def plot_worker(jobq,mask,pid,lineshape,range):
'''
args[0] = array file name
args[1] = output figure name
if mask, where masked==0 is masked
'''
if lineshape:
lines = shapefile.load_shape_list(lineshape)
else:
lines = None
while True:
#--get some args from the queue
args = jobq.get()
#--check if this is a sentenial
if args == None:
break
#--load
if args[2]:
arr = np.fromfile(args[0],dtype=np.float32)
arr.resize(bro.nrow,bro.ncol)
else:
arr = np.loadtxt(args[0])
if mask != None:
arr = np.ma.masked_where(mask==0,arr)
#print args[0],arr.min(),arr.max(),arr.mean()
#--generic plotting
fig = pylab.figure()
ax = pylab.subplot(1,1,1,aspect='equal')
if range:
vmax = range[1]
vmin = range[0]
else:
vmax = arr.max()
vmin = arr.min()
#p = ax.imshow(arr,interpolation='none')
p = ax.pcolor(bro.X,bro.Y,np.flipud(arr),vmax=vmax,vmin=vmin)
pylab.colorbar(p)
if lines:
for line in lines:
ax.plot(line[0,:],line[1,:],'k-',lw=1.0)
#break
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_xlim(bro.plt_x)
ax.set_ylim(bro.plt_y)
ax.set_title(args[0])
fmt = args[1].split('.')[-1]
pylab.savefig(args[1],dpi=300,format=fmt)
pylab.close(fig)
#--mark this task as done
jobq.task_done()
print 'plot worker',pid,' finished',args[0]
#--mark the sentenial as done
jobq.task_done()
return
def plot_worker(jobq, mask, pid, lineshape, range):
'''
args[0] = array file name
args[1] = output figure name
if mask, where masked==0 is masked
'''
if lineshape:
lines = shapefile.load_shape_list(lineshape)
else:
lines = None
while True:
#--get some args from the queue
args = jobq.get()
#--check if this is a sentenial
if args == None:
break
#--load
if args[2]:
arr = np.fromfile(args[0], dtype=np.float32)
arr.resize(bro.nrow, bro.ncol)
else:
arr = np.loadtxt(args[0])
if mask != None:
arr = np.ma.masked_where(mask == 0, arr)
#print args[0],arr.min(),arr.max(),arr.mean()
#--generic plotting
fig = pylab.figure()
ax = pylab.subplot(1, 1, 1, aspect='equal')
if range:
vmax = range[1]
vmin = range[0]
else:
vmax = arr.max()
vmin = arr.min()
#p = ax.imshow(arr,interpolation='none')
p = ax.pcolor(bro.X, bro.Y, np.flipud(arr), vmax=vmax, vmin=vmin)
pylab.colorbar(p)
if lines:
for line in lines:
ax.plot(line[0, :], line[1, :], 'k-', lw=1.0)
#break
ax.set_xticklabels([])
ax.set_yticklabels([])
ax.set_xlim(bro.plt_x)
ax.set_ylim(bro.plt_y)
ax.set_title(args[0])
fmt = args[1].split('.')[-1]
pylab.savefig(args[1], dpi=300, format=fmt)
pylab.close(fig)
#--mark this task as done
jobq.task_done()
print 'plot worker', pid, ' finished', args[0]
#--mark the sentenial as done
jobq.task_done()
return
def plot_worker(jobq,mask,pid,offset,delta,lineshape,range):
'''
args[0] = array file name
args[1] = output figure name
if mask, where masked==0 is masked
'''
if lineshape:
lines = shapefile.load_shape_list(lineshape)
else:
lines = None
while True:
#--get some args from the queue
args = jobq.get()
#--check if this is a sentenial
if args == None:
break
#--load
arr = np.loadtxt(args[0])
nrow,ncol = arr.shape
x = np.arange(0,ncol*delta,delta) + offset[0]
y = np.arange(0,nrow*delta,delta) + offset[1]
X,Y = np.meshgrid(x,y)
print x.shape,y.shape
if mask != None:
arr = np.ma.masked_where(mask==0,arr)
#print args[0],arr.min(),arr.max(),arr.mean()
#--generic plotting
fig = pylab.figure()
ax = pylab.subplot(111)
#p = ax.pcolor(arr)
if range:
#p = ax.pcolor(X,Y,arr,vmax=range[1],vmin=range[0])
if lines:
for line in lines:
ax.plot(line[:,0],line[:,1],'k-',lw=1.0)
else:
p = ax.imshow(arr,interpolation='none')
#pylab.colorbar(p)
fmt = args[1].split('.')[-1]
pylab.savefig(args[1],dpi=300,format=fmt)
pylab.close(fig)
#--mark this task as done
jobq.task_done()
print 'plot worker',pid,' finished',args[0]
#--mark the sentenial as done
jobq.task_done()
return
#--make sure output directories exist
OutputDir = os.path.join( ResultsDir, 'Figures', 'Zeta' )
umdutils.TestDirExist([os.path.join( ResultsDir,'Figures','dir.tst' ),os.path.join( OutputDir, 'dir.tst' )])
#--default data if command line argument not defined for variable
head_file = os.path.join( ResultsDir, 'UMD.hds' )
zeta_file = os.path.join( ResultsDir, 'UMD.zta' )
#--get available times in the head file
#--zeta surface to extract
zta_text = ' ZETAPLANE 2'
zetaObj = mfb.MODFLOW_CBB(nlay,nrow,ncol,zeta_file)
times = zetaObj.get_time_list(zta_text)
ntimes = times.shape[0]
#--make a map
#--read shapefile to use as base map on figures
shape_name = os.path.join('D:/','Data','Users','jdhughes','GIS','Project Data','2080DBF00','Spatial','FigureData','BaseMap')
hydrography = sf.load_shape_list(shape_name)
salinity_struct_shape_name = os.path.join('D:/','Data','Users','jdhughes','GIS','Project Data','2080DBF00','Spatial','FigureData','SalinityControlStructures')
salinity_struc = sf.load_shape_list(salinity_struct_shape_name)
df_struct_shape_name = os.path.join('D:/','Data','Users','jdhughes','GIS','Project Data','2080DBF00','Spatial','FigureData','DrainageFloodControlStructures')
df_struc = sf.load_shape_list(df_struct_shape_name)
pws_struct_shape_name = os.path.join('D:/','Data','Users','jdhughes','GIS','Project Data','2080DBF00','Spatial','Water Use','pumpwells_lb')
pws = sf.load_shape_list(pws_struct_shape_name)
#--coordinate information
x0, y0 = 539750.0, 2785750.0
dx,dy = 500., 500.
xcell = np.arange(x0+dx/2.,x0+(ncol*dx)+dx/2.0,dx)
ycell = np.arange(y0+dy/2.,y0+(nrow*dy)+dy/2.0,dy)
Xcell,Ycell = np.meshgrid(xcell,ycell)
xedge = np.arange(x0,x0+float(ncol)*dx+0.001,dx)
yedge = np.arange(y0,y0+float(nrow)*dy+0.001,dy)
Xedge,Yedge = np.meshgrid(xedge,yedge)
def main():
#--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()
#--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\\'
#--for ffmpeg - sequentially numbered
plt_num = 1
istart = 0
q_args = []
for i, dt in enumerate(flow.sp_start):
if i >= istart and i % sp_step == 0:
print 'building args list for ', dt
try:
h_seekpoint = long(htimes[i, 3])
except:
break
if zeta_file:
z_seekpoint = long(z1times[i, 3])
else:
z_seekpoint = None
act_lines = []
for ldt, line in zip(line_active, lines):
if ldt <= dt:
act_lines.append(line)
act_wells = []
if i == 0:
plt_start = dt
else:
plt_start = flow.sp_start[i - sp_step]
plt_end = flow.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}.png'.format(plt_num)
#fig_title = 'stress period '+str(i+1)+' start date '+dt.strftime('%d/%m/%Y')
fig_title = str(dt.year)
args = [
fig_name, h_seekpoint, z_seekpoint, act_lines, act_wells,
hds_layer_idx, zta_layer_idx, fig_title
]
q_args.append(args)
plt_num += 1
jobq = mp.JoinableQueue()
#--for testing
#jobq.put_nowait(q_args[0])
#jobq.put_nowait(None)
#plot_worker(jobq,0,head_file,None,hds_elev,zta_elev)
#return
procs = []
num_procs = 6
for i in range(num_procs):
#--pass the woker function jobq and a PID
p = mp.Process(target=plot_worker,
args=(jobq, i, head_file, zeta_file, hds_elev,
zta_elev))
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'
cmd_line = 'ffmpeg.exe -i results\sp%03d.png -r 24 demo.avi -y'
os.system(cmd_line)
return
mpl.rcParams['font.serif'] = 'Times'
mpl.rcParams['font.cursive'] = 'Zapf Chancery'
mpl.rcParams['font.fantasy'] = 'Comic Sans MS'
mpl.rcParams['font.monospace'] = 'Courier New'
mpl.rcParams['pdf.compression'] = 0
mpl.rcParams['pdf.fonttype'] = 42
ticksize = 6
mpl.rcParams['legend.fontsize'] = 6
mpl.rcParams['axes.labelsize'] = 8
mpl.rcParams['xtick.labelsize'] = ticksize
mpl.rcParams['ytick.labelsize'] = ticksize
#--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\\pws_filled_zeros.csv',
index_col=0,
parse_dates=True)
#--load lines and active dates
init_conc = np.zeros_like(botm)
#--process each active cell
for i in range(flow.nrow):
for j in range(flow.ncol):
if ibound[i, j] != 0:
b = botm[:, i, j]
z_elev = z1[i, j]
ic = in_layers(z_elev, b)
init_conc[:, i, j] = ic
for k, lname in enumerate(seawat.layer_botm_names):
aname = seawat.ref_dir + lname + '_srconc.ref'
np.savetxt(aname, init_conc[k, :, :], fmt='%13.5E')
#--plot
imshow_extent = [flow.x[0], flow.x[-1], flow.y[0], flow.y[-1]]
line_shapename = '..\\..\\_gis\shapes\sw_reaches'
lines = shapefile.load_shape_list(line_shapename)
for k in range(seawat.nlay):
fig = pylab.figure()
ax = pylab.subplot(111)
init_lay = init_conc[k, :, :]
init_lay = np.ma.masked_where(init_lay == 0, init_lay)
ax.imshow(init_lay, extent=imshow_extent)
for line in lines:
ax.plot(line[0, :], line[1, :], 'k-', lw=0.25)
l_name = seawat.layer_botm_names[k]
ax.set_title(l_name)
fig_name = 'png\\input\\init_conc_' + l_name + '.png'
pylab.savefig(fig_name, format='png', dpi=500)
def main():
# --load well locations and pandas dataframe
well_shapename = "..\\..\\_gis\\shapes\\pws_combine"
well_points = sf.load_shape_list(well_shapename)
# --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()
# --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\\"
# --for ffmpeg - sequentially numbered
plt_num = 1
istart = 0
q_args = []
for i, dt in enumerate(flow.sp_start):
if i >= istart and i % sp_step == 0:
print "building args list for ", dt
try:
h_seekpoint = long(htimes[i, 3])
except:
break
if zeta_file:
z_seekpoint = long(z1times[i, 3])
else:
z_seekpoint = None
fig_name = plt_dir + "sp{0:03.0f}.png".format(plt_num)
# fig_title = 'stress period '+str(i+1)+' start date '+dt.strftime('%d/%m/%Y')
fig_title = str(dt.year)
args = [fig_name, h_seekpoint, z_seekpoint, lines, well_points, hds_layer_idx, zta_layer_idx, fig_title]
q_args.append(args)
plt_num += 1
jobq = mp.JoinableQueue()
# --for testing
# jobq.put_nowait(q_args[0])
# jobq.put_nowait(None)
# plot_worker(jobq,0,head_file,None,hds_elev,zta_elev)
# 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, head_file, zeta_file, hds_elev, zta_elev))
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"
cmd_line = "ffmpeg.exe -i results\sp%03d.png -r 24 demo.avi -y"
os.system(cmd_line)
return
nlay,nrow,ncol = 3,189,101 #--read ibound ib_ref = os.path.join( '..', 'REF', 'UMD_IBOUND.ref' ) ib = au.loadArrayFromFile(nrow,ncol,ib_ref) #--read initial zetas ref = os.path.join( '..', 'REF', 'UMD_IHEAD_NAVD.ref' ) ihead = au.loadArrayFromFile(nrow,ncol,ref) #--read the top of the model lse_ref = os.path.join( '..', 'REF', 'UMD_URBAN_EDEN_TOPO.ref' ) model_lse = au.loadArrayFromFile(nrow,ncol,lse_ref) #--make a map iweek = 0 #--read shapefile to use as base map on figures shape_name = os.path.join( 'D:/','Data','Users','jdhughes','GIS','Project Data','2080DBF00','Spatial','FigureData','BaseMap' ) print shape_name hydrography = sf.load_shape_list(shape_name) #--coordinate information x0, y0 = 539750.0, 2785750.0 dx,dy = 500., 500. xcell = np.arange(x0+dx/2.,x0+(ncol*dx)+dx/2.0,dx) ycell = np.arange(y0+dy/2.,y0+(nrow*dy)+dy/2.0,dy) Xcell,Ycell = np.meshgrid(xcell,ycell) xedge = np.arange(x0,x0+float(ncol)*dx+0.001,dx) yedge = np.arange(y0,y0+float(nrow)*dy+0.001,dy) Xedge,Yedge = np.meshgrid(xedge,yedge) xmin,xmax = x0,x0+float(ncol)*dx ymin,ymax = y0,y0+float(nrow)*dy #--common data for each figure hdcontour = np.arange(-1.5,2.5,0.5) dtwcontour = np.arange(-5.,5.,1.) #--create figures for each output time
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
z.append(zt)
#--coordinate information
x0, y0 = 539750.0, 2785750.0
dx, dy = 500., 500.
xcell, ycell = mfd.cell_coordinates(nrow, ncol, dx, dy)
xcell += x0
ycell += y0
xedge, yedge = mfd.edge_coordinates(nrow, ncol, dx, dy)
xedge += x0
yedge += y0
xmin, xmax = xedge.min(), xedge.max()
ymin, ymax = yedge.min(), yedge.max()
#--read shapefile with cross-section data
shape_name = os.path.join('..', 'GIS', 'UMDCrossSections')
print shape_name
xsect_list = sf.load_shape_list(shape_name)
shapes, records = sf.load_as_dict(shape_name)
nxsect = len(shapes)
xsect_name = []
xsect_label = []
for idx in xrange(0, nxsect):
xsect_name.append(records['XSECT'][idx].replace(' ', ''))
xsect_label.append(records['Label'][idx])
#--create crossection figures
dxsect = 5.
ifigure = 0
lay_width = [0.5, 0.5, 0.5, 0.5]
lay_color = ['k', 'k', 'k', 'k']
# fresh brackish saltwater
#surf_color = ['#40d3f7','#4E8975','#F76541']
surf_color = ['#40d3f7', '#40d3f7', '#F76541']
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
import pylab
import shapefile
shape_name = 'polylines_active'
lines = shapefile.load_shape_list(shape_name)
fig = pylab.figure()
ax = pylab.subplot(111)
for line in lines:
ax.plot(line[0,:],line[1,:],'k--')
pylab.show()
#--process each active cell
for i in range(flow.nrow):
for j in range(flow.ncol):
if ibound[i,j] != 0:
b = botm[:,i,j]
z_elev = z1[i,j]
ic = in_layers(z_elev,b)
init_conc[:,i,j] = ic
for k,lname in enumerate(seawat.layer_botm_names):
aname = seawat.ref_dir+lname+'_srconc.ref'
np.savetxt(aname,init_conc[k,:,:],fmt='%13.5E')
#--plot
imshow_extent = [flow.x[0],flow.x[-1],flow.y[0],flow.y[-1]]
line_shapename = '..\\..\\_gis\shapes\sw_reaches'
lines = shapefile.load_shape_list(line_shapename)
for k in range(seawat.nlay):
fig = pylab.figure()
ax = pylab.subplot(111)
init_lay = init_conc[k,:,:]
init_lay = np.ma.masked_where(init_lay==0,init_lay)
ax.imshow(init_lay,extent=imshow_extent)
for line in lines:
ax.plot(line[0,:],line[1,:],'k-',lw=0.25)
l_name = seawat.layer_botm_names[k]
ax.set_title(l_name)
fig_name = 'png\\input\\init_conc_'+l_name+'.png'
pylab.savefig(fig_name,format='png',dpi=500)
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
def main():
#--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()
#--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\\'
#--for ffmpeg - sequentially numbered
plt_num = 1
istart = 0
q_args = []
for i,dt in enumerate(flow.sp_start):
if i >= istart and i%sp_step == 0:
print 'building args list for ',dt
try:
h_seekpoint = long(htimes[i,3])
except:
break
if zeta_file:
z_seekpoint = long(z1times[i,3])
else:
z_seekpoint = None
act_lines = []
for ldt,line in zip(line_active,lines):
if ldt <= dt:
act_lines.append(line)
act_wells = []
if i == 0:
plt_start = dt
else:
plt_start = flow.sp_start[i-sp_step]
plt_end = flow.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}.png'.format(plt_num)
#fig_title = 'stress period '+str(i+1)+' start date '+dt.strftime('%d/%m/%Y')
fig_title = str(dt.year)
args = [fig_name,h_seekpoint,z_seekpoint,act_lines,act_wells,hds_layer_idx,zta_layer_idx,fig_title]
q_args.append(args)
plt_num += 1
jobq = mp.JoinableQueue()
#--for testing
#jobq.put_nowait(q_args[0])
#jobq.put_nowait(None)
#plot_worker(jobq,0,head_file,None,hds_elev,zta_elev)
#return
procs = []
num_procs = 6
for i in range(num_procs):
#--pass the woker function jobq and a PID
p = mp.Process(target=plot_worker,args=(jobq,i,head_file,zeta_file,hds_elev,zta_elev))
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'
cmd_line = 'ffmpeg.exe -i results\sp%03d.png -r 24 demo.avi -y'
os.system(cmd_line)
return
z.append( zt )
#--coordinate information
x0, y0 = 539750.0, 2785750.0
dx,dy = 500., 500.
xcell, ycell = mfd.cell_coordinates(nrow,ncol,dx,dy)
xcell += x0
ycell += y0
xedge, yedge = mfd.edge_coordinates(nrow,ncol,dx,dy)
xedge += x0
yedge += y0
xmin,xmax = xedge.min(),xedge.max()
ymin,ymax = yedge.min(),yedge.max()
#--read shapefile with cross-section data
shape_name = os.path.join( '..','GIS','UMDCrossSections' )
print shape_name
xsect_list = sf.load_shape_list(shape_name)
shapes,records = sf.load_as_dict(shape_name)
nxsect = len(shapes)
xsect_name = []
xsect_label = []
for idx in xrange( 0, nxsect ):
xsect_name.append( records['XSECT'][idx].replace(' ','') )
xsect_label.append( records['Label'][idx] )
#--create crossection figures
dxsect = 5.
ifigure = 0
lay_width = [0.5,0.5,0.5,0.5]
lay_color = ['k','k','k','k']
# fresh brackish saltwater
#surf_color = ['#40d3f7','#4E8975','#F76541']
surf_color = ['#40d3f7','#40d3f7','#F76541']
text = ' ET SEGMENTS'
sys.stdout.write('Building time list for...{0}\n'.format(text))
ets_time_list = metObj.get_time_list(text)
text = ' NEXRAD RAINFALL'
sys.stdout.write('Building time list for...{0}\n'.format(text))
rch_time_list = metObj.get_time_list(text)
text = ' SEPTIC RETURN'
sys.stdout.write('Building time list for...{0}\n'.format(text))
sep_time_list = metObj.get_time_list(text)
ntimes = sep_time_list.shape[0]
#--make a map
#--read shapefile to use as base map on figures
shape_name = os.path.join('D:/', 'Data', 'Users', 'jdhughes', 'GIS',
'Project Data', '2080DBF00', 'Spatial', 'FigureData',
'BaseMap')
hydrography = sf.load_shape_list(shape_name)
salinity_struct_shape_name = os.path.join('D:/', 'Data', 'Users', 'jdhughes',
'GIS', 'Project Data', '2080DBF00',
'Spatial', 'FigureData',
'SalinityControlStructures')
salinity_struc = sf.load_shape_list(salinity_struct_shape_name)
df_struct_shape_name = os.path.join('D:/', 'Data', 'Users', 'jdhughes', 'GIS',
'Project Data', '2080DBF00', 'Spatial',
'FigureData',
'DrainageFloodControlStructures')
df_struc = sf.load_shape_list(df_struct_shape_name)
pws_struct_shape_name = os.path.join('D:/', 'Data', 'Users', 'jdhughes', 'GIS',
'Project Data', '2080DBF00', 'Spatial',
'Water Use', 'pumpwells_lb')
pws = sf.load_shape_list(pws_struct_shape_name)
#--coordinate information
def plot_worker(jobq,resultq,mask,pid,lineshape,plot):
'''
args[0] = figure name
args[1] = sp length
args[2] = rch array name
args[3] = ets array name
if mask, where masked==0 is masked
'''
imshow_extent = [flow.x[0],flow.x[-1],flow.y[0],flow.y[-1]]
lines = shapefile.load_shape_list(lineshape)
while True:
#--get some args from the queue
args = jobq.get()
#--check if this is a sentenial
if args == None:
break
#--load rch
rcharr = np.fromfile(args[2],dtype=np.float32)
rcharr.resize(flow.nrow,flow.ncol)
#rcharr *= flow.rch_mult
rcharr = np.ma.masked_where(mask==0,rcharr)
#--load ets
etsarr = np.fromfile(args[3],dtype=np.float32)
etsarr.resize(flow.nrow,flow.ncol)
etsarr /= 25.4
etsarr = np.ma.masked_where(mask==0,etsarr)
ratemax = max(rcharr.max(),etsarr.max())
ratemin = min(rcharr.min(),etsarr.min())
rchdepth = rcharr * args[1]
etsdepth = etsarr * args[1]
results = [args[-1],np.mean(rchdepth),np.max(rchdepth),np.min(rchdepth),np.mean(etsdepth),np.max(etsdepth),np.min(etsdepth)]
resultq.put(results)
depthmax = max(rchdepth.max(),etsdepth.max())
depthmin = min(rchdepth.min(),etsdepth.min())
#--plot
if plot:
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))
fig.text(0.5,0.965,args[0].split('.')[0])
p1 = ax1.imshow(rcharr,extent=imshow_extent,interpolation='none')#,vmax=ratemax,vmin=ratemin)
p2 = ax2.imshow(etsarr,extent=imshow_extent,interpolation='none')#,vmax=ratemax,vmin=ratemin)
p3 = ax3.imshow(rchdepth,extent=imshow_extent,interpolation='none')#,vmax=volmax,vmin=volmin)
p4 = ax4.imshow(rchdepth-etsdepth,extent=imshow_extent,interpolation='none')#,vmax=volmax,vmin=volmin)
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('recharge rate $in/day$')
cb2.set_label('reference ET rate $in/day$')
cb3.set_label('recharge depth $inches$')
cb4.set_label('recharge depth minus ref ET depth $inches$')
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([])
fmt = args[0].split('.')[-1]
pylab.savefig(args[0],dpi=300,format=fmt)
pylab.close(fig)
#--mark this task as done
jobq.task_done()
print 'plot worker',pid,' finished',args[0]
#--mark the sentenial as done
jobq.task_done()
resultq.put(None)
return
mpl.rcParams['font.cursive'] = 'Zapf Chancery'
mpl.rcParams['font.fantasy'] = 'Comic Sans MS'
mpl.rcParams['font.monospace'] = 'Courier New'
mpl.rcParams['pdf.compression'] = 0
mpl.rcParams['pdf.fonttype'] = 42
ticksize = 6
mpl.rcParams['legend.fontsize'] = 6
mpl.rcParams['axes.labelsize'] = 8
mpl.rcParams['xtick.labelsize'] = ticksize
mpl.rcParams['ytick.labelsize'] = ticksize
#--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\\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)
def main():
#--load well locations and pandas dataframe
well_shapename = '..\\..\\_gis\\shapes\\pws_combine'
well_points = sf.load_shape_list(well_shapename)
#--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()
#--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\\'
#--for ffmpeg - sequentially numbered
plt_num = 1
istart = 0
q_args = []
for i, dt in enumerate(flow.sp_start):
if i >= istart and i % sp_step == 0:
print 'building args list for ', dt
try:
h_seekpoint = long(htimes[i, 3])
except:
break
if zeta_file:
z_seekpoint = long(z1times[i, 3])
else:
z_seekpoint = None
fig_name = plt_dir + 'sp{0:03.0f}.png'.format(plt_num)
#fig_title = 'stress period '+str(i+1)+' start date '+dt.strftime('%d/%m/%Y')
fig_title = str(dt.year)
args = [
fig_name, h_seekpoint, z_seekpoint, lines, well_points,
hds_layer_idx, zta_layer_idx, fig_title
]
q_args.append(args)
plt_num += 1
jobq = mp.JoinableQueue()
#--for testing
#jobq.put_nowait(q_args[0])
#jobq.put_nowait(None)
#plot_worker(jobq,0,head_file,None,hds_elev,zta_elev)
#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, head_file, zeta_file, hds_elev,
zta_elev))
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'
cmd_line = 'ffmpeg.exe -i results\sp%03d.png -r 24 demo.avi -y'
os.system(cmd_line)
return
tgf.write( cval )
else:
cval = '% 9i %9i %9i %9.5f %9.3g %s\n' % ( ilay, irow+1, icol+1, te, cond, ctag)
tdf.write( cval )
return True
#--main script
cpath2mod = '..\\..\\UMD.01\\'
KeepAllPng = False
MakeImages = False
MakeMFFiles = False
maxdays = 0
shape_name = 'D:\\Data\\Users\\jdhughes\\GIS\\Project Data\\2080DBF00\\Spatial\\FigureData\\BaseMap'
hydrography = sf.load_shape_list(shape_name)
figuresize = [4.4,6]
#--get command line arguments
narg = len(sys.argv)
iarg = 0
if narg > 1:
while iarg < narg-1:
iarg += 1
basearg = sys.argv[iarg].lower()
if basearg == '-maxdays':
try:
iarg += 1
maxdays = int( sys.argv[iarg] )
print 'command line arg: maxdays = ', maxdays
def plot_worker(jobq, resultq, mask, pid, lineshape, plot):
'''
args[0] = figure name
args[1] = sp length
args[2] = rch array name
args[3] = ets array name
if mask, where masked==0 is masked
'''
imshow_extent = [flow.x[0], flow.x[-1], flow.y[0], flow.y[-1]]
lines = shapefile.load_shape_list(lineshape)
while True:
#--get some args from the queue
args = jobq.get()
#--check if this is a sentenial
if args == None:
break
#--load rch
rcharr = np.fromfile(args[2], dtype=np.float32)
rcharr.resize(flow.nrow, flow.ncol)
#rcharr *= flow.rch_mult
rcharr = np.ma.masked_where(mask == 0, rcharr)
#--load ets
etsarr = np.fromfile(args[3], dtype=np.float32)
etsarr.resize(flow.nrow, flow.ncol)
etsarr /= 25.4
etsarr = np.ma.masked_where(mask == 0, etsarr)
ratemax = max(rcharr.max(), etsarr.max())
ratemin = min(rcharr.min(), etsarr.min())
rchdepth = rcharr * args[1]
etsdepth = etsarr * args[1]
results = [
args[-1],
np.mean(rchdepth),
np.max(rchdepth),
np.min(rchdepth),
np.mean(etsdepth),
np.max(etsdepth),
np.min(etsdepth)
]
resultq.put(results)
depthmax = max(rchdepth.max(), etsdepth.max())
depthmin = min(rchdepth.min(), etsdepth.min())
#--plot
if plot:
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))
fig.text(0.5, 0.965, args[0].split('.')[0])
p1 = ax1.imshow(rcharr, extent=imshow_extent,
interpolation='none') #,vmax=ratemax,vmin=ratemin)
p2 = ax2.imshow(etsarr, extent=imshow_extent,
interpolation='none') #,vmax=ratemax,vmin=ratemin)
p3 = ax3.imshow(rchdepth,
extent=imshow_extent,
interpolation='none') #,vmax=volmax,vmin=volmin)
p4 = ax4.imshow(rchdepth - etsdepth,
extent=imshow_extent,
interpolation='none') #,vmax=volmax,vmin=volmin)
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('recharge rate $in/day$')
cb2.set_label('reference ET rate $in/day$')
cb3.set_label('recharge depth $inches$')
cb4.set_label('recharge depth minus ref ET depth $inches$')
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([])
fmt = args[0].split('.')[-1]
pylab.savefig(args[0], dpi=300, format=fmt)
pylab.close(fig)
#--mark this task as done
jobq.task_done()
print 'plot worker', pid, ' finished', args[0]
#--mark the sentenial as done
jobq.task_done()
resultq.put(None)
return
