def dissolve(inshp, outshp, dissolve_attribute):
df = GISio.shp2df(shp, geometry=True)
df_out = dissolve_df(df, dissolve_attribute)
# write dissolved polygons to new shapefile
GISio.df2shp(df_out, outshp, 'geometry', inshp[:-4]+'.prj')
def join_csv2shp(shapefile,
shp_joinfield,
csvfile,
csv_joinfield,
out_shapefile,
how='outer'):
'''
add attribute information to shapefile from csv file
shapefile: shapefile to add attributes to
shp_joinfield: attribute name in shapefile on which to make join
csvfile: csv file with information to be added to shapefile
csv_joinfield: column in csv with entries matching those in shp_joinfield
out_shapefile: output; original shapefile is not modified
type: pandas join type; see http://pandas.pydata.org/pandas-docs/dev/generated/pandas.DataFrame.join.html
'''
shpdf = GISio.shp2df(shapefile, index=shp_joinfield, geometry=True)
csvdf = pd.read_csv(csvfile, index_col=csv_joinfield)
print('joining to {}...'.format(csvfile))
joined = shpdf.join(csvdf, how='inner', lsuffix='L', rsuffix='R')
# write to shapefile
GISio.df2shp(joined, out_shapefile, 'geometry', shapefile[:-4] + '.prj')
def dissolve(inshp, outshp, dissolve_attribute=None):
df = GISio.shp2df(inshp)
df_out = dissolve_df(df, dissolve_attribute)
# write dissolved polygons to new shapefile
GISio.df2shp(df_out, outshp, prj=inshp[:-4]+'.prj')
def dissolve(inshp, outshp, dissolve_attribute=None):
df = GISio.shp2df(inshp)
df_out = dissolve_df(df, dissolve_attribute)
# write dissolved polygons to new shapefile
GISio.df2shp(df_out, outshp, prj=inshp[:-4] + '.prj')
def check_grid_intersection(self, sfr_linework_shapefile=None):
print '\Checking SFR cell geometries for consistancy with linework...'
if sfr_linework_shapefile is None:
print 'Need linework to check SFR cell geometries.'
return
else:
import GISio
df = GISio.shp2df(sfr_linework_shapefile)
try:
self.lines = df[['segment', 'reach', 'geometry']].copy()
self.lines.sort(['segment', 'reach'], inplace=True)
except IndexError:
print 'Linework shapfile must have segment and reach information!'
self._get_sfr_cell_geoms()
self.m1.sort(['segment', 'reach'], inplace=True)
lines, cells = self.lines.geometry.tolist(), self.m1.geometry.tolist()
intersections = np.array([lines[i].intersects(cell) for i, cell in enumerate(cells)])
nmismatch = len(self.m1[~intersections])
if nmismatch > 0:
reportfile = 'bad_intersections.csv'
print "{} SFR reaches don't coincide with linework in {}!" \
"see {}.".format(nmismatch, sfr_linework_shapefile, reportfile)
self.m1[~intersections].to_csv(reportfile, index=False)
else:
print 'passed.'
def check_grid_intersection(self, sfr_linework_shapefile=None):
print('\Checking SFR cell geometries for consistancy with linework...')
if sfr_linework_shapefile is None:
print('Need linework to check SFR cell geometries.')
return
else:
import GISio
df = GISio.shp2df(sfr_linework_shapefile)
try:
self.lines = df[['segment', 'reach', 'geometry']].copy()
self.lines.sort(['segment', 'reach'], inplace=True)
except IndexError:
print('Linework shapfile must have segment and reach information!')
self._get_sfr_cell_geoms()
self.m1.sort(['segment', 'reach'], inplace=True)
lines, cells = self.lines.geometry.tolist(), self.m1.geometry.tolist()
intersections = np.array([lines[i].intersects(cell) for i, cell in enumerate(cells)])
nmismatch = len(self.m1[~intersections])
if nmismatch > 0:
reportfile = 'bad_intersections.csv'
print("{} SFR reaches don't coincide with linework in {}!" \
"see {}.".format(nmismatch, sfr_linework_shapefile, reportfile))
self.m1[~intersections].to_csv(reportfile, index=False)
else:
print('passed.')
def get_drainage_areas(comids, CumulativeArea_file, units='mi2', areatype='TotDASqKM'):
CA = GISio.shp2df(CumulativeArea_file)
CA.index = CA.ComID
areas_dict = {}
for comid in comids:
if units == 'mi2':
areas_dict[comid] = CA.ix[comid, areatype] * 0.386102
elif units == 'km2':
areas_dict[comid] = CA.ix[comid, areatype]
return areas_dict
def write_shp(self, df, shpname='NWIS_export.shp', **kwargs):
"""Write a shapefile of points from NWIS site file
Parameters
----------
df: dataframe
dataframe of site info, must have dec_long_va and dec_lat_va columns with lon/lat in DD
shpname: string
Name for output shapefile
Notes
-----
NAD83 is assumed for dec_long_va and dec_lat_va.
If some entries are in NAD27, a difference of ~5 to >15m will result for WI
(see http://en.wikipedia.org/wiki/North_American_Datum#/media/File:Datum_Shift_Between_NAD27_and_NAD83.png)
"""
shpdf = df.copy()
shpdf['geometry'] = [Point(r.dec_long_va, r.dec_lat_va) for i, r in shpdf.iterrows()]
GISio.df2shp(shpdf, shpname, epsg=4269)
def join_csv2shp(shapefile, shp_joinfield, csvfile, csv_joinfield, out_shapefile, how='outer'):
'''
add attribute information to shapefile from csv file
shapefile: shapefile to add attributes to
shp_joinfield: attribute name in shapefile on which to make join
csvfile: csv file with information to be added to shapefile
csv_joinfield: column in csv with entries matching those in shp_joinfield
out_shapefile: output; original shapefile is not modified
type: pandas join type; see http://pandas.pydata.org/pandas-docs/dev/generated/pandas.DataFrame.join.html
'''
shpdf = GISio.shp2df(shapefile, index=shp_joinfield, geometry=True)
csvdf = pd.read_csv(csvfile, index_col=csv_joinfield)
print('joining to {}...'.format(csvfile))
joined = shpdf.join(csvdf, how='inner', lsuffix='L', rsuffix='R')
# write to shapefile
GISio.df2shp(joined, out_shapefile, 'geometry', shapefile[:-4]+'.prj')
def write_shp(self, df, shpname='NWIS_export.shp'):
"""Write a shapefile of points from NWIS site file
Parameters
----------
df: dataframe
dataframe of site info, must have dec_long_va and dec_lat_va columns with lon/lat in DD
shpname: string
Name for output shapefile
Notes
-----
NAD83 is assumed for dec_long_va and dec_lat_va.
If some entries are in NAD27, a difference of ~5 to >15m will result for WI
(see http://en.wikipedia.org/wiki/North_American_Datum#/media/File:Datum_Shift_Between_NAD27_and_NAD83.png)
"""
shpdf = df.copy()
shpdf['geometry'] = [Point(r.dec_long_va, r.dec_lat_va) for i, r in shpdf.iterrows()]
GISio.df2shp(shpdf, shpname, epsg=4269)
def get_drainage_areas(comids,
CumulativeArea_file,
units='mi2',
areatype='TotDASqKM'):
CA = GISio.shp2df(CumulativeArea_file)
CA.index = CA.ComID
areas_dict = {}
for comid in comids:
if units == 'mi2':
areas_dict[comid] = CA.ix[comid, areatype] * 0.386102
elif units == 'km2':
areas_dict[comid] = CA.ix[comid, areatype]
return areas_dict
def check_outlets(self, model_domain=None, buffer=100):
print("\nChecking for outlets in the model interior...")
if model_domain is None:
print('Need a shapefile of the model domain edge to check for interior outlets.\n' \
'(rotated coordinate systems not supported; ' \
'for rotated grids submit shapefile of unrotated domain in coordinates consistent with model cells.)')
return
else:
import GISio
df = GISio.shp2df(model_domain)
self.domain = df.iloc[0].geometry
self._get_sfr_cell_geoms()
print('\nChecking for breaks in routing (outlets) within the SFR network')
if 'Outlet' not in self.m1.columns:
circular_routing = self.map_outsegs()
if circular_routing is not None:
print(circular_routing)
print('\nCannot evaluate interior outlets until circular routing is fixed.')
return
else:
pass
outlets = np.unique(self.m1.Outlet.values)
self.m1.sort(['segment', 'reach'], inplace=True)
outlet_nodes = [self.m1.ix[(self.m1.segment == o), 'node'].values[-1] for o in outlets]
outlet_geoms = [self.m1.ix[(self.m1.segment == o), 'geometry'].values[-1] for o in outlets]
interior_outlets = [n for i, n in enumerate(outlet_nodes)
if outlet_geoms[i].buffer(buffer).within(self.domain)]
if len(interior_outlets) > 0:
print('Interior outlets found at the following nodes:\n')
for i in interior_outlets:
print('{} '.format(i), end=' ')
print('\n')
else:
# make sure that at least 1 SFR cell is inside the domain
for g in self.m1.geometry:
if g.within(self.domain):
print('passed.')
break
else:
continue
print("No SFR cells were inside of the supplied domain! Check domain shapefile coordinates,\n" \
"and that the correct model origin was supplied.")
def check_outlets(self, model_domain=None, buffer=100):
print "\nChecking for outlets in the model interior..."
if model_domain is None:
print 'Need a shapefile of the model domain edge to check for interior outlets.\n' \
'(rotated coordinate systems not supported; ' \
'for rotated grids submit shapefile of unrotated domain in coordinates consistent with model cells.)'
return
else:
import GISio
df = GISio.shp2df(model_domain)
self.domain = df.iloc[0].geometry
self._get_sfr_cell_geoms()
print '\nChecking for breaks in routing (outlets) within the SFR network'
if 'Outlet' not in self.m1.columns:
circular_routing = self.map_outsegs()
if circular_routing is not None:
print circular_routing
print '\nCannot evaluate interior outlets until circular routing is fixed.'
return
else:
pass
outlets = np.unique(self.m1.Outlet.values)
self.m1.sort(['segment', 'reach'], inplace=True)
outlet_nodes = [self.m1.ix[(self.m1.segment == o), 'node'].values[-1] for o in outlets]
outlet_geoms = [self.m1.ix[(self.m1.segment == o), 'geometry'].values[-1] for o in outlets]
interior_outlets = [n for i, n in enumerate(outlet_nodes)
if outlet_geoms[i].buffer(buffer).within(self.domain)]
if len(interior_outlets) > 0:
print 'Interior outlets found at the following nodes:\n'
for i in interior_outlets:
print '{} '.format(i),
print '\n'
else:
# make sure that at least 1 SFR cell is inside the domain
for g in self.m1.geometry:
if g.within(self.domain):
print 'passed.'
break
else:
continue
print "No SFR cells were inside of the supplied domain! Check domain shapefile coordinates,\n" \
"and that the correct model origin was supplied."
def portion_perennial(self, bounds=None):
'''
returns new dataframe of COMIDs classified as perennial (True) or ephemeral (False)
``bounds (optional)``: (polygon shapefile) encompassing streams to evaluate
'''
streams = self.df[(self.df.FCODE == 46006) | (self.df.FCODE == 46003)].copy()
streams['perennial'] = [True if r.FCODE == 46006 else False for i, r in streams.iterrows()]
if bounds:
bound = GISio.shp2df(bounds, geometry=True).iloc[0].geometry
intersected = [g.intersects(bound) for g in streams.geometry]
streams = streams.ix[intersected]
return streams
def check_outlets(self, model_domain=None, buffer=100):
if model_domain is None:
print 'Need a shapefile of the model domain edge to check for interior outlets.'
return
else:
import GISio
df = GISio.shp2df(model_domain)
self.domain = df.iloc[0].geometry
if 'geometry' not in self.m1.columns:
try:
self.get_cell_geometries()
except:
print "No geometry column in attribute m1; couldn't generate geometries from dis attribute.\n" \
"Read in the DIS file by running read_dis2()."
if self.xll == 0 and self.yll == 0:
print 'Warning, model origin for SFR object is 0, 0.'
print 'Checking for breaks in routing (outlets) within the SFR network'
if 'Outlet' not in self.m1.columns:
self.map_outsegs()
outlets = np.unique(self.m1.Outlet.values)
self.m1.sort(['segment', 'reach'], inplace=True)
outlet_nodes = [self.m1.ix[(self.m1.segment == o), 'node'].values[-1] for o in outlets]
outlet_geoms = [self.m1.ix[(self.m1.segment == o), 'geometry'].values[-1] for o in outlets]
interior_outlets = [n for i, n in enumerate(outlet_nodes)
if outlet_geoms[i].buffer(buffer).within(self.domain)]
if len(interior_outlets) > 0:
print 'Interior outlets found at the following nodes:\n'
for i in interior_outlets:
print '{} '.format(i),
else:
# make sure that at least 1 SFR cell is inside the domain
for g in self.m1.geometry:
if g.within(self.domain):
print 'passed.'
break
else:
continue
print "No SFR cells were inside of the supplied domain! Check domain shapefile coordinates,\n" \
"and that the correct model origin was supplied."
def portion_perennial(self, bounds=None):
'''
returns new dataframe of COMIDs classified as perennial (True) or ephemeral (False)
``bounds (optional)``: (polygon shapefile) encompassing streams to evaluate
'''
streams = self.df[(self.df.FCODE == 46006) |
(self.df.FCODE == 46003)].copy()
streams['perennial'] = [
True if r.FCODE == 46006 else False for i, r in streams.iterrows()
]
if bounds:
bound = GISio.shp2df(bounds, geometry=True).iloc[0].geometry
intersected = [g.intersects(bound) for g in streams.geometry]
streams = streams.ix[intersected]
return streams
def __init__(self, filename):
'''
``filename``: (string or list) shapefile(s) to load
'''
self.filename = filename
self.df = GISio.shp2df(self.filename, index='COMID', geometry=True)
def check_4gaps_in_routing(self, model_domain=None, tol=0):
print("\nChecking for gaps in routing between segments...")
if model_domain is None:
print('No model_domain supplied. ' \
'Routing gaps for segments intersecting model domain boundary will not be considered.\n' \
'(rotated coordinate systems not supported; ' \
'for rotated grids submit shapefile of unrotated domain in coordinates consistent with model cells.)')
else:
import GISio
df = GISio.shp2df(model_domain)
self.domain = df.iloc[0].geometry
self._get_sfr_cell_geoms()
m1 = self.m1.copy()
m2 = self.m2.copy()
if tol is None:
try:
tol = np.min([np.min(self.dis.delr),
np.min(self.dis.delc)])
except:
tol = 0
# get number of reaches for each segment
max_reach_numbers = [np.max(m1.reach[m1.segment == s]) for s in m2.segment]
# get cell centroids for last reach in each segment
end_centroids = [m1.geometry[(m1.segment == s) &
(m1.reach == max_reach_numbers[i])].values[0].centroid
for i, s in enumerate(m2.segment.tolist())]
# get cell centroids for first reach in each segment
start_centroids = [m1.geometry[(m1.segment == s) &
(m1.reach == 1)].values[0].centroid
for s in m2.segment]
# compute distances between end reach cell centroid, and cell centroid of outseg reach 1
distances = [end_centroids[i].distance(start_centroids[os-1]) if 0 < os < 999999 else 0
for i, os in enumerate(m2.outseg.astype(int))]
m2['routing_distance'] = distances
m2['end_reach_geom'] = [m1.geometry[(m1.segment == s) &
(m1.reach == max_reach_numbers[i])].values[0]
for i, s in enumerate(m2.segment.tolist())]
routing = m2.ix[m2.routing_distance > tol, ['segment', 'outseg', 'routing_distance', 'end_reach_geom']]\
.sort('routing_distance', ascending=False)
reportfile = 'routing_gaps.csv'
if model_domain is not None:
# identify routing gaps that do not occur along the model boundary
# (HWR code in sfr_classes may route segments along the model boundary to each other)
interior_gaps = [g.within(self.domain) for g in routing.end_reach_geom]
routing = routing[interior_gaps]
if len(routing) > 0:
print('{:.0f} gaps in routing greater than {} (default is minimum model cell size)' \
'\nfound that do not coincide with {}. See {}'.format(len(routing),
tol,
model_domain,
reportfile))
routing.drop('end_reach_geom', axis=1).to_csv(reportfile, index=False)
return
if len(routing) > 0:
print('{:.0f} gaps in routing greater than {} found, ' \
'but these may coincide with model domain boundary. See {}'.format(len(routing), tol, reportfile))
routing.drop('end_reach_geom', axis=1).to_csv(reportfile, index=False)
return
print('passed.')
def add_PlusFlowVAA(self, pfvaafile, **kwargs):
self.pfvaa = GISio.shp2df(pfvaafile, index='COMID')
self.df = self.df.join(self.pfvaa, **kwargs)
__author__ = 'aleaf'
'''
retrieve daily values for a list of NWIS sites
'''
import os
import pandas as pd
from shapely.geometry import Point
import flux_targets as ft
import sys
sys.path.append('D:\\ATLData\\Documents\\GitHub\\GIS_utils\\')
import GISio
NWIS_daily_values_sites_file = 'D:/ATLData/GFL files/Great_Divide/flux_targets/NWIS_daily_values_sites.txt'
output_folder = 'D:/ATLData/GFL files/Great_Divide/flux_targets/daily'
model_domain_polygon = 'D:/ATLData/CNNF_Great_Divide/GIS/shps/GD_nearfield.shp' # must be in geographic coordinates!
bounds = GISio.shp2df(model_domain_polygon, geometry=True).geometry[0]
# read in info from daily values sites file
header_text = open(NWIS_daily_values_sites_file).readlines()
columns, header_rows = ft.NWIS_header(header_text)
df = pd.read_csv(NWIS_daily_values_sites_file, sep='\t', names=columns, skiprows=header_rows)
for n in df.site_no:
# first test if the site is in the model domain
site_location = Point(df[df.site_no == n][['dec_long_va', 'dec_lat_va']].get_values()[0])
if site_location.within(bounds):
text = ft.get_nwis(n, '00060')
ofp = open(os.path.join(output_folder, '{}.txt'.format(n)), 'w')
for line in text:
if line.strip().split('\t')[0] == 'agency_cd':
columns = line.strip().split('\t')
knt += 2
break
else:
knt += 1
return columns, knt
# read in NWIS site information and study area boundary
header_text = open(NWIS_site_info_file).readlines()
columns, header_rows = NWIS_header(header_text)
df = pd.read_csv(NWIS_site_info_file, sep='\t', names=columns, skiprows=header_rows)
bounds = GISio.shp2df(model_domain_polygon, geometry=True).geometry[0]
# make geomtries for each station, and drop stations not in the study area
df['geometry'] = df.apply(lambda x: Point(x['dec_long_va'], x['dec_lat_va']), axis=1)
GISio.df2shp(df, 'D:/ATLData/GFL files/Great_Divide/flux_targets/NWIS_sites_all.shp', prj='epsg:4269')
within = [p.within(bounds) for p in df.geometry]
df = df[within]
GISio.df2shp(df, NWIS_site_info_file[:-4]+'.shp', prj='epsg:4269')
# now do spatial join of NWIS locations to NHD comids
arcpy.SpatialJoin_analysis(NWIS_site_info_file[:-4]+'.shp', flowlines_clipped, NWIS_site_info_file[:-4]+'_joined.shp',
"JOIN_ONE_TO_ONE", "KEEP_ALL", '', "WITHIN_A_DISTANCE", .001)
# now read back in and make a csv file for input into flux_targets.py
df = GISio.shp2df(NWIS_site_info_file[:-4]+'_joined.shp')
logq = np.log10(q)
qs_1e6 = q * 1e6
logqs_1e6 = np.log10(qs_1e6) # scale specific discharge to easier units for plotting
df = pd.DataFrame({'cellnum': cellnums.flatten(),
'x': xy[0].flatten(),
'y': xy[1].flatten(),
'U': U.flatten(),
'V': V.flatten(),
'Z': Z.flatten(),
'Q': Q.flatten(),
'logQ': logQ.flatten(),
'us': u.flatten(),
'vs': v.flatten(),
'zs': z.flatten(),
'qs_1e6': qs_1e6.flatten(),
'logqs_1e6': logqs_1e6.flatten(),
'rot': rot.flatten()})
df['updown'] = None
df.ix[df['zs'] > 0, 'updown'] = 'down'
df.ix[df['zs'] < 0, 'updown'] = 'up'
df['geometry'] = [Point(df.ix[i, 'x'], df.ix[i, 'y']) for i in df.index]
GISio.df2shp(df, os.path.join(path, 'cbb_arrows{}.shp'.format(l+1)), 'geometry', prj=PRJfile)
def check_4gaps_in_routing(self, model_domain=None, tol=0):
print "\nChecking for gaps in routing between segments..."
if model_domain is None:
print 'No model_domain supplied. ' \
'Routing gaps for segments intersecting model domain boundary will not be considered.\n' \
'(rotated coordinate systems not supported; ' \
'for rotated grids submit shapefile of unrotated domain in coordinates consistent with model cells.)'
else:
import GISio
df = GISio.shp2df(model_domain)
self.domain = df.iloc[0].geometry
self._get_sfr_cell_geoms()
m1 = self.m1.copy()
m2 = self.m2.copy()
if tol is None:
try:
tol = np.min([np.min(self.dis.delr),
np.min(self.dis.delc)])
except:
tol = 0
# get number of reaches for each segment
max_reach_numbers = [np.max(m1.reach[m1.segment == s]) for s in m2.segment]
# get cell centroids for last reach in each segment
end_centroids = [m1.geometry[(m1.segment == s) &
(m1.reach == max_reach_numbers[i])].values[0].centroid
for i, s in enumerate(m2.segment.tolist())]
# get cell centroids for first reach in each segment
start_centroids = [m1.geometry[(m1.segment == s) &
(m1.reach == 1)].values[0].centroid
for s in m2.segment]
# compute distances between end reach cell centroid, and cell centroid of outseg reach 1
distances = [end_centroids[i].distance(start_centroids[os-1]) if 0 < os < 999999 else 0
for i, os in enumerate(m2.outseg.astype(int))]
m2['routing_distance'] = distances
m2['end_reach_geom'] = [m1.geometry[(m1.segment == s) &
(m1.reach == max_reach_numbers[i])].values[0]
for i, s in enumerate(m2.segment.tolist())]
routing = m2.ix[m2.routing_distance > tol, ['segment', 'outseg', 'routing_distance', 'end_reach_geom']]\
.sort('routing_distance', ascending=False)
reportfile = 'routing_gaps.csv'
if model_domain is not None:
# identify routing gaps that do not occur along the model boundary
# (HWR code in sfr_classes may route segments along the model boundary to each other)
interior_gaps = [g.within(self.domain) for g in routing.end_reach_geom]
routing = routing[interior_gaps]
if len(routing) > 0:
print '{:.0f} gaps in routing greater than {} (default is minimum model cell size)' \
'\nfound that do not coincide with {}. See {}'.format(len(routing),
tol,
model_domain,
reportfile)
routing.drop('end_reach_geom', axis=1).to_csv(reportfile, index=False)
return
if len(routing) > 0:
print '{:.0f} gaps in routing greater than {} found, ' \
'but these may coincide with model domain boundary. See {}'.format(len(routing), tol, reportfile)
routing.drop('end_reach_geom', axis=1).to_csv(reportfile, index=False)
return
print 'passed.'
def add_fcode(self, fcodefile):
self.fcode = GISio.shp2df(fcodefile)
knt += 2
break
else:
knt += 1
return columns, knt
# read in NWIS site information and study area boundary
header_text = open(NWIS_site_info_file).readlines()
columns, header_rows = NWIS_header(header_text)
df = pd.read_csv(NWIS_site_info_file,
sep='\t',
names=columns,
skiprows=header_rows)
bounds = GISio.shp2df(model_domain_polygon, geometry=True).geometry[0]
# make geomtries for each station, and drop stations not in the study area
df['geometry'] = df.apply(lambda x: Point(x['dec_long_va'], x['dec_lat_va']),
axis=1)
GISio.df2shp(
df,
'D:/ATLData/GFL files/Great_Divide/flux_targets/NWIS_sites_all.shp',
prj='epsg:4269')
within = [p.within(bounds) for p in df.geometry]
df = df[within]
GISio.df2shp(df, NWIS_site_info_file[:-4] + '.shp', prj='epsg:4269')
# now do spatial join of NWIS locations to NHD comids
arcpy.SpatialJoin_analysis(NWIS_site_info_file[:-4] + '.shp',
def __init__(self, filename):
'''
``filename``: (string or list) shapefile(s) to load
'''
self.filename = filename
self.df = GISio.shp2df(self.filename, index='COMID', geometry=True)
arcpy.Clip_analysis(os.path.join(os.getcwd(), 'temp2.shp'), MFdomain,
os.path.join(os.getcwd(), 'catchments.shp'))
print 'performing spatial join of catchments to SFR cells...'
# intersect is way faster than spatial join
arcpy.SpatialJoin_analysis(SFR_shapefile,
os.path.join(os.getcwd(), 'catchments.shp'),
os.path.join(os.getcwd(), 'catchments_joined.shp'))
print 'and to model grid (this may take awhile)...'
arcpy.SpatialJoin_analysis(MFgrid, os.path.join(os.getcwd(), 'catchments.shp'),
os.path.join(os.getcwd(), 'MFgrid_catchments.shp'))
# now figure out which SFR segment each catchment should drain to
print 'reading {} into pandas dataframe...'.format(
os.path.join(os.getcwd(), 'catchments_joined.shp'))
SFRcatchments = GISio.shp2df(os.path.join(os.getcwd(),
'catchments_joined.shp'))
print 'assigning an SFR segment to each catchment... (this may take awhile)'
intersected_catchments = list(np.unique(SFRcatchments.FEATUREID))
segments_dict = {}
for cmt in intersected_catchments:
try:
segment = SFRcatchments[SFRcatchments.FEATUREID ==
cmt].segment.mode()[0]
except: # pandas crashes if mode is called on df of length 1
segment = SFRcatchments[SFRcatchments.FEATUREID == cmt].segment[0]
segments_dict[cmt] = segment
# can also use values_count() to get a frequency table for segments (reaches) in each catchment
print 'building UZF package IRUNBND array from {}'.format(MFgrid)
MFgrid_joined = GISio.shp2df(os.path.join(os.getcwd(),
print 'clipping to {}'.format(MFdomain)
arcpy.Clip_analysis(os.path.join(os.getcwd(), 'temp2.shp'), MFdomain, os.path.join(os.getcwd(), 'catchments.shp'))
print 'performing spatial join of catchments to SFR cells...'
# intersect is way faster than spatial join
arcpy.SpatialJoin_analysis(SFR_shapefile,
os.path.join(os.getcwd(), 'catchments.shp'),
os.path.join(os.getcwd(), 'catchments_joined.shp'))
print 'and to model grid (this may take awhile)...'
arcpy.SpatialJoin_analysis(MFgrid,
os.path.join(os.getcwd(), 'catchments.shp'),
os.path.join(os.getcwd(), 'MFgrid_catchments.shp'))
# now figure out which SFR segment each catchment should drain to
print 'reading {} into pandas dataframe...'.format(os.path.join(os.getcwd(), 'catchments_joined.shp'))
SFRcatchments = GISio.shp2df(os.path.join(os.getcwd(), 'catchments_joined.shp'))
print 'assigning an SFR segment to each catchment... (this may take awhile)'
intersected_catchments = list(np.unique(SFRcatchments.FEATUREID))
segments_dict = {}
for cmt in intersected_catchments:
try:
segment = SFRcatchments[SFRcatchments.FEATUREID == cmt].segment.mode()[0]
except: # pandas crashes if mode is called on df of length 1
segment = SFRcatchments[SFRcatchments.FEATUREID == cmt].segment[0]
segments_dict[cmt] = segment
# can also use values_count() to get a frequency table for segments (reaches) in each catchment
print 'building UZF package IRUNBND array from {}'.format(MFgrid)
MFgrid_joined = GISio.shp2df(os.path.join(os.getcwd(), 'MFgrid_catchments.shp'), geometry=True)
MFgrid_joined.index = MFgrid_joined.node
def add_fcode(self, fcodefile):
self.fcode = GISio.shp2df(fcodefile)
__author__ = 'aleaf'
'''
retrieve daily values for a list of NWIS sites
'''
import os
import pandas as pd
from shapely.geometry import Point
import flux_targets as ft
import sys
sys.path.append('D:\\ATLData\\Documents\\GitHub\\GIS_utils\\')
import GISio
NWIS_daily_values_sites_file = 'D:/ATLData/GFL files/Great_Divide/flux_targets/NWIS_daily_values_sites.txt'
output_folder = 'D:/ATLData/GFL files/Great_Divide/flux_targets/daily'
model_domain_polygon = 'D:/ATLData/CNNF_Great_Divide/GIS/shps/GD_nearfield.shp' # must be in geographic coordinates!
bounds = GISio.shp2df(model_domain_polygon, geometry=True).geometry[0]
# read in info from daily values sites file
header_text = open(NWIS_daily_values_sites_file).readlines()
columns, header_rows = ft.NWIS_header(header_text)
df = pd.read_csv(NWIS_daily_values_sites_file,
sep='\t',
names=columns,
skiprows=header_rows)
for n in df.site_no:
# first test if the site is in the model domain
site_location = Point(df[df.site_no == n][['dec_long_va',
'dec_lat_va']].get_values()[0])
def add_PlusFlowVAA(self, pfvaafile, **kwargs):
self.pfvaa = GISio.shp2df(pfvaafile, index='COMID')
self.df = self.df.join(self.pfvaa, **kwargs)
