def makeSHP(dic):
shpname = saveSHP()
shpWriter = Writer()
shpWriter.autoBalance = 1
shpWriter.field(headerEntry.get(), 'C', '255')
shpWriter.field('Longitude', 'F')
shpWriter.field('Latitude', 'F')
geomtype =1
shpWriter.shapeType = geomtype
parsedGeometryList = []
dicValList = []
dicKeyList = []
for k in dic.keys():
dicValList.append(dic[k])
valist = k,dic[k][0],dic[k][1]
dicKeyList.append(valist)
[parsedGeometryList.append(filez) for filez in dicValList]
[shpWriter.point(*parsedGeometry) for parsedGeometry in parsedGeometryList]
[shpWriter.record(*dList) for dList in dicKeyList]
shpWriter.save(shpname)
prj = generatePRJ(int(sridEntry.get()))
if prj != None:
prjfile = shpname.replace('.shp','') + '.prj'
prjfileOpen = open(prjfile, 'w')
prjfileOpen.write(prj)
prjfileOpen.close()
return shpname
def extract_HUC8(
self,
HUC8,
output,
gagefile='gagestations',
verbose=True,
):
"""
Extracts the USGS gage stations for a watershed from the gage
station shapefile into a shapefile for the 8-digit hydrologic unit
code of interest.
"""
# make sure the metadata exist locally
self.download_metadata()
# make sure the output destination exists
if not os.path.isdir(output): os.mkdir(output)
sfile = '{}/{}'.format(output, gagefile)
if not os.path.isfile(sfile + '.shp'):
# copy the projection
shutil.copy(self.NWIS + '.prj', sfile + '.prj')
# read the file
gagereader = Reader(self.NWIS, shapeType=1)
gagerecords = gagereader.records()
# pull out the HUC8 record to parse the dataset
HUC8_index = gagereader.fields.index(['HUC', 'C', 8, 0]) - 1
# iterate through the field and find gages in the watershed
its = HUC8, sfile
print('extracting gage stations in {} to {}\n'.format(*its))
gage_indices = []
i = 0
for record in gagerecords:
if record[HUC8_index] == HUC8: gage_indices.append(i)
i += 1
# write the data from the HUC8 to a new shapefile
w = Writer(shapeType=1)
for field in gagereader.fields:
w.field(*field)
for i in gage_indices:
point = gagereader.shape(i).points[0]
w.point(*point)
w.record(*gagerecords[i])
w.save(sfile)
if verbose:
print('successfully extracted NWIS gage stations\n')
elif verbose:
print('gage station file {} exists\n'.format(sfile))
self.set_metadata(sfile)
def extract_HUC8(self, HUC8, output, gagefile = 'gagestations',
verbose = True):
"""Extracts the USGS gage stations for a watershed from the gage
station shapefile into a shapefile for the 8-digit hydrologic unit
code of interest.
"""
# make sure the metadata exist locally
self.download_metadata()
# make sure the output destination exists
if not os.path.isdir(output): os.mkdir(output)
sfile = '{}/{}'.format(output, gagefile)
if not os.path.isfile(sfile + '.shp'):
# copy the projection
shutil.copy(self.NWIS + '.prj', sfile + '.prj')
# read the file
gagereader = Reader(self.NWIS, shapeType = 1)
gagerecords = gagereader.records()
# pull out the HUC8 record to parse the dataset
HUC8_index = gagereader.fields.index(['HUC', 'C', 8, 0]) - 1
# iterate through the field and find gages in the watershed
its = HUC8, sfile
print('extracting gage stations in {} to {}\n'.format(*its))
gage_indices = []
i = 0
for record in gagerecords:
if record[HUC8_index] == HUC8: gage_indices.append(i)
i+=1
# write the data from the HUC8 to a new shapefile
w = Writer(shapeType = 1)
for field in gagereader.fields: w.field(*field)
for i in gage_indices:
point = gagereader.shape(i).points[0]
w.point(*point)
w.record(*gagerecords[i])
w.save(sfile)
if verbose:
print('successfully extracted NWIS gage stations\n')
elif verbose:
print('gage station file {} exists\n'.format(sfile))
self.set_metadata(sfile)
def extract_bbox(self, bbox, output, verbose=True):
"""Extracts the NID dam locations for a watershed from the dam
shapefile and the 8-digit hydrologic unit code of interest.
"""
self.download_compressed()
xmin, ymin, xmax, ymax = bbox
# copy the projection files
if verbose: print('copying the projections from the NID source\n')
projection = self.source + '.prj'
shutil.copy(projection, output + '.prj')
# get the dams within the watershed
if verbose: print('reading the dam file\n')
sf = Reader(self.source, shapeType=1)
# work around for issues with pyshp
damrecords = []
for i in range(len(sf.shapes())):
try:
damrecords.append(sf.record(i))
except:
damrecords.append([-100 for i in range(len(sf.fields))])
name_index = sf.fields.index(['DAM_NAME', 'C', 65, 0]) - 1
nid_index = sf.fields.index(['NIDID', 'C', 7, 0]) - 1
long_index = sf.fields.index(['LONGITUDE', 'N', 19, 11]) - 1
lat_index = sf.fields.index(['LATITUDE', 'N', 19, 11]) - 1
river_index = sf.fields.index(['RIVER', 'C', 65, 0]) - 1
owner_index = sf.fields.index(['OWN_NAME', 'C', 65, 0]) - 1
type_index = sf.fields.index(['DAM_TYPE', 'C', 10, 0]) - 1
purp_index = sf.fields.index(['PURPOSES', 'C', 254, 0]) - 1
year_index = sf.fields.index(['YR_COMPL', 'C', 10, 0]) - 1
high_index = sf.fields.index(['NID_HEIGHT', 'N', 19, 11]) - 1
mstor_index = sf.fields.index(['MAX_STOR', 'N', 19, 11]) - 1
nstor_index = sf.fields.index(['NORMAL_STO', 'N', 19, 11]) - 1
area_index = sf.fields.index(['SURF_AREA', 'N', 19, 11]) - 1
# iterate through the fields and determine which points are in the box
if verbose: print('extracting dams into new file\n')
dam_indices = []
i = 0
for record in damrecords:
lat = record[lat_index]
lon = record[long_index]
if self.inside_box([xmin, ymin], [xmax, ymax], [lon, lat]):
dam_indices.append(i)
i += 1
# write the data from the bbox to a new shapefile
w = Writer(output, shapeType=1)
for field in sf.fields:
w.field(*field)
for i in dam_indices:
point = sf.shape(i).points[0]
w.point(*point)
values = damrecords[i]
rs = []
for value in values:
if isinstance(value, bytes): value = value.decode('utf-8')
rs.append(value)
w.record(*rs)
w.close()
if verbose:
print('successfully extracted NID dam locations to new file\n')
def extract_bbox(self, bbox, output, verbose = True):
"""Extracts the NID dam locations for a watershed from the dam
shapefile and the 8-digit hydrologic unit code of interest.
"""
self.download_compressed()
xmin, ymin, xmax, ymax = bbox
# copy the projection files
if verbose: print('copying the projections from the NID source\n')
projection = self.source + '.prj'
shutil.copy(projection, output + '.prj')
# get the dams within the watershed
if verbose: print('reading the dam file\n')
sf = Reader(self.source, shapeType = 1)
# work around for issues with pyshp
damrecords = []
for i in range(len(sf.shapes())):
try: damrecords.append(sf.record(i))
except: damrecords.append([-100 for i in range(len(sf.fields))])
name_index = sf.fields.index(['DAM_NAME', 'C', 65, 0]) - 1
nid_index = sf.fields.index(['NIDID', 'C', 7, 0]) - 1
long_index = sf.fields.index(['LONGITUDE', 'N', 19, 11]) - 1
lat_index = sf.fields.index(['LATITUDE', 'N', 19, 11]) - 1
river_index = sf.fields.index(['RIVER', 'C', 65, 0]) - 1
owner_index = sf.fields.index(['OWN_NAME', 'C', 65, 0]) - 1
type_index = sf.fields.index(['DAM_TYPE', 'C', 10, 0]) - 1
purp_index = sf.fields.index(['PURPOSES', 'C', 254, 0]) - 1
year_index = sf.fields.index(['YR_COMPL', 'C', 10, 0]) - 1
high_index = sf.fields.index(['NID_HEIGHT', 'N', 19, 11]) - 1
mstor_index = sf.fields.index(['MAX_STOR', 'N', 19, 11]) - 1
nstor_index = sf.fields.index(['NORMAL_STO', 'N', 19, 11]) - 1
area_index = sf.fields.index(['SURF_AREA', 'N', 19, 11]) - 1
# iterate through the fields and determine which points are in the box
if verbose: print('extracting dams into new file\n')
dam_indices = []
i = 0
for record in damrecords:
lat = record[lat_index]
lon = record[long_index]
if self.inside_box([xmin, ymin], [xmax, ymax], [lon, lat]):
dam_indices.append(i)
i+=1
# write the data from the bbox to a new shapefile
w = Writer(shapeType = 1)
for field in sf.fields: w.field(*field)
for i in dam_indices:
point = sf.shape(i).points[0]
w.point(*point)
values = damrecords[i]
rs = []
for value in values:
if isinstance(value, bytes): value = value.decode('utf-8')
rs.append(value)
w.record(*rs)
w.save(output)
if verbose:
print('successfully extracted NID dam locations to new file\n')
def export_data(self, query):
def get_label(item):
label = item.descriptor
if label is None:
return None
return label.label
def abbrev_to(name, chars, columns_abbrev):
if len(name) > chars:
n = 1
while True:
name_new = name[:chars - len(str(n))] + str(n)
if not name_new in columns_abbrev.values():
return name_new
n += 1
return name
path = as_path(self.url, check_if_exists = False)
if path is None:
return
geometries = [] # [[coords, geometry_type], ...]
row_idxs = [] # [row_idx, ...]
for row_idx, row in enumerate(query):
for column in row:
label = get_label(row[column])
if label.__class__.__name__ == "DGeometry":
geometries.append(label.coords)
row_idxs.append(row_idx)
break
if not row_idxs:
return
columns_abbrev = {} # {column: column_abbrev, ...}; abbreviated column names
for column in query.columns:
column_abbrev = column
if len(column_abbrev) > 10:
if "." in column_abbrev:
column_abbrev = column_abbrev.split(".")
column_abbrev = "_".join([abbrev_to(column_abbrev[0], 4, columns_abbrev), abbrev_to(column_abbrev[1], 5, columns_abbrev)])
else:
column_abbrev = abbrev_to(column_abbrev, 10, columns_abbrev)
column_abbrev = column_abbrev.replace(".", "_")
columns_abbrev[column] = column_abbrev
shapeType = -1
shape_types = {
"POINT": 1,
"LINESTRING": 3,
"POLYGON": 5,
"MULTIPOINT": 8,
"POINTZ": 11,
"LINESTRINGZ": 13,
"POLYGONZ": 15,
"MULTIPOINTZ": 18,
"POINTM": 21,
"LINESTRINGM": 23,
"POLYGONM": 25,
"MULTIPOINTM": 28,
}
for _, geometry_type in geometries:
if geometry_type not in shape_types:
raise Exception("Unknown geometry type")
if shapeType > -1:
if shape_types[geometry_type] != shapeType:
raise Exception("Geometries must be of the same type")
else:
shapeType = shape_types[geometry_type]
sf = Writer(shapeType = shapeType)
types = {} # {column: type, ...}
shp_types = {bool: "C", int: "N", float: "N", str: "C"}
conv_order = ["N", "C"]
for row in query:
for column in row:
label = get_label(row[column])
if label.__class__.__name__ != "DString":
continue
value = label.try_numeric
typ = type(value)
typ = shp_types[typ] if typ in shp_types else "C"
if (not column in types) or ((typ != types[column]) and (conv_order.index(typ) > conv_order.index(types[column]))):
types[column] = typ
for column in types:
sf.field(columns_abbrev[column], fieldType = types[column], size = "128")
for i in range(len(geometries)):
row = query[row_idxs[i]]
coords = geometries[i][0]
if shapeType in [1, 11, 21]: # point types
sf.point(*coords[0], shapeType = shapeType)
else:
sf.poly(shapeType = shapeType, parts = [coords])
if types:
record = []
for column in types:
label = get_label(row[column])
if label is not None:
label = label.value
record.append(label)
sf.record(*record)
sf.save(path)
