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#!/usr/bin/env python3
import matplotlib.colors as colors
import matplotlib.pyplot as plt
import numpy as np
import math
import os
with open('./topography.txt', "r") as data:
# while True:
# p = data.tell()
# line = data.readline()
# col1, col2, col3 = line.strip().split()
# if col2 == 'ncols': NXCELL = int(col3) #number of cells in x direction
# if col2 == 'nrows': NYCELL = int(col3) #number of cells in y direction
# if not line.startswith('#'):
# data.seek(p) # go back one line
# break
x, y, z = np.loadtxt(data, delimiter=' ', unpack=True)
xmax = (x[0]+x[-1]) # domain extent in x-direction
ymax = (y[0]+y[-1]) # domain extent in y-direction
NXCELL = int(math.sqrt(len(x)*xmax/ymax)) # number of cells in x-direction
NYCELL = int(len(x)/NXCELL) # number of cells in y-direction
# first reshape to 2-D array then rotate by ninety degrees and flip in
# vertical direction to conform to FullSWOF indexing convention
x_co = np.flipud(np.rot90(np.reshape(x, (NXCELL,NYCELL)))) # x co-ordinates
y_co = np.flipud(np.rot90(np.reshape(y, (NXCELL,NYCELL)))) # y co-ordinates
elev = np.flipud(np.rot90(np.reshape(z, (NXCELL,NYCELL)))) # elevation map
# calculate cell size in x and y directions
DX = x_co[0,1] - x_co[0,0]
DY = y_co[1,0] - y_co[0,0]
#print(DX)
#print(y_co[0])
#plt.plot(x,z, label='elevation')
#plt.xlabel('x / m')
#plt.ylabel('z / m')
# initialize boundary cells
bb = np.zeros((1, NXCELL)) # bottom boundary
tb = np.zeros((1, NXCELL)) # top boundary
lb = np.zeros((1, NYCELL + 2)) # left boundary
rb = np.zeros((1, NYCELL + 2)) # right boundary
# use forward/backward differencing to calculate boundary elevation values
for i in range(0, NXCELL):
bb[0,i] = 2.0*elev[0,i] - elev[1,i]
tb[0,i] = 2.0*elev[NYCELL-1,i] - elev[NYCELL-2,i]
# add boundary cells
z2 = np.concatenate((np.concatenate((bb, elev)), tb))
z3 = np.concatenate((np.concatenate((lb.T, z2), axis=1), rb.T), axis=1)
#print(z2[NYCELL + 1])
#print(z3.shape)
# initialize gradient dz/dy
dzdy = np.zeros((NYCELL, NXCELL))
# use central differencing to calculate nodal values
for i in range(1, NYCELL + 1):
for j in range(1, NXCELL + 1):
dzdy[i-1, j-1] = (z3[i+1, j] - z3[i-1, j])/(2.0*DY)
# array index and co-ordinates are related by:
# index = (co-ord - 0.25)*2
#print("dzdy", dzdy[NYCELL-1, 280:301])
#print("elev", elev[NYCELL-1, 280:301])
xMarker = []
yMarker = []
xch = [] # /pixels
ych = [] # /pixels
zch = [] # /metres
def detach_display():
fig, (ax1,ax2) = plt.subplots(1, 2, sharey='row')
#fig, ax1 = plt.subplots()
left = ax1.imshow(elev,
interpolation='nearest',
origin='lower',
cmap=plt.get_cmap('terrain_r'))
ax1.set_title('elevation / m')
ax1.set_xticks([0, 100, 200, 300, 400, 500])
ax1.plot(xMarker, yMarker, 'ro')
fig.colorbar(left, ax=ax1)
right = ax2.imshow(dzdy,
interpolation='nearest',
origin='lower',
norm=colors.Normalize(vmin=0, vmax=0.1))
ax2.set_title('slope')
ax2.set_xticks([0, 100, 200, 300, 400, 500])
fig.colorbar(right, ax=ax2)
# press a suitable key (one that is not bound already) to mark bank.
def on_key(event):
if event.inaxes is not None:
# print(np.rint(event.xdata).astype(int),
# np.rint(event.ydata).astype(int))
xMarker.append(np.rint(event.xdata).astype(int))
yMarker.append(np.rint(event.ydata).astype(int))
ax1.plot(event.xdata, event.ydata, 'ro')
fig.canvas.draw()
else:
print('Key pressed ouside axes bounds but inside plot window')
# TODO: check xMarker, yMarker have even number of items
# (all left bank and right bank markers are present).
#print(elev.min())
# Note: row-index is plotted vertically, column-index plotted
# horizontally.
#print(np.unravel_index(elev.argmin(), elev.shape))
cid = fig.canvas.callbacks.connect('key_press_event', on_key)
#plt.figure()
plt.show()
fig.canvas.callbacks.disconnect(cid)
#print(xMarker)
def plot_curve():
# sort markers by y value
#yx = list(zip(yMarker, xMarker))
#yx.sort()
#x_sorted = [x for y, x in yx]
#y_sorted = [y for y, x in yx]
#print(x_sorted)
#print(y_sorted)
xch.clear()
ych.clear()
zch.clear()
for i in range(0, len(xMarker), 2):
length = int(np.hypot(xMarker[i+1]-xMarker[i],
yMarker[i+1]-yMarker[i]))
#print(length)
x = np.linspace(xMarker[i+1], xMarker[i], length)
y = np.linspace(yMarker[i+1], yMarker[i], length)
# Extract the values along the line. Note index order: row,
# column.
zi = elev[y.astype(np.intp), x.astype(np.intp)]
# identify minimum value
zch.append(zi.min())
ind = np.unravel_index(zi.argmin(), zi.shape)
xch.append(x[ind].astype(np.intp))
ych.append(y[ind].astype(np.intp))
#print('xch = ', xch[i//2], ' ych = ', ych[i//2], ' zch = ', zch[i//2])
# TODO: Define starting point in channel. Find nearest neighbour to
# starting point. Extract from xch, ych, zch. Create new list with
# extracted point. Find nearest neighbour to extracted point. Extract.
# Add to list. Repeat.
# Fit with polyfit
m, c = np.polyfit([499.75 - y*0.5 for y in ych], zch, 1)
print('gradient =', m, 'intercept =', c)
fig, ax = plt.subplots()
line1, = ax.plot([499.75 - y*0.5 for y in ych], zch)
line2, = ax.plot([499.75 - y*0.5 for y in ych],
[c + m*499.75 - m*y*0.5 for y in ych], '--')
ax.set_xlabel('Distance / m')
ax.set_ylabel('Height / m')
ax.set_title('Channel profile')
#plt.figure()
plt.show()
#fig.clear()
#plt.clf()
#plt.cla()
#plt.close()
#fig.canvas.draw()
#fig.canvas.flush_events()
def save_xyz():
with open('1D.txt', 'w') as f:
for xitem, yitem, zitem in zip(reversed(xch),
reversed(ych),
reversed(zch)):
f.write('{:.2f} {:.2f} {:.4f}\n'.format(0.25+xitem*0.5,
499.75-yitem*0.5,
zitem))
EXIT_COMMAND = "q"
# if os.fork():
# # parent
# pass
# else:
# # child
# detach_display()
#detach_display()
while (True):
input_str = input('Locate markers (m), plot channel profile (p), save profile (s) or exit (q): ')
#print("input_str = {}".format(input_str))
if (input_str == EXIT_COMMAND):
print("End.")
break
elif(input_str == "m"):
detach_display()
elif(input_str == "p"):
plot_curve()
elif(input_str == "s"):
save_xyz()
#print("End.")
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