def main():
with open('GSMAlert.txt', 'w') as w:
w.write('')
window,config = rtw.getwindow()
props = q.GetRainProps('rain_props')
PublicAlert = pd.DataFrame({'timestamp': [window.end]*len(props), 'site': props['name'].values, 'source': ['public']*len(props), 'alert': [np.nan]*len(props), 'updateTS': [window.end]*len(props), 'palert_source': [np.nan]*len(props), 'internal_alert': [np.nan]*len(props), 'validity': [np.nan]*len(props), 'sensor_alert': [[]]*len(props), 'rain_alert': [np.nan]*len(props), 'ground_alert': [np.nan]*len(props), 'retriggerTS': [[]]*len(props), 'tech_info': [{}]*len(props)})
PublicAlert = PublicAlert[['timestamp', 'site', 'source', 'alert', 'updateTS', 'palert_source', 'internal_alert', 'validity', 'sensor_alert', 'rain_alert', 'ground_alert', 'retriggerTS', 'tech_info']]
Site_Public_Alert = PublicAlert.groupby('site')
PublicAlert = Site_Public_Alert.apply(SitePublicAlert, window=window)
PublicAlert = PublicAlert[['timestamp', 'site', 'alert', 'internal_alert', 'palert_source', 'validity', 'sensor_alert', 'rain_alert', 'ground_alert', 'retriggerTS', 'tech_info']]
PublicAlert = PublicAlert.rename(columns = {'palert_source': 'source'})
PublicAlert = PublicAlert.sort_values(['alert', 'site'], ascending = [False, True])
PublicAlert.to_csv('PublicAlert.txt', header=True, index=None, sep='\t', mode='w')
PublicAlert['timestamp'] = PublicAlert['timestamp'].apply(lambda x: str(x))
PublicAlert['validity'] = PublicAlert['validity'].apply(lambda x: str(x))
public_json = PublicAlert.to_json(orient="records")
invdf = pd.read_csv('InvalidAlert.txt', sep = ':')
invdf['timestamp'] = invdf['timestamp'].apply(lambda x: str(x))
inv_json = invdf.to_json(orient="records")
df_json = dict({'alerts': public_json, 'invalids': inv_json})
df_json = '[' + str(df_json).replace("\\\'", '').replace('\'', '').replace('alerts:', '"alerts":').replace('invalids:', '"invalids":') + ']'
with open('PublicAlert.json', 'w') as w:
w.write(df_json)
return PublicAlert
def SiteCoord():
RGdf = q.GetRainProps('rain_props')
RGdf = RGdf.loc[RGdf.name != 'msl']
RG = list(RGdf.rain_arq.dropna().apply(lambda x: x[:len(x) - 1]))
RG = '|'.join(RG)
query = "SELECT * FROM senslopedb.site_column where name REGEXP '%s'" % RG
RGCoord = q.GetDBDataFrame(query)
RGCoord['name'] = RGCoord.name.apply(lambda x: x + 'w')
RG = list(RGdf.rain_senslope.dropna().apply(lambda x: x[:len(x) - 1]))
RG = '|'.join(RG)
query = "SELECT * FROM senslopedb.site_column where name REGEXP '%s'" % RG
df = q.GetDBDataFrame(query)
df['name'] = df.name.apply(lambda x: x[0:3] + 'w')
RGCoord = RGCoord.append(df)
RGCoord = RGCoord.drop_duplicates(
['sitio', 'barangay', 'municipality', 'province'])
RGCoord = RGCoord[['name', 'lat', 'lon', 'barangay', 'province']]
RGCoord = RGCoord.rename(columns={
'name': 'dev_id',
'barangay': 'location'
})
RGCoord['type'] = 'SenslopeRG'
RGCoord = RGCoord.sort('dev_id')
return RGCoord
def main():
RGdf = q.GetRainProps('rain_props')[[
'r_id', 'name', 'max_rain_2year', 'rain_senslope', 'rain_arq'
]]
siteRGdf = RGdf.groupby('name')
RG = siteRGdf.apply(NearRGdf)
return RG
def main(site='', Print=True, end=datetime.now()):
output_path = os.path.abspath(
os.path.join(os.path.dirname(__file__), '../..'))
s = cfg.config()
#creates directory if it doesn't exist
if s.io.PrintPlot or s.io.PrintSummaryAlert:
if not os.path.exists(output_path + s.io.RainfallPlotsPath):
os.makedirs(output_path + s.io.RainfallPlotsPath)
#1. setting monitoring window
end, start, offsetstart = get_rt_window(s.io.rt_window_length,
s.io.roll_window_length,
end=end)
tsn = end.strftime("%Y-%m-%d_%H-%M-%S")
#rainprops containing noah id and threshold
rainprops = q.GetRainProps('rain_props')
if site == '':
pass
else:
rainprops = rainprops[rainprops.name == site]
siterainprops = rainprops.groupby('name')
summary = siterainprops.apply(RA.main, end=end, s=s)
summary = summary.reset_index(drop=True).set_index('site')[[
'1D cml', 'half of 2yr max', '3D cml', '2yr max', 'DataSource',
'alert', 'advisory'
]]
summary[['1D cml', 'half of 2yr max', '3D cml', '2yr max']] = np.round(
summary[['1D cml', 'half of 2yr max', '3D cml', '2yr max']], 1)
summary_json = summary.reset_index()
summary_json['ts'] = str(end)
summary_json = summary_json.to_json(orient="records")
if Print == True:
if s.io.PrintSummaryAlert:
summary.to_csv(output_path + s.io.RainfallPlotsPath +
'SummaryOfRainfallAlertGenerationFor' + tsn +
s.io.CSVFormat,
sep=',',
mode='w')
with open(
output_path + s.io.RainfallPlotsPath + 'summary' + tsn +
'.json', 'w') as w:
w.write(summary_json)
if s.io.PrintPlot:
siterainprops.apply(RP.main,
offsetstart=offsetstart,
start=start,
end=end,
tsn=tsn,
s=s,
output_path=output_path)
return summary_json
def main():
end = get_end_ts()
rainprops = q.GetRainProps('rain_props')
siterainprops = rainprops.groupby('name', as_index=False)
popup_notif = siterainprops.apply(notif, end=end)
popup_notif = popup_notif.dropna()
if len(popup_notif) != 0:
text = 'Check the following rainfall data:\n'
text += popup_notif[['site', 'rain_gauge']].to_csv(index=False,
header=False,
sep=':')
text = text.replace(':', ': ')
popupmsg(text)
def main():
while True:
site = raw_input('site name: ').lower()
df = q.GetRainProps('rain_props')
df['name'] = df['name'].apply(lambda x: x.lower())
if site in df.name.values:
break
else:
print 'site name is not in the list'
print '#'*45
print '##', ','.join(df.name.values[0:10]), '##'
print '##', ','.join(df.name.values[10:20]), '##'
print '##', ','.join(df.name.values[20:30]), '##'
print '##', ','.join(df.name.values[30:40]), '##'
print '##', ','.join(df.name.values[40:50]), '##'
print '#'*45
continue
WriteToDB(site)
def main(end='', site=''):
# data timestamp
if end == '':
while True:
try:
end = pd.to_datetime(
raw_input(
'timestamp format YYYY-MM-DD HH:MM (e.g. 2017-01-13 19:30): '
))
break
except:
print 'invalid timestamp format'
pass
rain_props = q.GetRainProps('rain_props')
# rain gauge properties
if site == '':
while True:
site = raw_input('site (e.g. agb): ').lower()
site_rain_props = rain_props[rain_props.name == site]
if len(site_rain_props) != 0:
break
print 'site not in the list'
else:
site_rain_props = rain_props[rain_props.name == site]
# 3-day threshold
twoyrmax = site_rain_props['max_rain_2year'].values[0]
# 1-day threshold
halfmax = twoyrmax / 2.
gauge_ids = [site_rain_props['RG1'].values[0]] + [
site_rain_props['RG2'].values[0]
] + [site_rain_props['RG3'].values[0]]
try:
if site_rain_props['rain_senslope'].values[0] != None:
gauge_ids = [site_rain_props['rain_senslope'].values[0]
] + gauge_ids
except:
pass
try:
if site_rain_props['rain_arq'].values[0] != None:
gauge_ids = [site_rain_props['rain_arq'].values[0]] + gauge_ids
except:
pass
# rain gauge id
while True:
gauge = raw_input('rain gauge id (e.g. agbtaw or 557): ').lower()
try:
gauge = 'rain_noah_' + str(int(gauge))
except:
pass
if gauge in gauge_ids:
break
print '\n\n'
print 'rain gauge id not in the list'
rain_lst = '## ' + ','.join(gauge_ids) + ' ##'
print '#' * len(rain_lst)
print rain_lst
print '#' * len(rain_lst)
print '\n\n'
# rainfall data for the past 3 days
start = end - timedelta(3)
offsetstart = start - timedelta(hours=0.5)
rainfall = A.GetResampledData(gauge, offsetstart, start, end)
rainfall = rainfall[(rainfall.index >= start) & (rainfall.index <= end)]
try:
one, three = A.onethree_val_writer(rainfall)
return end, site, one, halfmax, three, twoyrmax, gauge_ids, gauge
except:
one, three = '', ''
return end, site, one, halfmax, three, twoyrmax, gauge_ids, gauge
################################ MAIN ################################
#1. setting monitoring window
roll_window_numpts, end, start, offsetstart, monwin = set_monitoring_window(
roll_window_length, data_dt, rt_window_length, num_roll_window_ops)
index = pd.date_range(end - timedelta(rt_window_length),
periods=rt_window_length + 1,
freq='D')
columns = ['maxhalf', 'max']
base = pd.DataFrame(index=index, columns=columns)
tsn = end.strftime("%Y-%m-%d_%H-%M-%S")
#rainprops containing noah id and threshold
rainprops = q.GetRainProps()
rainprops['rain_arq'] = rainprops['rain_arq'].fillna(
rainprops['rain_senslope'])
rainprops = rainprops[[
'name', 'rain_arq', 'max_rain_2year', 'rain_noah', 'rain_noah2',
'rain_noah3'
]]
rainprops['rain_arq'] = rainprops['rain_arq'].fillna(rainprops['name'])
rainprops['site'] = rainprops['rain_arq']
rainprops = rainprops[[
'site', 'max_rain_2year', 'rain_noah', 'rain_noah2', 'rain_noah3'
]]
rainprops = rainprops.drop_duplicates(['site'], take_last=True)
rainprops = rainprops.reset_index(drop=True)
#empty dataframe