def test_extract():
import georasters as gr
raster = os.path.join(DATA, 'pre1500.tif')
data = gr.from_file(raster)
(xmin,xsize,x,ymax,y,ysize)=data.geot
(x,y)=(xmin+2507*xsize, ymax+1425*ysize)
assert data.raster[gr.map_pixel(x,y,data.x_cell_size,data.y_cell_size,data.xmin,data.ymax)]==data.extract(x,y).max()
assert data.raster[gr.map_pixel(x,y,data.x_cell_size,data.y_cell_size,data.xmin,data.ymax)]==data.map_pixel(x,y)
def test_extract():
import georasters as gr
raster = os.path.join(DATA, 'pre1500.tif')
data = gr.from_file(raster)
(xmin, xsize, x, ymax, y, ysize) = data.geot
(x, y) = (xmin + 2507 * xsize, ymax + 1425 * ysize)
assert data.raster[gr.map_pixel(x, y, data.x_cell_size, data.y_cell_size,
data.xmin,
data.ymax)] == data.extract(x, y).max()
assert data.raster[gr.map_pixel(x, y, data.x_cell_size, data.y_cell_size,
data.xmin,
data.ymax)] == data.map_pixel(x, y)
def lu_extract(row):
try:
c, r = gr.map_pixel(row['gpsLongitude'], row['gpsLatitude'], GeoT[1], GeoT[-1], GeoT[0], GeoT[3])
lu = esa[c, r]
return lu
except IndexError:
print('coordinates {} {} at sea!'.format(row['gpsLongitude'], row['gpsLatitude']))
def lu_extract(row):
try:
c, r = gr.map_pixel(row[lon_col], row[lat_col], GeoT[1], GeoT[-1], GeoT[0], GeoT[3])
lu = pop[c, r]
return lu
except IndexError:
pass
def gps2pixel(points_coord, geot):
# transform gps coordinate to pixel
return np.flip(np.vstack(gr.map_pixel(points_coord[:,0], points_coord[:,1],geot[1],geot[-1], geot[0],geot[3])).T,1)
def watershed(flow_dir_file, lake_data, val=47):
"""
__orig_author__ = Rdebbout
Description
----------
given a flow direction grid, develop tif representing lake watershed
Parameters
----------
flow_dir_file : grid file representing flow direction. DIR file within HydroSHEDS
lake_data : object representing lake information including id and pour point lat/lon
val : value to set watershed cells
Output
---------
tif file of a lake's watershed including value attribute table
"""
#get information about original flow direction raster
#NDV = no data values , xysize= raster size , tf = geotransform
NDV, xsize, ysize, tf, Projection, DataType = gr.get_geo_info(
flow_dir_file)
#print (tf)
#load into georaster from source file
arr = gr.from_file(flow_dir_file)
(xmin, xsize, x, ymax, y, ysize) = arr.geot
#get pour point lon and lat from lake object
pp_lon, pp_lat = lake_data.pour_pt_lon, lake_data.pour_pt_lat
# Function to map location in pixel of raster array: https://github.com/ozak/georasters/blob/master/georasters/georasters.py
here = gr.map_pixel(pp_lon, pp_lat, xsize, ysize, xmin, ymax)
init = []
init = ring_cells(here)
hold = []
temp_hold = eval_ring(init, arr)
hold = temp_hold
#Altered this to deal with an issue when iterating across multiple lakes in original code
#for every cell in ring evaluate if it is flowing to the pour point, if so add it to the hold, temp_hold continues until exhausted
while len(temp_hold) > 0:
for h in temp_hold:
init = ring_cells(h)
temp_hold = eval_ring(init, arr)
hold += temp_hold
#Add target cell
hold.append(here)
hold = list(set(hold))
# try to update transform info(tf) and shrink array
dd = np.array(hold)
r_min, col_min = np.amin(dd, axis=0)
r_max, col_max = np.amax(dd, axis=0)
#added step for WGS84 data that is not projected
lon, lat = gr.map_pixel_inv(r_min, col_min, tf[1], tf[-1], tf[0], tf[3])
# shift transform to reduce NoData in the output raster
shifted_tf = (lon, tf[1], tf[2], lat, tf[4], tf[5])
# insert val into the cells of the raster that represent watershed
out = np.zeros(arr.shape)
for idx in hold:
out[idx] = val
#plus 1 deals with index starting at 0, these are counts of rows, columns
new = out[r_min:(r_max + 1), col_min:(col_max + 1)]
go = gr.GeoRaster(new, shifted_tf, 0)
go.projection = Projection
go.datatype = DataType
#Set name of files and create
lk_id = str(lake_data.id)
#create tif file
go.to_tiff(f"output/lkshed/{lk_id}_watershed")
df = make_rat(f"output/lkshed/{lk_id}_watershed.tif")
#export value attribute table
df2dbf(df, f"output/lkshed/{lk_id}_watershed.tif.vat.dbf")
# #cleanup to help take care of issues on iterative processing
# arr = 0
go = None
here = None
arr = None
out = None
new = None
dd = None
shifted_tf = None
gc.collect()
def map_indexes_geot(geot, point_x, point_y):
row, col = gr.map_pixel(point_x, point_y,
geot[1], geot[-1], geot[0], geot[3])
return row, col
def map_indexes(raster, point_x, point_y):
row, col = gr.map_pixel(point_x, point_y,
raster.x_cell_size, raster.y_cell_size, raster.xmin, raster.ymax)
return row, col
