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EnMAP
sensormapgeo
Commits
7110af86
Commit
7110af86
authored
Aug 07, 2020
by
Daniel Scheffler
Browse files
First part of the solution.
Signed-off-by:
Daniel Scheffler
<
danschef@gfz-potsdam.de
>
parent
effe1819
Pipeline
#11259
passed with stage
in 1 minute and 43 seconds
Changes
1
Pipelines
1
Hide whitespace changes
Inline
Side-by-side
sensormapgeo/transformer_3d.py
View file @
7110af86
...
...
@@ -96,19 +96,19 @@ class SensorMapGeometryTransformer3D(object):
# bands: multiprocessing uses multiprocessing.Pool, implemented in to_map_geometry / to_sensor_geometry
# tiles: multiprocessing uses OpenMP implemented in pykdtree which is used by pyresample
self
.
opts
[
'nprocs'
]
=
opts
.
get
(
'nprocs'
,
multiprocessing
.
cpu_count
())
if
self
.
opts
[
'nprocs'
]
>
multiprocessing
.
cpu_count
():
self
.
opts
[
'nprocs'
]
=
multiprocessing
.
cpu_count
()
self
.
mp_alg
=
(
'bands'
if
self
.
lons
.
shape
[
2
]
>=
opts
[
'nprocs'
]
else
'tiles'
)
if
mp_alg
==
'auto'
else
mp_alg
@
staticmethod
def
_to_map_geometry_2D
(
kwargs_dict
:
dict
)
->
Tuple
[
np
.
ndarray
,
tuple
,
str
,
int
]:
assert
[
var
is
not
None
for
var
in
(
_global_shared_lons
,
_global_shared_lats
,
_global_shared_data
)]
SMGT2D
=
SensorMapGeometryTransformer
(
lons
=
_global_shared_lons
[:,
:,
kwargs_dict
[
'band_idx'
]],
lats
=
_global_shared_lats
[:,
:,
kwargs_dict
[
'band_idx'
]],
SMGT2D
=
SensorMapGeometryTransformer
(
lons
=
kwargs_dict
[
'lons'
],
lats
=
kwargs_dict
[
'lats'
],
resamp_alg
=
kwargs_dict
[
'resamp_alg'
],
radius_of_influence
=
kwargs_dict
[
'radius_of_influence'
],
**
kwargs_dict
[
'init_opts'
])
data_mapgeo
,
out_gt
,
out_prj
=
SMGT2D
.
to_map_geometry
(
data
=
_global_shared_data
[:,
:,
kwargs_dict
[
'
band_idx'
]
],
data_mapgeo
,
out_gt
,
out_prj
=
SMGT2D
.
to_map_geometry
(
data
=
kwargs_dict
[
'
data'
],
area_definition
=
kwargs_dict
[
'area_definition'
])
return
data_mapgeo
,
out_gt
,
out_prj
,
kwargs_dict
[
'band_idx'
]
...
...
@@ -214,16 +214,30 @@ class SensorMapGeometryTransformer3D(object):
radius_of_influence
=
self
.
radius_of_influence
,
init_opts
=
init_opts
,
area_definition
=
area_definition
,
band_idx
=
band
band_idx
=
band
,
lons
=
self
.
lons
[:,
:,
band
],
lats
=
self
.
lats
[:,
:,
band
],
data
=
data
[:,
:,
band
],
)
for
band
in
range
(
data
.
shape
[
2
])]
if
self
.
opts
[
'nprocs'
]
>
1
and
self
.
mp_alg
==
'bands'
:
with
multiprocessing
.
Pool
(
self
.
opts
[
'nprocs'
],
initializer
=
_initializer
,
initargs
=
(
self
.
lats
,
self
.
lons
,
data
))
as
pool
:
result
=
pool
.
map
(
self
.
_to_map_geometry_2D
,
args
)
from
time
import
time
t0
=
time
()
# data_mapgeo_v2 = np.empty((area_definition.height,
# area_definition.width,
# data.shape[2]),
# dtype=data.dtype)
with
multiprocessing
.
Pool
(
self
.
opts
[
'nprocs'
])
as
pool
:
result
=
[
res
for
res
in
pool
.
imap_unordered
(
self
.
_to_map_geometry_2D
,
args
)]
# for res in pool.imap_unordered(self._to_map_geometry_2D, args):
# data_mapgeo_v2[:, :, res[-1]] = res[0]
print
(
time
()
-
t0
)
else
:
_initializer
(
self
.
lats
,
self
.
lons
,
data
)
result
=
[
self
.
_to_map_geometry_2D
(
argsdict
)
for
argsdict
in
args
]
band_inds
=
[
res
[
-
1
]
for
res
in
result
]
...
...
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