-
Notifications
You must be signed in to change notification settings - Fork 0
/
main0.py
388 lines (355 loc) · 23.7 KB
/
main0.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
# Importação de Libs
import geopandas as gpd
import pandas as pd
from flask import Flask, render_template, request, send_file, make_response
from sqlalchemy import create_engine
# # Paths de arquivos para leitura
# # PATH TRAMPO
path_bacia = "C:\\Users\\paulo.smaia\\Documents\\LOCAL_DB\\BACIAS_GO\\BACIA_PIRAPETINGA\\MINIBACIAS_PIRAPETINGA.gpkg"
path_cnarh = "C:\\Users\\paulo.smaia\\Documents\\LOCAL_DB\\BACIAS_GO\\BACIA_PIRAPETINGA\\CNARH40_PIRAPETINGA.gpkg"
path_durhs = "C:\\Users\\paulo.smaia\\Documents\\LOCAL_DB\\BACIAS_GO\\BACIA_PIRAPETINGA\\DURHS_PIRAPETINGA.gpkg"
path_subtrecho = "C:\\Users\\paulo.smaia\\Documents\\LOCAL_DB\\BACIAS_GO\\BACIA_PIRAPETINGA\\SUBTRECHOS_PIRAPETINGA.gpkg"
# # PATH HOME
# #path_bacia = "D:\\SEMAD\\arq_disph\\BACIA_JOAOLEITE.gpkg"
# #path_cnarh = "D:\\SEMAD\\arq_disph\\cnarh40_joaoleite.gpkg"
# #path_durhs = "D:\\SEMAD\\arq_disph\\durhs_111121_joaoleite_points.gpkg"
# #path_subtrecho = "D:\\SEMAD\\arq_disph\\subtrechos.gpkg"
# #logo = "D:\\SEMAD\\arq_disph\\gota_icon_conv.ico"
#
#
bacia_joaoleite = gpd.read_file(path_bacia)
cnarh4_joaoleite = gpd.read_file(path_cnarh)
durhs_joaoleite = gpd.read_file(path_durhs)
subtrechos_joaoleite = gpd.read_file(path_subtrecho)
# Acesso à base de dados
# db_url = "postgresql://adm_geout:[email protected]:5432/base_hidro"
# engine = create_engine(db_url)
#
# sql_bacia = "SELECT * FROM public.bacia_joaoleite"
# sql_durhs = "SELECT * FROM public.durhs_joaoleite"
# sql_subtrechos = "SELECT * FROM public.subtrechos_joaoleite"
# sql_cnar40 = "SELECT * FROM public.cnarh4_joaoleite"
#
# bacia_joaoleite = gpd.read_postgis(sql_bacia, engine, geom_col='geometry', crs='ESRI:102033')
# cnarh4_joaoleite = gpd.read_postgis(sql_cnar40, engine, geom_col='geometry', crs='ESRI:102033')
# durhs_joaoleite = gpd.read_postgis(sql_durhs, engine, geom_col='geometry', crs='ESRI:102033')
# subtrechos_joaoleite = gpd.read_postgis(sql_subtrechos, engine, geom_col='geometry', crs='ESRI:102033')
# Reprojeção
bacia_joaoleite = bacia_joaoleite.to_crs(crs='EPSG:4674')
cnarh4_joaoleite = cnarh4_joaoleite.to_crs(crs='EPSG:4674')
durhs_joaoleite = durhs_joaoleite.to_crs(crs='EPSG:4674')
subtrechos_joaoleite = subtrechos_joaoleite.to_crs(crs='EPSG:4674')
# Tranformação de afluentes em 0 e mudança de tipo de dado
subtrechos_joaoleite['trecho_princ'] = (subtrechos_joaoleite['trecho_princ'].fillna(0)).astype(int)
subtrechos_joaoleite['esp_cd'] = subtrechos_joaoleite['esp_cd'].fillna(0)
subtrechos_joaoleite['q_q95espano'] = subtrechos_joaoleite['q_q95espano'].fillna(0)
# Cálculo da área à montante
def CalcAreaMont(location,durhs_joaoleite,subtrechos_joaoleite):
dic = {"cocursodag":(location.iloc[0]['cocursodag']), "cobacia":(location.iloc[0]['cobacia'])}
cobacia = dic.get("cobacia")
sel_loc = location[location['cobacia'] == cobacia]
area_mont = sel_loc['Q_nuareamont']
return area_mont
# Cálculo das Vazões sazonais com base na cobacia do subtrecho
# UNIDADE SAI EM m³/s
def ConVazoesSazonais(location,durhs_joaoleite,subtrechos_joaoleite):
DQ95ESPMES = [location.iloc[0]['Q95ESPJan'],location.iloc[0]['Q95ESPFev'],
location.iloc[0]['Q95ESPMar'],location.iloc[0]['Q95ESPAbr'],
location.iloc[0]['Q95ESPMai'],location.iloc[0]['Q95ESPJun'],
location.iloc[0]['Q95ESPJul'],location.iloc[0]['Q95ESPAgo'],
location.iloc[0]['Q95ESPSet'],location.iloc[0]['Q95ESPOut'],
location.iloc[0]['Q95ESPNov'],location.iloc[0]['Q95ESPDez']]
Q95Local = [location.iloc[0]['Q_DQ95Jan']*1000,location.iloc[0]['Q_DQ95Fev']*1000,
location.iloc[0]['Q_DQ95Mar']*1000,location.iloc[0]['Q_DQ95Abr']*1000,
location.iloc[0]['Q_DQ95Mai']*1000,location.iloc[0]['Q_DQ95Jun']*1000,
location.iloc[0]['Q_DQ95Jul']*1000,location.iloc[0]['Q_DQ95Ago']*1000,
location.iloc[0]['Q_DQ95Set']*1000,location.iloc[0]['Q_DQ95Out']*1000,
location.iloc[0]['Q_DQ95Nov']*1000,location.iloc[0]['Q_DQ95Dez']*1000]
Qoutorgavel = [i * 0.5 for i in Q95Local]
return DQ95ESPMES, Q95Local, Qoutorgavel
# CONSULTA DE DADOS DAS OUTORGAS À MONTANTE
def ConOutorgasAMontante(location,durhs_joaoleite,cnarh4_joaoleite,subtrechos_joaoleite):
dic = {"cocursodag":(location.iloc[0]['cocursodag']), "cobacia":(location.iloc[0]['cobacia']), "area_km2":(location.iloc[0]['area_km2'])}
cobacia = dic.get("cobacia")
cocursodag = dic.get("cocursodag")
area_km2 = dic.get("area_km2")
filter_otto = ((cnarh4_joaoleite['cocursodag'].str.contains(cocursodag)) & (cnarh4_joaoleite['cobacia'] > (cobacia)) & (cnarh4_joaoleite['INT_TSU_DS'] != 'Subterrânea'))
sel_cnarh_externo = cnarh4_joaoleite[filter_otto] #seleção cnarh externa utilizando cod. otto
filter_trec_princ = ((cnarh4_joaoleite['cobacia']==cobacia) & (cnarh4_joaoleite['cocursodag'] == cocursodag)& (cnarh4_joaoleite['INT_TSU_DS'] != 'Subterrânea')) #Análise em subtrecho????
filter_trec_princ = cnarh4_joaoleite[filter_trec_princ]
filter_trec_princ = gpd.sjoin_nearest(filter_trec_princ, subtrechos_joaoleite, how='inner')
sel_trec_princ = (filter_teste.loc[filter_teste['trecho_princ'] == 1]) #seleção cnarh interna para trecho principal
merge_all_cnarh = pd.concat([sel_trec_princ,sel_cnarh_externo])
dados_cnarh = merge_all_cnarh.loc[:,('INT_CD_CNARH40','EMP_NM_EMPREENDIMENTO','EMP_NM_USUARIO',
'EMP_NU_CPFCNPJ','EMP_DS_EMAILRESPONSAVEL','EMP_NU_CEPENDERECO',
'EMP_CD_IBGEMUNCORRESPONDENCIA','EMP_DS_LOGRADOURO','EMP_DS_COMPLEMENTOENDERECO',
'EMP_NU_LOGRADOURO','EMP_NU_CAIXAPOSTAL','EMP_DS_BAIRRO','EMP_NU_DDD','EMP_NU_TELEFONE',
'EMP_SG_UF','EMP_NM_MUNICIPIO')]
return dados_cnarh
# CONSULTA DE VAZOES DAS OUTORGAS À MONTANTE
def ConOutorgasTotaisAMontante(location,cnarh4_joaoleite,subtrechos_joaoleite):
dic = {"cocursodag":(location.iloc[0]['cocursodag']),
"cobacia":(location.iloc[0]['cobacia']),
"area_km2":(location.iloc[0]['area_km2'])}
cobacia = dic.get("cobacia")
cocursodag = dic.get("cocursodag")
area_km2 = dic.get("area_km2")
filter_otto = ((cnarh4_joaoleite['cocursodag'].str.contains(cocursodag)) & (cnarh4_joaoleite['cobacia'] > (cobacia))
& (cnarh4_joaoleite['INT_TSU_DS'] != 'Subterrânea'))
sel_cnarh_externo = cnarh4_joaoleite[filter_otto] #seleção cnarh externa utilizando cod. otto
filter_trec_princ = ((cnarh4_joaoleite['cobacia']==cobacia) & (cnarh4_joaoleite['cocursodag'] == cocursodag)
& (cnarh4_joaoleite['INT_TSU_DS'] != 'Subterrânea')) #Análise em subtrecho????
filter_trec_princ = cnarh4_joaoleite[filter_trec_princ]
filter_trec_princ = gpd.sjoin_nearest(filter_trec_princ, subtrechos_joaoleite, how='inner')
sel_trec_princ = (filter_trec_princ.loc[filter_trec_princ['trecho_princ'] == 1]) #seleção cnarh interna para trecho principal
merge_all_cnarh = pd.concat([sel_trec_princ,sel_cnarh_externo])
merge_all_cnarh.loc[:,'DAD_QT_VAZAODIAJAN':'DAD_QT_VAZAODIADEZ'] = merge_all_cnarh.loc[:,'DAD_QT_VAZAODIAJAN':'DAD_QT_VAZAODIADEZ'].astype(str).stack().str.replace('.','', regex=True).unstack()
merge_all_cnarh.loc[:,'DAD_QT_VAZAODIAJAN':'DAD_QT_VAZAODIADEZ'] = merge_all_cnarh.loc[:,'DAD_QT_VAZAODIAJAN':'DAD_QT_VAZAODIADEZ'].astype(str).stack().str.replace(',','.', regex=True).unstack()
merge_all_cnarh = merge_all_cnarh.fillna(value=0)
merge_all_cnarh.loc[:,'DAD_QT_VAZAODIAJAN':'DAD_QT_VAZAODIADEZ'] = merge_all_cnarh.loc[:,'DAD_QT_VAZAODIAJAN':'DAD_QT_VAZAODIADEZ'].astype(float)
tot_cnarh_jan = merge_all_cnarh[merge_all_cnarh['DAD_QT_VAZAODIAJAN'] != 0]
count_cnarh_jan = tot_cnarh_jan[tot_cnarh_jan.columns[0]].count()
tot_cnarh_fev = merge_all_cnarh[merge_all_cnarh['DAD_QT_VAZAODIAFEV'] != 0]
count_cnarh_fev = tot_cnarh_fev[tot_cnarh_fev.columns[0]].count()
tot_cnarh_mar = merge_all_cnarh[merge_all_cnarh['DAD_QT_VAZAODIAMAR'] != 0]
count_cnarh_mar = tot_cnarh_mar[tot_cnarh_mar.columns[0]].count()
tot_cnarh_abr = merge_all_cnarh[merge_all_cnarh['DAD_QT_VAZAODIAABR'] != 0]
count_cnarh_abr = tot_cnarh_abr[tot_cnarh_abr.columns[0]].count()
tot_cnarh_mai = merge_all_cnarh[merge_all_cnarh['DAD_QT_VAZAODIAMAI'] != 0]
count_cnarh_mai = tot_cnarh_mai[tot_cnarh_mai.columns[0]].count()
tot_cnarh_jun = merge_all_cnarh[merge_all_cnarh['DAD_QT_VAZAODIAJUN'] != 0]
count_cnarh_jun = tot_cnarh_jun[tot_cnarh_jun.columns[0]].count()
tot_cnarh_jul = merge_all_cnarh[merge_all_cnarh['DAD_QT_VAZAODIAJUL'] != 0]
count_cnarh_jul = tot_cnarh_jul[tot_cnarh_jul.columns[0]].count()
tot_cnarh_ago = merge_all_cnarh[merge_all_cnarh['DAD_QT_VAZAODIAAGO'] != 0]
count_cnarh_ago = tot_cnarh_ago[tot_cnarh_ago.columns[0]].count()
tot_cnarh_set = merge_all_cnarh[merge_all_cnarh['DAD_QT_VAZAODIASET'] != 0]
count_cnarh_set = tot_cnarh_set[tot_cnarh_set.columns[0]].count()
tot_cnarh_out = merge_all_cnarh[merge_all_cnarh['DAD_QT_VAZAODIAOUT'] != 0]
count_cnarh_out = tot_cnarh_out[tot_cnarh_out.columns[0]].count()
tot_cnarh_nov = merge_all_cnarh[merge_all_cnarh['DAD_QT_VAZAODIANOV'] != 0]
count_cnarh_nov = tot_cnarh_nov[tot_cnarh_nov.columns[0]].count()
tot_cnarh_dez = merge_all_cnarh[merge_all_cnarh['DAD_QT_VAZAODIADEZ'] != 0]
count_cnarh_dez = tot_cnarh_dez[tot_cnarh_dez.columns[0]].count()
total_outorgas = [count_cnarh_jan,count_cnarh_fev,count_cnarh_mar,count_cnarh_abr,
count_cnarh_mai,count_cnarh_jun,count_cnarh_jul,count_cnarh_ago,
count_cnarh_set,count_cnarh_out,count_cnarh_nov,count_cnarh_dez]
# Soma da DAD_QT_VAZAODIAMES e converter p L/s (*1000)/3600
vazao_tot_cnarh = [sum(merge_all_cnarh['DAD_QT_VAZAODIAJAN']/3.6),sum(merge_all_cnarh['DAD_QT_VAZAODIAFEV']/3.6),
sum(merge_all_cnarh['DAD_QT_VAZAODIAMAR']/3.6),sum(merge_all_cnarh['DAD_QT_VAZAODIAABR']/3.6),
sum(merge_all_cnarh['DAD_QT_VAZAODIAMAI']/3.6),sum(merge_all_cnarh['DAD_QT_VAZAODIAJUN']/3.6),
sum(merge_all_cnarh['DAD_QT_VAZAODIAJUL']/3.6),sum(merge_all_cnarh['DAD_QT_VAZAODIAAGO']/3.6),
sum(merge_all_cnarh['DAD_QT_VAZAODIASET']/3.6),sum(merge_all_cnarh['DAD_QT_VAZAODIAOUT']/3.6),
sum(merge_all_cnarh['DAD_QT_VAZAODIANOV']/3.6),sum(merge_all_cnarh['DAD_QT_VAZAODIADEZ']/3.6)]
return total_outorgas,vazao_tot_cnarh
# CONSULTA DE INFORMAÇÕES DA DURH ANALISADA
def getinfodurh(location):
# VAZÃO POR DIA
Qls = [location.iloc[0]['dad_qt_vazaodiajan'],location.iloc[0]['dad_qt_vazaodiafev'],
location.iloc[0]['dad_qt_vazaodiamar'],location.iloc[0]['dad_qt_vazaodiaabr'],
location.iloc[0]['dad_qt_vazaodiamai'],location.iloc[0]['dad_qt_vazaodiajun'],
location.iloc[0]['dad_qt_vazaodiajul'],location.iloc[0]['dad_qt_vazaodiaago'],
location.iloc[0]['dad_qt_vazaodiaset'],location.iloc[0]['dad_qt_vazaodiaout'],
location.iloc[0]['dad_qt_vazaodianov'],location.iloc[0]['dad_qt_vazaodiadez']]
# HORAS POR DIA
HD = [location.iloc[0]['dad_qt_horasdiajan'],location.iloc[0]['dad_qt_horasdiafev'],
location.iloc[0]['dad_qt_horasdiamar'],location.iloc[0]['dad_qt_horasdiaabr'],
location.iloc[0]['dad_qt_horasdiamai'],location.iloc[0]['dad_qt_horasdiajun'],
location.iloc[0]['dad_qt_horasdiajul'],location.iloc[0]['dad_qt_horasdiaago'],
location.iloc[0]['dad_qt_horasdiaset'],location.iloc[0]['dad_qt_horasdiaout'],
location.iloc[0]['dad_qt_horasdianov'],location.iloc[0]['dad_qt_horasdiadez']]
# DIA POR MES
DM = [location.iloc[0]['dad_qt_diasjan'],location.iloc[0]['dad_qt_diasfev'],
location.iloc[0]['dad_qt_diasmar'],location.iloc[0]['dad_qt_diasabr'],
location.iloc[0]['dad_qt_diasmai'],location.iloc[0]['dad_qt_diasjun'],
location.iloc[0]['dad_qt_diasjul'],location.iloc[0]['dad_qt_diasago'],
location.iloc[0]['dad_qt_diasset'],location.iloc[0]['dad_qt_diasout'],
location.iloc[0]['dad_qt_diasnov'],location.iloc[0]['dad_qt_diasdez']]
# HORAS POR MES
HM = [(location.iloc[0]['dad_qt_horasdiajan'])*(location.iloc[0]['dad_qt_diasjan']),
(location.iloc[0]['dad_qt_horasdiafev'])*(location.iloc[0]['dad_qt_diasfev']),
(location.iloc[0]['dad_qt_horasdiamar'])*(location.iloc[0]['dad_qt_diasmar']),
(location.iloc[0]['dad_qt_horasdiaabr'])*(location.iloc[0]['dad_qt_diasabr']),
(location.iloc[0]['dad_qt_horasdiamai'])*(location.iloc[0]['dad_qt_diasmai']),
(location.iloc[0]['dad_qt_horasdiajun'])*(location.iloc[0]['dad_qt_diasjun']),
(location.iloc[0]['dad_qt_horasdiajul'])*(location.iloc[0]['dad_qt_diasjul']),
(location.iloc[0]['dad_qt_horasdiaago'])*(location.iloc[0]['dad_qt_diasago']),
(location.iloc[0]['dad_qt_horasdiaset'])*(location.iloc[0]['dad_qt_diasset']),
(location.iloc[0]['dad_qt_horasdiaout'])*(location.iloc[0]['dad_qt_diasout']),
(location.iloc[0]['dad_qt_horasdianov'])*(location.iloc[0]['dad_qt_diasnov']),
(location.iloc[0]['dad_qt_horasdiadez'])*(location.iloc[0]['dad_qt_diasdez'])]
# M³ POR MÊS
M3 = [((x*y)*3.6) for x,y in zip(HM,Qls)]
# DIC DE INFORMAÇÕES
teste = {"Vazão/Dia":Qls,
"Horas/Mês":list(map(int, HM)),
"Horas/Dia":list(map(int, HD)),
"Dia/Mês":list(map(int, DM)),
"M³/Mês":M3}
# CRIAR DATAFRAME
dfinfos = pd.DataFrame(teste,index=['Jan', 'Fev', 'Mar', 'Abr', 'Mai', 'Jun', 'Jul', 'Ago', 'Set', 'Out', 'Nov', 'Dez'])
return dfinfos
#FUNÇÃO DE VAZAO DAS DURHS VALIDADAS
def ConVazoesDurhsValid(location,durhs_joaoleite,subtrechos_joaoleite):
dic = {"cocursodag":(location.iloc[0]['cocursodag']), "cobacia":(location.iloc[0]['cobacia']), "area_km2":(location.iloc[0]['area_km2'])}
cobacia = dic.get("cobacia")
cocursodag = dic.get("cocursodag")
sel_bacia = ((bacia_joaoleite['cocursodag'].str.contains(cocursodag)) & (bacia_joaoleite['cobacia'] > (cobacia)))
sel_bacia = bacia_joaoleite[sel_bacia]
sel_durhs_vald = durhs_joaoleite.loc[durhs_joaoleite['situacaodurh']== 'Validada'] # situacaodurh
clip_durhs = sel_durhs_vald.clip(sel_bacia)
tot_durh_jan = clip_durhs[clip_durhs['dad_qt_vazaodiajan'] != 0]
count_durhs_jan = tot_durh_jan[tot_durh_jan.columns[0]].count()
tot_durh_fev = clip_durhs[clip_durhs['dad_qt_vazaodiafev'] != 0]
count_durhs_fev = tot_durh_fev[tot_durh_fev.columns[0]].count()
tot_durh_mar = clip_durhs[clip_durhs['dad_qt_vazaodiamar'] != 0]
count_durhs_mar = tot_durh_mar[tot_durh_mar.columns[0]].count()
tot_durh_abr = clip_durhs[clip_durhs['dad_qt_vazaodiaabr'] != 0]
count_durhs_abr = tot_durh_abr[tot_durh_abr.columns[0]].count()
tot_durh_mai = clip_durhs[clip_durhs['dad_qt_vazaodiamai'] != 0]
count_durhs_mai = tot_durh_mai[tot_durh_mai.columns[0]].count()
tot_durh_jun = clip_durhs[clip_durhs['dad_qt_vazaodiajun'] != 0]
count_durhs_jun = tot_durh_jun[tot_durh_jun.columns[0]].count()
tot_durh_jul = clip_durhs[clip_durhs['dad_qt_vazaodiajul'] != 0]
count_durhs_jul = tot_durh_jul[tot_durh_jul.columns[0]].count()
tot_durh_ago = clip_durhs[clip_durhs['dad_qt_vazaodiaago'] != 0]
count_durhs_ago = tot_durh_ago[tot_durh_ago.columns[0]].count()
tot_durh_set = clip_durhs[clip_durhs['dad_qt_vazaodiaset'] != 0]
count_durhs_set = tot_durh_set[tot_durh_set.columns[0]].count()
tot_durh_out = clip_durhs[clip_durhs['dad_qt_vazaodiaout'] != 0]
count_durhs_out = tot_durh_out[tot_durh_out.columns[0]].count()
tot_durh_nov = clip_durhs[clip_durhs['dad_qt_vazaodianov'] != 0]
count_durhs_nov = tot_durh_nov[tot_durh_nov.columns[0]].count()
tot_durh_dez = clip_durhs[clip_durhs['dad_qt_vazaodiadez'] != 0]
count_durhs_dez = tot_durh_dez[tot_durh_dez.columns[0]].count()
total_durhs_mont = [count_durhs_jan,count_durhs_fev,count_durhs_mar,count_durhs_abr,
count_durhs_mai,count_durhs_jun,count_durhs_jul,count_durhs_ago,
count_durhs_set,count_durhs_out,count_durhs_nov,count_durhs_dez]
vaz_durhs_mont = [sum(clip_durhs.dad_qt_vazaodiajan), sum(clip_durhs.dad_qt_vazaodiafev),
sum(clip_durhs.dad_qt_vazaodiamar), sum(clip_durhs.dad_qt_vazaodiaabr),
sum(clip_durhs.dad_qt_vazaodiamai), sum(clip_durhs.dad_qt_vazaodiajun),
sum(clip_durhs.dad_qt_vazaodiajul), sum(clip_durhs.dad_qt_vazaodiaago),
sum(clip_durhs.dad_qt_vazaodiaset), sum(clip_durhs.dad_qt_vazaodiaout),
sum(clip_durhs.dad_qt_vazaodianov), sum(clip_durhs.dad_qt_vazaodiadez)]
return total_durhs_mont,vaz_durhs_mont
#Durhs diferente de validadas
def VazDurhsDif(location, subtrechos_joaoleite, durhs_joaoleite):
dic = {"cocursodag": (location.iloc[0]['cocursodag']), "cobacia": (location.iloc[0]['cobacia']),
"area_km2": (location.iloc[0]['area_km2'])}
cobacia = dic.get("cobacia")
cocursodag = dic.get("cocursodag")
sel_bacia = ((bacia_joaoleite['cocursodag'].str.contains(cocursodag)) & (bacia_joaoleite['cobacia'] > (cobacia)))
sel_bacia = bacia_joaoleite[sel_bacia]
sel_durhs = durhs_joaoleite.loc[(durhs_joaoleite['situacaodurh'] == 'Sujeita a outorga') |
(durhs_joaoleite['situacaodurh'] == 'Em Retificação') |
(durhs_joaoleite['situacaodurh'] == 'Enviada') |
(durhs_joaoleite['situacaodurh'] == 'Paralisada') |
(durhs_joaoleite['situacaodurh'] == 'Pendente')]
durhs_dif_mont = sel_durhs.clip(sel_bacia)
durh_dif_jan = durhs_dif_mont[durhs_dif_mont['dad_qt_vazaodiajan'] != 0]
count_durhs_jan = durh_dif_jan[durh_dif_jan.columns[0]].count()
durh_dif_fev = durhs_dif_mont[durhs_dif_mont['dad_qt_vazaodiafev'] != 0]
count_durhs_fev = durh_dif_fev[durh_dif_fev.columns[0]].count()
durh_dif_mar = durhs_dif_mont[durhs_dif_mont['dad_qt_vazaodiamar'] != 0]
count_durhs_mar = durh_dif_mar[durh_dif_mar.columns[0]].count()
durh_dif_abr = durhs_dif_mont[durhs_dif_mont['dad_qt_vazaodiaabr'] != 0]
count_durhs_abr = durh_dif_abr[durh_dif_abr.columns[0]].count()
durh_dif_mai = durhs_dif_mont[durhs_dif_mont['dad_qt_vazaodiamai'] != 0]
count_durhs_mai = durh_dif_mai[durh_dif_mai.columns[0]].count()
durh_dif_jun = durhs_dif_mont[durhs_dif_mont['dad_qt_vazaodiajun'] != 0]
count_durhs_jun = durh_dif_jun[durh_dif_jun.columns[0]].count()
durh_dif_jul = durhs_dif_mont[durhs_dif_mont['dad_qt_vazaodiajul'] != 0]
count_durhs_jul = durh_dif_jul[durh_dif_jul.columns[0]].count()
durh_dif_ago = durhs_dif_mont[durhs_dif_mont['dad_qt_vazaodiaago'] != 0]
count_durhs_ago = durh_dif_ago[durh_dif_ago.columns[0]].count()
durh_dif_set = durhs_dif_mont[durhs_dif_mont['dad_qt_vazaodiaset'] != 0]
count_durhs_set = durh_dif_set[durh_dif_set.columns[0]].count()
durh_dif_out = durhs_dif_mont[durhs_dif_mont['dad_qt_vazaodiaout'] != 0]
count_durhs_out = durh_dif_out[durh_dif_out.columns[0]].count()
durh_dif_nov = durhs_dif_mont[durhs_dif_mont['dad_qt_vazaodianov'] != 0]
count_durhs_nov = durh_dif_nov[durh_dif_nov.columns[0]].count()
durh_dif_dez = durhs_dif_mont[durhs_dif_mont['dad_qt_vazaodiadez'] != 0]
count_durhs_dez = durh_dif_dez[durh_dif_dez.columns[0]].count()
total_durhsdif_mont = [count_durhs_jan, count_durhs_fev, count_durhs_mar, count_durhs_abr,
count_durhs_mai, count_durhs_jun, count_durhs_jul, count_durhs_ago,
count_durhs_set, count_durhs_out, count_durhs_nov, count_durhs_dez]
vaz_durhs_dif = [sum(durhs_dif_mont.dad_qt_vazaodiajan), sum(durhs_dif_mont.dad_qt_vazaodiafev),
sum(durhs_dif_mont.dad_qt_vazaodiamar), sum(durhs_dif_mont.dad_qt_vazaodiaabr),
sum(durhs_dif_mont.dad_qt_vazaodiamai), sum(durhs_dif_mont.dad_qt_vazaodiajun),
sum(durhs_dif_mont.dad_qt_vazaodiajul), sum(durhs_dif_mont.dad_qt_vazaodiaago),
sum(durhs_dif_mont.dad_qt_vazaodiaset), sum(durhs_dif_mont.dad_qt_vazaodiaout),
sum(durhs_dif_mont.dad_qt_vazaodianov), sum(durhs_dif_mont.dad_qt_vazaodiadez)]
dicdif = {"Vazão durhs": vaz_durhs_dif,
"Qnt. usuarios": total_durhsdif_mont}
dfdurhs = pd.DataFrame(dicdif,
index=['Jan', 'Fev', 'Mar', 'Abr', 'Mai', 'Jun', 'Jul', 'Ago', 'Set', 'Out', 'Nov', 'Dez'])
return dfdurhs
# Após passar no critério de localização, a função de análise é executada
def analise(location):
total_outorgas, vazao_tot_cnarh = ConOutorgasTotaisAMontante(location,cnarh4_joaoleite,subtrechos_joaoleite)
DQ95ESPMES, Q95Local, Qoutorgavel = ConVazoesSazonais(location, durhs_joaoleite, subtrechos_joaoleite)
total_durhs_mont, vaz_durhs_mont = ConVazoesDurhsValid(location, durhs_joaoleite, subtrechos_joaoleite)
dfinfos = getinfodurh(location)
dfdurhs = VazDurhsDif(location, subtrechos_joaoleite, durhs_joaoleite) # durhs diferentes de validaadas
dfinfos['Q95 local l/s'] = Q95Local
dfinfos['Q95 Esp l/s/km²'] = DQ95ESPMES
dfinfos['Durhs val à mont'] = total_durhs_mont
dfinfos['vazao total Durhs Montante'] = vaz_durhs_mont
dfinfos["Qnt de outorgas à mont "] = total_outorgas
dfinfos["Vazao Total cnarh Montante L/s"] = vazao_tot_cnarh
dfinfos['Vazão Total à Montante'] = [(x + y) for x, y in zip(vazao_tot_cnarh, vaz_durhs_mont)]
dfinfos["Comprom individual(%)"] = (dfinfos['Vazão/Dia'] / (dfinfos['Q95 local l/s'] * 0.5)) * 100
dfinfos["Comprom bacia(%)"] = ((dfinfos['Vazão/Dia'] + dfinfos['Vazão Total à Montante']) / (dfinfos['Q95 local l/s'] * 0.5)) * 100
dfinfos["Q outorgável"] = Qoutorgavel
dfinfos["Q disponível"] = [(x - y - z) for x, y, z in zip(Q95Local, Qoutorgavel, (dfinfos['Vazão Total à Montante']))]
dfinfos.loc[dfinfos['Comprom bacia(%)'] > 100, 'Nivel critico Bacia'] = 'Alto Critico'
dfinfos.loc[dfinfos['Comprom bacia(%)'] <= 100, 'Nivel critico Bacia'] = 'Moderado Critico'
dfinfos.loc[dfinfos['Comprom bacia(%)'] <= 80, 'Nivel critico Bacia'] = 'Alerta'
dfinfos.loc[dfinfos['Comprom bacia(%)'] <= 50, 'Nivel critico Bacia'] = 'Normal'
# print(dfinfos)
return dfinfos
# Função inicial para pegar a localização da Durh
def getlocation(numero_durh, durhs_joaoleite, subtrechos_joaoleite):
point = durhs_joaoleite.loc[durhs_joaoleite['numerodurh']== numero_durh] # AQUI ENTRA NUMERO DA DURH
location = gpd.sjoin_nearest(point,subtrechos_joaoleite, how='inner')
if (location.iloc[0]['q_q95espano'] == 0):
print("Subtrecho em barragem/massa d'agua") # FUTURO POP-UP DE NOTIFICAÇÃO
else:
print("Subtrecho fora de barragem/massa d'agua")
mun_durh = point.iloc[0]['municipio']
corpodagua = point.iloc[0]['corpodagua']
subbacia = point.iloc[0]['subbacia']
analise(location)
return point, location, mun_durh, corpodagua, subbacia
# função inicial para rodar a localização
#def run(numero_durh):
# location, point = getlocation(numero_durh,durhs_joaoleite,subtrechos_joaoleite)
# return numero_durh,location
app = Flask(__name__)
@app.route("/")
# Função -> O que vc quer exibir naquela pagina
def homepage():
return render_template('homepage.html')
@app.route("/Resultados", methods=["POST", "GET"])
def run():
numero_durh = request.form['numero_durh']
point, location, mun_durh, corpodagua, subbacia = getlocation(numero_durh,durhs_joaoleite,subtrechos_joaoleite)
dfinfos = analise(location)
return render_template('resultados.html',
numero_durh=numero_durh,
dfinfos=dfinfos,
mun_durh=mun_durh,
corpodagua=corpodagua,
subbacia=subbacia,
tables=[dfinfos.to_html(classes='data', header="true")])
@app.route("/")
def return_to():
return redirect(url_for("/"))
#@app.route("/Resultados", methods=["GET"])
#def resultados():
# dfinfos = run()
# return render_template('resultados.html', tables=[dfinfos.to_html(classes='data', header="true")])
# DURH023031
#Colocar o site no ar
if __name__ == "__main__":
app.run(debug=True)