def plotter(fdict):
""" Go """
bins = [0, 1, 14, 31, 91, 182, 273, 365, 730, 1460, 2920, 3800]
pgconn = get_dbconn("postgis")
cursor = pgconn.cursor(cursor_factory=psycopg2.extras.DictCursor)
ctx = get_autoplot_context(fdict, get_description())
phenomena = ctx["phenomena"]
significance = ctx["significance"]
edate = ctx.get("edate")
if edate is not None:
edate = utc(edate.year, edate.month, edate.day, 0, 0)
cursor.execute(
"""
select wfo, extract(days from (%s::date - max(issue))) as m
from warnings where significance = %s and phenomena = %s
and issue < %s
GROUP by wfo ORDER by m ASC
""",
(edate, significance, phenomena, edate),
)
else:
cursor.execute(
"""
select wfo, extract(days from ('TODAY'::date - max(issue))) as m
from warnings where significance = %s and phenomena = %s
GROUP by wfo ORDER by m ASC
""",
(significance, phenomena),
)
edate = datetime.datetime.utcnow()
if cursor.rowcount == 0:
raise NoDataFound(("No Events Found for %s (%s.%s)") % (
vtec.get_ps_string(phenomena, significance),
phenomena,
significance,
))
data = {}
rows = []
for row in cursor:
wfo = row[0] if row[0] != "JSJ" else "SJU"
rows.append(dict(wfo=wfo, days=row[1]))
data[wfo] = max([row[1], 0])
df = pd.DataFrame(rows)
df.set_index("wfo", inplace=True)
mp = MapPlot(
sector="nws",
axisbg="white",
nocaption=True,
title="Days since Last %s by NWS Office" %
(vtec.get_ps_string(phenomena, significance), ),
subtitle="Valid %s" % (edate.strftime("%d %b %Y %H%M UTC"), ),
)
mp.fill_cwas(data, bins=bins, ilabel=True, units="Days", lblformat="%.0f")
return mp.fig, df
def main():
"""Go Main Go."""
dbconn = get_dbconn("postgis")
df = read_sql("""
WITH data as (
SELECT wfo, eventid, extract(year from issue) as year,
max(case when svs is not null then 1 else 0 end) as hit from
warnings where product_issue > '2014-04-01' and
product_issue < '2019-02-22' and phenomena = 'SV'
and date(issue) not in ('2017-08-25', '2017-08-26', '2017-08-27',
'2017-08-28', '2017-08-29', '2017-08-30')
and significance = 'W' GROUP by wfo, eventid, year
)
SELECT wfo, sum(hit) as got_update, count(*) as total_events from data
GROUP by wfo ORDER by total_events DESC
""", dbconn, index_col='wfo')
if 'JSJ' in df.index and 'SJU' not in df.index:
df.loc['SJU'] = df.loc['JSJ']
df['no_update_percent'] = (
100. - df['got_update'] / df['total_events'] * 100.
)
df.to_csv("140401_190221_svr_nofls.csv")
# NOTE: FFW followup is FFS
mp = MapPlot(
sector='nws',
title='Percentage of Severe TStorm Warnings without a SVS Update Issued',
subtitle=('1 April 2014 - 21 February 2019 (exclude Harvey 26-30 Aug '
'2017), based on unofficial data')
)
cmap = plt.get_cmap("copper_r")
cmap.set_under('white')
cmap.set_over('black')
ramp = range(0, 101, 5)
mp.fill_cwas(
df['no_update_percent'], bins=ramp, cmap=cmap, units='%', ilabel=True,
lblformat='%.1f'
)
mp.postprocess(filename='140401_190221_svr_nosvs.png')
def plotter(fdict):
""" Go """
fix()
pgconn = get_dbconn("afos")
ctx = get_autoplot_context(fdict, get_description())
pil = ctx["pil"][:3]
if ctx["ets"].astimezone(pytz.UTC) > utc():
ctx["ets"] = utc()
df = read_sql(
("SELECT source, pil, min(entered at time zone 'UTC') as first, "
"max(entered at time zone 'UTC') as last, count(*) from products "
"WHERE substr(pil, 1, 3) = %s and entered >= %s and entered < %s "
"GROUP by source, pil ORDER by source, pil ASC"),
pgconn,
params=(pil, ctx["sts"], ctx["ets"]),
index_col=None,
)
if df.empty:
raise NoDataFound("No text products found for query, sorry.")
data = {}
if ctx["var"] == "count":
gdf = df.groupby("source").sum()
elif ctx["var"] == "last":
gdf = df.groupby("source").max()
elif ctx["var"] == "first":
gdf = df.groupby("source").min()
minval = 1
maxval = gdf["count"].max()
if ctx["var"] in ["last", "first"]:
minval = gdf[ctx["var"]].min().year
maxval = gdf[ctx["var"]].max().year
if (maxval - minval) < 10:
bins = range(minval - 1, maxval + 2)
else:
bins = np.linspace(minval, maxval + 2, 10, dtype="i")
for source, row in gdf.iterrows():
if source == "PABR":
continue
key = source[1:]
if key == "JSJ":
key = "SJU"
if ctx["var"] == "count":
data[key] = row["count"]
else:
data[key] = row[ctx["var"]].year
mp = MapPlot(
title="NWS %s of %s" % (PDICT[ctx["var"]], prodDefinitions[pil]),
subtitle=("Plot valid between %s UTC and %s UTC, "
"based on unofficial IEM Archives") % (
ctx["sts"].strftime("%d %b %Y %H:%M"),
ctx["ets"].strftime("%d %b %Y %H:%M"),
),
sector="nws",
nocaption=True,
)
mp.fill_cwas(
data,
ilabel=True,
lblformat="%.0f",
cmap=ctx["cmap"],
extend="neither",
bins=bins,
units="count" if ctx["var"] == "count" else "year",
)
return mp.fig, df
