Python affine.Affine方法代碼示例

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def set_bbox(self, new_bbox):
        """
        Sets new bbox while maintaining the same cell dimensions. Updates
        self.affine and self.shape. Also resets self.mask.

        Note that this method rounds the given bbox to match the existing
        cell dimensions.

        Parameters
        ----------
        new_bbox : tuple of floats (length 4)
                   (xmin, ymin, xmax, ymax)
        """
        affine = self.affine
        xmin, ymin, xmax, ymax = new_bbox
        ul = np.around(~affine * (xmin, ymax)).astype(int)
        lr = np.around(~affine * (xmax, ymin)).astype(int)
        xmin, ymax = affine * tuple(ul)
        shape = tuple(lr - ul)[::-1]
        new_affine = Affine(affine.a, affine.b, xmin,
                            affine.d, affine.e, ymax)
        self.affine = new_affine
        self.shape = shape
        #TODO: For now, simply reset mask
        self.mask = np.ones(shape, dtype=np.bool) 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def set_indices(self, new_indices):
        """
        Updates self.affine and self.shape to correspond to new indices representing
        a new bounding rectangle. Also resets self.mask.

        Parameters
        ----------
        new_indices : tuple of ints (length 4)
                      (xmin_index, ymin_index, xmax_index, ymax_index)
        """
        affine = self.affine
        assert all((isinstance(ix, int) for ix in new_indices))
        ul = np.asarray((new_indices[0], new_indices[3]))
        lr = np.asarray((new_indices[2], new_indices[1]))
        xmin, ymax = affine * tuple(ul)
        shape = tuple(lr - ul)[::-1]
        new_affine = Affine(affine.a, affine.b, xmin,
                            affine.d, affine.e, ymax)
        self.affine = new_affine
        self.shape = shape
        #TODO: For now, simply reset mask
        self.mask = np.ones(shape, dtype=np.bool) 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def global_reader(value=None):
    array = np.ma.masked_array(
        np.empty(shape=(360, 720), dtype=np.float32, order="C"),
        np.empty(shape=(360, 720), dtype=np.bool, order="C"),
    )
    if value is None:
        array.mask.fill(True)
    else:
        array.fill(value)
        array.mask.fill(False)
    transform = Affine(-180.0, 0.5, 0.0, 90.0, 0.0, -0.5)
    reader = Mock(spec=DatasetReader)
    reader.read.return_value = array
    reader.shape = array.shape
    reader.transform = transform
    reader.bounds = (-180.0, -90.0, 180.0, 90.0)
    reader.window.return_value = ((0, 359), (0, 719))
    reader.window_transform.return_value = transform
    return reader 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def bounds_to_ranges(out_bounds=None, in_affine=None, in_shape=None):
    """
    Return bounds range values from geolocated input.

    Parameters
    ----------
    out_bounds : tuple
        left, bottom, right, top
    in_affine : Affine
        input geolocation
    in_shape : tuple
        input shape

    Returns
    -------
    minrow, maxrow, mincol, maxcol
    """
    return itertools.chain(
        *from_bounds(
            *out_bounds, transform=in_affine, height=in_shape[-2], width=in_shape[-1]
        ).round_lengths(pixel_precision=0).round_offsets(pixel_precision=0).toranges()
    ) 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def _morpho(self, scount):
        aff = self._aff * affine.Affine.translation(-scount, -scount)
        return Footprint(
            gt=aff.to_gdal(),
            rsize=(self.rsize + 2 * scount),
        ) 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def size(self):
        """Spatial distances: (||raster left - raster right||, ||raster top - raster bottom||)"""
        return np.abs(~affine.Affine.rotation(self.angle) * self.diagvec, dtype=np.float64) 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def rlength(self):
        """Pixel quantity: pixel count in the outer ring"""
        rx, ry = self.rsize
        # Convert to int before multiplication to avoid overflow
        inner_area = max(0, int(rx) - 2) * max(0, int(ry) - 2)
        return self.rarea - inner_area

    # Accessors - Affine transformations ******************************************************** ** 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def scale(self):
        """Spatial vector: scale used in the affine transformation, np.abs(scale) == pxsize"""
        aff = ~affine.Affine.rotation(self.angle)
        tl = np.asarray(aff * self.tl)
        br = np.asarray(aff * self.br)
        return np.asarray((br - tl) / self.rsize, dtype=np.float64) 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def ResampleRaster(InputRasterFile,OutputRasterFile,XResolution,YResolution=None,Format="ENVI"):

    """
    Description goes here...

    MDH

    """

    # import modules
    import rasterio, affine
    from rasterio.warp import reproject, Resampling

    # read the source raster
    with rasterio.open(InputRasterFile) as src:
        Array = src.read()
        OldResolution = src.res

        #setup output resolution
        if YResolution == None:
            YResolution = XResolution
        NewResolution = (XResolution,YResolution)


        # setup the transform to change the resolution
        XResRatio = OldResolution[0]/NewResolution[0]
        YResRatio = OldResolution[1]/NewResolution[1]
        NewArray = np.empty(shape=(Array.shape[0], int(round(Array.shape[1] * XResRatio)), int(round(Array.shape[2] * YResRatio))))
        Aff = src.affine
        NewAff = affine.Affine(Aff.a/XResRatio, Aff.b, Aff.c, Aff.d, Aff.e/YResRatio, Aff.f)

        # reproject the raster
        reproject(Array, NewArray, src_transform=Aff, dst_transform=NewAff, src_crs = src.crs, dst_crs = src.crs, resample=Resampling.bilinear)

        # write results to file
        with rasterio.open(OutputRasterFile, 'w', driver=src.driver, \
                            height=NewArray.shape[1],width=NewArray.shape[2], \
                            nodata=src.nodata,dtype=str(NewArray.dtype), \
                            count=src.count,crs=src.crs,transform=NewAff) as dst:
            dst.write(NewArray) 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def ConvertRaster2LatLong(InputRasterFile,OutputRasterFile):

    """
    Convert a raster to lat long WGS1984 EPSG:4326 coordinates for global plotting

    MDH

    """

    # import modules
    import rasterio
    from rasterio.warp import reproject, calculate_default_transform as cdt, Resampling

    # read the source raster
    with rasterio.open(InputRasterFile) as src:
        #get input coordinate system
        Input_CRS = src.crs
        # define the output coordinate system
        Output_CRS = {'init': "epsg:4326"}
        # set up the transform
        Affine, Width, Height = cdt(Input_CRS,Output_CRS,src.width,src.height,*src.bounds)
        kwargs = src.meta.copy()
        kwargs.update({
            'crs': Output_CRS,
            'transform': Affine,
            'affine': Affine,
            'width': Width,
            'height': Height
        })

        with rasterio.open(OutputRasterFile, 'w', **kwargs) as dst:
            for i in range(1, src.count+1):
                reproject(
                    source=rasterio.band(src, i),
                    destination=rasterio.band(dst, i),
                    src_transform=src.affine,
                    src_crs=src.crs,
                    dst_transform=Affine,
                    dst_crs=Output_CRS,
                    resampling=Resampling.bilinear) 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def __init__(self, affine, shape, mask=None, nodata=None,
                 crs=pyproj.Proj(_pyproj_init),
                 y_coord_ix=0, x_coord_ix=1):
        if affine is not None:
            self.affine = affine
        else:
            self.affine = Affine(0,0,0,0,0,0)
        super().__init__(shape=shape, mask=mask, nodata=nodata, crs=crs,
                         y_coord_ix=y_coord_ix, x_coord_ix=x_coord_ix) 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def affine(self, new_affine):
        assert(isinstance(new_affine, Affine))
        self._affine = new_affine 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def __init__(self, affine=Affine(0,0,0,0,0,0), shape=(1,1), nodata=0,
                 crs=pyproj.Proj(_pyproj_init),
                 mask=None):
        self.affine = affine
        self.shape = shape
        self.nodata = nodata
        self.crs = crs
        # TODO: Mask should be a raster, not an array
        if mask is None:
            self.mask = np.ones(shape)
        self.grids = [] 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def defaults(self):
        props = {
            'affine' : Affine(0,0,0,0,0,0),
            'shape' : (1,1),
            'nodata' : 0,
            'crs' : pyproj.Proj(_pyproj_init),
        }
        return props 

# 需要導入模塊: import affine [as 別名]
# 或者: from affine import Affine [as 別名]
def nearest_cell(self, x, y, affine=None, snap='corner'):
        """
        Returns the index of the cell (column, row) closest
        to a given geographical coordinate.
 
        Parameters
        ----------
        x : int or float
            x coordinate.
        y : int or float
            y coordinate.
        affine : affine.Affine
                 Affine transformation that defines the translation between
                 geographic x/y coordinate and array row/column coordinate.
                 Defaults to self.affine.
        snap : str
               Indicates the cell indexing method. If "corner", will resolve to 
               snapping the (x,y) geometry to the index of the nearest top-left 
               cell corner. If "center", will return the index of the cell that 
               the geometry falls within.
        Returns
        -------
        x_i, y_i : tuple of ints
                   Column index and row index
        """
        if not affine:
            affine = self.affine
        try:
            assert isinstance(affine, Affine)
        except:
            raise TypeError('affine must be an Affine instance.')
        snap_dict = {'corner': np.around, 'center': np.floor}
        col, row = snap_dict[snap](~affine * (x, y)).astype(int)
        return col, row