fullswof-utils: Rename code directory.

* python/makeBoundary: Move to...
* fullswof-utils/makeBoundary: ...here.
* python/slope.py: Move to...
* fullswof-utils/slope.py: ...here.

1 files changed, 0 insertions, 221 deletions

diff --git a/python/slope.py b/python/slope.py
deleted file mode 100755
index e0ca3e1..0000000
--- a/python/slope.py
+++ /dev/null
@@ -1,221 +0,0 @@
-#!/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
-
-    xtp, ytp, ztp = np.loadtxt(data, delimiter=' ', unpack=True)
-
-xmax   = (xtp[0]+xtp[-1])                   # domain extent in x-direction
-ymax   = (ytp[0]+ytp[-1])                   # domain extent in y-direction
-NXCELL = int(math.sqrt(len(xtp)*xmax/ymax)) # number of cells in x-direction
-NYCELL = int(len(xtp)/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(xtp, (NXCELL,NYCELL)))) # x co-ordinates
-y_co = np.flipud(np.rot90(np.reshape(ytp, (NXCELL,NYCELL)))) # y co-ordinates
-elev = np.flipud(np.rot90(np.reshape(ztp, (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)
-# Note: dz/dy index and co-ordinates are related by:
-#            index = int(co-ord/DX - 0.5)
-#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',
-                       cmap=plt.get_cmap('rainbow'))
-                       # norm=colors.Normalize(vmin=0, vmax=0.1))
-    ax2.set_title('slope ($dz/dy$)')
-    # 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(PX):
-    """
-    Fit straight line to channel elevation data.  Pixel size PX is
-    used to convert pixel indices to co-ordinate values.
-    """
-    # 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([(0.5 + y)*PX for y in ych], zch, 1)
-    print('gradient =', m, 'intercept =', c)
-
-    fig, ax = plt.subplots()
-    line1, = ax.plot([(0.5 + y)*PX for y in ych], zch)
-    line2, = ax.plot([(0.5 + y)*PX for y in ych],
-                     [c + m*(0.5 + y)*PX 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(PX):
-    """
-    Write channel elevation data to file.  Pixel size PX is used to
-    convert pixel indices to co-ordinate values.
-    """
-    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((0.5 + xitem)*PX,
-                                                    (0.5 + yitem)*PX,
-                                                    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(DY)
-    elif(input_str == "s"):
-        save_xyz(DY)
-    
-#print("End.")