def get(station):
cursor.execute(
"""
SELECT valid, sknt, tmpf, dwpf from alldata where station = %s
and tmpf is not null and dwpf is not null
and valid > '1971-01-01' ORDER by valid ASC
""",
(station,),
)
hits = {}
running = False
startr = None
for row in cursor:
relh = met.relh(temperature(row[2], "F"), temperature(row[3], "F")).value("%")
if relh > 25 or row[1] < (25.0 / 1.15):
if running:
delta = (row[0] - startr).seconds
if delta >= 60 * 60 * 1:
# print station, delta, row
hits[row[0].strftime("%Y%m%d")] = 1
running = False
else:
running = True
startr = row[0]
return len(hits.keys())
def test_relh(self):
""" Simple check of bad units in temperature """
tmp = datatypes.temperature(24, 'C')
dwp = datatypes.temperature(24, 'C')
relh = meteorology.relh(tmp, dwp)
self.assertEquals(100.0, relh.value("%"))
tmp = datatypes.temperature(32, 'C')
dwp = datatypes.temperature(10, 'C')
relh = meteorology.relh(tmp, dwp)
self.assertAlmostEquals(25.79, relh.value("%"), 2)
tmp = datatypes.temperature(32, 'C')
dwp = datatypes.temperature(15, 'C')
relh = meteorology.relh(tmp, dwp)
self.assertAlmostEquals(35.81, relh.value("%"), 2)
tmp = datatypes.temperature(5, 'C')
dwp = datatypes.temperature(4, 'C')
relh = meteorology.relh(tmp, dwp)
self.assertAlmostEquals(93.24, relh.value("%"), 2)
def test_relh():
""" Simple check of bad units in temperature """
tmp = datatypes.temperature(24, 'C')
dwp = datatypes.temperature(24, 'C')
relh = meteorology.relh(tmp, dwp)
assert relh.value("%") == 100.
tmp = datatypes.temperature(32, 'C')
dwp = datatypes.temperature(10, 'C')
relh = meteorology.relh(tmp, dwp)
assert abs(25.79 - relh.value("%")) < 0.01
tmp = datatypes.temperature(32, 'C')
dwp = datatypes.temperature(15, 'C')
relh = meteorology.relh(tmp, dwp)
assert abs(35.81 - relh.value("%")) < 0.01
tmp = datatypes.temperature(5, 'C')
dwp = datatypes.temperature(4, 'C')
relh = meteorology.relh(tmp, dwp)
assert abs(93.24 - relh.value("%")) < 0.01
def test_relh():
""" Simple check of bad units in temperature """
tmp = datatypes.temperature(24, "C")
dwp = datatypes.temperature(24, "C")
relh = meteorology.relh(tmp, dwp)
assert relh.value("%") == 100.0
tmp = datatypes.temperature(32, "C")
dwp = datatypes.temperature(10, "C")
relh = meteorology.relh(tmp, dwp)
assert abs(25.79 - relh.value("%")) < 0.01
tmp = datatypes.temperature(32, "C")
dwp = datatypes.temperature(15, "C")
relh = meteorology.relh(tmp, dwp)
assert abs(35.81 - relh.value("%")) < 0.01
tmp = datatypes.temperature(5, "C")
dwp = datatypes.temperature(4, "C")
relh = meteorology.relh(tmp, dwp)
assert abs(93.24 - relh.value("%")) < 0.01
def test_relh(self):
""" Simple check of bad units in temperature """
tmp = datatypes.temperature(24, 'C')
dwp = datatypes.temperature(24, 'C')
relh = meteorology.relh(tmp, dwp)
self.assertEquals(100.0, relh.value("%"))
tmp = datatypes.temperature(32, 'C')
dwp = datatypes.temperature(10, 'C')
relh = meteorology.relh(tmp, dwp)
self.assertAlmostEquals(25.79, relh.value("%"), 2)
tmp = datatypes.temperature(32, 'C')
dwp = datatypes.temperature(15, 'C')
relh = meteorology.relh(tmp, dwp)
self.assertAlmostEquals(35.81, relh.value("%"), 2)
tmp = datatypes.temperature(5, 'C')
dwp = datatypes.temperature(4, 'C')
relh = meteorology.relh(tmp, dwp)
self.assertAlmostEquals(93.24, relh.value("%"), 2)
def computeOthers(d):
r = {}
# Need something to compute other values needed for output
for sid in d.keys():
ob = d[sid]
ob["ticks"] = calendar.timegm(ob['utc_valid'].timetuple())
if ob['sknt'] is not None:
ob["sped"] = ob["sknt"] * 1.17
if ob.get('tmpf') is not None and ob.get('dwpf') is not None:
tmpf = temperature(ob['tmpf'], 'F')
dwpf = temperature(ob['dwpf'], 'F')
ob["relh"] = meteorology.relh(tmpf, dwpf).value('%')
else:
ob['relh'] = None
if ob['relh'] == 'M':
ob['relh'] = None
if (ob.get('tmpf') is not None and ob.get('dwpf') is not None and
ob.get('sped') is not None):
ob['feel'] = meteorology.mcalc_feelslike(
masked_array([ob['tmpf'], ], units('degF'), mask=[False, ]),
masked_array([ob['dwpf'], ], units('degF'), mask=[False, ]),
masked_array([ob['sped'], ], units('mile per hour'),
mask=[False, ])
).to(units('degF')).magnitude[0]
else:
ob['feel'] = None
if ob['feel'] == 'M':
ob['feel'] = None
ob["altiTend"] = 'S'
ob["drctTxt"] = util.drct2text(ob["drct"])
if ob["max_drct"] is None:
ob["max_drct"] = 0
ob["max_drctTxt"] = util.drct2text(ob["max_drct"])
ob["20gu"] = 0
if ob['gust'] is not None:
ob["gmph"] = ob["gust"] * 1.17
if ob['max_gust'] is not None:
ob["max_sped"] = ob["max_gust"] * 1.17
else:
ob['max_sped'] = 0
ob['pday'] = 0 if ob['pday'] is None else ob['pday']
ob['pmonth'] = 0 if ob['pmonth'] is None else ob['pmonth']
ob["gtim"] = "0000"
ob["gtim2"] = "12:00 AM"
if ob["max_gust_ts"] is not None and ob["max_gust_ts"] != "null":
ob["gtim"] = ob["max_gust_ts"].strftime("%H%M")
ob["gtim2"] = ob["max_gust_ts"].strftime("%-I:%M %p")
r[sid] = ob
return r
def computeOthers(d):
r = {}
# Need something to compute other values needed for output
for sid in d.keys():
ob = d[sid]
ob["ticks"] = calendar.timegm(ob['utc_valid'].timetuple())
if ob['sknt'] is not None:
ob["sped"] = ob["sknt"] * 1.17
if ob.get('tmpf') is not None and ob.get('dwpf') is not None:
tmpf = temperature(ob['tmpf'], 'F')
dwpf = temperature(ob['dwpf'], 'F')
ob["relh"] = meteorology.relh(tmpf, dwpf).value('%')
else:
ob['relh'] = None
if ob['relh'] == 'M':
ob['relh'] = None
if (ob.get('tmpf') is not None and ob.get('dwpf') is not None and
ob.get('sped') is not None):
tmpf = temperature(ob['tmpf'], 'F')
dwpf = temperature(ob['dwpf'], 'F')
sknt = speed(ob['sped'], 'MPH')
ob["feel"] = meteorology.feelslike(tmpf, dwpf, sknt).value("F")
else:
ob['feel'] = None
if ob['feel'] == 'M':
ob['feel'] = None
ob["altiTend"] = 'S'
ob["drctTxt"] = util.drct2text(ob["drct"])
if ob["max_drct"] is None:
ob["max_drct"] = 0
ob["max_drctTxt"] = util.drct2text(ob["max_drct"])
ob["20gu"] = 0
if ob['gust'] is not None:
ob["gmph"] = ob["gust"] * 1.17
if ob['max_gust'] is not None:
ob["max_sped"] = ob["max_gust"] * 1.17
else:
ob['max_sped'] = 0
ob['pday'] = 0 if ob['pday'] is None else ob['pday']
ob['pmonth'] = 0 if ob['pmonth'] is None else ob['pmonth']
ob["gtim"] = "0000"
ob["gtim2"] = "12:00 AM"
if ob["max_gust_ts"] is not None and ob["max_gust_ts"] != "null":
ob["gtim"] = ob["max_gust_ts"].strftime("%H%M")
ob["gtim2"] = ob["max_gust_ts"].strftime("%-I:%M %p")
r[sid] = ob
return r
def grid_relh(nc, ts, rs):
lats = []
lons = []
vals = []
for i in range(len(rs)):
if rs[i]['max_tmpf'] is not None and rs[i]['max_dwpf'] is not None:
lats.append(nt.sts[rs[i]['station']]['lat'])
lons.append(nt.sts[rs[i]['station']]['lon'])
vals.append((meteorology.relh(temperature(rs[i]['max_tmpf'], 'F'),
temperature(rs[i]['max_dwpf'], 'F'))
).value('%'))
if len(vals) < 4:
print "No RELH data at all for time: %s" % (ts,)
return
grid = griddata((lons, lats), np.array(vals), (XI, YI), method='nearest')
offset = int((ts - BASE).total_seconds() / 3600.)
if grid is not None:
nc.variables['relh'][offset, :, :] = np.where(grid < 12., 12., grid)
else:
print "RELH gridding failed, len vals %s" % (len(vals),)
def main():
""" Go main Go """
check_load()
form = cgi.FieldStorage()
try:
tzinfo = pytz.timezone(form.getfirst("tz", "Etc/UTC"))
except pytz.exceptions.UnknownTimeZoneError as exp:
sys.stdout.write("Content-type: text/plain\n\n")
sys.stdout.write("Invalid Timezone (tz) provided")
sys.stderr.write("asos.py invalid tz: %s\n" % (exp, ))
sys.exit()
pgconn = psycopg2.connect(database='asos', host='iemdb', user='******')
acursor = pgconn.cursor('mystream',
cursor_factory=psycopg2.extras.DictCursor)
# Save direct to disk or view in browser
direct = True if form.getfirst('direct', 'no') == 'yes' else False
report_type = form.getlist('report_type')
stations = get_stations(form)
if direct:
sys.stdout.write('Content-type: application/octet-stream\n')
fn = "%s.txt" % (stations[0],)
if len(stations) > 1:
fn = "asos.txt"
sys.stdout.write('Content-Disposition: attachment; filename=%s\n\n' % (
fn,))
else:
sys.stdout.write("Content-type: text/plain \n\n")
dbstations = stations
if len(dbstations) == 1:
dbstations.append('XYZXYZ')
dataVars = form.getlist("data")
sts, ets = get_time_bounds(form, tzinfo)
delim = form.getfirst("format", "onlycomma")
if "all" in dataVars:
queryCols = ("tmpf, dwpf, relh, drct, sknt, p01i, alti, mslp, "
"vsby, gust, skyc1, skyc2, skyc3, skyc4, skyl1, "
"skyl2, skyl3, skyl4, presentwx, metar")
outCols = ['tmpf', 'dwpf', 'relh', 'drct', 'sknt', 'p01i', 'alti',
'mslp', 'vsby', 'gust', 'skyc1', 'skyc2', 'skyc3',
'skyc4', 'skyl1', 'skyl2', 'skyl3', 'skyl4',
'presentwx', 'metar']
else:
for _colname in ['station', 'valid']:
if _colname in dataVars:
dataVars.remove(_colname)
dataVars = tuple(dataVars)
outCols = dataVars
dataVars = str(dataVars)[1:-2]
queryCols = re.sub("'", " ", dataVars)
if delim in ["tdf", "onlytdf"]:
rD = "\t"
queryCols = re.sub(",", "\t", queryCols)
else:
rD = ","
gtxt = {}
gisextra = False
if form.getfirst("latlon", "no") == "yes":
gisextra = True
MESOSITE = psycopg2.connect(database='mesosite', host='iemdb',
user='******')
mcursor = MESOSITE.cursor()
mcursor.execute("""SELECT id, ST_x(geom) as lon, ST_y(geom) as lat
from stations WHERE id in %s
and (network ~* 'AWOS' or network ~* 'ASOS')
""", (tuple(dbstations),))
for row in mcursor:
gtxt[row[0]] = "%.4f%s%.4f%s" % (row[1], rD, row[2], rD)
rlimiter = ""
if len(report_type) == 1:
rlimiter = " and report_type = %s" % (int(report_type[0]),)
elif len(report_type) > 1:
rlimiter = (" and report_type in %s"
) % (tuple([int(a) for a in report_type]), )
acursor.execute("""SELECT * from alldata
WHERE valid >= %s and valid < %s and station in %s """+rlimiter+"""
ORDER by valid ASC""", (sts, ets, tuple(dbstations)))
if delim not in ['onlytdf', 'onlycomma']:
sys.stdout.write("#DEBUG: Format Typ -> %s\n" % (delim,))
sys.stdout.write("#DEBUG: Time Period -> %s %s\n" % (sts, ets))
sys.stdout.write("#DEBUG: Time Zone -> %s\n" % (tzinfo,))
sys.stdout.write(("#DEBUG: Data Contact -> daryl herzmann "
"[email protected] 515-294-5978\n"))
sys.stdout.write("#DEBUG: Entries Found -> %s\n" % (acursor.rowcount,))
sys.stdout.write("station"+rD+"valid"+rD)
if gisextra:
sys.stdout.write("lon"+rD+"lat"+rD)
sys.stdout.write(queryCols+"\n")
for row in acursor:
sys.stdout.write(row["station"] + rD)
sys.stdout.write(
(row["valid"].astimezone(tzinfo)).strftime("%Y-%m-%d %H:%M") + rD)
if gisextra:
sys.stdout.write(gtxt.get(row['station'], "M%sM%s" % (rD, rD)))
r = []
for data1 in outCols:
if data1 == 'relh':
if row['tmpf'] is not None and row['dwpf'] is not None:
tmpf = temperature(row['tmpf'], 'F')
dwpf = temperature(row['dwpf'], 'F')
val = meteorology.relh(tmpf, dwpf)
r.append("%.2f" % (val.value("%"),))
else:
r.append("M")
elif data1 == 'sped':
if row['sknt'] >= 0:
r.append("%.1f" % (speed(row['sknt'],
'KT').value('MPH'), ))
else:
r.append("M")
elif data1 == 'gust_mph':
if row['gust'] >= 0:
r.append("%.1f" % (speed(row['gust'],
'KT').value('MPH'), ))
else:
r.append("M")
elif data1 == 'p01m':
if row['p01i'] >= 0:
r.append("%.2f" % (row['p01i'] * 25.4, ))
else:
r.append("M")
elif data1 == 'tmpc':
if row['tmpf'] is not None:
val = temperature(row['tmpf'], 'F').value('C')
r.append("%.2f" % (val, ))
else:
r.append("M")
elif data1 == 'dwpc':
if row['dwpf'] is not None:
val = temperature(row['dwpf'], 'F').value('C')
r.append("%.2f" % (val, ))
else:
r.append("M")
elif data1 == 'presentwx':
if row['presentwx'] is not None:
r.append("%s" % (row['presentwx'].replace(",", " "), ))
else:
r.append("M")
elif data1 in ["metar", "skyc1", "skyc2", "skyc3", "skyc4"]:
if row[data1] is None:
r.append("M")
else:
r.append("%s" % (row[data1].replace(",", " "), ))
elif (row.get(data1) is None or row[data1] <= -99.0 or
row[data1] == "M"):
r.append("M")
else:
r.append("%2.2f" % (row[data1], ))
sys.stdout.write("%s\n" % (rD.join(r),))
from pyiem import meteorology
dbconn = psycopg2.connect(database='asos', host='iemdb', user='******')
cursor = dbconn.cursor()
otmpf = []
odwpf = []
cursor.execute("""SELECT tmpf, dwpf from alldata where station = 'DSM' and
tmpf >= 80 and dwpf > 0 and tmpf < 110""")
for row in cursor:
otmpf.append( row[0] )
odwpf.append( row[1] )
otmpf = dt.temperature(numpy.array(otmpf), 'F')
odwpf = dt.temperature(numpy.array(odwpf), 'F')
orelh = meteorology.relh(otmpf, odwpf)
tmpf = dt.temperature(numpy.arange(80,110), 'F')
dwpf = dt.temperature(numpy.arange(40,80), 'F')
(t, d) = numpy.meshgrid(tmpf.value("F"), dwpf.value("F"))
hindex = meteorology.heatindex(dt.temperature(t,'F'), dt.temperature(d, 'F'))
counts = numpy.zeros( numpy.shape(hindex.value("F")), 'f')
for otmp, odwp in zip(otmpf.value("F"), odwpf.value("F")):
if odwp < 40 or odwp >= 79.5:
continue
counts[(int(round(odwp)) - 40), int(round(otmp)) - 80 ] += 1.0
ttot = numpy.sum(counts,0)
print ttot
for sid in indices:
idx = indices[sid]['idx']
name = nc.variables["stationName"][idx].tostring().replace('\x00','')
latitude = nc.variables['latitude'][idx]
longitude = nc.variables['longitude'][idx]
tmpf = s(nc.variables['temperature'][idx])
dwpf = s(nc.variables['dewpoint'][idx])
qcd = nc.variables['temperatureQCD'][idx][0]
if qcd < -10 or qcd > 10:
tmpf = "M"
dwpf = "M"
heat = "M"
if tmpf != "M" and dwpf != "M":
t = temperature(nc.variables['temperature'][idx], 'K')
d = temperature(nc.variables['dewpoint'][idx], 'K')
relh = meteorology.relh(t, d).value("%")
heat = "%5.1f" % (meteorology.heatindex(t, d).value("F"),)
drct = s2( nc.variables['windDir'][idx])
smps = s2( nc.variables['windSpeed'][idx])
sped = "M"
if smps != "M":
sped = "%5.1f" % (nc.variables['windSpeed'][idx] * 2.23694,)
wcht = "M"
if tmpf != "M" and sped != "M":
t = temperature(nc.variables['temperature'][idx], 'K')
sped = speed( nc.variables['windSpeed'][idx], 'MPS')
wcht = "%5.1f" % (meteorology.windchill(t, sped).value("F"),)
ts = indices[sid]['ts']
from pyiem.datatypes import temperature, speed, distance
from pyiem.meteorology import relh
pgconn = psycopg2.connect(database='asos', host='iemdb', user='******')
# air temperature, RH, Radiation, WS, and precipitation
df = read_sql("""SELECT valid, tmpf, dwpf, sknt, p01i,
extract(month from valid) as month,
extract(hour from valid + '10 minutes'::interval) as hour,
extract(day from valid + '10 minutes'::interval) as day from alldata
WHERE station = 'DSM' and extract(month from valid) in (10, 11)
and extract(minute from valid) = 54
and valid > '1986-01-01'
""", pgconn, index_col=None)
df['relh'] = relh(temperature(df['tmpf'], 'F'),
temperature(df['dwpf'], 'F')).value('%')
gdf = df.groupby(by=['month', 'day', 'hour']).mean()
pgconn = psycopg2.connect(database='isuag', host='iemdb', user='******')
# air temperature, RH, Radiation, WS, and precipitation
df2 = read_sql("""SELECT
extract(month from valid) as month,
extract(hour from valid + '10 minutes'::interval) as hour,
extract(day from valid + '10 minutes'::interval) as day,
c800 from hourly
WHERE station = 'A130209' and extract(month from valid) in (10, 11)
""", pgconn, index_col=None)
gdf2 = df2.groupby(by=['month', 'day', 'hour']).mean()
def plotter(fdict):
""" Go """
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
pgconn = psycopg2.connect(database='asos', host='iemdb', user='******')
ctx = get_autoplot_context(fdict, get_description())
station = ctx['zstation']
network = ctx['network']
nt = NetworkTable(network)
year = ctx['year']
varname = ctx['var']
_ = PDICT[varname]
df = read_sql("""
SELECT extract(year from valid) as year,
extract(doy from valid) as doy, tmpf, dwpf from alldata
where station = %s and dwpf > -50 and dwpf < 90 and
tmpf > -50 and tmpf < 120 and valid > '1950-01-01'
and report_type = 2
""", pgconn, params=(station,), index_col=None)
df['relh'] = relh(temperature(df['tmpf'].values, 'F'),
temperature(df['dwpf'].values, 'F')).value('%')
df['tmpc'] = temperature(df['tmpf'].values, 'F').value('C')
df['svp'] = 0.611 * np.exp(17.502 * df['tmpc'].values /
(240.97 + df['tmpc'].values))
df['vpd'] = (1. - (df['relh'] / 100.)) * df['svp']
df['mixing_ratio'] = mixing_ratio(
temperature(df['dwpf'].values, 'F')).value('KG/KG')
dailymeans = df[['year', 'doy', varname]].groupby(['year', 'doy']).mean()
dailymeans = dailymeans.reset_index()
df2 = dailymeans[['doy', varname]].groupby('doy').describe()
dyear = df[df['year'] == year]
df3 = dyear[['doy', varname]].groupby('doy').describe()
df3[(varname, 'diff')] = df3[(varname, 'mean')] - df2[(varname, 'mean')]
(fig, ax) = plt.subplots(2, 1, figsize=(8, 6))
multiplier = 1000. if varname == 'mixing_ratio' else 10.
ax[0].fill_between(df2[(varname, 'min')].index.values,
df2[(varname, 'min')].values * multiplier,
df2[(varname, 'max')].values * multiplier,
color='gray')
ax[0].plot(df2[(varname, 'mean')].index.values,
df2[(varname, 'mean')].values * multiplier,
label="Climatology")
ax[0].plot(df3[(varname, 'mean')].index.values,
df3[(varname, 'mean')].values * multiplier,
color='r', label="%s" % (year, ))
ax[0].set_title(("%s [%s]\nDaily Mean Surface %s"
) % (station, nt.sts[station]['name'],
PDICT[varname]))
lbl = ("Mixing Ratio ($g/kg$)" if varname == 'mixing_ratio'
else PDICT[varname])
ax[0].set_ylabel(lbl)
ax[0].set_xlim(0, 366)
ax[0].set_ylim(bottom=0)
ax[0].set_xticks((1, 32, 60, 91, 121, 152, 182, 213, 244, 274, 305, 335,
365))
ax[0].set_xticklabels(calendar.month_abbr[1:])
ax[0].grid(True)
ax[0].legend(loc=2, fontsize=10)
cabove = 'b' if varname == 'mixing_ratio' else 'r'
cbelow = 'r' if cabove == 'b' else 'b'
rects = ax[1].bar(df3[(varname, 'diff')].index.values,
df3[(varname, 'diff')].values * multiplier,
facecolor=cabove, edgecolor=cabove)
for rect in rects:
if rect.get_height() < 0.:
rect.set_facecolor(cbelow)
rect.set_edgecolor(cbelow)
units = '$g/kg$' if varname == 'mixing_ratio' else 'hPa'
ax[1].set_ylabel("%.0f Departure (%s)" % (year, units))
ax[1].set_xlim(0, 366)
ax[1].set_xticks((1, 32, 60, 91, 121, 152, 182, 213, 244, 274, 305, 335,
365))
ax[1].set_xticklabels(calendar.month_abbr[1:])
ax[1].grid(True)
return fig, df3
def main(argv):
"""Go Main Go"""
network = argv[1]
wxcfn = argv[2]
utc = datetime.datetime.utcnow()
utc = utc.replace(tzinfo=pytz.timezone("UTC"))
out = open(wxcfn, 'w')
out.write("""Weather Central 001d0300 Surface Data TimeStamp=%s
12
5 Station
25 Station Name
8 Lat
10 Lon
2 Hour
2 Minute
5 Air Temperature F
5 Dew Point F
5 Wind Direction deg
5 Wind Speed mph
5 Heat Index F
5 Wind Chill F
""" % (utc.strftime("%Y.%m.%d.%H%M"),))
fn = None
for i in range(4):
now = utc - datetime.timedelta(hours=i)
testfn = now.strftime("/mesonet/data/madis/mesonet1/%Y%m%d_%H00.nc")
if os.path.isfile(testfn):
fn = testfn
break
if fn is None:
sys.exit()
indices = {}
BOGUS = datetime.datetime(2000, 1, 1)
BOGUS = BOGUS.replace(tzinfo=pytz.utc)
nc = netCDF4.Dataset(fn, 'r')
for i, provider in enumerate(nc.variables["dataProvider"][:]):
if provider.tostring().replace('\x00', '') != network:
continue
sid = nc.variables["stationId"][i].tostring().replace('\x00', '')
# We have an ob!
ticks = nc.variables["observationTime"][i]
ts = datetime.datetime(1970, 1, 1) + datetime.timedelta(seconds=ticks)
ts = ts.replace(tzinfo=pytz.timezone("UTC"))
if ts > indices.get(sid, {'ts': BOGUS})['ts']:
indices[sid] = {'ts': ts, 'idx': i}
for sid in indices:
idx = indices[sid]['idx']
name = nc.variables["stationName"][idx].tostring().replace('\x00', '')
latitude = nc.variables['latitude'][idx]
longitude = nc.variables['longitude'][idx]
tmpf = s(nc.variables['temperature'][idx])
dwpf = s(nc.variables['dewpoint'][idx])
qcd = nc.variables['temperatureQCD'][idx][0]
if qcd < -10 or qcd > 10:
tmpf = "M"
dwpf = "M"
heat = "M"
if tmpf != "M" and dwpf != "M":
t = temperature(nc.variables['temperature'][idx], 'K')
d = temperature(nc.variables['dewpoint'][idx], 'K')
relh = meteorology.relh(t, d).value("%")
heat = "%5.1f" % (meteorology.heatindex(t, d).value("F"),)
drct = s2(nc.variables['windDir'][idx])
smps = s2(nc.variables['windSpeed'][idx])
sped = "M"
if smps != "M":
sped = "%5.1f" % (nc.variables['windSpeed'][idx] * 2.23694,)
wcht = "M"
if tmpf != "M" and sped != "M":
t = temperature(nc.variables['temperature'][idx], 'K')
sped = speed(nc.variables['windSpeed'][idx], 'MPS')
wcht = "%5.1f" % (meteorology.windchill(t, sped).value("F"), )
ts = indices[sid]['ts']
out.write(("%5.5s %25.25s %8.4f %10.4f "
"%02i %02i %5s %5s %5s %5s %5s %5s\n"
) % (sid, name, latitude, longitude, ts.hour,
ts.minute, tmpf, dwpf, drct, sped, heat, wcht))
nc.close()
out.close()
pqstr = "data c 000000000000 wxc/wxc_%s.txt bogus txt" % (network.lower(),)
subprocess.call("/home/ldm/bin/pqinsert -p '%s' %s" % (
pqstr, wxcfn), shell=True)
os.remove(wxcfn)
def plotter(fdict):
""" Go """
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
pgconn = psycopg2.connect(database='asos', host='iemdb', user='******')
cursor = pgconn.cursor(cursor_factory=psycopg2.extras.DictCursor)
ctx = get_autoplot_context(fdict, get_description())
station = ctx['zstation']
network = ctx['network']
month = ctx['month']
nt = NetworkTable(network)
if month == 'all':
months = range(1, 13)
elif month == 'fall':
months = [9, 10, 11]
elif month == 'winter':
months = [12, 1, 2]
elif month == 'spring':
months = [3, 4, 5]
elif month == 'summer':
months = [6, 7, 8]
else:
ts = datetime.datetime.strptime("2000-"+month+"-01", '%Y-%b-%d')
# make sure it is length two for the trick below in SQL
months = [ts.month, 999]
cursor.execute("""
SELECT tmpf::int as t, dwpf from alldata where station = %s
and tmpf is not null and dwpf is not null and dwpf <= tmpf
and tmpf >= 0 and tmpf <= 140
and extract(month from valid) in %s
""", (station, tuple(months)))
sums = np.zeros((140,), 'f')
counts = np.zeros((140,), 'f')
for row in cursor:
r = mixing_ratio(temperature(row[1], 'F')).value('KG/KG')
sums[row[0]] += r
counts[row[0]] += 1
rows = []
for i in range(140):
if counts[i] < 3:
continue
r = sums[i] / float(counts[i])
d = dewpoint_from_pq(pressure(1000, 'MB'),
mixingratio(r, 'KG/KG')
).value('F')
rh = relh(temperature(i, 'F'), temperature(d, 'F')).value('%')
rows.append(dict(tmpf=i, dwpf=d, rh=rh))
df = pd.DataFrame(rows)
tmpf = df['tmpf']
dwpf = df['dwpf']
rh = df['rh']
(fig, ax) = plt.subplots(1, 1, figsize=(8, 6))
ax.bar(tmpf-0.5, dwpf, ec='green', fc='green', width=1)
ax.grid(True, zorder=11)
ax.set_title(("%s [%s]\nAverage Dew Point by Air Temperature (month=%s) "
"(%s-%s)\n"
"(must have 3+ hourly observations at the given temperature)"
) % (nt.sts[station]['name'], station, month.upper(),
nt.sts[station]['archive_begin'].year,
datetime.datetime.now().year), size=10)
ax.plot([0, 140], [0, 140], color='b')
ax.set_ylabel("Dew Point [F]")
y2 = ax.twinx()
y2.plot(tmpf, rh, color='k')
y2.set_ylabel("Relative Humidity [%] (black line)")
y2.set_yticks([0, 5, 10, 25, 50, 75, 90, 95, 100])
y2.set_ylim(0, 100)
ax.set_ylim(0, max(tmpf)+2)
ax.set_xlim(0, max(tmpf)+2)
ax.set_xlabel("Air Temperature $^\circ$F")
return fig, df
def do(ts):
"""Process this date timestamp"""
asos = psycopg2.connect(database='asos', host='iemdb', user='******')
cursor = asos.cursor()
iemaccess = psycopg2.connect(database='iem', host='iemdb')
icursor = iemaccess.cursor()
cursor.execute("""
select station, network, iemid, drct, sknt, valid at time zone tzname,
tmpf, dwpf from
alldata d JOIN stations t on (t.id = d.station)
where (network ~* 'ASOS' or network = 'AWOS')
and valid between %s and %s and t.tzname is not null
ORDER by valid ASC
""", (ts - datetime.timedelta(days=2), ts + datetime.timedelta(days=2)))
wdata = dict()
rhdata = dict()
for row in cursor:
if row[5].strftime("%m%d") != ts.strftime("%m%d"):
continue
station = "%s|%s|%s" % (row[0], row[1], row[2])
if row[6] is not None and row[7] is not None:
tmpf = temperature(row[6], 'F')
dwpf = temperature(row[7], 'F')
rh = meteorology.relh(tmpf, dwpf)
if station not in rhdata:
rhdata[station] = dict(valid=[], rh=[])
rhdata[station]['valid'].append(row[5])
rhdata[station]['rh'].append(rh.value('%'))
if row[4] is not None and row[3] is not None:
sknt = speed(row[4], 'KT')
drct = direction(row[3], 'DEG')
(u, v) = meteorology.uv(sknt, drct)
if station not in wdata:
wdata[station] = {'valid': [], 'sknt': [], 'u': [], 'v': []}
wdata[station]['valid'].append(row[5])
wdata[station]['sknt'].append(row[4])
wdata[station]['u'].append(u.value('KT'))
wdata[station]['v'].append(v.value('KT'))
table = "summary_%s" % (ts.year,)
for stid in rhdata:
# Not enough data
if len(rhdata[stid]['valid']) < 6:
continue
station, network, iemid = stid.split("|")
now = datetime.datetime(ts.year, ts.month, ts.day)
runningrh = 0
runningtime = 0
for i, valid in enumerate(rhdata[stid]['valid']):
delta = (valid - now).seconds
runningtime += delta
runningrh += (delta * rhdata[stid]['rh'][i])
now = valid
if runningtime == 0:
print(("compute_daily %s has time domain %s %s"
) % (stid, rhdata[stid]['valid'][0],
rhdata[stid]['valid'][-1]))
continue
avg_rh = clean_rh(runningrh / runningtime)
min_rh = clean_rh(min(rhdata[stid]['rh']))
max_rh = clean_rh(max(rhdata[stid]['rh']))
def do_update():
icursor.execute("""UPDATE """ + table + """
SET avg_rh = %s, min_rh = %s, max_rh = %s WHERE
iemid = %s and day = %s""", (avg_rh, min_rh, max_rh, iemid, ts))
do_update()
if icursor.rowcount == 0:
print(('compute_daily Adding %s for %s %s %s'
) % (table, station, network, ts))
icursor.execute("""INSERT into """ + table + """
(iemid, day) values (%s, %s)""", (iemid, ts))
do_update()
for stid in wdata:
# Not enough data
if len(wdata[stid]['valid']) < 6:
continue
station, network, iemid = stid.split("|")
now = datetime.datetime(ts.year, ts.month, ts.day)
runningsknt = 0
runningtime = 0
runningu = 0
runningv = 0
for i, valid in enumerate(wdata[stid]['valid']):
delta = (valid - now).seconds
runningtime += delta
runningsknt += (delta * wdata[stid]['sknt'][i])
runningu += (delta * wdata[stid]['u'][i])
runningv += (delta * wdata[stid]['v'][i])
now = valid
if runningtime == 0:
print(("compute_daily %s has time domain %s %s"
) % (stid, wdata[stid]['valid'][0],
wdata[stid]['valid'][-1]))
continue
sknt = runningsknt / runningtime
u = speed(runningu / runningtime, 'KT')
v = speed(runningv / runningtime, 'KT')
drct = meteorology.drct(u, v).value("DEG")
def do_update():
icursor.execute("""UPDATE """ + table + """
SET avg_sknt = %s, vector_avg_drct = %s WHERE
iemid = %s and day = %s""", (sknt, drct, iemid, ts))
do_update()
if icursor.rowcount == 0:
print(('compute_daily Adding %s for %s %s %s'
) % (table, station, network, ts))
icursor.execute("""INSERT into """ + table + """
(iemid, day) values (%s, %s)""", (iemid, ts))
do_update()
icursor.close()
iemaccess.commit()
iemaccess.close()
def main():
"""Do Something"""
sys.stdout.write("Content-type: text/plain \n\n")
form = cgi.FormContent()
metadata = {}
mcursor.execute(
"""SELECT id, ST_x(geom) as lon, ST_y(geom) as lat
from stations WHERE network ~* 'ASOS' or network = 'AWOS'
and country = 'US' """
)
for row in mcursor:
metadata[row[0]] = {"lon": "%.4f" % (row[1],), "lat": "%.4f" % (row[2],)}
year = int(form["year"][0])
month = int(form["month"][0])
day = int(form["day"][0])
hour = int(form["hour"][0])
ts = mx.DateTime.DateTime(year, month, day, hour)
queryCols = (
"tmpf, dwpf, relh, drct, sknt, p01i, alti, mslp, vsby, "
"gust, skyc1, skyc2, skyc3, skyc4, skyl1, skyl2, skyl3, "
"skyl4, metar"
)
outCols = [
"tmpf",
"dwpf",
"relh",
"drct",
"sknt",
"p01i",
"alti",
"mslp",
"vsby",
"gust",
"skyc1",
"skyc2",
"skyc3",
"skyc4",
"skyl1",
"skyl2",
"skyl3",
"skyl4",
"metar",
]
fmt = "%Y-%m-%d %H:%M"
queryStr = """SELECT * from t%s
WHERE valid >= '%s' and valid < '%s'
ORDER by station ASC
""" % (
ts.year,
(ts - mx.DateTime.RelativeDateTime(minutes=10)).strftime(fmt),
(ts + mx.DateTime.RelativeDateTime(minutes=1)).strftime(fmt),
)
rD = ","
acursor.execute("SET TIME ZONE 'UTC'")
acursor.execute(queryStr)
print "station" + rD + "valid (UTC timezone)" + rD + "lon" + rD + "lat" + rD,
print queryCols
for row in acursor:
if row["station"] not in metadata:
continue
sys.stdout.write(row["station"] + rD)
sys.stdout.write(row["valid"].strftime("%Y-%m-%d %H:%M") + rD)
sys.stdout.write(metadata[row["station"]]["lon"] + rD)
sys.stdout.write(metadata[row["station"]]["lat"] + rD)
for data1 in outCols:
if data1 == "relh":
temp = temperature(row["tmpf"], "F")
dewp = temperature(row["dwpf"], "F")
val = meteorology.relh(temp, dewp).value("%")
if val != "M":
sys.stdout.write("%.2f%s" % (val, rD))
else:
sys.stdout.write("M%s" % (rD,))
elif data1 == "p01m":
if row["p01i"] >= 0:
sys.stdout.write("%.2f%s" % (row["p01i"] * 25.4, rD))
else:
sys.stdout.write("M%s" % (rD,))
elif data1 == "tmpc":
if row["tmpf"] is not None:
val = temperature(row["tmpf"], "F").value("C")
sys.stdout.write("%.2f%s" % (val, rD))
else:
sys.stdout.write("M%s" % (rD,))
elif data1 == "dwpc":
if row["dwpf"] is not None:
val = temperature(row["dwpf"], "F").value("C")
sys.stdout.write("%.2f%s" % (val, rD))
else:
sys.stdout.write("M%s" % (rD,))
elif data1 in ["metar", "skyc1", "skyc2", "skyc3", "skyc4"]:
sys.stdout.write("%s%s" % (row[data1], rD))
elif row[data1] is None or row[data1] <= -99.0:
sys.stdout.write("M%s" % (rD,))
else:
sys.stdout.write("%2.2f%s" % (row[data1], rD))
print
from pyiem import meteorology
dbconn = psycopg2.connect(database='asos', host='iemdb', user='******')
cursor = dbconn.cursor()
otmpf = []
odwpf = []
cursor.execute("""SELECT tmpf, dwpf from alldata where station = 'DSM' and
tmpf >= 80 and dwpf > 0 and tmpf < 110""")
for row in cursor:
otmpf.append(row[0])
odwpf.append(row[1])
otmpf = dt.temperature(numpy.array(otmpf), 'F')
odwpf = dt.temperature(numpy.array(odwpf), 'F')
orelh = meteorology.relh(otmpf, odwpf)
tmpf = dt.temperature(numpy.arange(80, 110), 'F')
dwpf = dt.temperature(numpy.arange(40, 80), 'F')
(t, d) = numpy.meshgrid(tmpf.value("F"), dwpf.value("F"))
hindex = meteorology.heatindex(dt.temperature(t, 'F'), dt.temperature(d, 'F'))
counts = numpy.zeros(numpy.shape(hindex.value("F")), 'f')
for otmp, odwp in zip(otmpf.value("F"), odwpf.value("F")):
if odwp < 40 or odwp >= 79.5:
continue
counts[(int(round(odwp)) - 40), int(round(otmp)) - 80] += 1.0
ttot = numpy.sum(counts, 0)
print ttot
def main():
""" Go main Go """
form = cgi.FieldStorage()
try:
tzinfo = pytz.timezone(form.getfirst("tz", "Etc/UTC"))
except:
sys.stdout.write("Invalid Timezone (tz) provided")
sys.exit()
# Save direct to disk or view in browser
direct = True if form.getfirst('direct', 'no') == 'yes' else False
stations = get_stations(form)
if direct:
sys.stdout.write('Content-type: application/octet-stream\n')
fn = "%s.txt" % (stations[0],)
if len(stations) > 1:
fn = "asos.txt"
sys.stdout.write('Content-Disposition: attachment; filename=%s\n\n' % (
fn,))
else:
sys.stdout.write("Content-type: text/plain \n\n")
dbstations = stations
if len(dbstations) == 1:
dbstations.append('XYZXYZ')
dataVars = form.getlist("data")
sts, ets = get_time_bounds(form, tzinfo)
delim = form.getfirst("format")
if "all" in dataVars:
queryCols = ("tmpf, dwpf, relh, drct, sknt, p01i, alti, mslp, "
"vsby, gust, skyc1, skyc2, skyc3, skyc4, skyl1, "
"skyl2, skyl3, skyl4, presentwx, metar")
outCols = ['tmpf', 'dwpf', 'relh', 'drct', 'sknt', 'p01i', 'alti',
'mslp', 'vsby', 'gust', 'skyc1', 'skyc2', 'skyc3',
'skyc4', 'skyl1', 'skyl2', 'skyl3', 'skyl4',
'presentwx', 'metar']
else:
dataVars = tuple(dataVars)
outCols = dataVars
dataVars = str(dataVars)[1:-2]
queryCols = re.sub("'", " ", dataVars)
if delim == "tdf":
rD = "\t"
queryCols = re.sub("," , "\t", queryCols)
else:
rD = ","
gtxt = {}
gisextra = False
if form.getfirst("latlon", "no") == "yes":
gisextra = True
mcursor.execute("""SELECT id, ST_x(geom) as lon, ST_y(geom) as lat
from stations WHERE id in %s
and (network ~* 'AWOS' or network ~* 'ASOS')""",
(tuple(dbstations),))
for row in mcursor:
gtxt[row[0]] = "%.4f%s%.4f%s" % (row['lon'], rD, row['lat'], rD)
acursor.execute("""SELECT * from alldata
WHERE valid >= %s and valid < %s and station in %s
ORDER by valid ASC""", (sts, ets, tuple(dbstations)))
sys.stdout.write("#DEBUG: Format Typ -> %s\n" % (delim,))
sys.stdout.write("#DEBUG: Time Period -> %s %s\n" % (sts, ets))
sys.stdout.write("#DEBUG: Time Zone -> %s\n" % (tzinfo,))
sys.stdout.write(("#DEBUG: Data Contact -> daryl herzmann "
"[email protected] 515-294-5978\n"))
sys.stdout.write("#DEBUG: Entries Found -> %s\n" % (acursor.rowcount,))
sys.stdout.write("station"+rD+"valid"+rD)
if gisextra:
sys.stdout.write("lon"+rD+"lat"+rD)
sys.stdout.write(queryCols+"\n")
for row in acursor:
sys.stdout.write(row["station"] + rD)
sys.stdout.write(
(row["valid"].astimezone(tzinfo)).strftime("%Y-%m-%d %H:%M") + rD )
if gisextra:
sys.stdout.write( gtxt.get(row['station'], "M%sM%s" % (rD, rD)) )
r = []
for data1 in outCols:
if data1 == 'relh':
if row['tmpf'] is not None and row['dwpf'] is not None:
tmpf = temperature(row['tmpf'], 'F')
dwpf = temperature(row['dwpf'], 'F')
val = meteorology.relh( tmpf, dwpf )
r.append("%.2f" % (val.value("%"),))
else:
r.append("M")
elif data1 == 'sped':
if row['sknt'] >= 0:
r.append("%.1f" % (row['sknt'] * 1.14, ))
else:
r.append("M")
elif data1 == 'gust_mph':
if row['gust'] >= 0:
r.append("%.1f" % (row['gust'] * 1.14, ))
else:
r.append("M")
elif data1 == 'p01m':
if row['p01i'] >= 0:
r.append("%.2f" % (row['p01i'] * 25.4, ))
else:
r.append("M")
elif data1 == 'tmpc':
if row['tmpf'] is not None:
val = temperature( row['tmpf'] , 'F').value('C')
r.append("%.2f" % (val, ))
else:
r.append("M")
elif data1 == 'dwpc':
if row['dwpf'] is not None:
val = temperature( row['dwpf'], 'F').value('C')
r.append("%.2f" % (val, ))
else:
r.append("M")
elif data1 == 'presentwx':
if row['presentwx'] is not None:
r.append("%s" % (row['presentwx'].replace(",", " "), ))
else:
r.append("M")
elif data1 in ["metar","skyc1","skyc2","skyc3","skyc4"]:
if row[data1] is None:
r.append("M")
else:
r.append("%s" % (row[data1], ))
elif row[ data1 ] is None or row[ data1 ] <= -99.0 or row[ data1 ] == "M":
r.append("M")
else:
r.append("%2.2f" % (row[ data1 ],))
sys.stdout.write("%s\n" % (rD.join(r),))
pgconn = psycopg2.connect(database='asos', host='iemdb', user='******')
# air temperature, RH, Radiation, WS, and precipitation
df = read_sql("""SELECT valid, tmpf, dwpf, sknt, p01i,
extract(month from valid) as month,
extract(hour from valid + '10 minutes'::interval) as hour,
extract(day from valid + '10 minutes'::interval) as day from alldata
WHERE station = 'DSM' and extract(month from valid) in (10, 11)
and extract(minute from valid) = 54
and valid > '1986-01-01'
""",
pgconn,
index_col=None)
df['relh'] = relh(temperature(df['tmpf'], 'F'), temperature(df['dwpf'],
'F')).value('%')
gdf = df.groupby(by=['month', 'day', 'hour']).mean()
pgconn = psycopg2.connect(database='isuag', host='iemdb', user='******')
# air temperature, RH, Radiation, WS, and precipitation
df2 = read_sql("""SELECT
extract(month from valid) as month,
extract(hour from valid + '10 minutes'::interval) as hour,
extract(day from valid + '10 minutes'::interval) as day,
c800 from hourly
WHERE station = 'A130209' and extract(month from valid) in (10, 11)
""",
pgconn,
index_col=None)
for sid in indices:
idx = indices[sid]['idx']
name = nc.variables["stationName"][idx].tostring().replace('\x00', '')
latitude = nc.variables['latitude'][idx]
longitude = nc.variables['longitude'][idx]
tmpf = s(nc.variables['temperature'][idx])
dwpf = s(nc.variables['dewpoint'][idx])
qcd = nc.variables['temperatureQCD'][idx][0]
if qcd < -10 or qcd > 10:
tmpf = "M"
dwpf = "M"
heat = "M"
if tmpf != "M" and dwpf != "M":
t = temperature(nc.variables['temperature'][idx], 'K')
d = temperature(nc.variables['dewpoint'][idx], 'K')
relh = meteorology.relh(t, d).value("%")
heat = "%5.1f" % (meteorology.heatindex(t, d).value("F"), )
drct = s2(nc.variables['windDir'][idx])
smps = s2(nc.variables['windSpeed'][idx])
sped = "M"
if smps != "M":
sped = "%5.1f" % (nc.variables['windSpeed'][idx] * 2.23694, )
wcht = "M"
if tmpf != "M" and sped != "M":
t = temperature(nc.variables['temperature'][idx], 'K')
sped = speed(nc.variables['windSpeed'][idx], 'MPS')
wcht = "%5.1f" % (meteorology.windchill(t, sped).value("F"), )
ts = indices[sid]['ts']
if met.heatindex(t, td).value('F') > 90:
heat = 'Y'
if t.value('F') < 50:
print t.value('F'), td.value('F'), met.heatindex(t, td).value('F')
if row2[1] < 32 and row2[3] > 10:
windchill = 'Y' #approx
sky = 'Clear'
if 'OVC' in [row2[4], row2[5], row2[6]]:
sky = 'Overcast'
elif 'BKN' in [row2[4], row2[5], row2[6]]:
sky = 'Broken'
elif 'FEW' in [row2[4], row2[5], row2[6]]:
sky = 'Fair Skies'
if row2[0].hour > 7 and row2[0].hour < 18:
relh.append( met.relh(t,td).value('%') )
tmpf.append( row2[1] )
if sky in ['Overcast', 'Broken']:
clcount += 1
cloudy = 'N'
if clcount > 4:
cloudy = 'Y'
relh = np.array(relh)
tmpf = np.array(tmpf)
avgrelh = np.average(relh)
avgtmpf = np.average(tmpf)
climatetmpf = (climate[day.strftime("%m%d")]['high'] +
climate[day.strftime("%m%d")]['low']) / 2.0
T = 'BELOW'
if avgtmpf > climatetmpf:
def plotter(fdict):
""" Go """
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
pgconn = psycopg2.connect(database='asos', host='iemdb', user='******')
station = fdict.get('zstation', 'AMW')
network = fdict.get('network', 'IA_ASOS')
nt = NetworkTable(network)
year = int(fdict.get('year', 2015))
varname = fdict.get('var', 'mixing_ratio')
_ = PDICT[varname]
df = read_sql("""
SELECT extract(year from valid) as year,
extract(doy from valid) as doy, tmpf, dwpf from alldata
where station = %s and dwpf > -50 and dwpf < 90 and
tmpf > -50 and tmpf < 120 and valid > '1950-01-01'
and report_type = 2
""", pgconn, params=(station,), index_col=None)
df['relh'] = relh(temperature(df['tmpf'].values, 'F'),
temperature(df['dwpf'].values, 'F')).value('%')
df['tmpc'] = temperature(df['tmpf'].values, 'F').value('C')
df['svp'] = 0.611 * np.exp(17.502 * df['tmpc'].values /
(240.97 + df['tmpc'].values))
df['vpd'] = (1. - (df['relh'] / 100.)) * df['svp']
df['mixing_ratio'] = mixing_ratio(
temperature(df['dwpf'].values, 'F')).value('KG/KG')
dailymeans = df[['year', 'doy', varname]].groupby(['year', 'doy']).mean()
dailymeans = dailymeans.reset_index()
df2 = dailymeans[['doy', varname]].groupby('doy').describe()
df2 = df2.unstack(level=-1)
dyear = df[df['year'] == year]
df3 = dyear[['doy', varname]].groupby('doy').describe()
df3 = df3.unstack(level=-1)
df3['diff'] = df3[(varname, 'mean')] - df2[(varname, 'mean')]
(fig, ax) = plt.subplots(2, 1)
multiplier = 1000. if varname == 'mixing_ratio' else 10.
ax[0].fill_between(df2.index.values, df2[(varname, 'min')] * multiplier,
df2[(varname, 'max')] * multiplier, color='gray')
ax[0].plot(df2.index.values, df2[(varname, 'mean')] * multiplier,
label="Climatology")
ax[0].plot(df3.index.values, df3[(varname, 'mean')] * multiplier,
color='r', label="%s" % (year, ))
ax[0].set_title(("%s [%s]\nDaily Mean Surface %s"
) % (station, nt.sts[station]['name'],
PDICT[varname]))
lbl = ("Mixing Ratio ($g/kg$)" if varname == 'mixing_ratio'
else PDICT[varname])
ax[0].set_ylabel(lbl)
ax[0].set_xlim(0, 366)
ax[0].set_ylim(bottom=0)
ax[0].set_xticks((1, 32, 60, 91, 121, 152, 182, 213, 244, 274, 305, 335,
365))
ax[0].set_xticklabels(calendar.month_abbr[1:])
ax[0].grid(True)
ax[0].legend(loc=2, fontsize=10)
cabove = 'b' if varname == 'mixing_ratio' else 'r'
cbelow = 'r' if cabove == 'b' else 'b'
rects = ax[1].bar(df3.index.values, df3['diff'] * multiplier,
facecolor=cabove, edgecolor=cabove)
for rect in rects:
if rect.get_y() < 0.:
rect.set_facecolor(cbelow)
rect.set_edgecolor(cbelow)
units = '$g/kg$' if varname == 'mixing_ratio' else 'hPa'
ax[1].set_ylabel("%.0f Departure (%s)" % (year, units))
ax[1].set_xlim(0, 366)
ax[1].set_xticks((1, 32, 60, 91, 121, 152, 182, 213, 244, 274, 305, 335,
365))
ax[1].set_xticklabels(calendar.month_abbr[1:])
ax[1].grid(True)
return fig, df3
def plotter(fdict):
""" Go """
import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt
pgconn = psycopg2.connect(database='asos', host='iemdb', user='******')
cursor = pgconn.cursor(cursor_factory=psycopg2.extras.DictCursor)
station = fdict.get('zstation', 'AMW')
network = fdict.get('network', 'IA_ASOS')
month = fdict.get('month', 'all')
nt = NetworkTable(network)
if month == 'all':
months = range(1, 13)
elif month == 'fall':
months = [9, 10, 11]
elif month == 'winter':
months = [12, 1, 2]
elif month == 'spring':
months = [3, 4, 5]
elif month == 'summer':
months = [6, 7, 8]
else:
ts = datetime.datetime.strptime("2000-"+month+"-01", '%Y-%b-%d')
# make sure it is length two for the trick below in SQL
months = [ts.month, 999]
cursor.execute("""
SELECT tmpf::int as t, dwpf from alldata where station = %s
and tmpf is not null and dwpf is not null and dwpf <= tmpf
and tmpf >= 0 and tmpf <= 140
and extract(month from valid) in %s
""", (station, tuple(months)))
sums = np.zeros((140,), 'f')
counts = np.zeros((140,), 'f')
for row in cursor:
r = mixing_ratio(temperature(row[1], 'F')).value('KG/KG')
sums[row[0]] += r
counts[row[0]] += 1
rows = []
for i in range(140):
if counts[i] < 3:
continue
r = sums[i] / float(counts[i])
d = dewpoint_from_pq(pressure(1000, 'MB'),
mixingratio(r, 'KG/KG')
).value('F')
rh = relh(temperature(i, 'F'), temperature(d, 'F')).value('%')
rows.append(dict(tmpf=i, dwpf=d, rh=rh))
df = pd.DataFrame(rows)
tmpf = df['tmpf']
dwpf = df['dwpf']
rh = df['rh']
(fig, ax) = plt.subplots(1, 1)
ax.bar(tmpf-0.5, dwpf, ec='green', fc='green', width=1)
ax.grid(True, zorder=11)
ax.set_title(("%s [%s]\nAverage Dew Point by Air Temperature (month=%s) "
"(%s-%s)\n"
"(must have 3+ hourly observations at the given temperature)"
) % (nt.sts[station]['name'], station, month.upper(),
nt.sts[station]['archive_begin'].year,
datetime.datetime.now().year), size=10)
ax.plot([0, 140], [0, 140], color='b')
ax.set_ylabel("Dew Point [F]")
y2 = ax.twinx()
y2.plot(tmpf, rh, color='k')
y2.set_ylabel("Relative Humidity [%] (black line)")
y2.set_yticks([0, 5, 10, 25, 50, 75, 90, 95, 100])
y2.set_ylim(0, 100)
ax.set_ylim(0, max(tmpf)+2)
ax.set_xlim(0, max(tmpf)+2)
ax.set_xlabel("Air Temperature $^\circ$F")
return fig, df
def main():
""" Go main Go """
form = cgi.FieldStorage()
try:
tzinfo = pytz.timezone(form.getfirst("tz", "Etc/UTC"))
except:
sys.stdout.write("Invalid Timezone (tz) provided")
sys.exit()
# Save direct to disk or view in browser
direct = True if form.getfirst('direct', 'no') == 'yes' else False
stations = get_stations(form)
if direct:
sys.stdout.write('Content-type: application/octet-stream\n')
fn = "%s.txt" % (stations[0], )
if len(stations) > 1:
fn = "asos.txt"
sys.stdout.write('Content-Disposition: attachment; filename=%s\n\n' %
(fn, ))
else:
sys.stdout.write("Content-type: text/plain \n\n")
dbstations = stations
if len(dbstations) == 1:
dbstations.append('XYZXYZ')
dataVars = form.getlist("data")
sts, ets = get_time_bounds(form, tzinfo)
delim = form.getfirst("format")
if "all" in dataVars:
queryCols = ("tmpf, dwpf, relh, drct, sknt, p01i, alti, mslp, "
"vsby, gust, skyc1, skyc2, skyc3, skyc4, skyl1, "
"skyl2, skyl3, skyl4, presentwx, metar")
outCols = [
'tmpf', 'dwpf', 'relh', 'drct', 'sknt', 'p01i', 'alti', 'mslp',
'vsby', 'gust', 'skyc1', 'skyc2', 'skyc3', 'skyc4', 'skyl1',
'skyl2', 'skyl3', 'skyl4', 'presentwx', 'metar'
]
else:
dataVars = tuple(dataVars)
outCols = dataVars
dataVars = str(dataVars)[1:-2]
queryCols = re.sub("'", " ", dataVars)
if delim == "tdf":
rD = "\t"
queryCols = re.sub(",", "\t", queryCols)
else:
rD = ","
gtxt = {}
gisextra = False
if form.getfirst("latlon", "no") == "yes":
gisextra = True
mcursor.execute(
"""SELECT id, ST_x(geom) as lon, ST_y(geom) as lat
from stations WHERE id in %s
and (network ~* 'AWOS' or network ~* 'ASOS')""",
(tuple(dbstations), ))
for row in mcursor:
gtxt[row[0]] = "%.4f%s%.4f%s" % (row['lon'], rD, row['lat'], rD)
acursor.execute(
"""SELECT * from alldata
WHERE valid >= %s and valid < %s and station in %s
ORDER by valid ASC""", (sts, ets, tuple(dbstations)))
sys.stdout.write("#DEBUG: Format Typ -> %s\n" % (delim, ))
sys.stdout.write("#DEBUG: Time Period -> %s %s\n" % (sts, ets))
sys.stdout.write("#DEBUG: Time Zone -> %s\n" % (tzinfo, ))
sys.stdout.write(("#DEBUG: Data Contact -> daryl herzmann "
"[email protected] 515-294-5978\n"))
sys.stdout.write("#DEBUG: Entries Found -> %s\n" % (acursor.rowcount, ))
sys.stdout.write("station" + rD + "valid" + rD)
if gisextra:
sys.stdout.write("lon" + rD + "lat" + rD)
sys.stdout.write(queryCols + "\n")
for row in acursor:
sys.stdout.write(row["station"] + rD)
sys.stdout.write(
(row["valid"].astimezone(tzinfo)).strftime("%Y-%m-%d %H:%M") + rD)
if gisextra:
sys.stdout.write(gtxt.get(row['station'], "M%sM%s" % (rD, rD)))
r = []
for data1 in outCols:
if data1 == 'relh':
if row['tmpf'] is not None and row['dwpf'] is not None:
tmpf = temperature(row['tmpf'], 'F')
dwpf = temperature(row['dwpf'], 'F')
val = meteorology.relh(tmpf, dwpf)
r.append("%.2f" % (val.value("%"), ))
else:
r.append("M")
elif data1 == 'sped':
if row['sknt'] >= 0:
r.append("%.1f" % (row['sknt'] * 1.14, ))
else:
r.append("M")
elif data1 == 'gust_mph':
if row['gust'] >= 0:
r.append("%.1f" % (row['gust'] * 1.14, ))
else:
r.append("M")
elif data1 == 'p01m':
if row['p01i'] >= 0:
r.append("%.2f" % (row['p01i'] * 25.4, ))
else:
r.append("M")
elif data1 == 'tmpc':
if row['tmpf'] is not None:
val = temperature(row['tmpf'], 'F').value('C')
r.append("%.2f" % (val, ))
else:
r.append("M")
elif data1 == 'dwpc':
if row['dwpf'] is not None:
val = temperature(row['dwpf'], 'F').value('C')
r.append("%.2f" % (val, ))
else:
r.append("M")
elif data1 == 'presentwx':
if row['presentwx'] is not None:
r.append("%s" % (row['presentwx'].replace(",", " "), ))
else:
r.append("M")
elif data1 in ["metar", "skyc1", "skyc2", "skyc3", "skyc4"]:
if row[data1] is None:
r.append("M")
else:
r.append("%s" % (row[data1], ))
elif row[data1] is None or row[data1] <= -99.0 or row[data1] == "M":
r.append("M")
else:
r.append("%2.2f" % (row[data1], ))
sys.stdout.write("%s\n" % (rD.join(r), ))
def main():
"""Do Something"""
sys.stdout.write("Content-type: text/plain \n\n")
form = cgi.FormContent()
metadata = {}
mcursor.execute("""SELECT id, ST_x(geom) as lon, ST_y(geom) as lat
from stations WHERE network ~* 'ASOS' or network = 'AWOS'
and country = 'US' """)
for row in mcursor:
metadata[row[0]] = {'lon': "%.4f" % (row[1],),
'lat': "%.4f" % (row[2],)}
year = int(form["year"][0])
month = int(form["month"][0])
day = int(form["day"][0])
hour = int(form["hour"][0])
ts = mx.DateTime.DateTime(year, month, day, hour)
queryCols = ("tmpf, dwpf, relh, drct, sknt, p01i, alti, mslp, vsby, "
"gust, skyc1, skyc2, skyc3, skyc4, skyl1, skyl2, skyl3, "
"skyl4, metar")
outCols = ['tmpf', 'dwpf', 'relh', 'drct', 'sknt', 'p01i', 'alti', 'mslp',
'vsby', 'gust', 'skyc1', 'skyc2', 'skyc3', 'skyc4',
'skyl1', 'skyl2', 'skyl3', 'skyl4', 'metar']
fmt = "%Y-%m-%d %H:%M"
queryStr = """SELECT * from t%s
WHERE valid >= '%s' and valid < '%s'
ORDER by station ASC
""" % (ts.year,
(ts - mx.DateTime.RelativeDateTime(minutes=10)).strftime(fmt),
(ts + mx.DateTime.RelativeDateTime(minutes=1)).strftime(fmt))
rD = ","
acursor.execute("SET TIME ZONE 'UTC'")
acursor.execute(queryStr)
print "station"+rD+"valid (UTC timezone)"+rD+"lon"+rD+"lat"+rD,
print queryCols
for row in acursor:
if row['station'] not in metadata:
continue
sys.stdout.write(row["station"] + rD)
sys.stdout.write(row["valid"].strftime("%Y-%m-%d %H:%M") + rD)
sys.stdout.write(metadata[row['station']]['lon'] + rD)
sys.stdout.write(metadata[row['station']]['lat'] + rD)
for data1 in outCols:
if data1 == 'relh':
temp = temperature(row['tmpf'], 'F')
dewp = temperature(row['dwpf'], 'F')
val = meteorology.relh(temp, dewp).value('%')
if val != "M":
sys.stdout.write("%.2f%s" % (val, rD))
else:
sys.stdout.write("M%s" % (rD,))
elif data1 == 'p01m':
if row['p01i'] >= 0:
sys.stdout.write("%.2f%s" % (row['p01i'] * 25.4, rD))
else:
sys.stdout.write("M%s" % (rD,))
elif data1 == 'tmpc':
if row['tmpf'] is not None:
val = temperature(row['tmpf'], 'F').value('C')
sys.stdout.write("%.2f%s" % (val, rD))
else:
sys.stdout.write("M%s" % (rD,))
elif data1 == 'dwpc':
if row['dwpf'] is not None:
val = temperature(row['dwpf'], 'F').value('C')
sys.stdout.write("%.2f%s" % (val, rD))
else:
sys.stdout.write("M%s" % (rD,))
elif data1 in ["metar", "skyc1", "skyc2", "skyc3", "skyc4"]:
sys.stdout.write("%s%s" % (row[data1], rD))
elif row[data1] is None or row[data1] <= -99.0:
sys.stdout.write("M%s" % (rD,))
else:
sys.stdout.write("%2.2f%s" % (row[data1], rD))
print