAX_TOTAL_MB: {:.2f}".format(self._maxmb_out))
# warnings.warn("Actual adapt_grid_factor: {:.4f}".format(self._adapt_grid_factor_out))
# warnings.warn("Actual cell_point_ratio: {:.4f}".format(self._cell_point_out))
def integrate_to_sensor(self, sensor, single_scatter=False):
"""Calculates the StokesVector at specified geometry using an RTE solution.
Integrates the source function along rays with positions and
directions specified in sensor. This is the method SHDOM uses to calculate
Radiances. Each 'ray' StokesVector is as close to an idealized (delta function)
sampling of the radiance field as the discretization used by SHDOM allows.
As such the ray values are not area averaged.
Parameters
----------
sensor : xr.Dataset
A valid at3d sensor dataset (see sensor.py) that contains AT LEAST
the ray geometries required to perform the Source function integration.
Returns
-------
sensor : xr.Dataset
The same sensor that was input but modified in-place by the addition
of the simulated Stokes Vector.
"""
if not isinstance(sensor, xr.Dataset):
raise TypeError("`sensor` should be an xr.Dataset not "
"of type '{}''".format(type(sensor)))
at3d.checks.check_hasdim(sensor, ray_mu='nrays', ray_phi='nrays',
ray_x='nrays', ray_y='nrays', ray_z='nrays',
stokes='stokes_index')
if 'nimage' in sensor.stokes.dims:
stokes_averaged = sensor.stokes.any('nimage')
else:
stokes_averaged = sensor.stokes
if stokes_averaged.sum('stokes_index') > self._nstokes:
raise ValueError("'{}' Stokes components are required by sensor but RTE "
"only has nstokes={}".format(stokes_averaged.data,
self._nstokes)
)
camx = sensor['ray_x'].data
camy = sensor['ray_y'].data
camz = sensor['ray_z'].data
cammu = sensor['ray_mu'].data
camphi = sensor['ray_phi'].data
total_pix = sensor.sizes['nrays']
self.check_solved()
self._precompute_phase()
self._bcrad_output, output, ierr, errmsg = at3d.core.render(
correctinterpolate=self._correctinterpolate,
singlescatter=single_scatter,
transcut=self._transcut,
tautol=self._tautol,
maxnmicro=self._pa.max_num_micro,
interpmethod=self._interpmethod,
phaseinterpwt=self._phaseinterpwt[:,:self._npts,:],
phasemax=self._phasemax,
nstphase=self._nstphase,
ylmsun=self._ylmsun,
phasetab=self._phasetab,
nscatangle=self._nscatangle,
ncs=self._ncs,
nstokes=self._nstokes,
nstleg=self._nstleg,
camx=camx,
camy=camy,
camz=camz,
cammu=cammu,
camphi=camphi,
npix=total_pix,
nx=self._nx,
ny=self._ny,
nz=self._nz,
bcflag=self._bcflag,
ipflag=self._ipflag,
npts=self._npts,
ncells=self._ncells,
ml=self._ml,
mm=self._mm,
nlm=self._nlm,
numphase=self._pa.numphase,
nmu=self._nmu,
nphi0max=self._nphi0max,
nphi0=self._nphi0,
maxnbc=self._maxnbc,
ntoppts=self._ntoppts,
nbotpts=self._nbotpts,
nsfcpar=self._nsfcpar,
gridptr=self._gridptr,
neighptr=self._neighptr,
treeptr=self._treeptr,
shptr=self._shptr,
bcptr=self._bcptr,
cellflags=self._cellflags,
iphase=self._iphase[:,:self._npts],
deltam=self._deltam,
solarmu=self._solarmu,
solaraz=self._solaraz,
gndtemp=self._gndtemp,
gndalbedo=self._gndalbedo,
skyrad=self._skyrad,
waveno=self._waveno,
wavelen=self.wavelength,
mu=self._mu,
phi=self._phi.reshape(self._nmu, -1),
wtdo=self._wtdo.reshape(self._nmu, -1),
xgrid=self._xgrid,
ygrid=self._ygrid,
zgrid=self._zgrid,
gridpos=self._gridpos,
sfcgridparms=self._sfcgridparms,
bcrad=copy.deepcopy(self._bcrad), #deep copied as it is modified in place
#which is otherwise bad for parallelization.
extinct=self._extinct[:self._npts],
albedo=self._albedo[:self._npts],
legen=self._legen,
dirflux=self._dirflux,
fluxes=self._fluxes,
source=self._source,
srctype=self._srctype,
sfctype=self._sfctype,
units=self._units,
total_ext=self._total_ext[:self._npts],
npart=self._npart)
at3d.checks.check_errcode(ierr, errmsg)
sensor['I'] = xr.DataArray(
data=output[0],
dims='nrays',
attrs={
'long_name': 'Radiance'
}
)
if self._nstokes > 1:
sensor['Q'] = xr.DataArray(
data=output[1],
dims='nrays',
attrs={
'long_name': 'Stokes Parameter for Linear Polarization (Q)'
}
)
sensor['U'] = xr.DataArray(
data=output[2],
dims='nrays',
attrs={
'long_name': 'Stokes Parameter for Linear Polarization (U)'
}
)
if self._nstokes == 4:
sensor['V'] = xr.DataArray(
data=output[3],
dims='nrays',
attrs={
'long_name': 'Stokes Parameter for Circular Polarization (V)'
}
)
return sensor
def optical_path(self, sensor, deltam_scaled_path=False):
"""Calculates the optical paths along specified rays by integrating
the extinction field.
Parameters
----------
sensor : xr.Dataset
A valid at3d sensor dataset (see sensor.py) that contains AT LEAST
the ray geometries required to define the line integration of extinction.
deltam_scaled_path : bool
If True then the optical path is calculated for the delta-M scaled
extinction, if False then the total extinction of the field is used.
Returns
-------
sensor : xr.Dataset
The same `sensor` as input but modified in place to include the
calculated optical paths.
"""
if not isinstance(sensor, xr.Dataset):
raise TypeError("`sensor` should be an xr.Dataset "
"not of type '{}''".format(type(sensor)))
at3d.checks.check_hasdim(sensor, ray_mu='nrays', ray_phi='nrays',
ray_x='nrays', ray_y='nrays', ray_z='nrays')
camx = sensor['ray_x'].data
camy = sensor['ray_y'].data
camz = sensor['ray_z'].data
cammu = sensor['ray_mu'].data
camphi = sensor['ray_phi'].data
total_pix = sensor.sizes['nrays']
optical_path = at3d.core.optical_depth(
maxnmicro=self._pa.max_num_micro,
interpmethod=self._interpmethod,
phasemax=self._phasemax,
phaseinterpwt=self._phaseinterpwt[:, :self._npts],
nx=self._nx,
ny=self._ny,
nz=self._nz,
npts=self._npts,
ncells=self._ncells,
gridptr=self._gridptr,
neighptr=self._neighptr,
treeptr=self._treeptr,
cellflags=self._cellflags,
bcflag=self._bcflag,
ipflag=self._ipflag,
xgrid=self._xgrid,
ygrid=self._ygrid,
zgrid=self._zgrid,
gridpos=self._gridpos,
camx=camx,
camy=camy,
camz=camz,
cammu=cammu,
camphi=camphi,
npix=total_pix,
extinct=self._extinct[:self._npts],
albedo=self._albedo[:self._npts],
iphase=self._iphase[:, :self._npts],
legen=self._legen,
npart=self._npart,
nstleg=self._nstleg,
deltam=self._deltam,
deltampath=deltam_scaled_path,
nleg=self._nleg,
ml=self._ml
)
if deltam_scaled_path:
sensor['optical_path_deltam'] = (['nrays'], optical_path)
else:
sensor['optical_path'] = (['nrays'], optical_path)
return sensor
def transmission_integral(self, sensor, field):
if not isinstance(sensor, xr.Dataset):
raise TypeError("`sensor` should be an xr.Dataset "
" not of type '{}''".format(type(sensor)))
at3d.checks.check_hasdim(sensor, ray_mu='nrays', ray_phi='nrays',
ray_x='nrays', ray_y='nrays', ray_z='nrays')
camx = sensor['ray_x'].data
camy = sensor['ray_y'].data
camz = sensor['ray_z'].data
cammu = sensor['ray_mu'].data
camphi = sensor['ray_phi'].data
total_pix = sensor.sizes['nrays']
if self.check_solved(verbose=False):
raise at3d.exceptions.SHDOMError(
"This function can only be run before RTE.solve()"
)
transmission_integral = at3d.core.transmission_integral(
nx=self._nx,
ny=self._ny,
nz=self._nz,
npts=self._npts,
ncells=self._ncells,
gridptr=self._gridptr,
neighptr=self._neighptr,
treeptr=self._treeptr,
cellflags=self._cellflags,
bcflag=self._bcflag,
ipflag=self._ipflag,
xgrid=self._xgrid,
ygrid=self._ygrid,
zgrid=self._zgrid,
gridpos=self._gridpos,
camx=camx,
camy=camy,
camz=camz,
cammu=cammu,
camphi=camphi,
npix=total_pix,
total_ext=self._total_ext[:self._npts],
field=field,
transcut=self._transcut,
tautol=self._tautol
)
sensor['transmission_integral'] = (['nrays'], transmission_integral)
return sensor
def min_optical_path(self, sensor, deltam_scaled_path=False, do_all=False):
if not isinstance(sensor, xr.Dataset):
raise TypeError("`sensor` should be an xr.Dataset "
" not of type '{}''".format(type(sensor)))
at3d.checks.check_hasdim(sensor, ray_mu='nrays', ray_phi='nrays',
ray_x='nrays', ray_y='nrays', ray_z='nrays')
camx = sensor['ray_x'].data
camy = sensor['ray_y'].data
camz = sensor['ray_z'].data
cammu = sensor['ray_mu'].data
camphi = sensor['ray_phi'].data
total_pix = sensor.sizes['nrays']
if self.check_solved(verbose=False):
raise at3d.exceptions.SHDOMError(
"This function can only be run before RTE.solve()"
)
if do_all:
#optical_path = np.zeros((npixels, self._npts))
paths_size = total_pix
else:
paths_size = 1
optical_path = at3d.core.min_optical_depth(
maxnmicro=self._pa.max_num_micro,
interpmethod=self._interpmethod,
phasemax=self._phasemax,
phaseinterpwt=self._phaseinterpwt[:, :self._npts],
nx=self._nx,
ny=self._ny,
nz=self._nz,
npts=self._npts,
ncells=self._ncells,
gridptr=self._gridptr,
neighptr=self._neighptr,
treeptr=self._treeptr,
cellflags=self._cellflags,
bcflag=self._bcflag,
ipflag=self._ipflag,
xgrid=self._xgrid,
ygrid=self._ygrid,
zgrid=self._zgrid,
gridpos=self._gridpos,
camx=camx,
camy=camy,
camz=camz,
cammu=cammu,
camphi=camphi,
npix=total_pix,
extinct=self._extinct[:self._npts],
albedo=self._albedo[:self._npts],
iphase=self._iphase[:, :self._npts],
legen=self._legen,
npart=self._npart,
nstleg=self._nstleg,
deltam=self._deltam,
deltampath=deltam_scaled_path,
paths_size=paths_size,
nleg=self._nleg,
ml=self._ml
)
name = 'min_optical_path'
if deltam_scaled_path:
name = name + '_deltam'
if do_all:
optical_path_dataset = xr.Dataset(
data_vars={
name:(['x', 'y', 'z', 'npixels'],
optical_path[:self._nbpts, :].reshape(
self._nx, self._ny, self._nz, -1)
)},
coords={'x': self._grid.x,
'y': self._grid.y,
'z': self._grid.z,
},
)
else:
optical_path_dataset = xr.Dataset(
data_vars={
name:(['x', 'y', 'z'],
optical_path[:self._nbpts, 0].reshape(
self._nx, self._ny, self._nz)
)},
coords={'x': self._grid.x,
'y': self._grid.y,
'z': self._grid.z,
},
)
return optical_path_dataset
def check_solved(self, verbose=True):
"""
A simple check on whether the solver solution has actually converged.
Useful for determining if outputs should be truested. May be used just to
print a warning or in some contexts the flag may be used to raise an Exception,
for example.
"""
#note that evaluation is sequential. If the first criterion is True,
#the subsequent in an or statement are not even evaluated so this won't
#cause an error.
flag = True
if self._solcrit is None or (self._solcrit >= self._solacc):
flag = False
if verbose:
warnings.warn(
"Solution has not converged to the "
"specified accuracy log10(SOLCRIT): {:3f} > log10(SOLUTION_ACCURACY): {:3f}. "
"Calculated quantities will not be accurate.".format(
np.log10(self._solcrit), np.log10(self._solacc)
)
)
return flag
@property
def spherical_harmonics(self):
"""
Calculates the mean intensity and 3 spatial fluxes (Fx, Fy, Fz) of the
radiation field.
This is equivalent SH_OUT from SHDOM in a dataset but only on the tidy base grid,
so the same as the netCDF output. If output on the adaptive grid points
access the self.shterms property as all values are stored there in
array form.
The root-mean-square of the higher order radiance terms is also
returned if the `high_order_radiance` was set to True in the
numerical_parameters used to initialize the `RTE` object.
Returns
-------
sh_out_dataset : xr.Dataset
Dataset containing mean intensity and 3 spatial fluxes (Fx, Fy, Fz)
on SHDOM's base grid.
Notes
-----
This is basically a wrapper for COMPUTE_SH in src/shdomsub2.f
"""
self.check_solved()
if self._highorderrad:
nshout = 5
else:
nshout = 4
if self._shterms is None:
shterms = at3d.core.compute_sh(nshout=nshout,
nstokes=self._nstokes,
npts=self._npts,
srctype=self._srctype,
solarmu=self._solarmu,
solaraz=self._solaraz,
dirflux=self._dirflux[:self._npts],
rshptr=self._rshptr[:self._npts+1],
ml=self._ml,
mm=self._mm,
radiance=self._radiance,
)
self._shterms = shterms
if len(self._xgrid) == self._nx1:
xcoord = self._xgrid
elif len(self._xgrid)-1 == self._nx1:
xcoord = self._xgrid[:-1]
else:
raise at3d.exceptions.SHDOMError(
"Inconsistent sizes of RTE grid and property grid. "
"There has been a mistake in interpretation."
)
if len(self._ygrid) == self._ny1:
ycoord = self._ygrid
elif len(self._ygrid)-1 == self._ny1:
ycoord = self._ygrid[:-1]
else:
raise at3d.exceptions.SHDOMError(
"Inconsistent sizes of RTE grid and property grid. "
"There has been a mistake in interpretation."
)
sh_out_dataset = xr.Dataset(
data_vars={
'mean_intensity': (['x', 'y', 'z'], self._shterms[0, :self._nbpts].reshape(
self._nx1, self._ny1, self._nz)),
'Fx': (['x', 'y', 'z'], self._shterms[1, :self._nbpts].reshape(
self._nx1, self._ny1, self._nz)),
'Fy': (['x', 'y', 'z'], self._shterms[2, :self._nbpts].reshape(
self._nx1, self._ny1, self._nz)),
'Fz': (['x', 'y', 'z'], self._shterms[3, :self._nbpts].reshape(
self._nx1, self._ny1, self._nz)),
},
coords={'x': xcoord,
'y': ycoord,
'z': self._zgrid,
},
attrs={
'long_names':{'Fx': 'Net Flux in x direction',
'Fy': 'Net Flux in y direction',
'Fz': 'Net Flux in z direction'},
}
)
if self._highorderrad & (self._shterms.shape[0] == 5):
sh_out_dataset['rms_higher_rad'] = (['x', 'y', 'z'],
self._shterms[-1, :self._nbpts].reshape(
self._nx1, self._ny1, self._nz)/ \
(np.sqrt(np.pi*4.0*self._nlm)))
return sh_out_dataset