def __init__(self, network, updated_qs_table):
"""
:param network:
:param updated_qs_table:
"""
self.streams = network
self.network = gpd.read_file(self.streams)
table = pd.read_csv(updated_qs_table, sep=',', header=0)
table = table.dropna(axis='columns')
# add da values to table and then sort by da so disturbance is accounted for from upstream to downstream
da_values = []
for x in table.index:
da = self.network.loc[table.loc[x, 'Segment ID'], 'Drain_Area']
da_values.append(da)
table['DA'] = da_values
sortedtable = table.sort_values(by='DA')
self.sortedtable = sortedtable.reset_index(drop=True)
self.segids = self.sortedtable['Segment ID']
self.values = self.sortedtable['newQs']
self.topo = nt.TopologyTools(network)
self.network['newQs'] = -9999
self.network['eff_DA'] = -9999
def __init__(self, network, qs_table):
"""
:param network: string - path to stream network shapefile with topology attributes
:param qs_table: string - path to csv with headers 'Segment ID': segment ID for downstream reach that bounds a
specific value for average annual sediment yield 'Qs': the associated value of sediment yield that applies
to segments upstream of associated segment ID (tonnes/km2/yr).
"""
self.streams = network
self.network = gpd.read_file(network)
table = pd.read_csv(qs_table, sep=',', header=0)
table = table.dropna(axis='columns')
# add da values to table and then sort by da so Qs is attributed from top of network down
da_values = []
for x in table.index:
da = self.network.loc[table.loc[x, 'Segment ID'], 'Drain_Area']
da_values.append(da)
table['DA'] = da_values
sortedtable = table.sort_values(by='DA')
self.sortedtable = sortedtable.reset_index(drop=True)
self.segids = self.sortedtable['Segment ID']
self.values = self.sortedtable['Qs']
self.topo = nt.TopologyTools(self.streams)
self.qs_to_network()
def __init__(
self,
hydrograph,
flow_exp,
network,
mannings_n=0.4,
tl_factor=15
): # should probably make mannnings n and total load factor parameters
"""
:param hydrograph: table with fields 'Gage', 'segid', 'Easting', 'Northing', 'DA', and 'Day1' ..... 'DayN'
:param denude_rate:
:param network:
"""
self.hydrographs = pd.read_csv(hydrograph, index_col='Gage')
self.flow_exp = flow_exp # need the b in the equation for flow~DA so that you can recalculate a at each time step
self.network = gpd.read_file(network)
self.mannings_n = mannings_n
self.tl_factor = tl_factor
self.nt = nt.TopologyTools(network)
# subset of hydrographs above dams
segs_ab_dams = []
for x in self.hydrographs.index:
print x
if self.network.loc[self.hydrographs.loc[x, 'segid'],
'Drain_Area'] == self.network.loc[
self.hydrographs.loc[x,
'segid'], 'eff_DA']:
segs_ab_dams.append(self.hydrographs.loc[x, 'segid'])
self.hyd_ab_dams = self.hydrographs[self.hydrographs['segid'].isin(
segs_ab_dams)]
# obtain number of time steps for output table
time = np.arange(1, self.hydrographs.shape[1] - 3, 1, dtype=np.int)
# build multi-index dataframe for storing data/outputs
self.network = gpd.read_file(network)
segments = np.arange(0, len(self.network.index + 1), 1)
ydim = len(time) * len(segments)
zeros = np.zeros((ydim, 8)) # where cols is number of attributes
iterables = [time, segments]
index = pd.MultiIndex.from_product(iterables,
names=['time', 'segment'])
self.outdf = pd.DataFrame(zeros,
index=index,
columns=[
'Q', 'Qs', 'Qs_out', 'CSR', 'Store_chan',
'Store_tot', 'Store_delta', 'S*'
]) # add the names of attributes
def __init__(self, network, updated_Q2_table, a=None, b=None):
"""
:param network: stream network shapefile
:param updated_Q2_table: csv file with stream segment id and new, post-disturbance Q2 value
"""
self.streams = network
self.a = a
self.b = b
self.network = gpd.read_file(self.streams)
table = pd.read_csv(updated_Q2_table, sep=',', header=0)
table = table.dropna(axis=0)
self.segid = table['Segment ID']
self.newQ2 = table['Updated Q2 (cms)']
self.topo = nt.TopologyTools(network)
def __init__(self, network):
"""
:param network: drainage network shapefile
"""
self.streams = network
self.network = gpd.read_file(network)
self.topo = nt.TopologyTools(network)
# add an 'effective drainage area' field, default to actual DA
if 'eff_DA' in self.network.columns:
pass
else:
for i in self.network.index:
self.network.loc[i, 'eff_DA'] = self.network.loc[i, 'Drain_Area']
# add a denudation rate field, default to 0
if 'denude' in self.network.columns:
pass
else:
for i in self.network.index:
self.network.loc[i, 'denude'] = -9999