def test_fillstates():
"""Can we fill states"""
data = {'AK': 10, 'HI': 30, 'IA': 40, 'NY': 80}
mp = MapPlot(sector='nws', title='Fill AK, HI, IA, NY States',
subtitle='test_fillstates', nocaption=True)
mp.fill_states(data, ilabel=True)
return mp.fig
def plotter(fdict):
""" Go """
pgconn = get_dbconn("postgis")
ctx = get_autoplot_context(fdict, get_description())
sts = ctx["sdate"]
sts = sts.replace(tzinfo=pytz.utc)
ets = ctx["edate"]
by = ctx["by"]
ets = ets.replace(tzinfo=pytz.utc)
myfilter = ctx["filter"]
if myfilter == "NONE":
tlimiter = ""
elif myfilter == "NRS":
tlimiter = " and typetext not in ('HEAVY RAIN', 'SNOW', 'HEAVY SNOW') "
elif myfilter == "CON":
tlimiter = (" and typetext in ('TORNADO', 'HAIL', 'TSTM WND GST', "
"'TSTM WND DMG') ")
else:
tlimiter = " and typetext = '%s' " % (myfilter, )
df = read_sql(
"""
WITH data as (
SELECT distinct wfo, state, valid, type, magnitude, geom from lsrs
where valid >= %s and valid < %s """ + tlimiter + """
)
SELECT """ + by + """, count(*) from data GROUP by """ + by + """
""",
pgconn,
params=(sts, ets),
index_col=by,
)
data = {}
for idx, row in df.iterrows():
if idx == "JSJ":
idx = "SJU"
data[idx] = row["count"]
maxv = df["count"].max()
bins = np.linspace(1, maxv, 12, dtype="i")
bins[-1] += 1
mp = MapPlot(
sector="nws",
axisbg="white",
title=("Preliminary/Unfiltered Local Storm Report Counts %s") %
(PDICT[by], ),
subtitlefontsize=10,
subtitle=("Valid %s - %s UTC, type limiter: %s") % (
sts.strftime("%d %b %Y %H:%M"),
ets.strftime("%d %b %Y %H:%M"),
MDICT.get(myfilter),
),
)
cmap = plt.get_cmap(ctx["cmap"])
if by == "wfo":
mp.fill_cwas(data, bins=bins, cmap=cmap, ilabel=True)
else:
mp.fill_states(data, bins=bins, cmap=cmap, ilabel=True)
return mp.fig, df
def plotter(fdict):
""" Go """
pgconn = get_dbconn('postgis')
ctx = get_autoplot_context(fdict, get_description())
sts = ctx['sdate']
sts = sts.replace(tzinfo=pytz.utc)
ets = ctx['edate']
by = ctx['by']
ets = ets.replace(tzinfo=pytz.utc)
myfilter = ctx['filter']
if myfilter == 'NONE':
tlimiter = ''
elif myfilter == 'NRS':
tlimiter = " and typetext not in ('HEAVY RAIN', 'SNOW', 'HEAVY SNOW') "
elif myfilter == 'CON':
tlimiter = (" and typetext in ('TORNADO', 'HAIL', 'TSTM WND GST', "
"'TSTM WND DMG') ")
else:
tlimiter = " and typetext = '%s' " % (myfilter, )
df = read_sql("""
WITH data as (
SELECT distinct wfo, state, valid, type, magnitude, geom from lsrs
where valid >= %s and valid < %s """ + tlimiter + """
)
SELECT """ + by + """, count(*) from data GROUP by """ + by + """
""",
pgconn,
params=(sts, ets),
index_col=by)
data = {}
for idx, row in df.iterrows():
if idx == 'JSJ':
idx = 'SJU'
data[idx] = row['count']
maxv = df['count'].max()
bins = np.linspace(1, maxv, 12, dtype='i')
bins[-1] += 1
mp = MapPlot(
sector='nws',
axisbg='white',
title=('Preliminary/Unfiltered Local Storm Report Counts %s') %
(PDICT[by], ),
subtitlefontsize=10,
subtitle=('Valid %s - %s UTC, type limiter: %s') %
(sts.strftime("%d %b %Y %H:%M"), ets.strftime("%d %b %Y %H:%M"),
MDICT.get(myfilter)))
cmap = plt.get_cmap(ctx['cmap'])
if by == 'wfo':
mp.fill_cwas(data, bins=bins, cmap=cmap, ilabel=True)
else:
mp.fill_states(data, bins=bins, cmap=cmap, ilabel=True)
return mp.fig, df
from pyiem.plot import MapPlot
import pandas as pd
import StringIO
import matplotlib.pyplot as plt
df = pd.read_csv(StringIO.StringIO(txt.replace(" ", "")), sep='|')
df.columns = ['states', 'date']
df2 = df.groupby('states').count()
data = {}
for i, row in df2.iterrows():
data[i] = row['date']
print data
m = MapPlot(
sector='conus',
title='Days with Tornado *Watch* & Winter Storm or Blizzard Warning',
subtitle=
'1 Oct 2005 - 24 Mar 2016 :: # of Dates with both alerts active within the same state at the same time',
axisbg='white')
cmap = plt.get_cmap('jet')
cmap.set_over('black')
cmap.set_under('white')
m.fill_states(data,
bins=[0, 1, 2, 3, 4, 5, 6, 7, 10, 15, 20],
units='count',
ilabel=True,
cmap=cmap)
m.postprocess(filename='states.png')
CO | 2015-11-16
NM | 2015-11-16
TX | 2015-12-26
OK | 2015-12-26
TX | 2015-12-27
GA | 2016-01-22
NE | 2016-03-23
IA | 2016-03-23
KS | 2016-03-23"""
from pyiem.plot import MapPlot
import pandas as pd
import StringIO
import matplotlib.pyplot as plt
df = pd.read_csv(StringIO.StringIO(txt.replace(" ", "")), sep='|')
df.columns = ['states', 'date']
df2 = df.groupby('states').count()
data = {}
for i, row in df2.iterrows():
data[i] = row['date']
print data
m = MapPlot(sector='conus', title='Days with Tornado *Watch* & Winter Storm or Blizzard Warning', subtitle='1 Oct 2005 - 24 Mar 2016 :: # of Dates with both alerts active within the same state at the same time', axisbg='white')
cmap = plt.get_cmap('jet')
cmap.set_over('black')
cmap.set_under('white')
m.fill_states(data, bins=[0, 1, 2, 3, 4, 5, 6, 7, 10, 15, 20], units='count', ilabel=True, cmap=cmap)
m.postprocess(filename='states.png')
