def stats(output, date, fd):
fd.write('-' * 80)
fd.write(os.linesep)
fd.write('NDVI class statistics ({0}: {1})'.format(output, date))
fd.write(os.linesep)
fd.write('-' * 80)
fd.write(os.linesep)
from subprocess import PIPE
ret = Module('v.report', map=output, option='area', stdout_=PIPE)
for line in ret.outputs.stdout.splitlines(
)[1:]: # skip first line (cat|label|area)
# parse line (eg. 1||2712850)
data = line.split('|')
cat = data[0]
area = float(data[-1])
fd.write('NDVI class {0}: {1:.1f} ha'.format(cat, area / 1e4))
fd.write(os.linesep)
data = vector_db_select(output)
for vals in data['values'].values():
# unfortunately we need to cast values by float
fd.write('NDVI class {0}: {1:.4f} (min) {2:.4f} (max) {3:.4f} (mean)'.
format(vals[0], float(vals[2]), float(vals[3]),
float(vals[4])))
fd.write(os.linesep)
def stats():
print('-' * 80)
print('NDVI class statistics')
print('-' * 80)
from subprocess import PIPE
ret = Module('v.report',
map=options["output"],
option='area',
stdout_=PIPE)
for line in ret.outputs.stdout.splitlines(
)[1:]: # skip first line (cat|label|area)
# parse line (eg. 1||2712850)
data = line.split('|')
cat = data[0]
area = float(data[-1])
print('NDVI class {0}: {1:.1f} ha'.format(cat, area / 1e4))
# v.to.rast: use -c flag for updating statistics if exists
Module('v.rast.stats',
flags='c',
map=options["output"],
raster='ndvi',
column_prefix='ndvi',
method=['minimum', 'maximum', 'average'])
data = vector_db_select(options["output"])
for vals in data['values'].itervalues():
# unfortunately we need to cast values by float
print('NDVI class {0}: {1:.4f} (min) {2:.4f} (max) {3:.4f} (mean)'.
format(vals[0], float(vals[2]), float(vals[3]), float(vals[4])))
def basin_discharge_plots(self, save=False, show=True, legend=True, bigtitle=False, alltimes=False, onefig=True, ICE=None):
from grass.script import vector as vect
import matplotlib.pyplot as plt
Qmodern = dict(Mississippi=18430., Mackenzie=9910., Colorado=665., Rio_Grande=150., Hudson=620., Columbia=7500., Susquehanna=1082., Saint_Lawrence=12000., Hudson_Strait=30900., Yukon=6428.)
if ICE:
pass
else:
try:
ICE = self.ICE
except:
# hack-ey solution here to plotting
ICE = grass.parse_command('g.gisenv')['LOCATION_NAME']
ICE = re.findall("[a-zA-Z0-9]+", ICE)[0]
self.ICE = ICE
# River list
self.riversAll = np.array(list(set(list(grass.parse_command('v.db.select', map='river_mouth_regions', columns='river', flags="c")))))
self.rnumAll = np.arange(1,len(self.riversAll)+1) # Is this OK? what about database table rnum?
# Create dicts to hold lists of Q_i, Q_m, Q_t
# WHICH RIVERS WE USE ARE PRE-DEFINED HERE; CLUNKY TO CHANGE!
self.Q_i = dict(Mississippi=[], Mackenzie=[], Colorado=[], Rio_Grande=[], Hudson=[], Columbia=[], Susquehanna=[], Saint_Lawrence=[], Hudson_Strait=[], Yukon=[])
self.Q_m = dict(Mississippi=[], Mackenzie=[], Colorado=[], Rio_Grande=[], Hudson=[], Columbia=[], Susquehanna=[], Saint_Lawrence=[], Hudson_Strait=[], Yukon=[])
self.Q_t = dict(Mississippi=[], Mackenzie=[], Colorado=[], Rio_Grande=[], Hudson=[], Columbia=[], Susquehanna=[], Saint_Lawrence=[], Hudson_Strait=[], Yukon=[])
#shortRivers = np.array(['Mississippi River', 'Susquehanna River', 'Hudson River', 'Saint Lawrence River', 'Hudson Strait', 'Mackenzie River', 'Columbia River', 'Colorado River', 'Rio Grande'])
#srnu = np.array(['Mississippi', 'Susquehanna', 'Hudson', 'Saint_Lawrence', 'Hudson_Strait', 'Mackenzie', 'Columbia', 'Colorado', 'Rio_Grande'])
#self.Q_i = dict(Mississippi=[], Mackenzie=[], Columbia=[], Saint_Lawrence=[], Hudson_Strait=[], Other_North=[], Volga=[], White_Sea = [], Daugava_and_Baltic=[])
#self.Q_m = dict(Mississippi=[], Mackenzie=[], Columbia=[], Saint_Lawrence=[], Hudson_Strait=[], Other_North=[], Volga=[], White_Sea = [], Daugava_and_Baltic=[])
#self.Q_t = dict(Mississippi=[], Mackenzie=[], Columbia=[], Saint_Lawrence=[], Hudson_Strait=[], Other_North=[], Volga=[], White_Sea = [], Daugava_and_Baltic=[])
srnu = self.Q_t.keys()
shortRivers = []
for i in range(len(srnu)): # space for list of names
shortRivers.append(srnu[i].replace('_', ' '))
# Update rivers and rnum to include only these desired outputs
self.rivers = np.array(self.Q_t.keys())
for i in range(len(self.rivers)): # space for list of names
self.rivers[i] = self.rivers[i].replace('_', ' ')
self.rnum = []
for river in self.rivers:
self.rnum.append(self.rnumAll[self.riversAll == river][0])
for age in self.ages:
print age
drainage_basins = 'drainage_basins_' + age
try:
drainage_basins_cols = vect.vector_db_select(drainage_basins)['columns']
drainage_basins_lol = vect.vector_db_select(drainage_basins)['values'].values()
river_name_column = (np.array(drainage_basins_cols) == 'river').nonzero()[0][0]
meltwater_discharge_column = (np.array(drainage_basins_cols) == 'Q_ice').nonzero()[0][0]
meteoric_discharge_column = (np.array(drainage_basins_cols) == 'Q_meteoric_uncorrected').nonzero()[0][0]
#total_discharge_column = (np.array(drainage_basins_cols) == 'Q_total').nonzero()[0][0]
except:
print 'Error at', age
drainage_basins_cols = None
for river in self.rivers:
rnu = river.replace(' ', '_') # Underscore for dict
# Some rivers not appearing in database table, so have to do this as a quick fix!
# Maybe clashing rules files from running many of these at once?
self.Q_i[rnu].append(np.nan)
self.Q_m[rnu].append(np.nan)
self.Q_t[rnu].append(np.nan)
if drainage_basins_cols:
for river in self.rivers:
rnu = river.replace(' ', '_') # Underscore for dict
# Some rivers not appearing in database table, so have to do this as a quick fix!
# Maybe clashing rules files from running many of these at once?
self.Q_i[rnu].append(np.nan)
self.Q_m[rnu].append(np.nan)
self.Q_t[rnu].append(np.nan)
for row in drainage_basins_lol:
if row[river_name_column] == river:
#print row
#if row[total_discharge_column] != '':
self.Q_i[rnu][-1] = row[meltwater_discharge_column]
self.Q_m[rnu][-1] = row[meteoric_discharge_column]
"""
else:
print age, '!!!', river
self.Q_i[rnu].append(np.nan)
self.Q_m[rnu].append(np.nan)
self.Q_t[rnu].append(np.nan)
if river == 'Hudson':
print age, row[total_discharge_column]
"""
self.Q_meteoric_simulated_now = []
for river in self.rivers:
rnu = river.replace(' ', '_') # Underscore for dict
self.Q_m[rnu] = np.array(self.Q_m[rnu]).astype(float)
self.Q_t[rnu] = np.array(self.Q_i[rnu]).astype(float)
try:
self.Q_meteoric_simulated_now.append(self.Q_m[rnu][-1])
self.Q_m[rnu] *= float(Qmodern[rnu]) / np.mean(np.array(self.Q_m[rnu]).astype(float)[self.ages_numeric < 3000])
self.Q_t[rnu] += np.array(self.Q_m[rnu]).astype(float) # now forced to match!
except:
self.Q_meteoric_simulated_now.append(np.nan)
self.output.HighDischargeTimes(self)
outvars = {'ages': self.ages, 'ages_numeric': self.ages_numeric, \
'Q_i': self.Q_i, 'Q_m': self.Q_m, 'Q_t': self.Q_t}
np.save(self.ICE+'.npy', outvars)
sys.exit("Mostly, need to fix long vs. short names, but just use Qhist_all.py after running this")
if alltimes:
agei=0
if onefig:
print "OneFig doesn't function currently for all times"
#for age in self.ages:
for i in range(len(self.rivers)):
river = self.rivers[i]
print river
rnu = river.replace(' ', '_') # Underscore for dict
plt.figure(i, figsize=(8,5))
if bigtitle:
plt.plot(self.ages_numeric/1000., self.Q_t[rnu],'k-', linewidth=10, label='Total')
plt.plot(self.ages_numeric/1000., self.Q_m[rnu],'g-', linewidth=4, label='Meteoric')
plt.plot(self.ages_numeric/1000., self.Q_i[rnu], 'b--', linewidth=4, label='Melt')
plt.plot(self.ages_numeric/1000.[1+agei], self.Q_t[rnu][agei], 'ro', markersize=20)
elif onefig:
pass
else:
plt.plot(self.ages_numeric/1000., self.Q_t[rnu],'k-', linewidth=6, label='Total')
plt.plot(self.ages_numeric/1000., self.Q_m[rnu],'g-', linewidth=2, label='Meteoric')
plt.plot(self.ages_numeric/1000., self.Q_i[rnu], 'b--', linewidth=2, label='Melt')
plt.plot(self.ages_numeric/1000.[1+agei], self.Q_t[rnu][agei], 'ro', markersize=12)
if legend:
plt.legend(loc='upper left')
elif onefig:
pass
if bigtitle:
plt.title(river, fontsize=48, fontweight='bold')
plt.xlabel('Age [ka]', fontsize=24)
plt.ylabel('Discharge [m$^3$/s]', fontsize=24)
elif onefig:
pass
else:
plt.title(river, fontsize=24, fontweight='bold')
plt.xlabel('Age [ka]', fontsize=16)
plt.ylabel('Discharge [m$^3$/s]', fontsize=16)
fig = plt.gcf()
if bigtitle:
fig.subplots_adjust(top=0.84)
for label in plt.gca().get_xticklabels() + plt.gca().get_yticklabels():
label.set_fontsize(20)
fig.subplots_adjust(left=0.22)
fig.subplots_adjust(bottom=0.15)
elif onefig:
pass
else:
fig.subplots_adjust(left=0.16)
fig.subplots_adjust(bottom=0.12)
if save:
if bigtitle:
plt.savefig('alltimes/dischargefigs_bigtitles/'+rnu+'_'+age)
elif legend:
plt.savefig('alltimes/dischargefigs_legends/'+rnu+'_'+age)
else:
plt.savefig('alltimes/dischargefigs/'+rnu+'_'+age)
plt.clf()
agei+=1
if show:
print "Not allowing hundreds of figures to be shown - poor computer!"
else:
if onefig:
print "onefig ignores bigtitle"
fig = plt.figure(figsize = (10, 14))
fig.text((1+.17-.1)/2., 0.04, 'Age [ka]', ha='center', va='center', fontsize=24, fontweight='bold')
fig.text(0.06, 0.5, 'Discharge [m$^3$s$^{-1}$]', ha='center', va='center', rotation='vertical', fontsize=24, fontweight='bold')
#ax0 = fig.add_subplot(111)
#ax0.spines['top'].set_color('none')
#ax0.spines['bottom'].set_color('none')
#ax0.spines['left'].set_color('none')
#ax0.spines['right'].set_color('none')
#ax0.tick_params(labelcolor='w', top='off', bottom='off', left='off', right='off')
#ax0.set_xlabel('Age [ka]', fontsize=16)
#ax0.set_ylabel('Discharge [m$^3$s$^{-1}$]', fontsize=16)
iof = 1
for i in range(len(shortRivers)):
print shortRivers[i]
rnu = srnu[i].replace(' ', '_') # Underscore for dict
ax = fig.add_subplot(5, 2, iof)
try:
for row in self.EnhancedQ[shortRivers[i]]:
ax.axvspan(row[0], row[1], facecolor='0.8', linewidth='0')
except:
print "No geological constraints entered for", shortRivers[i]
ax.plot(self.ages_numeric/1000., self.Q_t[rnu],'k-', linewidth=6, label='Total discharge')
ax.plot(self.ages_numeric/1000., self.Q_i[rnu], 'b--', linewidth=2, label='Meltwater discharge')
ax.plot(self.ages_numeric/1000., self.Q_m[rnu],'g-', linewidth=2, label='Meteoric water\n(P-ET) discharge')
ax.set_title(shortRivers[i], fontsize=16, fontweight='bold')
ax.set_xlim((0, 20))
ax.set_ylim((0, ax.get_ylim()[-1]))
try:
plt.plot(self.ages_numeric[-1]/1000., self.Q_meteoric_simulated_now[(self.rivers == rnu).nonzero()[0][0]], 'go', markersize=10, zorder=-100)
except:
print "No discharge constraints entered for", shortRivers[i]
# set y-lim based on model outputs
"""
if rnu == 'Mississippi':
ax.set_ylim((0, 200000))
elif rnu == 'Susquehanna':
ax.set_ylim((0, 40000))
elif rnu == 'Hudson':
ax.set_ylim((0, 120000))
elif rnu == 'Saint_Lawrence':
ax.set_ylim((0, 160000))
elif rnu == 'Hudson_Strait':
ax.set_ylim((0, 250000))
elif rnu == 'Mackenzie':
ax.set_ylim((0, 160000))
elif rnu == 'Columbia':
ax.set_ylim((0, 18000))
elif rnu == 'Colorado':
ax.set_ylim((0, 2000))
elif rnu == 'Rio_Grande':
ax.set_ylim((0, 600))
"""
if iof == 9:
ax.legend(loc = 'center', bbox_to_anchor = (1.71, 0.5), fontsize=14)
iof += 1
fig.tight_layout()
fig.subplots_adjust(left=.17, bottom=.08, right=None, top=None, wspace=None, hspace=.4)
if save:
plt.savefig('all_rivers_'+ICE+'.png')
plt.savefig('all_rivers_'+ICE+'.pdf')
else:
for i in range(len(self.rivers)):
river = self.rivers[i]
rnu = river.replace(' ', '_') # Underscore for dict
plt.figure(i, figsize=(8,5))
if bigtitle:
plt.plot(self.ages_numeric/1000., self.Q_t[rnu],'k-', linewidth=10, label='Total')
plt.plot(self.ages_numeric/1000., self.Q_m[rnu],'g-', linewidth=4, label='Meteoric')
plt.plot(self.ages_numeric/1000., self.Q_i[rnu], 'b--', linewidth=4, label='Melt')
else:
plt.plot(self.ages_numeric/1000., self.Q_t[rnu],'k-', linewidth=6, label='Total')
plt.plot(self.ages_numeric/1000., self.Q_m[rnu],'g-', linewidth=2, label='Meteoric')
plt.plot(self.ages_numeric/1000., self.Q_i[rnu], 'b--', linewidth=2, label='Melt')
if legend:
plt.legend(loc='upper left')
if bigtitle:
plt.title(river, fontsize=48, fontweight='bold')
plt.xlabel('Age [ka]', fontsize=24)
plt.ylabel('Discharge [m$^3$/s]', fontsize=24)
else:
plt.title(river, fontsize=24, fontweight='bold')
plt.xlabel('Age [ka]', fontsize=16)
plt.ylabel('Discharge [m$^3$/s]', fontsize=16)
fig = plt.gcf()
if bigtitle:
fig.subplots_adjust(top=0.84)
for label in plt.gca().get_xticklabels() + plt.gca().get_yticklabels():
label.set_fontsize(20)
fig.subplots_adjust(left=0.22)
fig.subplots_adjust(bottom=0.15)
else:
fig.subplots_adjust(left=0.16)
fig.subplots_adjust(bottom=0.12)
if save:
if bigtitle:
plt.savefig('dischargefigs_bigtitles/'+rnu)
elif legend:
plt.savefig('dischargefigs_legends/'+rnu)
else:
plt.savefig('dischargefigs/'+rnu)
if show:
plt.show()
else:
if onefig:
plt.close()
else:
for i in range(len(self.rivers)):
plt.figure(i)
#plt.clf()
plt.close()
#----------------------------------------------------
# 9.2 - perform some maintenance. remove lines that have NULL entries
colList = ['orig', 'r10pa', 'r15pa', 'r20pa', 'r25pa', 'r30pa', \
'r35pa','r40pa', 'r45pa', 'r50pa', 'r55pa', 'r01pa', \
'r10ap', 'r15ap', 'r20ap', 'r25ap', 'r30ap', 'r35ap', \
'r40ap', 'r45ap', 'r50ap', 'r55ap', 'r01ap']
region = ['amazon','qf','andes']
for reg in region:
for param in ['aspect_compass','slope']:
vect = reg + '_' + param + '_random'
print 'maintenance for vector ' + vect
for col in colList:
# get column from db as a dict
col_dict = gvect.vector_db_select(map=vect, columns=col)['values']
# get cats of NULL entries
null_list = [int(i[1]) for i in col_dict.values() if i[0]=='']
print 'removing NULL entries...'
for n in null_list:
grass.write_command("db.execute", \
stdin="DELETE FROM %s WHERE cat = %d" % (vect,n))
grass.db_describe(vect)
#----------------------------------------------------
# 9.3 - correlation for slope (linear)
# files for results
os.chdir('/Volumes/HDD/Users/guano/Dropbox/artigos/derivadas_dem/stats')
fileOut = open('correlacao_PA_AP_original_slope.txt', 'w')