-
Notifications
You must be signed in to change notification settings - Fork 9
/
solweig_algorithm.py
1319 lines (1164 loc) · 65.2 KB
/
solweig_algorithm.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
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
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
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
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
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
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
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
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
509
510
511
512
513
514
515
516
517
518
519
520
521
522
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
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
860
861
862
863
864
865
866
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
897
898
899
900
901
902
903
904
905
906
907
908
909
910
911
912
913
914
915
916
917
918
919
920
921
922
923
924
925
926
927
928
929
930
931
932
933
934
935
936
937
938
939
940
941
942
943
944
945
946
947
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969
970
971
972
973
974
975
976
977
978
979
980
981
982
983
984
985
986
987
988
989
990
991
992
993
994
995
996
997
998
999
1000
# -*- coding: utf-8 -*-
"""
/***************************************************************************
ProcessingUMEP
A QGIS plugin
UMEP for processing toolbox
Generated by Plugin Builder: http://g-sherman.github.io/Qgis-Plugin-Builder/
-------------------
begin : 2020-04-02
copyright : (C) 2020 by Fredrik Lindberg
email : fredrikl@gvc.gu.se
***************************************************************************/
/***************************************************************************
* *
* This program is free software; you can redistribute it and/or modify *
* it under the terms of the GNU General Public License as published by *
* the Free Software Foundation; either version 2 of the License, or *
* (at your option) any later version. *
* *
***************************************************************************/
"""
__author__ = 'Fredrik Lindberg'
__date__ = '2020-04-02'
__copyright__ = '(C) 2020 by Fredrik Lindberg'
# This will get replaced with a git SHA1 when you do a git archive
__revision__ = '$Format:%H$'
from qgis.PyQt.QtCore import QCoreApplication, QDate, QTime, Qt, QVariant
from qgis.core import (QgsProcessing,
QgsProcessingAlgorithm,
QgsProcessingParameterString,
QgsProcessingParameterBoolean,
QgsProcessingParameterNumber,
QgsProcessingParameterFolderDestination,
QgsProcessingParameterRasterDestination,
QgsProcessingParameterFileDestination,
QgsProcessingParameterFile,
QgsProcessingException,
QgsProcessingParameterDefinition,
QgsProcessingParameterEnum,
QgsProcessingParameterFeatureSource,
QgsProcessingParameterField,
QgsProcessingParameterRasterLayer,
QgsVectorLayer)
from processing.gui.wrappers import WidgetWrapper
from qgis.PyQt.QtWidgets import QDateEdit, QTimeEdit
import numpy as np
from osgeo import gdal, osr
from osgeo.gdalconst import *
import os
from qgis.PyQt.QtGui import QIcon
import inspect
from pathlib import Path, PurePath
from ..util.misc import get_ders, saveraster
import zipfile
from osgeo.gdalconst import *
from ..util.SEBESOLWEIGCommonFiles.Solweig_v2015_metdata_noload import Solweig_2015a_metdata_noload
from ..util.SEBESOLWEIGCommonFiles import Solweig_v2015_metdata_noload as metload
from ..util.SEBESOLWEIGCommonFiles.clearnessindex_2013b import clearnessindex_2013b
from ..functions.SOLWEIGpython.Tgmaps_v1 import Tgmaps_v1
from ..functions.SOLWEIGpython import Solweig_2022a_calc_forprocessing as so
from ..functions.SOLWEIGpython import WriteMetadataSOLWEIG
from ..functions.SOLWEIGpython import PET_calculations as p
from ..functions.SOLWEIGpython import UTCI_calculations as utci
from ..functions.SOLWEIGpython.CirclePlotBar import PolarBarPlot
import matplotlib.pyplot as plt
from shutil import copyfile, rmtree
import string
import random
# For "Save necessary rasters for TreePlanter tool"
from shutil import copyfile
class ProcessingSOLWEIGAlgorithm(QgsProcessingAlgorithm):
"""
This algorithm is a processing version of SOLWEIG
"""
# Constants used to refer to parameters and outputs. They will be
# used when calling the algorithm from another algorithm, or when
# calling from the QGIS console.
#Spatial data
INPUT_DSM = 'INPUT_DSM'
INPUT_SVF = 'INPUT_SVF'
INPUT_CDSM = 'INPUT_CDSM'
INPUT_TDSM = 'INPUT_TDSM'
INPUT_HEIGHT = 'INPUT_HEIGHT'
INPUT_ASPECT = 'INPUT_ASPECT'
TRANS_VEG = 'TRANS_VEG'
LEAF_START = 'LEAF_START'
LEAF_END = 'LEAF_END'
CONIFER_TREES = 'CONIFER_TREES'
INPUT_THEIGHT = 'INPUT_THEIGHT'
INPUT_LC = 'INPUT_LC'
USE_LC_BUILD = 'USE_LC_BUILD'
INPUT_DEM = 'INPUT_DEM'
SAVE_BUILD = 'SAVE_BUILD'
INPUT_ANISO = 'INPUT_ANISO'
#Enivornmental parameters
ALBEDO_WALLS = 'ALBEDO_WALLS'
ALBEDO_GROUND = 'ALBEDO_GROUND'
EMIS_WALLS = 'EMIS_WALLS'
EMIS_GROUND = 'EMIS_GROUND'
#Tmrt parameters
ABS_S = 'ABS_S'
ABS_L = 'ABS_L'
POSTURE = 'POSTURE'
#Meteorology
INPUT_MET = 'INPUTMET'
ONLYGLOBAL = 'ONLYGLOBAL'
UTC = 'UTC'
#PET parameters
AGE = 'AGE'
ACTIVITY = 'ACTIVITY'
CLO = 'CLO'
WEIGHT = 'WEIGHT'
HEIGHT = 'HEIGHT'
SEX = 'SEX'
SENSOR_HEIGHT = 'SENSOR_HEIGHT'
#Optional settings
# POI = 'POI'
POI_FILE = 'POI_FILE'
POI_FIELD = 'POI_FIELD'
CYL = 'CYL'
#Output
OUTPUT_DIR = 'OUTPUT_DIR'
OUTPUT_TMRT = 'OUTPUT_TMRT'
OUTPUT_LUP = 'OUTPUT_LUP'
OUTPUT_KUP = 'OUTPUT_KUP'
OUTPUT_KDOWN = 'OUTPUT_KDOWN'
OUTPUT_LDOWN = 'OUTPUT_LDOWN'
OUTPUT_SH = 'OUTPUT_SH'
OUTPUT_TREEPLANTER = 'OUTPUT_TREEPLANTER'
def initAlgorithm(self, config):
#spatial
self.addParameter(QgsProcessingParameterRasterLayer(self.INPUT_DSM,
self.tr('Building and ground Digital Surface Model (DSM)'), None, optional=False))
self.addParameter(QgsProcessingParameterFile(self.INPUT_SVF,
self.tr('Sky View Factor grids (.zip)'), extension='zip'))
self.addParameter(QgsProcessingParameterRasterLayer(self.INPUT_HEIGHT,
self.tr('Wall height raster'), '', optional=False))
self.addParameter(QgsProcessingParameterRasterLayer(self.INPUT_ASPECT,
self.tr('Wall aspect raster'), '', optional=False))
self.addParameter(QgsProcessingParameterRasterLayer(self.INPUT_CDSM,
self.tr('Vegetation Canopy DSM'), '', optional=True))
self.addParameter(QgsProcessingParameterNumber(self.TRANS_VEG,
self.tr('Transmissivity of light through vegetation (%):'),
QgsProcessingParameterNumber.Integer,
QVariant(3), True, minValue=0, maxValue=100))
self.addParameter(QgsProcessingParameterNumber(self.LEAF_START,
self.tr('First day of year with leaves on trees (if deciduous)'), QgsProcessingParameterNumber.Integer,
QVariant(97), False, minValue=0, maxValue=366))
self.addParameter(QgsProcessingParameterNumber(self.LEAF_END,
self.tr('Last day of year with leaves on trees (if deciduous)'), QgsProcessingParameterNumber.Integer,
QVariant(300), False, minValue=0, maxValue=366))
self.addParameter(QgsProcessingParameterBoolean(self.CONIFER_TREES,
self.tr("Coniferous trees (deciduous default)"), defaultValue=False))
self.addParameter(QgsProcessingParameterRasterLayer(self.INPUT_TDSM,
self.tr('Vegetation Trunk-zone DSM'), '', optional=True))
self.addParameter(QgsProcessingParameterNumber(self.INPUT_THEIGHT,
self.tr("Trunk zone height (percent of Canopy Height). Used if no Vegetation Trunk-zone DSM is loaded"),
QgsProcessingParameterNumber.Double,
QVariant(25.0), optional=True, minValue=0.1, maxValue=99.9))
self.addParameter(QgsProcessingParameterRasterLayer(self.INPUT_LC,
self.tr('UMEP land cover grid'), '', optional=True))
self.addParameter(QgsProcessingParameterBoolean(self.USE_LC_BUILD,
self.tr("Use land cover grid to derive building grid"), defaultValue=False, optional=True))
self.addParameter(QgsProcessingParameterRasterLayer(self.INPUT_DEM,
self.tr('Digital Elevation Model (DEM)'), '', optional=True))
self.addParameter(QgsProcessingParameterBoolean(self.SAVE_BUILD,
self.tr("Save generated building grid"), defaultValue=False, optional=True))
self.addParameter(QgsProcessingParameterFile(self.INPUT_ANISO,
self.tr('Shadow maps used for anisotropic model for sky diffuse and longwave radiation (.npz)'), extension='npz', optional=True))
#Environmental parameters
self.addParameter(QgsProcessingParameterNumber(self.ALBEDO_WALLS,
self.tr('Albedo (walls)'), QgsProcessingParameterNumber.Double,
QVariant(0.20), False, minValue=0, maxValue=1))
self.addParameter(QgsProcessingParameterNumber(self.ALBEDO_GROUND,
self.tr('Albedo (ground)'), QgsProcessingParameterNumber.Double,
QVariant(0.15), False, minValue=0, maxValue=1))
self.addParameter(QgsProcessingParameterNumber(self.EMIS_WALLS,
self.tr('Emissivity (walls)'), QgsProcessingParameterNumber.Double,
QVariant(0.90), False, minValue=0, maxValue=1))
self.addParameter(QgsProcessingParameterNumber(self.EMIS_GROUND,
self.tr('Emissivity (ground)'), QgsProcessingParameterNumber.Double,
QVariant(0.95), False, minValue=0, maxValue=1))
#Tmrt parameters
self.addParameter(QgsProcessingParameterNumber(self.ABS_S,
self.tr('Absorption of shortwave radiation of human body'), QgsProcessingParameterNumber.Double,
QVariant(0.70), False, minValue=0, maxValue=1))
self.addParameter(QgsProcessingParameterNumber(self.ABS_L,
self.tr('Absorption of longwave radiation of human body'), QgsProcessingParameterNumber.Double,
QVariant(0.95), False, minValue=0, maxValue=1))
self.addParameter(QgsProcessingParameterEnum(
self.POSTURE, self.tr('Posture of human body'), ['Standing', 'Sitting'], defaultValue=0))
self.addParameter(QgsProcessingParameterBoolean(self.CYL,
self.tr("Consider human as cylinder instead of box"), defaultValue=True))
#Meteorology
self.addParameter(QgsProcessingParameterFile(self.INPUT_MET,
self.tr('Input meteorological file (.txt)'), extension='txt'))
self.addParameter(QgsProcessingParameterBoolean(self.ONLYGLOBAL,
self.tr("Estimate diffuse and direct shortwave radiation from global radiation"), defaultValue=False))
self.addParameter(QgsProcessingParameterNumber(self.UTC,
self.tr('Coordinated Universal Time (UTC) '),
QgsProcessingParameterNumber.Integer,
QVariant(0), False, minValue=-12, maxValue=12))
#ADVANCED PARAMETERS
#POIs for thermal comfort estimations
# poi = QgsProcessingParameterBoolean(self.POI,
# self.tr("Include Point of Interest(s) for thermal comfort calculations (PET and UTCI)"), defaultValue=False)
# poi.setFlags(poi.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
# self.addParameter(poi)
poifile = QgsProcessingParameterFeatureSource(self.POI_FILE,
self.tr('Vector point file including Point of Interest(s) for thermal comfort calculations (PET and UTCI)'), [QgsProcessing.TypeVectorPoint], optional=True)
poifile.setFlags(poifile.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
self.addParameter(poifile)
poi_field = QgsProcessingParameterField(self.POI_FIELD,
self.tr('ID field'),'', self.POI_FILE, QgsProcessingParameterField.Numeric, optional=True)
poi_field.setFlags(poi_field.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
self.addParameter(poi_field)
#PET parameters
age = QgsProcessingParameterNumber(self.AGE, self.tr('Age (yy)'),
QgsProcessingParameterNumber.Integer,
QVariant(35), optional=True, minValue=0, maxValue=120)
age.setFlags(age.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
self.addParameter(age)
act = QgsProcessingParameterNumber(self.ACTIVITY, self.tr('Activity (W)'),
QgsProcessingParameterNumber.Double,
QVariant(80), optional=True, minValue=0, maxValue=1000)
act.setFlags(act.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
self.addParameter(act)
clo = QgsProcessingParameterNumber(self.CLO, self.tr('Clothing (clo)'),
QgsProcessingParameterNumber.Double,
QVariant(0.9), optional=True, minValue=0, maxValue=10)
clo.setFlags(clo.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
self.addParameter(clo)
wei = QgsProcessingParameterNumber(self.WEIGHT, self.tr('Weight (kg)'),
QgsProcessingParameterNumber.Integer,
QVariant(75), optional=True, minValue=0, maxValue=500)
wei.setFlags(wei.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
self.addParameter(wei)
hei = QgsProcessingParameterNumber(self.HEIGHT, self.tr('Height (cm)'),
QgsProcessingParameterNumber.Integer,
QVariant(180), optional=True, minValue=0, maxValue=250)
hei.setFlags(hei.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
self.addParameter(hei)
sex = QgsProcessingParameterEnum(
self.SEX, self.tr('Sex'), ['Male', 'Female'], optional=True, defaultValue=0)
sex.setFlags(sex.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
self.addParameter(sex)
shei = QgsProcessingParameterNumber(self.SENSOR_HEIGHT, self.tr('Height of wind sensor (m agl)'),
QgsProcessingParameterNumber.Double,
QVariant(10), optional=True, minValue=0, maxValue=250)
shei.setFlags(shei.flags() | QgsProcessingParameterDefinition.FlagAdvanced)
self.addParameter(shei)
#OUTPUT
self.addParameter(QgsProcessingParameterBoolean(self.OUTPUT_TMRT,
self.tr("Save Mean Radiant Temperature raster(s)"), defaultValue=True))
self.addParameter(QgsProcessingParameterBoolean(self.OUTPUT_KDOWN,
self.tr("Save Incoming shortwave radiation raster(s)"), defaultValue=False))
self.addParameter(QgsProcessingParameterBoolean(self.OUTPUT_KUP,
self.tr("Save Outgoing shortwave radiation raster(s)"), defaultValue=False))
self.addParameter(QgsProcessingParameterBoolean(self.OUTPUT_LDOWN,
self.tr("Save Incoming longwave radiation raster(s)"), defaultValue=False))
self.addParameter(QgsProcessingParameterBoolean(self.OUTPUT_LUP,
self.tr("Save Outgoing longwave radiation raster(s)"), defaultValue=False))
self.addParameter(QgsProcessingParameterBoolean(self.OUTPUT_SH,
self.tr("Save shadow raster(s)"), defaultValue=False))
self.addParameter(QgsProcessingParameterBoolean(self.OUTPUT_TREEPLANTER,
self.tr("Save necessary raster(s) for the TreePlanter and Spatial TC tools"), defaultValue=False))
self.addParameter(QgsProcessingParameterFolderDestination(self.OUTPUT_DIR,
'Output folder'))
self.plugin_dir = os.path.dirname(__file__)
temp_dir_name = 'temp-' + ''.join(random.choice(string.ascii_uppercase) for _ in range(8))
self.temp_dir = os.path.join(os.path.dirname(self.plugin_dir), temp_dir_name)
def processAlgorithm(self, parameters, context, feedback):
np.seterr(divide='ignore', invalid='ignore')
# InputParameters
dsmlayer = self.parameterAsRasterLayer(parameters, self.INPUT_DSM, context)
transVeg = self.parameterAsDouble(parameters, self.TRANS_VEG, context) / 100.
firstdayleaf = self.parameterAsInt(parameters, self.LEAF_START, context)
lastdayleaf = self.parameterAsInt(parameters, self.LEAF_END, context)
conifer_bool = self.parameterAsBool(parameters, self.CONIFER_TREES, context)
vegdsm = self.parameterAsRasterLayer(parameters, self.INPUT_CDSM, context)
vegdsm2 = self.parameterAsRasterLayer(parameters, self.INPUT_TDSM, context)
lcgrid = self.parameterAsRasterLayer(parameters, self.INPUT_LC, context)
useLcBuild = self.parameterAsBool(parameters, self.USE_LC_BUILD, context)
dem = None
inputSVF = self.parameterAsString(parameters, self.INPUT_SVF, context)
whlayer = self.parameterAsRasterLayer(parameters, self.INPUT_HEIGHT, context)
walayer = self.parameterAsRasterLayer(parameters, self.INPUT_ASPECT, context)
trunkr = self.parameterAsDouble(parameters, self.INPUT_THEIGHT, context)
onlyglobal = self.parameterAsBool(parameters, self.ONLYGLOBAL, context)
utc = self.parameterAsDouble(parameters, self.UTC, context)
inputMet = self.parameterAsString(parameters, self.INPUT_MET, context)
# usePOI = self.parameterAsBool(parameters, self.POI, context)
poilyr = self.parameterAsVectorLayer(parameters, self.POI_FILE, context)
poi_field = None
mbody = None
ht = None
clo = None
age = None
activity = None
sex = None
sensorheight = None
saveBuild = self.parameterAsBool(parameters, self.SAVE_BUILD, context)
demforbuild = 0
folderPathPerez = self.parameterAsString(parameters, self.INPUT_ANISO, context)
poisxy = None
poiname = None
# Other parameters #
absK = self.parameterAsDouble(parameters, self.ABS_S, context)
absL = self.parameterAsDouble(parameters, self.ABS_L, context)
pos = self.parameterAsInt(parameters, self.POSTURE, context)
if self.parameterAsBool(parameters, self.CYL, context):
cyl = 1
else:
cyl = 0
if pos == 0:
Fside = 0.22
Fup = 0.06
height = 1.1
Fcyl = 0.28
else:
Fside = 0.166666
Fup = 0.166666
height = 0.75
Fcyl = 0.2
albedo_b = self.parameterAsDouble(parameters, self.ALBEDO_WALLS, context)
albedo_g = self.parameterAsDouble(parameters, self.ALBEDO_GROUND, context)
ewall = self.parameterAsDouble(parameters, self.EMIS_WALLS, context)
eground = self.parameterAsDouble(parameters, self.EMIS_GROUND, context)
elvis = 0 # option removed 20200907 in processing UMEP
outputDir = self.parameterAsString(parameters, self.OUTPUT_DIR, context)
outputTmrt = self.parameterAsBool(parameters, self.OUTPUT_TMRT, context)
outputSh = self.parameterAsBool(parameters, self.OUTPUT_SH, context)
outputKup = self.parameterAsBool(parameters, self.OUTPUT_KUP, context)
outputKdown = self.parameterAsBool(parameters, self.OUTPUT_KDOWN, context)
outputLup = self.parameterAsBool(parameters, self.OUTPUT_LUP, context)
outputLdown = self.parameterAsBool(parameters, self.OUTPUT_LDOWN, context)
outputTreeplanter = self.parameterAsBool(parameters, self.OUTPUT_TREEPLANTER, context)
outputKdiff = False
#outputSstr = False
# If "Save necessary rasters for TreePlanter tool" is ticked, save the following raster for TreePlanter or Spatial TC
if outputTreeplanter:
outputTmrt = True
outputKup = True
outputKdown = True
outputLup = True
outputLdown = True
outputSh = True
saveBuild = True
outputKdiff = True
#outputSstr = True
if parameters['OUTPUT_DIR'] == 'TEMPORARY_OUTPUT':
if not (os.path.isdir(outputDir)):
os.mkdir(outputDir)
# Code from old plugin
provider = dsmlayer.dataProvider()
filepath_dsm = str(provider.dataSourceUri())
gdal_dsm = gdal.Open(filepath_dsm)
dsm = gdal_dsm.ReadAsArray().astype(float)
sizex = dsm.shape[0]
sizey = dsm.shape[1]
rows = dsm.shape[0]
cols = dsm.shape[1]
# response to issue #85
nd = gdal_dsm.GetRasterBand(1).GetNoDataValue()
dsm[dsm == nd] = 0.
# dsmcopy = np.copy(dsm)
if dsm.min() < 0:
dsmraise = np.abs(dsm.min())
dsm = dsm + dsmraise
feedback.setProgressText('Digital Surface Model (DSM) included negative values. DSM raised with ' + str(dsmraise) + 'm.')
else:
dsmraise = 0
# Get latlon from grid coordinate system
old_cs = osr.SpatialReference()
dsm_ref = dsmlayer.crs().toWkt()
old_cs.ImportFromWkt(dsm_ref)
wgs84_wkt = """
GEOGCS["WGS 84",
DATUM["WGS_1984",
SPHEROID["WGS 84",6378137,298.257223563,
AUTHORITY["EPSG","7030"]],
AUTHORITY["EPSG","6326"]],
PRIMEM["Greenwich",0,
AUTHORITY["EPSG","8901"]],
UNIT["degree",0.01745329251994328,
AUTHORITY["EPSG","9122"]],
AUTHORITY["EPSG","4326"]]"""
new_cs = osr.SpatialReference()
new_cs.ImportFromWkt(wgs84_wkt)
transform = osr.CoordinateTransformation(old_cs, new_cs)
widthx = gdal_dsm.RasterXSize
heightx = gdal_dsm.RasterYSize
geotransform = gdal_dsm.GetGeoTransform()
minx = geotransform[0]
miny = geotransform[3] + widthx * geotransform[4] + heightx * geotransform[5]
lonlat = transform.TransformPoint(minx, miny)
gdalver = float(gdal.__version__[0])
if gdalver == 3.:
lon = lonlat[1] #changed to gdal 3
lat = lonlat[0] #changed to gdal 3
else:
lon = lonlat[0] #changed to gdal 2
lat = lonlat[1] #changed to gdal 2
scale = 1 / geotransform[1]
alt = np.median(dsm)
if alt < 0:
alt = 3
feedback.setProgressText('Longitude derived from DSM: ' + str(lon))
feedback.setProgressText('Latitude derived from DSM: ' + str(lat))
trunkfile = 0
trunkratio = 0
# psi = transVeg / 100.0
# if useVegdem:
if vegdsm is not None:
usevegdem = 1
feedback.setProgressText('Vegetation scheme activated')
# load raster
gdal.AllRegister()
provider = vegdsm.dataProvider()
filePathOld = str(provider.dataSourceUri())
dataSet = gdal.Open(filePathOld)
vegdsm = dataSet.ReadAsArray().astype(float)
filePath_cdsm = filePathOld
vegsizex = vegdsm.shape[0]
vegsizey = vegdsm.shape[1]
if not (vegsizex == sizex) & (vegsizey == sizey):
raise QgsProcessingException("Error in Vegetation Canopy DSM: All rasters must be of same extent and resolution")
if vegdsm2 is not None:
gdal.AllRegister()
provider = vegdsm2.dataProvider()
filePathOld = str(provider.dataSourceUri())
filePath_tdsm = filePathOld
dataSet = gdal.Open(filePathOld)
vegdsm2 = dataSet.ReadAsArray().astype(float)
else:
trunkratio = trunkr / 100.0
vegdsm2 = vegdsm * trunkratio
filePath_tdsm = None
vegsizex = vegdsm2.shape[0]
vegsizey = vegdsm2.shape[1]
if not (vegsizex == sizex) & (vegsizey == sizey): # &
raise QgsProcessingException("Error in Trunk Zone DSM: All rasters must be of same extent and resolution")
else:
vegdsm = np.zeros([rows, cols])
vegdsm2 = np.zeros([rows, cols])
usevegdem = 0
filePath_cdsm = None
filePath_tdsm = None
# Land cover
if lcgrid is not None:
landcover = 1
feedback.setProgressText('Land cover scheme activated')
# load raster
gdal.AllRegister()
provider = lcgrid.dataProvider()
filePath_lc = str(provider.dataSourceUri())
dataSet = gdal.Open(filePath_lc)
lcgrid = dataSet.ReadAsArray().astype(float)
lcsizex = lcgrid.shape[0]
lcsizey = lcgrid.shape[1]
if not (lcsizex == sizex) & (lcsizey == sizey):
raise QgsProcessingException("Error in land cover grid: All grids must be of same extent and resolution")
baddataConifer = (lcgrid == 3)
baddataDecid = (lcgrid == 4)
if baddataConifer.any():
raise QgsProcessingException("Error in land cover grid: Land cover grid includes Confier land cover class. Ground cover information (underneath canopy) is required.")
if baddataDecid.any():
raise QgsProcessingException("Error in land cover grid: Land cover grid includes Decidiuous land cover class. Ground cover information (underneath canopy) is required.")
if np.isnan(lcgrid).any():
raise QgsProcessingException("Error in land cover grid: Land cover grid includes NaN values. Use the QGIS Fill NoData cells tool to remove NaN values.")
else:
filePath_lc = None
landcover = 0
# DEM #
if not useLcBuild:
demforbuild = 1
dem = self.parameterAsRasterLayer(parameters, self.INPUT_DEM, context)
if dem is None:
raise QgsProcessingException("Error: No valid DEM selected")
# load raster
gdal.AllRegister()
provider = dem.dataProvider()
filePathOld = str(provider.dataSourceUri())
dataSet = gdal.Open(filePathOld)
dem = dataSet.ReadAsArray().astype(float)
demsizex = dem.shape[0]
demsizey = dem.shape[1]
if not (demsizex == sizex) & (demsizey == sizey):
raise QgsProcessingException( "Error in DEM: All grids must be of same extent and resolution")
# response to issue and #230
nd = dataSet.GetRasterBand(1).GetNoDataValue()
dem[dem == nd] = 0.
if dem.min() < 0:
demraise = np.abs(dem.min())
dem = dem + demraise
feedback.setProgressText('Digital Evevation Model (DEM) included negative values. DEM raised with ' + str(demraise) + 'm.')
else:
demraise = 0
alt = np.median(dem)
if alt > 0:
alt = 3.
if (dsmraise != demraise) and (dsmraise - demraise > 0.5):
feedback.setProgressText('WARNiNG! DEM and DSM was raised unequally (difference > 0.5 m). Check your input data!')
#SVFs
zip = zipfile.ZipFile(inputSVF, 'r')
zip.extractall(self.temp_dir)
zip.close()
try:
dataSet = gdal.Open(self.temp_dir + "/svf.tif")
svf = dataSet.ReadAsArray().astype(float)
dataSet = gdal.Open(self.temp_dir + "/svfN.tif")
svfN = dataSet.ReadAsArray().astype(float)
dataSet = gdal.Open(self.temp_dir + "/svfS.tif")
svfS = dataSet.ReadAsArray().astype(float)
dataSet = gdal.Open(self.temp_dir + "/svfE.tif")
svfE = dataSet.ReadAsArray().astype(float)
dataSet = gdal.Open(self.temp_dir + "/svfW.tif")
svfW = dataSet.ReadAsArray().astype(float)
if usevegdem == 1:
dataSet = gdal.Open(self.temp_dir + "/svfveg.tif")
svfveg = dataSet.ReadAsArray().astype(float)
dataSet = gdal.Open(self.temp_dir + "/svfNveg.tif")
svfNveg = dataSet.ReadAsArray().astype(float)
dataSet = gdal.Open(self.temp_dir + "/svfSveg.tif")
svfSveg = dataSet.ReadAsArray().astype(float)
dataSet = gdal.Open(self.temp_dir + "/svfEveg.tif")
svfEveg = dataSet.ReadAsArray().astype(float)
dataSet = gdal.Open(self.temp_dir + "/svfWveg.tif")
svfWveg = dataSet.ReadAsArray().astype(float)
dataSet = gdal.Open(self.temp_dir + "/svfaveg.tif")
svfaveg = dataSet.ReadAsArray().astype(float)
dataSet = gdal.Open(self.temp_dir + "/svfNaveg.tif")
svfNaveg = dataSet.ReadAsArray().astype(float)
dataSet = gdal.Open(self.temp_dir + "/svfSaveg.tif")
svfSaveg = dataSet.ReadAsArray().astype(float)
dataSet = gdal.Open(self.temp_dir + "/svfEaveg.tif")
svfEaveg = dataSet.ReadAsArray().astype(float)
dataSet = gdal.Open(self.temp_dir + "/svfWaveg.tif")
svfWaveg = dataSet.ReadAsArray().astype(float)
else:
svfveg = np.ones((rows, cols))
svfNveg = np.ones((rows, cols))
svfSveg = np.ones((rows, cols))
svfEveg = np.ones((rows, cols))
svfWveg = np.ones((rows, cols))
svfaveg = np.ones((rows, cols))
svfNaveg = np.ones((rows, cols))
svfSaveg = np.ones((rows, cols))
svfEaveg = np.ones((rows, cols))
svfWaveg = np.ones((rows, cols))
except:
raise QgsProcessingException("SVF import error: The zipfile including the SVFs seems corrupt. Retry calcualting the SVFs in the Pre-processor or choose another file.")
svfsizex = svf.shape[0]
svfsizey = svf.shape[1]
if not (svfsizex == sizex) & (svfsizey == sizey): # &
raise QgsProcessingException("Error in svf rasters: All grids must be of same extent and resolution")
tmp = svf + svfveg - 1.
tmp[tmp < 0.] = 0.
# %matlab crazyness around 0
svfalfa = np.arcsin(np.exp((np.log((1. - tmp)) / 2.)))
feedback.setProgressText('Sky View Factor rasters loaded')
# wall height layer
if whlayer is None:
raise QgsProcessingException("Error: No valid wall height raster layer is selected")
provider = whlayer.dataProvider()
filepath_wh = str(provider.dataSourceUri())
self.gdal_wh = gdal.Open(filepath_wh)
wallheight = self.gdal_wh.ReadAsArray().astype(float)
vhsizex = wallheight.shape[0]
vhsizey = wallheight.shape[1]
if not (vhsizex == sizex) & (vhsizey == sizey):
raise QgsProcessingException("Error in Wall height raster: All rasters must be of same extent and resolution")
# wall aspectlayer
if walayer is None:
raise QgsProcessingException("Error: No valid wall aspect raster layer is selected")
provider = walayer.dataProvider()
filepath_wa = str(provider.dataSourceUri())
self.gdal_wa = gdal.Open(filepath_wa)
wallaspect = self.gdal_wa.ReadAsArray().astype(float)
vasizex = wallaspect.shape[0]
vasizey = wallaspect.shape[1]
if not (vasizex == sizex) & (vasizey == sizey):
raise QgsProcessingException("Error in Wall aspect raster: All rasters must be of same extent and resolution")
voxelheight = geotransform[1] # float
# Metdata
headernum = 1
delim = ' '
Twater = []
try:
self.metdata = np.loadtxt(inputMet,skiprows=headernum, delimiter=delim)
metfileexist = 1
except:
raise QgsProcessingException("Error: Make sure format of meteorological file is correct. You can"
"prepare your data by using 'Prepare Existing Data' in "
"the Pre-processor")
testwhere = np.where((self.metdata[:, 14] < 0.0) | (self.metdata[:, 14] > 1300.0))
if testwhere[0].__len__() > 0:
raise QgsProcessingException("Error: Kdown - beyond what is expected at line: " + str(testwhere[0] + 1))
if self.metdata.shape[1] == 24:
feedback.setProgressText("Meteorological data successfully loaded")
else:
raise QgsProcessingException("Error: Wrong number of columns in meteorological data. You can "
"prepare your data by using 'Prepare Existing Data' in "
"the Pre-processor")
feedback.setProgressText("Calculating sun positions for each time step")
location = {'longitude': lon, 'latitude': lat, 'altitude': alt}
YYYY, altitude, azimuth, zen, jday, leafon, dectime, altmax = \
Solweig_2015a_metdata_noload(self.metdata,location, utc)
# Creating vectors from meteorological input
DOY = self.metdata[:, 1]
hours = self.metdata[:, 2]
minu = self.metdata[:, 3]
Ta = self.metdata[:, 11]
RH = self.metdata[:, 10]
radG = self.metdata[:, 14]
radD = self.metdata[:, 21]
radI = self.metdata[:, 22]
P = self.metdata[:, 12]
Ws = self.metdata[:, 9]
# Check if diffuse and direct radiation exist
if onlyglobal == 0:
if np.min(radD) == -999:
raise QgsProcessingException("Diffuse radiation include NoData values",
'Tick in the box "Estimate diffuse and direct shortwave..." or aqcuire '
'observed values from external data sources.')
if np.min(radI) == -999:
raise QgsProcessingException("Direct radiation include NoData values",
'Tick in the box "Estimate diffuse and direct shortwave..." or aqcuire '
'observed values from external data sources.')
# POIs check
if poilyr is not None: # usePOI:
#header = 'yyyy id it imin dectime altitude azimuth kdir kdiff kglobal kdown kup keast ksouth ' \
# 'kwest knorth ldown lup least lsouth lwest lnorth Ta Tg RH Esky Tmrt ' \
# 'I0 CI Shadow SVF_b SVF_bv KsideI PET UTCI'
header = 'yyyy id it imin dectime altitude azimuth kdir kdiff kglobal kdown kup keast ksouth ' \
'kwest knorth ldown lup least lsouth lwest lnorth Ta Tg RH Esky Tmrt ' \
'I0 CI Shadow SVF_b SVF_bv KsideI PET UTCI CI_Tg CI_TgG KsideD Lside diffDown Kside'
# poilyr = self.parameterAsVectorLayer(parameters, self.POI_FILE, context)
# if poilyr is None:
# raise QgsProcessingException("No valid point layer is selected")
poi_field = self.parameterAsFields(parameters, self.POI_FIELD, context)
# if poi_field[0] is None:
# raise QgsProcessingException("An attribute field with unique values must be selected when using a POI vector file")
vlayer = poilyr
prov = vlayer.dataProvider()
fields = prov.fields()
idx = vlayer.fields().indexFromName(poi_field[0])
numfeat = vlayer.featureCount()
poiname = []
poisxy = np.zeros((numfeat, 3)) - 999
ind = 0
for f in vlayer.getFeatures(): # looping through each POI
y = f.geometry().centroid().asPoint().y()
x = f.geometry().centroid().asPoint().x()
poiname.append(f.attributes()[idx])
poisxy[ind, 0] = ind
poisxy[ind, 1] = np.ceil((x - minx) * scale) - 1
if miny >= 0:
poisxy[ind, 2] = np.ceil((miny + rows * (1. / scale) - y) * scale) - 1
else:
poisxy[ind, 2] = np.ceil((miny + rows * (1. / scale) - y) * scale) - 1
ind += 1
for k in range(0, poisxy.shape[0]):
poi_save = [] # np.zeros((1, 33))
data_out = outputDir + '/POI_' + str(poiname[k]) + '.txt'
np.savetxt(data_out, poi_save, delimiter=' ', header=header, comments='')
# Other PET variables
mbody = self.parameterAsDouble(parameters, self.WEIGHT, context)
ht = self.parameterAsDouble(parameters, self.HEIGHT, context) / 100.
clo = self.parameterAsDouble(parameters, self.CLO, context)
age = self.parameterAsDouble(parameters, self.AGE, context)
activity = self.parameterAsDouble(parameters, self.WEIGHT, context)
sex = self.parameterAsInt(parameters, self.SEX, context) + 1
sensorheight = self.parameterAsDouble(parameters, self.SENSOR_HEIGHT, context)
feedback.setProgressText("Point of interest (POI) vector data successfully loaded")
# %Parameterisarion for Lup
if not height:
height = 1.1
# %Radiative surface influence, Rule of thumb by Schmid et al. (1990).
first = np.round(height)
if first == 0.:
first = 1.
second = np.round((height * 20.))
if usevegdem == 1:
# Conifer or deciduous
if conifer_bool:
leafon = np.ones((1, DOY.shape[0]))
else:
leafon = np.zeros((1, DOY.shape[0]))
if firstdayleaf > lastdayleaf:
leaf_bool = ((DOY > firstdayleaf) | (DOY < lastdayleaf))
else:
leaf_bool = ((DOY > firstdayleaf) & (DOY < lastdayleaf))
leafon[0, leaf_bool] = 1
# % Vegetation transmittivity of shortwave radiation
psi = leafon * transVeg
psi[leafon == 0] = 0.5
# amaxvalue
vegmax = vegdsm.max()
amaxvalue = dsm.max() - dsm.min()
amaxvalue = np.maximum(amaxvalue, vegmax)
# Elevation vegdsms if buildingDEM includes ground heights
vegdsm = vegdsm + dsm
vegdsm[vegdsm == dsm] = 0
vegdsm2 = vegdsm2 + dsm
vegdsm2[vegdsm2 == dsm] = 0
# % Bush separation
bush = np.logical_not((vegdsm2 * vegdsm)) * vegdsm
svfbuveg = (svf - (1. - svfveg) * (1. - transVeg)) # % major bug fixed 20141203
else:
psi = leafon * 0. + 1.
svfbuveg = svf
bush = np.zeros([rows, cols])
amaxvalue = 0
# %Initialization of maps
Knight = np.zeros((rows, cols))
Tgmap1 = np.zeros((rows, cols))
Tgmap1E = np.zeros((rows, cols))
Tgmap1S = np.zeros((rows, cols))
Tgmap1W = np.zeros((rows, cols))
Tgmap1N = np.zeros((rows, cols))
# building grid and land cover preparation
sitein = self.plugin_dir + "/landcoverclasses_2016a.txt"
f = open(sitein)
lin = f.readlines()
lc_class = np.zeros((lin.__len__() - 1, 6))
for i in range(1, lin.__len__()):
lines = lin[i].split()
for j in np.arange(1, 7):
lc_class[i - 1, j - 1] = float(lines[j])
f.close()
if demforbuild == 0:
buildings = np.copy(lcgrid)
buildings[buildings == 7] = 1
buildings[buildings == 6] = 1
buildings[buildings == 5] = 1
buildings[buildings == 4] = 1
buildings[buildings == 3] = 1
buildings[buildings == 2] = 0
else:
buildings = dsm - dem
buildings[buildings < 2.] = 1.
buildings[buildings >= 2.] = 0.
if saveBuild:
saveraster(gdal_dsm, outputDir + '/buildings.tif', buildings)
# Import shadow matrices (Anisotropic sky)
if folderPathPerez: #UseAniso
anisotropic_sky = 1
data = np.load(folderPathPerez)
shmat = data['shadowmat']
vegshmat = data['vegshadowmat']
vbshvegshmat = data['vbshmat']
if usevegdem == 1:
diffsh = np.zeros((rows, cols, shmat.shape[2]))
for i in range(0, shmat.shape[2]):
diffsh[:, :, i] = shmat[:, :, i] - (1 - vegshmat[:, :, i]) * (1 - transVeg) # changes in psi not implemented yet
else:
diffsh = shmat
vegshmat += 1
vbshvegshmat += 1
# Estimate number of patches based on shadow matrices
if shmat.shape[2] == 145:
patch_option = 1 # patch_option = 1 # 145 patches
elif shmat.shape[2] == 153:
patch_option = 2 # patch_option = 2 # 153 patches
elif shmat.shape[2] == 306:
patch_option = 3 # patch_option = 3 # 306 patches
elif shmat.shape[2] == 612:
patch_option = 4 # patch_option = 4 # 612 patches
# asvf to calculate sunlit and shaded patches
asvf = np.arccos(np.sqrt(svf))
anisotropic_feedback = "Sky divided into " + str(int(shmat.shape[2])) + " patches\n \
Anisotropic sky for diffuse shortwave radiation (Perez et al., 1993) and longwave radiation (Martin & Berdahl, 1984)"
feedback.setProgressText(anisotropic_feedback)
else:
feedback.setProgressText("Isotropic sky")
anisotropic_sky = 0
diffsh = None
shmat = None
vegshmat = None
vbshvegshmat = None
asvf = None
patch_option = 0
# % Ts parameterisation maps
if landcover == 1.:
if np.max(lcgrid) > 21 or np.min(lcgrid) < 1:
raise QgsProcessingException("The land cover grid includes integer values higher (or lower) than UMEP-formatted"
"land cover grid (should be integer between 1 and 7). If other LC-classes should be included they also need to be included in landcoverclasses_2016a.txt")
if np.where(lcgrid) == 3 or np.where(lcgrid) == 4:
raise QgsProcessingException("The land cover grid includes values (decidouos and/or conifer) not appropriate for SOLWEIG-formatted land cover grid (should not include 3 or 4).")
[TgK, Tstart, alb_grid, emis_grid, TgK_wall, Tstart_wall, TmaxLST, TmaxLST_wall] = Tgmaps_v1(lcgrid, lc_class)
else:
TgK = Knight + 0.37
Tstart = Knight - 3.41
alb_grid = Knight + albedo_g
emis_grid = Knight + eground
TgK_wall = 0.37
Tstart_wall = -3.41
TmaxLST = 15.
TmaxLST_wall = 15.
# Initialisation of time related variables
if Ta.__len__() == 1:
timestepdec = 0
else:
timestepdec = dectime[1] - dectime[0]
timeadd = 0.
timeaddE = 0.
timeaddS = 0.
timeaddW = 0.
timeaddN = 0.
firstdaytime = 1.
WriteMetadataSOLWEIG.writeRunInfo(outputDir, filepath_dsm, gdal_dsm, usevegdem,
filePath_cdsm, trunkfile, filePath_tdsm, lat, lon, utc, landcover,
filePath_lc, metfileexist, inputMet, self.metdata, self.plugin_dir,
absK, absL, albedo_b, albedo_g, ewall, eground, onlyglobal, trunkratio,
transVeg, rows, cols, pos, elvis, cyl, demforbuild, anisotropic_sky)
feedback.setProgressText("Writing settings for this model run to specified output folder (Filename: RunInfoSOLWEIG_YYYY_DOY_HHMM.txt)")
# Save svf
if anisotropic_sky:
if not poisxy is None:
patch_characteristics = np.zeros((shmat.shape[2], poisxy.shape[0]))
for idx in range(poisxy.shape[0]):
for idy in range(shmat.shape[2]):
# Calculations for patches on sky, shmat = 1 = sky is visible
temp_sky = ((shmat[:,:,idy] == 1) & (vegshmat[:,:,idy] == 1))
# Calculations for patches that are vegetation, vegshmat = 0 = shade from vegetation
temp_vegsh = ((vegshmat[:,:,idy] == 0) | (vbshvegshmat[:,:,idy] == 0))
# Calculations for patches that are buildings, shmat = 0 = shade from buildings
temp_vbsh = (1 - shmat[:,:,idy]) * vbshvegshmat[:,:,idy]
temp_sh = (temp_vbsh == 1)
# Sky patch
if temp_sky[int(poisxy[idx, 2]), int(poisxy[idx, 1])]:
patch_characteristics[idy,idx] = 1.8
# Vegetation patch
elif (temp_vegsh[int(poisxy[idx, 2]), int(poisxy[idx, 1])]):
patch_characteristics[idy,idx] = 2.5
# Building patch
elif (temp_sh[int(poisxy[idx, 2]), int(poisxy[idx, 1])]):
patch_characteristics[idy,idx] = 4.5
# If metfile starts at night
CI = 1.
# Main function
feedback.setProgressText("Executing main model")
tmrtplot = np.zeros((rows, cols))
TgOut1 = np.zeros((rows, cols))
# Initiate array for I0 values
if np.unique(DOY).shape[0] > 1:
unique_days = np.unique(DOY)
first_unique_day = DOY[DOY == unique_days[0]]
I0_array = np.zeros((first_unique_day.shape[0]))
else:
first_unique_day = DOY.copy()
I0_array = np.zeros((DOY.shape[0]))
#numformat = '%d %d %d %d %.5f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f ' \
# '%.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f'
numformat = '%d %d %d %d %.5f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f ' \
'%.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f ' \
'%.2f %.2f %.2f %.2f %.2f %.2f %.2f %.2f'
for i in np.arange(0, Ta.__len__()):
feedback.setProgress(int(i * (100. / Ta.__len__()))) # move progressbar forward
if feedback.isCanceled():
feedback.setProgressText("Calculation cancelled")
break
# Daily water body temperature
if landcover == 1:
if ((dectime[i] - np.floor(dectime[i]))) == 0 or (i == 0):
Twater = np.mean(Ta[jday[0] == np.floor(dectime[i])])
# Nocturnal cloudfraction from Offerle et al. 2003
if (dectime[i] - np.floor(dectime[i])) == 0:
daylines = np.where(np.floor(dectime) == dectime[i])
if daylines.__len__() > 1:
alt = altitude[0][daylines]
alt2 = np.where(alt > 1)
rise = alt2[0][0]
[_, CI, _, _, _] = clearnessindex_2013b(zen[0, i + rise + 1], jday[0, i + rise + 1],
Ta[i + rise + 1],
RH[i + rise + 1] / 100., radG[i + rise + 1], location,
P[i + rise + 1]) # i+rise+1 to match matlab code. correct?
if (CI > 1.) or (CI == np.inf):