Python gdal.GRA_Bilinear() Examples

The following are 3 code examples of gdal.GRA_Bilinear(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module gdal , or try the search function .
Example #1
Source File: modis_tg_halli.py    From hydrology with GNU General Public License v3.0 5 votes vote down vote up 
def reproject_dataset(dataset, output_file_name, wkt_from="+proj=sinu +lon_0=0 +x_0=0 +y_0=0 +a=6371007.181 +b=6371007.181 +units=m +no_defs", epsg_to=32643, pixel_spacing=1000, file_format='GTiff'):
    '''
    :param dataset: Modis subset name use gdal.GetSubdatasets()
    :param output_file_name: file location along with proper extension
    :param wkt_from: Modis wkt (default)
    :param epsg_to: integer default(32643)
    :param pixel_spacing: in metres
    :param file_format: default GTiff
    :return:
    '''
    wgs84 = osr.SpatialReference()
    wgs84.ImportFromEPSG(epsg_to)
    modis = osr.SpatialReference()
    modis.ImportFromProj4(wkt_from)
    tx = osr.CoordinateTransformation(modis, wgs84)
    g = gdal.Open(dataset)
    geo_t = g.GetGeoTransform()
    print geo_t
    x_size = g.RasterXSize
    y_size = g.RasterYSize
    (ulx, uly, ulz) = tx.TransformPoint(geo_t[0], geo_t[3])
    (lrx, lry, lrz) = tx.TransformPoint(geo_t[0] + (geo_t[1]*x_size), geo_t[3]+ (geo_t[5]*y_size))
    mem_drv = gdal.GetDriverByName(file_format)
    dest = mem_drv.Create(output_file_name, int((lrx-ulx)/pixel_spacing), int((uly - lry)/pixel_spacing), 1, gdal.GDT_Float32)
    new_geo = ([ulx, pixel_spacing, geo_t[2], uly, geo_t[4], -pixel_spacing])
    dest.SetGeoTransform(new_geo)
    dest.SetProjection(wgs84.ExportToWkt())
    gdal.ReprojectImage(g, dest, modis.ExportToWkt(), wgs84.ExportToWkt(), gdal.GRA_Bilinear)
    print "reprojected"
Example #2
Source File: functions.py    From hants with Apache License 2.0 4 votes vote down vote up 
def Raster_to_Array(input_tiff, ll_corner, x_ncells, y_ncells,
                    values_type='float32'):
    """
    Loads a raster into a numpy array
    """
    # Input
    inp_lyr = gdal.Open(input_tiff)
    inp_srs = inp_lyr.GetProjection()
    inp_transform = inp_lyr.GetGeoTransform()
    inp_band = inp_lyr.GetRasterBand(1)
    inp_data_type = inp_band.DataType

    cellsize_x = inp_transform[1]
    rot_1 = inp_transform[2]
    rot_2 = inp_transform[4]
    cellsize_y = inp_transform[5]
    NoData_value = inp_band.GetNoDataValue()

    ll_x = ll_corner[0]
    ll_y = ll_corner[1]

    top_left_x = ll_x
    top_left_y = ll_y - cellsize_y*y_ncells

    # Change start point
    temp_path = tempfile.mkdtemp()
    temp_driver = gdal.GetDriverByName('GTiff')
    temp_tiff = os.path.join(temp_path, os.path.basename(input_tiff))
    temp_source = temp_driver.Create(temp_tiff, x_ncells, y_ncells,
                                     1, inp_data_type)
    temp_source.GetRasterBand(1).SetNoDataValue(NoData_value)
    temp_source.SetGeoTransform((top_left_x, cellsize_x, rot_1,
                                 top_left_y, rot_2, cellsize_y))
    temp_source.SetProjection(inp_srs)

    # Snap
    gdal.ReprojectImage(inp_lyr, temp_source, inp_srs, inp_srs,
                        gdal.GRA_Bilinear)
    temp_source = None

    # Read array
    d_type = pd.np.dtype(values_type)
    out_lyr = gdal.Open(temp_tiff)
    array = out_lyr.ReadAsArray(0, 0, out_lyr.RasterXSize,
                                out_lyr.RasterYSize).astype(d_type)
    array[pd.np.isclose(array, NoData_value)] = pd.np.nan
    out_lyr = None

    return array
Example #3
Source File: functions.py    From wa with Apache License 2.0 4 votes vote down vote up 
def Raster_to_Array(input_tiff, ll_corner, x_ncells, y_ncells,
                    values_type='float32'):
    """
    Loads a raster into a numpy array
    """
    # Input
    inp_lyr = gdal.Open(input_tiff)
    inp_srs = inp_lyr.GetProjection()
    inp_transform = inp_lyr.GetGeoTransform()
    inp_band = inp_lyr.GetRasterBand(1)
    inp_data_type = inp_band.DataType

    cellsize_x = inp_transform[1]
    rot_1 = inp_transform[2]
    rot_2 = inp_transform[4]
    cellsize_y = inp_transform[5]
    NoData_value = inp_band.GetNoDataValue()

    ll_x = ll_corner[0]
    ll_y = ll_corner[1]

    top_left_x = ll_x
    top_left_y = ll_y - cellsize_y*y_ncells

    # Change start point
    temp_path = tempfile.mkdtemp()
    temp_driver = gdal.GetDriverByName('GTiff')
    temp_tiff = os.path.join(temp_path, os.path.basename(input_tiff))
    temp_source = temp_driver.Create(temp_tiff, x_ncells, y_ncells,
                                     1, inp_data_type)
    temp_source.GetRasterBand(1).SetNoDataValue(NoData_value)
    temp_source.SetGeoTransform((top_left_x, cellsize_x, rot_1,
                                 top_left_y, rot_2, cellsize_y))
    temp_source.SetProjection(inp_srs)

    # Snap
    gdal.ReprojectImage(inp_lyr, temp_source, inp_srs, inp_srs,
                        gdal.GRA_Bilinear)
    temp_source = None

    # Read array
    d_type = pd.np.dtype(values_type)
    out_lyr = gdal.Open(temp_tiff)
    array = out_lyr.ReadAsArray(0, 0, out_lyr.RasterXSize,
                                out_lyr.RasterYSize).astype(d_type)
    array[pd.np.isclose(array, NoData_value)] = pd.np.nan
    out_lyr = None

    return array