def write_control(self, path , linkList = None):
'''Writes the control.sav file used by the model to determine at which links store the
obtained results.'''
#If no link list it tries to obtain the control fronm the database
if linkList is None:
con = db.DataBaseConnect(user='******', password='******')
if self.linkid > 0:
q = db.sql.SQL("SELECT distinct \
us.link_id \
FROM \
pers_nico.iowa_usgs_stations us, \
pers_nico.subbasin("+str(self.linkid)+") sub \
where us.link_id = sub")
elif self.linkid == 0:
q = db.sql.SQL("SELECT distinct \
us.link_id \
FROM \
pers_nico.iowa_usgs_stations us, \
pers_nico.master_lambda_vo mas \
where us.link_id = mas.link_id")
linkList = pd.read_sql(q, con).values.T.astype(int).tolist()[0]
#Opens the file
f = open(path,'w',newline = '\n')
Links = self.Table.index.tolist()
for l in linkList:
try:
Links.index(l)
f.write('%d\n' % l)
except:
pass
f.close()
return linkList
def write_rvr(self, path = None, database = 'rt_precipitation'):
#conncet to the database
con = db.DataBaseConnect(user = '******', password = '******',)
#restore_res_env_92
#Query to ask for the link ids and the topology
if self.linkid > 0:
q = db.sql.SQL("WITH all_links(id) AS (SELECT link_id FROM pers_nico.master_lambda_vo) \
SELECT all_links.id,pers_nico.master_lambda_vo.link_id FROM pers_nico.master_lambda_vo,all_links \
WHERE (all_links.id IN (SELECT nodeX.link_id FROM pers_nico.master_lambda_vo AS nodeX, \
pers_nico.master_lambda_vo AS parentX \
WHERE (nodeX.left BETWEEN parentX.left AND parentX.right) AND parentX.link_id = "+str(self.linkid)+")) AND pers_nico.master_lambda_vo.parent_link = all_links.id ORDER BY all_links.id")
elif self.linkid == 0:
q = db.sql.SQL("WITH all_links(id) AS (SELECT link_id FROM pers_nico.master_lambda_vo) \
SELECT DISTINCT all_links.id,pers_nico.master_lambda_vo.link_id FROM pers_nico.master_lambda_vo,all_links \
WHERE all_links.id > 1 AND pers_nico.master_lambda_vo.model AND \
pers_nico.master_lambda_vo.parent_link = all_links.id ORDER BY all_links.id;")
self.topo = pd.read_sql(q, con)
con.close()
topo = self.topo.values.T
#Convert the query to a rvr file
if path is not None:
f = open(path,'w', newline='\n')
f.write('%d\n\n' % topo.shape[1])
#List = self.Table.index.tolist()
for t in topo[1]:
#List.index(t)
f.write('%d\n'% t)
p = np.where(topo[0] == t)[0]
if len(p)>0:
f.write('%d ' % p.size)
for i in p:
f.write('%d ' % topo[1][i])
f.write('\n\n')
else:
f.write('0\n\n')
f.close()
#Check for consistency with the Table
a = pd.Series(self.topo.shape[0], self.topo['link_id'].values)
b = 0
for i in self.Table.index:
if i in a.index:
b += 1
else:
self.Table = self.Table.drop(i, axis = 0)
def write_rainfall(self, date1, date2, path):
'''Writes binary files for the rainfall of the defined watershed.
- date1: initial date of the data to write.
- date2: end date
- path: where to store binary files eg: /home/user/basin/rain/BasinStage4_
Returns:
- the mean rainfall of the watershed for the selected period'''
#Databse connection and query.
unix1 = str(aux.__datetime2unix__(date1))
unix2 = str(aux.__datetime2unix__(date2))
con = db.DataBaseConnect(database='rt_precipitation')
if self.linkid > 0:
q = db.sql.SQL("WITH subbasin AS (SELECT nodeX.link_id AS link_id FROM students.env_master_km \
AS nodeX, students.env_master_km AS parentX WHERE (nodeX.left BETWEEN parentX.left AND parentX.right) \
AND parentX.link_id = "+str(self.linkid)+") SELECT A.unix_time,sum(weight*A.val) as rain,B.link_id FROM stage_4.data AS \
A,env_lookup_hrap_lid_v4 AS B,subbasin WHERE A.grid_x = B.x AND A.grid_y=B.y AND B.link_id = subbasin.link_id \
AND A.unix_time >= "+str(unix1)+" AND A.unix_time < "+str(unix2)+" AND A.val < 99.0 GROUP BY B.link_id,A.unix_time ORDER BY A.unix_time")
else:
q = db.sql.SQL("SELECT \
A.unix_time, \
sum(weight*A.val) as rain, \
B.link_id \
FROM \
stage_4.data AS A, \
env_lookup_hrap_lid_v4 AS B \
WHERE A.grid_x = B.x AND A.grid_y=B.y AND A.unix_time >= "+str(unix1)+" AND A.unix_time < "+str(unix2)+" AND A.val < 999.0 \
GROUP BY B.link_id,A.unix_time \
ORDER BY A.unix_time;")
E = pd.read_sql(q, con, index_col='unix_time')
con.close()
#SEtup for the data with the mean rainfall for that period
d = pd.date_range(date1, date2, freq='1H')
MeanRain = pd.Series(np.zeros(d.size), index = d)
#Rainfall binary files creation
for i in np.arange(E.index[0], E.index[-1], 3600):
Rain = E[['link_id','rain']][E.index == i]
__saveBin__(Rain['link_id'].values, Rain['rain'].values, Rain['rain'].size,path+str(i))
MeanRain[pd.to_datetime(i,unit='s')] = Rain['rain'].mean()
MeanRain[np.isnan(MeanRain) == True] = 0.0
return MeanRain
from ifis_tools import asynch_manager as am
from ifis_tools import series_tools as ser
import pandas as pd
import glob
import numpy as np
def get_links2(l):
links = []
for i in l:
links.append(i.split('/')[-1].split('_')[0])
return links
usgs = db.SQL_USGS_at_IFIS()
#Get the link properties
q = db.sql.SQL("select link_id, travel_time07, up_area from pers_nico.master_lambda_vo")
con = db.DataBaseConnect(user='******', password='******')
Lprop = pd.read_sql(q, con, index_col='link_id')
con.close()
perf = ser.performance(links_prop=Lprop, prop_col_names={'travel_time07':'ttime','up_area':'area'})
perf.update_dic('4',
base=True,
path='/Users/nicolas/Parameter_identifiability/data/hlm_outputs/south/*vr4*',
abr = '4',
isDataFrame = True,
DataFrameColumn = 'Q',
path2linkFunc = get_links2)
perf.update_dic('5', path='/Users/nicolas/Parameter_identifiability/data/hlm_outputs/south/*vr5*',
path2linkFunc=get_links2,
isDataFrame = True,
DataFrameColumn = 'Q')