spatial_analysis

functions to analyse data in raster and/or feature datasets to replace ArcGridDataProcessing

Assumptions:

  • map unit is meter

  • its cellsize is the same in both x and y direction

  • its reference position is on the lower left corner of the southwest cell

To do:

  • read and write arc

hydro_raster.spatial_analysis.arc_header_read(file_name, header_rows=6)

read the header of a asc file as a dictionary

Parameters:

  • file_name – (string) file name

  • header_rows – (int) number of header rows

Returns:

header: a dictionary with keys:

ncols: (int) number of columns

nrows: (int) number of rows

xllcorner: (int/float) x-coordinate of the lower left corner of the lower left cell of the grid

yllcorner: (int/float) y-coordinate of the lower left corner of the bottom left cell of the grid

cellsize: (int/float) the length of one square cell

NODATA_value: (int/float)|-9999 the value representing nodata cell

Return type:

dict

hydro_raster.spatial_analysis.arcgridread(file_name, header_rows=6, return_nan=True)

Read ArcGrid format raster file

Parameters:

  • file_name – (str) the file name to read data

  • header_rows – (int) the number of head rows of the asc file

Returns:

the data content dict: head of the raster to provide reference information of the grid tuple: outline extent of the grid (left, right, bottom, top)

Return type:

numpy array

Note

this function can also read compressed gz files

hydro_raster.spatial_analysis.arcgridwrite(file_name, array, header, compression=False)

write gird data into a ascii file

Parameters:

  • file_name – (str) the file name to write grid data. A compressed file will automatically add a suffix ‘.gz’

  • array – (int/float numpy array)

  • header – (dict) to provide reference information of the grid

  • compression – (logic) to inidcate whether compress the ascii file

Example:

gird = np.zeros((5,10))
grid[0,:] = -9999
grid[-1,:] = -9999
header = {'ncols':10, 'nrows':5, 'xllcorner':0, 'yllcorner':0,
          'cellsize':2, 'NODATA_value':-9999}
file_name = 'example_file.asc'
arcgridwrite(file_name, array, header, compression=False)
arcgridwrite(file_name, array, header, compression=True)
hydro_raster.spatial_analysis.byte_file_read(file_name)

Read file from a bytes object

hydro_raster.spatial_analysis.check_file_existence(file_name)

check whether a file exists

hydro_raster.spatial_analysis.combine_raster(asc_files, num_header_rows=6)

Combine a list of asc files to a DEM Raster

Parameters:

  • asc_files – a list of asc file names. All raster files have the same

  • cellsize. –

hydro_raster.spatial_analysis.compare_extent(extent0, extent1)

Compare and show the difference between two Raster extents

Parameters:

  • extent0 – objects or extent dicts to be compared

  • extent1 – objects or extent dicts to be compared

  • displaye – whether to show the extent in figures

Returns:

0 extent0>=extent1; 1 extent0<extent1; 2 extent0 and extent1 have intersections

Return type:

int

hydro_raster.spatial_analysis.extent2shape_points(extent)

Convert extent to a two-col numpy array of shape points

hydro_raster.spatial_analysis.header2extent(header)

convert a header dict to a 4-element tuple (left, right, bottom, top) all four elements shows the coordinates at the edge of a cell, not center

hydro_raster.spatial_analysis.map2sub(X, Y, geo_ref)

convert map coordinates to subscripts of the raster array according to geo_ref which is either a header or a geo_transform object from raster

Parameters:

  • X (scalar or numpy.ndarray) – Input X coordinate

  • Y (scalar or numpy.ndarray) – Input Y coordinate

  • geo_ref (_type_) – _description_

Returns:

rows and cols in the array

Return type:

tuple (int, int)

hydro_raster.spatial_analysis.meta2header(ras_meta)

Transfer rasterio meta object to a header dict

hydro_raster.spatial_analysis.shape_extent_to_header(shape, extent, nan_value=-9999)

Create a header dict with shape and extent of an array

hydro_raster.spatial_analysis.sub2map(rows, cols, header)

convert subscripts of a matrix to map coordinates rows, cols: subscripts of the data matrix, starting from 0

Parameters:

  • rows – rows in the array

  • cols – cols in the array

Returns:

X and Y coordinate values

hydro_raster.spatial_analysis.tif_read(file_name, read_extent=None)

read tif file (only the 1st band) and return array, header, crs and meta

Parameters:

  • file_name (str) – tif file name

  • read_extent (dict, optional) – extent window (left, right, bottom, top in map coordinates) to read part of the raster. Defaults to None.

Returns:

_description_

Return type:

_type_