def extract(iter, kper):
if iter != None:
bak_prefix = seawat.ref_dir + 'bak\\' + str(iter) + '_'
conc_file = 'MT3D001.UCN'
concObj = mfb.MT3D_Concentration(seawat.nlay, seawat.nrow, seawat.ncol,
conc_file)
ctimes = concObj.get_time_list()
init_time = ctimes[np.where(ctimes[:, 2] == kper)][0]
init_seekpoint = long(init_time[-1])
totim, kstp, kper, c, success = concObj.get_array(init_seekpoint)
for k, lay in enumerate(seawat.layer_botm_names):
aname = seawat.ref_dir + 'mod\\sconc_1_' + str(k + 1) + '.ref'
if iter != None:
bakname = bak_prefix + 'sconc_1_' + str(k + 1) + '.ref'
aname2 = seawat.ref_dir + 'sconc_1_' + str(k + 1) + '.ref'
shutil.copy(aname, bakname)
shutil.copy(aname, aname2)
print 'writing ', aname
f = open(aname, 'w', 0)
f.write(toString(c[k, :, :]))
f.close()
print 'head', totim
if success == False:
break
fig = pylab.figure()
ax = pylab.subplot(111, aspect='equal')
p = ax.pcolor(np.flipud(hd[:, xsec_row, :]),
cmap=cmap_heads,
vmin=hd.min(),
vmax=hd.max())
ax.set_yticklabels([])
ax.set_xticklabels([])
cax = pylab.colorbar(p, orientation='horizontal')
cax.ax.set_title('heads ' + str(totim))
axes.append(ax)
if 'c' in plt:
conc_handle = mfb.MT3D_Concentration(nlay, nrow, ncol, 'MT3D001.UCN')
while True:
totim_c, kstp_c, kper_c, c, success = conc_handle.next()
print 'conc', totim_c
if success == False:
break
fig = pylab.figure()
ax = pylab.subplot(111, aspect='equal')
p = ax.pcolor(np.flipud(c[:, xsec_row, :]),
cmap=cmap_conc,
vmin=c.min(),
vmax=c.max())
ax.set_yticklabels([])
ax.set_xticklabels([])
cax = pylab.colorbar(p, orientation='horizontal')
cax.ax.set_title('conc ' + str(totim_c))
def apply():
#--calibration
keyfile = 'misc\\bro.03_calibration_seawatlist.key'
key_well, key_wfield = {}, {}
wconc, wfconc, wfflux, wfmass = {}, {}, {}, {}
f = open(keyfile, 'r')
for line in f:
if 'wel' in line:
raw = line.strip().split()
kij = (int(raw[1]) - 1, int(raw[2]) - 1, int(raw[3]) - 1)
if raw[0] in key_wfield.keys():
if kij not in key_wfield[raw[0]]:
key_wfield[raw[0]].append(kij)
else:
key_wfield[raw[0]] = [kij]
wfconc[raw[0]] = []
wfflux[raw[0]] = []
wfmass[raw[0]] = []
if raw[4] in key_well.keys():
key_well[raw[4]].append(kij)
else:
key_well[raw[4]] = [kij]
wconc[raw[4]] = []
path = 'bro.03\\calibration\\'
cbc_file = path + cal.root + '_wel.cbc'
cbc_obj = mfb.MODFLOW_CBB(cal.nlay, cal.nrow, cal.ncol, cbc_file)
flux_type = ' WELLS'
conc_file = path + 'MT3D001.UCN'
conc_obj = mfb.MT3D_Concentration(cal.nlay, cal.nrow, cal.ncol, conc_file)
dts = []
for itime, end in enumerate(cal.sp_end):
print end, '\r',
ctotim, conc, kstp, kper, csuccess = conc_obj.next()
flux, ftotim, fsuccess = cbc_obj.read_next_fluxtype(flux_type)
if not csuccess:
#raise Exception('Error reading binary file: '+str(conc_file))
break
if not fsuccess:
#raise Exception('Error reading binary file: '+str(cbc_file))
break
if kper != itime + 1:
#raise Exception('cbc kper not the same as loop kper')
break
if ctotim != ftotim:
#raise Exception('cbc totim not the same as conc totim')
break
dts.append(end)
#--individual wells - max concetration at any node for active wells
for wname, kijs in key_well.iteritems():
max_conc, max_flux = 0.0, 0.0
for (k, i, j) in kijs:
cn = conc[k, i, j]
fx = np.abs(flux[k, i, j])
if fx > 0.0 and cn > max_conc:
max_conc = cn
max_flux = fx
if max_flux != 0.0:
wconc[wname].append(max_conc)
else:
wconc[wname].append(np.NaN)
#-- well fields
for wname, kijs in key_wfield.iteritems():
tot_mass, tot_fx = 0.0, 0.0
for (k, i, j) in kijs:
cn = conc[k, i, j]
fx = np.abs(flux[k, i, j])
tot_mass += (cn * fx)
tot_fx += fx
if tot_fx > 0.0:
avg_conc = tot_mass / tot_fx
else:
avg_conc = np.NaN
tot_mass = np.NaN
wfconc[wname].append(avg_conc)
wfflux[wname].append(tot_fx)
wfmass[wname].append(tot_mass)
df_wconc = pandas.DataFrame(wconc, index=dts)
df_wconc.to_csv('calibration_wconc.csv')
df_wfconc = pandas.DataFrame(wfconc, index=dts)
df_wfconc.to_csv('calibration_wfconc.csv')
df_wfmass = pandas.DataFrame(wfmass, index=dts)
df_wfmass.to_csv('calibration_wfmass.csv')
import numpy as np
import MFBinaryClass as mfb
from bro_pred import seawat
'''get initial conditions for seawat model predictive run - heads and zetas
'''
hds_file = '..\\..\\_model\\bro.02\\seawat.hds'
conc_file = '..\\..\\_model\\bro.02\\MT3D001.UCN'
hds_obj = mfb.MODFLOW_Head(seawat.nlay, seawat.nrow, seawat.ncol, hds_file)
conc_obj = mfb.MT3D_Concentration(seawat.nlay, seawat.nrow, seawat.ncol,
conc_file)
htimes = hds_obj.get_time_list()
ctimes = conc_obj.get_time_list()
hseekpoint = long(htimes[-1, 3])
cseekpoint = long(ctimes[-1, 3])
hds_save = seawat.ref_dir + 'strt_'
conc_save = seawat.ref_dir + 'sconc_1_'
htotim, kstp, kper, h, hsuccess = hds_obj.get_array(hseekpoint)
ctotim, ckstp, ckper, c, csuccess = conc_obj.get_array(cseekpoint)
if not hsuccess:
raise Exception('could not extract heads')
if not csuccess:
raise Exception('could not extract zetas')
def plot_worker(jobq, pid, conc_file):
concObj = mfb.MT3D_Concentration(seawat.nlay, seawat.nrow, seawat.ncol,
conc_file)
ctimes = concObj.get_time_list()
while True:
args = jobq.get()
if args == None:
break
'''args[0] = plot name
args[1] = conc seekpoint
args[2] = conc layer to plot
args[3] = active reaches
args[4] = active wells
args[5] = fig_title
'''
fig_name = args[0]
conc_seekpoint = args[1]
lay_idxs = args[2]
lines = args[3]
wells = args[4]
fig_title = args[5]
totim, kstp, kper, c, success = concObj.get_array(conc_seekpoint)
c = np.ma.masked_where(c <= 0.014, c)
fig = pylab.figure(figsize=(8, 8))
ax1 = pylab.axes((0.05, 0.525, 0.45, 0.45))
ax2 = pylab.axes((0.05, 0.055, 0.45, 0.45))
ax3 = pylab.axes((0.525, 0.525, 0.45, 0.45))
ax4 = pylab.axes((0.525, 0.055, 0.45, 0.45))
cax1 = pylab.axes((0.05, 0.53, 0.45, 0.015))
cax2 = pylab.axes((0.05, 0.05, 0.45, 0.015))
cax3 = pylab.axes((0.525, 0.53, 0.45, 0.015))
cax4 = pylab.axes((0.525, 0.05, 0.45, 0.015))
print np.max(c[lay_idxs[1], :, :])
print np.min(c[lay_idxs[1], :, :])
p1 = ax1.imshow(c[lay_idxs[0], :, :],
extent=imshow_extent,
cmap=cmap,
interpolation='none',
vmax=1.0,
vmin=0.0)
p2 = ax2.imshow(c[lay_idxs[1], :, :],
extent=imshow_extent,
cmap=cmap,
interpolation='none',
vmax=1.0,
vmin=0.0)
p3 = ax3.imshow(c[lay_idxs[2], :, :],
extent=imshow_extent,
cmap=cmap,
interpolation='none',
vmax=1.0,
vmin=0.0)
p4 = ax4.imshow(c[lay_idxs[3], :, :],
extent=imshow_extent,
cmap=cmap,
interpolation='none',
vmax=1.0,
vmin=0.0)
cb1 = pylab.colorbar(p1, cax=cax1, orientation='horizontal')
cb2 = pylab.colorbar(p2, cax=cax2, orientation='horizontal')
cb3 = pylab.colorbar(p3, cax=cax3, orientation='horizontal')
cb4 = pylab.colorbar(p4, cax=cax4, orientation='horizontal')
cb1.set_label('Concentration ' + seawat.layer_botm_names[lay_idxs[0]])
cb2.set_label('Concentration ' + seawat.layer_botm_names[lay_idxs[1]])
cb3.set_label('Concentration ' + seawat.layer_botm_names[lay_idxs[2]])
cb4.set_label('Concentration ' + seawat.layer_botm_names[lay_idxs[3]])
ax1.set_ylim(flow.plt_y)
ax1.set_xlim(flow.plt_x)
ax2.set_ylim(flow.plt_y)
ax2.set_xlim(flow.plt_x)
ax3.set_ylim(flow.plt_y)
ax3.set_xlim(flow.plt_x)
ax4.set_ylim(flow.plt_y)
ax4.set_xlim(flow.plt_x)
ax1.set_xticklabels([])
ax3.set_xticklabels([])
ax3.set_yticklabels([])
ax4.set_yticklabels([])
#-- plot active reaches
for line in lines:
ax1.plot(line[0, :], line[1, :], 'k-', lw=0.25)
ax2.plot(line[0, :], line[1, :], 'k-', lw=0.25)
ax3.plot(line[0, :], line[1, :], 'k-', lw=0.25)
ax4.plot(line[0, :], line[1, :], 'k-', lw=0.25)
#-- plot active wells
#for wpoint in wells:
# color=salt_well_color
# if hds_name:
# ax1.plot(wpoint[0],wpoint[1],'.',mfc=color,mec='none',ms=4)
# ax2.plot(wpoint[0],wpoint[1],'.',mfc=color,mec='none',ms=4)
# if zta_name:
# ax3.plot(wpoint[0],wpoint[1],'.',mfc=color,mec='none',ms=4)
# ax4.plot(wpoint[0],wpoint[1],'.',mfc=color,mec='none',ms=4)
for wpoint in wells:
color = 'k'
ax1.plot(wpoint[0], wpoint[1], '.', mfc=color, mec='none', ms=4)
ax2.plot(wpoint[0], wpoint[1], '.', mfc=color, mec='none', ms=4)
ax3.plot(wpoint[0], wpoint[1], '.', mfc=color, mec='none', ms=4)
ax4.plot(wpoint[0], wpoint[1], '.', mfc=color, mec='none', ms=4)
fig.text(0.5, 0.965, fig_title, ha='center')
pylab.savefig(fig_name, dpi=300, format='png', bbox_inches='tight')
pylab.close('all')
print pid, '-- done--', fig_title
jobq.task_done()
jobq.task_done()
return
def main(num_plots):
#--load well locations and pandas dataframe
well_shapename = '..\\..\\_gis\\shapes\\pws_combine'
well_points = sf.load_shape_list(well_shapename)
#shp = sf.reader(well_shapename)
#print sf.get_fieldnames(well_shapename)
records = sf.load_as_dict(well_shapename, loadShapes=False)
well_names = records['DPEP_NAME']
well_zbots = records['zbot']
float_zbots = []
for i, wb in enumerate(well_zbots):
float_zbots.append(float(wb))
well_zbots = np.array(float_zbots)
well_rows, well_cols = records['row'], records['column']
pump = pandas.read_csv(
'..\\..\\_pumpage\\dataframes\\pws_filled_zeros.csv',
index_col=0,
parse_dates=True)
#--load lines and active dates
line_shapename = '..\\..\\_gis\shapes\sw_reaches'
lines = sf.load_shape_list(line_shapename)
shp = sf.Reader(line_shapename)
fnames = sf.get_fieldnames(line_shapename, ignorecase=True)
#for i,fn in enumerate(fnames):
# print i,fn
a_idx = fnames.index('ACTIVE_ST')
line_active = []
for i in range(shp.numRecords):
rec = shp.record(i)
year = int(rec[a_idx])
if year < flow.start.year:
year = flow.start.year
dt = datetime(year=year, month=1, day=1)
line_active.append(dt)
#--head stuff
#--use bot of Q5 to check for dry cells
#hds_elev = np.loadtxt(flow.ref_dir+'Q5_bot.ref')
#hds_layer_idx = 0
#head_file = flow.root+'.hds'
#headObj = mfb.MODFLOW_Head(flow.nlay,flow.nrow,flow.ncol,head_file)
#htimes = headObj.get_time_list()
#--conc stuff
conc_lay_idxs = [0, 5, 9, 11]
conc_file = 'MT3D001.UCN'
concObj = mfb.MT3D_Concentration(seawat.nlay, seawat.nrow, seawat.ncol,
conc_file)
ctimes = concObj.get_time_list()
#--zeta stuff
#zta_layer_idx = 0
#zta_elev = np.loadtxt(flow.ref_dir+'Q1_bot.ref')
#zeta_file = flow.root+'.zta'
#zetaObj = mfb.MODFLOW_CBB(flow.nlay,flow.nrow,flow.ncol,zeta_file)
#zta_text = ' ZETAPLANE 1'
#z1times = zetaObj.get_time_list(zta_text)
#zeta_file = None
#-- stress period step
sp_step = 1
plt_dir = 'png\\results\\seawat\\'
#--for ffmpeg - sequentially numbered
plt_num = 1
istart = 0
q_args = []
for i, [start, end] in enumerate(zip(seawat.sp_start, seawat.sp_end)):
if i >= istart and i % sp_step == 0:
print 'building args list for stress period ending on ', end
#--find the conc output nearest the end of the stress period
try:
kper_seekpoints = ctimes[np.where(ctimes[:, 2] == i + 1), -1]
c_seekpoint = long(kper_seekpoints[0][-1])
except:
break
act_lines = []
for ldt, line in zip(line_active, lines):
if ldt <= start:
act_lines.append(line)
act_wells = []
if i == 0:
plt_start = start
else:
plt_start = seawat.sp_start[i - sp_step]
plt_end = seawat.sp_end[i]
pump_plt = pump[plt_start:plt_end]
pump_plt_sum = pump_plt.sum()
for wname, wpoint, wrow, wcol, wzbot in zip(
well_names, well_points, well_rows, well_cols, well_zbots):
if wname in pump_plt.keys() and pump_plt_sum[wname] != 0:
act_wells.append(wpoint)
fig_name = plt_dir + 'sp{0:03.0f}_conc.png'.format(plt_num)
fig_title = 'stress period ' + str(
i + 1) + ' start date ' + start.strftime('%d/%m/%Y')
args = [
fig_name, c_seekpoint, conc_lay_idxs, act_lines, act_wells,
fig_title
]
q_args.append(args)
plt_num += 1
if num_plots != None and i > num_plots:
break
jobq = mp.JoinableQueue()
#--for testing
if num_plots != None:
jobq.put_nowait(q_args[0])
jobq.put_nowait(None)
plot_worker(jobq, 1, conc_file)
return
procs = []
num_procs = 3
for i in range(num_procs):
#--pass the woker function jobq and a PID
p = mp.Process(target=plot_worker, args=(jobq, i, conc_file))
p.daemon = True
print 'starting process', p.name
p.start()
procs.append(p)
for q in q_args:
jobq.put(q)
for p in procs:
jobq.put(None)
#--block until all finish
for p in procs:
p.join()
print p.name, 'Finished'
anim_name = 'png\\demo_conc.avi'
if os.path.exists(anim_name):
os.remove(anim_name)
cmd_line = 'ffmpeg.exe -i png\\results\\seawat\\sp%03d_conc.png -r 24 ' + anim_name + ' -y'
os.system(cmd_line)
return
def main(num_plots):
#--load well locations and pandas dataframe
well_shapename = '..\\..\\_gis\\shapes\\pws_combine'
well_points = sf.load_shape_list(well_shapename)
#shp = sf.reader(well_shapename)
#print sf.get_fieldnames(well_shapename)
records = sf.load_as_dict(well_shapename, loadShapes=False)
well_names = records['DPEP_NAME']
well_aban = records['ABAN_YEAR']
act_wells = []
for pt, ab in zip(well_points, well_aban):
if ab == '':
act_wells.append(pt)
#--load lines and active dates
line_shapename = '..\\..\\_gis\shapes\sw_reaches'
lines = sf.load_shape_list(line_shapename)
#--head stuff
#--use bot of Q5 to check for dry cells
#hds_elev = np.loadtxt(flow.ref_dir+'Q5_bot.ref')
#hds_layer_idx = 0
#head_file = flow.root+'.hds'
#headObj = mfb.MODFLOW_Head(flow.nlay,flow.nrow,flow.ncol,head_file)
#htimes = headObj.get_time_list()
#--conc stuff
conc_lay_idxs = [0, 2, 3, 4, 5]
conc_file = 'MT3D001.UCN'
concObj = mfb.MT3D_Concentration(seawat.nlay, seawat.nrow, seawat.ncol,
conc_file)
ctimes = concObj.get_time_list()
#-- stress period step
sp_step = 1
plt_dir = 'png\\results\\seawat\\'
#--for ffmpeg - sequentially numbered
plt_num = 1
istart = 0
q_args = []
for i, [start, end] in enumerate(zip(seawat.sp_start, seawat.sp_end)):
if i >= istart and i % sp_step == 0:
print 'building args list for stress period ending on ', end
#--find the conc output nearest the end of the stress period
try:
kper_seekpoints = ctimes[np.where(ctimes[:, 2] == i + 1), -1]
c_seekpoint = long(kper_seekpoints[0][-1])
except:
break
fig_name = plt_dir + 'sp{0:03.0f}_conc.png'.format(plt_num)
fig_title = 'stress period ' + str(
i + 1) + ' start date ' + start.strftime('%d/%m/%Y')
args = [
fig_name, c_seekpoint, conc_lay_idxs, lines, act_wells,
fig_title
]
q_args.append(args)
plt_num += 1
if num_plots != None and i > num_plots:
break
jobq = mp.JoinableQueue()
#--for testing
#if num_plots != None:
# jobq.put_nowait(q_args[0])
# jobq.put_nowait(None)
# plot_worker(jobq,1,conc_file)
# return
procs = []
num_procs = 4
for i in range(num_procs):
#--pass the woker function jobq and a PID
p = mp.Process(target=plot_worker, args=(jobq, i, conc_file))
p.daemon = True
print 'starting process', p.name
p.start()
procs.append(p)
for q in q_args:
jobq.put(q)
for p in procs:
jobq.put(None)
#--block until all finish
for p in procs:
p.join()
print p.name, 'Finished'
anim_name = 'png\\demo_conc.avi'
if os.path.exists(anim_name):
os.remove(anim_name)
cmd_line = 'ffmpeg.exe -i png\\results\\seawat\\sp%03d_conc.png -r 24 ' + anim_name + ' -y'
os.system(cmd_line)
return
import numpy as np
from numpy import ma
import pylab
import MFBinaryClass as mfb
import shapefile
import arrayUtil as au
import bro_info as bi
#nrow,ncol,nlay = 411,501,6
#delr,delc = 500,500
#offset = [728600.0,577350.0,0.0]
#results = 'results\\'
#nreach = 10810
day_2_sec = 1.0 / 86400.0
hds_handle = mfb.MODFLOW_Head(bi.nlay, bi.nrow, bi.ncol,
results + 'bro_6lay.hds')
totim, kstp, kper, h, success = hds_handle.get_record()
conc_handle = mfb.MT3D_Concentration(bi.nlay, bi.nrow, bi.ncol, 'MT3D001.UCN')
totim_c, kstp_c, kper_c, c, success = conc_handle.get_record()
ibound = np.loadtxt('ref\\ibound.ref')
for l in range(bi.nlay):
print 'max conc in layer ' + str(l + 1) + ' :' + str(
c[l, :, :].max()), c[l, :, :].shape
np.savetxt('init_conc_' + str(l + 1) + '.ref', c[l, :, :], fmt='%15.6e')
np.savetxt('init_heads_' + str(l + 1) + '.ref', h[l, :, :], fmt='%15.6e')
