baseclasses.py 73.8 KB
Newer Older
1 2 3 4
# -*- coding: utf-8 -*-

import os
import warnings
5
from importlib import util
6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
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
27 28 29 30
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
31
from py_tools_ds.geo.projection import prj_equal, WKT2EPSG, EPSG2WKT, isLocal
32 33
from py_tools_ds.geo.raster.conversion import raster2polygon
from py_tools_ds.geo.vector.topology \
34
    import get_footprint_polygon, polyVertices_outside_poly, fill_holes_within_poly
35 36
from py_tools_ds.geo.vector.geometry import boxObj
from py_tools_ds.io.raster.gdal import get_GDAL_ds_inmem
37
from py_tools_ds.compatibility.gdal import get_gdal_func
38
from py_tools_ds.numeric.numbers import is_number
39
from py_tools_ds.numeric.array import get_array_tilebounds
40 41 42 43

#  internal imports
from .subsetting import get_array_at_mapPos

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 94 95 96 97
            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
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
153 154 155 156 157 158 159 160
            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. " \
161
                                                     "Received %s." % type(list_bandnames)
162 163 164 165 166
            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))
167 168
            assert len(bN_dict) == self.bands, \
                'Bands must not have the same name. Received band list: %s' % list_bandnames
169 170 171

            self._bandnames = bN_dict

172 173 174 175 176 177 178 179 180 181 182 183
            # update bandnames in metadata
            if self._metadata is not None:
                self.metadata.loc['band_name', :] = list_bandnames
        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:
            self.metadata.loc['band_name', :] = list(self._bandnames.keys())

184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225
    @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."""

226
        return self.shape[2] if len(self.shape) > 2 else 1
227 228 229 230 231 232 233 234 235 236 237 238 239 240 241

    @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):
242
        """Get the GDAL GeoTransform of the associated image, e.g., (283500.0, 5.0, 0.0, 4464500.0, 0.0, -5.0)"""
243 244 245 246 247 248 249

        if self._geotransform:
            return self._geotransform
        elif not self.is_inmem:
            self.set_gdalDataset_meta()
            return self._geotransform
        else:
250
            return [0, 1, 0, 0, 0, -1]
251 252 253

    @geotransform.setter
    def geotransform(self, gt):
254 255
        assert isinstance(gt, (list, tuple)) and len(gt) == 6,\
            'geotransform must be a list with 6 numbers. Got %s.' % str(gt)
256

257
        for i in gt:
258
            assert is_number(i), "geotransform must contain only numbers. Got '%s' (type: %s)." % (i, type(i))
259

260
        self._geotransform = gt
261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282

    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].
        """

283
        def get_grid(gt, xgsd, ygsd): return [[gt[0], gt[0] + xgsd], [gt[3], gt[3] - ygsd]]
284 285 286 287 288 289 290 291 292 293 294 295 296
        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()
297
            return self._projection  # or "LOCAL_CS[\"MAP\"]"
298
        else:
299
            return ''  # '"LOCAL_CS[\"MAP\"]"
300 301 302 303

    @projection.setter
    def projection(self, prj):
        if self.filePath:
304
            assert self.projection is None or prj_equal(self.projection, prj), \
305
                "Cannot set %s.projection to the given value because it does not match the projection from the file " \
306
                "on disk." % self.__class__.__name__
307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341
        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
342
                self._nodata = self.find_noDataVal()
343 344 345 346 347 348
                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"
349
                              % (self.__class__.__name__, self.basename, self._nodata))
350 351 352 353 354 355 356 357 358 359 360 361 362 363 364
            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:
365
            self.calc_mask_nodata()  # sets self._mask_nodata
366 367 368 369 370 371 372 373 374 375 376
            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
377 378
            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
379
            geoArr_mask.prj = geoArr_mask.prj if geoArr_mask.prj else self.prj
380
            imName = "the %s '%s'" % (self.__class__.__name__, self.basename)
381 382 383 384

            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 ' \
385
                                                            'rows and columns as the %s itself.' % imName
386 387
            assert geoArr_mask.gt == self.gt, \
                'The geotransform of the given nodata mask for %s must match the geotransform of the %s itself. ' \
388
                'Got %s.' % (imName, self.__class__.__name__, geoArr_mask.gt)
389 390
            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.' \
391
                % (imName, self.__class__.__name__)
392 393

            self._mask_nodata = geoArr_mask
394 395 396 397 398 399
        else:
            del self.mask_nodata

    @mask_nodata.deleter
    def mask_nodata(self):
        self._mask_nodata = None
400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418

    @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
419 420
            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
421
            geoArr_mask.prj = geoArr_mask.prj if geoArr_mask.prj else self.prj
422
            imName = "the %s '%s'" % (self.__class__.__name__, self.basename)
423 424 425 426

            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 ' \
427
                                                            'rows and columns as the %s itself.' % imName
428 429
            assert geoArr_mask.gt == self.gt, \
                'The geotransform of the given bad data mask for %s must match the geotransform of the %s itself. ' \
430
                'Got %s.' % (imName, self.__class__.__name__, geoArr_mask.gt)
431 432
            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.' \
433
                % (imName, self.__class__.__name__)
434 435

            self._mask_baddata = geoArr_mask
436 437 438 439 440 441
        else:
            del self.mask_baddata

    @mask_baddata.deleter
    def mask_baddata(self):
        self._mask_baddata = None
442 443 444 445 446 447 448 449 450 451

    @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. '
452
            if False not in self.mask_nodata[:]:
453 454 455 456
                # do not run raster2polygon if whole image is filled with data
                self._footprint_poly = self.box.mapPoly
            else:
                try:
457 458
                    multipolygon = raster2polygon(self.mask_nodata.astype(np.uint8), self.gt, self.prj, exact=False,
                                                  progress=self.progress, q=self.q, maxfeatCount=10, timeout=3)
459
                    self._footprint_poly = fill_holes_within_poly(multipolygon)
460
                except (RuntimeError, TimeoutError):
461 462 463 464
                    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 "
465
                                      "%s." % (self.__class__.__name__, self.basename, self.nodata))
466 467 468
                    self._footprint_poly = self.box.mapPoly

            # validation
469 470 471 472
            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
473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502
            # 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))
503
            # for bn,idx in self.bandnames.items():
504 505 506 507 508 509 510 511 512 513
            #    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):
514
        assert isinstance(GDF, (GeoDataFrame, DataFrame)) and len(GDF.columns) == self.bands, \
515
            "%s.metadata can only be set with an instance of geopandas.GeoDataFrame of which the column number " \
516
            "corresponds to the band number of %s." % (self.__class__.__name__, self.__class__.__name__)
517 518 519 520 521
        self._metadata = GDF

    meta = alias_property('metadata')

    def __getitem__(self, given):
522
        if isinstance(given, (int, float, slice)) and self.ndim == 3:
523 524 525 526 527 528 529 530 531 532 533 534 535
            # 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:
536
                    return self.arr if self.ndim == 2 else self.arr[:, :, self.bandnames[given]]
537 538 539 540
                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.'
541
                                 % self.__class__.__name__)
542 543 544 545 546 547 548

        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()

549
            if len(given) == 3:
550 551

                # handle strings in the 3rd dim of 'given' -> convert them to a band index
552
                if isinstance(given[2], str):
553 554 555 556 557 558 559 560
                    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:
561
                            return self.arr if (self.ndim == 2 and band_idx == 0) else self.arr[:, :, band_idx]
562
                        else:
563 564
                            getitem_params = \
                                given[:2] if (self.ndim == 2 and band_idx == 0) else given[:2] + (band_idx,)
565 566 567 568 569 570 571
                            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
572
                elif self.ndim == 2 and given[2] == 0:
573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596
                    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.'
597
                                      % self.__class__.__name__)
598 599 600

    def __getattr__(self, attr):
        # check if the requested attribute can not be present because GeoArray has been instanced with an array
601 602
        if attr not in self.__dir__() and not self.is_inmem and attr in ['shape', 'dtype', 'geotransform',
                                                                         'projection']:
603 604
            self.set_gdalDataset_meta()

605 606 607
        if attr in self.__dir__():  # __dir__() includes also methods and properties
            return self.__getattribute__(attr)  # __getattribute__ avoids infinite loop
        elif hasattr(np.array([]), attr):
608 609
            return self[:].__getattribute__(attr)
        else:
610
            raise AttributeError("%s object has no attribute '%s'." % (self.__class__.__name__, attr))
611 612 613 614 615 616 617 618 619 620 621 622 623 624 625 626 627 628 629 630 631 632 633 634 635 636 637

    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
638
            arr = self[:, :, fromBand] if self.ndim == 3 and fromBand is not None else self[:]
639 640 641

            if self.nodata is None:
                self.mask_nodata = np.ones((self.rows, self.cols), np.bool)
642 643 644 645
            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)
646
            else:
647
                self.mask_nodata = \
648 649
                    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)
650

651 652 653 654 655 656 657 658
    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

659 660
        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)]
661 662 663 664
        # possVals==[]: all corners are filled with data; np.std(possVals)==0: noDataVal clearly identified

        if possVals:
            if np.std(possVals) != 0:
665 666 667 668 669 670
                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'
671 672 673 674 675
            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 "
676 677 678
                                  "the correct nodata value."
                                  % (possVals[0], self.basename, ('2 image corners' if len(possVals) == 2 else
                                                                  '1 image corner')))
679
                nodata = possVals[0]
680
        else:
681 682 683
            nodata = None

        return nodata
684

685 686 687 688 689 690 691 692 693 694
    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)
695 696 697
            if not ds:
                raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())

698
            # set private class variables (in order to avoid recursion error)
699 700
            self._shape = tuple([ds.RasterYSize, ds.RasterXSize] + ([ds.RasterCount] if ds.RasterCount > 1 else []))
            self._dtype = gdal_array.GDALTypeCodeToNumericTypeCode(ds.GetRasterBand(1).DataType)
701
            self._geotransform = list(ds.GetGeoTransform())
702 703

            # for some reason GDAL reads arbitrary geotransforms as (0, 1, 0, 0, 0, 1) instead of (0, 1, 0, 0, 0, -1)
704
            self._geotransform[5] = -abs(self._geotransform[5])  # => force ygsd to be negative
705

706 707
            # 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
708 709
            wkt = ds.GetProjection()
            self._projection = EPSG2WKT(WKT2EPSG(wkt)) if not isLocal(wkt) else ''
710

711 712 713 714
            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()
715

716
            # read global domain metadata
717 718
            # TODO check to specifically use the 'ENVI' metadata domain ds.GetMetadata('ENVI')
            global_meta = ds.GetMetadata()
719

720 721
            # read band domain metadata
            for b in range(self.bands):
722 723
                band = ds.GetRasterBand(b + 1)
                meta_gs = GeoSeries(band.GetMetadata())
724

725 726 727 728 729 730
                # 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

731 732 733 734 735
                # avoid double-call of set_gdalDataset_meta by setting self._metadata to default value
                self._metadata = \
                    self._metadata if self._metadata is not None else GeoDataFrame(columns=range(self.bands))

                # fill metadata
736
                self.metadata[b] = meta_gs
737
                del band
738

739
            del ds
740 741 742 743 744 745 746 747 748 749 750 751 752 753

        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)
754 755 756
        if not ds:
            raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())

757
        R, C, B = ds.RasterYSize, ds.RasterXSize, ds.RasterCount
758
        del ds
759

760
        # convert getitem_params to subset area to be read ##
761 762 763 764 765 766 767 768 769 770 771 772 773 774 775 776 777 778 779 780 781 782 783 784 785 786
        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
787
                elif isinstance(givenB, (tuple, list)):
788 789 790 791 792 793 794 795 796 797 798 799 800 801 802 803 804 805 806 807 808 809 810 811 812 813
                    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
814
        bL = [b if b >= 0 else (self.bands + b) for b in bL]
815 816

        # validate subset area bounds to be read
817 818 819 820 821 822 823
        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))
824 825

        # summarize requested array position in arr_pos
826
        # NOTE: # bandlist must be string because truth value of an array with more than one element is ambiguous
827 828 829
        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
830
        if self._arr_cache is not None and self._arr_cache['pos'] == arr_pos:
831
            out_arr = self._arr_cache['arr_cached']
832 833 834 835 836 837 838

        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
839 840
                if out_arr is None:
                    raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())
841 842 843 844
            else:
                ds = gdal.Open(path)
                if len(bL) == 1:
                    band = ds.GetRasterBand(bL[0] + 1)
845
                    out_arr = band.ReadAsArray(cS, rS, cE - cS + 1, rE - rS + 1)
846 847
                    if out_arr is None:
                        raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())
848
                    del band
849 850 851 852 853
                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)
854 855
                        if out_arr is None:
                            raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())
856
                        del band
857

858
                del ds
859 860

            # only set self.arr if the whole cube has been read (in order to avoid sudden shape changes)
861
            if out_arr.shape == self.shape:
862 863 864 865 866
                self.arr = out_arr

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

867 868
        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
869 870 871 872 873 874 875 876

    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.
877 878
        :param creationOptions: <list> GDAL creation options,
                                e.g., ["QUALITY=80", "REVERSIBLE=YES", "WRITE_METADATA=YES"]
879 880 881
        """

        if not self.q:
882 883
            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.'
884 885 886 887 888 889 890 891 892 893

        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:
894 895
            ds = get_GDAL_ds_inmem(self.arr, self.geotransform, self.projection,
                                   self.nodata)  # expects rows,columns,bands
896 897 898

            # set metadata
            if not self.metadata.empty:
899 900 901
                global_meta = {}

                # set band domain metadata
902
                for bidx in range(self.bands):
903
                    band = ds.GetRasterBand(bidx + 1)
904
                    meta2write = self.metadata[bidx].to_dict()
905
                    meta2write = dict((k, v) for k, v in meta2write.items() if v is not np.nan)
906 907

                    if 'band_name' in meta2write:
908
                        global_meta['Band_%s' % str(bidx + 1)] = meta2write['band_name']
909 910
                        del meta2write['band_name']

911
                    band.SetMetadata(meta2write)
912
                    del band
913

914 915 916
                # set global domain metadata
                ds.SetMetadata(global_meta)

917 918 919 920 921
                # 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
922

923 924
            driver.CreateCopy(out_path, ds, options=creationOptions if creationOptions else [])

925 926 927 928
            # 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
929 930 931

        else:
            src_ds = gdal.Open(self.filePath)
932 933 934
            if not src_ds:
                raise Exception('Error reading file:  ' + gdal.GetLastErrorMsg())

935 936
            gdal_Translate = get_gdal_func('Translate')
            gdal_Translate(out_path, src_ds, format=fmt, creationOptions=creationOptions)
937
            del src_ds
938 939 940 941 942 943 944 945 946

        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
947 948
        with open(out_path, 'wb') as outF:
            dill.dump(self, outF)
949 950 951 952 953 954 955 956 957

    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:
958 959
            cS, cE = xlim if isinstance(xlim, (tuple, list)) else (0, self.columns)
            rS, rE = ylim if isinstance(ylim, (tuple, list)) else (0, self.rows)
960 961

            image2plot = self[rS:rE, cS:cE, band] if band is not None else self[rS:rE, cS:cE]
962
            gt, prj = self.geotransform, self.projection
963

964
        transOpt = ['SRC_METHOD=NO_GEOTRANSFORM'] if tuple(gt) == (0, 1, 0, 0, 0, -1) else None
965
        xdim, ydim = None, None
966
        nodataVal = nodataVal if nodataVal is not None else self.nodata
967 968

        if res_factor != 1. and image2plot.shape[0] * image2plot.shape[1] > 1e6:  # shape > 1000*1000
969 970 971 972
            # 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)))
973 974 975
            xdim, ydim = int(xdim), int(ydim)

        if xdim or ydim or out_prj:
976
            from py_tools_ds.geo.raster.reproject import warp_ndarray
977 978 979 980 981
            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)
982 983
                gt = list(gt)
                gt[3] = 0
984 985 986 987 988 989 990

            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,
991 992
             interpolation='none', vmin=None, vmax=None, pmin=2, pmax=98, cmap=None, nodataVal=None,
             res_factor=None, interactive=False):
993 994 995 996 997 998 999 1000 1001 1002
        """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:
1003 1004 1005 1006
        :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)
1007 1008
        :param cmap:
        :param nodataVal:
Daniel Scheffler's avatar
Daniel Scheffler committed
1009 1010
        :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)
1011 1012 1013 1014 1015 1016 1017 1018
        :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
1019
        nodataVal = nodataVal if nodataVal is not None else self.nodata
Daniel Scheffler's avatar
Daniel Scheffler committed
1020 1021 1022
        image2plot, gt, prj = \
            self._get_plottable_image(xlim, ylim, band, boundsMap=boundsMap, boundsMapPrj=boundsMapPrj,
                                      res_factor=res_factor, nodataVal=nodataVal)
1023 1024

        # set color palette
1025
        palette = cmap if cmap else plt.get_cmap('gray')
1026
        if nodataVal is not None and np.std(image2plot) != 0:  # do not show nodata
1027
            image2plot = np.ma.masked_equal(image2plot, nodataVal)
1028
            vmin_auto, vmax_auto = \
1029
                np.nanpercentile(image2plot.compressed(), pmin), np.nanpercentile(image2plot.compressed(), pmax)
1030 1031
            palette.set_bad('aqua', 0)
        else:
1032
            vmin_auto, vmax_auto = np.nanpercentile(image2plot, pmin), np.nanpercentile(image2plot, pmax)
1033 1034 1035 1036

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

1037
        palette.set_over('1')
1038 1039
        palette.set_under('0')

1040 1041 1042 1043 1044 1045
        # 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

1046
        if interactive and image2plot.ndim == 3:
1047 1048 1049 1050 1051 1052 1053
            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)

1054
            image2plot = np.array(rescale_intensity(image2plot, in_range=(vmin, vmax)))
1055

1056 1057 1058 1059 1060 1061 1062
            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)
1063 1064 1065