def make_plot(huc12, scenario):
"""Make the map"""
import seaborn as sns
os.chdir("/i/%s/slp/%s/%s" % (scenario, huc12[:8], huc12[8:]))
res = []
for fn in glob.glob("*.slp"):
slp = read_slp(fn)
bulk = (slp[-1]['y'][-1]) / slp[-1]['x'][-1]
length = slp[-1]['x'][-1]
if bulk < -1:
print("Greater than 100%% slope, %s %s" % (fn, bulk))
continue
res.append([(0 - bulk) * 100., length])
data = np.array(res)
g = sns.jointplot(data[:, 1],
data[:, 0],
s=40,
stat_func=None,
zorder=1,
color='tan').plot_joint(sns.kdeplot, n_levels=6)
g.ax_joint.set_xlabel("Slope Length [m]")
g.ax_joint.set_ylabel("Bulk Slope [%]")
g.fig.subplots_adjust(top=.8, bottom=0.2, left=0.15)
g.ax_joint.grid()
g.ax_marg_x.set_title(
("HUC12 %s DEP Hillslope\n"
"Kernel Density Estimate (KDE) Overlain") % (huc12, ),
fontsize=10)
ram = BytesIO()
plt.gcf().set_size_inches(3.6, 2.4)
plt.savefig(ram, format='png', dpi=100)
ram.seek(0)
return ram.read()
def make_plot(huc12, scenario):
"""Make the map"""
import seaborn as sns
os.chdir("/i/%s/slp/%s/%s" % (scenario, huc12[:8], huc12[8:]))
res = []
for fn in glob.glob("*.slp"):
slp = read_slp(fn)
bulk = (slp[-1]['y'][-1]) / slp[-1]['x'][-1]
length = slp[-1]['x'][-1]
if bulk < -1:
print("Greater than 100%% slope, %s %s" % (fn, bulk))
continue
res.append([(0 - bulk) * 100., length])
data = np.array(res)
g = sns.jointplot(
data[:, 1], data[:, 0], s=40, stat_func=None, zorder=1,
color='tan'
).plot_joint(sns.kdeplot, n_levels=6)
g.ax_joint.set_xlabel("Slope Length [m]")
g.ax_joint.set_ylabel("Bulk Slope [%]")
g.fig.subplots_adjust(top=.8, bottom=0.2, left=0.15)
g.ax_joint.grid()
g.ax_marg_x.set_title((
"HUC12 %s DEP Hillslope\n"
"Kernel Density Estimate (KDE) Overlain") % (huc12, ), fontsize=10)
ram = BytesIO()
plt.gcf().set_size_inches(3.6, 2.4)
plt.savefig(ram, format='png', dpi=100)
ram.seek(0)
return ram.read()
def main():
"""Go Main Go"""
# ['id', 'CropRotationString', 'slope',
# 'rainfall', 'runoff', 'detach', 'delivery'])
rows = []
for root, _dirs, files in tqdm(os.walk("/i/0/ofe")):
for filename in files:
ofedf = read_ofe("%s/%s" % (root, filename))
# Drop any 2007 or 2018+ data
ofedf = ofedf[(ofedf['date'] < datetime.date(2018, 1, 1))
& (ofedf['date'] >= datetime.date(2008, 1, 1))]
# Figure out the crop string
man = "%s/%s" % (root.replace(
"ofe", "man"), filename.replace("ofe", "man"))
try:
manres = read_man(man)
except Exception as exp:
print("failure reading %s\n%s" % (man, exp))
continue
slp = "%s/%s" % (root.replace(
"ofe", "slp"), filename.replace("ofe", "slp"))
slpres = read_slp(slp)
soils = get_soils(slp.replace('slp', 'prj'))
for ofe in ofedf['ofe'].unique():
myofe = ofedf[ofedf['ofe'] == ofe]
length = slpres[ofe - 1]['x'][-1] - slpres[ofe - 1]['x'][0]
slp = ((slpres[ofe - 1]['y'][0] - slpres[ofe - 1]['y'][-1]) /
length)
rows.append({
'id':
"%s_%s" % (filename[:-4], ofe),
'huc12':
filename[:12],
'fpath':
filename.split("_")[1][:-4],
'ofe':
ofe,
'CropRotationString': (get_rotation_string(manres, ofe)),
'slope[1]':
slp,
'soil_mukey':
soils[ofe - 1],
'rainfall':
-1,
'runoff[mm/yr]':
myofe['runoff'].sum() / YEARS,
'detach':
-1,
'length[m]':
length,
'delivery[t/a/yr]':
(myofe['sedleave'].sum() / YEARS / length * 4.463)
})
df = pd.DataFrame(rows)
df.to_csv('results.csv', index=False)
def main():
"""Go Main Go"""
# ['id', 'CropRotationString', 'slope',
# 'rainfall', 'runoff', 'detach', 'delivery'])
rows = []
for root, _dirs, files in tqdm(os.walk("/i/0/ofe")):
for filename in files:
ofedf = read_ofe("%s/%s" % (root, filename))
# Drop any 2007 or 2018+ data
ofedf = ofedf[(ofedf['date'] < datetime.date(2018, 1, 1)) &
(ofedf['date'] >= datetime.date(2008, 1, 1))]
# Figure out the crop string
man = "%s/%s" % (root.replace("ofe", "man"),
filename.replace("ofe", "man"))
try:
manres = read_man(man)
except Exception as exp:
print("failure reading %s\n%s" % (man, exp))
continue
slp = "%s/%s" % (root.replace("ofe", "slp"),
filename.replace("ofe", "slp"))
slpres = read_slp(slp)
soils = get_soils(slp.replace('slp', 'prj'))
for ofe in ofedf['ofe'].unique():
myofe = ofedf[ofedf['ofe'] == ofe]
length = slpres[ofe - 1]['x'][-1] - slpres[ofe - 1]['x'][0]
slp = ((slpres[ofe - 1]['y'][0] - slpres[ofe - 1]['y'][-1]) /
length)
rows.append({
'id': "%s_%s" % (filename[:-4], ofe),
'huc12': filename[:12],
'fpath': filename.split("_")[1][:-4],
'ofe': ofe,
'CropRotationString': (
get_rotation_string(manres, ofe)),
'slope[1]': slp,
'soil_mukey': soils[ofe - 1],
'rainfall': -1,
'runoff[mm/yr]': myofe['runoff'].sum() / YEARS,
'detach': -1,
'length[m]': length,
'delivery[t/a/yr]': (
myofe['sedleave'].sum() / YEARS / length * 4.463)
})
df = pd.DataFrame(rows)
df.to_csv('results.csv', index=False)
def main(argv):
"""Go Main Go"""
SCENARIO = int(argv[1])
SLOPE_THRESHOLD = float(argv[2])
# make needed mods
# use old one with mods if slope less than threshold
# replace rotation if slope greater
os.chdir("/i/0/prj")
hits = 0
total = 0
for huc8 in tqdm(glob.glob("*")):
os.chdir(huc8)
for huc4 in glob.glob("*"):
os.chdir(huc4)
for fn in glob.glob("*.prj"):
total += 1
hillslope = fn.split("_")[1].split(".")[0]
newfn = "/i/%s/prj/%s/%s/%s" % (SCENARIO, huc8, huc4, fn)
# Figure out the slope
slpfn = "/i/0/slp/%s/%s/%s%s_%s.slp" % (
huc8,
huc4,
huc8,
huc4,
hillslope,
)
slp = read_slp(slpfn)
bulk = (slp[-1]["y"][-1]) / slp[-1]["x"][-1]
slope_percent = (0 - bulk) * 100.0
if slope_percent >= SLOPE_THRESHOLD:
hits += 1
lines = open(fn).readlines()
for i, line in enumerate(lines):
if line.find("EventFile") > 0:
lines[i] = line.replace("/i/0/env",
"/i/%s/env" % (SCENARIO, ))
if (slope_percent >= SLOPE_THRESHOLD
and line.find('File = "IDEP2/') > 0):
lines[i] = (" File = "
'"IDEP2/CSCAP/SWITCHGRASS.rot"\n')
fp = open(newfn, "w")
fp.write("".join(lines))
fp.close()
os.chdir("..")
os.chdir("..")
print(("Slope: %s hits: %s total: %s ratio: %.2f") %
(SLOPE_THRESHOLD, hits, total, hits / float(total) * 100.0))
def read_data():
"""Do intensive stuff"""
os.chdir("/i/0/slp")
res = []
for huc8 in glob.glob("*"):
os.chdir(huc8)
for huc12 in glob.glob("*"):
os.chdir(huc12)
for fn in glob.glob("*.slp"):
slp = read_slp(fn)
bulk = (slp[-1]['y'][-1]) / slp[-1]['x'][-1]
if bulk < -1:
print("Greater than 100%% slope, %s %s" % (fn, bulk))
continue
res.append((0 - bulk) * 100.)
os.chdir("..")
os.chdir("..")
df = pd.DataFrame({'slopes': res})
df.to_csv('/tmp/slopes.csv', index=False)
def main(argv):
"""Go Main Go"""
SCENARIO = int(argv[1])
SLOPE_THRESHOLD = float(argv[2])
# make needed mods
# use old one with mods if slope less than threshold
# replace rotation if slope greater
os.chdir("/i/0/prj")
hits = 0
total = 0
for huc8 in tqdm(glob.glob("*")):
os.chdir(huc8)
for huc4 in glob.glob("*"):
os.chdir(huc4)
for fn in glob.glob("*.prj"):
total += 1
hillslope = fn.split("_")[1].split(".")[0]
newfn = "/i/%s/prj/%s/%s/%s" % (SCENARIO, huc8, huc4, fn)
# Figure out the slope
slpfn = "/i/0/slp/%s/%s/%s%s_%s.slp" % (huc8, huc4, huc8, huc4,
hillslope)
slp = read_slp(slpfn)
bulk = (slp[-1]['y'][-1]) / slp[-1]['x'][-1]
slope_percent = (0 - bulk) * 100.
if slope_percent >= SLOPE_THRESHOLD:
hits += 1
lines = open(fn).readlines()
for i, line in enumerate(lines):
if line.find("EventFile") > 0:
lines[i] = line.replace("/i/0/env",
"/i/%s/env" % (SCENARIO, ))
if (slope_percent >= SLOPE_THRESHOLD and
line.find('File = "IDEP2/') > 0):
lines[i] = (' File = '
'"IDEP2/CSCAP/SWITCHGRASS.rot"\n')
fp = open(newfn, 'w')
fp.write("".join(lines))
fp.close()
os.chdir("..")
os.chdir("..")
print(("Slope: %s hits: %s total: %s ratio: %.2f"
) % (SLOPE_THRESHOLD, hits, total, hits / float(total) * 100.))
def test_slp():
"""Read a slope file"""
slp = dep.read_slp(get_path('slp.txt'))
assert len(slp) == 5
assert abs(slp[4]['y'][-1] + 8.3) < 0.1
def test_slp():
"""Read a slope file"""
slp = dep.read_slp(get_path("slp.txt"))
assert len(slp) == 5
assert abs(slp[4]["y"][-1] + 2.91) < 0.01
assert abs(slp[4]["slopes"][-1] - 0.033) < 0.01
def test_slp(self):
"""Read a slope file"""
slp = dep.read_slp(get_path('slp.txt'))
self.assertEquals(len(slp), 5)
self.assertAlmostEquals(slp[4]['y'][-1], -8.3, 1)
def test_slp():
"""Read a slope file"""
slp = dep.read_slp(get_path('slp.txt'))
assert len(slp) == 5
assert abs(slp[4]['y'][-1] + 8.3) < 0.1
def read_data():
"""Do intensive stuff"""
scenarios = []
res = []
peakslopes = []
lengths = []
for huc12 in [
"070600060701",
"070801020905",
"101702040703",
"070600020602",
"071000090201",
"102300020202",
"102300060407",
"071000091101",
"101702032003",
"071000081503",
"102300031404",
"070801021001",
"101702031903",
"071000070402",
"102400030501",
"070600040401",
"102300030402",
"070802050304",
"070801060604",
"071000061401",
"102802010402",
"102400090404",
"070802070602",
"071000050703",
"070802090401",
"102400050501",
"070802060403",
]:
for scenario in [0, 1002]:
os.chdir("/i/%s/slp/%s/%s" % (scenario, huc12[:8], huc12[8:]))
for fn in glob.glob("*.slp"):
slp = read_slp(fn)
# The peak instantaneous slope
maxval = 0
for seg in slp:
maxval = max([maxval, np.max(seg["slopes"])])
# The bulk slope
bulk = (slp[-1]["y"][-1]) / slp[-1]["x"][-1]
res.append((0 - bulk) * 100.0)
scenarios.append(scenario)
peakslopes.append(maxval * 100.0)
lengths.append(slp[-1]["x"][-1])
# check for sanity
if (res[-1] - 0.01) > peakslopes[-1]:
print("max: %s bulk: %s" % (res[-1], peakslopes[-1]))
print(slp)
print(fn)
sys.exit(1)
df = pd.DataFrame(
{
"slopes": res,
"scenario": scenarios,
"maxslope": peakslopes,
"length": lengths,
}
)
df.to_csv("/tmp/slopes.csv", index=False)