def _init(status, conf):
# From download.py
__this.status = status
__this.conf = conf
account = conf['account']
folder = conf['folder']
product = conf['product']
# Init supported classes
__this.GIS = GIS(status, conf)
__this.Dtime = Dtime(status, conf)
__this.Log = Log(conf['log'])
return account, folder, product
def _init(status, conf):
# From download.py
__this.status = status
__this.conf = conf
__this.path = os.path.join(
os.getcwd(), os.path.dirname(inspect.getfile(inspect.currentframe())))
account = conf['account']
folder = conf['folder']
product = conf['product']
# Init supported classes
__this.GIS = GIS(status, conf)
__this.Dtime = Dtime(status, conf)
__this.Log = Log(conf['log'])
return account, folder, product
def _init(status, conf) -> tuple:
# test = sys.modules
# print('GIS' in test)
# From download.py
__this.status = status
__this.conf = conf
account = conf['account']
folder = conf['folder']
product = conf['product']
# Init supported classes
__this.GIS = GIS(status, conf)
__this.Dtime = Dtime(status, conf)
__this.Log = Log(conf['log'])
return account, folder, product
def DownloadData(status, conf) -> int:
"""This is main interface.
Args:
status (dict): Status.
conf (dict): Configuration.
"""
__this.account = conf['account']
__this.product = conf['product']
__this.Log = Log(conf['log'])
Waitbar = 0
cores = 1
bbox = conf['product']['bbox']
Startdate = conf['product']['period']['s']
Enddate = conf['product']['period']['e']
para_name = conf['product']['parameter']
resolution = conf['product']['resolution']
variable = conf['product']['variable']
TimeFreq = conf['product']['freq']
latlim = conf['product']['data']['lat']
lonlim = conf['product']['data']['lon']
folder = conf['folder']
# Define parameter depedent variables
parameter = para_name.lower()
unit = conf['product']['data']['units']['l']
latlim = [bbox['s'], bbox['n']]
lonlim = [bbox['w'], bbox['e']]
# converts the latlim and lonlim into names of the tiles which must be
# downloaded
if resolution == '3s':
name, rangeLon, rangeLat = Find_Document_Names(latlim, lonlim, parameter)
# Memory for the map x and y shape (starts with zero)
size_X_tot = 0
size_Y_tot = 0
if resolution == '15s' or resolution == '30s':
name = Find_Document_names_15s_30s(latlim, lonlim, parameter, resolution)
nameResults = []
# Create a temporary folder for processing
output_folder = folder['l']
output_folder_trash = folder['t']
# Download, extract, and converts all the files to tiff files
for nameFile in name:
try:
# Download the data from
# http://earlywarning.usgs.gov/hydrodata/
output_file, file_name = Download_Data(nameFile,
output_folder_trash, parameter,
para_name, resolution)
# extract zip data
Extract_Data_zip(output_file, output_folder_trash)
# Converts the data with a adf extention to a tiff extension.
# The input is the file name and in which directory the data must be stored
file_name_tiff = file_name.split('.')[0] + '_trans_temporary.tif'
file_name_extract = file_name.split('_')[0:3]
if resolution == '3s':
file_name_extract2 = file_name_extract[0] + '_' + file_name_extract[1]
if resolution == '15s':
file_name_extract2 = file_name_extract[0] + '_' + file_name_extract[1] + '_15s'
if resolution == '30s':
file_name_extract2 = file_name_extract[0] + '_' + file_name_extract[1] + '_30s'
output_tiff = os.path.join(output_folder_trash, file_name_tiff)
# convert data from adf to a tiff file
if (resolution == "15s" or resolution == "3s"):
input_adf = os.path.join(output_folder_trash, file_name_extract2,
file_name_extract2, 'hdr.adf')
output_tiff = Convert_adf_to_tiff(input_adf, output_tiff)
# convert data from adf to a tiff file
if resolution == "30s":
input_bil = os.path.join(output_folder_trash,
'%s.bil' % file_name_extract2)
output_tiff = Convert_bil_to_tiff(input_bil, output_tiff)
geo_out, proj, size_X, size_Y = Open_array_info(output_tiff)
if (resolution == "3s" and (
int(size_X) != int(6000) or int(size_Y) != int(6000))):
data = np.ones((6000, 6000)) * -9999
# Create the latitude bound
Vfile = str(nameFile)[1:3]
SignV = str(nameFile)[0]
SignVer = 1
# If the sign before the filename is a south sign than latitude is negative
if SignV is "s":
SignVer = -1
Bound2 = int(SignVer) * int(Vfile)
# Create the longitude bound
Hfile = str(nameFile)[4:7]
SignH = str(nameFile)[3]
SignHor = 1
# If the sign before the filename is a west sign than longitude is negative
if SignH is "w":
SignHor = -1
Bound1 = int(SignHor) * int(Hfile)
Expected_X_min = Bound1
Expected_Y_max = Bound2 + 5
Xid_start = int(np.round((geo_out[0] - Expected_X_min) / geo_out[1]))
Xid_end = int(np.round(
((geo_out[0] + size_X * geo_out[1]) - Expected_X_min) / geo_out[1]))
Yid_start = int(np.round((Expected_Y_max - geo_out[3]) / (-geo_out[5])))
Yid_end = int(np.round(
(Expected_Y_max - (geo_out[3] + (size_Y * geo_out[5]))) / (
-geo_out[5])))
data[Yid_start:Yid_end, Xid_start:Xid_end] = Open_tiff_array(
output_tiff)
if np.max(data) == 255:
data[data == 255] = -9999
data[data < -9999] = -9999
geo_in = [Bound1, 0.00083333333333333, 0.0, int(Bound2 + 5),
0.0, -0.0008333333333333333333]
# save chunk as tiff file
Save_as_tiff(name=output_tiff, data=data, geo=geo_in, projection="WGS84")
except:
if resolution == '3s':
# If tile not exist create a replacing zero tile (sea tiles)
output = nameFile.split('.')[0] + "_trans_temporary.tif"
output_tiff = os.path.join(output_folder_trash, output)
file_name = nameFile
data = np.ones((6000, 6000)) * -9999
data = data.astype(np.float32)
# Create the latitude bound
Vfile = str(file_name)[1:3]
SignV = str(file_name)[0]
SignVer = 1
# If the sign before the filename is a south sign than latitude is negative
if SignV is "s":
SignVer = -1
Bound2 = int(SignVer) * int(Vfile)
# Create the longitude bound
Hfile = str(file_name)[4:7]
SignH = str(file_name)[3]
SignHor = 1
# If the sign before the filename is a west sign than longitude is negative
if SignH is "w":
SignHor = -1
Bound1 = int(SignHor) * int(Hfile)
# Geospatial data for the tile
geo_in = [Bound1, 0.00083333333333333, 0.0, int(Bound2 + 5),
0.0, -0.0008333333333333333333]
# save chunk as tiff file
Save_as_tiff(name=output_tiff, data=data, geo=geo_in, projection="WGS84")
if resolution == '15s':
print('no 15s data is in dataset')
if resolution == '3s':
# clip data
Data, Geo_data = Clip_Data(output_tiff, latlim, lonlim)
size_Y_out = int(np.shape(Data)[0])
size_X_out = int(np.shape(Data)[1])
# Total size of the product so far
size_Y_tot = int(size_Y_tot + size_Y_out)
size_X_tot = int(size_X_tot + size_X_out)
if nameFile is name[0]:
Geo_x_end = Geo_data[0]
Geo_y_end = Geo_data[3]
else:
Geo_x_end = np.min([Geo_x_end, Geo_data[0]])
Geo_y_end = np.max([Geo_y_end, Geo_data[3]])
# create name for chunk
FileNameEnd = "%s_temporary.tif" % (nameFile)
nameForEnd = os.path.join(output_folder_trash, FileNameEnd)
nameResults.append(str(nameForEnd))
# save chunk as tiff file
Save_as_tiff(name=nameForEnd, data=Data, geo=Geo_data, projection="WGS84")
if resolution == '3s':
# size_X_end = int(size_X_tot) #!
# size_Y_end = int(size_Y_tot) #!
size_X_end = int(size_X_tot / len(rangeLat)) + 1 # !
size_Y_end = int(size_Y_tot / len(rangeLon)) + 1 # !
# Define the georeference of the end matrix
geo_out = [Geo_x_end, Geo_data[1], 0, Geo_y_end, 0, Geo_data[5]]
latlim_out = [geo_out[3] + geo_out[5] * size_Y_end, geo_out[3]]
lonlim_out = [geo_out[0], geo_out[0] + geo_out[1] * size_X_end]
# merge chunk together resulting in 1 tiff map
datasetTot = Merge_DEM(latlim_out, lonlim_out, nameResults, size_Y_end,
size_X_end)
datasetTot[datasetTot < -9999] = -9999
if resolution == '15s':
output_file_merged = os.path.join(output_folder_trash, 'merged.tif')
datasetTot, geo_out = Merge_DEM_15s_30s(output_folder_trash, output_file_merged,
latlim, lonlim, resolution)
if resolution == '30s':
output_file_merged = os.path.join(output_folder_trash, 'merged.tif')
datasetTot, geo_out = Merge_DEM_15s_30s(output_folder_trash, output_file_merged,
latlim, lonlim, resolution)
# name of the end result
output_DEM_name = "%s_HydroShed_%s_%s.tif" % (para_name, unit, resolution)
Save_name = os.path.join(output_folder, output_DEM_name)
# Make geotiff file
Save_as_tiff(name=Save_name, data=datasetTot, geo=geo_out, projection="WGS84")
os.chdir(output_folder)
