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253 lines
8.1 KiB
Python
253 lines
8.1 KiB
Python
from ctypes import byref, c_double, c_int, c_void_p
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from django.contrib.gis.gdal.error import GDALException
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from django.contrib.gis.gdal.prototypes import raster as capi
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from django.contrib.gis.gdal.raster.base import GDALRasterBase
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from django.contrib.gis.shortcuts import numpy
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from django.utils.encoding import force_str
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from .const import (
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GDAL_COLOR_TYPES, GDAL_INTEGER_TYPES, GDAL_PIXEL_TYPES, GDAL_TO_CTYPES,
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)
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class GDALBand(GDALRasterBase):
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"""
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Wrap a GDAL raster band, needs to be obtained from a GDALRaster object.
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"""
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def __init__(self, source, index):
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self.source = source
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self._ptr = capi.get_ds_raster_band(source._ptr, index)
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def _flush(self):
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"""
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Call the flush method on the Band's parent raster and force a refresh
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of the statistics attribute when requested the next time.
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"""
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self.source._flush()
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self._stats_refresh = True
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@property
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def description(self):
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"""
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Return the description string of the band.
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"""
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return force_str(capi.get_band_description(self._ptr))
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@property
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def width(self):
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"""
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Width (X axis) in pixels of the band.
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"""
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return capi.get_band_xsize(self._ptr)
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@property
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def height(self):
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"""
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Height (Y axis) in pixels of the band.
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"""
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return capi.get_band_ysize(self._ptr)
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@property
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def pixel_count(self):
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"""
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Return the total number of pixels in this band.
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"""
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return self.width * self.height
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_stats_refresh = False
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def statistics(self, refresh=False, approximate=False):
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"""
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Compute statistics on the pixel values of this band.
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The return value is a tuple with the following structure:
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(minimum, maximum, mean, standard deviation).
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If approximate=True, the statistics may be computed based on overviews
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or a subset of image tiles.
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If refresh=True, the statistics will be computed from the data directly,
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and the cache will be updated where applicable.
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For empty bands (where all pixel values are nodata), all statistics
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values are returned as None.
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For raster formats using Persistent Auxiliary Metadata (PAM) services,
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the statistics might be cached in an auxiliary file.
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"""
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# Prepare array with arguments for capi function
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smin, smax, smean, sstd = c_double(), c_double(), c_double(), c_double()
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stats_args = [
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self._ptr, c_int(approximate), byref(smin), byref(smax),
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byref(smean), byref(sstd), c_void_p(), c_void_p(),
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]
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if refresh or self._stats_refresh:
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func = capi.compute_band_statistics
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else:
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# Add additional argument to force computation if there is no
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# existing PAM file to take the values from.
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force = True
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stats_args.insert(2, c_int(force))
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func = capi.get_band_statistics
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# Computation of statistics fails for empty bands.
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try:
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func(*stats_args)
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result = smin.value, smax.value, smean.value, sstd.value
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except GDALException:
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result = (None, None, None, None)
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self._stats_refresh = False
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return result
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@property
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def min(self):
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"""
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Return the minimum pixel value for this band.
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"""
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return self.statistics()[0]
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@property
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def max(self):
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"""
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Return the maximum pixel value for this band.
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"""
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return self.statistics()[1]
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@property
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def mean(self):
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"""
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Return the mean of all pixel values of this band.
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"""
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return self.statistics()[2]
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@property
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def std(self):
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"""
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Return the standard deviation of all pixel values of this band.
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"""
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return self.statistics()[3]
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@property
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def nodata_value(self):
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"""
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Return the nodata value for this band, or None if it isn't set.
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"""
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# Get value and nodata exists flag
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nodata_exists = c_int()
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value = capi.get_band_nodata_value(self._ptr, nodata_exists)
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if not nodata_exists:
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value = None
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# If the pixeltype is an integer, convert to int
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elif self.datatype() in GDAL_INTEGER_TYPES:
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value = int(value)
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return value
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@nodata_value.setter
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def nodata_value(self, value):
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"""
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Set the nodata value for this band.
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"""
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if value is None:
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if not capi.delete_band_nodata_value:
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raise ValueError('GDAL >= 2.1 required to delete nodata values.')
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capi.delete_band_nodata_value(self._ptr)
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elif not isinstance(value, (int, float)):
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raise ValueError('Nodata value must be numeric or None.')
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else:
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capi.set_band_nodata_value(self._ptr, value)
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self._flush()
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def datatype(self, as_string=False):
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"""
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Return the GDAL Pixel Datatype for this band.
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"""
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dtype = capi.get_band_datatype(self._ptr)
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if as_string:
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dtype = GDAL_PIXEL_TYPES[dtype]
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return dtype
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def color_interp(self, as_string=False):
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"""Return the GDAL color interpretation for this band."""
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color = capi.get_band_color_interp(self._ptr)
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if as_string:
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color = GDAL_COLOR_TYPES[color]
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return color
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def data(self, data=None, offset=None, size=None, shape=None, as_memoryview=False):
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"""
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Read or writes pixel values for this band. Blocks of data can
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be accessed by specifying the width, height and offset of the
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desired block. The same specification can be used to update
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parts of a raster by providing an array of values.
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Allowed input data types are bytes, memoryview, list, tuple, and array.
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"""
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offset = offset or (0, 0)
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size = size or (self.width - offset[0], self.height - offset[1])
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shape = shape or size
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if any(x <= 0 for x in size):
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raise ValueError('Offset too big for this raster.')
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if size[0] > self.width or size[1] > self.height:
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raise ValueError('Size is larger than raster.')
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# Create ctypes type array generator
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ctypes_array = GDAL_TO_CTYPES[self.datatype()] * (shape[0] * shape[1])
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if data is None:
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# Set read mode
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access_flag = 0
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# Prepare empty ctypes array
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data_array = ctypes_array()
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else:
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# Set write mode
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access_flag = 1
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# Instantiate ctypes array holding the input data
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if isinstance(data, (bytes, memoryview)) or (numpy and isinstance(data, numpy.ndarray)):
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data_array = ctypes_array.from_buffer_copy(data)
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else:
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data_array = ctypes_array(*data)
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# Access band
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capi.band_io(self._ptr, access_flag, offset[0], offset[1],
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size[0], size[1], byref(data_array), shape[0],
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shape[1], self.datatype(), 0, 0)
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# Return data as numpy array if possible, otherwise as list
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if data is None:
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if as_memoryview:
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return memoryview(data_array)
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elif numpy:
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# reshape() needs a reshape parameter with the height first.
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return numpy.frombuffer(
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data_array, dtype=numpy.dtype(data_array)
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).reshape(tuple(reversed(size)))
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else:
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return list(data_array)
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else:
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self._flush()
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class BandList(list):
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def __init__(self, source):
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self.source = source
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super().__init__()
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def __iter__(self):
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for idx in range(1, len(self) + 1):
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yield GDALBand(self.source, idx)
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def __len__(self):
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return capi.get_ds_raster_count(self.source._ptr)
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def __getitem__(self, index):
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try:
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return GDALBand(self.source, index + 1)
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except GDALException:
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raise GDALException('Unable to get band index %d' % index)
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