def get_summary_flood(table_popatrisk=None, iso_alpha3=None):
now = datetime.datetime.now()
current_month = now.strftime("%b").lower()
if (not table_popatrisk) or (not iso_alpha3):
raise Exception("Missing table_popatrisk or iso3 for get_summary_flood.")
num_breakpoints = 5
connection = psycopg2.connect(settings.GEODASH_DB_CONN_STR)
cursor = connection.cursor()
values = data_local_country_hazard_all().get(
cursor=cursor,
iso_alpha3=iso_alpha3,
hazard="flood",
template="sparc2/sql/_hazard_data_all.sql",
table=table_popatrisk)
natural = calc_breaks_natural(values, num_breakpoints)
summary = {
'all': {
"max": {
'at_country_month': None,
'at_admin2_month': None
},
'breakpoints': {
'natural': natural,
'natural_adjusted': None
}
},
"rp": {},
"admin2": {}
}
returnPeriods = [25, 50, 100, 200, 500, 1000]
values_by_rp = {}
for rp in returnPeriods:
q2 = get_template("sparc2/sql/_flood_data_all_at_admin2.sql").render({
'admin2_popatrisk': table_popatrisk,
'iso_alpha3': iso_alpha3,
'rp': rp})
cursor.execute(q2)
values = None
try:
values = cursor.fetchone()[0].split(",")
except:
values = [] # No values since not effected by that disaster, e.g., Afghanistan and cyclones
values_by_rp[str(rp)] = [float(x) for x in values]
natural_adjusted = []
values = values_by_rp["25"]
breakpoints = calc_breaks_natural(values, num_breakpoints-2)
natural_adjusted.extend(breakpoints)
#print "<= RP 25"
#print "Breakpoints", breakpoints
#print "Natural Adjusted", natural_adjusted
#
values = values + values_by_rp["50"] + values_by_rp["100"]
breakpoints = calc_breaks_natural(values, num_breakpoints-1)
if breakpoints[-2] > natural_adjusted[-2]:
natural_adjusted.append(breakpoints[-2])
else:
natural_adjusted = breakpoints[:-1];
#print "<= RP 100"
#print "Breakpoints", breakpoints
#print "Natural Adjusted", natural_adjusted
#
values = values + values_by_rp["200"] + values_by_rp["500"] + values_by_rp["1000"]
breakpoints = calc_breaks_natural(values, num_breakpoints)
if breakpoints[-2] > natural_adjusted[-2]:
natural_adjusted.append(breakpoints[-2])
else:
natural_adjusted = breakpoints[:-1];
#print "<= RP 1000"
#print "Breakpoints", breakpoints
#print "Natural Adjusted", natural_adjusted
#
summary["all"]["max"]["at_admin2_month"] = max(values)
summary["all"]["breakpoints"]["natural_adjusted"] = [0] + natural_adjusted + [max(values)]
for rp in returnPeriods:
# Breakpoints by RP
summary["rp"][str(rp)] = {
'breakpoints': {
'natural': calc_breaks_natural(values_by_rp[str(rp)], num_breakpoints)
}
}
##########
# Flood data by RP x month
q3 = get_template("sparc2/sql/_flood_data_by_rp_month.sql").render({
'admin2_popatrisk': table_popatrisk,
'iso3': iso_alpha3,
'rp': rp})
cursor.execute(q3)
values = None
try:
values = cursor.fetchone()[0].split(",")
except:
values = [] # No values since not effected by that disaster, e.g., Afghanistan and cyclones
summary["rp"][str(rp)]['by_month'] = [float(x) for x in values]
##########
# Flood data by admin2 x RP x month
q4 = get_template("sparc2/sql/_flood_data_by_admin2_rp_month.sql").render({
'admin2_popatrisk': table_popatrisk,
'iso3': iso_alpha3,
'rp': rp})
cursor.execute(q4)
for row in cursor.fetchall():
admin2_code, values = row
keys = [admin2_code, "rp", str(rp), 'by_month']
value = [float(x) for x in values.split(",")]
summary["admin2"] = insertIntoObject(summary["admin2"], keys, value)
summary['header'] = {
'all_breakpoints_natural': len(summary["all"]["breakpoints"]["natural"]),
'all_breakpoints_natural_adjusted': len(summary["all"]["breakpoints"]["natural_adjusted"]),
'admin2': len(summary["admin2"].keys()),
'returnPeriods': returnPeriods
}
return summary
def get_summary_flood(table_popatrisk=None, iso_alpha3=None):
now = datetime.datetime.now()
current_month = now.strftime("%b").lower()
if (not table_popatrisk) or (not iso_alpha3):
raise Exception("Missing table_popatrisk or iso3 for get_summary_flood.")
num_breakpoints = 5
connection = psycopg2.connect(settings.GEODASH_DB_CONN_STR)
cursor = connection.cursor()
values = data_local_country_hazard_all().get(
cursor=cursor,
iso_alpha3=iso_alpha3,
hazard="flood",
template="sparc2/sql/_hazard_data_all.sql",
table=table_popatrisk)
natural = calc_breaks_natural(values, num_breakpoints)
summary = {
'all': {
"max": {
'at_country_month': None,
'at_admin2_month': None
},
'breakpoints': {
'natural': natural,
'natural_adjusted': None
}
},
"rp": {},
"admin2": {}
}
returnPeriods = [25, 50, 100, 200, 500, 1000]
values_by_rp = {}
for rp in returnPeriods:
q2 = get_template("sparc2/sql/_flood_data_all_at_admin2.sql").render({
'admin2_popatrisk': table_popatrisk,
'iso_alpha3': iso_alpha3,
'rp': rp})
cursor.execute(q2)
values = None
try:
values = cursor.fetchone()[0].split(",")
except:
values = [] # No values since not effected by that disaster, e.g., Afghanistan and cyclones
values_by_rp[str(rp)] = [float(x) for x in values]
natural_adjusted = []
values = values_by_rp["25"]
breakpoints = calc_breaks_natural(values, num_breakpoints-2)
natural_adjusted.extend(breakpoints)
#print "<= RP 25"
#print "Breakpoints", breakpoints
#print "Natural Adjusted", natural_adjusted
#
values = values + values_by_rp["50"] + values_by_rp["100"]
breakpoints = calc_breaks_natural(values, num_breakpoints-1)
if breakpoints[-2] > natural_adjusted[-2]:
natural_adjusted.append(breakpoints[-2])
else:
natural_adjusted = breakpoints[:-1];
#print "<= RP 100"
#print "Breakpoints", breakpoints
#print "Natural Adjusted", natural_adjusted
#
values = values + values_by_rp["200"] + values_by_rp["500"] + values_by_rp["1000"]
breakpoints = calc_breaks_natural(values, num_breakpoints)
if breakpoints[-2] > natural_adjusted[-2]:
natural_adjusted.append(breakpoints[-2])
else:
natural_adjusted = breakpoints[:-1];
#print "<= RP 1000"
#print "Breakpoints", breakpoints
#print "Natural Adjusted", natural_adjusted
#
max_value = 0
if len(values) != 0:
max_value = max(values)
summary["all"]["max"]["at_admin2_month"] = max_value
summary["all"]["breakpoints"]["natural_adjusted"] = [0] + natural_adjusted + [max(values)]
for rp in returnPeriods:
# Breakpoints by RP
summary["rp"][str(rp)] = {
'breakpoints': {
'natural': calc_breaks_natural(values_by_rp[str(rp)], num_breakpoints)
}
}
##########
# Flood data by RP x month
q3 = get_template("sparc2/sql/_flood_data_by_rp_month.sql").render({
'admin2_popatrisk': table_popatrisk,
'iso3': iso_alpha3,
'rp': rp})
cursor.execute(q3)
values = None
try:
values = cursor.fetchone()[0].split(",")
except:
values = [] # No values since not effected by that disaster, e.g., Afghanistan and cyclones
summary["rp"][str(rp)]['by_month'] = [float(x) for x in values]
##########
# Flood data by admin2 x RP x month
q4 = get_template("sparc2/sql/_flood_data_by_admin2_rp_month.sql").render({
'admin2_popatrisk': table_popatrisk,
'iso3': iso_alpha3,
'rp': rp})
cursor.execute(q4)
for row in cursor.fetchall():
admin2_code, values = row
keys = [admin2_code, "rp", str(rp), 'by_month']
value = [float(x) for x in values.split(",")]
summary["admin2"] = insertIntoObject(summary["admin2"], keys, value)
summary['header'] = {
'all_breakpoints_natural': len(summary["all"]["breakpoints"]["natural"]),
'all_breakpoints_natural_adjusted': len(summary["all"]["breakpoints"]["natural_adjusted"]),
'admin2': len(summary["admin2"].keys()),
'returnPeriods': returnPeriods
}
return summary
def get_summary_landslide(table_popatrisk=None, iso_alpha3=None):
now = datetime.datetime.now()
current_month = now.strftime("%b").lower()
if (not table_popatrisk) or (not iso_alpha3):
raise Exception("Missing table_popatrisk or iso3 for get_summary_flood.")
summary = {
'all': {
"max": {
'at_country_month': None,
'at_admin2_month': None
},
'breakpoints': {
'natural': None,
'natural_adjusted': None
},
"by_month": None
},
"admin2": {}
}
num_breakpoints = 5
connection = psycopg2.connect(settings.GEODASH_DB_CONN_STR)
cursor = connection.cursor()
values = data_local_country_hazard_all().get(
cursor=cursor,
iso_alpha3=iso_alpha3,
hazard="landslide",
template="sparc2/sql/_hazard_data_all.sql",
table=table_popatrisk)
natural = calc_breaks_natural(values, num_breakpoints)
values_as_integer = [int(x) for x in values]
natural_adjusted = natural
summary["all"]["max"]["at_admin2_month"] = max(values_as_integer)
summary["all"]["breakpoints"]["natural"] = natural
summary["all"]["breakpoints"]["natural_adjusted"] = [0] + natural_adjusted + [max(values_as_integer)]
with GeoDashDatabaseConnection() as geodash_conn:
values = geodash_conn.exec_query_single_aslist(
get_template("sparc2/sql/_landslide_data_by_month.sql").render({
'admin2_popatrisk': 'landslide.admin2_popatrisk',
'iso_alpha3': iso_alpha3}))
print "values by month: ", values
summary["all"]["by_month"] = [int(x) for x in values]
rows = geodash_conn.exec_query_multiple(
get_template("sparc2/sql/_landslide_data_by_admin2_month_asjson.sql").render({
'admin2_popatrisk': 'landslide.admin2_popatrisk',
'iso_alpha3': iso_alpha3}))
values_by_admin2 = {}
for row in rows:
admin2_code, data = row
data.pop(u"admin2_code")
summary["admin2"][str(admin2_code)] = {}
summary["admin2"][str(admin2_code)]["by_month"] = valuesByMonthToList(data)
return summary
