def main():
"""GO!"""
pgconn = get_dbconn('idep')
cursor = pgconn.cursor()
scenario = int(sys.argv[1])
mp = MapPlot(sector='iowa', axisbg='white', nologo=True,
subtitle='1 Jan 2014 thru 31 Dec 2014',
caption='Daily Erosion Project',
title=('Harvest Index 0.8 Change in 2014 Soil Delivery '
'from Baseline'))
cursor.execute("""
with baseline as (
SELECT huc_12, sum(avg_delivery) * 4.463 as loss from results_by_huc12
where valid between '2014-01-01' and '2015-01-01' and
scenario = 0 GROUP by huc_12),
scenario as (
SELECT huc_12, sum(avg_delivery) * 4.463 as loss from results_by_huc12
where valid between '2014-01-01' and '2015-01-01' and
scenario = %s GROUP by huc_12),
agg as (
SELECT b.huc_12, b.loss as baseline_loss, s.loss as scenario_loss from
baseline b LEFT JOIN scenario s on (b.huc_12 = s.huc_12))
SELECT ST_Transform(simple_geom, 4326),
(scenario_loss - baseline_loss) / 1.0 as val, i.huc_12
from huc12 i JOIN agg d on (d.huc_12 = i.huc_12)
WHERE i.states ~* 'IA' ORDER by val DESC
""", (scenario, ))
# bins = np.arange(0, 101, 10)
bins = [-5, -2, -1, -0.5, 0, 0.5, 1, 2, 5]
cmap = plt.get_cmap("BrBG_r")
cmap.set_under('purple')
cmap.set_over('black')
norm = mpcolors.BoundaryNorm(bins, cmap.N)
for row in cursor:
# print "%s,%s" % (row[2], row[1])
polygon = loads(row[0].decode('hex'))
arr = np.asarray(polygon.exterior)
points = mp.ax.projection.transform_points(ccrs.Geodetic(),
arr[:, 0], arr[:, 1])
val = float(row[1])
# We have very small negative numbers that should just be near a
# positive zero
if val < 0 and val > -0.1:
val = 0.001
color = cmap(norm([val, ]))[0]
poly = Polygon(points[:, :2], fc=color, ec='k', zorder=2, lw=0.1)
mp.ax.add_patch(poly)
mp.draw_colorbar(bins, cmap, norm, units='T/a/yr')
mp.drawcounties()
mp.postprocess(filename='test.png')
def test_colorbar():
"""Run tests against the colorbar algorithm"""
mp = MapPlot(sector='iowa', nocaption=True)
cmap = plot.maue()
cmap.set_under('white')
clevs = list(range(0, 101, 10))
norm = mpcolors.BoundaryNorm(clevs, cmap.N)
mp.drawcities()
mp.draw_colorbar(clevs, cmap, norm)
return mp.fig
def main(argv):
"""Do Great Things"""
year = int(argv[1])
pgconn = psycopg2.connect(database='idep',
host='localhost',
port=5555,
user='******')
cursor = pgconn.cursor()
mp = MapPlot(continentalcolor='white',
nologo=True,
sector='custom',
south=36.8,
north=45.0,
west=-99.2,
east=-88.9,
subtitle='Assumes 56 lb test weight',
title=('%s Corn Yield HUC12 Average') % (year, ))
cursor.execute(
"""
with hucs as (
select huc_12, ST_Transform(simple_geom, 4326) as geo
from huc12),
data as (
SELECT huc12, avg(yield_kgm2) * 8921.8 / 56. as val from harvest
where crop = 'Corn' and valid between %s and %s
GROUP by huc12
)
SELECT geo, huc12, val from hucs h JOIN data d on (h.huc_12 = d.huc12)
""", (datetime.date(year, 1, 1), datetime.date(year, 12, 31)))
bins = np.arange(0, 310, 30)
cmap = nwsprecip()
cmap.set_under('white')
cmap.set_over('black')
norm = mpcolors.BoundaryNorm(bins, cmap.N)
for row in cursor:
polygon = loads(row[0].decode('hex'))
arr = np.asarray(polygon.exterior)
points = mp.ax.projection.transform_points(ccrs.Geodetic(), arr[:, 0],
arr[:, 1])
color = cmap(norm([
float(row[2]),
]))[0]
poly = Polygon(points[:, :2], fc=color, ec='None', zorder=2, lw=.1)
mp.ax.add_patch(poly)
mp.draw_colorbar(bins, cmap, norm, units='bu/acre')
# mp.drawcounties()
mp.postprocess(filename='test.png')
def test_colorbar3():
"""draw another colorbar"""
mp = MapPlot(sector='iowa', nocaption=True)
cmap = plot.maue()
cmap.set_over('black')
clevs = [0, 100, 250, 500, 1000, 2000, 20000]
norm = mpcolors.BoundaryNorm(clevs, cmap.N)
mp.draw_colorbar(
clevs, cmap, norm, title="Erosion $kg/m^2$", spacing='uniform'
)
return mp.fig
def test_colorbar2():
"""draw a colorbar"""
mp = MapPlot(sector='iowa', nocaption=True)
cmap = plot.maue()
clevs = list(range(0, 101, 10))
clevlabels = ["One", "Three", "Blahh", "Longest", "Five",
"Six", "Ten", "Fourty", 100000, "Hi\nHo", 100]
norm = mpcolors.BoundaryNorm(clevs, cmap.N)
mp.draw_colorbar(
clevs, cmap, norm, clevlabels=clevlabels
)
return mp.fig
def main():
pgconn = psycopg2.connect(database='idep')
cursor = pgconn.cursor()
mp = MapPlot(continentalcolor='white',
nologo=True,
sector='custom',
south=36.8,
north=45.0,
west=-99.2,
east=-88.9,
title=("HUC12 Frequency of Flowpaths with 1+ segment with "
"'T' management"))
cursor.execute("""
with data as (
select distinct flowpath from flowpath_points
where (lu2007 || lu2008 || lu2009 || lu2010 || lu2011 || lu2012
|| lu2013 || lu2014 || lu2015 || lu2016 || lu2017) ~* 'T'
and scenario = 0),
agg as (select huc_12, count(*) from flowpaths f JOIn data d
on (f.fid = d.flowpath) GROUP by huc_12)
SELECT ST_Transform(geom, 4326), h.huc_12,
coalesce(a.count, 0) from huc12 h
LEFT JOIN agg a on (h.huc_12 = a.huc_12) WHERE h.scenario = 0
ORDER by count DESC
""")
bins = np.arange(1, 45, 4)
cmap = james2()
cmap.set_under('tan')
cmap.set_over('black')
norm = mpcolors.BoundaryNorm(bins, cmap.N)
for row in cursor:
if row[2] > 30:
print("%s %s" % (row[1], row[2]))
multipoly = loads(row[0].decode('hex'))
for polygon in multipoly:
arr = np.asarray(polygon.exterior)
points = mp.ax.projection.transform_points(ccrs.Geodetic(),
arr[:, 0], arr[:, 1])
color = cmap(norm([
float(row[2]),
]))[0]
poly = Polygon(points[:, :2], fc=color, ec='None', zorder=2, lw=.1)
mp.ax.add_patch(poly)
mp.draw_colorbar(bins, cmap, norm, units='count')
mp.drawcounties()
mp.postprocess(filename='test.png')
def main():
pgconn = get_dbconn('idep')
cursor = pgconn.cursor()
mp = MapPlot(continentalcolor='white', nologo=True, # sector='custom',
# south=36.8, north=45.0, west=-99.2, east=-88.9,
caption='Daily Erosion Project',
subtitle='HUC12 Areal Averaged',
title=("Est. Hillslope Soil Loss between 12 April "
"2008 and 12 June 2008 (inclusive)"))
cursor.execute("""
with agg as (
select huc_12, sum(avg_delivery) * 4.463 as runoff from results_by_huc12
WHERE valid >= '2008-04-12' and valid <= '2008-06-12' and scenario = 0
GROUP by huc_12)
SELECT ST_Transform(geom, 4326), h.huc_12,
coalesce(a.runoff, 0) as runoff from huc12 h
LEFT JOIN agg a on (h.huc_12 = a.huc_12) WHERE h.scenario = 0
and h.states ~* 'IA'
ORDER by runoff DESC
""")
#bins = np.arange(0, 26, 2)
bins = [0.05, 0.25, 0.5, 1, 1.5, 2, 3, 5, 7, 10, 15, 20]
cmap = plt.get_cmap("plasma_r")
cmap.set_under('white')
cmap.set_over('black')
norm = mpcolors.BoundaryNorm(bins, cmap.N)
for row in cursor:
# val = distance(row[2], 'MM').value('IN')
val = row[2]
if val > 30:
print("%s %s" % (row[1], val))
multipoly = loads(row[0].decode('hex'))
for polygon in multipoly:
arr = np.asarray(polygon.exterior)
points = mp.ax.projection.transform_points(ccrs.Geodetic(),
arr[:, 0], arr[:, 1])
color = cmap(norm([val, ]))[0]
poly = Polygon(points[:, :2], fc=color, ec='None', zorder=2, lw=.1)
mp.ax.add_patch(poly)
mp.draw_colorbar(bins, cmap, norm, units='tons/acre')
mp.drawcounties()
plt.savefig('test.pdf')
def test_issue98_labelbar():
"""Sometimes our label bar sucks."""
mp = MapPlot(
title='Proportional Colorbar with some rotation',
sector='iowa', nocaption=True)
cmap = plot.maue()
cmap.set_under('white')
cmap.set_over('black')
clevs = np.arange(0, 1., 0.1)
clevs[-1] = 3.987654
norm = mpcolors.BoundaryNorm(clevs, cmap.N)
mp.plot_values(
[-94, -92, -91, -92], [42, 41, 43, 42.4],
['0.5', '0.25', '1.0', '5.0'], color=cmap(norm([0.5, 0.25, 1.0, 5.0])),
showmarker=True
)
mp.draw_colorbar(clevs, cmap, norm, spacing='proportional')
return mp.fig
def main(argv):
"""Do Great Things"""
pgconn = get_dbconn('idep')
cursor = pgconn.cursor()
mp = MapPlot(
continentalcolor='#EEEEEE',
nologo=True,
# sector='custom',
# south=36.8, north=45.0, west=-99.2, east=-88.9,
subtitle='',
title=('DEP MLRA identifier assignment using HUC12 Centroid'))
cursor.execute("""
select st_transform(geom, 4326), mlra_id from huc12 where scenario = 0
""")
bins = [
106, 107, 108, 109, 121, 137, 150, 155, 166, 175, 176, 177, 178, 179,
181, 182, 186, 187, 188, 196, 197, 204, 205
]
cmap = plt.get_cmap('terrain')
cmap.set_under('white')
cmap.set_over('black')
norm = mpcolors.BoundaryNorm(bins, cmap.N)
for row in cursor:
for polygon in loads(row[0].decode('hex')):
arr = np.asarray(polygon.exterior)
points = mp.ax.projection.transform_points(ccrs.Geodetic(),
arr[:, 0], arr[:, 1])
color = cmap(norm([
float(row[1]),
]))[0]
poly = Polygon(points[:, :2], fc=color, ec='None', zorder=2, lw=.1)
mp.ax.add_patch(poly)
mp.draw_colorbar(bins, cmap, norm, units='MLRA ID')
# mp.drawcounties()
mp.postprocess(filename='test.png')
def main(argv):
"""Go Main Go"""
v = argv[1]
agg = argv[2]
ts = datetime.date(2008, 1, 1)
ts2 = datetime.date(2017, 12, 31)
scenario = 0
# suggested for runoff and precip
if V2UNITS[v] in ['mm', 'inches']:
colors = ['#ffffa6', '#9cf26d', '#76cc94', '#6399ba', '#5558a1']
# suggested for detachment
elif v in ['avg_loss', 'avg_loss_metric']:
colors = ['#cbe3bb', '#c4ff4d', '#ffff4d', '#ffc44d', '#ff4d4d',
'#c34dee']
# suggested for delivery
elif v in ['avg_delivery', 'avg_delivery_metric']:
colors = ['#ffffd2', '#ffff4d', '#ffe0a5', '#eeb74d', '#ba7c57',
'#96504d']
cmap = mpcolors.ListedColormap(colors, 'james')
cmap.set_under('white')
cmap.set_over('black')
pgconn = get_dbconn('idep')
title = "for %s" % (ts.strftime("%-d %B %Y"),)
if ts != ts2:
title = "between %s and %s" % (ts.strftime("%-d %b %Y"),
ts2.strftime("%-d %b %Y"))
mp = MapPlot(axisbg='#EEEEEE', nologo=True, sector='iowa',
nocaption=True,
title=("DEP %s %s %s"
) % (V2NAME[v.replace("_metric", "")],
"Yearly Average" if agg == 'avg' else 'Total',
title),
caption='Daily Erosion Project')
df = read_postgis("""
WITH data as (
SELECT huc_12, extract(year from valid) as yr,
sum(""" + v.replace("_metric", "") + """) as d from results_by_huc12
WHERE scenario = %s and valid >= %s and valid <= %s
GROUP by huc_12, yr),
agg as (
SELECT huc_12, """ + agg + """(d) as d from data GROUP by huc_12)
SELECT ST_Transform(simple_geom, 4326) as geo, coalesce(d.d, 0) as data
from huc12 i LEFT JOIN agg d
ON (i.huc_12 = d.huc_12) WHERE i.scenario = %s and i.states ~* 'IA'
""", pgconn, params=(scenario, ts, ts2, scenario), geom_col='geo',
index_col=None)
df['data'] = df['data'] * V2MULTI[v]
if df['data'].max() < 0.01:
bins = [0.01, 0.02, 0.03, 0.04, 0.05]
else:
bins = np.array(V2RAMP[v]) * (10. if agg == 'sum' else 1.)
norm = mpcolors.BoundaryNorm(bins, cmap.N)
# m.ax.add_geometries(df['geo'], ccrs.PlateCarree())
for _, row in df.iterrows():
c = cmap(norm([row['data'], ]))[0]
arr = np.asarray(row['geo'].exterior)
points = mp.ax.projection.transform_points(ccrs.Geodetic(),
arr[:, 0], arr[:, 1])
p = Polygon(points[:, :2], fc=c, ec='k', zorder=2, lw=0.1)
mp.ax.add_patch(p)
mp.drawcounties()
mp.drawcities()
lbl = [round(_, 2) for _ in bins]
u = "%s, Avg: %.2f" % (V2UNITS[v], df['data'].mean())
mp.draw_colorbar(bins, cmap, norm,
clevlabels=lbl, units=u,
title="%s :: %s" % (V2NAME[v], V2UNITS[v]))
plt.savefig('%s_%s_%s%s.png' % (ts.year, ts2.year, v,
"_sum" if agg == 'sum' else ''))
if df["data"].max() < 0.01:
bins = [0.01, 0.02, 0.03, 0.04, 0.05]
else:
bins = V2RAMP[v]
norm = mpcolors.BoundaryNorm(bins, cmap.N)
patches = []
# m.ax.add_geometries(df['geo'], ccrs.PlateCarree())
for i, row in df.iterrows():
c = cmap(norm([row["data"]]))[0]
arr = np.asarray(row["geo"].exterior)
points = m.ax.projection.transform_points(
ccrs.Geodetic(), arr[:, 0], arr[:, 1]
)
p = Polygon(points[:, :2], fc=c, ec="k", zorder=2, lw=0.1)
m.ax.add_patch(p)
# m.ax.add_collection(PatchCollection(patches, match_original=True))
m.drawcounties()
m.drawcities()
lbl = [round(_, 2) for _ in bins]
u = "%s, Avg: %.2f" % (V2UNITS[v], df["data"].mean())
m.draw_colorbar(
bins,
cmap,
norm,
clevlabels=lbl,
title="%s :: %s" % (V2NAME[v], V2UNITS[v]),
)
plt.savefig("%s_%s.png" % (year, v))
#cmap = cm.get_cmap('BrBG')
#cmap.set_under('orange')
#cmap.set_over('black')
cmap = james()
cmap.set_under('white')
cmap.set_over('black')
norm = mpcolors.BoundaryNorm(bins, cmap.N)
patches = []
for row in cursor:
#print "%s,%s" % (row[2], row[1])
geom = loads(row[0].decode('hex'))
for polygon in geom:
a = np.asarray(polygon.exterior)
x, y = m.map(a[:, 0], a[:, 1])
a = zip(x, y)
#c = cmap( norm([float(row[1]),]) )[0]
diff = data.get(row[1], 0) - data1.get(row[1], 0)
print '%10s 1:%5.2f 2:%5.2f' % (row[1], data1.get(
row[1], 0), data.get(row[1], 0))
diff = data.get(row[1], 0)
c = cmap(norm([
float(diff),
]))[0]
p = Polygon(a, fc=c, ec='None', zorder=2, lw=.1)
patches.append(p)
m.ax.add_collection(PatchCollection(patches, match_original=True))
m.draw_colorbar(bins, cmap, norm, units='%')
m.drawcounties()
m.postprocess(filename='test.png')
from huc12 i LEFT JOIN data d
ON (i.huc_12 = d.huc_12) WHERE i.scenario = %s and i.states ~* 'IA'
""", pgconn, params=(scenario, ts, ts2, scenario), geom_col='geo',
index_col=None)
df['data'] = df['data'] * V2MULTI[v]
if df['data'].max() < 0.01:
bins = [0.01, 0.02, 0.03, 0.04, 0.05]
else:
bins = V2RAMP[v]
norm = mpcolors.BoundaryNorm(bins, cmap.N)
patches = []
#m.ax.add_geometries(df['geo'], ccrs.PlateCarree())
for i, row in df.iterrows():
c = cmap(norm([row['data'], ]))[0]
arr = np.asarray(row['geo'].exterior)
points = m.ax.projection.transform_points(ccrs.Geodetic(),
arr[:, 0], arr[:, 1])
p = Polygon(points[:, :2], fc=c, ec='k', zorder=2, lw=0.1)
m.ax.add_patch(p)
#print len(patches)
#m.ax.add_collection(PatchCollection(patches, match_original=True))
m.drawcounties()
m.drawcities()
lbl = [round(_, 2) for _ in bins]
u = "%s, Avg: %.2f" % (V2UNITS[v], df['data'].mean())
m.draw_colorbar(bins, cmap, norm,
clevlabels=lbl, title="%s :: %s" % (V2NAME[v], V2UNITS[v]))
plt.savefig('%s_%s.png' % (year, v))
JOIN hrap_polygons p on (p.hrap_i = foo.hrap_i)
--- select ST_Transform(the_geom,4326), total from
---
---(SELECT model_twp, sum(avg_loss) * 4.463 as total from results_by_twp WHERE
---valid between '%s-01-01' and '%s-01-01' GROUP by model_twp) as foo
---
---JOIN iatwp t on (t.model_twp = foo.model_twp) ORDER by total DESC
""" % (yr, yr, yr+1))
bins = np.array([0,0.1,0.5,0.75,1,2,3,4,5,7,10,15,20,25])
bins = np.arange(0,6.1,0.5)
cmap = cm.get_cmap('jet') #james2()
norm = mpcolors.BoundaryNorm(bins, cmap.N)
patches = []
for row in cursor:
geom = loads( row[0].decode('hex') )
for polygon in geom:
a = np.asarray(polygon.exterior)
x,y = m.map(a[:,0], a[:,1])
a = zip(x,y)
c = cmap( norm([float(row[1]),]) )[0]
p = Polygon(a,fc=c,ec='None',zorder=2, lw=.1)
patches.append(p)
m.ax.add_collection(PatchCollection(patches,match_original=True))
m.draw_colorbar(bins, cmap, norm, units='inches per hour')
m.drawcounties()
m.postprocess(filename='%srainfall.png' % (yr,))
def main(argv):
"""Go Main Go"""
v = argv[1]
agg = argv[2]
ts = datetime.date(2008, 1, 1)
ts2 = datetime.date(2016, 12, 31)
scenario = 0
# suggested for runoff and precip
if v in ['qc_precip', 'avg_runoff']:
colors = ['#ffffa6', '#9cf26d', '#76cc94', '#6399ba', '#5558a1']
# suggested for detachment
elif v in ['avg_loss']:
colors = ['#cbe3bb', '#c4ff4d', '#ffff4d', '#ffc44d', '#ff4d4d',
'#c34dee']
# suggested for delivery
elif v in ['avg_delivery']:
colors = ['#ffffd2', '#ffff4d', '#ffe0a5', '#eeb74d', '#ba7c57',
'#96504d']
cmap = mpcolors.ListedColormap(colors, 'james')
cmap.set_under('white')
cmap.set_over('black')
pgconn = psycopg2.connect(database='idep', host='localhost', port=5555,
user='******')
title = "for %s" % (ts.strftime("%-d %B %Y"),)
if ts != ts2:
title = "between %s and %s" % (ts.strftime("%-d %b %Y"),
ts2.strftime("%-d %b %Y"))
mp = MapPlot(axisbg='#EEEEEE', nologo=True, sector='iowa',
nocaption=True,
title=("DEP %s %s %s"
) % (V2NAME[v],
"Yearly Average" if agg == 'avg' else 'Total',
title),
caption='Daily Erosion Project')
df = read_postgis("""
WITH data as (
SELECT huc_12, extract(year from valid) as yr,
sum("""+v+""") as d from results_by_huc12
WHERE scenario = %s and valid >= %s and valid <= %s
GROUP by huc_12, yr),
agg as (
SELECT huc_12, """ + agg + """(d) as d from data GROUP by huc_12)
SELECT ST_Transform(simple_geom, 4326) as geo, coalesce(d.d, 0) as data
from huc12 i LEFT JOIN agg d
ON (i.huc_12 = d.huc_12) WHERE i.scenario = %s and i.states ~* 'IA'
""", pgconn, params=(scenario, ts, ts2, scenario), geom_col='geo',
index_col=None)
df['data'] = df['data'] * V2MULTI[v]
if df['data'].max() < 0.01:
bins = [0.01, 0.02, 0.03, 0.04, 0.05]
else:
bins = np.array(V2RAMP[v]) * (10. if agg == 'sum' else 1.)
norm = mpcolors.BoundaryNorm(bins, cmap.N)
# m.ax.add_geometries(df['geo'], ccrs.PlateCarree())
for _, row in df.iterrows():
c = cmap(norm([row['data'], ]))[0]
arr = np.asarray(row['geo'].exterior)
points = mp.ax.projection.transform_points(ccrs.Geodetic(),
arr[:, 0], arr[:, 1])
p = Polygon(points[:, :2], fc=c, ec='k', zorder=2, lw=0.1)
mp.ax.add_patch(p)
mp.drawcounties()
mp.drawcities()
lbl = [round(_, 2) for _ in bins]
u = "%s, Avg: %.2f" % (V2UNITS[v], df['data'].mean())
mp.draw_colorbar(bins, cmap, norm,
clevlabels=lbl, units=u,
title="%s :: %s" % (V2NAME[v], V2UNITS[v]))
plt.savefig('%s_%s_%s%s.eps' % (ts.year, ts2.year, v,
"_sum" if agg == 'sum' else ''))
SELECT ST_Transform(simple_geom, 4326),
(scenario_loss - baseline_loss) / 8.0 as val, i.huc_12
from huc12 i JOIN agg d on (d.huc_12 = i.huc_12)
WHERE i.states ~* 'IA' ORDER by val DESC
""", (scenario, ))
# bins = np.arange(0, 101, 10)
bins = [-25, -10, -5, -2, 0, 2, 5, 10, 25]
cmap = plt.get_cmap("BrBG_r")
cmap.set_under('purple')
cmap.set_over('black')
norm = mpcolors.BoundaryNorm(bins, cmap.N)
patches = []
for row in cursor:
# print "%s,%s" % (row[2], row[1])
polygon = loads(row[0].decode('hex'))
a = np.asarray(polygon.exterior)
x, y = m.map(a[:, 0], a[:, 1])
a = zip(x, y)
c = cmap(norm([float(row[1]), ]))[0]
p = Polygon(a, fc=c, ec='None', zorder=2, lw=.1)
patches.append(p)
m.ax.add_collection(PatchCollection(patches, match_original=True))
m.draw_colorbar(bins, cmap, norm, units='T/a')
m.drawcounties()
m.postprocess(filename='test.png')
""")
bins = np.arange(0, 18, 2)
# cmap = cm.get_cmap('BrBG')
# cmap.set_under('orange')
# cmap.set_over('black')
cmap = james()
cmap.set_under("white")
cmap.set_over("black")
norm = mpcolors.BoundaryNorm(bins, cmap.N)
patches = []
for row in cursor:
geom = loads(row[0].decode("hex"))
for polygon in geom:
a = np.asarray(polygon.exterior)
x, y = m.map(a[:, 0], a[:, 1])
a = zip(x, y)
# c = cmap( norm([float(row[1]),]) )[0]
diff = data.get(row[1], 0) - data1.get(row[1], 0)
diff = data.get(row[1], 0)
c = cmap(norm([float(diff)]))[0]
p = Polygon(a, fc=c, ec="None", zorder=2, lw=0.1)
patches.append(p)
m.ax.add_collection(PatchCollection(patches, match_original=True))
m.draw_colorbar(bins, cmap, norm, units="%")
m.drawcounties()
m.postprocess(filename="test.png")
def main(argv):
"""Go Main Go"""
v = argv[1]
agg = argv[2]
ts = datetime.date(2008, 1, 1)
ts2 = datetime.date(2017, 12, 31)
scenario = 0
# suggested for runoff and precip
if V2UNITS[v] in ["mm", "inches"]:
colors = ["#ffffa6", "#9cf26d", "#76cc94", "#6399ba", "#5558a1"]
# suggested for detachment
elif v in ["avg_loss", "avg_loss_metric"]:
colors = [
"#cbe3bb",
"#c4ff4d",
"#ffff4d",
"#ffc44d",
"#ff4d4d",
"#c34dee",
]
# suggested for delivery
elif v in ["avg_delivery", "avg_delivery_metric"]:
colors = [
"#ffffd2",
"#ffff4d",
"#ffe0a5",
"#eeb74d",
"#ba7c57",
"#96504d",
]
cmap = mpcolors.ListedColormap(colors, "james")
cmap.set_under("white")
cmap.set_over("black")
pgconn = get_dbconn("idep")
title = "for %s" % (ts.strftime("%-d %B %Y"), )
if ts != ts2:
title = "between %s and %s" % (
ts.strftime("%-d %b %Y"),
ts2.strftime("%-d %b %Y"),
)
mp = MapPlot(
axisbg="#EEEEEE",
nologo=True,
sector="iowa",
nocaption=True,
title=("DEP %s %s %s") % (
V2NAME[v.replace("_metric", "")],
"Yearly Average" if agg == "avg" else "Total",
title,
),
caption="Daily Erosion Project",
)
df = read_postgis(
"""
WITH data as (
SELECT huc_12, extract(year from valid) as yr,
sum(""" + v.replace("_metric", "") + """) as d from results_by_huc12
WHERE scenario = %s and valid >= %s and valid <= %s
GROUP by huc_12, yr),
agg as (
SELECT huc_12, """ + agg + """(d) as d from data GROUP by huc_12)
SELECT ST_Transform(simple_geom, 4326) as geo, coalesce(d.d, 0) as data
from huc12 i LEFT JOIN agg d
ON (i.huc_12 = d.huc_12) WHERE i.scenario = %s and i.states ~* 'IA'
""",
pgconn,
params=(scenario, ts, ts2, scenario),
geom_col="geo",
index_col=None,
)
df["data"] = df["data"] * V2MULTI[v]
if df["data"].max() < 0.01:
bins = [0.01, 0.02, 0.03, 0.04, 0.05]
else:
bins = np.array(V2RAMP[v]) * (10.0 if agg == "sum" else 1.0)
norm = mpcolors.BoundaryNorm(bins, cmap.N)
# m.ax.add_geometries(df['geo'], ccrs.PlateCarree())
for _, row in df.iterrows():
c = cmap(norm([row["data"]]))[0]
arr = np.asarray(row["geo"].exterior)
points = mp.ax.projection.transform_points(ccrs.Geodetic(), arr[:, 0],
arr[:, 1])
p = Polygon(points[:, :2], fc=c, ec="k", zorder=2, lw=0.1)
mp.ax.add_patch(p)
mp.drawcounties()
mp.drawcities()
lbl = [round(_, 2) for _ in bins]
u = "%s, Avg: %.2f" % (V2UNITS[v], df["data"].mean())
mp.draw_colorbar(
bins,
cmap,
norm,
clevlabels=lbl,
units=u,
title="%s :: %s" % (V2NAME[v], V2UNITS[v]),
)
plt.savefig("%s_%s_%s%s.png" %
(ts.year, ts2.year, v, "_sum" if agg == "sum" else ""))
