process_controller.py 32.8 KB
Newer Older
1
2
# -*- coding: utf-8 -*-

3
from __future__ import (division, print_function, unicode_literals, absolute_import)
4
5
6

import numpy as np
from pandas import DataFrame
7
8
9
10
import datetime
import os
import time
from itertools import chain
11
import signal
12
import re
Daniel Scheffler's avatar
Daniel Scheffler committed
13
from typing import TYPE_CHECKING
14

15
16
from ..io import output_writer as OUT_W
from ..io import input_reader as INP_R
17
18
19
20
21
from ..misc import database_tools as DB_T
from ..misc import helper_functions as HLP_F
from ..misc.path_generator import path_generator
from ..misc.logging import GMS_logger, shutdown_loggers
from ..algorithms import L1A_P, L1B_P, L1C_P, L2A_P, L2B_P, L2C_P
22
from ..model.metadata import get_LayerBandsAssignment
23
24
from ..model.gms_object import failed_GMS_object
from .pipeline import (L1A_map, L1A_map_1, L1A_map_2, L1A_map_3, L1B_map, L1C_map,
25
                       L2A_map, L2B_map, L2C_map)
26
from ..options.config import set_config, GMS_config
27
from .multiproc import MAP
28
from ..misc.definition_dicts import proc_chain, db_jobs_statistics_def
29

30
31
from py_tools_ds.numeric.array import get_array_tilebounds

32
if TYPE_CHECKING:
Daniel Scheffler's avatar
Daniel Scheffler committed
33
    from collections import OrderedDict  # noqa F401  # flake8 issue
34
35
36
37


__author__ = 'Daniel Scheffler'

38
39

class process_controller(object):
40
    def __init__(self, job_ID, **config_kwargs):
41
        """gms_preprocessing process controller
42

43
44
        :param job_ID:          job ID belonging to a valid database record within table 'jobs'
        :param config_kwargs:   keyword arguments to be passed to gms_preprocessing.set_config()
45
46
47
        """

        # assertions
48
49
        if not isinstance(job_ID, int):
            raise ValueError("'job_ID' must be an integer value. Got %s." % type(job_ID))
50

51
52
53
54
55
56
        # set GMS configuration
        config_kwargs.update(dict(reset_status=True))
        set_config(job_ID, **config_kwargs)
        self.config = GMS_config  # type: GMS_config

        # defaults
57
        self._logger = None
58
        self._DB_job_record = None
59
        self.profiler = None
60
61
62
63
64

        self.failed_objects = []
        self.L1A_newObjects = []
        self.L1B_newObjects = []
        self.L1C_newObjects = []
65
        self.L2A_tiles = []
66
67
68
69
        self.L2B_newObjects = []
        self.L2C_newObjects = []

        self.summary_detailed = None
70
        self.summary_quick = None
71

72
73
        # check if process_controller is executed by debugger
        # isdebugging = 1 if True in [frame[1].endswith("pydevd.py") for frame in inspect.stack()] else False
74
        # if isdebugging:  # override the existing settings in order to get write access everywhere
75
76
        #    pass

77
        # called_from_iPyNb = 1 if 'ipykernel/__main__.py' in sys.argv[0] else 0
78

79
        self.logger.info('Process Controller initialized for job ID %s (comment: %s).'
80
                         % (self.config.ID, self.DB_job_record.comment))
81

82
        if self.config.delete_old_output:
83
84
            self.logger.info('Deleting previously processed data...')
            self.DB_job_record.delete_procdata_of_entire_job(force=True)
85

86
87
88
89
90
    @property
    def logger(self):
        if self._logger and self._logger.handlers[:]:
            return self._logger
        else:
91
92
93
            self._logger = GMS_logger('log__%s' % self.config.ID,
                                      path_logfile=os.path.join(self.config.path_job_logs, '%s.log' % self.config.ID),
                                      log_level=self.config.log_level, append=False)
94
95
96
97
98
99
100
101
102
103
104
105
106
            return self._logger

    @logger.setter
    def logger(self, logger):
        self._logger = logger

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

    @property
107
108
109
110
    def DB_job_record(self):
        if self._DB_job_record:
            return self._DB_job_record
        else:
111
112
            self._DB_job_record = DB_T.GMS_JOB(self.config.conn_database)
            self._DB_job_record.from_job_ID(self.config.ID)
113
            return self._DB_job_record
114

115
116
117
    @DB_job_record.setter
    def DB_job_record(self, value):
        self._DB_job_record = value
118

119
120
121
    @property
    def sceneids_failed(self):
        return [obj.scene_ID for obj in self.failed_objects]
122

123
124
125
    @staticmethod
    def add_local_availability(dataset):
        # TODO revise this function
126
127
128
        # TODO this does not respect that all subsystems of the same scene ID must be available at the same proc level!

        # query the database and get the last written processing level and LayerBandsAssignment
129
        DB_match = DB_T.get_info_from_postgreSQLdb(
130
            GMS_config.conn_database, 'scenes_proc', ['proc_level', 'layer_bands_assignment'],
131
            dict(sceneid=dataset['scene_ID']))
132
133

        # get the corresponding logfile
134
135
        path_logfile = path_generator(
            dataset).get_path_logfile()  # FIXME this always returns the logfile for the subsystem.
136

137
138
        # FIXME -> merged logfiles (L2A+) are ignored
        # FIXME -> for subsystems the highest start procL is L2A
139

140
        def get_AllWrittenProcL_dueLog(path_log):  # TODO replace this by database query + os.path.exists
141
142
            """Returns all processing level that have been successfully written according to logfile."""

143
            if not os.path.exists(path_log):
144
                print("No logfile named '%s' found for %s at %s. Dataset has to be reprocessed."
145
146
147
148
149
150
                      % (os.path.basename(path_log), dataset['entity_ID'], os.path.dirname(path_log)))
                AllWrittenProcL_dueLog = []
            else:
                logfile = open(path_log, 'r').read()
                AllWrittenProcL_dueLog = re.findall(":*(\S*\s*) data successfully saved.", logfile, re.I)
                if not AllWrittenProcL_dueLog:  # AllWrittenProcL_dueLog = []
151
                    print('%s: According to logfile no completely processed data exist at any processing level. '
152
153
154
155
156
                          'Dataset has to be reprocessed.' % dataset['entity_ID'])
                else:
                    AllWrittenProcL_dueLog = HLP_F.sorted_nicely(list(set(AllWrittenProcL_dueLog)))
            return AllWrittenProcL_dueLog

157
        # check if there are not multiple database records for this dataset
158
        if len(DB_match) == 1 or DB_match == [] or DB_match == 'database connection fault':
159
160

            # get all processing level that have been successfully written
161
162
            AllWrittenProcL = get_AllWrittenProcL_dueLog(path_logfile)
            dataset['proc_level'] = None  # default (dataset has to be reprocessed)
163
164

            # loop through all the found proc. levels and find the one that fulfills all requirements
165
            for ProcL in reversed(AllWrittenProcL):
166
167
                if dataset['proc_level']:
                    break  # proc_level found; no further searching for lower proc_levels
168
                assumed_path_GMS_file = '%s_%s.gms' % (os.path.splitext(path_logfile)[0], ProcL)
169
170

                # check if there is also a corresponding GMS_file on disk
171
172
                if os.path.isfile(assumed_path_GMS_file):
                    GMS_file_dict = INP_R.GMSfile2dict(assumed_path_GMS_file)
173
                    target_LayerBandsAssignment = \
174
                        get_LayerBandsAssignment(dict(
175
176
177
178
179
                            image_type=dataset['image_type'],
                            Satellite=dataset['satellite'],
                            Sensor=dataset['sensor'],
                            Subsystem=dataset['subsystem'],
                            proc_level=ProcL,  # must be respected because LBA changes after atm. Corr.
180
                            dataset_ID=dataset['dataset_ID'],
181
182
183
184
                            logger=None), nBands=(1 if dataset['sensormode'] == 'P' else None))

                    # check if the LayerBandsAssignment of the written dataset on disk equals the
                    # desired LayerBandsAssignment
185
                    if target_LayerBandsAssignment == GMS_file_dict['LayerBandsAssignment']:
186
187

                        # update the database record if the dataset could not be found in database
188
                        if DB_match == [] or DB_match == 'database connection fault':
189
190
                            print('The dataset %s is not included in the database of processed data but according to '
                                  'logfile %s has been written successfully. Recreating missing database entry.'
191
192
                                  % (dataset['entity_ID'], ProcL))
                            DB_T.data_DB_updater(GMS_file_dict)
193

194
                            dataset['proc_level'] = ProcL
195
196

                        # if the dataset could be found in database
197
198
                        elif len(DB_match) == 1:
                            try:
199
                                print('Found a matching %s dataset for %s. Processing skipped until %s.'
200
                                      % (ProcL, dataset['entity_ID'], proc_chain[proc_chain.index(ProcL) + 1]))
201
                            except IndexError:
202
                                print('Found a matching %s dataset for %s. Processing already done.'
203
                                      % (ProcL, dataset['entity_ID']))
204

205
206
207
208
                            if DB_match[0][0] == ProcL:
                                dataset['proc_level'] = DB_match[0][0]
                            else:
                                dataset['proc_level'] = ProcL
209

210
                    else:
211
                        print('Found a matching dataset for %s but with a different LayerBandsAssignment. '
212
213
214
215
216
                              'Dataset has to be reprocessed.' % dataset['entity_ID'])
                else:
                    print('%s for dataset %s has been written due to logfile but no corresponding dataset has been '
                          'found.' % (ProcL, dataset['entity_ID']) + ' Searching for lower processing level...'
                          if AllWrittenProcL.index(ProcL) != 0 else '')
217

218
        elif len(DB_match) > 1:
219
            print('According to database there are multiple matches for the dataset %s. Dataset has to be reprocessed.'
220
221
                  % dataset['entity_ID'])
            dataset['proc_level'] = None
222

223
224
225
226
227
        else:
            dataset['proc_level'] = None

        return dataset

228
229
    @staticmethod
    def _is_inMEM(GMS_objects, dataset):
Daniel Scheffler's avatar
Daniel Scheffler committed
230
        # type: (list, OrderedDict) -> bool
231
232
233
234
        """Checks whether a dataset within a dataset list has been processed in the previous processing level.
        :param GMS_objects: <list> a list of GMS objects that has been recently processed
        :param dataset:     <collections.OrderedDict> as generated by L0A_P.get_data_list_of_current_jobID()
        """
235
        # check if the scene ID of the given dataset is in the scene IDs of the previously processed datasets
236
237
238
239
        return dataset['scene_ID'] in [obj.scene_ID for obj in GMS_objects]

    @staticmethod
    def _is_already_present(dataset, procLvl):
240
241
242
243
244
245
        """Checks if the given dataset is already available on disk.

        :param dataset:     <GMS object>
        :param procLvl:     <str> processing level to be checked
        :return:            <bool>
        """
246
247
248
        return HLP_F.proc_level_already_present(dataset['proc_level'], procLvl)

    def _get_processor_data_list(self, procLvl, prevLvl_objects=None):
249
        """Returns a list of datasets that have to be read from disk and then processed by a specific processor.
250
251
252
253
254

        :param procLvl:
        :param prevLvl_objects:
        :return:
        """
255
256
        def is_already_present(dataset):
            return HLP_F.proc_level_already_present(dataset['proc_level'], target_lvl=procLvl)
257
258

        if prevLvl_objects is None:
259
            return [dataset for dataset in self.config.data_list if not is_already_present(dataset)]  # TODO generator?
260
        else:
261
            return [dataset for dataset in self.config.data_list if not is_already_present(dataset) and
262
                    not self._is_inMEM(prevLvl_objects + self.failed_objects, dataset)]
263
264
265
266
267
268
269
270
271
272
273
274
275

    def get_DB_objects(self, procLvl, prevLvl_objects=None, parallLev=None, blocksize=None):
        """
        Returns a list of GMS objects for datasets available on disk that have to be processed by the current processor.

        :param procLvl:         <str> processing level oof the current processor
        :param prevLvl_objects: <list> of in-mem GMS objects produced by the previous processor
        :param parallLev:       <str> parallelization level ('scenes' or 'tiles')
                                -> defines if full cubes or blocks are to be returned
        :param blocksize:       <tuple> block size in case blocks are to be returned, e.g. (2000,2000)
        :return:
        """
        # TODO get prevLvl_objects automatically from self
276
        if procLvl == 'L1A':
277
278
279
            return []
        else:
            # handle input parameters
280
            parallLev = parallLev if parallLev else self.config.parallelization_level
281
            blocksize = blocksize if blocksize else self.config.tiling_block_size_XY
282
            prevLvl = proc_chain[proc_chain.index(procLvl) - 1]  # TODO replace by enum
283
284

            # get GMSfile list
285
            dataset_dicts = self._get_processor_data_list(procLvl, prevLvl_objects)
286
287
288
289
290
            GMSfile_list_prevLvl_inDB = INP_R.get_list_GMSfiles(dataset_dicts, prevLvl)

            # create GMS objects from disk with respect to parallelization level and block size
            if parallLev == 'scenes':
                # get input parameters for creating GMS objects as full cubes
291
                work = [[GMS, ['cube', None]] for GMS in GMSfile_list_prevLvl_inDB]
292
293
            else:
                # define tile positions and size
294
                def get_tilepos_list(GMSfile):
295
296
                    return get_array_tilebounds(array_shape=INP_R.GMSfile2dict(GMSfile)['shape_fullArr'],
                                                tile_shape=blocksize)
297
298
299

                # get input parameters for creating GMS objects as blocks
                work = [[GMSfile, ['block', tp]] for GMSfile in GMSfile_list_prevLvl_inDB
300
                        for tp in get_tilepos_list(GMSfile)]
301

302
303
304
305
            # create GMS objects for the found files on disk
            # NOTE: DON'T multiprocess that with MAP(GMS_object(*initargs).from_disk, work)
            # in case of multiple subsystems GMS_object(*initargs) would always point to the same object in memory
            # -> subsystem attribute will be overwritten each time
306
            def init_GMS_obj(): return HLP_F.parentObjDict[prevLvl](*HLP_F.initArgsDict[prevLvl])
307
308
            DB_objs = [init_GMS_obj().from_disk(tuple_GMS_subset=w) for w in work]  # init

309
310
311
312
313
            if DB_objs:
                DB_objs = list(chain.from_iterable(DB_objs)) if list in [type(i) for i in DB_objs] else list(DB_objs)

            return DB_objs

314
315
316
317
    def run_all_processors(self, custom_data_list=None):
        """
        Run all processors at once.
        """
318

319
        signal.signal(signal.SIGINT, self.stop)  # enable clean shutdown possibility
320

321
        # noinspection PyBroadException
322
        try:
323
            if self.config.profiling:
324
325
326
327
                from pyinstrument import Profiler
                self.profiler = Profiler()  # or Profiler(use_signal=False), see below
                self.profiler.start()

328
            self.logger.info('Execution of entire GeoMultiSens pre-processing chain started for job ID %s...'
329
                             % self.config.ID)
330
            self.DB_job_record.reset_job_progress()  # updates attributes of DB_job_record and related DB entry
331
            self.config.status = 'running'
332
            self.update_DB_job_record()  # TODO implement that into job.status.setter
333
334
335
336
337

            self.failed_objects = []

            # get list of datasets to be processed
            if custom_data_list:
338
                self.config.data_list = custom_data_list
339
340

            # add local availability
341
342
            self.config.data_list = MAP(self.add_local_availability, self.config.data_list)
            self.update_DB_job_statistics(self.config.data_list)
343
344
345
346
347
348
349
350
351
352
353
354

            self.L1A_processing()
            self.L1B_processing()
            self.L1C_processing()
            self.L2A_processing()
            self.L2B_processing()
            self.L2C_processing()

            # create summary
            self.create_job_summary()

            self.logger.info('Execution finished.')
355
            # TODO implement failed_with_warnings:
356
357
358
359
            self.config.status = 'finished' if not self.failed_objects else 'finished_with_errors'
            self.config.end_time = datetime.datetime.now()
            self.config.computation_time = self.config.end_time - self.config.start_time
            self.logger.info('Time for execution: %s' % self.config.computation_time)
360
361
362
363

            # update database entry of current job
            self.update_DB_job_record()

364
            if self.config.profiling:
365
366
367
368
369
                self.profiler.stop()
                print(self.profiler.output_text(unicode=True, color=True))

            shutdown_loggers()

370
        except Exception:  # noqa E722  # bare except
371
            if self.config.profiling:
372
373
374
                self.profiler.stop()
                print(self.profiler.output_text(unicode=True, color=True))

375
            self.config.status = 'failed'
376
377
            self.update_DB_job_record()

378
            if not self.config.disable_exception_handler:
379
                self.logger.error('Execution failed with an error:', exc_info=True)
380
381
                shutdown_loggers()
            else:
382
                self.logger.error('Execution failed with an error:')
383
384
                shutdown_loggers()
                raise
385

386
387
    def stop(self, signum, frame):
        """Interrupt the running process controller gracefully."""
388

389
        self.config.status = 'canceled'
390
391
        self.update_DB_job_record()

392
        self.logger.warning('Process controller stopped by user.')
393
394
        del self.logger
        shutdown_loggers()
395

396
        raise KeyboardInterrupt  # terminate execution and show traceback
397

398
399
400
401
    def benchmark(self):
        """
        Run a benchmark.
        """
402
        data_list_bench = self.config.data_list
403
404
405
406
        for count_datasets in range(len(data_list_bench)):
            t_processing_all_runs, t_IO_all_runs = [], []
            for count_run in range(10):
                current_data_list = data_list_bench[0:count_datasets + 1]
407
408
                if os.path.exists(self.config.path_database):
                    os.remove(self.config.path_database)
409
410
411
412
413
414
415
416
417
418
                t_start = time.time()
                self.run_all_processors(current_data_list)
                t_processing_all_runs.append(time.time() - t_start)
                t_IO_all_runs.append(globals()['time_IO'])

            assert current_data_list, 'Empty data list.'
            OUT_W.write_global_benchmark_output(t_processing_all_runs, t_IO_all_runs, current_data_list)

    def L1A_processing(self):
        """
419
        Run Level 1A processing: Data import and metadata homogenization
420
        """
421
        if self.config.exec_L1AP[0]:
422
            self.logger.info('\n\n##### Level 1A Processing started - raster format and metadata homogenization ####\n')
423

424
425
            datalist_L1A_P = self._get_processor_data_list('L1A')

426
            if self.config.parallelization_level == 'scenes':
427
                # map
428
                L1A_resObjects = MAP(L1A_map, datalist_L1A_P, CPUs=12)
429
            else:  # tiles
430
431
                all_L1A_tiles_map1 = MAP(L1A_map_1, datalist_L1A_P,
                                         flatten_output=True)  # map_1 # merge results to new list of splits
432

433
434
435
                L1A_obj_tiles = MAP(L1A_map_2, all_L1A_tiles_map1)  # map_2
                grouped_L1A_Tiles = HLP_F.group_objects_by_attributes(
                    L1A_obj_tiles, 'scene_ID', 'subsystem')  # group results
436

437
                L1A_objects = MAP(L1A_P.L1A_object().from_tiles, grouped_L1A_Tiles)  # reduce
438

439
                L1A_resObjects = MAP(L1A_map_3, L1A_objects)  # map_3
440

441
            self.L1A_newObjects = [obj for obj in L1A_resObjects if isinstance(obj, L1A_P.L1A_object)]
442
            self.failed_objects += [obj for obj in L1A_resObjects if isinstance(obj, failed_GMS_object) and
443
444
445
446
447
448
                                    obj.scene_ID not in self.sceneids_failed]

        return self.L1A_newObjects

    def L1B_processing(self):
        """
449
        Run Level 1B processing: calculation of geometric shifts
450
451
452
453
        """
        # TODO implement check for running spatial index mediator server
        # run on full cubes

454
        if self.config.exec_L1BP[0]:
455
            self.logger.info('\n\n####### Level 1B Processing started - detection of geometric displacements #######\n')
456

457
458
            L1A_DBObjects = self.get_DB_objects('L1B', self.L1A_newObjects, parallLev='scenes')
            L1A_Instances = self.L1A_newObjects + L1A_DBObjects  # combine newly and earlier processed L1A data
459

460
            L1B_resObjects = MAP(L1B_map, L1A_Instances)
461

462
463
464
            self.L1B_newObjects = [obj for obj in L1B_resObjects if isinstance(obj, L1B_P.L1B_object)]
            self.failed_objects += [obj for obj in L1B_resObjects if isinstance(obj, failed_GMS_object) and
                                    obj.scene_ID not in self.sceneids_failed]
465
466
467
468
469

        return self.L1B_newObjects

    def L1C_processing(self):
        """
470
        Run Level 1C processing: atmospheric correction
471
        """
472
        if self.config.exec_L1CP[0]:
473
            self.logger.info('\n\n############## Level 1C Processing started - atmospheric correction ##############\n')
474

475
            if self.config.parallelization_level == 'scenes':
476
477
478
479
                L1B_DBObjects = self.get_DB_objects('L1C', self.L1B_newObjects)
                L1B_Instances = self.L1B_newObjects + L1B_DBObjects  # combine newly and earlier processed L1B data

                # group by scene ID (all subsystems belonging to the same scene ID must be processed together)
480
                grouped_L1B_Instances = HLP_F.group_objects_by_attributes(L1B_Instances, 'scene_ID')
481

482
483
                L1C_resObjects = MAP(L1C_map, grouped_L1B_Instances, flatten_output=True,
                                     CPUs=15)  # FIXME CPUs set to 15 for testing
484

485
            else:  # tiles
486
487
                raise NotImplementedError("Tiled processing is not yet completely implemented for L1C processor. Use "
                                          "parallelization level 'scenes' instead!")
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
                # blocksize = (5000, 5000)
                # """if newly processed L1A objects are present: cut them into tiles"""
                # L1B_newTiles = []
                # if self.L1B_newObjects:
                #     tuples_obj_blocksize = [(obj, blocksize) for obj in self.L1B_newObjects]
                #     L1B_newTiles = MAP(HLP_F.cut_GMS_obj_into_blocks, tuples_obj_blocksize, flatten_output=True)
                #
                # """combine newly and earlier processed L1B data"""
                # L1B_newDBTiles = self.get_DB_objects('L1C', self.L1B_newObjects, blocksize=blocksize)
                # L1B_tiles = L1B_newTiles + L1B_newDBTiles
                #
                # # TODO merge subsets of S2/Aster in order to provide all bands for atm.correction
                # L1C_tiles = MAP(L1C_map, L1B_tiles)
                # grouped_L1C_Tiles = \
                #     HLP_F.group_objects_by_attributes(L1C_tiles, 'scene_ID', 'subsystem')  # group results
                # [L1C_tiles_group[0].delete_tempFiles() for L1C_tiles_group in grouped_L1C_Tiles]
                # L1C_resObjects = MAP(L1C_P.L1C_object().from_tiles, grouped_L1C_Tiles)  # reduce

            self.L1C_newObjects = [obj for obj in L1C_resObjects if isinstance(obj, L1C_P.L1C_object)]
507
            self.failed_objects += [obj for obj in L1C_resObjects if isinstance(obj, failed_GMS_object) and
508
509
510
511
512
513
                                    obj.scene_ID not in self.sceneids_failed]

        return self.L1C_newObjects

    def L2A_processing(self):
        """
514
        Run Level 2A processing: geometric homogenization
515
        """
516
        if self.config.exec_L2AP[0]:
517
518
            self.logger.info(
                '\n\n#### Level 2A Processing started - shift correction / geometric homogenization ####\n')
519

520
            """combine newly and earlier processed L1C data"""
521
522
            L1C_DBObjects = self.get_DB_objects('L2A', self.L1C_newObjects, parallLev='scenes')
            L1C_Instances = self.L1C_newObjects + L1C_DBObjects  # combine newly and earlier processed L1C data
523
524
525
526

            # group by scene ID (all subsystems belonging to the same scene ID must be processed together)
            grouped_L1C_Instances = HLP_F.group_objects_by_attributes(L1C_Instances, 'scene_ID')

527
            L2A_resTiles = MAP(L2A_map, grouped_L1C_Instances, flatten_output=True)
528

529
            self.L2A_tiles = [obj for obj in L2A_resTiles if isinstance(obj, L2A_P.L2A_object)]
530
            self.failed_objects += [obj for obj in L2A_resTiles if isinstance(obj, failed_GMS_object) and
531
532
533
534
535
536
                                    obj.scene_ID not in self.sceneids_failed]

        return self.L2A_tiles

    def L2B_processing(self):
        """
537
        Run Level 2B processing: spectral homogenization
538
        """
539
        if self.config.exec_L2BP[0]:
540
            self.logger.info('\n\n############# Level 2B Processing started - spectral homogenization ##############\n')
541

542
            if self.config.parallelization_level == 'scenes':
543
                # don't know if scenes makes sense in L2B processing because full objects are very big!
544
                """if newly processed L2A objects are present: merge them to scenes"""
545
546
                grouped_L2A_Tiles = HLP_F.group_objects_by_attributes(self.L2A_tiles, 'scene_ID')  # group results
                # reduce # will be too slow because it has to pickle back really large L2A_newObjects
547
                # L2A_newObjects  = MAP(HLP_F.merge_GMS_tiles_to_GMS_obj, grouped_L2A_Tiles)
548
                L2A_newObjects = [L2A_P.L2A_object().from_tiles(tileList) for tileList in grouped_L2A_Tiles]
549

550
                """combine newly and earlier processed L2A data"""
551
552
                L2A_DBObjects = self.get_DB_objects('L2B', self.L2A_tiles)
                L2A_Instances = L2A_newObjects + L2A_DBObjects  # combine newly and earlier processed L2A data
553

554
                L2B_resObjects = MAP(L2B_map, L2A_Instances)
555
556

            else:  # tiles
557
                L2A_newTiles = self.L2A_tiles  # tiles have the block size specified in L2A_map_2
558
559

                """combine newly and earlier processed L2A data"""
560
561
562
                blocksize = (2048, 2048)  # must be equal to the blocksize of L2A_newTiles specified in L2A_map_2
                L2A_newDBTiles = self.get_DB_objects('L2B', self.L2A_tiles, blocksize=blocksize)
                L2A_tiles = L2A_newTiles + L2A_newDBTiles
563

564
                L2B_tiles = MAP(L2B_map, L2A_tiles)
565
566

                grouped_L2B_Tiles = \
567
568
                    HLP_F.group_objects_by_attributes(L2B_tiles,
                                                      'scene_ID')  # group results # FIXME nötig an dieser Stelle?
569
570
                [L2B_tiles_group[0].delete_tempFiles() for L2B_tiles_group in grouped_L2B_Tiles]

571
                L2B_resObjects = [L2B_P.L2B_object().from_tiles(tileList) for tileList in grouped_L2B_Tiles]
572

573
            self.L2B_newObjects = [obj for obj in L2B_resObjects if isinstance(obj, L2B_P.L2B_object)]
574
            self.failed_objects += [obj for obj in L2B_resObjects if isinstance(obj, failed_GMS_object) and
575
576
577
578
579
580
                                    obj.scene_ID not in self.sceneids_failed]

        return self.L2B_newObjects

    def L2C_processing(self):
        """
581
        Run Level 2C processing: accurracy assessment and MGRS tiling
582
        """
583
        # FIXME only parallelization_level == 'scenes' implemented
584
        if self.config.exec_L2CP[0]:
585
            self.logger.info('\n\n########## Level 2C Processing started - calculation of quality layers ###########\n')
586

587
            """combine newly and earlier processed L2A data"""
588
589
            L2B_DBObjects = self.get_DB_objects('L2C', self.L2B_newObjects, parallLev='scenes')
            L2B_Instances = self.L2B_newObjects + L2B_DBObjects  # combine newly and earlier processed L2A data
590

591
            L2C_resObjects = MAP(L2C_map, L2B_Instances, CPUs=8)  # FIXME 8 workers due to heavy IO
592
            # FIXME in case of inmem_serialization mode results are too big to be back-pickled
593
            self.L2C_newObjects = [obj for obj in L2C_resObjects if isinstance(obj, L2C_P.L2C_object)]
594
            self.failed_objects += [obj for obj in L2C_resObjects if isinstance(obj, failed_GMS_object) and
595
596
597
598
599
600
601
602
                                    obj.scene_ID not in self.sceneids_failed]

        return self.L2C_newObjects

    def update_DB_job_record(self):
        """
        Update the database records of the current job (table 'jobs').
        """
603
        # TODO move this method to config.Job
604
605
        # update 'failed_sceneids' column of job record within jobs table
        sceneids_failed = list(set([obj.scene_ID for obj in self.failed_objects]))
606
        DB_T.update_records_in_postgreSQLdb(
607
            self.config.conn_database, 'jobs',
608
            {'failed_sceneids': sceneids_failed,  # update 'failed_sceneids' column
609
610
611
             'finishtime': self.config.end_time,  # add job finish timestamp
             'status': self.config.status},  # update 'job_status' column
            {'id': self.config.ID})
612

613
614
615
616
617
    def update_DB_job_statistics(self, usecase_datalist):
        """
        Update job statistics of the running job in the database.
        """
        # TODO move this method to config.Job
618
        already_updated_IDs = []
619
        for ds in usecase_datalist:
620
621
            if ds['proc_level'] is not None and ds['scene_ID'] not in already_updated_IDs:
                # update statistics column of jobs table
622
                DB_T.increment_decrement_arrayCol_in_postgreSQLdb(
623
                    self.config.conn_database, 'jobs', 'statistics', cond_dict={'id': self.config.ID},
624
625
626
                    idx_val2decrement=db_jobs_statistics_def['downloaded'],
                    idx_val2increment=db_jobs_statistics_def[ds['proc_level']])

627
628
629
                # avoid double updating in case of subsystems belonging to the same scene ID
                already_updated_IDs.append(ds['scene_ID'])

630
631
632
633
    def create_job_summary(self):
        """
        Create job success summary
        """
634
635
636

        # get objects with highest requested processing level
        highest_procL_Objs = []
637
        for pL in reversed(proc_chain):
638
            if getattr(self.config, 'exec_%sP' % pL)[0]:
639
                highest_procL_Objs = getattr(self, '%s_newObjects' % pL) if pL != 'L2A' else self.L2A_tiles
640
641
                break

642
643
644
645
        gms_objects2summarize = highest_procL_Objs + self.failed_objects
        if gms_objects2summarize:
            # create summaries
            detailed_JS, quick_JS = get_job_summary(gms_objects2summarize)
646
647
648
            detailed_JS.to_excel(os.path.join(self.config.path_job_logs, '%s_summary.xlsx' % self.config.ID))
            detailed_JS.to_csv(os.path.join(self.config.path_job_logs, '%s_summary.csv' % self.config.ID), sep='\t')
            self.logger.info('\nQUICK JOB SUMMARY (ID %s):\n' % self.config.ID + quick_JS.to_string())
649
650

            self.summary_detailed = detailed_JS
651
            self.summary_quick = quick_JS
652
653
654
655
656

        else:
            # TODO implement check if proc level with lowest procL has to be processed at all (due to job.exec_L1X)
            # TODO otherwise it is possible that get_job_summary receives an empty list
            self.logger.warning("Job summary skipped because get_job_summary() received an empty list of GMS objects.")
657
658
659
660
661
662

    def clear_lists_procObj(self):
        self.failed_objects = []
        self.L1A_newObjects = []
        self.L1B_newObjects = []
        self.L1C_newObjects = []
663
        self.L2A_tiles = []
664
        self.L2B_newObjects = []
665
666
667
668
669
        self.L2C_newObjects = []


def get_job_summary(list_GMS_objects):
    # get detailed job summary
670
671
    DJS_cols = ['GMS_object', 'scene_ID', 'entity_ID', 'satellite', 'sensor', 'subsystem', 'image_type', 'proc_level',
                'arr_shape', 'arr_pos', 'failedMapper', 'ExceptionType', 'ExceptionValue', 'ExceptionTraceback']
672
673
674
675
    DJS = DataFrame(columns=DJS_cols)
    DJS['GMS_object'] = list_GMS_objects

    for col in DJS_cols[1:]:
676
677
        def get_val(obj): return getattr(obj, col) if hasattr(obj, col) else None
        DJS[col] = list(DJS['GMS_object'].map(get_val))
678
679

    del DJS['GMS_object']
680
    DJS = DJS.sort_values(by=['satellite', 'sensor', 'entity_ID'])
681
682

    # get quick job summary
683
684
685
686
    QJS = DataFrame(columns=['satellite', 'sensor', 'count', 'proc_successfully', 'proc_failed'])
    all_sat, all_sen = zip(*[i.split('__') for i in (np.unique(DJS['satellite'] + '__' + DJS['sensor']))])
    QJS['satellite'] = all_sat
    QJS['sensor'] = all_sen
687
    # count objects with the same satellite/sensor/sceneid combination
688
689
    QJS['count'] = [len(DJS[(DJS['satellite'] == sat) & (DJS['sensor'] == sen)]['scene_ID'].unique())
                    for sat, sen in zip(all_sat, all_sen)]
690
    QJS['proc_successfully'] = [len(DJS[(DJS['satellite'] == sat) &
691
692
                                        (DJS['sensor'] == sen) &
                                        (DJS['failedMapper'].isnull())]['scene_ID'].unique())
693
                                for sat, sen in zip(all_sat, all_sen)]
694
    QJS['proc_failed'] = QJS['count'] - QJS['proc_successfully']
695
696
    QJS = QJS.sort_values(by=['satellite', 'sensor'])
    return DJS, QJS