def plot(argv):
"""Make a plot"""
df = pd.read_csv("%s_maxdailyprecip.txt" % (argv[1], ), dtype={'huc12': str})
df.set_index('huc12', inplace=True)
pgconn = get_dbconn('idep')
huc12df = gpd.GeoDataFrame.from_postgis("""
SELECT huc12, simple_geom as geo from wbd_huc12
WHERE swat_use ORDER by huc12
""", pgconn, index_col='huc12', geom_col='geo')
mp = MapPlot(
sector='custom', south=34, north=48, west=-98, east=-77,
title="%s Max Daily Precipitation" % (argv[1].split("_", 1)[1], )
)
bins = range(0, 201, 20)
cmap = stretch_cmap('terrain_r', bins)
norm = mpcolors.BoundaryNorm(bins, cmap.N)
for huc12, row in huc12df.iterrows():
for poly in row['geo']:
arr = np.asarray(poly.exterior)
points = mp.ax.projection.transform_points(ccrs.Geodetic(),
arr[:, 0], arr[:, 1])
color = cmap(norm([df.at[huc12, 'maxp'], ]))[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='mm')
mp.postprocess(filename='test.png')
def main():
"""Go Main Go."""
pgconn = get_dbconn("idep")
df = read_postgis(
"""
with centroids as (
select huc_12, st_centroid(geom) as center, simple_geom from huc12
where scenario = 0),
agg as (
select c.huc_12,
sum(case when st_y(center) < st_ymax(geom) then 1 else 0 end) as west,
count(*) from flowpaths f JOIN centroids c on
(f.huc_12 = c.huc_12) WHERE f.scenario = 0
GROUP by c.huc_12)
select a.huc_12, st_transform(c.simple_geom, 4326) as geo,
a.west, a.count from agg a JOIN centroids c
ON (a.huc_12 = c.huc_12)
""",
pgconn,
index_col=None,
geom_col="geo",
)
df["percent"] = df["west"] / df["count"] * 100.0
bins = np.arange(0, 101, 10)
cmap = plt.get_cmap("RdBu")
norm = mpcolors.BoundaryNorm(bins, cmap.N)
mp = MapPlot(
continentalcolor="thistle",
nologo=True,
sector="custom",
south=36.8,
north=48.0,
west=-99.2,
east=-88.9,
subtitle="",
title=("DEP Flowpaths North of HUC12 Centroid (%.0f/%.0f %.2f%%)" % (
df["west"].sum(),
df["count"].sum(),
df["west"].sum() / df["count"].sum() * 100.0,
)),
)
for _i, row in df.iterrows():
c = cmap(norm([row["percent"]]))[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="None", zorder=2, lw=0.1)
mp.ax.add_patch(p)
mp.drawcounties()
mp.draw_colorbar(bins, cmap, norm, title="Percent", extend="neither")
mp.postprocess(filename="/tmp/huc12_north.png")
def main():
"""Go Main Go."""
pgconn = get_dbconn("idep")
df = read_postgis(
"""
select f.huc_12, count(*) as fps,
st_transform(h.simple_geom, 4326) as geo
from flowpaths f JOIN huc12 h on
(f.huc_12 = h.huc_12) WHERE f.scenario = 0 and h.scenario = 0
GROUP by f.huc_12, geo ORDER by fps ASC
""",
pgconn,
index_col=None,
geom_col="geo",
)
bins = np.arange(1, 42, 2)
cmap = plt.get_cmap("copper")
cmap.set_over("white")
cmap.set_under("thistle")
norm = mpcolors.BoundaryNorm(bins, cmap.N)
mp = MapPlot(
continentalcolor="thistle",
nologo=True,
sector="custom",
south=36.8,
north=45.0,
west=-99.2,
east=-88.9,
subtitle="",
title=("DEP HUCs with <40 Flowpaths (%.0f/%.0f %.2f%%)" % (
len(df[df["fps"] < 40].index),
len(df.index),
len(df[df["fps"] < 40].index) / len(df.index) * 100.0,
)),
)
for _i, row in df.iterrows():
c = cmap(norm([row["fps"]]))[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="None", zorder=2, lw=0.1)
mp.ax.add_patch(p)
mp.drawcounties()
mp.draw_colorbar(bins, cmap, norm, title="Count")
mp.postprocess(filename="/tmp/huc12_cnts.png")
def main():
"""Go Main Go."""
pgconn = get_dbconn('idep')
df = read_postgis("""
select f.huc_12, count(*) as fps,
st_transform(h.simple_geom, 4326) as geo
from flowpaths f JOIN huc12 h on
(f.huc_12 = h.huc_12) WHERE f.scenario = 0 and h.scenario = 0
GROUP by f.huc_12, geo ORDER by fps ASC
""", pgconn, index_col=None, geom_col='geo')
bins = np.arange(1, 42, 2)
cmap = plt.get_cmap('copper')
cmap.set_over('white')
cmap.set_under('thistle')
norm = mpcolors.BoundaryNorm(bins, cmap.N)
mp = MapPlot(
continentalcolor='thistle', nologo=True,
sector='custom',
south=36.8, north=45.0, west=-99.2, east=-88.9,
subtitle='',
title=('DEP HUCs with <40 Flowpaths (%.0f/%.0f %.2f%%)' % (
len(df[df['fps'] < 40].index), len(df.index),
len(df[df['fps'] < 40].index) / len(df.index) * 100.
)))
for _i, row in df.iterrows():
c = cmap(norm([row['fps'], ]))[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='None', zorder=2, lw=0.1)
mp.ax.add_patch(p)
mp.drawcounties()
mp.draw_colorbar(
bins, cmap, norm,
title='Count')
mp.postprocess(filename='/tmp/huc12_cnts.png')
def make_map(ts, ts2, scenario, v):
"""Make the map"""
import matplotlib
matplotlib.use('agg')
from pyiem.plot.geoplot import MapPlot
import matplotlib.pyplot as plt
from matplotlib.patches import Polygon
import matplotlib.colors as mpcolors
import cartopy.crs as ccrs
# suggested for runoff and precip
if v in ['qc_precip', 'avg_runoff']:
c = ['#ffffa6', '#9cf26d', '#76cc94', '#6399ba', '#5558a1']
# suggested for detachment
elif v in ['avg_loss']:
c = ['#cbe3bb', '#c4ff4d', '#ffff4d', '#ffc44d', '#ff4d4d', '#c34dee']
# suggested for delivery
elif v in ['avg_delivery']:
c = ['#ffffd2', '#ffff4d', '#ffe0a5', '#eeb74d', '#ba7c57', '#96504d']
cmap = mpcolors.ListedColormap(c, 'james')
cmap.set_under('white')
cmap.set_over('black')
pgconn = get_dbconn('idep')
cursor = pgconn.cursor()
title = "for %s" % (ts.strftime("%-d %B %Y"), )
if ts != ts2:
title = "for period between %s and %s" % (ts.strftime("%-d %b %Y"),
ts2.strftime("%-d %b %Y"))
m = MapPlot(axisbg='#EEEEEE',
nologo=True,
sector='custom',
south=36.8,
north=45.0,
west=-99.2,
east=-88.9,
title='DEP %s by HUC12 %s' % (V2NAME[v], title),
caption='Daily Erosion Project')
# Check that we have data for this date!
cursor.execute("""
SELECT value from properties where key = 'last_date_0'
""")
lastts = datetime.datetime.strptime(cursor.fetchone()[0], '%Y-%m-%d')
floor = datetime.date(2007, 1, 1)
if ts > lastts.date() or ts2 > lastts.date() or ts < floor:
m.ax.text(0.5,
0.5,
"Data Not Available\nPlease Check Back Later!",
transform=m.ax.transAxes,
fontsize=20,
ha='center')
ram = cStringIO.StringIO()
plt.savefig(ram, format='png', dpi=100)
ram.seek(0)
return ram.read(), False
cursor.execute(
"""
WITH data as (
SELECT huc_12, sum(""" + v + """) as d from results_by_huc12
WHERE scenario = %s and valid between %s and %s
GROUP by huc_12)
SELECT ST_Transform(simple_geom, 4326), coalesce(d.d, 0)
from huc12 i LEFT JOIN data d
ON (i.huc_12 = d.huc_12) WHERE i.scenario = %s
""", (scenario, ts.strftime("%Y-%m-%d"), ts2.strftime("%Y-%m-%d"),
scenario))
patches = []
data = []
for row in cursor:
polygon = loads(row[0].decode('hex'))
a = np.asarray(polygon.exterior)
points = m.ax.projection.transform_points(ccrs.Geodetic(), a[:, 0],
a[:, 1])
p = Polygon(points[:, :2], fc='white', ec='k', zorder=2, lw=.1)
patches.append(p)
data.append(row[1])
data = np.array(data) * V2MULTI[v]
if np.max(data) < 0.05:
bins = [0.01, 0.02, 0.03, 0.04, 0.05]
else:
bins = myjenks(data, 'bah', len(c))
norm = mpcolors.BoundaryNorm(bins, cmap.N)
for val, patch in zip(data, patches):
c = cmap(norm([
val,
]))[0]
patch.set_facecolor(c)
m.ax.add_patch(patch)
lbl = [round(_, 2) for _ in bins]
m.draw_colorbar(bins, cmap, norm, units=V2UNITS[v], clevlabels=lbl)
ram = cStringIO.StringIO()
plt.savefig(ram, format='png', dpi=100)
ram.seek(0)
return ram.read(), True
def make_map(huc, ts, ts2, scenario, v, form):
"""Make the map"""
projection = EPSG[5070]
plt.close()
# suggested for runoff and precip
if v in ["qc_precip", "avg_runoff"]:
# c = ['#ffffa6', '#9cf26d', '#76cc94', '#6399ba', '#5558a1']
cmap = james()
# suggested for detachment
elif v in ["avg_loss"]:
# c =['#cbe3bb', '#c4ff4d', '#ffff4d', '#ffc44d', '#ff4d4d', '#c34dee']
cmap = dep_erosion()
# suggested for delivery
elif v in ["avg_delivery"]:
# c =['#ffffd2', '#ffff4d', '#ffe0a5', '#eeb74d', '#ba7c57', '#96504d']
cmap = dep_erosion()
pgconn = get_dbconn("idep")
cursor = pgconn.cursor()
title = "for %s" % (ts.strftime("%-d %B %Y"),)
if ts != ts2:
title = "for period between %s and %s" % (
ts.strftime("%-d %b %Y"),
ts2.strftime("%-d %b %Y"),
)
if "averaged" in form:
title = "averaged between %s and %s (2008-2017)" % (
ts.strftime("%-d %b"),
ts2.strftime("%-d %b"),
)
# Check that we have data for this date!
cursor.execute(
"SELECT value from properties where key = 'last_date_0'",
)
lastts = datetime.datetime.strptime(cursor.fetchone()[0], "%Y-%m-%d")
floor = datetime.date(2007, 1, 1)
if ts > lastts.date() or ts2 > lastts.date() or ts < floor:
plt.text(
0.5,
0.5,
"Data Not Available\nPlease Check Back Later!",
fontsize=20,
ha="center",
)
ram = BytesIO()
plt.savefig(ram, format="png", dpi=100)
plt.close()
ram.seek(0)
return ram.read(), False
if huc is None:
huclimiter = ""
elif len(huc) == 8:
huclimiter = " and substr(i.huc_12, 1, 8) = '%s' " % (huc,)
elif len(huc) == 12:
huclimiter = " and i.huc_12 = '%s' " % (huc,)
if "iowa" in form:
huclimiter += " and i.states ~* 'IA' "
if "mn" in form:
huclimiter += " and i.states ~* 'MN' "
if "averaged" in form:
# 11 years of data is standard
# 10 years is for the switchgrass one-off
with get_sqlalchemy_conn("idep") as conn:
df = read_postgis(
f"""
WITH data as (
SELECT huc_12, sum({v}) / 10. as d from results_by_huc12
WHERE scenario = %s and to_char(valid, 'mmdd') between %s and %s
and valid between '2008-01-01' and '2018-01-01'
GROUP by huc_12)
SELECT simple_geom as geom,
coalesce(d.d, 0) * %s as data
from huc12 i LEFT JOIN data d
ON (i.huc_12 = d.huc_12) WHERE i.scenario = %s {huclimiter}
""",
conn,
params=(
scenario,
ts.strftime("%m%d"),
ts2.strftime("%m%d"),
V2MULTI[v],
0,
),
geom_col="geom",
)
else:
with get_sqlalchemy_conn("idep") as conn:
df = read_postgis(
f"""
WITH data as (
SELECT huc_12, sum({v}) as d from results_by_huc12
WHERE scenario = %s and valid between %s and %s
GROUP by huc_12)
SELECT simple_geom as geom,
coalesce(d.d, 0) * %s as data
from huc12 i LEFT JOIN data d
ON (i.huc_12 = d.huc_12) WHERE i.scenario = %s {huclimiter}
""",
conn,
params=(
scenario,
ts.strftime("%Y-%m-%d"),
ts2.strftime("%Y-%m-%d"),
V2MULTI[v],
0,
),
geom_col="geom",
)
minx, miny, maxx, maxy = df["geom"].total_bounds
buf = 10000.0 # 10km
m = MapPlot(
axisbg="#EEEEEE",
logo="dep",
sector="custom",
south=miny - buf,
north=maxy + buf,
west=minx - buf,
east=maxx + buf,
projection=projection,
title="DEP %s by HUC12 %s" % (V2NAME[v], title),
titlefontsize=16,
caption="Daily Erosion Project",
)
if ts == ts2:
# Daily
bins = RAMPS["english"][0]
else:
bins = RAMPS["english"][1]
norm = mpcolors.BoundaryNorm(bins, cmap.N)
for _, row in df.iterrows():
p = Polygon(
row["geom"].exterior.coords,
fc=cmap(norm([row["data"]]))[0],
ec="k",
zorder=5,
lw=0.1,
)
m.ax.add_patch(p)
label_scenario(m.ax, scenario, pgconn)
lbl = [round(_, 2) for _ in bins]
if huc is not None:
m.drawcounties()
m.drawcities()
m.draw_colorbar(
bins, cmap, norm, units=V2UNITS[v], clevlabels=lbl, spacing="uniform"
)
if "progressbar" in form:
fig = plt.gcf()
avgval = df["data"].mean()
fig.text(
0.01,
0.905,
"%s: %4.1f T/a"
% (ts.year if "averaged" not in form else "Avg", avgval),
fontsize=14,
)
bar_width = 0.758
# yes, a small one off with years having 366 days
proportion = (ts2 - ts).days / 365.0 * bar_width
rect1 = Rectangle(
(0.15, 0.905),
bar_width,
0.02,
color="k",
zorder=40,
transform=fig.transFigure,
figure=fig,
)
fig.patches.append(rect1)
rect2 = Rectangle(
(0.151, 0.907),
proportion,
0.016,
color=cmap(norm([avgval]))[0],
zorder=50,
transform=fig.transFigure,
figure=fig,
)
fig.patches.append(rect2)
if "cruse" in form:
# Crude conversion of T/a to mm depth
depth = avgval / 5.0
m.ax.text(
0.9,
0.92,
"%.2fmm" % (depth,),
zorder=1000,
fontsize=24,
transform=m.ax.transAxes,
ha="center",
va="center",
bbox=dict(color="k", alpha=0.5, boxstyle="round,pad=0.1"),
color="white",
)
ram = BytesIO()
plt.savefig(ram, format="png", dpi=100)
plt.close()
ram.seek(0)
return ram.read(), True
