Release v0.5.0

docs/steady/02examples/collector_wells.ipynb

@@ -24,6 +24,20 @@
     "import timflow.steady as tfs"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "5d1e632f",
+   "metadata": {
+    "tags": [
+     "parameters"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "NGR = 101"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "35500d1a-fa15-4e42-8e86-4e2d2a633c79",
@@ -104,7 +118,7 @@
    "source": [
     "ml.plots.contour(\n",
     "    win=[-60, 60, -60, 60],\n",
-    "    ngr=50,\n",
+    "    ngr=NGR,\n",
     "    layers=7,\n",
     "    levels=np.arange(20, 24.1, 0.2),\n",
     "    decimals=1,\n",
@@ -133,7 +147,7 @@
    "source": [
     "ml.plots.contour(\n",
     "    win=[-60, 60, -60, 60],\n",
-    "    ngr=50,\n",
+    "    ngr=NGR,\n",
     "    layers=7,\n",
     "    levels=np.arange(20, 24.1, 0.2),\n",
     "    decimals=1,\n",
@@ -200,7 +214,7 @@
     "ml.solve()\n",
     "ml.plots.contour(\n",
     "    win=[-100, 100, -100, 100],\n",
-    "    ngr=101,\n",
+    "    ngr=NGR,\n",
     "    layers=7,\n",
     "    levels=np.arange(21, 30, 0.5),\n",
     "    decimals=1,\n",
@@ -247,7 +261,7 @@
     "ml.solve()\n",
     "ml.plots.contour(\n",
     "    win=[-100, 100, -100, 100],\n",
-    "    ngr=101,\n",
+    "    ngr=NGR,\n",
     "    layers=7,\n",
     "    levels=np.arange(21, 30, 0.5),\n",
     "    decimals=1,\n",
@@ -284,7 +298,7 @@
     "ml.solve()\n",
     "ml.plots.contour(\n",
     "    win=[-100, 100, -100, 100],\n",
-    "    ngr=101,\n",
+    "    ngr=NGR,\n",
     "    layers=7,\n",
     "    levels=np.arange(21, 30, 0.5),\n",
     "    decimals=1,\n",
@@ -322,7 +336,7 @@
     "# contour in layer 0\n",
     "ax = ml.plots.contour(\n",
     "    win=[-100, 100, -100, 100],\n",
-    "    ngr=101,\n",
+    "    ngr=NGR,\n",
     "    layers=0,\n",
     "    levels=np.arange(21, 30, 0.5),\n",
     "    decimals=1,\n",
@@ -333,7 +347,7 @@
     "# contour in layer 7\n",
     "ax = ml.plots.contour(\n",
     "    win=[-100, 100, -100, 100],\n",
-    "    ngr=101,\n",
+    "    ngr=NGR,\n",
     "    layers=7,\n",
     "    levels=np.arange(21, 30, 0.5),\n",
     "    decimals=1,\n",
@@ -381,9 +395,21 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3",
+   "display_name": "timflow (3.13.x)",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.13.-1"
   }
  },
  "nbformat": 4,

docs/steady/02examples/vertical_anisotropy.ipynb

@@ -169,6 +169,19 @@
     "So 1000 realizations takes on the order of 3000 seconds (on this machine), so around 50 minutes. "
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "tags": [
+     "parameters"
+    ]
+   },
+   "outputs": [],
+   "source": [
+    "NTOT = 1000"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,
@@ -185,10 +198,9 @@
    ],
    "source": [
     "kaq = np.array(80 * [1, 3.16, 10, 31.6, 100])\n",
-    "ntot = 1000\n",
-    "aniso = np.zeros(ntot)\n",
+    "aniso = np.zeros(NTOT)\n",
     "\n",
-    "for i in range(ntot):\n",
+    "for i in range(NTOT):\n",
     "    k = generatek(kaq, nsections=1, seed=i)\n",
     "    h0 = makemodel(k, k)\n",
     "    kx = np.mean(k)\n",

docs/steady/03xsections/cross_section_models.ipynb

@@ -206,7 +206,7 @@
     "\n",
     "ml.solve()\n",
     "\n",
-    "ml.plots.xsection(xy=[(-100, 0), (100, 0)]);"
+    "ax = ml.plots.xsection(xy=[(-100, 0), (100, 0)])"
    ]
   },
   {
@@ -314,6 +314,41 @@
     "ld1.plot(ax);  # plot wall"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plot velocity quiver near the wall."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x = np.linspace(-5, 5, 30)\n",
+    "y = np.array([0])\n",
+    "z = np.array([[4.5, 3.5, 2.5, 1.5, 0.5]]).T\n",
+    "fig, ax = plt.subplots(1, 1, figsize=(10, 3))\n",
+    "ml.plots.xsection(xy=[(x[0], 0), (x[-1], 0)], horizontal_axis=\"x\", labels=False, ax=ax)\n",
+    "\n",
+    "npts = 31\n",
+    "ml.plots.tracelines(\n",
+    "    -5 * np.ones(npts),\n",
+    "    np.zeros(npts),\n",
+    "    np.linspace(0, 5, npts),\n",
+    "    ax=ax,\n",
+    "    linewidth=1,\n",
+    "    hstepmax=1.0,\n",
+    "    vstepfrac=0.1,\n",
+    "    orientation=\"ver\",\n",
+    "    silent=True,\n",
+    ")\n",
+    "ld1.plot(ax)  # plot wall\n",
+    "ml.plots.quiver_z(x, y, z, ax=ax, normalize=True, scale=30, zorder=10);"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -506,13 +541,6 @@
     "ml.solve()"
    ]
   },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
-  },
   {
    "cell_type": "code",
    "execution_count": null,