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model.py
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"""model threat """
import logging
# import psycopg2
# import psycopg2.extras
from flask import g
import os
# import numpy as np
import collections
import statistics
import copy
import siteutils
cwd = os.path.dirname(os.path.realpath(__file__))
logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)
fh = logging.FileHandler(cwd + '/logs/logs.log')
formatter = logging.Formatter(
'%(asctime)s - %(name)s, %(lineno)s - %(levelname)s - %(message)s',
datefmt='%m/%d %H:%M:%S'
)
fh.setFormatter(formatter)
logger.addHandler(fh)
# def get_threat_report(huc12_str, query):
# col_hdrs = []
# outputType = []
# huc12s = huc12_str.split(", ")
# huc12s.sort()
# for col_hdr in query.keys():
# if col_hdr != 'year':
# col_hdrs.append(col_hdr)
# col_hdrs.sort()
# col_hdrs.append("result")
# # logger.debug(col_hdr)
# col_len = len(huc12s)
# outputType.append(("huc12", "U20"))
# for col_hdr in col_hdrs:
# outputType.append((col_hdr, 'i4'))
# dtype = np.dtype(outputType)
# nparray = np.ones((col_len,), dtype=dtype)
# for idx, row in enumerate(nparray):
# huc12 = huc12s[idx]
# # set huc12 value
# row['huc12'] = huc12
# # now rest of columns
# num_factors = len(query.keys()) - 1
# year = query.get('year')
# threat = 0
# if(query.get('urb', default='off') == 'on'):
# with g.db.cursor(cursor_factory=psycopg2.extras.DictCursor) as cur:
# cur.execute(
# "select * from nc_urb_mean where huc_12 = %s", (huc12, )
# )
# rec = cur.fetchone()
# try:
# threat += rec["yr" + year]
# row['urb'] = rec["yr" + year]
# except KeyError:
# continue
# if(query.get('frag', default='off') == 'on'):
# with g.db.cursor(cursor_factory=psycopg2.extras.DictCursor) as cur:
# cur.execute(
# "select * from data_frag where huc_12 = %s", (huc12, )
# )
# rec = cur.fetchone()
# try:
# threat += rec["yr" + year]
# row['frag'] = rec["yr" + year]
# except KeyError:
# continue
# with g.db.cursor(cursor_factory=psycopg2.extras.DictCursor) as cur:
# cur.execute(
# "select * from data_static where huc_12 = %s", (huc12, )
# )
# rec = cur.fetchone()
# if(query.get('polu1', default='off') == 'on'):
# threat += rec['polu1']
# row['polu1'] = rec['polu1']
# if(query.get('polu2', default='off') == 'on'):
# threat += rec['polu2']
# row['polu2'] = rec['polu2']
# if(query.get('dise1', default='off') == 'on'):
# threat += rec['dise1']
# row['dise1'] = rec['dise1']
# if(query.get('dise2', default='off') == 'on'):
# threat += rec['dise2']
# row['dise2'] = rec['dise2']
# if(query.get('slr', default='off') == 'on'):
# threat += rec['slr']
# row['slr'] = rec['slr']
# if(query.get('firp', default='off') == 'on'):
# threat += rec['firp']
# row['firp'] = rec['firp']
# if(query.get('firs', default='off') == 'on'):
# threat += rec['firs']
# row['firs'] = rec['firs']
# if(query.get('tran', default='off') == 'on'):
# threat += rec['tran']
# row['tran'] = rec['tran']
# try:
# threat = threat / (num_factors * 200) + 1
# except ZeroDivisionError:
# threat = 1
# pass
# if threat == 6:
# threat = 5
# row['result'] = threat
# col_disp = []
# for col in nparray.dtype.names:
# col_disp.append(col_names[col])
# return {
# "res_arr": nparray.tolist(),
# "col_hdrs": col_disp,
# "year": year
# }
col_names = {
'x': 'Baseline',
'a': 'Biofuel A',
'b': 'Biofuel B',
'c': 'Biofuel C',
'd': 'Biofuel D',
'e': 'Biofuel E',
'frst': 'Forest',
'ftwt': 'Wet forest',
'open': 'Open',
'shrb': 'Scrub',
'hbwt': 'Wet herbaceous'
}
def get_threat_report2(id, formdata, mode='state', huc12=''):
# logger.debug
formvals = {}
model_cols = ["huc"]
model_wts = []
mean_pct_areas = {}
logger.debug(formdata)
logger.debug(mode)
# create dict w/ key huc12 and val empty list
hucs_dict = collections.OrderedDict()
rank_data = collections.OrderedDict()
dt_data = collections.OrderedDict()
if int(id) == 0 or mode == 'state':
# could use any table here
query = "select huc12rng from huc_names order by huc12rng"
with g.db.cursor() as cur:
cur.execute(query)
hucs = cur.fetchall()
for huc in hucs:
hucs_dict[huc[0]] = []
hucs_dict[huc[0]].append(huc[0])
elif mode == 'aoi':
with g.db.cursor() as cur:
cur.execute("select huc12s from aoi_results where pk = %s", (id, ))
huc12_str = cur.fetchone()
hucs = huc12_str[0].split(",")
for huc in hucs:
hucs_dict[huc.strip()] = []
hucs_dict[huc.strip()].append(huc.strip())
elif mode == '12k':
with g.db.cursor() as cur:
cur.execute(
"select huc12s_12k from aoi_results where pk = %s", (id, )
)
huc12_str = cur.fetchone()
hucs = huc12_str[0].split(",")
for huc in hucs:
hucs_dict[huc.strip()] = []
hucs_dict[huc.strip()].append(huc.strip())
elif mode == '5k':
with g.db.cursor() as cur:
cur.execute(
"select huc12s_5k from aoi_results where pk = %s", (id, )
)
huc12_str = cur.fetchone()
hucs = huc12_str[0].split(",")
for huc in hucs:
hucs_dict[huc.strip()] = []
hucs_dict[huc.strip()].append(huc.strip())
elif mode == 'huc12':
hucs_dict[huc12] = [huc12]
hucs_dict_sv = copy.deepcopy(hucs_dict)
logger.debug(hucs_dict_sv)
# read formdata into formvals excluding notinclude
for formval in formdata:
if formdata[formval] == 'notinclude':
continue
formvals[formval] = formdata[formval]
try:
year = formvals['year']
scenario = formvals['scenario']
# habitat = formvals['habitat']
except KeyError:
year = '2010'
pass
# logger.info(formvals)
model_length = 0
# add habitat in in model
if 'frst' in formvals:
rank_data['frst'] = []
dt_data['frst'] = []
query = "select huc_12, frst%ssv, frst%sdt from lcscen_%s" % (
year[2:],
year[2:],
scenario
)
# query2 = "select huc_12, %s%spct from lcscen_%s_pct" % (
# 'frst',
# year[2:],
# scenario
# )
logger.debug(query)
# model_wts.append(float(formvals['frst']))
model_length += 1
model_col = "%s %s - (%s)" % (
col_names['frst'],
col_names[scenario],
formvals['frst']
)
model_cols.append(model_col)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
# logger.debug(row)
# if formvals['mode'] == 'single':
# try:
# hucs_dict[row[0]].append(row[1])
# except KeyError:
# pass
# continue
if float(row[2]) > float(formvals['frst']):
above = 1
# rank = int(row[2])
else:
above = 0
# rank = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
# must follow this line to get hucs correct
rank_data['frst'].append(float(row[1]))
dt_data['frst'].append(float(row[2]))
except KeyError:
pass
# pct_arr = []
# with g.db.cursor() as cur:
# cur.execute(query2)
# for row in cur:
# if row[0] in hucs_dict:
# pct_arr.append(row[1])
# pct_mean = statistics.mean(pct_arr)
# logger.debug(int(pct_mean * 10) / 10.0)
# mean_pct_areas['frst'] = int(pct_mean * 10) / 10.0
if 'ftwt' in formvals:
rank_data['ftwt'] = []
dt_data['ftwt'] = []
query = "select huc_12, ftwt%ssv, ftwt%sdt from lcscen_%s" % (
year[2:],
year[2:],
scenario
)
# model_wts.append(float(formvals['ftwt']))
logger.debug(query)
model_length += 1
model_cols.append(
"%s %s - (%s)" % (
col_names['ftwt'],
col_names[scenario],
formvals['ftwt'])
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
# if formvals['mode'] == 'single':
# try:
# hucs_dict[row[0]].append(row[1])
# except KeyError:
# pass
# continue
if float(row[2]) > float(formvals['ftwt']):
above = 1
# rank = int(row[1])
else:
above = 0
# rank = 0
# logger.debug(row)
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['ftwt'].append(float(row[1]))
dt_data['ftwt'].append(float(row[2]))
except KeyError:
pass
if 'hbwt' in formvals:
rank_data['hbwt'] = []
dt_data['hbwt'] = []
query = "select huc_12, hbwt%ssv, hbwt%sdt from lcscen_%s" % (
year[2:],
year[2:],
scenario
)
# model_wts.append(float(formvals['hbwt']))
model_length += 1
model_cols.append(
"%s %s - (%s)" % (
col_names['hbwt'],
col_names[scenario],
formvals['hbwt'])
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
# if formvals['mode'] == 'single':
# try:
# hucs_dict[row[0]].append(row[1])
# except KeyError:
# pass
# continue
# logger.debug(row)
if float(row[2]) > float(formvals['hbwt']):
above = 1
# rank = int(row[1])
else:
above = 0
# rank = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['hbwt'].append(float(row[1]))
dt_data['hbwt'].append(float(row[2]))
except KeyError:
pass
if 'open' in formvals:
rank_data['open'] = []
dt_data['open'] = []
query = "select huc_12, open%ssv, open%sdt from lcscen_%s" % (
year[2:],
year[2:],
scenario
)
# model_wts.append(float(formvals['open']))
model_length += 1
model_cols.append(
"%s %s - (%s)" % (
col_names['open'],
col_names[scenario],
formvals['open'])
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
# if formvals['mode'] == 'single':
# try:
# hucs_dict[row[0]].append(row[1])
# except KeyError:
# pass
# continue
# logger.debug(row)
if float(row[2]) > float(formvals['open']):
above = 1
# rank = int(row[1])
else:
above = 0
# rank = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['open'].append(float(row[1]))
dt_data['open'].append(float(row[2]))
except KeyError:
pass
if 'shrb' in formvals:
rank_data['shrb'] = []
dt_data['shrb'] = []
query = "select huc_12, shrb%ssv, shrb%sdt from lcscen_%s" % (
year[2:],
year[2:],
scenario
)
# model_wts.append(float(formvals['shrb']))
model_length += 1
model_cols.append(
"%s %s - (%s)" % (
col_names['shrb'],
col_names[scenario],
formvals['shrb'])
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
# if formvals['mode'] == 'single':
# try:
# hucs_dict[row[0]].append(row[1])
# except KeyError:
# pass
# continue
# logger.debug(row)
if float(row[2]) > float(formvals['shrb']):
above = 1
# rank = int(row[1])
else:
above = 0
# rank = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['shrb'].append(float(row[1]))
dt_data['shrb'].append(float(row[2]))
except KeyError:
pass
# add urban growth if included
if 'urbangrth' in formvals:
rank_data['urbangrth'] = []
dt_data['urbangrth'] = []
query = "select huc_12, urb%ssv, urb%sdt from urban" % (
year[2:], year[2:]
)
logger.debug(query)
# model_wts.append(float(formvals['urbangrth']))
model_cols.append("Urban Growth - (%s)" % formvals['urbangrth'])
model_length += 1
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
# if formvals['mode'] == 'single':
# try:
# hucs_dict[row[0]].append(row[1])
# except KeyError:
# pass
# continue
if float(row[2]) > float(formvals['urbangrth']):
above = 1
# rank = int(row[1])
else:
above = 0
# rank = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['urbangrth'].append(float(row[1]))
dt_data['urbangrth'].append(float(row[2]))
except KeyError:
pass
# add fire suppression
if 'firesup' in formvals:
rank_data['firesup'] = []
dt_data['firesup'] = []
query = "select huc_12, fsupp%ssv, fsupp%sdt from fsupp" % (
year[2:], year[2:]
)
# logger.debug(query)
# model_wts.append(float(formvals['firesup']))
model_length += 1
model_cols.append("Fire Suppression - (%s)" % formvals['firesup'])
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
# if formvals['mode'] == 'single':
# try:
# hucs_dict[row[0]].append(row[1])
# except KeyError:
# pass
# continue
if float(row[2]) > float(formvals['firesup']):
above = 1
# rank = int(row[1])
else:
above = 0
# rank = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['firesup'].append(float(row[1]))
dt_data['firesup'].append(float(row[2]))
except KeyError:
pass
# add highway
if 'hiway' in formvals:
rank_data['hiway'] = []
dt_data['hiway'] = []
query = "select huc_12, rds%ssv, rds%sdt from DCLRds" % (
year[2:], year[2:]
)
# model_wts.append(float(formvals['hiway']))
model_length += 1
model_cols.append("Highway - (%s)" % formvals['hiway'])
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
# if formvals['mode'] == 'single':
# try:
# hucs_dict[row[0]].append(row[1])
# except KeyError:
# pass
# continue
# logger.debug(row)
# hucs_dict[row[0]].append(int(row[1]))
if float(row[2]) > float(formvals['hiway']):
above = 1
else:
above = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['hiway'].append(float(row[1]))
dt_data['hiway'].append(float(row[2]))
except KeyError:
pass
# add slr up
if 'slr_up' in formvals:
rank_data['slr_up'] = []
dt_data['slr_up'] = []
query = "select huc_12, up%ssv, up%sdt from SLRup" % (
year[2:], year[2:]
)
# model_wts.append(float(formvals['slr_up']))
model_length += 1
model_cols.append(
"Sea Level rise Upland change - (%s)" % formvals['slr_up']
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
if float(row[2]) > float(formvals['slr_up']):
above = 1
else:
above = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['slr_up'].append(float(row[1]))
dt_data['slr_up'].append(float(row[2]))
except KeyError:
pass
# add sea level land cover
if 'slr_lc' in formvals:
rank_data['slr_lc'] = []
dt_data['slr_lc'] = []
query = "select huc_12, lc%ssv, lc%sdt from SLRlc" % (
year[2:], year[2:]
)
# model_wts.append(float(formvals['slr_lc']))
model_length += 1
model_cols.append(
"Sea Level rise landcover change - (%s)" % formvals['slr_lc']
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
if float(row[2]) > float(formvals['slr_lc']):
above = 1
else:
above = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['slr_lc'].append(float(row[1]))
dt_data['slr_lc'].append(float(row[2]))
except KeyError:
pass
# add triassic
if 'triassic' in formvals:
rank_data['triassic'] = []
dt_data['triassic'] = []
query = "select huc_12, triassic_sv, triassic_dt from Triassic"
# model_wts.append(float(formvals['triassic']))
model_length += 1
model_cols.append(
"Triassic Basin - (%s)" % formvals['triassic']
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
if float(row[2]) > float(formvals['triassic']):
above = 1
else:
above = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['triassic'].append(float(row[1]))
dt_data['triassic'].append(float(row[2]))
except KeyError:
pass
# add wind power
if 'wind' in formvals:
rank_data['wind'] = []
dt_data['wind'] = []
query = "select huc_12, WPC_sv, WPC_dt from WPC"
# model_wts.append(float(formvals['wind']))
model_length += 1
model_cols.append(
"Wind Power - (%s)" % formvals['wind']
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
if float(row[2]) > float(formvals['wind']):
above = 1
else:
above = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['wind'].append(float(row[1]))
dt_data['wind'].append(float(row[2]))
except KeyError:
pass
# add manure
if 'manure' in formvals:
rank_data['manure'] = []
dt_data['manure'] = []
query = "select huc_12, manu_sv, manu_dt from Manu"
# model_wts.append(float(formvals['manure']))
model_length += 1
model_cols.append(
"Manure Application - (%s)" % formvals['manure']
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
if float(row[2]) > float(formvals['manure']):
above = 1
else:
above = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['manure'].append(float(row[1]))
dt_data['manure'].append(float(row[2]))
except KeyError:
pass
# add nitrogen
if 'nitrofrt' in formvals:
rank_data['nitrofrt'] = []
dt_data['nitrofrt'] = []
query = "select huc_12, fert_sv, fert_dt from Fert"
# model_wts.append(float(formvals['nitrofrt']))
model_length += 1
model_cols.append(
"Synthetic Nitrogen - (%s)" % formvals['nitrofrt']
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
if float(row[2]) > float(formvals['nitrofrt']):
above = 1
else:
above = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['nitrofrt'].append(float(row[1]))
dt_data['nitrofrt'].append(float(row[2]))
except KeyError:
pass
# add total nitrogen
if 'totnitro' in formvals:
rank_data['totnitro'] = []
dt_data['totnitro'] = []
query = "select huc_12, tdnt_sv, tdnt_dt from TDNT"
# model_wts.append(float(formvals['totnitro']))
model_length += 1
model_cols.append(
"Total Nitrogen - (%s)" % formvals['totnitro']
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
if float(row[2]) > float(formvals['totnitro']):
above = 1
else:
above = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['totnitro'].append(float(row[1]))
dt_data['totnitro'].append(float(row[2]))
except KeyError:
pass
# add total sulphur
if 'totsulf' in formvals:
rank_data['totsulf'] = []
dt_data['totsulf'] = []
query = "select huc_12, tdst_sv, tdst_dt from TDST"
logger.debug(query)
# model_wts.append(float(formvals['totsulf']))
model_length += 1
model_cols.append(
"Total Sulfur - (%s)" % formvals['totsulf']
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
if float(row[2]) > float(formvals['totsulf']):
above = 1
else:
above = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['totsulf'].append(float(row[1]))
dt_data['totsulf'].append(float(row[2]))
except KeyError:
pass
# add forest health
if 'insectdisease' in formvals:
rank_data['insectdisease'] = []
dt_data['insectdisease'] = []
query = "select huc_12, FHlth_sv, FHlth_dt from FHlth"
# model_wts.append(float(formvals['insectdisease']))
model_length += 1
model_cols.append(
"Forest health - (%s)" % formvals['insectdisease']
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
if float(row[2]) > float(formvals['insectdisease']):
above = 1
else:
above = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['insectdisease'].append(float(row[1]))
dt_data['insectdisease'].append(float(row[2]))
except KeyError:
pass
# add number of dams
if 'ndams' in formvals:
rank_data['ndams'] = []
dt_data['ndams'] = []
query = "select huc_12, nid_sv, nid_dt from NID"
logger.debug(query)
# model_wts.append(float(formvals['ndams']))
model_length += 1
model_cols.append(
"# of dams - (%s)" % formvals['ndams']
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
if float(row[2]) > float(formvals['ndams']):
above = 1
else:
above = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['ndams'].append(float(row[1]))
dt_data['ndams'].append(float(row[2]))
except KeyError:
# logger.debug(row[0])
# hucs_dict[row[0]].append(0)
# hucs_dict_sv[row[0]].append(0)
pass
# add impaired biota
if 'impairbiota' in formvals:
rank_data['impairbiota'] = []
dt_data['impairbiota'] = []
query = "select huc_12, BioImpLen_sv, BioImpLen_dt from BioImpLen"
logger.debug(query)
# model_wts.append(float(formvals['impairbiota']))
model_length += 1
model_cols.append(
"Impaired biota - (%s)" % formvals['impairbiota']
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
if float(row[2]) > float(formvals['impairbiota']):
above = 1
else:
above = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['impairbiota'].append(float(row[1]))
dt_data['impairbiota'].append(float(row[2]))
except KeyError:
pass
# add impaired metals
if 'impairmetal' in formvals:
rank_data['impairmetal'] = []
dt_data['impairmetal'] = []
query = "select huc_12, MetImpLen_sv, MetImpLen_dt from MetImpLen"
logger.debug(query)
# model_wts.append(float(formvals['impairmetal']))
model_length += 1
model_cols.append(
"Impaired metal - threshold(%s)" % formvals['impairmetal']
)
with g.db.cursor() as cur:
cur.execute(query)
for row in cur:
if float(row[2]) > float(formvals['impairmetal']):
above = 1
else:
above = 0
try:
hucs_dict[row[0]].append(above)
hucs_dict_sv[row[0]].append(float(row[1]))
rank_data['impairmetal'].append(float(row[1]))
dt_data['impairmetal'].append(float(row[2]))
except KeyError:
pass
##################################################################
# start statistics
# call function to get Composite Threat Count
# also modifies hucs_dict_sv by reference
################################################################
comp_thrt_dict = siteutils.make_composite_threat_count(
hucs_dict, hucs_dict_sv, model_length
)
# logger.debug(comp_thrt_dict)
thrt_counts_summary = comp_thrt_dict['thrt_counts_summary']
threat_summary = [thrt_counts_summary]
threats_summ_dict = siteutils.make_report_threats_summary(
model_cols,
hucs_dict,
rank_data,
dt_data
)
report_rank = threats_summ_dict['report_rank']
num_threats = threats_summ_dict['num_threats']
occurences = threats_summ_dict['occurences']
thrts_included_msg = threats_summ_dict['thrts_included_msg']
####################################################
# other stats
###################################################
other_stats = {}
other_stats['comp_occ'] = int(
sum(occurences) * 100 / num_threats
)
# thrts_included_msg = "%d of %d " % (thrts_present, i + 1)
return {
"res_arr": hucs_dict_sv,
"col_hdrs": model_cols,
"year": year,
# "report": report,
"report_rank": report_rank,
"thrts_included_msg": thrts_included_msg,
"threat_summary": threat_summary,
"other_stats": other_stats
}
def get_indiv_report(id, mymap_str, mode='state'):
logger.debug(mymap_str)
logger.debug(mode)
col_name = ""
legend_titles = {
'frst': 'Forest Habitat (ha)',
'ftwt': 'Wet Forest Habitat (ha)',
'hbwt': 'Wet Herbaceous Habitat (ha)',
'open': 'Open Habitat (ha)',
'shrb': 'Scrub/Shrub Habitat (ha)',
'urban': 'Urban Land Cover (ha)',
'fire': 'Mean Urban Density w/in 5 mile radius',
'trans': 'Mean Length/Area of Major Highways (m/ha)',
"nutrient:manu": "Manure Application (kg/ha/yr)",
"nutrient:fert": "Syn. Nitrogen Fertilizer Application (kg/ha/yr)",
"nutrient:td_n_t": "Total Nitrogen Deposition (kg/ha/yr)",
"nutrient:td_s_t": "Total Sulfur Deposition (kg/ha/yr)",
'frsthlth': "Forest Insect/Disease Risk (ha)",
'energydev': "Triassic basin (ha)",
"water:bioimplen": "Biota Impairments (km*stream density)",
"water:metimplen": "Metal Impariments (km*stream density)",
"water:NID": "Number of Dams (n)",
'wind': "Wind Power Class (mean)",
'slr_lc': "Terrestrial Landcover Change (ha)",
'slr_up': "Undeveloped Upland Change (ha)"
}
year = 10
try:
mymap = mymap_str.split(":")[0]
# set year and param2 for queries where it is not year
year = mymap_str.split(":")[1]
param2 = mymap_str.split(":")[1]
scenario = mymap_str.split(":")[2]