baseclasses.py 68.6 KB
Newer Older
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
# -*- coding: utf-8 -*-

import os
import warnings
from collections import OrderedDict

import numpy as np
from matplotlib import pyplot as plt
from osgeo import gdal_array
# custom
from shapely.geometry import Polygon
from shapely.wkt import loads as shply_loads
from six import PY3

# mpl_toolkits.basemap -> imported when GeoArray.show_map() is used
# dill -> imported when dumping GeoArray

try:
    from osgeo import gdal
    from osgeo import gdalnumeric
except ImportError:
    import gdal
    import gdalnumeric
from geopandas import GeoDataFrame, GeoSeries
from pandas import DataFrame
26
27
28
29
30
31
32
from py_tools_ds.convenience.object_oriented import alias_property
from py_tools_ds.geo.coord_calc import get_corner_coordinates
from py_tools_ds.geo.coord_grid import snap_bounds_to_pixGrid
from py_tools_ds.geo.coord_trafo import mapXY2imXY, imXY2mapXY, transform_any_prj, reproject_shapelyGeometry
from py_tools_ds.geo.projection import prj_equal, WKT2EPSG, EPSG2WKT
from py_tools_ds.geo.raster.conversion import raster2polygon
from py_tools_ds.geo.vector.topology \
33
    import get_footprint_polygon, polyVertices_outside_poly, fill_holes_within_poly
34
35
from py_tools_ds.geo.vector.geometry import boxObj
from py_tools_ds.io.raster.gdal import get_GDAL_ds_inmem
36
37
38
39
40
from py_tools_ds.compatibility.gdal import get_gdal_func

#  internal imports
from .subsetting import get_array_at_mapPos

41
42
43
44
if PY3:
    from builtins import TimeoutError, FileNotFoundError
else:
    from py_tools_ds.compatibility.python.exceptions import TimeoutError, FileNotFoundError
45

46
__author__ = 'Daniel Scheffler'
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


class GeoArray(object):
    def __init__(self, path_or_array, geotransform=None, projection=None, bandnames=None, nodata=None, progress=True,
                 q=False):
        # type: (any, tuple, str, list, float, bool, bool) -> None
        """This class creates a fast Python interface for geodata - either on disk or in memory. It can be instanced with
        a file path or with a numpy array and the corresponding geoinformation. Instances can always be indexed like
        normal numpy arrays, no matter if GeoArray has been instanced from file or from an in-memory array. GeoArray
        provides a wide range of geo-related attributes belonging to the dataset as well as some functions for quickly
        visualizing the data as a map, a simple image or an interactive image.

        :param path_or_array:   a numpy.ndarray or a valid file path
        :param geotransform:    GDAL geotransform of the given array or file on disk
        :param projection:      projection of the given array or file on disk as WKT string
                                (only needed if GeoArray is instanced with an array)
        :param bandnames:       names of the bands within the input array, e.g. ['mask_1bit', 'mask_clouds'],
                                (default: ['B1', 'B2', 'B3', ...])
        :param nodata:          nodata value
        :param progress:        show progress bars (default: True)
        :param q:               quiet mode (default: False)
        """

        # TODO implement compatibility to GDAL VRTs
        if not (isinstance(path_or_array, (str, np.ndarray, GeoArray)) or
72
           issubclass(getattr(path_or_array, '__class__'), GeoArray)):
73
            raise ValueError("%s parameter 'arg' takes only string, np.ndarray or GeoArray(and subclass) instances. "
74
                             "Got %s." % (self.__class__.__name__, type(path_or_array)))
75
76

        if path_or_array is None:
77
            raise ValueError("The %s parameter 'path_or_array' must not be None!" % self.__class__.__name__)
78
79
80
81
82

        if isinstance(path_or_array, str):
            assert ' ' not in path_or_array, "The given path contains whitespaces. This is not supported by GDAL."

            if not os.path.exists(path_or_array):
83
                raise FileNotFoundError(path_or_array)
84

85
86
        if isinstance(path_or_array, GeoArray) or issubclass(getattr(path_or_array, '__class__'), GeoArray):
            self.__dict__ = path_or_array.__dict__.copy()
87
            self._initParams = dict([x for x in locals().items() if x[0] != "self"])
88
89
90
91
92
93
            self.geotransform = geotransform or self.geotransform
            self.projection = projection or self.projection
            self.bandnames = bandnames or list(self.bandnames.values())
            self._nodata = nodata if nodata is not None else self._nodata
            self.progress = False if progress is False else self.progress
            self.q = q if q is not None else self.q
94
95

        else:
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
            self._initParams = dict([x for x in locals().items() if x[0] != "self"])
            self.arg = path_or_array
            self._arr = path_or_array if isinstance(path_or_array, np.ndarray) else None
            self.filePath = path_or_array if isinstance(path_or_array, str) and path_or_array else None
            self.basename = os.path.splitext(os.path.basename(self.filePath))[0] if not self.is_inmem else 'IN_MEM'
            self.progress = progress
            self.q = q
            self._arr_cache = None  # dict containing key 'pos' and 'arr_cached'
            self._geotransform = None
            self._projection = None
            self._shape = None
            self._dtype = None
            self._nodata = nodata
            self._mask_nodata = None
            self._mask_baddata = None
111
112
            self._footprint_poly = None
            self._gdalDataset_meta_already_set = False
113
114
            self._metadata = None
            self._bandnames = None
115
116

            if bandnames:
117
                self.bandnames = bandnames  # use property in order to validate given value
118
            if geotransform:
119
                self.geotransform = geotransform  # use property in order to validate given value
120
            if projection:
121
                self.projection = projection  # use property in order to validate given value
122
123
124
125
126
127
128
129
130
131

            if self.filePath:
                self.set_gdalDataset_meta()

    @property
    def arr(self):
        return self._arr

    @arr.setter
    def arr(self, ndarray):
132
133
        assert isinstance(ndarray, np.ndarray), "'arr' can only be set to a numpy array! Got %s." % type(ndarray)
        # assert ndarray.shape == self.shape, "'arr' can only be set to a numpy array with shape %s. Received %s. " \
134
135
136
137
138
        #                                    "If you need to change the dimensions, create a new instance of %s." \
        #                                    %(self.shape, ndarray.shape, self.__class__.__name__)
        #  THIS would avoid warping like this: geoArr.arr, geoArr.gt, geoArr.prj = warp(...)

        if ndarray.shape != self.shape:
139
            self.flush_cache()  # the cached array is not useful anymore
140
141
142
143
144

        self._arr = ndarray

    @property
    def bandnames(self):
145
        if self._bandnames and len(self._bandnames) == self.bands:
146
147
148
149
150
151
152
153
154
155
156
            return self._bandnames
        else:
            self._bandnames = OrderedDict(('B%s' % band, i) for i, band in enumerate(range(1, self.bands + 1)))
            return self._bandnames

    @bandnames.setter
    def bandnames(self, list_bandnames):
        # type: (list) -> None

        if list_bandnames:
            assert isinstance(list_bandnames, list), "A list must be given when setting the 'bandnames' attribute. " \
157
                                                     "Received %s." % type(list_bandnames)
158
159
160
161
162
            assert len(list_bandnames) == self.bands, \
                'Number of given bandnames does not match number of bands in array.'
            assert len(list(set([type(b) for b in list_bandnames]))) == 1 and type(list_bandnames[0] == 'str'), \
                "'bandnames must be a set of strings. Got other datetypes in there.'"
            bN_dict = OrderedDict((band, i) for i, band in enumerate(list_bandnames))
163
164
            assert len(
                bN_dict) == self.bands, 'Bands must not have the same name. Received band list: %s' % list_bandnames
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

            self._bandnames = bN_dict

    @property
    def is_inmem(self):
        """Check if associated image array is completely loaded into memory."""

        return isinstance(self.arr, np.ndarray)

    @property
    def shape(self):
        """Get the array shape of the associated image array."""

        if self.is_inmem:
            return self.arr.shape
        else:
            if self._shape:
                return self._shape
            else:
                self.set_gdalDataset_meta()
                return self._shape

    @property
    def ndim(self):
        """Get the number dimensions of the associated image array."""
        return len(self.shape)

    @property
    def rows(self):
        """Get the number of rows of the associated image array."""

        return self.shape[0]

    @property
    def columns(self):
        """Get the number of columns of the associated image array."""

        return self.shape[1]

    cols = alias_property('columns')

    @property
    def bands(self):
        """Get the number of bands of the associated image array."""

210
        return self.shape[2] if len(self.shape) > 2 else 1
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225

    @property
    def dtype(self):
        """Get the numpy data type of the associated image array."""

        if self._dtype:
            return self._dtype
        elif self.is_inmem:
            return self.arr.dtype
        else:
            self.set_gdalDataset_meta()
            return self._dtype

    @property
    def geotransform(self):
226
        """Get the GDAL GeoTransform of the associated image, e.g., (283500.0, 5.0, 0.0, 4464500.0, 0.0, -5.0)"""
227
228
229
230
231
232
233

        if self._geotransform:
            return self._geotransform
        elif not self.is_inmem:
            self.set_gdalDataset_meta()
            return self._geotransform
        else:
234
            return [0, 1, 0, 0, 0, -1]
235
236
237

    @geotransform.setter
    def geotransform(self, gt):
238
239
        assert isinstance(gt, (list, tuple)) and len(gt) == 6,\
            'geotransform must be a list with 6 numbers. Got %s.' % str(gt)
240

241
242
        for i in gt:
            assert isinstance(i, (int, float)), "geotransform must contain only numbers. Got '%s'." % i
243

244
        self._geotransform = gt
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266

    gt = alias_property('geotransform')

    @property
    def xgsd(self):
        """Get the X resolution in units of the given or detected projection."""

        return self.geotransform[1]

    @property
    def ygsd(self):
        """Get the Y resolution in units of the given or detected projection."""

        return abs(self.geotransform[5])

    @property
    def xygrid_specs(self):
        """
        Get the specifications for the X/Y coordinate grid, e.g. [[15,30], [0,30]] for a coordinate with its origin
        at X/Y[15,0] and a GSD of X/Y[15,30].
        """

267
        def get_grid(gt, xgsd, ygsd): return [[gt[0], gt[0] + xgsd], [gt[3], gt[3] - ygsd]]
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
        return get_grid(self.geotransform, self.xgsd, self.ygsd)

    @property
    def projection(self):
        """
        Get the projection of the associated image. Setting the projection is only allowed if GeoArray has been
        instanced from memory or the associated file on disk has no projection.
        """

        if self._projection:
            return self._projection
        elif not self.is_inmem:
            self.set_gdalDataset_meta()
            return self._projection
        else:
            return ''

    @projection.setter
    def projection(self, prj):
        if self.filePath:
288
            assert self.projection is None or prj_equal(self.projection, prj), \
289
                "Cannot set %s.projection to the given value because it does not match the projection from the file " \
290
                "on disk." % self.__class__.__name__
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
        else:
            self._projection = prj

    prj = alias_property('projection')

    @property
    def epsg(self):
        """Get the EPSG code of the projection of the GeoArray."""

        return WKT2EPSG(self.projection)

    @epsg.setter
    def epsg(self, epsg_code):
        self.projection = EPSG2WKT(epsg_code)

    @property
    def box(self):
        mapPoly = get_footprint_polygon(get_corner_coordinates(gt=self.geotransform, cols=self.columns, rows=self.rows))
        return boxObj(gt=self.geotransform, prj=self.projection, mapPoly=mapPoly)

    @property
    def nodata(self):
        """
        Get the nodata value of the GeoArray. If GeoArray has been instanced with a file path the file is checked
        for an existing nodata value. Otherwise (if no value is exlicitly given during object instanciation) the nodata
        value is tried to be automatically detected.
        """

        if self._nodata is not None:
            return self._nodata
        else:
            # try to get nodata value from file
            if not self.is_inmem:
                self.set_gdalDataset_meta()
            if self._nodata is None:
Daniel Scheffler's avatar
Bugfix    
Daniel Scheffler committed
326
                self._nodata = self.find_noDataVal()
327
328
329
330
331
332
                if self._nodata == 'ambiguous':
                    warnings.warn('Nodata value could not be clearly identified. It has been set to None.')
                    self._nodata = None
                else:
                    if self._nodata is not None and not self.q:
                        print("Automatically detected nodata value for %s '%s': %s"
333
                              % (self.__class__.__name__, self.basename, self._nodata))
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
            return self._nodata

    @nodata.setter
    def nodata(self, value):
        self._nodata = value

    @property
    def mask_nodata(self):
        """
        Get the nodata mask of the associated image array. It is calculated using all image bands.
        """

        if self._mask_nodata is not None:
            return self._mask_nodata
        else:
349
            self.calc_mask_nodata()  # sets self._mask_nodata
350
351
352
353
354
355
356
357
358
359
360
            return self._mask_nodata

    @mask_nodata.setter
    def mask_nodata(self, mask):
        """Set bad data mask.

        :param mask:    Can be a file path, a numpy array or an instance o GeoArray.
        """

        if mask is not None:
            from .masks import NoDataMask
361
362
            geoArr_mask = NoDataMask(mask, progress=self.progress, q=self.q)
            geoArr_mask.gt = geoArr_mask.gt if geoArr_mask.gt not in [None, [0, 1, 0, 0, 0, -1]] else self.gt
363
            geoArr_mask.prj = geoArr_mask.prj if geoArr_mask.prj else self.prj
364
            imName = "the %s '%s'" % (self.__class__.__name__, self.basename)
365
366
367
368

            assert geoArr_mask.bands == 1, \
                'Expected one single band as nodata mask for %s. Got %s bands.' % (self.basename, geoArr_mask.bands)
            assert geoArr_mask.shape[:2] == self.shape[:2], 'The provided nodata mask must have the same number of ' \
369
                                                            'rows and columns as the %s itself.' % imName
370
371
            assert geoArr_mask.gt == self.gt, \
                'The geotransform of the given nodata mask for %s must match the geotransform of the %s itself. ' \
372
                'Got %s.' % (imName, self.__class__.__name__, geoArr_mask.gt)
373
374
            assert not geoArr_mask.prj or prj_equal(geoArr_mask.prj, self.prj), \
                'The projection of the given nodata mask for the %s must match the projection of the %s itself.' \
375
                % (imName, self.__class__.__name__)
376
377

            self._mask_nodata = geoArr_mask
378
379
380
381
382
383
        else:
            del self.mask_nodata

    @mask_nodata.deleter
    def mask_nodata(self):
        self._mask_nodata = None
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402

    @property
    def mask_baddata(self):
        """
        Returns the bad data mask for the associated image array if it has been explicitly previously. It can be set
         by passing a file path, a numpy array or an instance of GeoArray to the setter of this property.
        """

        return self._mask_baddata

    @mask_baddata.setter
    def mask_baddata(self, mask):
        """Set bad data mask.

        :param mask:    Can be a file path, a numpy array or an instance o GeoArray.
        """

        if mask is not None:
            from .masks import BadDataMask
403
404
            geoArr_mask = BadDataMask(mask, progress=self.progress, q=self.q)
            geoArr_mask.gt = geoArr_mask.gt if geoArr_mask.gt not in [None, [0, 1, 0, 0, 0, -1]] else self.gt
405
            geoArr_mask.prj = geoArr_mask.prj if geoArr_mask.prj else self.prj
406
            imName = "the %s '%s'" % (self.__class__.__name__, self.basename)
407
408
409
410

            assert geoArr_mask.bands == 1, \
                'Expected one single band as bad data mask for %s. Got %s bands.' % (self.basename, geoArr_mask.bands)
            assert geoArr_mask.shape[:2] == self.shape[:2], 'The provided bad data mask must have the same number of ' \
411
                                                            'rows and columns as the %s itself.' % imName
412
413
            assert geoArr_mask.gt == self.gt, \
                'The geotransform of the given bad data mask for %s must match the geotransform of the %s itself. ' \
414
                'Got %s.' % (imName, self.__class__.__name__, geoArr_mask.gt)
415
416
            assert prj_equal(geoArr_mask.prj, self.prj), \
                'The projection of the given bad data mask for the %s must match the projection of the %s itself.' \
417
                % (imName, self.__class__.__name__)
418
419

            self._mask_baddata = geoArr_mask
420
421
422
423
424
425
        else:
            del self.mask_baddata

    @mask_baddata.deleter
    def mask_baddata(self):
        self._mask_baddata = None
426
427
428
429
430
431
432
433
434
435

    @property
    def footprint_poly(self):
        # FIXME should return polygon in image coordinates if no projection is available
        """
        Get the footprint polygon of the associated image array (returns an instance of shapely.geometry.Polygon.
        """

        if self._footprint_poly is None:
            assert self.mask_nodata is not None, 'A nodata mask is needed for calculating the footprint polygon. '
436
            if np.std(self.mask_nodata[:]) == 0:
437
438
439
440
                # do not run raster2polygon if whole image is filled with data
                self._footprint_poly = self.box.mapPoly
            else:
                try:
441
442
                    multipolygon = raster2polygon(self.mask_nodata.astype(np.uint8), self.gt, self.prj, exact=False,
                                                  progress=self.progress, q=self.q, maxfeatCount=10, timeout=3)
443
                    self._footprint_poly = fill_holes_within_poly(multipolygon)
444
                except (RuntimeError, TimeoutError):
445
446
447
448
                    if not self.q:
                        warnings.warn("\nCalculation of footprint polygon failed for %s '%s'. Using outer bounds. One "
                                      "reason could be that the nodata value appears within the actual image (not only "
                                      "as fill value). To avoid this use another nodata value. Current nodata value is "
449
                                      "%s." % (self.__class__.__name__, self.basename, self.nodata))
450
451
452
                    self._footprint_poly = self.box.mapPoly

            # validation
453
454
455
456
            assert not polyVertices_outside_poly(self._footprint_poly, self.box.mapPoly), \
                "Computing footprint polygon for %s '%s' failed. The resulting polygon is partly or completely " \
                "outside of the image bounds." % (self.__class__.__name__, self.basename)
            # assert self._footprint_poly
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
            # for XY in self.corner_coord:
            #    assert self.GeoArray.box.mapPoly.contains(Point(XY)) or self.GeoArray.box.mapPoly.touches(Point(XY)), \
            #        "The corner position '%s' is outside of the %s." % (XY, self.imName)

        return self._footprint_poly

    @footprint_poly.setter
    def footprint_poly(self, poly):
        if isinstance(poly, Polygon):
            self._footprint_poly = poly
        elif isinstance(poly, str):
            self._footprint_poly = shply_loads(poly)
        else:
            raise ValueError("'footprint_poly' can only be set from a shapely polygon or a WKT string.")

    @property
    def metadata(self):
        """
        Returns a GeoDataFrame containing all available metadata (read from file if available).
        Use 'metadata[band_index].to_dict()' to get a metadata dictionary for a specific band.
        Use 'metadata.loc[row_name].to_dict()' to get all metadata values of the same key for all bands as dictionary.
        Use 'metadata.loc[row_name, band_index] = value' to set a new value.

        :return:  geopandas.GeoDataFrame
        """

        if self._metadata is not None:
            return self._metadata
        else:
            default = GeoDataFrame(columns=range(self.bands))
487
            # for bn,idx in self.bandnames.items():
488
489
490
491
492
493
494
495
496
497
            #    default.loc['band_index',bn] = idx
            self._metadata = default
            if not self.is_inmem:
                self.set_gdalDataset_meta()
                return self._metadata
            else:
                return self._metadata

    @metadata.setter
    def metadata(self, GDF):
498
        assert isinstance(GDF, (GeoDataFrame, DataFrame)) and len(GDF.columns) == self.bands, \
499
            "%s.metadata can only be set with an instance of geopandas.GeoDataFrame of which the column number " \
500
            "corresponds to the band number of %s." % (self.__class__.__name__, self.__class__.__name__)
501
502
503
504
505
        self._metadata = GDF

    meta = alias_property('metadata')

    def __getitem__(self, given):
506
        if isinstance(given, (int, float, slice)) and self.ndim == 3:
507
508
509
510
511
512
513
514
515
516
517
518
519
            # handle 'given' as index for 3rd (bands) dimension
            if self.is_inmem:
                return self.arr[:, :, given]
            else:
                return self.from_path(self.arg, [given])

        elif isinstance(given, str):
            # behave like a dictionary and return the corresponding band
            if self.bandnames:
                if given not in self.bandnames:
                    raise ValueError("'%s' is not a known band. Known bands are: %s"
                                     % (given, ', '.join(list(self.bandnames.keys()))))
                if self.is_inmem:
520
                    return self.arr if self.ndim == 2 else self.arr[:, :, self.bandnames[given]]
521
522
523
524
                else:
                    return self.from_path(self.arg, [self.bandnames[given]])
            else:
                raise ValueError('String indices are only supported if %s has been instanced with bandnames given.'
525
                                 % self.__class__.__name__)
526
527
528
529
530
531
532

        elif isinstance(given, (tuple, list)):
            # handle requests like geoArr[[1,2],[3,4]  -> not implemented in from_path if array is not in mem
            types = [type(i) for i in given]
            if list in types or tuple in types:
                self.to_mem()

533
            if len(given) == 3:
534
535

                # handle strings in the 3rd dim of 'given' -> convert them to a band index
536
                if isinstance(given[2], str):
537
538
539
540
541
542
543
544
                    if self.bandnames:
                        if given[2] not in self.bandnames:
                            raise ValueError("'%s' is not a known band. Known bands are: %s"
                                             % (given[2], ', '.join(list(self.bandnames.keys()))))

                        band_idx = self.bandnames[given[2]]
                        # NOTE: the string in the 3rd is ignored if ndim==2 and band_idx==0
                        if self.is_inmem:
545
                            return self.arr if (self.ndim == 2 and band_idx == 0) else self.arr[:, :, band_idx]
546
                        else:
547
548
                            getitem_params = \
                                given[:2] if (self.ndim == 2 and band_idx == 0) else given[:2] + (band_idx,)
549
550
551
552
553
554
555
                            return self.from_path(self.arg, getitem_params)
                    else:
                        raise ValueError(
                            'String indices are only supported if %s has been instanced with bandnames given.'
                            % self.__class__.__name__)

                # in case a third dim is requested from 2D-array -> ignore 3rd dim if 3rd dim is 0
556
                elif self.ndim == 2 and given[2] == 0:
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
                    if self.is_inmem:
                        return self.arr[given[:2]]
                    else:
                        return self.from_path(self.arg, given[:2])

        # if nothing has been returned until here -> behave like a numpy array
        if self.is_inmem:
            return self.arr[given]
        else:
            getitem_params = [given] if isinstance(given, slice) else given
            return self.from_path(self.arg, getitem_params)

    def __setitem__(self, idx, array2set):
        """Overwrites the pixel values of GeoArray.arr with the given array.

        :param idx:         <int, list, slice> the index position to overwrite
        :param array2set:   <np.ndarray> array to be set. Must be compatible to the given index position.
        :return:
        """

        if self.is_inmem:
            self.arr[idx] = array2set
        else:
            raise NotImplementedError('Item assignment for %s instances that are not in memory is not yet supported.'
581
                                      % self.__class__.__name__)
582
583
584

    def __getattr__(self, attr):
        # check if the requested attribute can not be present because GeoArray has been instanced with an array
585
586
        if attr not in self.__dir__() and not self.is_inmem and attr in ['shape', 'dtype', 'geotransform',
                                                                         'projection']:
587
588
            self.set_gdalDataset_meta()

589
590
591
        if attr in self.__dir__():  # __dir__() includes also methods and properties
            return self.__getattribute__(attr)  # __getattribute__ avoids infinite loop
        elif hasattr(np.array([]), attr):
592
593
            return self[:].__getattribute__(attr)
        else:
594
            raise AttributeError("%s object has no attribute '%s'." % (self.__class__.__name__, attr))
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

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

        # clean array cache in order to avoid cache pickling
        self.flush_cache()

        return self.__dict__

    def __setstate__(self, state):
        """Defines how the attributes of GMS object are unpickled.
        NOTE: This method has been implemented because otherwise pickled and unpickled instances show recursion errors
        within __getattr__ when requesting any attribute.
        """

        self.__dict__ = state

    def calc_mask_nodata(self, fromBand=None, overwrite=False):
        """Calculates a no data mask with (values: 0=nodata; 1=data)

        :param fromBand:  <int> index of the band to be used (if None, all bands are used)
        :param overwrite: <bool> whether to overwrite existing nodata mask that has already been calculated
        :return:
        """

        if self._mask_nodata is None or overwrite:
            assert self.ndim in [2, 3], "Only 2D or 3D arrays are supported. Got a %sD array." % self.ndim
622
            arr = self[:, :, fromBand] if self.ndim == 3 and fromBand is not None else self[:]
623
624
625
626
627

            if self.nodata is None:
                self.mask_nodata = np.ones((self.rows, self.cols), np.bool)
            else:
                self.mask_nodata = np.where(arr == self.nodata, 0, 1).astype(np.bool) if arr.ndim == 2 else \
628
                    np.all(np.where(arr == self.nodata, 0, 1), axis=2).astype(np.bool)
629

630
631
632
633
634
    def find_noDataVal(self, bandIdx=0, sz=3):
        """Tries to derive no data value from homogenious corner pixels within 3x3 windows (by default).
        :param bandIdx:
        :param sz: window size in which corner pixels are analysed
        """
635
        def get_mean_std(corner_subset): return {'mean': np.mean(corner_subset), 'std': np.std(corner_subset)}
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652

        wins = [self[0:sz, 0:sz, bandIdx], self[0:sz, -sz:, bandIdx],
                self[-sz:, -sz:, bandIdx], self[-sz:, 0:sz, bandIdx]]  # UL, UR, LR, LL
        means_stds = [get_mean_std(win) for win in wins]

        possVals = [i['mean'] for i in means_stds if i['std'] == 0]
        # possVals==[]: all corners are filled with data; np.std(possVals)==0: noDataVal clearly identified

        if possVals:
            if np.std(possVals) != 0:
                # different possible nodata values have been found in the image corner
                return 'ambiguous'
            else:
                if len(possVals) <= 2:
                    # each window in each corner
                    warnings.warn("\nAutomatic nodata value detection returned the value %s for GeoArray '%s' but this "
                                  "seems to be unreliable (occurs in only %s). To avoid automatic detection, just pass "
653
654
655
                                  "the correct nodata value."
                                  % (possVals[0], self.basename, ('2 image corners' if len(possVals) == 2 else
                                                                  '1 image corner')))
656
657
658
659
                return possVals[0]
        else:
            return None

660
661
662
663
664
665
666
667
668
669
    def set_gdalDataset_meta(self):
        """Retrieves GDAL metadata from file. This function is only executed once to avoid overwriting of user defined
         attributes, that are defined after object instanciation.

        :return:
        """

        if not self._gdalDataset_meta_already_set:
            assert self.filePath
            ds = gdal.Open(self.filePath)
670
671
672
            if not ds:
                raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())

673
            # set private class variables (in order to avoid recursion error)
674
675
            self._shape = tuple([ds.RasterYSize, ds.RasterXSize] + ([ds.RasterCount] if ds.RasterCount > 1 else []))
            self._dtype = gdal_array.GDALTypeCodeToNumericTypeCode(ds.GetRasterBand(1).DataType)
676
            self._geotransform = ds.GetGeoTransform()
677
678
679
            # temp conversion to EPSG needed because GDAL seems to modify WKT string when writing file to disk
            # (e.g. using gdal_merge) -> conversion to EPSG and back undos that
            self._projection = EPSG2WKT(WKT2EPSG(ds.GetProjection()))
680

681
682
683
684
            if 'nodata' not in self._initParams or self._initParams['nodata'] is None:
                band = ds.GetRasterBand(1)
                # FIXME this does not support different nodata values within the same file
                self._nodata = band.GetNoDataValue()
685

686
            # read global domain metadata
687
688
            # TODO check to specifically use the 'ENVI' metadata domain ds.GetMetadata('ENVI')
            global_meta = ds.GetMetadata()
689

690
691
            # read band domain metadata
            for b in range(self.bands):
692
693
                band = ds.GetRasterBand(b + 1)
                meta_gs = GeoSeries(band.GetMetadata())
694

695
696
697
698
699
700
701
                # add band names if available
                if 'Band_%s' % str(b + 1) in global_meta.keys():
                    meta_gs['band_name'] = global_meta['Band_%s' % str(b + 1)]

                # TODO add the remaining global metadata

                self.metadata[b] = meta_gs
702

703
            del ds, band
704
705
706
707
708
709
710
711
712
713
714
715
716
717

        self._gdalDataset_meta_already_set = True

    def from_path(self, path, getitem_params=None):
        # type: (str, list) -> np.ndarray
        """Read a GDAL compatible raster image from disk, with respect to the given image position.
        NOTE: If the requested array position is already in cache, it is returned from there.

        :param path:            <str> the file path of the image to read
        :param getitem_params:  <list> a list of slices in the form [row_slice, col_slice, band_slice]
        :return out_arr:        <np.ndarray> the output array
        """

        ds = gdal.Open(path)
718
719
720
        if not ds:
            raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())

721
        R, C, B = ds.RasterYSize, ds.RasterXSize, ds.RasterCount
722
        del ds
723

724
        # convert getitem_params to subset area to be read ##
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
        rS, rE, cS, cE, bS, bE, bL = [None] * 7

        # populate rS, rE, cS, cE, bS, bE, bL
        if getitem_params:
            if len(getitem_params) >= 2:
                givenR, givenC = getitem_params[:2]
                if isinstance(givenR, slice):
                    rS = givenR.start
                    rE = givenR.stop - 1 if givenR.stop is not None else None
                elif isinstance(givenR, int):
                    rS = givenR
                    rE = givenR
                if isinstance(givenC, slice):
                    cS = givenC.start
                    cE = givenC.stop - 1 if givenC.stop is not None else None
                elif isinstance(givenC, int):
                    cS = givenC
                    cE = givenC
            if len(getitem_params) in [1, 3]:
                givenB = getitem_params[2] if len(getitem_params) == 3 else getitem_params[0]
                if isinstance(givenB, slice):
                    bS = givenB.start
                    bE = givenB.stop - 1 if givenB.stop is not None else None
                elif isinstance(givenB, int):
                    bS = givenB
                    bE = givenB
751
                elif isinstance(givenB, (tuple, list)):
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
                    typesInGivenB = [type(i) for i in givenB]
                    assert len(list(set(typesInGivenB))) == 1, \
                        'Mixed data types within the list of bands are not supported.'
                    if isinstance(givenB[0], int):
                        bL = list(givenB)
                    elif isinstance(givenB[0], str):
                        bL = [self.bandnames[i] for i in givenB]
                elif type(givenB) in [str]:
                    bL = [self.bandnames[givenB]]

        # set defaults for not given values
        rS = rS if rS is not None else 0
        rE = rE if rE is not None else R - 1
        cS = cS if cS is not None else 0
        cE = cE if cE is not None else C - 1
        bS = bS if bS is not None else 0
        bE = bE if bE is not None else B - 1
        bL = list(range(bS, bE + 1)) if not bL else bL

        # convert negative to positive ones
        rS = rS if rS >= 0 else self.rows + rS
        rE = rE if rE >= 0 else self.rows + rE
        cS = cS if cS >= 0 else self.columns + cS
        cE = cE if cE >= 0 else self.columns + cE
        bS = bS if bS >= 0 else self.bands + bS
        bE = bE if bE >= 0 else self.bands + bE
778
        bL = [b if b >= 0 else (self.bands + b) for b in bL]
779
780

        # validate subset area bounds to be read
781
782
783
784
785
786
787
        def msg(v, idx, sz):
            # FIXME numpy raises that error ONLY for the 2nd axis
            return '%s is out of bounds for axis %s with size %s' % (v, idx, sz)

        for val, axIdx, axSize in zip([rS, rE, cS, cE, bS, bE], [0, 0, 1, 1, 2, 2], [R, R, C, C, B, B]):
            if not 0 <= val <= axSize - 1:
                raise ValueError(msg(val, axIdx, axSize))
788
789

        # summarize requested array position in arr_pos
790
        # NOTE: # bandlist must be string because truth value of an array with more than one element is ambiguous
791
792
793
        arr_pos = dict(rS=rS, rE=rE, cS=cS, cE=cE, bS=bS, bE=bE, bL=bL)

        # check if the requested array position is already in cache -> if yes, return it from there
794
        if self._arr_cache is not None and self._arr_cache['pos'] == arr_pos:
795
            out_arr = self._arr_cache['arr_cached']
796
797
798
799
800
801
802

        else:
            # TODO insert a multiprocessing.Lock here in order to prevent IO bottlenecks?
            # read subset area from disk
            if bL == list(range(0, B)):
                tempArr = gdalnumeric.LoadFile(path, cS, rS, cE - cS + 1, rE - rS + 1)
                out_arr = np.swapaxes(np.swapaxes(tempArr, 0, 2), 0, 1) if B > 1 else tempArr
803
804
                if out_arr is None:
                    raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())
805
806
807
808
            else:
                ds = gdal.Open(path)
                if len(bL) == 1:
                    band = ds.GetRasterBand(bL[0] + 1)
809
                    out_arr = band.ReadAsArray(cS, rS, cE - cS + 1, rE - rS + 1)
810
811
                    if out_arr is None:
                        raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())
812
                    del band
813
814
815
816
817
                else:
                    out_arr = np.empty((rE - rS + 1, cE - cS + 1, len(bL)))
                    for i, bIdx in enumerate(bL):
                        band = ds.GetRasterBand(bIdx + 1)
                        out_arr[:, :, i] = band.ReadAsArray(cS, rS, cE - cS + 1, rE - rS + 1)
818
819
                        if out_arr is None:
                            raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())
820
                        del band
821

822
                del ds
823
824

            # only set self.arr if the whole cube has been read (in order to avoid sudden shape changes)
825
            if out_arr.shape == self.shape:
826
827
828
829
830
                self.arr = out_arr

            # write _arr_cache
            self._arr_cache = dict(pos=arr_pos, arr_cached=out_arr)

831
832
        return out_arr  # TODO implement check of returned datatype (e.g. NoDataMask should always return np.bool
        # TODO -> would be np.int8 if an int8 file is read from disk
833
834
835
836
837
838
839
840

    def save(self, out_path, fmt='ENVI', creationOptions=None):
        # type: (str, str, list) -> None
        """Write the raster data to disk.

        :param out_path:        <str> output path
        :param fmt:             <str> the output format / GDAL driver code to be used for output creation, e.g. 'ENVI'
                                Refer to http://www.gdal.org/formats_list.html to get a full list of supported formats.
841
842
        :param creationOptions: <list> GDAL creation options,
                                e.g., ["QUALITY=80", "REVERSIBLE=YES", "WRITE_METADATA=YES"]
843
844
845
        """

        if not self.q:
846
847
            print('Writing GeoArray of size %s to %s.' % (self.shape, out_path))
        assert self.ndim in [2, 3], 'Only 2D- or 3D arrays are supported.'
848
849
850
851
852
853
854
855
856
857

        driver = gdal.GetDriverByName(fmt)
        if driver is None:
            raise Exception("'%s' is not a supported GDAL driver. Refer to www.gdal.org/formats_list.html for full "
                            "list of GDAL driver codes." % fmt)

        if not os.path.isdir(os.path.dirname(out_path)):
            os.makedirs(os.path.dirname(out_path))

        if self.is_inmem:
858
859
            ds = get_GDAL_ds_inmem(self.arr, self.geotransform, self.projection,
                                   self.nodata)  # expects rows,columns,bands
860
861
862

            # set metadata
            if not self.metadata.empty:
863
864
865
                global_meta = {}

                # set band domain metadata
866
                for bidx in range(self.bands):
867
                    band = ds.GetRasterBand(bidx + 1)
868
                    meta2write = self.metadata[bidx].to_dict()
869
                    meta2write = dict((k, v) for k, v in meta2write.items() if v is not np.nan)
870
871

                    if 'band_name' in meta2write:
872
                        global_meta['Band_%s' % str(bidx + 1)] = meta2write['band_name']
873
874
                        del meta2write['band_name']

875
                    band.SetMetadata(meta2write)
876
                    del band
877

878
879
880
                # set global domain metadata
                ds.SetMetadata(global_meta)

881
882
883
884
885
                # get ENVI metadata domain
                # ds_orig = gdal.Open(self.filePath)
                # envi_meta_domain = ds_orig.GetMetadata('ENVI')
                # ds.SetMetadata(envi_meta_domain, 'ENVI')
                # ds_orig = None
886

887
888
            driver.CreateCopy(out_path, ds, options=creationOptions if creationOptions else [])

889
890
891
892
            # rows, columns, bands => bands, rows, columns
            # out_arr = self.arr if self.ndim == 2 else np.swapaxes(np.swapaxes(self.arr, 0, 2), 1, 2)
            # gdalnumeric.SaveArray(out_arr, out_path, format=fmt, prototype=ds) # expects bands,rows,columns
            del ds
893
894
895

        else:
            src_ds = gdal.Open(self.filePath)
896
897
898
            if not src_ds:
                raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())

899
900
            gdal_Translate = get_gdal_func('Translate')
            gdal_Translate(out_path, src_ds, format=fmt, creationOptions=creationOptions)
901
            del src_ds
902
903
904
905
906
907
908
909
910

        if not os.path.exists(out_path):
            raise Exception(gdal.GetLastErrorMsg())

    def dump(self, out_path):
        # type: (str) -> None
        """Serialize the whole object instance to disk using dill."""

        import dill
911
912
        with open(out_path, 'wb') as outF:
            dill.dump(self, outF)
913
914
915
916
917
918
919
920
921

    def _get_plottable_image(self, xlim=None, ylim=None, band=None, boundsMap=None, boundsMapPrj=None, res_factor=None,
                             nodataVal=None, out_prj=None):
        # handle limits
        if boundsMap:
            boundsMapPrj = boundsMapPrj if boundsMapPrj else self.prj
            image2plot, gt, prj = self.get_mapPos(boundsMap, boundsMapPrj, band2get=band,
                                                  fillVal=nodataVal if nodataVal is not None else self.nodata)
        else:
922
923
            cS, cE = xlim if isinstance(xlim, (tuple, list)) else (0, self.columns)
            rS, rE = ylim if isinstance(ylim, (tuple, list)) else (0, self.rows)
924
925

            image2plot = self[rS:rE, cS:cE, band] if band is not None else self[rS:rE, cS:cE]
926
            gt, prj = self.geotransform, self.projection
927

928
        transOpt = ['SRC_METHOD=NO_GEOTRANSFORM'] if tuple(gt) == (0, 1, 0, 0, 0, -1) else None
929
        xdim, ydim = None, None
930
        nodataVal = nodataVal if nodataVal is not None else self.nodata
931
932

        if res_factor != 1. and image2plot.shape[0] * image2plot.shape[1] > 1e6:  # shape > 1000*1000
933
934
935
936
            # sample image down / normalize
            xdim, ydim = \
                (self.columns * res_factor, self.rows * res_factor) if res_factor else \
                tuple((np.array([self.columns, self.rows]) / (np.array([self.columns, self.rows]).max() / 1000)))
937
938
939
            xdim, ydim = int(xdim), int(ydim)

        if xdim or ydim or out_prj:
940
            from py_tools_ds.geo.raster.reproject import warp_ndarray
941
942
943
944
945
            image2plot, gt, prj = warp_ndarray(image2plot, self.geotransform, self.projection,
                                               out_XYdims=(xdim, ydim), in_nodata=nodataVal, out_nodata=nodataVal,
                                               transformerOptions=transOpt, out_prj=out_prj, q=True)
            if transOpt and 'NO_GEOTRANSFORM' in ','.join(transOpt):
                image2plot = np.flipud(image2plot)
946
947
                gt = list(gt)
                gt[3] = 0
948
949
950
951
952
953
954
955
956
957
958
959
960
961
962
963
964
965
966
967
968
969

            if xdim or ydim:
                print('Note: array has been downsampled to %s x %s for faster visualization.' % (xdim, ydim))

        return image2plot, gt, prj

    def show(self, xlim=None, ylim=None, band=None, boundsMap=None, boundsMapPrj=None, figsize=None,
             interpolation='none', vmin=None, vmax=None, cmap=None, nodataVal=None, res_factor=None, interactive=False):
        """Plots the desired array position into a figure.

        :param xlim:            [start_column, end_column]
        :param ylim:            [start_row, end_row]
        :param band:            the band index of the band to be plotted (if None and interactive==True all bands are
                                shown, otherwise the first band is chosen)
        :param boundsMap:       xmin, ymin, xmax, ymax
        :param boundsMapPrj:
        :param figsize:
        :param interpolation:
        :param vmin:
        :param vmax:
        :param cmap:
        :param nodataVal:
Daniel Scheffler's avatar
Daniel Scheffler committed
970
971
        :param res_factor:      <float> resolution factor for downsampling of the image to be plotted in order to save
                                plotting time and memory (default=None -> downsampling is performed to 1000x1000)
972
973
974
975
976
977
978
979
        :param interactive:     <bool> activates interactive plotting based on 'holoviews' library.
                                NOTE: this deactivates the magic '% matplotlib inline' in Jupyter Notebook
        :return:
        """

        band = (band if band is not None else 0) if not interactive else band

        # get image to plot
980
        nodataVal = nodataVal if nodataVal is not None else self.nodata
Daniel Scheffler's avatar
Daniel Scheffler committed
981
982
983
        image2plot, gt, prj = \
            self._get_plottable_image(xlim, ylim, band, boundsMap=boundsMap, boundsMapPrj=boundsMapPrj,
                                      res_factor=res_factor, nodataVal=nodataVal)
984
985

        # set color palette
986
987
        palette = cmap if cmap else plt.cm.gray
        if nodataVal is not None and np.std(image2plot) != 0:  # do not show nodata
988
            image2plot = np.ma.masked_equal(image2plot, nodataVal)
989
            vmin_auto, vmax_auto = np.percentile(image2plot.compressed(), 2), np.percentile(image2plot.compressed(), 98)
990
991
992
993
994
995
996
            palette.set_bad('aqua', 0)
        else:
            vmin_auto, vmax_auto = np.percentile(image2plot, 2), np.percentile(image2plot, 98)

        vmin = vmin if vmin is not None else vmin_auto
        vmax = vmax if vmax is not None else vmax_auto

997
        palette.set_over('1')
998
999
        palette.set_under('0')

1000
        if interactive and image2plot.ndim == 3:
1001
1002
1003
1004
1005
1006
1007
            import holoviews as hv
            from skimage.exposure import rescale_intensity
            hv.notebook_extension('matplotlib')

            cS, cE = xlim if isinstance(xlim, (tuple, list)) else (0, self.columns - 1)
            rS, rE = ylim if isinstance(ylim, (tuple, list)) else (0, self.rows - 1)

1008
            image2plot = np.array(rescale_intensity(image2plot, in_range=(vmin, vmax)))
1009

1010
1011
1012
1013
1014
1015
1016
            def get_hv_image(b):
                # FIXME ylabels have the wrong order
                return hv.Image(image2plot[:, :, b] if b is not None else image2plot,
                                bounds=(cS, rS, cE, rE))(
                    style={'cmap': 'gray'}, plot={'fig_inches': 4 if figsize is None else figsize, 'show_grid': True})

            # hvIm = hv.Image(image2plot)(style={'cmap': 'gray'}, figure_inches=figsize)
1017
1018
1019
1020
1021
1022
1023
            hmap = hv.HoloMap([(band, get_hv_image(band)) for band in range(image2plot.shape[2])], kdims=['band'])

            return hmap

        else:
            if interactive:
                warnings.warn('Currently there is no interactive mode for single-band arrays. '
1024
                              'Switching to standard matplotlib figure..')  # TODO implement zoomable fig
1025
1026
1027
1028
1029

            # show image
            plt.figure(figsize=figsize)
            rows, cols = image2plot.shape[:2]
            plt.imshow(image2plot, palette, interpolation=interpolation, extent=(0, cols, rows, 0),
1030
                       vmin=vmin, vmax=vmax, )  # compressed excludes nodata values
1031
1032
1033
1034
1035
1036
1037
1038
1039
1040
1041
1042
1043
1044
1045
1046
1047
1048
1049
            plt.show()

    def show_map(self, xlim=None, ylim=None, band=0, boundsMap=None, boundsMapPrj=None, ax=None, figsize=None,
                 interpolation='none', vmin=None, vmax=None, cmap=None, nodataVal=None, res_factor=None,
                 return_map=False, zoomable=False):
        """

        :param xlim:
        :param ylim:
        :param band:            band index (starting with 0)
        :param boundsMap:       xmin, ymin, xmax, ymax
        :param boundsMapPrj:
        :param ax:              allows to pass a matplotlib axis object where figure is plotted into
        :param figsize:
        :param interpolation:
        :param vmin:
        :param vmax:
        :param cmap:
        :param nodataVal:
Daniel Scheffler's avatar
Daniel Scheffler committed
1050
1051
        :param res_factor:      <float> resolution factor for downsampling of the image to be plotted in order to save
                                plotting time and memory (default=None -> downsampling is performed to 1000x1000)
1052
1053
1054
1055
1056
        :param return_map:
        :param zoomable:        <bool> enable or disable zooming via mpld3
        :return:
        """

1057
1058
1059
        try:
            from mpl_toolkits.basemap import Basemap
        except ImportError:
1060
1061
            warnings.warn('This function requires Basemap. You need to install basemap manually (see www./'
                          'matplotlib.org/basemap) if you want to plot maps. It is not automatically installed.')
1062
            raise
1063
1064
1065
1066
1067
1068
        try:
            import mpld3
            if zoomable:
                mpld3.enable_notebook()
            else:
                mpld3.disable_notebook()
1069
        except Exception:
1070
1071
1072
1073
            if zoomable:
                zoomable = False
                warnings.warn('mpld3 is not available. Zooming disabled.')

1074
1075
1076
        assert self.geotransform and tuple(self.geotransform) != (0, 1, 0, 0, 0, -1), \
            'A valid geotransform is needed for a map visualization. Got %s.' % list(self.geotransform)
        assert self.projection, 'A projection is needed for a map visualization. Got %s.' % self.projection
1077
1078

        # get image to plot
1079
        nodataVal = nodataVal if nodataVal is not None else self.nodata
1080
1081
1082
1083
1084
        image2plot, gt, prj = self._get_plottable_image(xlim, ylim, band, boundsMap=boundsMap,
                                                        boundsMapPrj=boundsMapPrj, res_factor=res_factor,
                                                        nodataVal=nodataVal, out_prj='epsg:4326')

        # calculate corner coordinates of plot
1085
        # if boundsMap:
1086
1087
1088
1089
1090
        #    boundsMapPrj = boundsMapPrj if boundsMapPrj else self.prj
        #    if not prj_equal(boundsMapPrj, 4326):
        #        boundsMap = reproject_shapelyGeometry(box(*boundsMap), boundsMapPrj, 4626).bounds
        #    xmin, ymin, xmax, ymax = boundsMap
        #    UL_XY, UR_XY, LR_XY, LL_XY = (xmin,ymax), (xmax, ymax), (xmax,ymin), (xmin, ymin)
1091
1092
1093
        # else:
        UL_XY, UR_XY, LR_XY, LL_XY = [(YX[1], YX[0]) for YX in GeoArray(image2plot, gt, prj).box.boxMapYX]
        center_lon, center_lat = (UL_XY[0] + UR_XY[0]) / 2., (UL_XY[1] + LL_XY[1]) / 2.
1094
1095
1096
1097
1098
1099

        # create map
        fig = plt.figure(figsize=figsize)
        plt.subplots_adjust(left=0.05, right=0.95, top=0.90, bottom=0.05, wspace=0.15, hspace=0.05)
        ax = ax if ax is not None else plt.subplot(111)

1100
        m = Basemap(projection='tmerc', resolution=None, lon_0=center_lon, lat_0=center_lat,
1101
1102
1103
1104
                    urcrnrlon=UR_XY[0], urcrnrlat=UR_XY[1], llcrnrlon=LL_XY[0], llcrnrlat=LL_XY[1])

        # set color palette
        palette = cmap if cmap else plt.cm.gray
1105
        if nodataVal is not None and np.std(image2plot) != 0:  # do not show nodata
1106
1107
1108
1109
1110
1111
1112
            image2plot = np.ma.masked_equal(image2plot, nodataVal)
            vmin_auto, vmax_auto = np.percentile(image2plot.compressed(), 2), np.percentile(image2plot.compressed(), 98)
            palette.set_bad('aqua', 0)
        else:
            vmin_auto, vmax_auto = np.percentile(image2plot, 2), np.percentile(image2plot, 98)
        vmin = vmin if vmin is not None else vmin_auto
        vmax = vmax if vmax is not None else vmax_auto
1113
        palette.set_over('1')
1114
1115
1116
1117
1118
1119
1120
1121
1122
        palette.set_under('0')

        # add image to map (y-axis must be inverted for basemap)
        if zoomable:
            m.imshow(image2plot, palette, interpolation=interpolation, vmin=vmin, vmax=vmax)
        else:
            m.imshow(np.flipud(image2plot), palette, interpolation=interpolation, vmin=vmin, vmax=vmax)

        # add coordinate grid lines
1123
1124
        parallels = np.arange(-90, 90., 0.25)  # TODO make this adjustable
        # parallels = np.arange(-90, 90., 0.1)
1125
1126
1127
        m.drawparallels(parallels, labels=[1, 0, 0, 0], fontsize=12, linewidth=0.4)

        meridians = np.arange(-180., 180., 0.25)
1128
        # meridians = np.arange(-180., 180., 0.1)
1129
1130
1131
        m.drawmeridians(meridians, labels=[0, 0, 0, 1], fontsize=12, linewidth=0.4)

        if return_map:
1132
            return fig, ax, m
1133
1134
1135
1136
1137
1138
        else:
            plt.show()

    def show_map_utm(self, xlim=None, ylim=None, band=0, figsize=None, interpolation='none', cmap=None,
                     nodataVal=None, vmin=None, vmax=None, res_factor=None, return_map=False):

1139
1140
1141
        try:
            from mpl_toolkits.basemap import Basemap
        except ImportError:
1142
1143
            warnings.warn('This function requires Basemap. You need to install basemap manually (see www./'
                          'matplotlib.org/basemap) if you want to plot maps. It is not automatically installed.')
1144
            raise
1145
1146
1147
1148
        warnings.warn(UserWarning('This function is still under construction and may not work as expected!'))
        # TODO debug this function

        # get image to plot
1149
        nodataVal = nodataVal if nodataVal is not None else self.nodata
1150
1151
1152
1153
        image2plot, gt, prj = self._get_plottable_image(xlim, ylim, band, res_factor, nodataVal)

        # calculate corner coordinates of plot
        box2plot = GeoArray(image2plot, gt, prj).box
1154
        # UL_XY, UR_XY, LR_XY, LL_XY = [(YX[1], YX[0]) for YX in GeoArray(image2plot, gt, prj).box.boxMapYX]
1155
        # Xarr, Yarr = self.box.get_coordArray_MapXY(prj=EPSG2WKT(4326))
1156
1157
        UL_XY, UR_XY, LR_XY, LL_XY = [transform_any_prj(self.projection, 'epsg:4326', x, y) for y, x in
                                      box2plot.boxMapYX]
1158
        center_X, center_Y = (UL_XY[0] + UR_XY[0]) / 2., (UL_XY[1] + LL_XY[1]) / 2.
1159
        center_lon, center_lat = transform_any_prj(prj, 'epsg:4326', center_X, center_Y)
1160
1161
1162
1163
1164
1165
1166
        print(center_lon, center_lat)

        # create map
        fig = plt.figure(figsize=figsize)
        plt.subplots_adjust(left=0.05, right=0.95, top=0.90, bottom=0.05, wspace=0.15, hspace=0.05)
        ax = plt.subplot(111)
        print(UL_XY, UR_XY, LR_XY, LL_XY)
1167
1168
        #        m = Basemap(projection='tmerc', resolution=None, lon_0=center_lon, lat_0=center_lat,
        #                    urcrnrx=UR_XY[0], urcrnry=UR_XY[1], llcrnrx=LL_XY[0], llcrnry=LL_XY[1])
1169
1170
        m = Basemap(projection='tmerc', resolution=None, lon_0=center_lon, lat_0=center_lat,
                    urcrnrlon=UR_XY[0], urcrnrlat=UR_XY[1], llcrnrlon=LL_XY[0], llcrnrlat=LL_XY[1],
1171
                    k_0=0.9996, rsphere=(6378137.00, 6356752.314245179), suppress_ticks=False)
1172
1173
1174
1175
        # m.pcolormesh(Xarr, Yarr, self[:], cmap=plt.cm.jet)

        # set color palette
        palette = cmap if cmap else plt.cm.gray
1176
        if nodataVal is not None:  # do not show nodata
1177
1178
1179
1180
1181
1182
1183
1184
1185
1186
1187
1188
1189
1190
1191
1192
1193
1194
1195
1196
1197
1198
1199
1200
1201
1202
1203
1204
1205
1206
1207
            image2plot = np.ma.masked_equal(image2plot, nodataVal)
            vmin_auto, vmax_auto = np.percentile(image2plot.compressed(), 2), np.percentile(image2plot.compressed(), 98)
            palette.set_bad('aqua', 0)
        else:
            vmin_auto, vmax_auto = np.percentile(image2plot, 2), np.percentile(image2plot, 98)
        vmin = vmin if vmin is not None else vmin_auto
        vmax = vmax if vmax is not None else vmax_auto
        palette.set_over('1')
        palette.set_under('0')

        # add image to map (y-axis must be inverted for basemap)
        m.imshow(np.flipud(image2plot), palette, interpolation=interpolation, vmin=vmin, vmax=vmax)

        # add coordinate grid lines
        parallels = np.arange(-90, 90., 0.25)
        m.drawparallels(parallels, labels=[1, 0, 0, 0], fontsize=12, linewidth=0.4)

        meridians = np.arange(-180., 180., 0.25)
        m.drawmeridians(meridians, labels=[0, 0, 0, 1], fontsize=12, linewidth=0.4)

        if return_map:
            return fig, ax, m
        else:
            plt.show()

    def show_footprint(self):
        """This method is intended to be called from Jupyter Notebook and shows a web map containing the calculated
        footprint of GeoArray.
        """

        try:
1208
1209
            import folium
            import geojson
1210
1211
1212
1213
1214
1215
1216
1217
1218
        except ImportError:
            folium, geojson = None, None
        if not folium or not geojson:
            raise ImportError(
                "This method requires the libraries 'folium' and 'geojson'. They can be installed with "
                "the shell command 'pip install folium geojson'.")

        lonlatPoly = reproject_shapelyGeometry(self.footprint_poly, self.epsg, 4326)

1219
        m = folium.Map(location=tuple(np.array(lonlatPoly.centroid.coords.xy).flatten())[::-1])
1220
1221
1222
1223
        gjs = geojson.Feature(geometry=lonlatPoly, properties={})
        folium.GeoJson(gjs).add_to(m)
        return m

1224
1225
1226
1227
1228
1229
1230
1231
1232
1233
1234
1235
1236
1237
1238
1239
1240
1241
1242
1243
1244
1245
1246
1247
1248
1249
1250
1251
1252
1253
1254
1255
1256
1257
1258
1259
    def show_histogram(self, band=1, bins=200, normed=False, exclude_nodata=True, vmin=None, vmax=None, figsize=None):
        # type: (int, int, bool, bool, float, float, tuple) -> None

        """Show a histogram of a given band.

        :param band:            the band to be used to plot the histogram
        :param bins:            number of bins to plot (default: 200)
        :param normed:          whether to normalize the y-axis or not (default: False)
        :param exclude_nodata:  whether tp exclude nodata value from the histogram
        :param vmin:            minimum value for the x-axis of the histogram
        :param vmax:            maximum value for the x-axis of the histogram
        :param figsize:         figure size (tuple)
        """

        if self.nodata is not None and exclude_nodata:
            data = np.ma.masked_equal(self[band], self.nodata)
            data = data.compressed()
        else:
            data = self[band]

        vmin = vmin if vmin is not None else np.percentile(data, 1)
        vmax = vmax if vmax is not None else np.percentile(data, 99)
        image2plot = data

        plt.figure(figsize=figsize)
        plt.hist(list(image2plot.flat), normed=normed, bins=bins, color='gray', range=[vmin, vmax])
        plt.xlabel('Pixel value')
        plt.ylabel('Probabilty' if normed else 'Count')
        plt.show()

        if not self.q:
            print('STD:', np.std(data))
            print('MEAN:', np.mean(data))
            print('2 % percentile:', np.percentile(data, 2))
            print('98 % percentile:', np.percentile(data, 98))

1260
    def get_mapPos(self, mapBounds, mapBounds_prj, band2get=None, out_prj=None, arr_gt=None, arr_prj=None, fillVal=None,
1261
                   rspAlg='near', progress=None, v=False):  # TODO implement slice for indexing bands
1262
1263
1264
1265
1266
1267
1268
1269
1270
1271
1272
1273
1274
1275
1276
1277
1278
1279
1280
1281
        # type: (tuple, str, int, str, tuple, str, int, str, bool, bool) -> (np.ndarray, tuple, str)
        """Returns the array data of GeoArray at a given geographic position.

        NOTE: The given mapBounds are snapped to the pixel grid of GeoArray. If the given mapBounds include areas
        outside of the extent of GeoArray, these areas are filled with the fill value of GeoArray.

        :param mapBounds:       xmin, ymin, xmax, ymax
        :param mapBounds_prj:   WKT projection string corresponding to mapBounds
        :param band2get:        band index of the band to be returned (full array if not given)
        :param out_prj:         output projection as WKT string. If not given, the self.projection is used.
        :param arr_gt:          GDAL GeoTransform (taken from self if not given)
        :param arr_prj:         WKT projection string (taken from self if not given)
        :param fillVal:         nodata value
        :param rspAlg:          <str> Resampling method to use. Available methods are:
                                near, bilinear, cubic, cubicspline, lanczos, average, mode, max, min, med, q1, q2
        :param progress:        whether to show progress bars or not
        :param v:               verbose mode (not related to GeoArray.v; must be explicitly set)
        :return:
        """

1282
1283
1284
1285
        arr_gt = arr_gt if arr_gt else self.geotransform
        arr_prj = arr_prj if arr_prj else self.projection
        out_prj = out_prj if out_prj else arr_prj
        fillVal = fillVal if fillVal is not None else self.nodata
1286
1287
1288
1289
1290
1291
1292
1293
1294
1295
1296
1297
1298
1299
1300
        progress = progress if progress is not None else self.progress

        if self.is_inmem and (not arr_gt or not arr_prj):
            raise ValueError('In case of in-mem arrays the respective geotransform and projection of the array '
                             'has to be passed.')

        if v:
            print('%s.get_mapPos() input parameters:')
            print('\tmapBounds', mapBounds, '<==>', self.box.boundsMap)
            print('\tEPSG', WKT2EPSG(mapBounds_prj), self.epsg)
            print('\tarr_gt', arr_gt, self.gt)
            print('\tarr_prj', WKT2EPSG(arr_prj), self.epsg)
            print('\tfillVal', fillVal, self.nodata, '\n')

        sub_arr, sub_gt, sub_prj = get_array_at_mapPos(self, arr_gt, arr_prj,
1301
1302
1303
1304
1305
1306
1307
1308
                                                       out_prj=out_prj,
                                                       mapBounds=mapBounds,
                                                       mapBounds_prj=mapBounds_prj,
                                                       fillVal=fillVal,
                                                       rspAlg=rspAlg,
                                                       out_gsd=(self.xgsd, self.ygsd),
                                                       band2get=band2get,
                                                       progress=progress)
1309
1310
        return sub_arr, sub_gt, sub_prj

1311
1312
1313
    def get_subset(self, xslice=None, yslice=None, zslice=None, return_GeoArray=True):
        # type: (slice, slice, slice, bool) -> GeoArray
        """Returns a new instatnce of GeoArray representing a subset of the initial one wit respect to given array position.
Daniel Scheffler's avatar
Daniel Scheffler committed
1314

1315
1316
1317
1318
        :param xslice:          a slice providing the X-position for the subset in the form slice(xstart, xend, xstep)
        :param yslice:          a slice providing the Y-position for the subset in the form slice(ystart, yend, ystep)
        :param zslice:          a slice providing the Z-position for the subset in the form slice(zstart, zend, zstep)
        :param return_GeoArray: whether to return an instance of GeoArray (default) or a tuple(np.ndarray, gt, prj)
Daniel Scheffler's avatar
Daniel Scheffler committed
1319
        :return:
1320
1321
        """

1322
1323
1324
        sub_arr = self[yslice if yslice else slice(None),  # row
                       xslice if xslice else slice(None),  # col
                       zslice if zslice else slice(None)]  # band
1325
1326
        sub_ulXY = imXY2mapXY((xslice.start, yslice.start), self.gt)
        sub_gt = (sub_ulXY[0], self.gt[1], self.gt[2], sub_ulXY[1], self.gt[4], self.gt[5])
1327
1328
1329
        sub_gA = GeoArray(sub_arr, sub_gt, self.prj,
                          bandnames=list(self.bandnames.keys()), nodata=self.nodata, progress=self.progress, q=self.q)
        sub_gA.meta = self.meta