def DinfFlowDir():
import argparse
parser = argparse.ArgumentParser(
description='Assigns a flow direction based on the D-infinity flow'
' method using the steepest slope of a triangular facet (Tarboton, '
'1997, "A New Method for the Determination of Flow Directions and '
'Contributing Areas in Grid Digital Elevation Models," Water Resources'
' Research, 33(2): 309-319).')
parser.add_argument('Input_Pit_Filled_Elevation',
help='The input pit-filled elevation file in '
'geotiff format.',
)
parser.add_argument('Input_Number_of_Chunks',
help="The approximate number of chunks that the input "
'file will be divided into for processing (potentially'
' on multiple processors).', type=int, default=1, nargs='?')
parser.add_argument('Output_D_Infinity_Flow_Direction',
help='Output filename for the flow direction. Default'
' value = ang.tif .', default='ang.tif', nargs='?')
parser.add_argument('Output_D_Infinity_Slope',
help='Output filename for the flow direction. Default'
' value = mag.tif .', default='mag.tif', nargs='?')
args = parser.parse_args()
fn = args.Input_Pit_Filled_Elevation
n_chunks = args.Input_Number_of_Chunks
fn_ang = args.Output_D_Infinity_Flow_Direction
fn_mag = args.Output_D_Infinity_Slope
from pydem.dem_processing import DEMProcessor
dem_proc = DEMProcessor(fn)
shape = dem_proc.data.shape
chunk_size = max(shape[0], shape[1]) / n_chunks
dem_proc.chunk_size_slp_dir = chunk_size
dem_proc.calc_slopes_directions()
dem_proc.save_array(dem_proc.mag, fn_mag, as_int=False)
dem_proc.save_array(dem_proc.direction, fn_ang, as_int=False)
if __name__ == "__main__":
from pydem.test_pydem import get_test_data
from pydem.dem_processing import DEMProcessor
from pydem.test_pydem import make_file_names
import sys
if len(sys.argv) <= 1:
testnum = 30 # Default test number
NN = 64 # Resolution of tile
# Get test data and create DEMProcessor
elev, ang, test_data = get_test_data(testnum, NN)
filename = make_file_names(testnum, NN)['fel']
dem_proc = DEMProcessor(filename, dx_dy_from_file=False)
# Calculate magnitude and direction of slopes
mag, direction = dem_proc.calc_slopes_directions()
# Calculate UCA/TWI on entire tile
area1 = dem_proc.calc_uca(0)
twi1 = dem_proc.calc_twi()
# Calculate UCA/TWI on chunks
dem_proc.resolve_edges = True # If false, won't do edge resolution
dem_proc.chunk_size_uca = 9 # Chunk size
dem_proc.chunk_overlap_uca = 3 #Overlap between chunks
area2 = dem_proc.calc_uca(0)
twi2 = dem_proc.calc_twi()
if testnum >= 28:
filename = make_file_names(testnum, NN)["elev"]
else:
filename = make_file_names(testnum, NN)["fel"]
elev, ang, test_data = get_test_data(testnum, NN)
# Make the filenames of the results
filename2 = make_file_names(testnum, NN)["uca"]
if os.path.exists(filename2):
uca_file = GdalReader(file_name=filename2)
uca, = uca_file.raster_layers
# Make the pydem Processor object and process the elevation
dem_proc = DEMProcessor(filename, dx_dy_from_file=dx_dy_from_file)
mag, direction = dem_proc.calc_slopes_directions()
area = dem_proc.calc_uca(0)
twi = dem_proc.calc_twi()
#
# Now process using tauDEM
os.chdir("testtiff")
try:
os.remove("test_sca.tif")
os.remove("test_ang.tif")
os.remove("test_slp.tif")
except:
pass
cmd = 'dinfflowdir -fel "%s" -ang "%s" -slp "%s"' % (os.path.split(filename)[-1], "test_ang.tif", "test_slp.tif")
taudem._run(cmd)
if __name__ == "__main__":
from pydem.test_pydem import get_test_data
from pydem.dem_processing import DEMProcessor
from pydem.test_pydem import make_file_names
import sys, os
if len(sys.argv) <= 1:
testnum = 13 # Default test number
NN = 64 # Resolution of tile
# Get test data and create DEMProcessor
elev, ang, test_data = get_test_data(testnum, NN)
elev = elev.raster_data
dem_proc1 = DEMProcessor(elev)
# Calculate TWI
twi1 = dem_proc1.calc_twi()
# Stretch the latitude direction
lats = [0, 2] # degrees
lons = [0, 1] # degrees
dem_proc2 = DEMProcessor((elev, lats, lons))
twi2 = dem_proc2.calc_twi()
# plot results
import matplotlib.pyplot as plt
plt.matshow(twi1); plt.colorbar()
plt.title('TWI calculated from Array, dx/dy determined from array shape')
plt.matshow(dem_proc1.data); plt.colorbar()
plt.title('Elevation from Array (after fixing flats)')
"""
if __name__ == "__main__":
from pydem.test_pydem import get_test_data
from pydem.dem_processing import DEMProcessor
from pydem.test_pydem import make_file_names
import sys
if len(sys.argv) <= 1:
testnum = 30 # Default test number
NN = 64 # Resolution of tile
# Get test data and create DEMProcessor
elev, ang, test_data = get_test_data(testnum, NN)
filename = make_file_names(testnum, NN)['fel']
dem_proc = DEMProcessor(filename, dx_dy_from_file=False)
# Calculate magnitude and direction of slopes
mag, direction = dem_proc.calc_slopes_directions()
# Calculate UCA/TWI on entire tile
area1 = dem_proc.calc_uca(0)
twi1 = dem_proc.calc_twi()
# Calculate UCA/TWI on chunks
dem_proc.resolve_edges = True # If false, won't do edge resolution
dem_proc.chunk_size_uca = 9 # Chunk size
dem_proc.chunk_overlap_uca = 3 #Overlap between chunks
area2 = dem_proc.calc_uca(0)
twi2 = dem_proc.calc_twi()
if testnum >= 28:
filename = make_file_names(testnum, NN)['elev']
else:
filename = make_file_names(testnum, NN)['fel']
elev, ang, test_data = get_test_data(testnum, NN)
# Make the filenames of the results
filename2 = make_file_names(testnum, NN)['uca']
if os.path.exists(filename2):
uca_file = GdalReader(file_name=filename2)
uca, = uca_file.raster_layers
# Make the pydem Processor object and process the elevation
dem_proc = DEMProcessor(filename, dx_dy_from_file=dx_dy_from_file)
mag, direction = dem_proc.calc_slopes_directions()
area = dem_proc.calc_uca(0)
twi = dem_proc.calc_twi()
#
# Now process using tauDEM
os.chdir('testtiff')
try:
os.remove('test_sca.tif')
os.remove('test_ang.tif')
os.remove('test_slp.tif')
except:
pass
cmd = ('dinfflowdir -fel "%s" -ang "%s" -slp "%s"' %
(os.path.split(filename)[-1], 'test_ang.tif', 'test_slp.tif'))
sys.setrecursionlimit(1000000)
# Ori
tiffile = r'C:\Users\thril\Desktop\ETOPO1DEM_Bedrock_gridRegis\ETOPO1_Bed_g_geotiff.tif'
Oritif = gdal.Open(tiffile)
if Oritif is None:
print('cannot open tif')
sys.exit(1)
OritifPro = Oritif.GetProjection()
OritifTra = Oritif.GetGeoTransform()
tifband = Oritif.GetRasterBand(1)
tifData = tifband.ReadAsArray(0, 0, Oritif.RasterXSize, Oritif.RasterYSize)
print('over in data')
# pyDEM
dem_proc = DEMProcessor(tiffile)
dem_proc.fill_flats = False
print('begin cal TWI')
twi = dem_proc.calc_twi()
cols = np.size(twi, 0)
rows = np.size(twi, 1)
print('over pyDEM process')
# out
imgdriver = gdal.GetDriverByName('GTiff')
resultPath = 'C:\\Users\\thril\\Desktop\\ETOPO1DEM_Bedrock_gridRegis\\ETOPO1_TWI.tif'
resultds = imgdriver.Create(resultPath, cols, rows, 1, twi.DataType)
resultds.SetGeoTransform(OritifTra)
resultds.SetProjection(OritifPro)
resultds.GetRasterBand(1).WriteArray(twi)
resultds = None
def TWIDinf():
import argparse
parser = argparse.ArgumentParser(
description='Calculates a grid of topographic wetness index '
' which is the log_e(uca / mag), that is, the natural log of the ratio'
' of contributing area per unit contour length and the magnitude of '
' the slope. Note, this function takes the elevation '
'as an input, and it calculates the '
'slope, direction, and contributing area as intermediate steps.')
parser.add_argument('Input_Pit_Filled_Elevation',
help='The input pit-filled elevation file in '
'geotiff format.',
)
parser.add_argument('Input_Number_of_Chunks',
help="The approximate number of chunks that the input "
'file will be divided into for processing (potentially'
' on multiple processors).', type=int, default=1,
nargs='?')
parser.add_argument('Output_D_Infinity_TWI',
help='Output filename for the topographic wetness '
'index. Default value = twi.tif .', default='twi.tif',
nargs='?')
parser.add_argument('--save-all', '--sa',
help='If set, will save all intermediate files as well.',
action='store_true')
args = parser.parse_args()
fn = args.Input_Pit_Filled_Elevation
n_chunks = args.Input_Number_of_Chunks
fn_twi = args.Output_D_Infinity_TWI
sa = args.save_all
from pydem.dem_processing import DEMProcessor
dem_proc = DEMProcessor(fn)
shape = dem_proc.data.shape
chunk_size = max(shape[0], shape[1]) / n_chunks
dem_proc.chunk_size_slp_dir = chunk_size
dem_proc.chunk_size_uca = chunk_size
dem_proc.calc_slopes_directions()
dem_proc.calc_uca()
if sa:
dem_proc.save_array(dem_proc.mag, 'mag.tif', as_int=False)
dem_proc.save_array(dem_proc.direction, 'ang.tif', as_int=False)
dem_proc.save_array(dem_proc.uca, 'uca.tif', as_int=False)
dem_proc.calc_twi()
dem_proc.save_array(dem_proc.twi, fn_twi, as_int=True)
def AreaDinf():
import argparse
parser = argparse.ArgumentParser(
description='Calculates a grid of specific catchment area which is the'
' contributing area per unit contour length using the multiple flow '
'direction D-infinity approach. Note, this is different from the '
'equivalent tauDEM function, in that it takes the elevation '
'(not the flow direction) as an input, and it calculates the '
'slope and direction as intermediate steps.')
parser.add_argument('Input_Pit_Filled_Elevation',
help='The input pit-filled elevation file in '
'geotiff format.',
)
parser.add_argument('Input_Number_of_Chunks',
help="The approximate number of chunks that the input "
'file will be divided into for processing (potentially'
' on multiple processors).', type=int, default=1,
nargs='?')
parser.add_argument('Output_D_Infinity_Specific_Catchment_Area',
help='Output filename for the flow direction. Default'
' value = uca.tif .', default='uca.tif', nargs='?')
parser.add_argument('--save-all', '--sa',
help='If set, will save all intermediate files as well.',
action='store_true')
args = parser.parse_args()
fn = args.Input_Pit_Filled_Elevation
n_chunks = args.Input_Number_of_Chunks
fn_uca = args.Output_D_Infinity_Specific_Catchment_Area
sa = args.save_all
from pydem.dem_processing import DEMProcessor
dem_proc = DEMProcessor(fn)
shape = dem_proc.data.shape
chunk_size = max(shape[0], shape[1]) / n_chunks
dem_proc.chunk_size_slp_dir = chunk_size
dem_proc.chunk_size_uca = chunk_size
dem_proc.calc_slopes_directions()
if sa:
dem_proc.save_array(dem_proc.mag, 'mag.tif', as_int=False)
dem_proc.save_array(dem_proc.direction, 'ang.tif', as_int=False)
dem_proc.calc_uca()
dem_proc.save_array(dem_proc.uca, fn_uca, as_int=False)
