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Tom Rink
python
Commits
0c8882bf
Commit
0c8882bf
authored
9 months ago
by
tomrink
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modules/util/romio.py
+0
-64
0 additions, 64 deletions
modules/util/romio.py
modules/util/sss1day_FMB_py3.py
+0
-308
0 additions, 308 deletions
modules/util/sss1day_FMB_py3.py
with
0 additions
and
372 deletions
modules/util/romio.py
deleted
100644 → 0
+
0
−
64
View file @
8ae8c5a8
import
xarray
as
xr
import
numpy
as
np
from
util.geos_nav
import
GEOSNavigation
from
netCDF4
import
Dataset
import
pickle
from
util.util
import
haversine_np
def
romio_to_fgf
(
filename
,
goes_e_w
=
'
EAST
'
):
ds
=
xr
.
open_dataset
(
filename
,
engine
=
'
cfgrib
'
)
lons
=
ds
[
'
longitude
'
]
lats
=
ds
[
'
latitude
'
]
lons
=
lons
.
values
lats
=
lats
.
values
lat_array
,
lon_array
=
np
.
meshgrid
(
lats
,
lons
,
indexing
=
'
ij
'
)
nav
=
GEOSNavigation
()
if
goes_e_w
==
'
EAST
'
:
nav
=
GEOSNavigation
()
elif
goes_e_w
==
'
WEST
'
:
nav
=
GEOSNavigation
(
sub_lon
=-
137.0
)
cc
,
ll
=
nav
.
earth_to_lc_s
(
lon_array
.
flatten
(),
lat_array
.
flatten
())
tlons
,
tlats
=
nav
.
lc_to_earth
(
cc
,
ll
)
dist
=
haversine_np
(
lon_array
.
flatten
(),
lat_array
.
flatten
(),
tlons
,
tlats
)
ok
=
np
.
invert
(
np
.
isnan
(
dist
))
print
(
np
.
average
(
dist
[
ok
]))
print
(
np
.
histogram
(
dist
[
ok
]))
cc
=
cc
.
reshape
(
lon_array
.
shape
)
ll
=
ll
.
reshape
(
lon_array
.
shape
)
f
=
open
(
'
/home/rink/elems.pkl
'
,
'
wb
'
)
pickle
.
dump
(
cc
,
f
)
f
.
close
()
f
=
open
(
'
/home/rink/lines.pkl
'
,
'
wb
'
)
pickle
.
dump
(
ll
,
f
)
f
.
close
()
ds
.
close
()
return
cc
,
ll
def
create_file
(
filename
,
fgf_elem
,
fgf_line
):
dim_x_len
=
fgf_elem
.
shape
[
1
]
dim_y_len
=
fgf_elem
.
shape
[
0
]
rootgrp
=
Dataset
(
filename
,
'
w
'
,
format
=
'
NETCDF4
'
)
dim_x
=
rootgrp
.
createDimension
(
'
romio_x
'
,
size
=
dim_x_len
)
dim_y
=
rootgrp
.
createDimension
(
'
romio_y
'
,
size
=
dim_y_len
)
romio_fgf_elems
=
rootgrp
.
createVariable
(
'
romio_fgf_elems
'
,
'
f4
'
,
[
'
romio_y
'
,
'
romio_x
'
])
romio_fgf_lines
=
rootgrp
.
createVariable
(
'
romio_fgf_lines
'
,
'
f4
'
,
[
'
romio_y
'
,
'
romio_x
'
])
romio_fgf_elems
[:,
:]
=
fgf_elem
[:,
:]
romio_fgf_lines
[:,
:]
=
fgf_line
[:,
:]
rootgrp
.
close
()
This diff is collapsed.
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modules/util/sss1day_FMB_py3.py
deleted
100644 → 0
+
0
−
308
View file @
8ae8c5a8
import
os
import
numpy
# Import CODA definitions
# Older dates
# os.putenv('CODA_DEFINITION', '/home/huiliu/CODA/share/coda/definitions/')
# os.putenv('CODA_DEFINITION', '/home/stevew/CODA/share/coda/definitions/')
os
.
putenv
(
'
CODA_DEFINITION
'
,
'
/data/Personal/stevew/AEOLUS/CODA/share/coda/definitions/
'
)
# Newer dates
#os.putenv('CODA_DEFINITION', '/home/huiliu/CODA/share/coda/definitions/AEOLUS-20190611.codadef')
from
numpy
import
vstack
,
zeros
,
linspace
,
where
,
logical_and
import
sys
# Tell python scripts where to find CODA (next import coda) --------
# sys.path.append('/home/huiliu/CODA/lib/python2.7/site-packages')
# sys.path.append('/home/stevew/CODA/lib/python2.7/site-packages')
sys
.
path
.
append
(
'
/data/Personal/stevew/AEOLUS/CODA/lib/python3.7/site-packages
'
)
import
coda
import
matplotlib.pyplot
as
plt
import
glob
,
ast
,
datetime
files
=
open
(
'
flist_adm.txt
'
).
read
().
split
()
print
(
files
)
nfile
=
len
(
files
)
allobs
=
0
wind_err_thresh
=
50
check_wind_err
=
True
f66
=
open
(
'
./ray1day.out
'
,
'
w+
'
)
f60
=
open
(
'
./mie1day.out
'
,
'
w+
'
)
# ------- loop over data files ------
for
n
,
filename
in
enumerate
(
files
):
print
(
'
Reading file: %s
'
%
filename
)
product
=
coda
.
open
(
filename
)
### ------- Mie wind profile ---------
### ------- Mie wind profile ---------
# print("Individual Mie HLOS wind points")
# latitude = coda.fetch(product, 'mie_geolocation',-1, 'windresult_geolocation/latitude_cog')
# longitude = coda.fetch(product, 'mie_geolocation',-1, 'windresult_geolocation/longitude_cog')
# mie_alt in (m)
mie_alt0
=
coda
.
fetch
(
product
,
'
mie_geolocation
'
,
-
1
,
'
windresult_geolocation/altitude_vcog
'
)
mie_altt
=
coda
.
fetch
(
product
,
'
mie_geolocation
'
,
-
1
,
'
windresult_geolocation/altitude_top
'
)
mie_altb
=
coda
.
fetch
(
product
,
'
mie_geolocation
'
,
-
1
,
'
windresult_geolocation/altitude_bottom
'
)
mie_azimuth0
=
coda
.
fetch
(
product
,
'
mie_geolocation
'
,
-
1
,
'
windresult_geolocation/los_azimuth
'
)
mie_length0
=
coda
.
fetch
(
product
,
'
mie_hloswind
'
,
-
1
,
'
windresult/integration_length
'
)
mie_valid0
=
coda
.
fetch
(
product
,
'
mie_hloswind
'
,
-
1
,
'
windresult/validity_flag
'
)
mie_wind0
=
coda
.
fetch
(
product
,
'
mie_hloswind
'
,
-
1
,
'
windresult/mie_wind_velocity
'
)
# new field for Mie scattering ratio
# sr0 = coda.fetch(product, 'mie_wind_prod_conf_data', -1, 'mie_wind_qc', 'fitting_mie_sr')
#klukens
# mie_pppp0 = coda.fetch(product, 'mie_hloswind',-1, 'windresult/reference_pressure')
# mie_pppp0 = coda.get_field_names(product,'mie_geolocation[0]/windresult_geolocation')
# mie_pppp0 = coda.get_field_names(product,'mie_hloswind[0]/windresult')
# print "mie_pppp0 fetch all = ",mie_pppp0
mie_err0
=
coda
.
fetch
(
product
,
'
mie_wind_prod_conf_data
'
,
-
1
,
'
mie_wind_qc/hlos_error_estimate
'
)
# mie_snr0 = coda.fetch(product, 'mie_wind_prod_conf_data',-1, 'mie_wind_qc/mie_snr')
# ------- Rayleigh profiles ---------
# ------- Rayleigh profiles ---------
# print("Individual Rayleight HLOS wind points")
rayleigh_azimuth0
=
coda
.
fetch
(
product
,
'
rayleigh_geolocation
'
,
-
1
,
'
windresult_geolocation/los_azimuth
'
)
# latitude = coda.fetch(product, 'rayleigh_geolocation',-1, 'windresult_geolocation/latitude_cog')
# longitude = coda.fetch(product, 'rayleigh_geolocation',-1, 'windresult_geolocation/longitude_cog')
rayleigh_alt0
=
coda
.
fetch
(
product
,
'
rayleigh_geolocation
'
,
-
1
,
'
windresult_geolocation/altitude_vcog
'
)
rayleigh_altt
=
coda
.
fetch
(
product
,
'
rayleigh_geolocation
'
,
-
1
,
'
windresult_geolocation/altitude_top
'
)
rayleigh_altb
=
coda
.
fetch
(
product
,
'
rayleigh_geolocation
'
,
-
1
,
'
windresult_geolocation/altitude_bottom
'
)
rayleigh_wind0
=
coda
.
fetch
(
product
,
'
rayleigh_hloswind
'
,
-
1
,
'
windresult/rayleigh_wind_velocity
'
)
# ----- rayleigh data is from top (26.5km) --> bottom (24 levels) ---------
# wind_err in (m/s)
rayleigh_err0
=
coda
.
fetch
(
product
,
'
rayleigh_wind_prod_conf_data
'
,
-
1
,
'
rayleigh_wind_qc/hlos_error_estimate
'
)
rayleigh_sratio0
=
coda
.
fetch
(
product
,
'
rayleigh_wind_prod_conf_data
'
,
-
1
,
'
rayleigh_wind_qc/scattering_ratio
'
)
rayleigh_wind_to_T
=
coda
.
fetch
(
product
,
'
rayleigh_hloswind
'
,
-
1
,
'
windresult/rayleigh_wind_to_temperature
'
)
rayleigh_wind_to_P
=
coda
.
fetch
(
product
,
'
rayleigh_hloswind
'
,
-
1
,
'
windresult/rayleigh_wind_to_pressure
'
)
rayleigh_temp
=
coda
.
fetch
(
product
,
'
rayleigh_hloswind
'
,
-
1
,
'
windresult/reference_temperature
'
)
rayleigh_pppp
=
coda
.
fetch
(
product
,
'
rayleigh_hloswind
'
,
-
1
,
'
windresult/reference_pressure
'
)
ray_length0
=
coda
.
fetch
(
product
,
'
rayleigh_hloswind
'
,
-
1
,
'
windresult/integration_length
'
)
rayleigh_valid0
=
coda
.
fetch
(
product
,
'
rayleigh_hloswind
'
,
-
1
,
'
windresult/validity_flag
'
)
# print(rayleigh_wind0.shape)
#=================================================
## ---------- Mie profile information ------------
#=================================================
print
(
"
Mie HLOS wind profiles
"
)
rid
=
coda
.
fetch
(
product
,
'
mie_profile
'
,
-
1
,
'
l2b_wind_profiles/wind_result_id_number
'
)
rid
=
vstack
(
rid
)
# print(rid.shape)
typ_id
=
coda
.
fetch
(
product
,
'
mie_profile
'
,
-
1
,
'
l2b_wind_profiles/Obs_Type
'
)
nprofm
=
rid
.
shape
[
0
]
nlevm
=
rid
.
shape
[
1
]
# ----------------- the data is from top --> bottom -------------
# NOTE: i = 0 - nprof-1 in the xrange FUNTION of PYTHON
#-----------------------------------------------------------------
mie_azimuth
=
zeros
(
rid
.
shape
)
mie_err
=
zeros
(
rid
.
shape
)
mie_hhh
=
zeros
(
rid
.
shape
)
mie_hht
=
zeros
(
rid
.
shape
)
mie_hhb
=
zeros
(
rid
.
shape
)
mie_wind
=
zeros
(
rid
.
shape
)
# mie_pppp = zeros(rid.shape) #klukens
mie_valid
=
zeros
(
rid
.
shape
)
mie_length
=
zeros
(
rid
.
shape
)
mie_sratio
=
zeros
(
rid
.
shape
)
# mie_snr = zeros(rid.shape)
# wind m/s,
mie_wind
[
rid
!=
0
]
=
mie_wind0
[
rid
[
rid
!=
0
]
-
1
]
*
0.01
mie_azimuth
[
rid
!=
0
]
=
mie_azimuth0
[
rid
[
rid
!=
0
]
-
1
]
*
1.0
mie_valid
[
rid
!=
0
]
=
mie_valid0
[
rid
[
rid
!=
0
]
-
1
]
# length in km output
mie_length
[
rid
!=
0
]
=
mie_length0
[
rid
[
rid
!=
0
]
-
1
]
*
0.001
# mie_pppp[rid !=0] = mie_pppp0[rid[rid !=0]-1]*0.01 #klukens
# wind error m/s
mie_err
[
rid
!=
0
]
=
mie_err0
[
rid
[
rid
!=
0
]
-
1
]
*
1.0
# mie_snr [rid !=0] = mie_snr0 [rid[rid !=0]-1]*1.0
# height in (km)
# add 250m shift to the height for this version of L2B data
mie_hhh
[
rid
!=
0
]
=
mie_alt0
[
rid
[
rid
!=
0
]
-
1
]
*
0.001
+
0.25
mie_hht
[
rid
!=
0
]
=
mie_altt
[
rid
[
rid
!=
0
]
-
1
]
*
0.001
+
0.25
mie_hhb
[
rid
!=
0
]
=
mie_altb
[
rid
[
rid
!=
0
]
-
1
]
*
0.001
+
0.25
latrid
=
coda
.
fetch
(
product
,
'
mie_profile
'
,
-
1
,
'
Profile_lat_average
'
)
lonrid
=
coda
.
fetch
(
product
,
'
mie_profile
'
,
-
1
,
'
Profile_lon_average
'
)
sstime
=
coda
.
fetch
(
product
,
'
mie_profile
'
,
-
1
,
'
Profile_DateTime_Average
'
)
for
i
in
range
(
nprofm
):
timestep
=
datetime
.
datetime
(
2000
,
1
,
1
)
+
datetime
.
timedelta
(
seconds
=
sstime
[
i
])
yyyy
=
timestep
.
strftime
(
'
%Y
'
)
mm
=
timestep
.
strftime
(
'
%m
'
)
dd
=
timestep
.
strftime
(
'
%d
'
)
hh
=
timestep
.
strftime
(
'
%H
'
)
min
=
timestep
.
strftime
(
'
%M
'
)
sec
=
timestep
.
strftime
(
'
%S
'
)
# klukens
if
check_wind_err
:
totlevs
=
numpy
.
sum
(
logical_and
(
mie_valid
[
i
,
:]
>
0
,
logical_and
(
rid
[
i
,
:]
>
0
,
mie_err
[
i
,
:]
<
wind_err_thresh
)))
else
:
totlevs
=
numpy
.
sum
(
logical_and
(
mie_valid
[
i
,
:]
>
0
,
rid
[
i
,
:]
>
0
))
if
totlevs
>
0
:
if
typ_id
[
i
]
==
1
:
# cloudy type Mie winds
print
(
yyyy
,
mm
,
dd
,
hh
,
min
,
sec
,
'
%7.2f %7.2f %2i
'
%
(
float
(
lonrid
[
i
]),
float
(
latrid
[
i
]),
int
(
totlevs
)),
file
=
f60
)
if
check_wind_err
:
for
m
in
range
(
nlevm
):
# keep consistent with the lines of totlevs above !!!
if
rid
[
i
,
m
]
>
0
:
if
mie_err
[
i
,
m
]
<
wind_err_thresh
:
if
mie_valid
[
i
,
m
]
>
0.0
:
print
(
'
%2i %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f
'
%
(
int
(
m
+
1
),
mie_hhh
[
i
,
m
],
mie_hht
[
i
,
m
],
mie_hhb
[
i
,
m
],
mie_err
[
i
,
m
],
mie_azimuth
[
i
,
m
],
mie_wind
[
i
,
m
],
mie_length
[
i
,
m
]),
file
=
f60
)
else
:
for
m
in
range
(
nlevm
):
if
rid
[
i
,
m
]
>
0
:
if
mie_valid
[
i
,
m
]
>
0.0
:
print
(
'
%2i %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f
'
%
(
int
(
m
+
1
),
mie_hhh
[
i
,
m
],
mie_hht
[
i
,
m
],
mie_hhb
[
i
,
m
],
mie_err
[
i
,
m
],
mie_azimuth
[
i
,
m
],
mie_wind
[
i
,
m
],
mie_length
[
i
,
m
]),
file
=
f60
)
# -----------------------------------------------
# Rayleigh profile information
# -----------------------------------------------
print
(
"
Rayleigh HLOS wind profiles
"
)
rid
=
coda
.
fetch
(
product
,
'
rayleigh_profile
'
,
-
1
,
'
l2b_wind_profiles/wind_result_id_number
'
)
rid
=
vstack
(
rid
)
#==========================================
# tpye =1, cloudy, =2 clear
#==========================================
typ_id
=
coda
.
fetch
(
product
,
'
rayleigh_profile
'
,
-
1
,
'
l2b_wind_profiles/Obs_Type
'
)
# profile number of Rayleigh winds profiles in this orbit
nprof
=
rid
.
shape
[
0
]
nlev
=
rid
.
shape
[
1
]
# print(rid.shape)
# ----------------- the data is from top --> bottom -------------
# NOTE: i = 0 - nprof-1 in the xrange FUNTION of PYTHON
#-----------------------------------------------------------------
ray_azimuth
=
zeros
(
rid
.
shape
)
ray_err
=
zeros
(
rid
.
shape
)
wind_sens_T
=
zeros
(
rid
.
shape
)
wind_sens_P
=
zeros
(
rid
.
shape
)
ray_length
=
zeros
(
rid
.
shape
)
ray_valid
=
zeros
(
rid
.
shape
)
ref_temp
=
zeros
(
rid
.
shape
)
ref_pppp
=
zeros
(
rid
.
shape
)
ray_hhh
=
zeros
(
rid
.
shape
)
ray_hht
=
zeros
(
rid
.
shape
)
ray_hhb
=
zeros
(
rid
.
shape
)
ray_wind
=
zeros
(
rid
.
shape
)
ray_sratio
=
zeros
(
rid
.
shape
)
ray_wind
[
rid
!=
0
]
=
rayleigh_wind0
[
rid
[
rid
!=
0
]
-
1
]
*
0.01
ray_azimuth
[
rid
!=
0
]
=
rayleigh_azimuth0
[
rid
[
rid
!=
0
]
-
1
]
*
1.0
ray_sratio
[
rid
!=
0
]
=
rayleigh_sratio0
[
rid
[
rid
!=
0
]
-
1
]
*
1.0
# print(rayleigh_wind0.shape)
# print(rid.shape)
# print(rid)
# from 2D OBS fortran index rid (1-nnn), to index 0-(nnn-1) of 1D mie_wind0
#
# wind error m/s
ray_err
[
rid
!=
0
]
=
rayleigh_err0
[
rid
[
rid
!=
0
]
-
1
]
*
1.0
# m/s/K
wind_sens_T
[
rid
!=
0
]
=
rayleigh_wind_to_T
[
rid
[
rid
!=
0
]
-
1
]
*
0.01
# K
ref_temp
[
rid
!=
0
]
=
rayleigh_temp
[
rid
[
rid
!=
0
]
-
1
]
ref_pppp
[
rid
!=
0
]
=
rayleigh_pppp
[
rid
[
rid
!=
0
]
-
1
]
*
0.01
# cm/s/hPa
wind_sens_P
[
rid
!=
0
]
=
rayleigh_wind_to_P
[
rid
[
rid
!=
0
]
-
1
]
*
1.0e-4
ray_length
[
rid
!=
0
]
=
ray_length0
[
rid
[
rid
!=
0
]
-
1
]
*
0.001
ray_valid
[
rid
!=
0
]
=
rayleigh_valid0
[
rid
[
rid
!=
0
]
-
1
]
# height in (km)
# add 250m shift to the height for this version of L2B data
ray_hhh
[
rid
!=
0
]
=
rayleigh_alt0
[
rid
[
rid
!=
0
]
-
1
]
*
0.001
+
0.25
ray_hht
[
rid
!=
0
]
=
rayleigh_altt
[
rid
[
rid
!=
0
]
-
1
]
*
0.001
+
0.25
ray_hhb
[
rid
!=
0
]
=
rayleigh_altb
[
rid
[
rid
!=
0
]
-
1
]
*
0.001
+
0.25
latrid
=
coda
.
fetch
(
product
,
'
rayleigh_profile
'
,
-
1
,
'
Profile_lat_average
'
)
lonrid
=
coda
.
fetch
(
product
,
'
rayleigh_profile
'
,
-
1
,
'
Profile_lon_average
'
)
sstime
=
coda
.
fetch
(
product
,
'
rayleigh_profile
'
,
-
1
,
'
Profile_DateTime_Average
'
)
for
i
in
range
(
nprof
):
timestep
=
datetime
.
datetime
(
2000
,
1
,
1
)
+
datetime
.
timedelta
(
seconds
=
sstime
[
i
])
yyyy
=
timestep
.
strftime
(
'
%Y
'
)
mm
=
timestep
.
strftime
(
'
%m
'
)
dd
=
timestep
.
strftime
(
'
%d
'
)
hh
=
timestep
.
strftime
(
'
%H
'
)
min
=
timestep
.
strftime
(
'
%M
'
)
sec
=
timestep
.
strftime
(
'
%S
'
)
#klukens
if
check_wind_err
:
totlevs
=
numpy
.
sum
(
logical_and
(
ray_valid
[
i
,
:]
>
0
,
logical_and
(
rid
[
i
,
:]
>
0
,
ray_err
[
i
,
:]
<
wind_err_thresh
)))
else
:
totlevs
=
numpy
.
sum
(
logical_and
(
ray_valid
[
i
,
:]
>
0
,
rid
[
i
,
:]
>
0
))
# for clear sky Rayleigh winds ----------
if
totlevs
>
0
:
if
typ_id
[
i
]
==
2
:
print
(
yyyy
,
mm
,
dd
,
hh
,
min
,
sec
,
'
%7.2f %7.2f %2i
'
%
(
float
(
lonrid
[
i
]),
float
(
latrid
[
i
]),
int
(
totlevs
)),
file
=
f66
)
if
check_wind_err
:
for
m
in
range
(
nlev
):
# keep consistent with the lines of totlevs above !!!
if
rid
[
i
,
m
]
>
0
:
if
ray_err
[
i
,
m
]
<
wind_err_thresh
:
if
ray_valid
[
i
,
m
]
>
0.0
:
print
(
'
%2i %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f
'
%
(
int
(
m
+
1
),
ray_hhh
[
i
,
m
],
ray_hht
[
i
,
m
],
ray_hhb
[
i
,
m
],
ray_err
[
i
,
m
],
ray_azimuth
[
i
,
m
],
ray_wind
[
i
,
m
],
ref_temp
[
i
,
m
]
*
0.01
,
ref_pppp
[
i
,
m
],
wind_sens_T
[
i
,
m
],
wind_sens_P
[
i
,
m
],
ray_sratio
[
i
,
m
],
ray_length
[
i
,
m
]),
file
=
f66
)
else
:
for
m
in
range
(
nlev
):
if
rid
[
i
,
m
]
>
0
:
if
ray_valid
[
i
,
m
]
>
0.0
:
print
(
'
%2i %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f %7.2f
'
%
(
int
(
m
+
1
),
ray_hhh
[
i
,
m
],
ray_hht
[
i
,
m
],
ray_hhb
[
i
,
m
],
ray_err
[
i
,
m
],
ray_azimuth
[
i
,
m
],
ray_wind
[
i
,
m
],
ref_temp
[
i
,
m
]
*
0.01
,
ref_pppp
[
i
,
m
],
wind_sens_T
[
i
,
m
],
wind_sens_P
[
i
,
m
],
ray_sratio
[
i
,
m
],
ray_length
[
i
,
m
]),
file
=
f66
)
coda
.
close
(
product
)
print
(
'
Finished data. Processed, file loop
'
)
exit
()
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