Raster

To do:

  1. Read, write, analyze, and visualise gridded raster data

  2. Convert shape data to raster data

class IO.Raster.Raster(source_file=None, array=None, header=None, xllcorner=0, yllcorner=0, cellsize=100, NODATA_value=-9999, crs=None, num_header_rows=6)

To deal with raster data with a ESRI ASCII or GTiff format

source_file

file name to read grid data

output_file

file name to write a raster object

array

a numpy array storing grid cell values

header

a dict storing reference information of the grid, with keys: nrows, ncols, xllcorner, yllcorner, cellsize, NODATA_value

extent

a tuple storing outline limits of the raster (left, right, bottom, top)

shape

shape of the Raster value array

cellsize

the length of each square cell

extent_dict

a dictionary storing outline limits of the raster

wkt

(string) the Well-Known_Text (wkt) projection information

__init__(source_file=None, array=None, header=None, xllcorner=0, yllcorner=0, cellsize=100, NODATA_value=-9999, crs=None, num_header_rows=6)

Initialise the object

Parameters

  • source_file – name of a asc/tif file if a file read is needed

  • array – values in each raster cell [a numpy array]

  • header – georeference of the raster [a dictionary containing 6 keys] nrows, nclos [int] cellsize, xllcorner, yllcorner NODATA_value

  • crs – coordinate reference system, either epsg(epsg code, int) or wkt(string), or a rasterio.crs object

Example: define a raster object with a random array

array = np.random.rand(10, 10) header = {‘ncols’:array.shape[1], ‘nrows’:array.shape[0],

‘xllcorner’:0, ‘yllcorner’:1, ‘cellsize’:100, ‘NODATA_value’:-9999}

obj_ras = Raster(array=array, header=header) obj_ras.mapshow() %plot map

assign_to(new_header)

Assign_to the object to a new grid defined by new_header

If their cellsizes are not equal, the original Raster will be resampled to the target grid.

Returns

A newly defined grid

Return type

Raster

clip(clip_mask=None)

clip raster according to a mask

Parameters

mask – 1. string name of a shapefile or 2. 2-col numpy array giving X and Y coords in each column to shape the mask polygon

Returns

a new raster object

Return type

Raster

get_meta(src_epsg=27700)

Get rasterio meta data

get_summary()

Get information summary of the object

Returns

summary – information summary of the object.

Return type

dict

grid_interpolate(value_grid, method='nearest')

Interpolate values of a grid to all cells on the Raster object

2D interpolate

Parameters

  • value_grid – a grid file string or Raster object

  • method – {‘linear’, ‘nearest’, ‘cubic’}, optional Method of interpolation.

Returns

the interpolated grid with the same size of the self

object

Return type

numpy array

grid_resample_nearest(newsize)

resample a grid to a new grid resolution via nearest interpolation

Alias: GridResample

hillshade(**kwargs)

Draw a hillshade map

mapshow(**kwargs)

Display raster data without projection

Parameters

  • figname – str, the file name to export map

  • figsize – tuple, the size of map

  • dpi – scalar, The resolution in dots per inch

  • cax_str – str, the title of the colorbar

  • relocate – True|False, relocate the origin of the grid to (0, 0)

  • scale_ratio – 1|1000, axis unit 1 m or 1000 meter

  • vmin – define the data range that the colormap covers

  • vmax – define the data range that the colormap covers

  • ytick_labelrotation – degree to rotate tick labels on y axis

Example

mapshow(ax=ax, figname=’my_fig’, figsize=(6, 8), dpi=300,

title=’My map’, cax=True, cax_str=’Meter’, relocate=False, scale_ratio=1000, ytick_labelrotation=90)

paste_on(obj_large, ignore_nan=True)

Paste the object to a larger grid defined by obj_large and replace corresponding grid values with the object array

If their cellsizes MUST be equal

point_interpolate(points, values, method='nearest')

Interpolate values of 2D points to all cells on the Raster object

2D interpolate

Parameters

  • points – ndarray of floats, shape (n, 2) Data point coordinates. Can either be an array of shape (n, 2), or a tuple of ndim arrays.

  • values – ndarray of float or complex, shape (n, ) Data values.

  • method – {‘linear’, ‘nearest’, ‘cubic’}, optional Method of interpolation.

rankshow(**kwargs)

Display array values in ranks

Parameters

  • breaks – list of values to define rank. Array values lower than the first break value are set as nodata.

  • color – color series of the ranks

  • ylabelrotation – scalar giving degree to rotate yticklabel

  • legend_kw – dict, keyword arguments to set legend. A colobar rather than a legend be displayed if legend_kw is None.

  • **kwargs – keywords argument of function imshow

Example

rankshow(figname=None, figsize=None,

dpi=200, ax=None, color=’Blues’, breaks=[0.2, 0.3, 0.5, 1, 2], legend_kw={‘loc’:’upper left’, ‘facecolor’:None,

‘fontsize’:’small’, ‘title’:’depth(m)’, ‘labelspacing’:0.1},

ytick_labelrotation=None, relocate=False, scale_ratio=1, alpha=1)

rasterize(shp_filename)
rasterize the shapefile to the raster object and return a bool array

with Ture value in and on the polygon/polyline

Parameters

shp_filename – string for shapefile name, or a list of shapefile geometry with attributes ‘type’ and ‘coordinates’

Returns

an array of True|False values masking the shapefile

Return type

index_array

rect_clip(clip_extent)

clip raster according to a rectangle extent

Parameters

clip_extent – list of [left, right, bottom, top]

Returns

a new raster object

Return type

Raster

reproject(dst_epsg, output_file=None)

Reproject the raster to a different coordinate referenece system

Parameters

  • output_file – a string to give output file name

  • src_epsg – int scalar to give EPSG code of the coordinate reference system of the original dataset, default is 27700 for BNG

Returns

destination rasterio dataset

Return type

dst_rio

resample(new_cellsize, method='bilinear')

Resample the raster object to a new resolution

Parameters

  • new_cellsize – scalar, the resoltion of the new raster object

  • method – string, one of the values including ‘nearest’, ‘bilinear’,

  • 'cubic' –

  • 'cubic_spline' –

  • 'lanczos' –

  • 'average' –

  • 'mode' –

  • 'gauss' –

:param : :param ‘max’: :param ‘min’: :param ‘med’: :param ‘q1’: :param ‘q3’:

Returns

Raster object

set_crs(crs)

set reference coordinate system :param crs: epsg code|wkt|asterio.crs object :type crs: int|string|rasterio.crs object

to_points()

Get X and Y coordinates of all raster cells

Returns

coordinates of the raster object

Return type

numpy array

vectorshow(obj_y, **kwargs)

plot velocity map of U and V, whose values stored in two raster objects seperately

write(output_file, compression=False)

Export to a file, tif, asc, txt, or gz :param output_file: file name, ends with tif, asc, txt, or gz. :type output_file: string :param compression: whether compress or not. The default is False. :type compression: logical, optional

Return type

None.

write_asc(output_file, compression=False, export_prj=False)

write raster as asc format file

Alias: Write_asc

Parameters

  • output_file – output file name

  • compression – logic, whether compress write the asc file as gz

write_tif(output_file, src_epsg=27700)

Convert to a rasterio dataset

Parameters

  • output_file – a string to give output file name

  • src_epsg – int scalar to give EPSG code of the coordinate reference system of the original dataset, default is 27700 for BNG

IO.Raster.main()

Main function

IO.Raster.merge(obj_origin, obj_target, resample_method='bilinear')

Merge the obj_origin to obj_target

assign grid values in the origin Raster to the cooresponding grid cells in the target object. If cellsize are not equal, the origin Raster will be firstly resampled to the target object.

Parameters

  • obj_origin – (Raster) original raster

  • obj_target – (Raster) target raster