def Ttime_plot_contourf(self, Ttimes, plotBranch=True, write2shp=False):
"""
function Ttime_plot_contourf is different from function Ttime_plot
This function creates a collection of lines like contourf lines,
so that we can import the contourf lines to ArcGIS for visualization
"""
#### call segment class for plotting
Bthfile = '%s\\%s' % (self.workdir, 'Bth_WB1.npt')
WS = W2_Segmentation(Bthfile)
WS.VisSeg2()
nt = []
for l in Ttimes:
nt.append(len(l))
def travel_time(self, Np, Nt, InitialSeg, starttime, branchID, location_x,
write2shp, density, excelfile):
"""
calculate travel time based on the particle tracking
"""
if branchID == 1:
#### read segment information
WB = W2_Bathymetry(self.Bthfile)
pat = WB.VisBranch2(branchID)
#### create empty array for travel time
Ttime = np.zeros([Np, WB.X.shape[0]])
#### calculate travel time
for i in range(Np):
for tstep in range(Nt):
location_x_tem = location_x[i, tstep]
ind = self.Xsearch(location_x_tem, WB.X)
if tstep == 0:
Ttime[i, InitialSeg - 1:ind + 1] = tstep + 1
ind_tem = ind
else:
ind_nonzero = np.nonzero(Ttime[i, :])[0].max(
) ## only add travel time to zero elements
if ind > max(ind_tem, ind_nonzero):
Ttime[i,
max(ind_tem + 1, ind_nonzero + 1):ind +
1] = tstep + 1
print(Ttime[i, :])
ind_tem = ind
#### calculate the average among particles
#### be careful about this average among particles
#Ttime = np.mean(Ttime, axis=0, dtype=np.int)
#### simply average may yield smaller travel time at the downstream end
#### because some particle may not travel to the last segment, which has zero travel time there
#### so only average among non-zero values.
Ttime_avg = np.zeros([WB.X.shape[0]])
for i in range(WB.X.shape[0]):
if i >= InitialSeg - 1:
Ttime_avg[i] = np.median(Ttime[:, i][np.nonzero(Ttime[:,
i])])
#pdb.set_trace()
Ttime_avg = Ttime_avg[1:-1]
## calculate concentrate/water_level based on the travel time
concentrate, water_level = self.Concentrate_branch1(
Nt, starttime, Ttime_avg)
## calculate distance to WTP gate
dist = self.dist2WTP_branch1(Ttime_avg)
## calculate particle percentage
percentage = self.Percentage_branch1(Np, Nt, starttime, location_x,
Ttime_avg)
Ttime_avg[
Ttime_avg != 0] = Ttime_avg[-1] - Ttime_avg[Ttime_avg != 0]
#### call segment class for segment information
WS = W2_Segmentation(self.Bthfile)
WS.VisSeg2()
#### save travel time data to txt file ####
#self.savetxt_Traveltime_branch1(WS, Ttime_avg, density, self.flows[self.flow_condition], txtfile)
save_excel_Traveltime_branch1(WS, Ttime_avg, density, self.solubility, self.flows[self.flow_condition], \
concentrate, water_level, dist, excelfile)
if write2shp:
from myshapefile import writeShpLines_one_branch
writeShpLines_one_branch(
WS,
Ttime_avg,
shpname='particle_surface_traveltime_branch1')
if branchID == 5:
"""
Under development
"""
#### read segment information for branch 5
WB = W2_Bathymetry(self.Bthfile)
pat = WB.VisBranch2(branchID)
x_branch5 = WB.X #### segment x coordinates for branch 5
#### read segment information for branch 1
WB = W2_Bathymetry(self.Bthfile)
pat = WB.VisBranch2(branchID=1)
x_branch1 = WB.X
#### create empty array for travel time
#### should not include the inactive cell at the end of branch5 when combining
# x_combined = x_branch5.tolist()[0:-1] + \
# (x_branch1[self.DHS5-1:] - x_branch1[self.DHS5-1] + x_branch5[-2]).tolist()
x_combined = x_branch5.tolist()[0:-1] + \
(x_branch1[self.DHS5-1:] - x_branch1[self.DHS5-1] + x_branch5[-2]).tolist()[1:]
x_combined = np.asarray(x_combined)
Ttime = np.zeros([Np, x_combined.shape[0]])
#### calculate travel time
for i in range(Np):
for tstep in range(Nt):
location_x_tem = location_x[i, tstep]
ind = self.Xsearch(location_x_tem, x_combined)
if tstep == 0:
Ttime[i, InitialSeg - 1:ind + 1] = tstep + 1
ind_tem = ind
else:
ind_nonzero = np.nonzero(Ttime[i, :])[0].max(
) ## only add travel time to zero elements
if ind > max(ind_tem, ind_nonzero):
Ttime[i,
max(ind_tem + 1, ind_nonzero + 1):ind +
1] = tstep + 1
print(Ttime[i, :])
ind_tem = ind
#### separate the travel time to branch 1 segments and branch 5 segments
Ttime5 = Ttime[:, 0:len(x_branch5[0:-1]) + 1]
Ttime1 = np.zeros([Np, len(x_branch1)])
#Ttime1[:, self.DHS5:] = Ttime[:, len(x_branch5[0:-1])+1:]
Ttime1[:, self.DHS5:-1] = Ttime[:, len(x_branch5[0:-1]) + 1:]
#pdb.set_trace()
#### calculate the average among particles
Ttime_avg1 = np.zeros([Ttime1.shape[1]])
for i in range(Ttime1.shape[1]):
if i >= self.DHS5 and len(Ttime1[:, i].nonzero()[0]) != 0:
Ttime_avg1[i] = np.median(Ttime1[:,
i][np.nonzero(Ttime1[:,
i])])
Ttime_avg5 = np.zeros([Ttime5.shape[1]])
for i in range(Ttime5.shape[1]):
if i >= InitialSeg - 1:
Ttime_avg5[i] = np.median(Ttime5[:,
i][np.nonzero(Ttime5[:,
i])])
Ttime_avg1 = Ttime_avg1[1:-1]
Ttime_avg5 = Ttime_avg5[1:-1]
Ttimes_avg = [Ttime_avg1, Ttime_avg5]
## calculate concentrate/water level based on the travel time
concentrates, water_levels = self.Concentrate_branch5(
Nt, starttime, Ttimes_avg)
## calculate distance to WTP gate
dists = self.dist2WTP_branch5(Ttimes_avg)
## calculate particle percentage
percentages = self.Percentage_branch5(Np, Nt, starttime,
location_x, x_combined,
Ttimes_avg)
MaxTime = Ttimes_avg[0][-1]
for Ttime in Ttimes_avg:
Ttime[Ttime != 0] = MaxTime - Ttime[Ttime != 0]
#### call segment class for segment information
WS = W2_Segmentation(self.Bthfile)
WS.VisSeg2()
#### save travel time data to txt file ####
#self.savetxt_Traveltime_branch5(WS, Ttimes_avg, density, self.flows[self.flow_condition], txtfile)
save_excel_Traveltime_branch5(WS, Ttimes_avg, density, self.solubility, self.flows[self.flow_condition], \
concentrates, water_levels, dists, excelfile)
if write2shp:
from myshapefile import writeShpLines
writeShpLines(WS,
Ttimes_avg,
shpname='particle_bottom_traveltime_branch5')
def Ttime_plot(self, Ttimes, plotBranch=True, write2shp=False):
"""
Visualize the travel time on W2 segments
multiple lines' color changing the values corresponding to gradient color:
https://stackoverflow.com/questions/55587674/how-to-make-multiple-lines-color-changing-with-values-corresponding-to-gradient
Matplotlib - add colorbar to a sequence of line plots:
https://stackoverflow.com/questions/8342549/matplotlib-add-colorbar-to-a-sequence-of-line-plots
"""
#### call segment class for plotting
WS = W2_Segmentation(self.Bthfile)
WS.VisSeg2()
if self.initialBranch == 1:
## branch 1
MaxTime = Ttimes[0][-1]
Ttime = Ttimes[0]
## conversion to zero travel time at donwstream gate (only on nonzero values)
Ttime[Ttime!=0] = Ttime[-1] - Ttime[Ttime!=0]
#### write to ArcGIS
if write2shp:
self.writeShpLines_one_branch(WS, Ttime, shpname='traveltime_branch1')
#### line color
zz = np.asarray(Ttime)
r = (zz.astype(np.float)-zz.min())/(zz.max()-zz.min())
g = np.zeros_like(r)
b = 1 - r
colorlist = []
for i in range(len(zz)):
colorlist.append((r[i], g[i], b[i]))
#### gray color for zero travel time
for i in range(len(zz)):
if zz[i] == 0:
colorlist[i] = 'gray'
colorlist = []
for i in range(len(zz)):
colorlist.append((r[i], g[i], b[i]))
#### gray color for zero travel time
for i in range(len(zz)):
if zz[i] == 0:
colorlist[i] = 'gray'
#### colorbar: Setting up a colormap that's a simple transtion
mymap = mpl.colors.LinearSegmentedColormap.from_list('mycolors',['blue','red'])
# Using contourf to provide my colorbar info, then clearing the figure
ss = 1
levels = np.arange(zz.min(),zz.max(),ss)
CS3 = plt.contourf([[0,0],[0,0]], levels, cmap=mymap)
plt.clf()
#### matplotlib plotting
plt.rcParams.update({'font.size': 14})
fig = plt.figure(figsize=(10,12))
ax = fig.add_subplot(111)
if plotBranch:
ax.plot(WS.Pnts1[:,0], WS.Pnts1[:,1], '.-', markersize=2, color='0.5')
#### Plot segments
for i in range(len(WS.westPnts1)):
ax.plot([WS.westPnts1[i,0], WS.eastPnts1[i,0]], [WS.westPnts1[i,1], WS.eastPnts1[i,1]], '-', color=colorlist[i])
for i in range(len(WS.segs1)):
if Ttimes[0][i] != 0:
ax.annotate('%s'%str(int(Ttimes[0][i])), (WS.Pnts1[i,0], WS.Pnts1[i,1]), color=colorlist[i], fontsize=8)
elif self.initialBranch == 5:
## branch 5
nt = []
for l in Ttimes:
nt.append(len(l))
MaxTime = Ttimes[0][-1]
for Ttime in Ttimes:
Ttime[Ttime!=0] = MaxTime - Ttime[Ttime!=0]
#### write to ArcGIS
if write2shp:
self.writeShpLines(WS, Ttimes, shpname='traveltime_branch5')
#### line color
zz = np.asarray(Ttimes[0].tolist() + Ttimes[1].tolist())
r = (zz.astype(np.float)-zz.min())/(zz.max()-zz.min())
g = np.zeros_like(r)
b = 1 - r
colorlist = []
for i in range(len(zz)):
colorlist.append((r[i], g[i], b[i]))
#### gray color for zero travel time
for i in range(len(zz)):
if zz[i] == 0:
colorlist[i] = 'gray'
#### colorbar: Setting up a colormap that's a simple transtion
mymap = mpl.colors.LinearSegmentedColormap.from_list('mycolors',['blue','red'])
# Using contourf to provide my colorbar info, then clearing the figure
ss = 1
levels = np.arange(zz.min(),zz.max(),ss)
CS3 = plt.contourf([[0,0],[0,0]], levels, cmap=mymap)
plt.clf()
#### matplotlib plotting
plt.rcParams.update({'font.size': 14})
fig = plt.figure(figsize=(10,12))
ax = fig.add_subplot(111)
if plotBranch:
ax.plot(WS.Pnts1[:,0], WS.Pnts1[:,1], '.-', markersize=2, color='0.5')
ax.plot(WS.Pnts5[:,0], WS.Pnts5[:,1], '.-', markersize=2, color='0.5')
for i in range(len(WS.westPnts1)):
ax.plot([WS.westPnts1[i,0], WS.eastPnts1[i,0]], [WS.westPnts1[i,1], WS.eastPnts1[i,1]], '-', color=colorlist[i])
for i in range(len(WS.westPnts5)):
ax.plot([WS.westPnts5[i,0], WS.eastPnts5[i,0]], [WS.westPnts5[i,1], WS.eastPnts5[i,1]], '-', color=colorlist[i+nt[0]])
#### Plot segments
for i in range(len(WS.segs1)):
if Ttimes[0][i] != 0:
ax.annotate('%s'%str(int(Ttimes[0][i])), (WS.Pnts1[i,0], WS.Pnts1[i,1]), color=colorlist[i], fontsize=8)
for i in range(len(WS.segs5)):
if Ttimes[1][::-1][i] != 0:
ax.annotate('%s'%str(int(Ttimes[1][::-1][i])), (WS.Pnts5[i,0], WS.Pnts5[i,1]), color=colorlist[sum(nt[:])-i-1], fontsize=8)
ax.set_xlabel('Easting [m]')
ax.set_ylabel('Northing [m]')
fig.colorbar(CS3)
ax.set_aspect(True)
fig.tight_layout()
plt.show()
def travel_time_full_branch(self, starttime, initialBranch=1, initialSeg=1, flow_condition='high', write2shp=False, write2txt=True):
"""
call travel time function, and calculate the travel time for all branches: 1 to 5
"""
self.initialBranch = initialBranch
self.initialSeg = initialSeg
#### read conservative tracer file for all branches, so don't need to read the file multiple times
self.Readcpl()
#starttime = 0
#endtime = 149
starttime = starttime
endtime = starttime + 300
#### calculate the travel time for all branches
Ttime1 = self.travel_time(starttime=starttime, endtime=endtime, branchID=1)
#Ttime2 = self.travel_time(endtime=endtime, branchID=2)
#Ttime3 = self.travel_time(endtime=endtime, branchID=3)
#Ttime4 = self.travel_time(endtime=endtime, branchID=4)
Ttime5 = self.travel_time(starttime=starttime, endtime=endtime, branchID=5)
if self.initialBranch == 5:
print ('Spill released at branch 5 \n')
#Ttime1[self.DHS5-2:] += Ttime5[-1]
#### because branch 1 and branch 5 are calculated separate
if Ttime1[self.DHS5] < Ttime5[-2]:
dt_tem = Ttime1[self.DHS5+1] - Ttime1[self.DHS5]
Ttime1[self.DHS5] = Ttime5[-2] + 1
Ttime1[self.DHS5+1] = Ttime1[self.DHS5] + dt_tem
elif self.initialBranch == 1:
print ('Spill released at branch 1 \n')
## delete inactive segments
Ttime1 = Ttime1[1:-1]
#Ttime2 = Ttime2[1:-1]
#Ttime3 = Ttime3[1:-1]
#Ttime4 = Ttime4[1:-1]
Ttime5 = Ttime5[1:-1]
## branch 2, 3, 4, 5, adding time from the main branch
#Ttime2[Ttime2!=0] = Ttime2[Ttime2!=0] - Ttime2[-1] + Ttime1[self.DHS2-2]
#Ttime3[Ttime3!=0] = Ttime3[Ttime3!=0] - Ttime3[-1] + Ttime1[self.DHS3-2]
#Ttime4[Ttime4!=0] = Ttime4[Ttime4!=0] - Ttime4[-1] + Ttime1[self.DHS4-2]
#Ttime5[Ttime5!=0] = Ttime5[Ttime5!=0] - Ttime5[-1] + Ttime1[self.DHS5-2]
## also remember to remove inactivate segments from Ttimes
Ttimes = [Ttime1, Ttime5]
## save to txt file
if write2txt:
#### call segment class for segment information
WS = W2_Segmentation(self.Bthfile)
WS.VisSeg2()
#### save travel time data to txt file ####
if self.initialBranch == 1:
## calculate tracer concentrate based on the travel time
concentrate, water_level = self.Concentrate_branch1(starttime, endtime, Ttimes[0])
## calculate distance to WTP gate
dist = self.dist2WTP_branch1(Ttimes[0])
## conversion to zero travel time at donwstream gate (only on nonzero values)
Ttime = Ttimes[0]
Ttime[Ttime!=0] = Ttime[-1] - Ttime[Ttime!=0]
## save txt
density = 9 ## density information not useful for non-soluble contanminants
#txtfile=r'txt\tracer_branch%s_%s.txt'%(str(self.initialBranch), flow_condition)
#self.savetxt_Traveltime_branch1(WS, Ttime, density, self.flows[flow_condition], concentrate, txtfile)
excelfile=r'excel\tracer_branch%s_%s.xlsx'%(str(self.initialBranch), flow_condition)
save_excel_Traveltime_branch1(WS, Ttime, density, self.solubility, self.flows[flow_condition], concentrate, water_level, dist, excelfile)
elif self.initialBranch == 5:
## calculate tracer concentrate based on the travel time
concentrates, water_levels = self.Concentrate_branch5(starttime, endtime, Ttimes)
## calculate distance to WTP gate
dists = self.dist2WTP_branch5(Ttimes)
## conversion to zero travel time at donwstream gate (only on nonzero values)
MaxTime = Ttimes[0][-1]
for Ttime in Ttimes:
Ttime[Ttime!=0] = MaxTime - Ttime[Ttime!=0]
## save txt
density = 9
#txtfile=r'txt\tracer_branch%s_%s.txt'%(str(self.initialBranch), flow_condition)
#self.savetxt_Traveltime_branch5(WS, Ttimes, density, self.flows[flow_condition], concentrates, txtfile)
excelfile=r'excel\tracer_branch%s_%s.xlsx'%(str(self.initialBranch), flow_condition)
save_excel_Traveltime_branch5(WS, Ttimes, density, self.solubility, self.flows[flow_condition], concentrates, water_levels, dists, excelfile)
self.Ttime_plot(Ttimes, plotBranch=True, write2shp=write2shp)
def Ttime_plot(self, Ttimes, plotBranch=True, write2shp=False):
"""
Visualize the travel time on W2 segments
multiple lines' color changing the values corresponding to gradient color:
https://stackoverflow.com/questions/55587674/how-to-make-multiple-lines-color-changing-with-values-corresponding-to-gradient
Matplotlib - add colorbar to a sequence of line plots:
https://stackoverflow.com/questions/8342549/matplotlib-add-colorbar-to-a-sequence-of-line-plots
"""
#### calculate travel time first
#self.travel_time(endtime=1460, branchID=1)
#### call segment class for plotting
Bthfile = '%s\\%s' % (self.workdir, 'Bth_WB1.npt')
WS = W2_Segmentation(Bthfile)
WS.VisSeg2()
#### create shapefile to integrate with ArcGIS
if write2shp:
self.writeShpLines(WS, Ttimes)
pdb.set_trace()
nt = []
for l in Ttimes:
nt.append(len(l))
#### line color
zz = Ttimes[0].tolist() + Ttimes[1].tolist() + Ttimes[2].tolist(
) + Ttimes[3].tolist() + Ttimes[4].tolist()
zz = np.asarray(zz)
r = (zz.astype(np.float) - zz.min()) / (zz.max() - zz.min())
g = np.zeros_like(r)
b = 1 - r
colorlist = []
for i in range(len(zz)):
colorlist.append((r[i], g[i], b[i]))
# #### black color for zero travel time
for i in range(len(zz)):
if zz[i] == 0:
colorlist[i] = 'gray'
#### colorbar
# Setting up a colormap that's a simple transtion
mymap = mpl.colors.LinearSegmentedColormap.from_list(
'mycolors', ['blue', 'red'])
# Using contourf to provide my colorbar info, then clearing the figure
ss = 1
levels = np.arange(zz.min(), zz.max(), ss)
CS3 = plt.contourf([[0, 0], [0, 0]], levels, cmap=mymap)
plt.clf()
plt.rcParams.update({'font.size': 14})
fig = plt.figure(figsize=(10, 12))
ax = fig.add_subplot(111)
if plotBranch:
ax.plot(WS.Pnts1[:, 0],
WS.Pnts1[:, 1],
'.-',
markersize=2,
color='0.5')
ax.plot(WS.Pnts2[:, 0],
WS.Pnts2[:, 1],
'.-',
markersize=2,
color='0.5')
ax.plot(WS.Pnts3[:, 0],
WS.Pnts3[:, 1],
'.-',
markersize=2,
color='0.5')
ax.plot(WS.Pnts4[:, 0],
WS.Pnts4[:, 1],
'.-',
markersize=2,
color='0.5')
ax.plot(WS.Pnts5[:, 0],
WS.Pnts5[:, 1],
'.-',
markersize=2,
color='0.5')
#### Plot segments
for i in range(len(WS.westPnts1)):
ax.plot([WS.westPnts1[i, 0], WS.eastPnts1[i, 0]],
[WS.westPnts1[i, 1], WS.eastPnts1[i, 1]],
'-',
color=colorlist[i])
for i in range(len(WS.westPnts2)):
ax.plot([WS.westPnts2[i, 0], WS.eastPnts2[i, 0]],
[WS.westPnts2[i, 1], WS.eastPnts2[i, 1]],
'-',
color=colorlist[i + sum(nt[:1])])
for i in range(len(WS.westPnts3)):
ax.plot([WS.westPnts3[i, 0], WS.eastPnts3[i, 0]],
[WS.westPnts3[i, 1], WS.eastPnts3[i, 1]],
'-',
color=colorlist[i + sum(nt[:2])])
for i in range(len(WS.westPnts4)):
ax.plot([WS.westPnts4[i, 0], WS.eastPnts4[i, 0]],
[WS.westPnts4[i, 1], WS.eastPnts4[i, 1]],
'-',
color=colorlist[i + sum(nt[:3])])
for i in range(len(WS.westPnts5)):
ax.plot([WS.westPnts5[i, 0], WS.eastPnts5[i, 0]],
[WS.westPnts5[i, 1], WS.eastPnts5[i, 1]],
'-',
color=colorlist[i + sum(nt[:4])])
#### len(WS.segs1) = 44, segments 2-45
# for i in range(len(WS.segs1)):
# ax.annotate('%s:%s'%(str(WS.segs1[i]),str(int(Ttimes[0][i]))), (WS.Pnts1[i,0], WS.Pnts1[i,1]), color=(r[i],g, b[i]), fontsize=8)
# #ax.annotate('Seg %s, Time=%s'%(str(WS.segs1[i]),str(int(self.Ttime[i+1]))), (WS.Pnts1[i,0], WS.Pnts1[i,1]), color=(r[i],g, b[i]), fontsize=18) ## for zoom plot only
# for i in range(len(WS.segs2)):
# ax.annotate('%s:%s'%(str(WS.segs2[i]),str(int(Ttimes[1][::-1][i]))), (WS.Pnts2[i,0], WS.Pnts2[i,1]), color=(r[i],g, b[i]), fontsize=8)
# for i in range(len(WS.segs3)):
# ax.annotate('%s:%s'%(str(WS.segs3[i]),str(int(Ttimes[2][::-1][i]))), (WS.Pnts3[i,0], WS.Pnts3[i,1]), color=(r[i],g, b[i]), fontsize=8)
# for i in range(len(WS.segs4)):
# ax.annotate('%s:%s'%(str(WS.segs4[i]),str(int(Ttimes[3][::-1][i]))), (WS.Pnts4[i,0], WS.Pnts4[i,1]), color=(r[i],g, b[i]), fontsize=8)
# for i in range(len(WS.segs5)):
# ax.annotate('%s:%s'%(str(WS.segs5[i]),str(int(Ttimes[4][::-1][i]))), (WS.Pnts5[i,0], WS.Pnts5[i,1]), color=(r[i],g, b[i]), fontsize=8)
#### label segment without the segment ID
for i in range(len(WS.segs1)):
if Ttimes[0][i] != 0:
ax.annotate('%s' % str(int(Ttimes[0][i])),
(WS.Pnts1[i, 0], WS.Pnts1[i, 1]),
color=colorlist[i],
fontsize=8)
#ax.annotate('Seg %s, Time=%s'%(str(WS.segs1[i]),str(int(self.Ttime[i+1]))), (WS.Pnts1[i,0], WS.Pnts1[i,1]), color=(r[i],g, b[i]), fontsize=18) ## for zoom plot only
for i in range(len(WS.segs2)):
if Ttimes[1][::-1][i] != 0:
ax.annotate('%s' % str(int(Ttimes[1][::-1][i])),
(WS.Pnts2[i, 0], WS.Pnts2[i, 1]),
color=colorlist[sum(nt[:2]) - i - 1],
fontsize=8)
for i in range(len(WS.segs3)):
if Ttimes[2][::-1][i] != 0:
ax.annotate('%s' % str(int(Ttimes[2][::-1][i])),
(WS.Pnts3[i, 0], WS.Pnts3[i, 1]),
color=colorlist[sum(nt[:3]) - i - 1],
fontsize=8)
for i in range(len(WS.segs4)):
if Ttimes[3][::-1][i] != 0:
ax.annotate('%s' % str(int(Ttimes[3][::-1][i])),
(WS.Pnts4[i, 0], WS.Pnts4[i, 1]),
color=colorlist[sum(nt[:4]) - i - 1],
fontsize=8)
for i in range(len(WS.segs5)):
if Ttimes[4][::-1][i] != 0:
ax.annotate('%s' % str(int(Ttimes[4][::-1][i])),
(WS.Pnts5[i, 0], WS.Pnts5[i, 1]),
color=colorlist[sum(nt[:]) - i - 1],
fontsize=8)
#pdb.set_trace()
ax.set_xlabel('Easting [m]')
ax.set_ylabel('Northing [m]')
fig.colorbar(CS3)
ax.set_aspect(True)
fig.tight_layout()
plt.show()
def VisFinal(self, PlotGrid=True, saveshp=True):
"""
visualize the particle trajectories at a given time step
set PlotTemp == False for now, need to figure out how to contour plot 1D array
"""
self.ReadFinalcsv()
## call the segmentation class to get some information
filename = r'M:\Projects\0326\099-09\2-0 Wrk Prod\Dongyu_work\spill_modeling\particle_tracking_test\20191111_baseline4\Bth_WB1.npt'
WB = W2_Segmentation(filename)
WB.readBathymetry()
x = []
y = []
for i in range(len(self.Part)):
#for i in [0,1,2,3,4,5]:
## for a specific particle
particleID = self.Part[i]
segID = self.Seg[i]
branchID = self.Branch[i]
layerID = self.Layer[i]
laterDist = self.LaterDist[i]
print "Reading particle %s ... \n"%str(particleID)
## search the corresponding seg info
segs = WB.lyrs_segID[WB.lyrs_branchID==branchID]
seg_length = np.asarray(WB.seg_length)[WB.lyrs_branchID==branchID]
seg_ori = np.asarray(WB.seg_ori)[WB.lyrs_branchID==branchID]
lyrs = WB.lyrs[WB.lyrs_branchID==branchID]
## truncate boundary cells
segs = segs[1:-1]
seg_length = seg_length[1:-1]
seg_ori = seg_ori[1:-1]
lyrs = lyrs[1:-1]
## read corresponding seg points info
segs, Pnts= WB.BranchPnt(branchID=branchID)
## goes longitudinal direction
xtem = Pnts[segID-2][0] - self.Xlocation[i]*np.sin(seg_ori[segID-2])
ytem = Pnts[segID-2][1] - self.Xlocation[i]*np.cos(seg_ori[segID-2])
## goes Lateral direction starting from left bank, the left is determined facing downstream, manual page 309
#x.append( xtem + lyrs[segID-2][layerID]/2.*np.cos(np.pi*2-seg_ori[segID-2]) )
#y.append( ytem + lyrs[segID-2][layerID]/2.*np.sin(np.pi*2-seg_ori[segID-2]) )
## This is the left facing upstream
#x.append( xtem - lyrs[segID-2][layerID]/2.*np.cos(np.pi*2-seg_ori[segID-2]) + laterDist*np.cos(np.pi*2-seg_ori[segID-2]) )
#y.append( ytem - lyrs[segID-2][layerID]/2.*np.sin(np.pi*2-seg_ori[segID-2]) + laterDist*np.sin(np.pi*2-seg_ori[segID-2]) )
## This is the left facing downstream
x.append( xtem + lyrs[segID-2][layerID-1]/2.*np.cos(np.pi*2-seg_ori[segID-2]) - laterDist*np.cos(np.pi*2-seg_ori[segID-2]) )
y.append( ytem + lyrs[segID-2][layerID-1]/2.*np.sin(np.pi*2-seg_ori[segID-2]) - laterDist*np.sin(np.pi*2-seg_ori[segID-2]) )
#pdb.set_trace()
if saveshp == True:
self.writeShp(x, y)
plt.rcParams.update({'font.size': 18})
#fig = plt.figure(figsize=(11.5,10))
fig = plt.figure(figsize=(11.5,8))
ax = fig.add_subplot(111)
ax.plot(x, y, '.', color = 'r', markersize=8)
if PlotGrid==True:
WB.VisSeg2()
ax.plot(WB.Pnts1[:,0], WB.Pnts1[:,1], '.-k')
ax.plot(WB.Pnts2[:,0], WB.Pnts2[:,1], '.-b')
ax.plot(WB.Pnts3[:,0], WB.Pnts3[:,1], '.-b')
ax.plot(WB.Pnts4[:,0], WB.Pnts4[:,1], '.-b')
ax.plot(WB.Pnts5[:,0], WB.Pnts5[:,1], '.-b')
for i in range(len(WB.westPnts1)):
ax.plot([WB.westPnts1[i,0], WB.eastPnts1[i,0]], [WB.westPnts1[i,1], WB.eastPnts1[i,1]], '-k')
for i in range(len(WB.westPnts2)):
ax.plot([WB.westPnts2[i,0], WB.eastPnts2[i,0]], [WB.westPnts2[i,1], WB.eastPnts2[i,1]], '-k')
for i in range(len(WB.westPnts3)):
ax.plot([WB.westPnts3[i,0], WB.eastPnts3[i,0]], [WB.westPnts3[i,1], WB.eastPnts3[i,1]], '-k')
for i in range(len(WB.westPnts4)):
ax.plot([WB.westPnts4[i,0], WB.eastPnts4[i,0]], [WB.westPnts4[i,1], WB.eastPnts4[i,1]], '-k')
for i in range(len(WB.westPnts5)):
ax.plot([WB.westPnts5[i,0], WB.eastPnts5[i,0]], [WB.westPnts5[i,1], WB.eastPnts5[i,1]], '-k')
for i in range(len(WB.segs1)):
ax.annotate('%s'%str(WB.segs1[i]), (WB.Pnts1[i,0], WB.Pnts1[i,1]), color='b', fontsize=8)
for i in range(len(WB.segs2)):
ax.annotate('%s'%str(WB.segs2[i]), (WB.Pnts2[i,0], WB.Pnts2[i,1]), color='b', fontsize=8)
for i in range(len(WB.segs3)):
ax.annotate('%s'%str(WB.segs3[i]), (WB.Pnts3[i,0], WB.Pnts3[i,1]), color='b', fontsize=8)
for i in range(len(WB.segs4)):
ax.annotate('%s'%str(WB.segs4[i]), (WB.Pnts4[i,0], WB.Pnts4[i,1]), color='b', fontsize=8)
for i in range(len(WB.segs5)):
ax.annotate('%s'%str(WB.segs5[i]), (WB.Pnts5[i,0], WB.Pnts5[i,1]), color='b', fontsize=8)
#ax.set_xlim([-20000,10000])
ax.set_xlabel('Easting [m]')
ax.set_ylabel('Northing [m]')
ax.set_aspect(True)
plt.show()