gms_object.py 79.8 KB
Newer Older
1
2
3
4
5
# -*- coding: utf-8 -*-

import collections
import copy
import datetime
6
import functools
7
8
9
10
11
12
13
import glob
import json
import os
import re
import shutil
import sys
import warnings
14
import logging
15
from collections import OrderedDict
16
from itertools import chain
17
from typing import Iterable, List, Union, TYPE_CHECKING  # noqa F401  # flake8 issue
18
19
20

import numpy as np
import spectral
21
from spectral.io import envi
22
from numba import jit
23
from pandas import DataFrame, read_csv
24
from nested_dict import nested_dict
25

26
27
28
29
try:
    from osgeo import gdalnumeric
except ImportError:
    import gdalnumeric
30

31
from geoarray import GeoArray
32
from py_tools_ds.geo.coord_grid import is_coord_grid_equal
33
from py_tools_ds.geo.projection import EPSG2WKT
34
35
36
from py_tools_ds.geo.map_info import geotransform2mapinfo, mapinfo2geotransform
from py_tools_ds.geo.coord_calc import calc_FullDataset_corner_positions
from py_tools_ds.geo.coord_trafo import pixelToLatLon, pixelToMapYX
37
from sicor.options import get_options as get_ac_options
38

39
from ..misc.logging import GMS_logger as DatasetLogger
40
from ..model.mgrs_tile import MGRS_tile
41
from ..model.metadata import METADATA, get_dict_LayerOptTherm, metaDict_to_metaODict
42
43
44
from ..model.dataset import Dataset
from ..misc import path_generator as PG
from ..misc import database_tools as DB_T
45
from ..options.config import GMS_config as CFG
46
47
48
from ..algorithms import geoprocessing as GEOP
from ..io import input_reader as INP_R
from ..io import output_writer as OUT_W
49
50
from ..misc import helper_functions as HLP_F
from ..misc import definition_dicts as DEF_D
51

52
53
54
if TYPE_CHECKING:
    from ..algorithms.L1C_P import L1C_object  # noqa F401  # flake8 issue

55
__author__ = 'Daniel Scheffler'
56
57


58
class GMS_object(Dataset):
59
60
61
62
    # class attributes
    # NOTE: these attributes can be modified and seen by ALL GMS_object instances
    proc_status_all_GMSobjs = nested_dict()

63
64
65
66
    def __init__(self, pathImage=''):
        # get all attributes of base class "Dataset"
        super(GMS_object, self).__init__()

67
        # add private attributes
68
        self._dict_LayerOptTherm = None
69
70
        self._cloud_masking_algorithm = None
        self._meta_odict = None
71
        self._coreg_info = None
72

73
        self.job_ID = CFG.ID
74
        # FIXME not needed anymore?:
75
        # self.dataset_ID = int(DB_T.get_info_from_postgreSQLdb(CFG.conn_database, 'scenes', ['datasetid'],
76
77
78
        #                                {'id': self.scene_ID})[0][0]) if self.scene_ID !=-9999 else -9999
        self.scenes_proc_ID = None  # set by Output writer after creation/update of db record in table scenes_proc
        self.mgrs_tiles_proc_ID = None  # set by Output writer after creation/update of db rec in table mgrs_tiles_proc
79
        self.MGRS_info = None
80
81

        # set pathes
82
83
84
85
        self.path_cloud_class_obj = ''

        # handle initialization arguments
        if pathImage:
86
87
            # run the setter for 'arr' of the base class 'Dataset' which creates an Instance of GeoArray
            self.arr = pathImage
88
89
90
91

    def __getstate__(self):
        """Defines how the attributes of GMS object are pickled."""

Daniel Scheffler's avatar
Bugfix    
Daniel Scheffler committed
92
        self.close_loggers()
93
        del self.pathGen  # path generator can only be used for the current processing level
94
95

        # delete arrays if their in-mem size is to big to be pickled
96
        # => (avoids MaybeEncodingError: Error sending result: '[<gms_preprocessing.algorithms.L2C_P.L2C_object
97
        #    object at 0x7fc44f6399e8>]'. Reason: 'error("'i' format requires -2147483648 <= number <= 2147483647",)')
98
        if self.proc_level == 'L2C' and CFG.inmem_serialization:
99
100
            # FIXME check by bandname
            if self.mask_nodata is not None and self.masks.bands > 1 and self.mask_clouds is not None:
101
                del self.masks
102

Daniel Scheffler's avatar
Bugfix    
Daniel Scheffler committed
103
104
        return self.__dict__

105
    def set_pathes(self):
106
107
108
109
110
111
        self.baseN = self.pathGen.get_baseN()
        self.path_procdata = self.pathGen.get_path_procdata()
        self.ExtractedFolder = self.pathGen.get_path_tempdir()
        self.path_logfile = self.pathGen.get_path_logfile()
        self.pathGen = PG.path_generator(self.__dict__)  # passes a logger in addition to previous attributes
        self.path_archive = self.pathGen.get_local_archive_path_baseN()
112

113
        if not CFG.inmem_serialization:
Daniel Scheffler's avatar
Daniel Scheffler committed
114
            self.path_InFilePreprocessor = os.path.join(self.ExtractedFolder, '%s%s_DN.bsq'
115
116
                                                        % (self.entity_ID,
                                                           ('_%s' % self.subsystem if self.subsystem else '')))
117
        else:  # keep data in memory
118
            self.path_InFilePreprocessor = None  # None: keeps all produced data in memory (numpy array attributes)
119
120
121
122
123
124

        self.path_MetaPreprocessor = self.path_archive

    def validate_pathes(self):
        if not os.path.isfile(self.path_archive) and not os.path.isdir(self.path_archive):
            self.logger.info("The %s dataset '%s' has not been processed earlier and no corresponding raw data archive"
125
                             "has been found at %s." % (self.sensor, self.entity_ID, self.path_archive))
126
            self.logger.info('Trying to download the dataset...')
127
            self.path_archive_valid = self._data_downloader(self.sensor, self.entity_ID)
128
129
130
        else:
            self.path_archive_valid = True

131
        if not CFG.inmem_serialization and self.ExtractedFolder and not os.path.isdir(self.ExtractedFolder):
132
133
134
135
136
137
138
            os.makedirs(self.ExtractedFolder)

        assert os.path.exists(self.path_archive), 'Invalid path to RAW data. File %s does not exist at %s.' \
                                                  % (os.path.basename(self.path_archive),
                                                     os.path.dirname(self.path_archive))
        assert isinstance(self.path_archive, str), 'Invalid path to RAW data. Got %s instead of string or unicode.' \
                                                   % type(self.path_archive)
139
        if not CFG.inmem_serialization and self.ExtractedFolder:
140
141
            assert os.path.exists(self.path_archive), \
                'Invalid path for temporary files. Directory %s does not exist.' % self.ExtractedFolder
142
143
144
145
146
147
148
149

    @property
    def logger(self):
        if self._loggers_disabled:
            return None
        if self._logger and self._logger.handlers[:]:
            return self._logger
        else:
150
            self._logger = DatasetLogger('log__' + self.baseN, fmt_suffix=self.scene_ID, path_logfile=self.path_logfile,
151
                                         log_level=CFG.log_level, append=True)
152
153
154
155
            return self._logger

    @logger.setter
    def logger(self, logger):
156
        assert isinstance(logger, logging.Logger) or logger in ['not set', None], \
157
            "GMS_obj.logger can not be set to %s." % logger
158
159

        # save prior logs
160
        # if logger is None and self._logger is not None:
161
        #    self.log += self.logger.captured_stream
162
163
        self._logger = logger

164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
    @property
    def proc_status(self):
        # type: () -> str
        """
        Get the processing status of the current GMS_object (subclass) instance for the current processing level.

        Possible values: 'initialized', 'running', 'finished', 'failed'
        """
        # NOTE: self.proc_status_all_GMSobjs is a class attribute (visible and modifyable from any other subsystem)
        return self.proc_status_all_GMSobjs[self.scene_ID][self.subsystem][self.proc_level]

    @proc_status.setter
    def proc_status(self, new_status):
        # type: (str) -> None
        self.proc_status_all_GMSobjs[self.scene_ID][self.subsystem][self.proc_level] = new_status

180
181
    @property
    def GMS_identifier(self):
182
183
        return collections.OrderedDict(zip(
            ['image_type', 'Satellite', 'Sensor', 'Subsystem', 'proc_level', 'dataset_ID', 'logger'],
184
185
            [self.image_type, self.satellite, self.sensor, self.subsystem, self.proc_level, self.dataset_ID,
             self.logger]))
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201

    @property
    def MetaObj(self):
        if self._meta_odict:
            # if there is already a meta_odict -> create a new MetaObj from it (ensures synchronization!)
            self._MetaObj = METADATA(self.GMS_identifier).from_odict(self._meta_odict)
            del self.meta_odict
        elif not self._MetaObj:
            # if there is no meta_odict and no MetaObj -> create MetaObj by reading metadata from disk
            pass  # reading from disk should use L1A_P.L1A_object.import_metadata -> so just return None

        return self._MetaObj

    @MetaObj.setter
    def MetaObj(self, MetaObj):
        assert isinstance(MetaObj, METADATA), "'MetaObj' can only be set to an instance of METADATA class. " \
202
                                              "Got %s." % type(MetaObj)
203
204
205
        self._MetaObj = MetaObj

        # update meta_odict
206
        del self.meta_odict  # it is recreated if getter is used the next time
207
208
209

    @MetaObj.deleter
    def MetaObj(self):
210
211
212
213
214
        if hasattr(self, '_MetaObj') and self._MetaObj and hasattr(self._MetaObj, 'logger') and \
                self._MetaObj.logger not in [None, 'not set']:
            self._MetaObj.logger.close()
            self._MetaObj.logger = None

215
216
217
218
219
        self._MetaObj = None

    @property
    def meta_odict(self):
        if self._MetaObj:
220
            # if there is already a MetaObj -> create new meta_odict from it (ensures synchronization!)
221
222
223
224
            self._meta_odict = self._MetaObj.to_odict()
            del self.MetaObj
        elif not self._meta_odict:
            # if there is no MetaObj and no meta_odict -> use MetaObj getter to read metadata from disk
225
            pass  # reading from disk should use L1A_P.L1A_object.import_metadata -> so just return None
226
227
228
229
230
231
            self._meta_odict = None

        return self._meta_odict

    @meta_odict.setter
    def meta_odict(self, odict):
232
233
        assert isinstance(odict, (collections.OrderedDict, dict)), "'meta_odict' can only be set to an instance of " \
                                                                   "collections.OrderedDict. Got %s." % type(odict)
234
235
236
        self._meta_odict = odict

        # update MetaObj
237
        del self.MetaObj  # it is recreated if getter is used the next time
238
239
240
241
242

    @meta_odict.deleter
    def meta_odict(self):
        self._meta_odict = None

243
244
245
246
247
    @property
    def dict_LayerOptTherm(self):
        if self._dict_LayerOptTherm:
            return self._dict_LayerOptTherm
        elif self.LayerBandsAssignment:
248
            self._dict_LayerOptTherm = get_dict_LayerOptTherm(self.identifier, self.LayerBandsAssignment)
249
250
251
252
253
254
255
            return self._dict_LayerOptTherm
        else:
            return None

    @property
    def georef(self):
        """Returns True if the current dataset can serve as spatial reference."""
Daniel Scheffler's avatar
Daniel Scheffler committed
256

257
258
259
260
        return True if self.image_type == 'RSD' and re.search('OLI', self.sensor, re.I) else False

    @property
    def coreg_needed(self):
261
        if self._coreg_needed is None:
262
            self._coreg_needed = not (self.dataset_ID == CFG.datasetid_spatial_ref)
263
        return self._coreg_needed
264
265
266
267
268

    @coreg_needed.setter
    def coreg_needed(self, value):
        self._coreg_needed = value

269
270
271
272
273
274
275
276
277
278
279
280
281
282
    @property
    def coreg_info(self):
        if not self._coreg_info:
            self._coreg_info = {
                'corrected_shifts_px': {'x': 0, 'y': 0},
                'corrected_shifts_map': {'x': 0, 'y': 0},
                'original map info': self.meta_odict['map info'],
                'updated map info': None,
                'reference scene ID': None,
                'reference entity ID': None,
                'reference geotransform': None,
                # reference projection must be the own projection in order to avoid overwriting with a wrong EPSG
                'reference projection': self.meta_odict['coordinate system string'],
                'reference extent': {'rows': None, 'cols': None},
283
284
                'reference grid': [list(CFG.spatial_ref_gridx),
                                   list(CFG.spatial_ref_gridy)],
285
286
287
288
289
290
291
292
293
                'success': False
            }

        return self._coreg_info

    @coreg_info.setter
    def coreg_info(self, val):
        self._coreg_info = val

294
295
296
297
    @property
    def resamp_needed(self):
        if self._resamp_needed is None:
            gt = mapinfo2geotransform(self.meta_odict['map info'])
298
299
            self._resamp_needed = not is_coord_grid_equal(gt, CFG.spatial_ref_gridx,
                                                          CFG.spatial_ref_gridy)
300
301
302
303
304
305
306
307
        return self._resamp_needed

    @resamp_needed.setter
    def resamp_needed(self, value):
        self._resamp_needed = value

    @property
    def masks(self):
308
        # if self.mask_nodata is not None and self.mask_clouds is not None and \
309
310
311
312
        #     self._masks is not None and self._masks.bands==1:

        #     self.build_combined_masks_array()

313
314
315
        return self._masks

    @masks.setter
316
    def masks(self, *geoArr_initArgs):
317
318
319
320
        """
        NOTE: This does not automatically update mask_nodata and mask_clouds BUT if mask_nodata and mask_clouds are
        None their getters will automatically synchronize!
        """
Daniel Scheffler's avatar
Daniel Scheffler committed
321

322
        if geoArr_initArgs[0] is not None:
323
            self._masks = GeoArray(*geoArr_initArgs)
324
            self._masks.nodata = 0
325
326
            self._masks.gt = self.arr.gt
            self._masks.prj = self.arr.prj
327
328
        else:
            del self.masks
329

330
331
332
333
    @masks.deleter
    def masks(self):
        self._masks = None

334
335
336
    @property
    def cloud_masking_algorithm(self):
        if not self._cloud_masking_algorithm:
337
            self._cloud_masking_algorithm = CFG.cloud_masking_algorithm[self.satellite]
338
339
        return self._cloud_masking_algorithm

340
341
342
    @property
    def ac_options(self):
        """
343
344
        Returns the options dictionary needed as input for atmospheric correction. If an empty dictionary is returned,
        atmospheric correction is not yet available for the current sensor and will later be skipped.
345
        """
Daniel Scheffler's avatar
Daniel Scheffler committed
346

347
        if not self._ac_options:
348
            path_ac_options = CFG.path_custom_sicor_options or PG.get_path_ac_options(self.GMS_identifier)
349

350
            if path_ac_options and os.path.exists(path_ac_options):
351
352
                # don't validate because options contain pathes that do not exist on another server:
                opt_dict = get_ac_options(path_ac_options, validation=False)
353

Daniel Scheffler's avatar
Daniel Scheffler committed
354
                # update some file paths depending on the current environment
355
356
                opt_dict['DEM']['fn'] = CFG.path_dem_proc_srtm_90m
                opt_dict['ECMWF']['path_db'] = CFG.path_ECMWF_db
357
358
359
                opt_dict['S2Image'][
                    'S2_MSI_granule_path'] = None  # only a placeholder -> will always be None for GMS usage
                opt_dict['output'] = []  # outputs are not needed for GMS -> so
360
                opt_dict['report']['report_path'] = os.path.join(self.pathGen.get_path_procdata(), '[TYPE]')
361
362
                if 'uncertainties' in opt_dict:
                    opt_dict['uncertainties']['snr_model'] = PG.get_path_snr_model(self.GMS_identifier)
363

364
365
366
367
368
369
                # apply custom configuration
                opt_dict["logger"]['level'] = CFG.log_level
                opt_dict["ram"]['upper_limit'] = CFG.ac_max_ram_gb
                opt_dict["ram"]['unit'] = 'GB'
                opt_dict["AC"]['fill_nonclear_areas'] = CFG.ac_fillnonclear_areas
                opt_dict["AC"]['clear_area_labels'] = CFG.ac_clear_area_labels
370
                # opt_dict['AC']['n_cores'] = CFG.CPUs if CFG.allow_subMultiprocessing else 1
371

372
                self._ac_options = opt_dict
373
374
375
            else:
                self.logger.warning('There is no options file available for atmospheric correction. '
                                    'Atmospheric correction must be skipped.')
376

377
378
        return self._ac_options

379
    def get_copied_dict_and_props(self, remove_privates=False):
380
        # type: (bool) -> dict
381
        """Returns a copy of the current object dictionary including the current values of all object properties."""
382
383
384

        # loggers must be closed
        self.close_GMS_loggers()
385
386
        # this disables automatic recreation of loggers (otherwise loggers are created by using getattr()):
        self._loggers_disabled = True
387
388
389
390
391

        out_dict = self.__dict__.copy()

        # add properties
        property_names = [p for p in dir(self.__class__) if isinstance(getattr(self.__class__, p), property)]
392
        [out_dict.update({propK: copy.copy(getattr(self, propK))}) for propK in property_names]
393
394
395
396
397
398
399
400
401

        # remove private attributes
        if remove_privates:
            out_dict = {k: v for k, v in out_dict.items() if not k.startswith('_')}

        self._loggers_disabled = False  # enables automatic recreation of loggers

        return out_dict

402
403
    def attributes2dict(self, remove_privates=False):
        # type: (bool) -> dict
404
        """Returns a copy of the current object dictionary including the current values of all object properties."""
405
406
407

        # loggers must be closed
        self.close_GMS_loggers()
408
409
        # this disables automatic recreation of loggers (otherwise loggers are created by using getattr()):
        self._loggers_disabled = True
410
411
412
413

        out_dict = self.__dict__.copy()

        # add some selected property values
414
415
        for i in ['GMS_identifier', 'LayerBandsAssignment', 'coreg_needed', 'coreg_info', 'resamp_needed',
                  'dict_LayerOptTherm', 'georef', 'meta_odict']:
416
            out_dict[i] = getattr(self, i)
417
418
419
420
421

        # remove private attributes
        if remove_privates:
            out_dict = {k: v for k, v in out_dict.items() if not k.startswith('_')}

422
        self._loggers_disabled = False  # enables automatic recreation of loggers
423
424
        return out_dict

425
    def _data_downloader(self, sensor, entity_ID):
426
427
428
429
        self.logger.info('Data downloader started.')
        success = False
        " > download source code for Landsat here < "
        if not success:
430
431
            self.logger.critical(
                "Download for %s dataset '%s' failed. No further processing possible." % (sensor, entity_ID))
432
            raise RuntimeError('Archive download failed.')
433
434
        return success

435
436
437
438
439
    def from_disk(self, tuple_GMS_subset):
        """Fills an already instanced GMS object with data from disk. Excludes array attributes in Python mode.

        :param tuple_GMS_subset:    <tuple> e.g. ('/path/gms_file.gms', ['cube', None])
        """
440

441
        path_GMS_file = tuple_GMS_subset[0]
442
        GMSfileDict = INP_R.GMSfile2dict(path_GMS_file)
443
444

        # copy all attributes from GMS file (private attributes are not touched since they are not included in GMS file)
445
        self.meta_odict = GMSfileDict['meta_odict']  # set that first in order to make some getters and setters work
446
447
        for key, value in GMSfileDict.items():
            if key in ['GMS_identifier', 'georef', 'dict_LayerOptTherm']:
448
                continue  # properties that should better be created on the fly
449
450
            try:
                setattr(self, key, value)
451
452
            except Exception:
                raise AttributeError("Can't set attribute %s." % key)
453

454
        self.acq_datetime = datetime.datetime.strptime(self.acq_datetime, '%Y-%m-%d %H:%M:%S.%f%z')
455
456
        self.arr_shape, self.arr_pos = tuple_GMS_subset[1]

457
458
459
        self.arr = self.pathGen.get_path_imagedata()
        # self.mask_nodata and self.mask_clouds are auto-synchronized via self.masks (see their getters):
        self.masks = self.pathGen.get_path_maskdata()
460

461
462
        return copy.copy(self)

463
    def from_sensor_subsystems(self, list_GMS_objs):
464
465
        # type: (List[GMS_object]) -> GMS_object
        # TODO convert to classmethod
466
467
468
469
470
471
        """Merge separate GMS objects belonging to the same scene-ID into ONE GMS object.

        :param list_GMS_objs:   <list> of GMS objects covering the same geographic area but representing different
                                sensor subsystems (e.g. 3 GMS_objects for Sentinel-2 10m/20m/60m bands)
        """

472
        # assertions
473
474
        assert len(list_GMS_objs) > 1, "'GMS_object.from_sensor_subsystems()' expects multiple input GMS objects. " \
                                       "Got %d." % len(list_GMS_objs)
475
        assert all([is_coord_grid_equal(list_GMS_objs[0].arr.gt, *obj.arr.xygrid_specs) for obj in list_GMS_objs[1:]]),\
476
477
478
            "The input GMS objects must have the same pixel grid. Received: %s" \
            % np.array([obj.arr.xygrid_specs for obj in list_GMS_objs])
        assert len(list(set([GMS_obj.proc_level for GMS_obj in list_GMS_objs]))) == 1, \
479
480
481
            "The input GMS objects for GMS_object.from_sensor_subsystems() must have the same processing level."
        subsystems = [GMS_obj.subsystem for GMS_obj in list_GMS_objs]
        assert len(subsystems) == len(list(set(subsystems))), \
482
            "The input 'list_GMS_objs' contains duplicates: %s" % subsystems
483

484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
        ##################
        # merge logfiles #
        ##################

        # read all logs into DataFrame, sort it by the first column
        [GMS_obj.close_GMS_loggers() for GMS_obj in list_GMS_objs]  # close the loggers of the input objects
        paths_inLogs = [GMS_obj.pathGen.get_path_logfile() for GMS_obj in list_GMS_objs]
        allLogs_df = DataFrame()
        for log in paths_inLogs:
            df = read_csv(log, sep='\n', delimiter=':   ', header=None,
                          engine='python')  # engine suppresses a pandas warning
            allLogs_df = allLogs_df.append(
                df)  # FIXME this will log e.g. atm. corr 3 times for S2A -> use captured streams instead?

        allLogs_df = allLogs_df.sort_values(0)

        # set common metadata, needed for logfile
        self.baseN = list_GMS_objs[0].pathGen.get_baseN(merged_subsystems=True)
        self.path_logfile = list_GMS_objs[0].pathGen.get_path_logfile(merged_subsystems=True)
        self.scene_ID = list_GMS_objs[0].scene_ID

        # write the merged logfile and flush previous logger
        np.savetxt(self.path_logfile, np.array(allLogs_df), delimiter=':   ', fmt="%s")
        self.close_GMS_loggers()

509
        # log
510
511
        self.logger.info('Merging the subsystems %s to a single GMS object...'
                         % ', '.join([GMS_obj.subsystem for GMS_obj in list_GMS_objs]))
512
513

        # find the common extent. NOTE: boundsMap is expected in the order [xmin,xmax,ymin,ymax]
514
515
        geoExtents = np.array([GMS_obj.arr.box.boundsMap for GMS_obj in list_GMS_objs])
        common_extent = (min(geoExtents[:, 0]), max(geoExtents[:, 1]), min(geoExtents[:, 2]), max(geoExtents[:, 3]))
516

517
518
519
520
        ##################
        # MERGE METADATA #
        ##################

521
522
523
        # copy all attributes from the first input GMS file (private attributes are not touched)
        for key, value in list_GMS_objs[0].__dict__.copy().items():
            if key in ['GMS_identifier', 'georef', 'dict_LayerOptTherm']:
524
                continue  # properties that should better be created on the fly
525
526
            elif key in ['baseN', 'path_logfile', 'scene_ID', 'subsystem']:
                continue  # either previously set with common values or not needed for merged GMS_object
527
528
            try:
                setattr(self, key, value)
529
530
            except Exception:
                raise AttributeError("Can't set attribute %s." % key)
531

532
        # update LayerBandsAssignment and get full list of output bandnames
533
        from .metadata import get_LayerBandsAssignment
534
535
        # use identifier of first input GMS object for getting LBA (respects current proc_level):
        gms_idf = list_GMS_objs[0].GMS_identifier
536
        self.LayerBandsAssignment = get_LayerBandsAssignment(gms_idf, return_fullLBA=True)
537
        bandnames = ['B%s' % i if len(i) == 2 else 'B0%s' % i for i in self.LayerBandsAssignment]
538
539
540

        # update layer-dependent metadata with respect to remaining input GMS objects
        self.meta_odict.update({
541
542
543
544
            'band names': [('Band %s' % i) for i in self.LayerBandsAssignment],
            'LayerBandsAssignment': self.LayerBandsAssignment,
            'Subsystem': '',
            'PhysUnit': self.meta_odict['PhysUnit'],  # TODO can contain val_optical / val_thermal
545
546
        })
        self.subsystem = ''
547
548
        del self.pathGen  # must be refreshed because subsystem is now ''
        self.close_GMS_loggers()  # must also be refreshed because it depends on pathGen
549

550
551
        for attrN in ['SolIrradiance', 'CWL', 'FWHM', 'Offsets', 'OffsetsRef', 'Gains', 'GainsRef',
                      'ThermalConstK1', 'ThermalConstK2', 'ViewingAngle_arrProv', 'IncidenceAngle_arrProv']:
552
553
554
555
556
557
558

            # combine values from separate subsystems to a single value
            attrDic_fullLBA = {}
            for GMS_obj in list_GMS_objs:
                attr_val = getattr(GMS_obj.MetaObj, attrN)
                if isinstance(attr_val, list):
                    attrDic_fullLBA.update(dict(zip(GMS_obj.LayerBandsAssignment, attr_val)))
559
                elif isinstance(attr_val, (dict, collections.OrderedDict)):
560
561
562
563
564
565
566
                    attrDic_fullLBA.update(attr_val)
                else:
                    raise ValueError(attrN)

            # update the attribute in self.MetaObj
            if attrDic_fullLBA:
                val2set = [attrDic_fullLBA[bN] for bN in self.LayerBandsAssignment] \
567
                    if isinstance(getattr(list_GMS_objs[0].MetaObj, attrN), list) else attrDic_fullLBA
568
569
                setattr(self.MetaObj, attrN, val2set)

570
571
572
        ####################
        # MERGE ARRAY DATA #
        ####################
573

574
        # overwrite array data with merged arrays, clipped to common_extent and reordered according to FullLayerBandsAss
575
576
577
        for attrname in ['arr', 'ac_errors', 'dem', 'mask_nodata', 'mask_clouds', 'mask_clouds_confidence', 'masks']:

            # get current attribute of each subsystem without running property getters
578
            all_arrays = [getattr(GMS_obj, '_%s' % attrname) for GMS_obj in list_GMS_objs]
579
580
581
582
583
584
585
586
587

            # get the same geographical extent for each input GMS object
            if len(set(tuple(ext) for ext in geoExtents.tolist())) > 1:
                # in case of different extents
                geoArrs_same_extent = []

                for geoArr in all_arrays:

                    if geoArr is not None:
588
589
                        # FIXME mask_clouds_confidence is until here no GeoArray
                        # FIXME -> has no nodata value -> calculation throughs warning
590
591
                        geoArr_same_extent = \
                            GeoArray(*geoArr.get_mapPos(
592
593
594
595
                                mapBounds=np.array(common_extent)[[0, 2, 1, 3]],  # pass (xmin, ymin, xmax, ymax)
                                mapBounds_prj=geoArr.prj),
                                     bandnames=list(geoArr.bandnames.keys()),
                                     nodata=geoArr.nodata)
596
597
                        geoArrs_same_extent.append(geoArr_same_extent)
                    else:
598
599
                        # e.g. in case of cloud mask that is only appended to the GMS object with the same
                        # spatial resolution)
600
601
602
603
604
605
                        geoArrs_same_extent.append(None)

            else:
                # skip get_mapPos() if all input GMS objects have the same extent
                geoArrs_same_extent = all_arrays

606
607
            # validate output GeoArrays #
            #############################
608
609
            if len([gA for gA in geoArrs_same_extent if gA is not None]) > 1:
                equal_bounds = all([geoArrs_same_extent[0].box.boundsMap == gA.box.boundsMap
610
                                    for gA in geoArrs_same_extent[1:]])
611
612
                equal_epsg = all([geoArrs_same_extent[0].epsg == gA.epsg for gA in geoArrs_same_extent[1:]])
                equal_xydims = all([geoArrs_same_extent[0].shape[:2] == gA.shape[:2] for gA in geoArrs_same_extent[1:]])
613
614
615
616
617
                if not all([equal_bounds, equal_epsg, equal_xydims]):
                    raise RuntimeError('Something went wrong during getting the same geographical extent for all the '
                                       'input GMS objects. The extents, projections or pixel dimensions of the '
                                       'calculated input GMS objects are not equal.')

618
619
            # set output arrays #
            #####################
620
621
622
            if attrname in ['arr', 'ac_errors'] and list(set(geoArrs_same_extent)) != [None]:
                # the bands of these arrays have to be reordered according to FullLayerBandsAssignment

623
624
                # check that each desired band name for the current attribute is provided by one of the input
                # GMS objects
625
626
                available_bandNs = list(chain.from_iterable([list(gA.bandnames) for gA in geoArrs_same_extent]))
                for bN in bandnames:
627
                    if bN not in available_bandNs:
628
                        raise ValueError("The given input GMS objects (subsystems) do not provide a bandname '%s' for "
629
630
                                         "the attribute '%s'. Available band names amongst all input GMS objects are: "
                                         "%s" % (bN, attrname, str(available_bandNs)))
631
632

                # merge arrays
633
634
                def get_band(bandN):
                    return [gA[bandN] for gA in geoArrs_same_extent if gA and bandN in gA.bandnames][0]
635
636
                full_geoArr = GeoArray(np.dstack((get_band(bandN) for bandN in bandnames)),
                                       geoArrs_same_extent[0].gt, geoArrs_same_extent[0].prj,
637
638
                                       bandnames=bandnames,
                                       nodata=geoArrs_same_extent[0].nodata)
639
640
641
642
643
                setattr(self, attrname, full_geoArr)

            else:
                # masks, dem, mask_nodata, mask_clouds, mask_clouds_confidence
                if attrname == 'dem':
644
645
                    # use the DEM of the first input object
                    # (if the grid is the same, the DEMs should be the same anyway)
646
                    self.dem = geoArrs_same_extent[0]
647

648
649
650
                elif attrname == 'mask_nodata':
                    # must not be merged -> self.arr is already merged, so just recalculate it (np.all)
                    self.mask_nodata = self.calc_mask_nodata(overwrite=True)
651

652
653
654
                elif attrname == 'mask_clouds':
                    # possibly only present in ONE subsystem (set by atm. Corr.)
                    mask_clouds = [msk for msk in geoArrs_same_extent if msk is not None]
655
656
                    if len(mask_clouds) > 1:
                        raise ValueError('Expected mask clouds in only one subsystem. Got %s.' % len(mask_clouds))
657
                    self.mask_clouds = mask_clouds[0] if mask_clouds else None
658

659
660
661
                elif attrname == 'mask_clouds_confidence':
                    # possibly only present in ONE subsystem (set by atm. Corr.)
                    mask_clouds_conf = [msk for msk in geoArrs_same_extent if msk is not None]
662
663
664
                    if len(mask_clouds_conf) > 1:
                        raise ValueError(
                            'Expected mask_clouds_conf in only one subsystem. Got %s.' % len(mask_clouds_conf))
665
                    self.mask_clouds_confidence = mask_clouds_conf[0] if mask_clouds_conf else None
666

667
                elif attrname == 'masks':
668
669
670
671
672
673
674
675
                    # self.mask_nodata and self.mask_clouds will already be set here -> so just recreate it from there
                    self.masks = None

        # recreate self.masks
        self.build_combined_masks_array()

        # update array-dependent metadata
        self.meta_odict.update({
676
677
            'samples': self.arr.cols, 'lines': self.arr.rows, 'bands': self.arr.bands,
            'map info': geotransform2mapinfo(self.arr.gt, self.arr.prj), 'coordinate system string': self.arr.prj, })
678
679

        # set shape of full array
680
        self.shape_fullArr = self.arr.shape
681
682
683

        return copy.copy(self)

684
685
686
687
688
689
    def from_tiles(self, list_GMS_tiles):
        # type: (list) -> self
        """Merge separate GMS objects with different spatial coverage but belonging to the same scene-ID to ONE GMS object.

        :param list_GMS_tiles: <list> of GMS objects that have been created by cut_GMS_obj_into_blocks()
        """
Daniel Scheffler's avatar
Daniel Scheffler committed
690

691
692
693
694
695
        if 'IMapUnorderedIterator' in str(type(list_GMS_tiles)):
            list_GMS_tiles = list(list_GMS_tiles)

        # copy all attributes except of array attributes
        tile1 = list_GMS_tiles[0]
696
697
        [setattr(self, i, getattr(tile1, i)) for i in tile1.__dict__
         if not callable(getattr(tile1, i)) and not isinstance(getattr(tile1, i), (np.ndarray, GeoArray))]
698
699

        # MERGE ARRAY-ATTRIBUTES
700
        list_arraynames = [i for i in tile1.__dict__ if not callable(getattr(tile1, i)) and
701
                           isinstance(getattr(tile1, i), (np.ndarray, GeoArray))]
702
703
        list_arraynames = ['_arr'] + [i for i in list_arraynames if
                                      i != '_arr']  # list must start with _arr, otherwise setters will not work
704
705
706
707

        for arrname in list_arraynames:
            samplearray = getattr(tile1, arrname)
            assert isinstance(samplearray, (np.ndarray, GeoArray)), \
708
                'Received a %s object for attribute %s. Expected a numpy array or an instance of GeoArray.' \
709
                % (type(samplearray), arrname)
710
711
            is_3d = samplearray.ndim == 3
            bands = (samplearray.shape[2],) if is_3d else ()  # dynamic -> works for arr, cld_arr,...
712
713
714
715
            target_shape = tuple(self.shape_fullArr[:2]) + bands
            target_dtype = samplearray.dtype
            merged_array = self._numba_array_merger(list_GMS_tiles, arrname, target_shape, target_dtype)

716
717
            setattr(self, arrname if not arrname.startswith('_') else arrname[1:],
                    merged_array)  # use setters if possible
718
719
720
721
            # NOTE: this asserts that each attribute starting with '_' has also a property with a setter!

        # UPDATE ARRAY-DEPENDENT ATTRIBUTES
        self.arr_shape = 'cube'
722
        self.arr_pos = None
723
724
725

        # update MetaObj attributes
        self.meta_odict.update({
726
727
            'samples': self.arr.cols, 'lines': self.arr.rows, 'bands': self.arr.bands,
            'map info': geotransform2mapinfo(self.arr.gt, self.arr.prj), 'coordinate system string': self.arr.prj, })
728
729
730
731

        # calculate data_corners_imXY (mask_nodata is always an array here because get_mapPos always returns an array)
        corners_imYX = calc_FullDataset_corner_positions(
            self.mask_nodata, assert_four_corners=False, algorithm='shapely')
732
        self.trueDataCornerPos = [(YX[1], YX[0]) for YX in corners_imYX]  # [UL, UR, LL, LR]
733
734
735
736
737
738

        # calculate trueDataCornerLonLat
        data_corners_LatLon = pixelToLatLon(self.trueDataCornerPos, geotransform=self.arr.gt, projection=self.arr.prj)
        self.trueDataCornerLonLat = [(YX[1], YX[0]) for YX in data_corners_LatLon]

        # calculate trueDataCornerUTM
739
740
        data_corners_utmYX = pixelToMapYX(self.trueDataCornerPos, geotransform=self.arr.gt,
                                          projection=self.arr.prj)  # FIXME asserts gt in UTM coordinates
741
742
743
744
        self.trueDataCornerUTM = [(YX[1], YX[0]) for YX in data_corners_utmYX]

        return copy.copy(self)

745
746
747
    @staticmethod
    @jit
    def _numba_array_merger(list_GMS_tiles, arrname2merge, target_shape, target_dtype):
Daniel Scheffler's avatar
Daniel Scheffler committed
748
        # type: (list, str, tuple, np.dtype) -> np.ndarray
749
750
751
752
753
754
755
756
757
        """
        private function, e.g. called by merge_GMS_tiles_to_GMS_obj() in order to fasten array merging

        :param list_GMS_tiles:
        :param arrname2merge:
        :param target_shape:
        :param target_dtype:
        :return:
        """
Daniel Scheffler's avatar
Daniel Scheffler committed
758

759
760
761
762
763
764
765
        out_arr = np.empty(target_shape, dtype=target_dtype)
        for idx, tile in enumerate(list_GMS_tiles):
            rowStart, rowEnd = tile.arr_pos[0]
            colStart, colEnd = tile.arr_pos[1]
            out_arr[rowStart:rowEnd + 1, colStart:colEnd + 1] = getattr(tile, arrname2merge)
        return out_arr

Daniel Scheffler's avatar
Daniel Scheffler committed
766
    def log_for_fullArr_or_firstTile(self, log_msg, subset=None):
767
768
769
770
771
772
773
        """Send a message to the logger only if full array or the first tile is currently processed.
        This function can be called when processing any tile but log message will only be sent from first tile.

        :param log_msg:  the log message to be logged
        :param subset:   subset argument as sent to e.g. DN2TOARadRefTemp that indicates which tile is to be processed.
                         Not needed if self.arr_pos is not None.
        """
Daniel Scheffler's avatar
Daniel Scheffler committed
774

775
776
777
778
        if subset is None and \
            (self.arr_shape == 'cube' or self.arr_pos is None or [self.arr_pos[0][0], self.arr_pos[1][0]] == [0, 0]) or\
                subset == ['cube', None] or (subset and [subset[1][0][0], subset[1][1][0]] == [0, 0]) or \
                hasattr(self, 'logAtThisTile') and getattr(self, 'logAtThisTile'):  # cube or 1st tile
Daniel Scheffler's avatar
Daniel Scheffler committed
779
            self.logger.info(log_msg)
780
781
782
783
        else:
            pass

    def apply_nodata_mask_to_ObjAttr(self, attrname, out_nodata_val=None):
784
        # type: (str,int) -> None
785
        """Applies self.mask_nodata to the specified array attribute by setting all values where mask_nodata is 0 to the
786
787
788
789
790
791
792
        given nodata value.

        :param attrname:         The attribute to apply the nodata mask to. Must be an array attribute or
                                 a string path to a previously saved ENVI-file.
        :param out_nodata_val:   set the values of the given attribute to this value.
        """

793
        assert hasattr(self, attrname)
794

795
        if getattr(self, attrname) is not None:
796

797
798
799
            if isinstance(getattr(self, attrname), str):
                update_spec_vals = True if attrname == 'arr' else False
                self.apply_nodata_mask_to_saved_ENVIfile(getattr(self, attrname), out_nodata_val, update_spec_vals)
800
            else:
801
                assert isinstance(getattr(self, attrname), (np.ndarray, GeoArray)), \
802
                    'L1A_obj.%s must be a numpy array or an instance of GeoArray. Got type %s.' \
803
804
                    % (attrname, type(getattr(self, attrname)))
                assert hasattr(self, 'mask_nodata') and self.mask_nodata is not None
805

806
                self.log_for_fullArr_or_firstTile('Applying nodata mask to L1A_object.%s...' % attrname)
807

808
                nodata_val = out_nodata_val if out_nodata_val else \
809
                    DEF_D.get_outFillZeroSaturated(getattr(self, attrname).dtype)[0]
810
                getattr(self, attrname)[self.mask_nodata.astype(np.int8) == 0] = nodata_val
811

812
813
                if attrname == 'arr':
                    self.MetaObj.spec_vals['fill'] = nodata_val
814
815
816
817
818
819

    def build_combined_masks_array(self):
        # type: () -> dict
        """Generates self.masks attribute (unsigned integer 8bit) from by concatenating all masks included in GMS obj.
        The corresponding metadata is assigned to L1A_obj.masks_meta. Empty mask attributes are skipped."""

820
        arrays2combine = [aN for aN in ['mask_nodata', 'mask_clouds']
821
                          if hasattr(self, aN) and isinstance(getattr(self, aN), (GeoArray, np.ndarray))]
822
823
        if arrays2combine:
            self.log_for_fullArr_or_firstTile('Combining masks...')
824
825

            def get_data(arrName): return getattr(self, arrName).astype(np.uint8)[:, :, None]
826
827

            for aN in arrays2combine:
828
                if False in np.equal(getattr(self, aN), getattr(self, aN).astype(np.uint8)):
829
830
831
                    warnings.warn('Some pixel values of attribute %s changed during data type '
                                  'conversion within build_combined_masks_array().')

832
            # set self.masks
833
834
835
            self.masks = get_data(arrays2combine[0]) if len(arrays2combine) == 1 else \
                np.concatenate([get_data(aN) for aN in arrays2combine], axis=2)
            self.masks.bandnames = arrays2combine  # set band names of GeoArray (allows later indexing by band name)
836

837
            # set self.masks_meta
838
            nodataVal = DEF_D.get_outFillZeroSaturated(self.masks.dtype)[0]
839
            self.masks_meta = {'map info': self.MetaObj.map_info, 'coordinate system string': self.MetaObj.projection,
840
841
                               'bands': len(arrays2combine), 'band names': arrays2combine,
                               'data ignore value': nodataVal}
842
843

            return {'desc': 'masks', 'row_start': 0, 'row_end': self.shape_fullArr[0],
844
                    'col_start': 0, 'col_end': self.shape_fullArr[1], 'data': self.masks}  # usually not needed
845
846

    def apply_nodata_mask_to_saved_ENVIfile(self, path_saved_ENVIhdr, custom_nodata_val=None, update_spec_vals=False):
847
        # type: (str,int,bool) -> None
848
849
        """Applies self.mask_nodata to a saved ENVI file with the same X/Y dimensions like self.mask_nodata by setting all
         values where mask_nodata is 0 to the given nodata value.
850
851
852
853
854
855
856
857

        :param path_saved_ENVIhdr:  <str> The path of the ENVI file to apply the nodata mask to.
        :param custom_nodata_val:   <int> set the values of the given attribute to this value.
        :param update_spec_vals:    <bool> whether to update self.MetaObj.spec_vals['fill']
        """

        self.log_for_fullArr_or_firstTile('Applying nodata mask to saved ENVI file...')
        assert os.path.isfile(path_saved_ENVIhdr)
858
859
860
        assert hasattr(self, 'mask_nodata') and self.mask_nodata is not None
        if not path_saved_ENVIhdr.endswith('.hdr') and os.path.isfile(os.path.splitext(path_saved_ENVIhdr)[0] + '.hdr'):
            path_saved_ENVIhdr = os.path.splitext(path_saved_ENVIhdr)[0] + '.hdr'
861
        if custom_nodata_val is None:
862
            dtype_IDL = int(INP_R.read_ENVIhdr_to_dict(path_saved_ENVIhdr)['data type'])
863
            nodata_val = DEF_D.get_outFillZeroSaturated(DEF_D.dtype_lib_IDL_Python[dtype_IDL])[0]
864
865
        else:
            nodata_val = custom_nodata_val
866
        FileObj = spectral.open_image(path_saved_ENVIhdr)
867
        File_memmap = FileObj.open_memmap(writable=True)
868
        File_memmap[self.mask_nodata == 0] = nodata_val
869
870
        if update_spec_vals:
            self.MetaObj.spec_vals['fill'] = nodata_val
871
872

    def combine_tiles_to_ObjAttr(self, tiles, target_attr):
873
        # type: (list,str) -> None
874
        """Combines tiles, e.g. produced by L1A_P.L1A_object.DN2TOARadRefTemp() to a single attribute.
875
        If CFG.inmem_serialization is False, the produced attribute is additionally written to disk.
876
877
878
879
880

        :param tiles:           <list> a list of dictionaries with the keys 'desc', 'data', 'row_start','row_end',
                                'col_start' and 'col_end'
        :param target_attr:     <str> the name of the attribute to be produced
        """
Daniel Scheffler's avatar
Daniel Scheffler committed
881

882
        warnings.warn("'combine_tiles_to_ObjAttr' is deprecated.", DeprecationWarning)
883
        assert tiles[0] and isinstance(tiles, list) and isinstance(tiles[0], dict), \
884
885
886
            "The 'tiles' argument has to be list of dictionaries with the keys 'desc', 'data', 'row_start'," \
            "'row_end', 'col_start' and 'col_end'."
        self.logger.info("Building L1A attribute '%s' by combining given tiles..." % target_attr)
887
888
        tiles = [tiles] if not isinstance(tiles, list) else tiles
        sampleTile = dict(tiles[0])
889
890
        target_shape = self.shape_fullArr if len(sampleTile['data'].shape) == 3 else self.shape_fullArr[:2]
        setattr(self, target_attr, np.empty(target_shape, dtype=sampleTile['data'].dtype))
891
        for tile in tiles:  # type: dict
892
893
894
895
896
            rS, rE, cS, cE = tile['row_start'], tile['row_end'], tile['col_start'], tile['col_end']
            if len(target_shape) == 3:
                getattr(self, target_attr)[rS:rE + 1, cS:cE + 1, :] = tile['data']
            else:
                getattr(self, target_attr)[rS:rE + 1, cS:cE + 1] = tile['data']
897
        if target_attr == 'arr':
898
899
            self.arr_desc = sampleTile['desc']
            self.arr_shape = 'cube' if len(self.arr.shape) == 3 else 'band' if len(self.arr.shape) == 2 else 'unknown'
900

901
            if not CFG.inmem_serialization:
902
                path_radref_file = os.path.join(self.ExtractedFolder, self.baseN + '__' + self.arr_desc)
903
904
905
906
907
908
909
910
911
912
913
                # path_radref_file = os.path.abspath('./testing/out/%s_TOA_Ref' % self.baseN)
                while not os.path.isdir(os.path.dirname(path_radref_file)):
                    try:
                        os.makedirs(os.path.dirname(path_radref_file))
                    except OSError as e:  # maybe not neccessary anymore in python 3
                        if not e.errno == 17:
                            raise
                GEOP.ndarray2gdal(self.arr, path_radref_file, importFile=self.MetaObj.Dataname, direction=3)
                self.MetaObj.Dataname = path_radref_file

    def write_tiles_to_ENVIfile(self, tiles, overwrite=True):
914
        # type: (list,bool) -> None
915
916
917
918
919
920
921
922
        """Writes tiles, e.g. produced by L1A_P.L1A_object.DN2TOARadRefTemp() to a single output ENVI file.

        :param tiles:           <list> a list of dictionaries with the keys 'desc', 'data', 'row_start','row_end',
                                'col_start' and 'col_end'
        :param overwrite:       whether to overwrite files that have been produced earlier
        """

        self.logger.info("Writing tiles '%s' temporarily to disk..." % tiles[0]['desc'])
923
        outpath = os.path.join(self.ExtractedFolder, '%s__%s.%s' % (self.baseN, tiles[0]['desc'], self.outInterleave))
924
925
        if CFG.target_radunit_optical in tiles[0]['desc'] or \
           CFG.target_radunit_thermal in tiles[0]['desc']:
926
            self.meta_odict = self.MetaObj.to_odict()  # important in order to keep geotransform/projection
927
928
929
930
            self.arr_desc = tiles[0]['desc']
            self.arr = outpath
            # self.arr = os.path.abspath('./testing/out/%s_TOA_Ref.bsq' % self.baseN)
            self.MetaObj.Dataname = self.arr
931
            self.arr_shape = \
932
933
                'cube' if len(tiles[0]['data'].shape) == 3 else 'band' if len(
                    tiles[0]['data'].shape) == 2 else 'unknown'
934
935
936
        elif tiles[0]['desc'] == 'masks':
            self.masks = outpath
        elif tiles[0]['desc'] == 'lonlat_arr':
937
938
939
940
941
            # outpath = os.path.join(os.path.abspath('./testing/out/'),'%s__%s.%s'
            #     %(self.baseN, tiles[0]['desc'], self.outInterleave))
            self.lonlat_arr = outpath  # FIXME
        outpath = os.path.splitext(outpath)[0] + '.hdr' if not outpath.endswith('.hdr') else outpath
        out_shape = self.shape_fullArr[:2] + ([tiles[0]['data'].shape[2]] if len(tiles[0]['data'].shape) == 3 else [1])
942
943
        OUT_W.Tiles_Writer(tiles, outpath, out_shape, tiles[0]['data'].dtype, self.outInterleave, self.meta_odict,
                           overwrite=overwrite)
944
945

    def to_MGRS_tiles(self, pixbuffer=10, v=False):
946
        # type: (int) -> self
947
        """Returns a generator object where items represent the MGRS tiles for the GMS object.
948
949
950
951
952

        :param pixbuffer:   <int> a buffer in pixel values used to generate an overlap between the returned MGRS tiles
        :param v:           <bool> verbose mode
        :return:            <list> of MGRS_tile objects
        """
Daniel Scheffler's avatar
Daniel Scheffler committed
953

954
        assert self.arr_shape == 'cube', "Only 'cube' objects can be cut into MGRS tiles. Got %s." % self.arr_shape
955
        self.logger.info('Cutting scene %s (entity ID %s) into MGRS tiles...' % (self.scene_ID, self.entity_ID))