baseclasses.py 77.3 KB
Newer Older
1 2 3 4
# -*- coding: utf-8 -*-

import os
import warnings
5
from importlib import util
6
from collections import OrderedDict
Daniel Scheffler's avatar
Daniel Scheffler committed
7
from copy import deepcopy
8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

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
26 27 28 29
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
30
from py_tools_ds.geo.projection import prj_equal, WKT2EPSG, EPSG2WKT, isLocal
31 32
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
from py_tools_ds.compatibility.gdal import get_gdal_func
37
from py_tools_ds.numeric.numbers import is_number
38
from py_tools_ds.numeric.array import get_array_tilebounds
39 40 41

#  internal imports
from .subsetting import get_array_at_mapPos
42
from .metadata import GDAL_Metadata
43

44
if PY3:
45
    # noinspection PyCompatibility
46 47 48
    from builtins import TimeoutError, FileNotFoundError
else:
    from py_tools_ds.compatibility.python.exceptions import TimeoutError, FileNotFoundError
49

50
__author__ = 'Daniel Scheffler'
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


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
76
           issubclass(getattr(path_or_array, '__class__'), GeoArray)):
77
            raise ValueError("%s parameter 'arg' takes only string, np.ndarray or GeoArray(and subclass) instances. "
78
                             "Got %s." % (self.__class__.__name__, type(path_or_array)))
79 80

        if path_or_array is None:
81
            raise ValueError("The %s parameter 'path_or_array' must not be None!" % self.__class__.__name__)
82 83 84 85 86

        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):
87
                raise FileNotFoundError(path_or_array)
88

89 90
        if isinstance(path_or_array, GeoArray) or issubclass(getattr(path_or_array, '__class__'), GeoArray):
            self.__dict__ = path_or_array.__dict__.copy()
91
            self._initParams = dict([x for x in locals().items() if x[0] != "self"])
92 93
            self.geotransform = geotransform or self.geotransform
            self.projection = projection or self.projection
94
            self.bandnames = bandnames or list(self.bandnames.keys())
95 96 97
            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
98 99

        else:
100 101 102 103 104 105 106 107 108 109 110 111 112 113 114
            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
115 116
            self._footprint_poly = None
            self._gdalDataset_meta_already_set = False
117 118
            self._metadata = None
            self._bandnames = None
119 120

            if bandnames:
121
                self.bandnames = bandnames  # use property in order to validate given value
122
            if geotransform:
123
                self.geotransform = geotransform  # use property in order to validate given value
124
            if projection:
125
                self.projection = projection  # use property in order to validate given value
126 127 128 129 130 131 132 133 134 135

            if self.filePath:
                self.set_gdalDataset_meta()

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

    @arr.setter
    def arr(self, ndarray):
136 137
        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. " \
138 139 140 141 142
        #                                    "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:
143
            self.flush_cache()  # the cached array is not useful anymore
144 145 146 147 148

        self._arr = ndarray

    @property
    def bandnames(self):
149
        if self._bandnames and len(self._bandnames) == self.bands:
150 151
            return self._bandnames
        else:
152
            del self.bandnames  # runs deleter which sets it to default values
153 154 155 156 157 158 159
            return self._bandnames

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

        if list_bandnames:
160 161 162 163 164 165 166 167
            if not isinstance(list_bandnames, list):
                raise TypeError("A list must be given when setting the 'bandnames' attribute. "
                                "Received %s." % type(list_bandnames))
            if len(list_bandnames) != self.bands:
                raise ValueError('Number of given bandnames does not match number of bands in array.')
            if len(list(set([type(b) for b in list_bandnames]))) != 1 or not isinstance(list_bandnames[0], str):
                raise ValueError("'bandnames must be a set of strings. Got other datatypes in there.'")

168
            bN_dict = OrderedDict((band, i) for i, band in enumerate(list_bandnames))
169 170 171

            if len(bN_dict) != self.bands:
                raise ValueError('Bands must different names. Received band list: %s' % list_bandnames)
172 173 174

            self._bandnames = bN_dict

175
            try:
176
                self.metadata.band_meta['band_names'] = list_bandnames
177 178 179
            except AttributeError:
                # in case self._metadata is None
                pass
180 181 182 183 184 185 186
        else:
            del self.bandnames

    @bandnames.deleter
    def bandnames(self):
        self._bandnames = OrderedDict(('B%s' % band, i) for i, band in enumerate(range(1, self.bands + 1)))
        if self._metadata is not None:
187
            self.metadata.band_meta['band_names'] = list(self._bandnames.keys())
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
    @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."""

229
        return self.shape[2] if len(self.shape) > 2 else 1
230 231 232 233 234 235 236 237 238 239 240 241 242 243 244

    @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):
245
        """Get the GDAL GeoTransform of the associated image, e.g., (283500.0, 5.0, 0.0, 4464500.0, 0.0, -5.0)"""
246 247 248 249 250 251 252

        if self._geotransform:
            return self._geotransform
        elif not self.is_inmem:
            self.set_gdalDataset_meta()
            return self._geotransform
        else:
253
            return [0, 1, 0, 0, 0, -1]
254 255 256

    @geotransform.setter
    def geotransform(self, gt):
257 258
        assert isinstance(gt, (list, tuple)) and len(gt) == 6,\
            'geotransform must be a list with 6 numbers. Got %s.' % str(gt)
259

260
        for i in gt:
261
            assert is_number(i), "geotransform must contain only numbers. Got '%s' (type: %s)." % (i, type(i))
262

263
        self._geotransform = gt
264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285

    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].
        """

286
        def get_grid(gt, xgsd, ygsd): return [[gt[0], gt[0] + xgsd], [gt[3], gt[3] - ygsd]]
287 288 289 290 291 292 293 294 295 296 297 298 299
        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()
300
            return self._projection  # or "LOCAL_CS[\"MAP\"]"
301
        else:
302
            return ''  # '"LOCAL_CS[\"MAP\"]"
303 304 305 306

    @projection.setter
    def projection(self, prj):
        if self.filePath:
307
            assert self.projection is None or prj_equal(self.projection, prj), \
308
                "Cannot set %s.projection to the given value because it does not match the projection from the file " \
309
                "on disk." % self.__class__.__name__
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
        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
345
                self._nodata = self.find_noDataVal()
346 347 348 349 350 351
                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"
352
                              % (self.__class__.__name__, self.basename, self._nodata))
353 354 355 356 357 358 359 360 361 362 363 364 365 366 367
            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:
368
            self.calc_mask_nodata()  # sets self._mask_nodata
369 370 371 372 373 374 375 376 377 378 379
            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
380 381
            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
382
            geoArr_mask.prj = geoArr_mask.prj if geoArr_mask.prj else self.prj
383
            imName = "the %s '%s'" % (self.__class__.__name__, self.basename)
384 385 386 387

            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 ' \
388
                                                            'rows and columns as the %s itself.' % imName
389 390
            assert geoArr_mask.gt == self.gt, \
                'The geotransform of the given nodata mask for %s must match the geotransform of the %s itself. ' \
391
                'Got %s.' % (imName, self.__class__.__name__, geoArr_mask.gt)
392 393
            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.' \
394
                % (imName, self.__class__.__name__)
395 396

            self._mask_nodata = geoArr_mask
397 398 399 400 401 402
        else:
            del self.mask_nodata

    @mask_nodata.deleter
    def mask_nodata(self):
        self._mask_nodata = None
403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421

    @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
422 423
            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
424
            geoArr_mask.prj = geoArr_mask.prj if geoArr_mask.prj else self.prj
425
            imName = "the %s '%s'" % (self.__class__.__name__, self.basename)
426 427 428 429

            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 ' \
430
                                                            'rows and columns as the %s itself.' % imName
431 432
            assert geoArr_mask.gt == self.gt, \
                'The geotransform of the given bad data mask for %s must match the geotransform of the %s itself. ' \
433
                'Got %s.' % (imName, self.__class__.__name__, geoArr_mask.gt)
434 435
            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.' \
436
                % (imName, self.__class__.__name__)
437 438

            self._mask_baddata = geoArr_mask
439 440 441 442 443 444
        else:
            del self.mask_baddata

    @mask_baddata.deleter
    def mask_baddata(self):
        self._mask_baddata = None
445 446 447 448 449 450 451 452 453 454

    @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. '
455
            if False not in self.mask_nodata[:]:
456 457 458 459
                # do not run raster2polygon if whole image is filled with data
                self._footprint_poly = self.box.mapPoly
            else:
                try:
460 461
                    multipolygon = raster2polygon(self.mask_nodata.astype(np.uint8), self.gt, self.prj, exact=False,
                                                  progress=self.progress, q=self.q, maxfeatCount=10, timeout=3)
462
                    self._footprint_poly = fill_holes_within_poly(multipolygon)
463
                except (RuntimeError, TimeoutError):
464 465 466 467
                    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 "
468
                                      "%s." % (self.__class__.__name__, self.basename, self.nodata))
469 470 471
                    self._footprint_poly = self.box.mapPoly

            # validation
472 473 474 475
            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
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
            # 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:
505 506
            default = GDAL_Metadata(nbands=self.bands)

507 508 509 510 511 512 513 514
            self._metadata = default
            if not self.is_inmem:
                self.set_gdalDataset_meta()
                return self._metadata
            else:
                return self._metadata

    @metadata.setter
515 516 517 518 519 520
    def metadata(self, meta):
        if not isinstance(meta, GDAL_Metadata) or meta.bands != self.bands:
            raise ValueError("%s.metadata can only be set with an instance of geoarray.metadata.GDAL_Metadata of "
                             "which the band number corresponds to the band number of %s."
                             % (self.__class__.__name__, self.__class__.__name__))
        self._metadata = meta
521 522 523 524

    meta = alias_property('metadata')

    def __getitem__(self, given):
525
        if isinstance(given, (int, float, slice)) and self.ndim == 3:
526 527 528 529 530 531 532 533 534 535 536 537 538
            # 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:
539
                    return self.arr if self.ndim == 2 else self.arr[:, :, self.bandnames[given]]
540 541 542 543
                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.'
544
                                 % self.__class__.__name__)
545 546 547 548 549 550 551

        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()

552
            if len(given) == 3:
553 554

                # handle strings in the 3rd dim of 'given' -> convert them to a band index
555
                if isinstance(given[2], str):
556 557 558 559 560 561 562 563
                    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:
564
                            return self.arr if (self.ndim == 2 and band_idx == 0) else self.arr[:, :, band_idx]
565
                        else:
566 567
                            getitem_params = \
                                given[:2] if (self.ndim == 2 and band_idx == 0) else given[:2] + (band_idx,)
568 569 570 571 572 573 574
                            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
575
                elif self.ndim == 2 and given[2] == 0:
576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599
                    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.'
600
                                      % self.__class__.__name__)
601 602 603

    def __getattr__(self, attr):
        # check if the requested attribute can not be present because GeoArray has been instanced with an array
604 605
        attrsNot2Link2np = ['__deepcopy__']   # attributes we don't want to inherit from numpy.ndarray

606 607
        if attr not in self.__dir__() and not self.is_inmem and attr in ['shape', 'dtype', 'geotransform',
                                                                         'projection']:
608 609
            self.set_gdalDataset_meta()

610 611
        if attr in self.__dir__():  # __dir__() includes also methods and properties
            return self.__getattribute__(attr)  # __getattribute__ avoids infinite loop
612
        elif attr not in attrsNot2Link2np and hasattr(np.array([]), attr):
613 614
            return self[:].__getattribute__(attr)
        else:
615
            raise AttributeError("%s object has no attribute '%s'." % (self.__class__.__name__, attr))
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

    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
643
            arr = self[:, :, fromBand] if self.ndim == 3 and fromBand is not None else self[:]
644

645 646 647
            min_v, max_v = np.min(arr), np.max(arr)
            if (min_v == max_v == self.nodata) or (np.isnan(min_v) and np.isnan(max_v) and np.isnan(self.nodata)):
                self.mask_nodata = np.full(arr.shape[:2], False)
648
            else:
649 650 651 652 653 654 655 656 657 658
                if self.nodata is None:
                    self.mask_nodata = np.ones((self.rows, self.cols), np.bool)
                elif np.isnan(self.nodata):
                    self.mask_nodata = \
                        np.invert(np.isnan(arr)) if arr.ndim == 2 else \
                        np.all(np.invert(np.isnan(arr)), axis=2)
                else:
                    self.mask_nodata = \
                        np.ma.masked_not_equal(arr, self.nodata).mask if arr.ndim == 2 else \
                        np.all(np.ma.masked_not_equal(arr, self.nodata).mask, axis=2)
659

660 661 662 663 664 665 666 667
    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
        """
        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

668 669
        means, stds = [np.mean(win) for win in wins], [np.std(win) for win in wins]
        possVals = [mean for mean, std in zip(means, stds) if std == 0 or np.isnan(std)]
670 671 672 673
        # possVals==[]: all corners are filled with data; np.std(possVals)==0: noDataVal clearly identified

        if possVals:
            if np.std(possVals) != 0:
674 675 676 677 678 679
                if np.isnan(np.std(possVals)):
                    # at least one of the possible values is np.nan
                    nodata = np.nan
                else:
                    # different possible nodata values have been found in the image corner
                    nodata = 'ambiguous'
680 681 682 683 684
            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 "
685 686 687
                                  "the correct nodata value."
                                  % (possVals[0], self.basename, ('2 image corners' if len(possVals) == 2 else
                                                                  '1 image corner')))
688
                nodata = possVals[0]
689
        else:
690 691 692
            nodata = None

        return nodata
693

694 695 696 697 698 699 700 701 702 703
    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)
704 705 706
            if not ds:
                raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())

707
            # set private class variables (in order to avoid recursion error)
708 709
            self._shape = tuple([ds.RasterYSize, ds.RasterXSize] + ([ds.RasterCount] if ds.RasterCount > 1 else []))
            self._dtype = gdal_array.GDALTypeCodeToNumericTypeCode(ds.GetRasterBand(1).DataType)
710
            self._geotransform = list(ds.GetGeoTransform())
711 712

            # for some reason GDAL reads arbitrary geotransforms as (0, 1, 0, 0, 0, 1) instead of (0, 1, 0, 0, 0, -1)
713
            self._geotransform[5] = -abs(self._geotransform[5])  # => force ygsd to be negative
714

715 716
            # 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
717 718
            wkt = ds.GetProjection()
            self._projection = EPSG2WKT(WKT2EPSG(wkt)) if not isLocal(wkt) else ''
719

720 721 722 723
            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()
724

725 726 727 728
            # set metadata attribute
            if self.is_inmem or not self.filePath:
                # metadata cannot be read from disk -> set it to the default
                self._metadata = GDAL_Metadata(nbands=self.bands)
729

730 731
            else:
                self._metadata = GDAL_Metadata(filePath=self.filePath)
732

733
            del ds
734 735 736 737 738 739 740 741 742 743 744 745 746 747

        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)
748 749 750
        if not ds:
            raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())

751
        R, C, B = ds.RasterYSize, ds.RasterXSize, ds.RasterCount
752
        del ds
753

754
        # convert getitem_params to subset area to be read #
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
        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
781
                elif isinstance(givenB, (tuple, list)):
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
                    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
808
        bL = [b if b >= 0 else (self.bands + b) for b in bL]
809 810

        # validate subset area bounds to be read
811 812 813 814 815 816 817
        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))
818 819

        # summarize requested array position in arr_pos
820
        # NOTE: # bandlist must be string because truth value of an array with more than one element is ambiguous
821 822 823
        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
824
        if self._arr_cache is not None and self._arr_cache['pos'] == arr_pos:
825
            out_arr = self._arr_cache['arr_cached']
826 827 828 829 830 831 832

        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
833 834
                if out_arr is None:
                    raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())
835 836 837 838
            else:
                ds = gdal.Open(path)
                if len(bL) == 1:
                    band = ds.GetRasterBand(bL[0] + 1)
839
                    out_arr = band.ReadAsArray(cS, rS, cE - cS + 1, rE - rS + 1)
840 841
                    if out_arr is None:
                        raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())
842
                    del band
843 844 845 846 847
                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)
848 849
                        if out_arr is None:
                            raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())
850
                        del band
851

852
                del ds
853

854 855 856 857 858
            # 3D to 2D conversion in case out_arr can be represented by a 2D array (avoids shapes like (1,2,2
            # NOTE: -> numpy also returns a 2D array in that case
            if 1 in out_arr.shape:
                out_arr = out_arr.reshape(*[i for i in out_arr.shape if i != 1])

859
            # only set self.arr if the whole cube has been read (in order to avoid sudden shape changes)
860
            if out_arr.shape == self.shape:
861 862 863 864 865
                self.arr = out_arr

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

866 867
        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
868 869 870 871 872 873 874 875

    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.
876 877
        :param creationOptions: <list> GDAL creation options,
                                e.g., ["QUALITY=80", "REVERSIBLE=YES", "WRITE_METADATA=YES"]
878 879 880
        """

        if not self.q:
881 882
            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.'
883 884 885 886 887 888 889 890 891

        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))

892 893
        envi_metadict = self.metadata.to_ENVI_metadict()

894
        if self.is_inmem:
Daniel Scheffler's avatar
Daniel Scheffler committed
895 896 897 898 899
            ds_inmem = get_GDAL_ds_inmem(self.arr, self.geotransform, self.projection,
                                         self.nodata)  # expects rows,columns,bands

            # write dataset
            ds_out = driver.CreateCopy(out_path, ds_inmem, options=creationOptions if creationOptions else [])
900 901 902 903 904 905

            # # 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_inmem)  # expects bands,rows,columns
            # ds_out = gdal.Open(out_path)

Daniel Scheffler's avatar
Daniel Scheffler committed
906
            del ds_inmem
907

908 909 910 911
            ################
            # set metadata #
            ################

Daniel Scheffler's avatar
Daniel Scheffler committed
912
            # NOTE:  The dataset has to be written BEFORE metadata are added. Otherwise, metadata are not written.
913 914 915

            # ENVI #
            ########
916 917
            if fmt == 'ENVI':
                ds_out.SetMetadata(envi_metadict, 'ENVI')
918

919
                if 'band_names' in envi_metadict:
920 921
                    for bidx in range(self.bands):
                        band = ds_out.GetRasterBand(bidx + 1)
922 923 924 925
                        bandname = self.metadata.band_meta['band_names'][bidx].strip()
                        band.SetDescription(bandname)

                        assert band.GetDescription() == bandname
926 927 928 929
                        del band

                if 'description' in envi_metadict:
                    ds_out.SetDescription(envi_metadict['description'])
930

931 932
                ds_out.FlushCache()
                gdal.Unlink(out_path + '.aux.xml')
933

934 935 936
            elif self.metadata.all_meta:
                    # set global domain metadata
                    if self.metadata.global_meta:
937
                        ds_out.SetMetadata(dict((k, repr(v)) for k, v in self.metadata.global_meta.items()))
938

939 940 941
                    if 'description' in envi_metadict:
                        ds_out.SetDescription(envi_metadict['description'])

942
                    # set band domain metadata
943 944
                    bandmeta_dict = self.metadata.to_DataFrame().astype(str).to_dict()

945 946
                    for bidx in range(self.bands):
                        band = ds_out.GetRasterBand(bidx + 1)
947 948 949
                        bandmeta = bandmeta_dict[bidx]
                        # meta2write = dict((k, repr(v)) for k, v in self.metadata.band_meta.items() if v is not np.nan)
                        band.SetMetadata(bandmeta)
950 951

                        if 'band_names' in envi_metadict:
952
                            band.SetDescription(self.metadata.band_meta['band_names'][bidx].strip())
953

954 955
                        band.FlushCache()
                        del band
956

Daniel Scheffler's avatar
Daniel Scheffler committed
957 958
            ds_out.FlushCache()
            del ds_out
959 960 961

        else:
            src_ds = gdal.Open(self.filePath)
962 963 964
            if not src_ds:
                raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())

965 966
            gdal_Translate = get_gdal_func('Translate')
            gdal_Translate(out_path, src_ds, format=fmt, creationOptions=creationOptions)
967
            del src_ds
968

969 970 971 972 973 974 975 976 977
            # add band names
            if 'band_names' in envi_metadict:
                ds_out = gdal.Open(out_path)

                for bidx in range(self.bands):
                    band = ds_out.GetRasterBand(bidx + 1)
                    band.SetDescription(self.metadata.band_meta['band_names'][bidx])
                    del band

978 979 980 981 982 983 984 985
        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
986 987
        with open(out_path, 'wb') as outF:
            dill.dump(self, outF)
988 989 990 991 992 993 994 995 996

    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:
997 998
            cS, cE = xlim if isinstance(xlim, (tuple, list)) else (0, self.columns)
            rS, rE = ylim if isinstance(ylim, (tuple, list)) else (0, self.rows)
999 1000

            image2plot = self[rS:rE, cS:cE, band] if band is not None else self[rS:rE, cS:cE]
1001
            gt, prj = self.geotransform, self.projection
1002

1003
        transOpt = ['SRC_METHOD=NO_GEOTRANSFORM'] if tuple(gt) == (0, 1, 0, 0, 0, -1) else None
1004
        xdim, ydim = None, None
1005
        nodataVal = nodataVal if nodataVal is not None else self.nodata
1006 1007

        if res_factor != 1. and image2plot.shape[0] * image2plot.shape[1] > 1e6:  # shape > 1000*1000
1008 1009 1010 1011
            # 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)))
1012 1013 1014
            xdim, ydim = int(xdim), int(ydim)

        if xdim or ydim or out_prj:
1015
            from py_tools_ds.geo.raster.reproject import warp_ndarray
1016 1017 1018 1019 1020
            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)
1021 1022
                gt = list(gt)
                gt[3] = 0
1023 1024 1025 1026 1027 1028 1029

            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,
1030 1031
             interpolation='none', vmin=None, vmax=None, pmin=2, pmax=98, cmap=None, nodataVal=None,
             res_factor=None, interactive=False):
1032 1033 1034 1035 1036 1037 1038 1039 1040 1041
        """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:
1042 1043 1044 1045
        :param vmin:            darkest pixel value to be included in stretching
        :param vmax:            brightest pixel value to be included in stretching
        :param pmin:            percentage to be used for excluding the darkest pixels from stretching (default: 2)
        :param pmax:            percentage to be used for excluding the brightest pixels from stretching (default: 98)
1046 1047
        :param cmap:
        :param nodataVal:
Daniel Scheffler's avatar
Daniel Scheffler committed
1048 1049
        :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)
1050 1051 1052 1053 1054 1055 1056 1057
        :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
1058
        nodataVal = nodataVal if nodataVal is not None else self.nodata
Daniel Scheffler's avatar
Daniel Scheffler committed
1059 1060 1061
        image2plot, gt, prj = \
            self._get_plottable_image(xlim, ylim, band, boundsMap=boundsMap, boundsMapPrj=boundsMapPrj,
                                      res_factor=res_factor, nodataVal=nodataVal)
1062 1063

        # set color palette
1064
        palette = cmap if cmap else plt.get_cmap('gray')
1065
        if nodataVal is not None and np.std(image2plot) != 0:  # do not show nodata
1066
            image2plot = np.ma.masked_equal(image2plot, nodataVal)
1067
            vmin_auto, vmax_auto = \
1068
                np.nanpercentile(image2plot.compressed(), pmin), np.nanpercentile(image2plot.compressed(), pmax)
1069 1070
            palette.set_bad('aqua', 0)
        else:
1071
            vmin_auto, vmax_auto = np.nanpercentile(image2plot, pmin), np.nanpercentile(image2plot, pmax)
1072 1073 1074 1075

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

1076
        palette.set_over('1')
1077 1078
        palette.set_under('0')

1079 1080 1081 1082 1083 1084
        # check availability of holoviews
        if not util.find_spec('holoviews'):
            warnings.warn("Interactive mode requires holoviews. Install it by running, e.g., "
                          "'conda install --yes -c ioam bokeh holoviews'. Using non-interactive mode.")
            interactive = False

1085
        if interactive and image2plot.ndim == 3:
1086 1087 1088 1089 1090 1091 1092
            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)

1093
            image2plot = np.array(rescale_intensity(image2plot, in_range=(vmin, vmax)))
1094

Daniel Scheffler's avatar