本文整理汇总了Python中pyiem.plot.MapPlot.fill_ugc_counties方法的典型用法代码示例。如果您正苦于以下问题：Python MapPlot.fill_ugc_counties方法的具体用法？Python MapPlot.fill_ugc_counties怎么用？Python MapPlot.fill_ugc_counties使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类pyiem.plot.MapPlot的用法示例。
在下文中一共展示了MapPlot.fill_ugc_counties方法的3个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: as
# 需要导入模块: from pyiem.plot import MapPlot [as 别名]
# 或者: from pyiem.plot.MapPlot import fill_ugc_counties [as 别名]
GROUP by ugc),
u as (SELECT ugc, ST_Area(ST_Transform(geom, 2163)) / 1000000. as area
from ugcs where substr(ugc,3,1) = 'C' and end_ts is null)
SELECT data.ugc, data.data, data.data / u.area
from data JOIN u on (u.ugc = data.ugc)
'''
pcursor.execute("""
WITH data as (
SELECT ugc, count(*) / %s as data from
(select distinct ugc, generate_series(issue, expire, '1 minute'::interval)
from warnings where phenomena in %s and significance = 'W'
and ugc is not null and (expire - issue) < '1440 minutes'::interval
and issue > %s and issue < %s) as foo2
GROUP by ugc),
u as (SELECT ugc, ST_Area(ST_Transform(geom, 2163)) / 1000000. as area
from ugcs where substr(ugc,3,1) = 'C' and end_ts is null)
SELECT data.ugc, data.data, data.data / u.area
from data JOIN u on (u.ugc = data.ugc)
""", (opts['years'], opts['dbcols'], opts['sdate'], opts['edate']))
data = {}
for row in pcursor:
data[row[0]] = float(row[2 if opts['normalized'] else 1])
m.fill_ugc_counties(data, bins, cmap=cmap, units=opts['units'])
m.postprocess(filename=fn)
subprocess.call("xv %s" % (fn,), shell=True)
示例2: as
# 需要导入模块: from pyiem.plot import MapPlot [as 别名]
# 或者: from pyiem.plot.MapPlot import fill_ugc_counties [as 别名]
title='1+ TOR warn for 100 most active TOR warn days 1986-2015',
subtitle=('A day is defined as 12 to 12 UTC period, did the '
'county get 1+ warning during those 100 events?'),
cwas=True)
bins = np.arange(0, 101, 10)
bins[0] = 1
norm = mpcolors.BoundaryNorm(bins, cmap.N)
pcursor.execute("""
WITH data as (
SELECT ugc, date(issue at time zone 'UTC' + '12 hours'::interval)
from warnings where phenomena in ('TO') and significance = 'W'
),
maxdays as (
SELECT date, count(*) from data GROUP by date ORDER by count DESC LIMIT 100
),
events as (
SELECT distinct ugc, d.date from data d JOIN maxdays m on (m.date = d.date)
)
SELECT ugc, count(*) from events GROUP by ugc
""")
data = {}
for row in pcursor:
data[row[0]] = float(row[1])
m.fill_ugc_counties(data, bins, cmap=cmap, units='Count')
m.postprocess(filename='test.png')
示例3: as
# 需要导入模块: from pyiem.plot import MapPlot [as 别名]
# 或者: from pyiem.plot.MapPlot import fill_ugc_counties [as 别名]
WITH data as (
SELECT distinct s.iemid from summary s JOIN stations t on (t.iemid = s.iemid)
WHERE t.network = 'IACOCORAHS' and s.day > '2014-04-12' and pday > 0)
SELECT ugc_county, count(*) from stations t JOIN data d on (d.iemid = t.iemid)
GROUP by ugc_county ORDER by count DESC
""")
data = {}
for row in icursor:
data[row[0]] = row[1]
# Query out centroids of counties...
pcursor.execute("""SELECT ugc, ST_x(ST_centroid(geom)) as lon,
ST_y(ST_centroid(geom)) as lat
from ugcs WHERE state = 'IA' and end_ts is null and substr(ugc,3,1) = 'C'""")
clons = []
clats = []
cvals = []
for row in pcursor:
cvals.append(data.get(row[0],0))
clats.append(row[2])
clons.append(row[1])
m = MapPlot(axisbg='white', title='Iowa CoCoRaHS Observers Per County',
subtitle='Sites with at least one report in past year (Apr 2014-2015)')
m.fill_ugc_counties(data, [1,2,3,4,5,7,10,15,20])
m.plot_values(clons, clats, cvals)
m.drawcounties()
m.postprocess(filename='test.png')