update notebook so that it works with latest changes

Author: zsylvester

meanderpy/meanderpy.ipynb

@@ -12,27 +12,6 @@
     "%matplotlib qt"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/plain": [
-       "<module 'meanderpy' from '/Users/zoltan/Dropbox/Channels/meanderpy/meanderpy/meanderpy.py'>"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "from importlib import reload\n",
-    "reload(mp)"
-   ]
-  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -42,29 +21,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
     "nit = 2000                   # number of iterations\n",
     "W = 200.0                    # channel width (m)\n",
     "D = 6.0                      # channel depth (m)\n",
-    "depths = D * np.ones((nit,))  # channel depths for different iterations  \n",
+    "depths = D * np.ones((nit,)) # channel depths for different iterations  \n",
     "pad = 100                    # padding (number of nodepoints along centerline)\n",
     "deltas = 50.0                # sampling distance along centerline           \n",
     "Cfs = 0.011 * np.ones((nit,)) # dimensionless Chezy friction factor\n",
     "crdist = 2 * W               # threshold distance at which cutoffs occur\n",
     "kl = 60.0/(365*24*60*60.0)   # migration rate constant (m/s)\n",
-    "kv =  1.0e-11               # vertical slope-dependent erosion rate constant (m/s)\n",
-    "dt = 2*0.05*365*24*60*60.0     # time step (s)\n",
+    "kv =  1.0e-11                # vertical slope-dependent erosion rate constant (m/s)\n",
+    "dt = 2*0.05*365*24*60*60.0   # time step (s)\n",
     "dens = 1000                  # density of water (kg/m3)\n",
     "saved_ts = 20                # which time steps will be saved\n",
     "n_bends = 30                 # approximate number of bends you want to model\n",
-    "Sl = 0.002                     # initial slope (matters more for submarine channels than rivers)\n",
-    "t1 = 500                    # time step when incision starts\n",
-    "t2 = 700                    # time step when lateral migration starts\n",
+    "Sl = 0.002                   # initial slope (matters more for submarine channels than rivers)\n",
+    "t1 = 500                     # time step when incision starts\n",
+    "t2 = 700                     # time step when lateral migration starts\n",
     "t3 = 1200                    # time step when aggradation starts\n",
-    "aggr_factor = 2e-9         # aggradation factor (m/s, about 0.18 m/year, it kicks in after t3)"
+    "aggr_factor = 2e-9           # aggradation factor (m/s, about 0.18 m/year, it kicks in after t3)"
    ]
   },
   {
@@ -76,7 +55,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -93,14 +72,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|███████████████████████████████████████| 2000/2000 [00:21<00:00, 91.67it/s]\n"
+      "100%|██████████| 2000/2000 [00:16<00:00, 119.93it/s]\n"
      ]
     }
    ],
@@ -111,7 +90,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -130,11 +109,15 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = chb.plot('morph', 20, 60, chb.cl_times[-1], len(chb.channels))"
+    "# pb_age — Age of point bars (in years) at which they get covered by vegetation\n",
+    "# ob_age — Age of oxbow lakes (in years) at which they get covered by vegetation\n",
+    "\n",
+    "fig = chb.plot('morph', pb_age=60, ob_age=100, end_time=chb.cl_times[-1], \n",
+    "                n_channels=len(chb.channels))\n"
    ]
   },
   {
@@ -146,11 +129,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig = chb.plot('age', 20, 60, chb.cl_times[-1], len(chb.channels))"
+    "fig = chb.plot('age', chb.cl_times[-1], len(chb.channels))"
    ]
   },
   {
@@ -162,13 +145,34 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Animation saved to: channel_evolution.mp4\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.animation.FuncAnimation at 0x33baaead0>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "dirname = '/Users/zoltan/Dropbox/Channels/temp/'\n",
-    "chb.create_movie(xmin=10000, xmax=30000, plot_type='strat', filename='movie', dirname=dirname,\n",
-    "                 pb_age = 1, ob_age = 20, end_time = chb.cl_times[-1], n_channels = len(chb.channels))"
+    "# this can take a couple of minutes\n",
+    "# change file extension to .gif to save a file in gif format\n",
+    "# change xmin, xmax to zoom in on a specific area\n",
+    "\n",
+    "chb.create_movie(xmin=10000, xmax=30000, plot_type='strat', \n",
+    "                 filename='channel_evolution.mp4', fps=10, dpi=150)"
    ]
   },
   {
@@ -184,31 +188,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "100%|█████████████████████████████████████████| 100/100 [00:39<00:00,  2.50it/s]"
-     ]
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "43.98457647341001\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "h_mud = 2.0 * np.ones((len(chb.channels),)) # thickness of overbank deposit for each time step\n",
     "dx = 10.0 # gridcell size in meters\n",
@@ -242,14 +224,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 18,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|███████████████████████████████████████| 2000/2000 [00:22<00:00, 90.27it/s]\n"
+      "100%|██████████| 2000/2000 [00:17<00:00, 113.11it/s]\n"
      ]
     }
    ],
@@ -280,19 +262,11 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 27,
+   "execution_count": 19,
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "100%|█████████████████████████████████████████| 100/100 [01:07<00:00,  1.48it/s]\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "# add a bit more incision:\n",
     "for i in range(len(chb.channels)):\n",
@@ -319,14 +293,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 20,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|█████████████████████████████████████████| 100/100 [01:00<00:00,  1.65it/s]\n"
+      "100%|██████████| 100/100 [01:08<00:00,  1.45it/s]\n"
      ]
     }
    ],
@@ -349,7 +323,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 42,
+   "execution_count": 21,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -373,7 +347,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 43,
+   "execution_count": 22,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -383,14 +357,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 44,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|███████████████████████████████████████| 2000/2000 [00:23<00:00, 84.27it/s]\n"
+      "100%|██████████| 2000/2000 [00:18<00:00, 109.57it/s]\n"
      ]
     }
    ],
@@ -409,14 +383,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 45,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "100%|█████████████████████████████████████████| 100/100 [03:21<00:00,  2.01s/it]\n"
+      "  0%|          | 0/100 [00:00<?, ?it/s]/Users/zoltan/Documents/Channels/meanderpy/meanderpy/meanderpy.py:1435: FutureWarning: `square` is deprecated since version 0.25 and will be removed in version 0.27. Use `skimage.morphology.footprint_rectangle` instead.\n",
+      "  img1 = morphology.binary_dilation(img, morphology.square(2)).astype(np.uint8)\n",
+      "100%|██████████| 100/100 [00:56<00:00,  1.78it/s]\n"
      ]
     }
    ],
@@ -435,17 +411,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 47,
+   "execution_count": 26,
    "metadata": {},
    "outputs": [],
    "source": [
-    "fig1,fig2,fig3 = chb_3d.plot_xsection(1000, [[0.9,0.9,0], [0.5,0.25,0]], 10)"
+    "fig1,fig2,fig3 = chb_3d.plot_xsection(400, [[0.9,0.9,0], [0.5,0.25,0]], 10)"
    ]
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "meanderpy",
    "language": "python",
    "name": "python3"
   },
@@ -459,7 +435,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.14.2"
   }
  },
  "nbformat": 4,

meanderpy/meanderpy.py

@@ -1432,15 +1432,15 @@ def dist_map(x, y, z, xmin, xmax, ymin, ymax, dx, delta_s):
     img = np.array(img)
     img = img[:,:,0]
     img[img==255] = 1 
-    img1 = morphology.binary_dilation(img, morphology.square(2)).astype(np.uint8)
+    img1 = morphology.dilation(img, morphology.square(2)).astype(np.uint8)
     if len(np.where(img1==0)[0])>0:
         x_pix, y_pix = eliminate_bad_pixels(img, img1)
         x_pix,y_pix = order_cl_pixels(x_pix, y_pix, img) 
-    img1 = morphology.binary_dilation(img, np.array([[1,0,1], [1,1,1]], dtype=np.uint8)).astype(np.uint8)
+    img1 = morphology.dilation(img, np.array([[1,0,1], [1,1,1]], dtype=np.uint8)).astype(np.uint8)
     if len(np.where(img1==0)[0])>0:
         x_pix, y_pix = eliminate_bad_pixels(img,img1)
         x_pix,y_pix = order_cl_pixels(x_pix, y_pix, img)
-    img1 = morphology.binary_dilation(img, np.array([[1,0,1], [0,1,0], [1,0,1]], dtype=np.uint8)).astype(np.uint8)
+    img1 = morphology.dilation(img, np.array([[1,0,1], [0,1,0], [1,0,1]], dtype=np.uint8)).astype(np.uint8)
     if len(np.where(img1==0)[0])>0:
         x_pix, y_pix = eliminate_bad_pixels(img, img1)
         x_pix,y_pix = order_cl_pixels(x_pix, y_pix, img)