Python array.store方法代碼示例

# 需要導入模塊: from dask import array [as 別名]
# 或者: from dask.array import store [as 別名]
def compute_writer_results(results):
    """Compute all the given dask graphs `results` so that the files are saved.

    Args:
        results (iterable): Iterable of dask graphs resulting from calls to
                            `scn.save_datasets(..., compute=False)`
    """
    if not results:
        return

    sources, targets, delayeds = split_results(results)

    # one or more writers have targets that we need to close in the future
    if targets:
        delayeds.append(da.store(sources, targets, compute=False))

    if delayeds:
        da.compute(delayeds)

    if targets:
        for target in targets:
            if hasattr(target, 'close'):
                target.close() 

# 需要導入模塊: from dask import array [as 別名]
# 或者: from dask.array import store [as 別名]
def save_dataset(self, dataset, filename=None, fill_value=None,
                     compute=True, **kwargs):
        """Save the ``dataset`` to a given ``filename``.

        This method must be overloaded by the subclass.

        Args:
            dataset (xarray.DataArray): Dataset to save using this writer.
            filename (str): Optionally specify the filename to save this
                            dataset to. If not provided then `filename`
                            which can be provided to the init method will be
                            used and formatted by dataset attributes.
            fill_value (int or float): Replace invalid values in the dataset
                                       with this fill value if applicable to
                                       this writer.
            compute (bool): If `True` (default), compute and save the dataset.
                            If `False` return either a :doc:`dask:delayed`
                            object or tuple of (source, target). See the
                            return values below for more information.
            **kwargs: Other keyword arguments for this particular writer.

        Returns:
            Value returned depends on `compute`. If `compute` is `True` then
            the return value is the result of computing a
            :doc:`dask:delayed` object or running :func:`dask.array.store`.
            If `compute` is `False` then the returned value is either a
            :doc:`dask:delayed` object that can be computed using
            `delayed.compute()` or a tuple of (source, target) that should be
            passed to :func:`dask.array.store`. If target is provided the the
            caller is responsible for calling `target.close()` if the target
            has this method.

        """
        raise NotImplementedError(
            "Writer '%s' has not implemented dataset saving" % (self.name, )) 

# 需要導入模塊: from dask import array [as 別名]
# 或者: from dask.array import store [as 別名]
def save_image(self, img, filename=None, compute=True, **kwargs):
        """Save Image object to a given ``filename``.

        Args:
            img (trollimage.xrimage.XRImage): Image object to save to disk.
            filename (str): Optionally specify the filename to save this
                            dataset to. It may include string formatting
                            patterns that will be filled in by dataset
                            attributes.
            compute (bool): If `True` (default), compute and save the dataset.
                            If `False` return either a :doc:`dask:delayed`
                            object or tuple of (source, target). See the
                            return values below for more information.
            **kwargs: Other keyword arguments to pass to this writer.

        Returns:
            Value returned depends on `compute`. If `compute` is `True` then
            the return value is the result of computing a
            :doc:`dask:delayed` object or running :func:`dask.array.store`.
            If `compute` is `False` then the returned value is either a
            :doc:`dask:delayed` object that can be computed using
            `delayed.compute()` or a tuple of (source, target) that should be
            passed to :func:`dask.array.store`. If target is provided the the
            caller is responsible for calling `target.close()` if the target
            has this method.

        """
        raise NotImplementedError("Writer '%s' has not implemented image saving" % (self.name,)) 

# 需要導入模塊: from dask import array [as 別名]
# 或者: from dask.array import store [as 別名]
def _generate_tile_info(self):
        """Get numbered tile metadata."""
        x = self.x
        y = self.y
        ts = self.tile_shape
        tc = self.tile_count

        if self._tile_cache:
            for tile_info in self._tile_cache:
                yield tile_info

        for ty in range(tc[0]):
            for tx in range(tc[1]):
                tile_id = self._tile_identifier(ty, tx)
                tile_row_offset = ty * ts[0]
                tile_column_offset = tx * ts[1]

                # store tile data to an intermediate array
                # the tile may be larger than the remaining data, handle that:
                max_row_idx = min((ty + 1) * ts[0], self._rows) - (ty * ts[0])
                max_col_idx = min((tx + 1) * ts[1], self._cols) - (tx * ts[1])
                tile_slices = (slice(0, max_row_idx), slice(0, max_col_idx))
                data_slices = (slice(ty * ts[0], (ty + 1) * ts[0]),
                               slice(tx * ts[1], (tx + 1) * ts[1]))

                tmp_x = x[data_slices[1]]
                tmp_y = y[data_slices[0]]

                tile_info = TileInfo(
                    tc, self.image_shape, ts,
                    tile_row_offset, tile_column_offset, tile_id,
                    tmp_x, tmp_y, tile_slices, data_slices)
                self._tile_cache.append(tile_info)
                yield tile_info 

# 需要導入模塊: from dask import array [as 別名]
# 或者: from dask.array import store [as 別名]
def write_raster(path, array, **kwargs):
    """Write a dask array to a raster file

    If array is 2d, write array on band 1.
    If array is 3d, write data on each band

    Arguments:
        path {string} -- path of raster to write
        array {dask.array.Array} -- band array
        kwargs {dict} -- keyword arguments to delegate to rasterio.open

    Examples:
        # Write a single band raster
        >> red_band = read_raster_band("test.tif", band=1)
        >> write_raster("new.tif", red_band)

        # Write a multiband raster
        >> img = read_raster("test.tif")
        >> new_img = process(img)
        >> write_raster("new.tif", new_img)

    """
    if len(array.shape) != 2 and len(array.shape) != 3:
        raise TypeError('invalid shape (must be either 2d or 3d)')

    if is_dask_collection(array):
        with RasterioDataset(path, 'w', **kwargs) as dst:
            da.store(array, dst, lock=True)
    else:
        with rasterio.open(path, 'w', **kwargs) as dst:
            if len(array.shape) == 2:
                dst.write(array, 1)
            else:
                dst.write(array) 

# 需要導入模塊: from dask import array [as 別名]
# 或者: from dask.array import store [as 別名]
def to_geotiff(arr, path='./output.tif', proj=None, spec=None, bands=None, **kwargs):
    ''' Write out a geotiff file of the image

    Args:
        path (str): path to write the geotiff file to, default is ./output.tif
        proj (str): EPSG string of projection to reproject to
        spec (str): if set to 'rgb', write out color-balanced 8-bit RGB tif
        bands (list): list of bands to export. If spec='rgb' will default to RGB bands
    
    Returns:
        str: path the geotiff was written to'''
        
    assert has_rasterio, "To create geotiff images please install rasterio" 

    try:
        img_md = arr.rda.metadata["image"]
        x_size = img_md["tileXSize"]
        y_size = img_md["tileYSize"]
    except (AttributeError, KeyError):
        x_size = kwargs.get("chunk_size", 256)
        y_size = kwargs.get("chunk_size", 256)

    try:
        tfm = kwargs['transform'] if 'transform' in kwargs else arr.affine
    except:
        tfm = None

    dtype = arr.dtype.name if arr.dtype.name != 'int8' else 'uint8' 

    if spec is not None and spec.lower() == 'rgb':
        
        assert arr.options.get('dra'), 'To write RGB geotiffs, create your image option with `dra=True`'
        if bands is None:
            bands = arr._rgb_bands
        arr = arr[bands,...].astype(np.uint8)
        dtype = 'uint8'
    else:
        if bands is not None:
            arr = arr[bands,...]
    meta = {
        'width': arr.shape[2],
        'height': arr.shape[1],
        'count': arr.shape[0],
        'dtype': dtype,
        'driver': 'GTiff',
        'transform': tfm
    }
    if proj is not None:
        meta["crs"] = {'init': proj}

    if "tiled" in kwargs and kwargs["tiled"]:
        meta.update(blockxsize=x_size, blockysize=y_size, tiled="yes")

    with rasterio.open(path, "w", **meta) as dst:
        writer = rio_writer(dst)
        result = store(arr, writer, compute=False)
        result.compute(scheduler=threaded_get)
    
    return path 

# 需要導入模塊: from dask import array [as 別名]
# 或者: from dask.array import store [as 別名]
def save_datasets(self, datasets, compute=True, **kwargs):
        """Save all datasets to one or more files.

        Subclasses can use this method to save all datasets to one single
        file or optimize the writing of individual datasets. By default
        this simply calls `save_dataset` for each dataset provided.

        Args:
            datasets (iterable): Iterable of `xarray.DataArray` objects to
                                 save using this writer.
            compute (bool): If `True` (default), compute all of the saves to
                            disk. If `False` then the return value is either
                            a :doc:`dask:delayed` object or two lists to
                            be passed to a :func:`dask.array.store` call.
                            See return values below for more details.
            **kwargs: Keyword arguments to pass to `save_dataset`. See that
                      documentation for more details.

        Returns:
            Value returned depends on `compute` keyword argument. If
            `compute` is `True` the value is the result of a either a
            :func:`dask.array.store` operation or a :doc:`dask:delayed`
            compute, typically this is `None`. If `compute` is `False` then
            the result is either a :doc:`dask:delayed` object that can be
            computed with `delayed.compute()` or a two element tuple of
            sources and targets to be passed to :func:`dask.array.store`. If
            `targets` is provided then it is the caller's responsibility to
            close any objects that have a "close" method.

        """
        results = []
        for ds in datasets:
            results.append(self.save_dataset(ds, compute=False, **kwargs))

        if compute:
            LOG.info("Computing and writing results...")
            return compute_writer_results([results])

        targets, sources, delayeds = split_results([results])
        if delayeds:
            # This writer had only delayed writes
            return delayeds
        else:
            return targets, sources