L1C_P.py 41 KB
Newer Older
Daniel Scheffler's avatar
Daniel Scheffler committed
1
# -*- coding: utf-8 -*-
Daniel Scheffler's avatar
Daniel Scheffler committed
2
"""Level 1C Processor:   Atmospheric correction of TOA-reflectance data."""
Daniel Scheffler's avatar
Daniel Scheffler committed
3

4
import warnings
5
6
import re
import logging
7
import dill
8
import traceback
9
from typing import List, TypeVar
10

11
import numpy as np
Daniel Scheffler's avatar
Daniel Scheffler committed
12

13
from geoarray import GeoArray
14
from py_tools_ds.geo.map_info import mapinfo2geotransform
15

Daniel Scheffler's avatar
Daniel Scheffler committed
16
17
18
from ..config import GMS_config as CFG
from . import GEOPROCESSING as GEOP
from .L1B_P import L1B_object
19
from ..model.METADATA import get_LayerBandsAssignment
20
from ..misc.definition_dicts import get_outFillZeroSaturated, proc_chain, get_mask_classdefinition
21
from ..io.Input_reader import SRF
22
# from .cloud_masking import Cloud_Mask_Creator  # circular dependencies
23

24
from sicor.sicor_ac import ac_gms
25
from sicor.sensors import RSImage
26
from sicor.Mask import S2Mask
27

Daniel Scheffler's avatar
Daniel Scheffler committed
28
29
__author__ = 'Daniel Scheffler'

Daniel Scheffler's avatar
Daniel Scheffler committed
30

31
class L1C_object(L1B_object):
32
    def __init__(self, L1B_obj=None):
33
        super(L1C_object, self).__init__()
34
35
36

        if L1B_obj:
            # populate attributes
Daniel Scheffler's avatar
Daniel Scheffler committed
37
            [setattr(self, key, value) for key, value in L1B_obj.__dict__.items()]
38

39
40
41
42
43
44
45
46
        # private attributes
        self._VZA_arr = None
        self._VAA_arr = None
        self._SZA_arr = None
        self._SAA_arr = None
        self._RAA_arr = None
        self._lonlat_arr = None

47
        self.proc_level = 'L1C'
48

49
50
51
    @property
    def lonlat_arr(self):
        """Calculates pixelwise 2D-array with longitude and latitude coordinates.
52

53
54
55
56
57
58
59
60
        :return:
        """
        if self._lonlat_arr is None:
            self.logger.info('Calculating LonLat array...')
            self._lonlat_arr = \
                GEOP.get_lonlat_coord_array(self.shape_fullArr, self.arr_pos,
                                            mapinfo2geotransform(self.meta_odict['map info']),
                                            self.meta_odict['coordinate system string'],
Daniel Scheffler's avatar
Daniel Scheffler committed
61
62
                                            meshwidth=10,  # for faster processing
                                            nodata_mask=None,  # dont overwrite areas outside the image with nodata
63
64
                                            outFill=get_outFillZeroSaturated(np.float32)[0])[0]
        return self._lonlat_arr
65

66
67
68
    @lonlat_arr.setter
    def lonlat_arr(self, lonlat_arr):
        self._lonlat_arr = lonlat_arr
69

70
71
72
73
74
75
76
77
78
79
80
81
    @property
    def VZA_arr(self):
        """Get viewing zenith angle.

        :return:
        """
        if self._VZA_arr is None:
            self.logger.info('Calculating viewing zenith array...')
            if 'ViewingAngle_arrProv' in self.meta_odict and self.meta_odict['ViewingAngle_arrProv']:
                # Sentinel-2
                self._VZA_arr = GEOP.adjust_acquisArrProv_to_shapeFullArr(self.meta_odict['ViewingAngle_arrProv'],
                                                                          self.shape_fullArr,
Daniel Scheffler's avatar
Daniel Scheffler committed
82
                                                                          meshwidth=10,  # for faster processing
83
84
85
86
                                                                          subset=None,
                                                                          bandwise=0)
            else:
                self._VZA_arr = GEOP.calc_VZA_array(self.shape_fullArr, self.arr_pos, self.fullSceneCornerPos,
87
88
89
                                                    float(self.meta_odict['ViewingAngle']),
                                                    float(self.meta_odict['FieldOfView']),
                                                    self.logger,
Daniel Scheffler's avatar
Daniel Scheffler committed
90
                                                    nodata_mask=None,  # dont overwrite areas outside image with nodata
91
                                                    outFill=get_outFillZeroSaturated(np.float32)[0],
Daniel Scheffler's avatar
Daniel Scheffler committed
92
                                                    meshwidth=10)  # for faster processing
93
94
95
96
97
        return self._VZA_arr

    @VZA_arr.setter
    def VZA_arr(self, VZA_arr):
        self._VZA_arr = VZA_arr
98

99
100
101
    @property
    def VAA_arr(self):
        """Get viewing azimuth angle.
102

103
104
105
106
107
108
109
110
        :return:
        """
        if self._VAA_arr is None:
            self.logger.info('Calculating viewing azimuth array...')
            if 'IncidenceAngle_arrProv' in self.meta_odict and self.meta_odict['IncidenceAngle_arrProv']:
                # Sentinel-2
                self._VAA_arr = GEOP.adjust_acquisArrProv_to_shapeFullArr(self.meta_odict['IncidenceAngle_arrProv'],
                                                                          self.shape_fullArr,
Daniel Scheffler's avatar
Daniel Scheffler committed
111
                                                                          meshwidth=10,  # for faster processing
112
113
114
115
116
                                                                          subset=None,
                                                                          bandwise=0)
            else:
                # only a mean VAA is available
                if self.VAA_mean is None:
117
118
                    self.VAA_mean = \
                        GEOP.calc_VAA_using_fullSceneCornerLonLat(self.fullSceneCornerLonLat, self.MetaObj.orbitParams)
119
120
                    assert isinstance(self.VAA_mean, float)

121
                self._VAA_arr = np.full(self.VZA_arr.shape, self.VAA_mean, np.float32)
122
123
124
125
126
        return self._VAA_arr

    @VAA_arr.setter
    def VAA_arr(self, VAA_arr):
        self._VAA_arr = VAA_arr
127

128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
    @property
    def SZA_arr(self):
        """Get solar zenith angle.

        :return:
        """
        if self._SZA_arr is None:
            self.logger.info('Calculating solar zenith and azimuth arrays...')
            self._SZA_arr, self._SAA_arr = \
                GEOP.calc_SZA_SAA_array(
                    self.shape_fullArr, self.arr_pos,
                    self.meta_odict['AcqDate'],
                    self.meta_odict['AcqTime'],
                    self.fullSceneCornerPos,
                    self.fullSceneCornerLonLat,
                    self.meta_odict['overpass duraction sec'],
                    self.logger,
                    meshwidth=10,
                    nodata_mask=None,  # dont overwrite areas outside the image with nodata
                    outFill=get_outFillZeroSaturated(np.float32)[0],
                    accurracy=CFG.job.SZA_SAA_calculation_accurracy,
                    lonlat_arr=self.lonlat_arr if CFG.job.SZA_SAA_calculation_accurracy == 'fine' else None)
        return self._SZA_arr

    @SZA_arr.setter
    def SZA_arr(self, SZA_arr):
        self._SZA_arr = SZA_arr

    @property
    def SAA_arr(self):
        """Get solar azimuth angle.

        :return:
        """
        if self._SAA_arr is None:
163
164
            # noinspection PyStatementEffect
            self.SZA_arr  # getter also sets self._SAA_arr
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
        return self._SAA_arr

    @SAA_arr.setter
    def SAA_arr(self, SAA_arr):
        self._SAA_arr = SAA_arr

    @property
    def RAA_arr(self):
        """Get relative azimuth angle.

        :return:
        """
        if self._RAA_arr is None:
            self.logger.info('Calculating relative azimuth array...')
            self._RAA_arr = GEOP.calc_RAA_array(self.SAA_arr, self.VAA_mean,
                                                nodata_mask=None, outFill=get_outFillZeroSaturated(np.float32)[0])
        return self._RAA_arr

    @RAA_arr.setter
    def RAA_arr(self, RAA_arr):
        self._RAA_arr = RAA_arr
186

187
    def delete_ac_input_arrays(self):
Daniel Scheffler's avatar
Daniel Scheffler committed
188
189
190
191
192
        self.VZA_arr = None  # not needed anymore
        self.SZA_arr = None  # not needed anymore
        self.SAA_arr = None  # not needed anymore
        self.RAA_arr = None  # not needed anymore
        self.lonlat_arr = None  # not needed anymore
Daniel Scheffler's avatar
Daniel Scheffler committed
193
194
195
196
197

        # use self.dem deleter
        # would have to be resampled when writing MGRS tiles
        # -> better to directly warp it to the output dims and projection
        del self.dem
198
199


200
201
202
_T_list_L1Cobjs = TypeVar(List[L1C_object])


203
class AtmCorr(object):
204
    def __init__(self, *L1C_objs, reporting=False):
205
        """Wrapper around atmospheric correction by Andre Hollstein, GFZ Potsdam
206
207
208
209
210
211

        Creates the input arguments for atmospheric correction from one or multiple L1C_object instance(s) belonging to
        the same scene ID, performs the atmospheric correction and returns the atmospherically corrected L1C object(s).

        :param L1C_objs: one or more instances of L1C_object belonging to the same scene ID
        """
212
        # FIXME not yet usable for data < 2012 due to missing ECMWF archive
213
214
215
        L1C_objs = L1C_objs if isinstance(L1C_objs, tuple) else (L1C_objs,)

        # hidden attributes
Daniel Scheffler's avatar
Daniel Scheffler committed
216
217
218
        self._logger = None
        self._GSDs = []
        self._data = {}
219
        self._metadata = {}
Daniel Scheffler's avatar
Daniel Scheffler committed
220
        self._nodata = {}
221
        self._band_spatial_sampling = {}
Daniel Scheffler's avatar
Daniel Scheffler committed
222
        self._options = {}
223
224
225

        # assertions
        scene_IDs = [obj.scene_ID for obj in L1C_objs]
Daniel Scheffler's avatar
Daniel Scheffler committed
226
        assert len(list(set(scene_IDs))) == 1, \
Daniel Scheffler's avatar
Daniel Scheffler committed
227
            "Input GMS objects for 'AtmCorr' must all belong to the same scene ID!. Received %s." % scene_IDs
228

229
        self.inObjs = L1C_objs  # type: _T_list_L1Cobjs
230
        self.reporting = reporting
Daniel Scheffler's avatar
Daniel Scheffler committed
231
232
        self.ac_input = {}  # set by self.run_atmospheric_correction()
        self.results = None  # direct output of external atmCorr module (set by run_atmospheric_correction)
233
        self.proc_info = {}
Daniel Scheffler's avatar
Daniel Scheffler committed
234
        self.outObjs = []  # atmospherically corrected L1C objects
235
236

        # append AtmCorr object to input L1C objects
Daniel Scheffler's avatar
Daniel Scheffler committed
237
        # [setattr(L1C_obj, 'AtmCorr', self) for L1C_obj in self.inObjs] # too big for serialization
238

239
240
241
242
        if not re.search('Sentinel-2', self.inObjs[0].satellite, re.I):
            warnings.warn('Calculation of acquisition geometry arrays is currently only validated for Sentinel-2!')
            # validation possible by comparing S2 angles provided by ESA with own angles

243
244
245
246
247
    @property
    def logger(self):
        if self._logger and self._logger.handlers[:]:
            return self._logger
        else:
Daniel Scheffler's avatar
Daniel Scheffler committed
248
            if len(self.inObjs) == 1:
249
250
251
252
253
254
255
256
257
258
                # just use the logger of the inObj
                logger_atmCorr = self.inObjs[0].logger
            else:
                # in case of multiple GMS objects to be processed at once:
                # get the logger of the first inObj
                logger_atmCorr = self.inObjs[0].logger

                # add additional file handlers for the remaining inObj (that belong to the same scene_ID)
                for inObj in self.inObjs[1:]:
                    path_logfile = inObj.pathGen.get_path_logfile()
Daniel Scheffler's avatar
Daniel Scheffler committed
259
                    fileHandler = logging.FileHandler(path_logfile, mode='a')
260
261
262
263
264
                    fileHandler.setFormatter(logger_atmCorr.formatter_fileH)
                    fileHandler.setLevel(logging.DEBUG)

                    logger_atmCorr.addHandler(fileHandler)

Daniel Scheffler's avatar
Daniel Scheffler committed
265
266
                    inObj.close_GMS_loggers()

267
268
269
270
271
272
            self._logger = logger_atmCorr
            return self._logger

    @logger.setter
    def logger(self, logger):
        assert isinstance(logger, logging.Logger) or logger in ['not set', None], \
Daniel Scheffler's avatar
Daniel Scheffler committed
273
            "AtmCorr.logger can not be set to %s." % logger
274
275
276
277
278
279
280
281
        if logger in ['not set', None]:
            self._logger.close()
            self._logger = logger
        else:
            self._logger = logger

    @logger.deleter
    def logger(self):
282
283
284
        if self._logger not in [None, 'not set']:
            self._logger.close()
            self._logger = None
285

Daniel Scheffler's avatar
Daniel Scheffler committed
286
287
        [inObj.close_GMS_loggers() for inObj in self.inObjs]

288
289
290
291
292
293
294
295
    @property
    def GSDs(self):
        """
        Returns a list of spatial samplings within the input GMS objects, e.g. [10,20,60].
        """
        for obj in self.inObjs:
            if obj.arr.xgsd != obj.arr.ygsd:
                warnings.warn("X/Y GSD is not equal for entity ID %s" % obj.entity_ID +
Daniel Scheffler's avatar
Daniel Scheffler committed
296
                              (' (%s)' % obj.subsystem if obj.subsystem else '') +
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
                              'Using X-GSD as key for spatial sampling dictionary.')
                self._GSDs.append(obj.arr.xgsd)

        return self._GSDs

    @property
    def data(self):
        """

        :return:
            ___ attribute: data, type:<class 'dict'>
            ______ key:B05, value_type:<class 'numpy.ndarray'>, repr: [[nan nan nan ...,0. [..] 085998540.0803833 ]]
            ______ key:B01, value_type:<class 'numpy.ndarray'>, repr: [[nan nan nan ...,0. [..] 131225590.13208008]]
            ______ key:B06, value_type:<class 'numpy.ndarray'>, repr: [[nan nan nan ...,0. [..] .14965820.13977051]]
            ______ key:B11, value_type:<class 'numpy.ndarray'>, repr: [[nan nan nan ...,0. [..] .11492920.10192871]]
            ______ key:B02, value_type:<class 'numpy.ndarray'>, repr: [[nan nan nan ...,0. [..] 104187010.10308838]]
            ______ key:B10, value_type:<class 'numpy.ndarray'>, repr: [[nan nan nan ...,0. [..] 013099670.01300049]]
            ______ key:B08, value_type:<class 'numpy.ndarray'>, repr: [[nan nan nan ...,0. [..] .16857910.15783691]]
            ______ key:B04, value_type:<class 'numpy.ndarray'>, repr: [[nan nan nan ...,0. [..] 065490720.06228638]]
            ______ key:B03, value_type:<class 'numpy.ndarray'>, repr: [[nan nan nan ...,0. [..] 082702640.08148193]]
            ______ key:B12, value_type:<class 'numpy.ndarray'>, repr: [[nan nan nan ...,0. [..] 068420410.06060791]]
            ______ key:B8A, value_type:<class 'numpy.ndarray'>, repr: [[nan nan nan ...,0. [..] 192138670.17553711]]
            ______ key:B09, value_type:<class 'numpy.ndarray'>, repr: [[nan nan nan ...,0. [..] .09600830.09887695]]
            ______ key:B07, value_type:<class 'numpy.ndarray'>, repr: [[nan nan nan ...,0. [..] 173339840.15600586]]
        """
        if not self._data:
323
324
            data_dict = {}

325
            for inObj in self.inObjs:
326
                for bandN, bandIdx in inObj.arr.bandnames.items():
327
                    if bandN not in data_dict:
Daniel Scheffler's avatar
Daniel Scheffler committed
328
329
330
331
                        # float32! -> conversion to np.float16 will convert -9999 to -10000
                        arr2pass = inObj.arr[:, :, bandIdx].astype(np.float32)
                        arr2pass[arr2pass == inObj.arr.nodata] = np.nan  # set nodata values to np.nan
                        data_dict[bandN] = (arr2pass / inObj.meta_odict['ScaleFactor']).astype(np.float16)
332
                    else:
333
                        inObj.logger.warning("Band '%s' cannot be included into atmospheric correction because it "
Daniel Scheffler's avatar
Daniel Scheffler committed
334
                                             "exists multiple times." % bandN)
335

336
            # validate: data must have all bands needed for AC
Daniel Scheffler's avatar
Daniel Scheffler committed
337
338
            full_LBA = get_LayerBandsAssignment(self.inObjs[0].GMS_identifier, return_fullLBA=True)
            all_bNs_AC = ['B%s' % i if len(i) == 2 else 'B0%s' % i for i in full_LBA]
339
340
            if not all([bN in list(data_dict.keys()) for bN in all_bNs_AC]):
                raise RuntimeError('Atmospheric correction did not receive all the needed bands. \n\tExpected: %s;\n\t'
Daniel Scheffler's avatar
Daniel Scheffler committed
341
                                   'Received: %s' % (str(all_bNs_AC), str(list(sorted(data_dict.keys())))))
342
343
344

            self._data = data_dict

345
346
347
348
349
350
351
352
        return self._data

    @data.setter
    def data(self, data_dict):
        assert isinstance(data_dict, dict), \
            "'data' can only be set to a dictionary with band names as keys and numpy arrays as values."
        self._data = data_dict

353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
    @property
    def nodata(self):
        """

        :return:
            ___ attribute: nodata, type:<class 'dict'>
            ______ key:60.0, value_type:<class 'numpy.ndarray'>, repr: [[ TrueTrueTrue ..., [..]  False False False]]
            ______ key:10.0, value_type:<class 'numpy.ndarray'>, repr: [[ TrueTrueTrue ..., [..]  False False False]]
            ______ key:20.0, value_type:<class 'numpy.ndarray'>, repr: [[ TrueTrueTrue ..., [..]  False False False]]
        """

        if not self._nodata:
            for inObj in self.inObjs:
                self._nodata[inObj.arr.xgsd] = ~inObj.arr.mask_nodata[:]

        return self._nodata

    @property
    def tile_name(self):
372
        """Returns S2A tile name.
373
        NOTE: this is only needed if no DEM is passed to ac_gms
374
375
376
377
378

        :return: e.g.
            '32UMA'
        """

Daniel Scheffler's avatar
Daniel Scheffler committed
379
        return ''  # FIXME
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
406
407

    @property
    def band_spatial_sampling(self):
        """

        :return: e.g.
            {'B01': 60.0,
             'B02': 10.0,
             'B03': 10.0,
             'B04': 10.0,
             'B05': 20.0,
             'B06': 20.0,
             'B07': 20.0,
             'B08': 10.0,
             'B09': 60.0,
             'B10': 60.0,
             'B11': 20.0,
             'B12': 20.0,
             'B8A': 20.0}
        """

        if not self._band_spatial_sampling:
            for inObj in self.inObjs:
                for bandN in inObj.arr.bandnames:
                    if bandN not in self._band_spatial_sampling:
                        self._band_spatial_sampling[bandN] = inObj.arr.xgsd
        return self._band_spatial_sampling

408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
    @property
    def metadata(self):
        """

        :return:
            ___ attribute: metadata, type:<class 'dict'>
            ______ key:spatial_samplings
            _________ key:60.0
            ____________ key:ULY, value_type:<class 'int'>, repr: 4900020
            ____________ key:NCOLS, value_type:<class 'int'>, repr: 1830
            ____________ key:XDIM, value_type:<class 'int'>, repr: 60
            ____________ key:ULX, value_type:<class 'int'>, repr: 600000
            ____________ key:NROWS, value_type:<class 'int'>, repr: 1830
            ____________ key:YDIM, value_type:<class 'int'>, repr: -60
            _________ key:10.0
            ____________ key:ULY, value_type:<class 'int'>, repr: 4900020
            ____________ key:NCOLS, value_type:<class 'int'>, repr: 10980
            ____________ key:XDIM, value_type:<class 'int'>, repr: 10
            ____________ key:ULX, value_type:<class 'int'>, repr: 600000
            ____________ key:NROWS, value_type:<class 'int'>, repr: 10980
            ____________ key:YDIM, value_type:<class 'int'>, repr: -10
            _________ key:20.0
            ____________ key:ULY, value_type:<class 'int'>, repr: 4900020
            ____________ key:NCOLS, value_type:<class 'int'>, repr: 5490
            ____________ key:XDIM, value_type:<class 'int'>, repr: 20
            ____________ key:ULX, value_type:<class 'int'>, repr: 600000
            ____________ key:NROWS, value_type:<class 'int'>, repr: 5490
            ____________ key:YDIM, value_type:<class 'int'>, repr: -20
            ______ key:SENSING_TIME, value_type:<class 'datetime.datetime'>, repr: 2016-03-26 10:34:06.538000+00:00
        """
438
        # TODO add SRF object
Daniel Scheffler's avatar
Daniel Scheffler committed
439

440
        if not self._metadata:
Daniel Scheffler's avatar
Daniel Scheffler committed
441
            del self.logger  # otherwise each input object would have multiple fileHandlers
442

Daniel Scheffler's avatar
Daniel Scheffler committed
443
444
445
446
447
448
449
450
451
452
453
454
455
            metadata = dict(
                U=self.inObjs[0].meta_odict['EarthSunDist'],
                SENSING_TIME=self.inObjs[0].acq_datetime,
                # SENSING_TIME=datetime.strptime('2015-08-12 10:40:21 +0000', '%Y-%m-%d %H:%M:%S %z'),
                viewing_zenith=self._meta_get_viewing_zenith(),
                viewing_azimuth=self._meta_get_viewing_azimuth(),
                relative_viewing_azimuth=self._meta_get_relative_viewing_azimuth(),
                sun_mean_azimuth=self.inObjs[0].meta_odict['SunAzimuth'],
                sun_mean_zenith=90 - self.inObjs[0].meta_odict['SunElevation'],
                solar_irradiance=self._meta_get_solar_irradiance(),
                aux_data=self._meta_get_aux_data(),
                spatial_samplings=self._meta_get_spatial_samplings()
            )
456
457

            self._metadata = metadata
458
459
460

        return self._metadata

461
462
463
464
    @property
    def options(self):
        """Returns a dictionary containing AC options.
        """
Daniel Scheffler's avatar
Daniel Scheffler committed
465
        # type: -> dict
466
467
468
469
        if self._options:
            return self._options
        else:
            self._options = self.inObjs[0].ac_options
Daniel Scheffler's avatar
Daniel Scheffler committed
470
            self._options["AC"]['bands'] = [b for b in self.data.keys() if b in self._options["AC"]['bands']]
471
            self._options["report"]["reporting"] = self.reporting
472
473
            return self._options

474
    def _meta_get_spatial_samplings(self):
475
476
477
        """

        :return:
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
         {10.0: {'NCOLS': 10980,
           'NROWS': 10980,
           'ULX': 499980.0,
           'ULY': 5800020.0,
           'XDIM': 10.0,
           'YDIM': -10.0},
          20.0: {'NCOLS': 5490,
           'NROWS': 5490,
           'ULX': 499980.0,
           'ULY': 5800020.0,
           'XDIM': 20.0,
           'YDIM': -20.0},
          60.0: {'NCOLS': 1830,
           'NROWS': 1830,
           'ULX': 499980.0,
           'ULY': 5800020.0,
           'XDIM': 60.0,
           'YDIM': -60.0}}
496
        """
497
498
        # set corner coordinates and dims
        spatial_samplings = {}
499
500
501

        for inObj in self.inObjs:

502
503
504
505
506
            # validate GSD
            if inObj.arr.xgsd != inObj.arr.ygsd:
                warnings.warn("X/Y GSD is not equal for entity ID %s" % inObj.entity_ID +
                              (' (%s)' % inObj.subsystem if inObj.subsystem else '') +
                              'Using X-GSD as key for spatial sampling dictionary.')
507

508
509
            # set spatial information
            spatial_samplings[inObj.arr.xgsd] = dict(
Daniel Scheffler's avatar
Daniel Scheffler committed
510
511
512
513
514
515
                ULX=inObj.arr.box.boxMapYX[0][1],
                ULY=inObj.arr.box.boxMapYX[0][0],
                XDIM=inObj.arr.xgsd,
                YDIM=-inObj.arr.ygsd,
                NROWS=inObj.arr.rows,
                NCOLS=inObj.arr.cols)
516

517
518
519
        return spatial_samplings

    def _meta_get_solar_irradiance(self):
520
521
522
        """

        :return:
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
        {'B01': 1913.57,
         'B02': 1941.63,
         'B03': 1822.61,
         'B04': 1512.79,
         'B05': 1425.56,
         'B06': 1288.32,
         'B07': 1163.19,
         'B08': 1036.39,
         'B09': 813.04,
         'B10': 367.15,
         'B11': 245.59,
         'B12': 85.25,
         'B8A': 955.19}
        """

        solar_irradiance = {}

        for inObj in self.inObjs:
            for bandN, bandIdx in inObj.arr.bandnames.items():
                if bandN not in solar_irradiance:
                    solar_irradiance[bandN] = inObj.meta_odict['SolIrradiance'][bandIdx]
        return solar_irradiance

    def _meta_get_viewing_zenith(self):
        """

        :return: {B10:ndarray(dtype=float16),[...],B09:ndarray(dtype=float16)}
        """

        viewing_zenith = {}

Daniel Scheffler's avatar
Daniel Scheffler committed
554
        for inObj in self.inObjs:  # type: L1C_object
555
            for bandN, bandIdx in inObj.arr.bandnames.items():
556
                if bandN not in viewing_zenith:
557
558
                    arr2pass = inObj.VZA_arr[:, :, bandIdx] if inObj.VZA_arr.ndim == 3 else inObj.VZA_arr
                    viewing_zenith[bandN] = arr2pass.astype(np.float16)
Daniel Scheffler's avatar
Daniel Scheffler committed
559
                    # viewing_zenith[bandN] = inObj.VZA_arr[:, :, bandIdx] if inObj.VZA_arr.ndim==3 else inObj.VZA_arr
560
561
562
563
564
565
566
567
568
569
        return viewing_zenith

    def _meta_get_viewing_azimuth(self):
        """

        :return: {B10:ndarray(dtype=float16),[...],B09:ndarray(dtype=float16)}
        """

        viewing_azimuth = {}

Daniel Scheffler's avatar
Daniel Scheffler committed
570
        for inObj in self.inObjs:  # type: L1C_object
571
            for bandN, bandIdx in inObj.arr.bandnames.items():
572
                if bandN not in viewing_azimuth:
Daniel Scheffler's avatar
Daniel Scheffler committed
573
                    arr2pass = inObj.VAA_arr[:, :, bandIdx] if inObj.VAA_arr.ndim == 3 else inObj.VAA_arr
574
                    viewing_azimuth[bandN] = arr2pass.astype(np.float16)
Daniel Scheffler's avatar
Daniel Scheffler committed
575
                    # viewing_azimuth[bandN] = inObj.VAA_arr[:, :, bandIdx] if inObj.VAA_arr.ndim==3 else inObj.VAA_arr
576

577
578
579
580
581
582
        return viewing_azimuth

    def _meta_get_relative_viewing_azimuth(self):
        """

        :return: {B10:ndarray(dtype=float16),[...],B09:ndarray(dtype=float16)}
583
584
        """

585
586
        relative_viewing_azimuth = {}

Daniel Scheffler's avatar
Daniel Scheffler committed
587
        for inObj in self.inObjs:  # type: L1C_object
588
            for bandN, bandIdx in inObj.arr.bandnames.items():
589
                if bandN not in relative_viewing_azimuth:
590
591
                    arr2pass = inObj.RAA_arr[:, :, bandIdx] if inObj.RAA_arr.ndim == 3 else inObj.RAA_arr
                    relative_viewing_azimuth[bandN] = arr2pass.astype(np.float16)
Daniel Scheffler's avatar
Daniel Scheffler committed
592
593
                    # relative_viewing_azimuth[bandN] = \
                    #     inObj.RAA_arr[:, :, bandIdx] if inObj.RAA_arr.ndim==3 else inObj.RAA_arr
594

595
        return relative_viewing_azimuth
596

597
598
599
600
601
602
603
604
    def _meta_get_aux_data(self):
        """

        :return:  {lons:ndarray(dtype=float16),,lats:ndarray(dtype=float16)}
        """

        aux_data = dict(
            # set lons and lats (a 2D array for all bands is enough (different band resolutions dont matter))
Daniel Scheffler's avatar
Daniel Scheffler committed
605
606
            lons=self.inObjs[0].lonlat_arr[::10, ::10, 0].astype(np.float16),  # 2D array of lon values: 0° - 360°
            lats=self.inObjs[0].lonlat_arr[::10, ::10, 1].astype(np.float16)  # 2D array of lat values: -90° - 90°
607
            # FIXME correct to reduce resolution here by factor 10?
608
609
610
611
612
613
614
615
616
617
618
619
        )

        return aux_data

    def _get_dem(self):
        """Get a DEM to be used in atmospheric correction.

        :return: <np.ndarray> 2D array (with 20m resolution in case of Sentinel-2)
        """
        # determine which input GMS object is used to generate DEM
        if re.search('Sentinel-2', self.inObjs[0].satellite):
            # in case of Sentinel-2 the 20m DEM must be passed
Daniel Scheffler's avatar
Daniel Scheffler committed
620
            inObj4dem = [obj for obj in self.inObjs if obj.arr.xgsd == 20]
621
622
623
            if not inObj4dem:
                self.logger.warning('Sentinel-2 20m subsystem could not be found. DEM passed to '
                                    'atmospheric correction might have wrong resolution.')
624
625
626
627
            inObj4dem = inObj4dem[0]
        else:
            inObj4dem = self.inObjs[0]

628
629
630
631
        try:
            dem = inObj4dem.dem[:].astype(np.float32)
        except Exception as e:
            dem = None
Daniel Scheffler's avatar
Daniel Scheffler committed
632
            self.logger.warning('A static elevation is assumed during atmospheric correction due to an error during '
633
634
635
                                'creation of the DEM corresponding to scene %s (entity ID: %s). Error message was: '
                                '\n%s\n' % (self.inObjs[0].scene_ID, self.inObjs[0].entity_ID, repr(e)))
            self.logger.info("Print traceback in case you care:")
636
            self.logger.warning(traceback.format_exc())
637
638

        return dem
639
640

    def _get_srf(self):
641
        """Returns an instance of SRF in the same structure like sicor.sensors.SRF.SensorSRF
642
        """
643
644
645
        # FIXME calculation of center wavelengths within SRF() used not the GMS algorithm
        # SRF instance must be created for all bands and the previous proc level
        GMS_identifier_fullScene = self.inObjs[0].GMS_identifier
Daniel Scheffler's avatar
Daniel Scheffler committed
646
        GMS_identifier_fullScene['Subsystem'] = ''
647
648
649
        GMS_identifier_fullScene['proc_level'] = proc_chain[proc_chain.index(self.inObjs[0].proc_level) - 1]

        return SRF(GMS_identifier_fullScene, wvl_unit='nanometers', format_bandnames=True)
650

651
652
653
654
655
656
    def _get_mask_clouds(self):
        """Returns an instance of S2Mask in case cloud mask is given by input GMS objects. Otherwise None is returned.

        :return:
        """

657
658
        tgt_res = self.inObjs[0].ac_options['cld_mask']['target_resolution']

659
660
        # check if input GMS objects provide a cloud mask
        avail_cloud_masks = {inObj.GMS_identifier['Subsystem']: inObj.mask_clouds for inObj in self.inObjs}
661
        no_avail_CMs = list(set(avail_cloud_masks.values())) == [None]
662
663

        # compute cloud mask if not already provided
664
665
        if no_avail_CMs:
            algorithm = CFG.job.cloud_masking_algorithm[self.inObjs[0].satellite]
666

667
668
            if algorithm == 'SICOR':
                return None
669

670
671
672
673
674
675
676
677
678
679
680
            else:
                # FMASK or Classical Bayesian
                try:
                    from .cloud_masking import Cloud_Mask_Creator

                    CMC = Cloud_Mask_Creator(self.inObjs[0], algorithm=algorithm)
                    CMC.calc_cloud_mask()
                    cm_geoarray = CMC.cloud_mask_geoarray
                    cm_array = CMC.cloud_mask_array
                    cm_legend = CMC.cloud_mask_legend
                except Exception as err:
681
682
                    self.logger.error('\nAn error occurred during FMASK cloud masking. Error message was: ')
                    self.logger.error(traceback.format_exc())
683
                    return None
684

685
686
        else:
            # check if there is a cloud mask with suitable GSD
Daniel Scheffler's avatar
Daniel Scheffler committed
687
            inObjs2use = [obj for obj in self.inObjs if obj.mask_clouds is not None and obj.mask_clouds.xgsd == tgt_res]
688
689
            if not inObjs2use:
                raise ValueError('Error appending cloud mask to input arguments of atmospheric correction. No input '
Daniel Scheffler's avatar
Daniel Scheffler committed
690
                                 'GMS object provides a cloud mask with spatial resolution of %s.' % tgt_res)
691
692
693
694
695
696
697
698
            inObj2use = inObjs2use[0]

            # get mask (geo)array
            cm_geoarray = inObj2use.mask_clouds
            cm_array = inObj2use.mask_clouds[:]

            # get legend
            cm_legend = get_mask_classdefinition('mask_clouds', inObj2use.satellite)
699
            #    {'Clear': 10, 'Thick Clouds': 20, 'Thin Clouds': 30, 'Snow': 40}  # FIXME hardcoded
700
701
702
703
704
705

            # validate that xGSD equals yGSD
            if cm_geoarray.xgsd != cm_geoarray.ygsd:
                warnings.warn("Cloud mask X/Y GSD is not equal for entity ID %s" % inObj2use.entity_ID +
                              (' (%s)' % inObj2use.subsystem if inObj2use.subsystem else '') +
                              'Using X-GSD as key for cloud mask geocoding.')
706
707
708
709

        # get geocoding
        cm_geocoding = self.metadata["spatial_samplings"][tgt_res]

710
711
        # get nodata value
        self.options['cld_mask']['nodata_value_mask'] = cm_geoarray.nodata
712

713
        # append cloud mask to input object with the same spatial resolution if there was no mask before
714
        for inObj in self.inObjs:
715
            if inObj.arr.xgsd == cm_geoarray.xgsd:
716
717
                inObj.mask_clouds = cm_geoarray
                inObj.build_combined_masks_array()
Daniel Scheffler's avatar
Daniel Scheffler committed
718
                break  # appending it to one inObj is enough
719

720
721
722
        return S2Mask(mask_array=cm_array,
                      mask_legend=cm_legend,
                      geo_coding=cm_geocoding)
723

724
725
    def run_atmospheric_correction(self, dump_ac_input=False):
        # type: (bool) -> list
726
727
728
        """Collects all input data for atmospheric correction, runs the AC and returns the corrected L1C objects
        containing surface reflectance.

729
730
        :param dump_ac_input:   allows to dump the inputs of AC to the scene's processing folder in case AC fails
        :return:                list of L1C_object instances containing atmospherically corrected data
731
        """
732
733

        # collect input args/kwargs for AC
734
735
        self.logger.info('Calculating input data for atmospheric correction...')

736
        rs_data = dict(
Daniel Scheffler's avatar
Daniel Scheffler committed
737
738
739
740
741
742
743
744
745
            data=self.data,
            metadata=self.metadata,
            nodata=self.nodata,
            band_spatial_sampling=self.band_spatial_sampling,
            tile_name=self.tile_name,
            dem=self._get_dem(),
            srf=self._get_srf(),
            mask_clouds=self._get_mask_clouds()
            # returns an instance of S2Mask or None if cloud mask is not given by input GMS objects
Daniel Scheffler's avatar
Daniel Scheffler committed
746
        )  # NOTE: all keys of this dict are later converted to attributes of RSImage
747

Daniel Scheffler's avatar
Daniel Scheffler committed
748
        script = False
749

750
751
752
        # create an instance of RSImage
        rs_image = RSImage(**rs_data)

753
        self.ac_input = dict(
754
            rs_image=rs_image,
Daniel Scheffler's avatar
Daniel Scheffler committed
755
            options=self.options,  # type: dict
756
757
            logger=repr(self.logger),  # only a string
            script=script
758
        )
759

760
761
762
763
        # path_dump = self.inObjs[0].pathGen.get_path_ac_input_dump()
        # with open(path_dump, 'wb') as outF:
        #     dill.dump(self.ac_input, outF)

764
        # run AC
765
        self.logger.info('Atmospheric correction started.')
766
        try:
767
            rs_image.logger = self.logger
768
            self.results = ac_gms(rs_image, self.options, logger=self.logger, script=script)
769

770
        except Exception as e:
771
            # serialialize AC input
772
773
774
775
776
777
            if dump_ac_input:
                path_dump = self.inObjs[0].pathGen.get_path_ac_input_dump()
                with open(path_dump, 'wb') as outF:
                    dill.dump(self.ac_input, outF)

                self.logger.error('An error occurred during atmospheric correction. Inputs have been dumped to %s.'
Daniel Scheffler's avatar
Daniel Scheffler committed
778
                                  % path_dump)
779
780

            # delete AC input arrays
Daniel Scheffler's avatar
Daniel Scheffler committed
781
            for inObj in self.inObjs:  # type: L1C_object
782
783
                inObj.delete_ac_input_arrays()

784
785
            self.logger.error('\nAn error occurred during atmospheric correction. BE AWARE THAT THE SCENE %s '
                              '(ENTITY ID %s) HAS NOT BEEN ATMOSPHERICALLY CORRECTED! Error message was: \n%s\n'
786
                              % (self.inObjs[0].scene_ID, self.inObjs[0].entity_ID, repr(e)))
787
            self.logger.error(traceback.format_exc())
788
            # TODO include that in the job summary
789

790
791
            return list(self.inObjs)

792
        # get processing infos
Daniel Scheffler's avatar
Daniel Scheffler committed
793
        self.proc_info = self.ac_input['options']['processing']  # FIXME this is not appended to GMS objects
794

795
        # join results
Daniel Scheffler's avatar
Daniel Scheffler committed
796
        self._join_results_to_inObjs()  # sets self.outObjs
797

798
799
        # delete input arrays that are not needed anymore
        [inObj.delete_ac_input_arrays() for inObj in self.inObjs]
800

801
802
803
        return self.outObjs

    def _join_results_to_inObjs(self):
804
805
806
        """
        Join results of atmospheric correction to the input GMS objects.
        """
807

808
        self.logger.info('Joining results of atmospheric correction to input GMS objects.')
Daniel Scheffler's avatar
Daniel Scheffler committed
809
810
811
        # delete logger
        # -> otherwise logging in inObjs would open a second FileHandler to the same file (which is permitted)
        del self.logger
812
813
814
815
816
817
818
819

        self._join_data_ac()
        self._join_data_errors()
        self._join_mask_clouds()
        self._join_mask_confidence_array()

        # update masks (always do that because masks can also only contain one layer)
        [inObj.build_combined_masks_array() for inObj in self.inObjs]
820

821
822
823
824
        self.outObjs = self.inObjs

    def _join_data_ac(self):
        """
Daniel Scheffler's avatar
Daniel Scheffler committed
825
826
        Join ATMOSPHERICALLY CORRECTED ARRAY as 3D int8 or int16 BOA reflectance array, scaled to scale factor from
        config.
827
        """
828

829
        if self.results.data_ac is not None:
830
            for inObj in self.inObjs:
831
                assert isinstance(inObj, L1B_object)
832
                nodata = self.results.nodata[inObj.arr.xgsd]  # 2D mask with True outside of image coverage
Daniel Scheffler's avatar
Daniel Scheffler committed
833
                ac_bandNs = [bandN for bandN in inObj.arr.bandnames if bandN in self.results.data_ac.keys()]
834
                out_LBA = [bN.split('B0')[1] if bN.startswith('B0') else bN.split('B')[1] for bN in ac_bandNs]
835

836
837
838
839
840
841
                # update metadata
                inObj.arr_desc = 'BOA_Ref'
                inObj.MetaObj.bands = len(self.results.data_ac)
                inObj.MetaObj.PhysUnit = 'BOA_Reflectance in [0-%d]' % CFG.usecase.scale_factor_BOARef
                inObj.MetaObj.LayerBandsAssignment = out_LBA
                inObj.MetaObj.filter_layerdependent_metadata()
842
                inObj.meta_odict = inObj.MetaObj.to_odict()  # actually auto-updated by getter
843

844
                # join SURFACE REFLECTANCE as 3D int16 array, scaled to scale factor from config
845
846
                # FIXME AC output nodata values = 0 -> new nodata areas but mask not updated
                oF_refl, oZ_refl, oS_refl = get_outFillZeroSaturated(inObj.arr.dtype)
847
                surf_refl = np.dstack((self.results.data_ac[bandN] for bandN in ac_bandNs))
848
849
850
                surf_refl *= CFG.usecase.scale_factor_BOARef  # scale using scale factor (output is float16)
                # FIXME really set AC nodata values to GMS outZero?
                surf_refl[nodata] = oZ_refl  # overwrite AC nodata values with GMS outZero
Daniel Scheffler's avatar
Daniel Scheffler committed
851
                # apply the original nodata mask (indicating background values)
852
                surf_refl[np.array(inObj.mask_nodata).astype(np.int8) == 0] = oF_refl
853

Daniel Scheffler's avatar
Daniel Scheffler committed
854
                if self.results.bad_data_value is np.nan:
855
                    surf_refl[np.isnan(surf_refl)] = oF_refl
Daniel Scheffler's avatar
Daniel Scheffler committed
856
                else:
Daniel Scheffler's avatar
Daniel Scheffler committed
857
858
                    surf_refl[
                        surf_refl == self.results.bad_data_value] = oF_refl  # FIXME meaningful to set AC nans to -9999?
859
860
861

                # overwrite LayerBandsAssignment and use inObj.arr setter to generate a GeoArray
                inObj.LayerBandsAssignment = out_LBA
862
                inObj.arr = surf_refl.astype(inObj.arr.dtype)  # -> int16 (also converts NaNs to 0 if needed
863

864
865
866
        else:
            self.logger.warning('Atmospheric correction did not return a result for the input array. '
                                'Thus the output keeps NOT atmospherically corrected.')
867

868
869
870
871
872
873
874
875
876
877
878
879
880
881
882
883
884
885
886
887
888
889
890
891
892
893
894
895
896
    def _join_data_errors(self):
        """
        Join ERRORS ARRAY as 3D int8 or int16 BOA reflectance array, scaled to scale factor from config.
        """

        if self.results.data_errors is not None:
            for inObj in self.inObjs:
                nodata = self.results.nodata[inObj.arr.xgsd]  # 2D mask with True outside of image coverage
                ac_bandNs = [bandN for bandN in inObj.arr.bandnames if bandN in self.results.data_ac.keys()]

                ac_errors = np.dstack((self.results.data_errors[bandN] for bandN in ac_bandNs))
                ac_errors *= CFG.usecase.scale_factor_errors_ac  # scale using scale factor (output is float16)
                out_dtype = np.int8 if CFG.usecase.scale_factor_errors_ac <= 255 else np.int16
                ac_errors[nodata] = get_outFillZeroSaturated(out_dtype)[0]
                ac_errors = ac_errors.astype(out_dtype)
                inObj.ac_errors = ac_errors  # setter generates a GeoArray with the same bandnames like inObj.arr
                # TODO how to handle nans?
        else:
            self.logger.warning("Atmospheric correction did not provide a 'data_errors' array. Maybe due to "
                                "missing SNR model? GMS_object.ac_errors kept None.")

    def _join_mask_clouds(self):
        """
        Join CLOUD MASK as 2D uint8 array.
        NOTE: mask_clouds has also methods 'export_mask_rgb()', 'export_confidence_to_jpeg2000()', ...
        """

        if self.results.mask_clouds.mask_array is not None:
            mask_clouds_ac = self.results.mask_clouds.mask_array  # uint8 2D array
897

898
899
            joined = False
            for inObj in self.inObjs:
900
901
                # delete all previous cloud masks
                del inObj.mask_clouds
902
903
904
905

                # append mask_clouds only to the input GMS object with the same dimensions
                if inObj.arr.shape[:2] == mask_clouds_ac.shape:
                    inObj.mask_clouds = mask_clouds_ac
906
907
                    inObj.mask_clouds.legend = self.results.mask_clouds.mask_legend  # dict(value=string, string=value))
                    # FIXME legend is not used later
908
909

                    # set cloud mask nodata value
910
                    tgt_nodata = get_outFillZeroSaturated(mask_clouds_ac.dtype)[0]
911
912
                    ac_out_nodata = self.ac_input['options']['cld_mask']['nodata_value_mask']
                    if tgt_nodata not in self.results.mask_clouds.mask_legend.keys():
913
                        inObj.mask_clouds[inObj.mask_clouds[:] == ac_out_nodata] = tgt_nodata
914
915
916
917
                        mask_clouds_nodata = tgt_nodata
                    else:
                        warnings.warn('The cloud mask from AC output already uses the desired nodata value %s for the '
                                      'class %s. Using AC output nodata value %s.'
918
                                      % (tgt_nodata, self.results.mask_clouds.mask_legend[tgt_nodata], ac_out_nodata))
919
920
921
922
                        mask_clouds_nodata = ac_out_nodata

                    inObj.mask_clouds.nodata = mask_clouds_nodata

923
                    joined = True
924

925
926
927
928
            if not joined:
                self.logger.warning('Cloud mask has not been appended to one of the AC inputs because there was no'
                                    'input GMS object with the same dimensions.')

929
        else:
930
931
            self.logger.warning("Atmospheric correction did not provide a 'mask_clouds.mask_array' array. "
                                "GMS_object.mask_clouds kept None.")
932

933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
    def _join_mask_confidence_array(self):
        """
        Join confidence array for mask_clouds.
        """

        if self.results.mask_clouds.mask_confidence_array is not None:
            cfd_arr = self.results.mask_clouds.mask_confidence_array  # float32 2D array, scaled [0-1, nodata 255]
            cfd_arr[cfd_arr == self.ac_input['options']['cld_mask']['nodata_value_mask']] = -1
            cfd_arr = (cfd_arr * CFG.usecase.scale_factor_BOARef).astype(np.int16)
            cfd_arr[cfd_arr == -CFG.usecase.scale_factor_BOARef] = get_outFillZeroSaturated(cfd_arr.dtype)[0]

            joined = False
            for inObj in self.inObjs:

                # append mask_clouds only to the input GMS object with the same dimensions
                if inObj.arr.shape[:2] == cfd_arr.shape:
                    # set cloud mask confidence array
                    inObj.mask_clouds_confidence = GeoArray(cfd_arr, inObj.arr.gt, inObj.arr.prj,
                                                            nodata=get_outFillZeroSaturated(cfd_arr.dtype)[0])
                    joined = True
953

954
955
956
            if not joined:
                self.logger.warning('Cloud mask confidence array has not been appended to one of the AC inputs because '
                                    'there was no input GMS object with the same dimensions.')
957

958
959
        else:
            self.logger.warning("Atmospheric correction did not provide a 'mask_confidence_array' array for "
960
                                "attribute 'mask_clouds. GMS_object.mask_clouds_confidence kept None.")