Merge pull request #22 from EdCaunt/notebook_tidyup

examples: tidied up notebooks and examples for paper submission

Author: EdCaunt

examples/10_1st_order_acoustic_sinusoid_hill.ipynb

@@ -7,15 +7,18 @@
    "source": [
     "# 1st-order exact solution comparison\n",
     "\n",
-    "In this notebook, we will compare a solution of the 1st-order acoustic wave equation using an immersed boundary to the previously-used exact solution."
+    "In this notebook, a solution of the 1st-order acoustic wave equation using an immersed boundary is compared to the previously-used exact solution."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 1,
    "id": "5fb0a3a7",
    "metadata": {
-    "scrolled": false
+    "scrolled": false,
+    "tags": [
+     "nbval-ignore-output"
+    ]
    },
    "outputs": [
     {
@@ -205,7 +208,11 @@
    "cell_type": "code",
    "execution_count": 4,
    "id": "6ea21c04",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "nbval-ignore-output"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -257,7 +264,11 @@
    "cell_type": "code",
    "execution_count": 6,
    "id": "db7e40b9",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "nbval-ignore-output"
+    ]
+   },
    "outputs": [
     {
      "data": {
@@ -279,7 +290,9 @@
     "cel_data_full = np.concatenate((cel_data[-5:-1], cel_data, cel_data[1:5]))\n",
     "cel.data[:, :-4] = cel_data_full[:]\n",
     "\n",
-    "plt.imshow(cel.data.T, extent=(-4*grid.spacing[0], 2*np.pi+4*grid.spacing[0], 0, -3*np.pi/4), aspect='auto')\n",
+    "plt.imshow(cel.data.T,\n",
+    "           extent=(-4*grid.spacing[0], 2*np.pi+4*grid.spacing[0],0, -3*np.pi/4),\n",
+    "           aspect='auto')\n",
     "plt.title(\"Celerity field\")\n",
     "plt.colorbar()\n",
     "plt.show()"
@@ -300,7 +313,11 @@
    "cell_type": "code",
    "execution_count": 8,
    "id": "53bb70bd",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "nbval-ignore-output"
+    ]
+   },
    "outputs": [
     {
      "data": {
@@ -365,7 +382,11 @@
    "cell_type": "code",
    "execution_count": 9,
    "id": "e8559026",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "nbval-ignore-output"
+    ]
+   },
    "outputs": [
     {
      "data": {
@@ -484,11 +505,7 @@
       "Generating stencils for Derivative(p(t, x, y), x)\n",
       "Generating stencils for Derivative(p(t, x, y), y)\n",
       "Generating stencils for Derivative(v_x(t + dt, x + h_x/2, y), x)\n",
-      "Support expanded. Remaining =  123\n",
-      "Support expanded. Remaining =  12\n",
-      "Generating stencils for Derivative(v_y(t + dt, x, y + h_y/2), y)\n",
-      "Support expanded. Remaining =  300\n",
-      "Support expanded. Remaining =  24\n"
+      "Generating stencils for Derivative(v_y(t + dt, x, y + h_y/2), y)\n"
      ]
     }
    ],
@@ -610,28 +627,34 @@
    "cell_type": "code",
    "execution_count": 18,
    "id": "924f66fc",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "nbval-ignore-output"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Operator `Kernel` ran in 86.33 s\n"
+      "Operator `Kernel` ran in 93.14 s\n"
      ]
     },
     {
      "data": {
       "text/plain": [
        "PerformanceSummary([(PerfKey(name='section0', rank=None),\n",
-       "                     PerfEntry(time=10.052069999999967, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[])),\n",
+       "                     PerfEntry(time=10.634757999999968, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[])),\n",
        "                    (PerfKey(name='section1', rank=None),\n",
-       "                     PerfEntry(time=0.021199999999998883, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[])),\n",
+       "                     PerfEntry(time=0.02746699999999824, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[])),\n",
        "                    (PerfKey(name='section2', rank=None),\n",
-       "                     PerfEntry(time=76.1822969999998, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[])),\n",
+       "                     PerfEntry(time=0.059053999999997234, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[])),\n",
        "                    (PerfKey(name='section3', rank=None),\n",
-       "                     PerfEntry(time=0.013786999999999834, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[])),\n",
+       "                     PerfEntry(time=82.33782100000003, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[])),\n",
        "                    (PerfKey(name='section4', rank=None),\n",
-       "                     PerfEntry(time=0.04537799999999799, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[]))])"
+       "                     PerfEntry(time=0.015068999999999659, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[])),\n",
+       "                    (PerfKey(name='section5', rank=None),\n",
+       "                     PerfEntry(time=0.05057899999999759, gflopss=0.0, gpointss=0.0, oi=0.0, ops=0, itershapes=[]))])"
       ]
      },
      "execution_count": 18,
@@ -647,7 +670,11 @@
    "cell_type": "code",
    "execution_count": 19,
    "id": "174a4bdf",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "nbval-ignore-output"
+    ]
+   },
    "outputs": [
     {
      "data": {
@@ -676,7 +703,10 @@
    "execution_count": 20,
    "id": "7d898c47",
    "metadata": {
-    "scrolled": false
+    "scrolled": false,
+    "tags": [
+     "nbval-ignore-output"
+    ]
    },
    "outputs": [
     {
@@ -702,7 +732,10 @@
    "execution_count": 21,
    "id": "3e37500a",
    "metadata": {
-    "scrolled": false
+    "scrolled": false,
+    "tags": [
+     "nbval-ignore-output"
+    ]
    },
    "outputs": [
     {
@@ -727,7 +760,11 @@
    "cell_type": "code",
    "execution_count": 22,
    "id": "3891c06c",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "nbval-ignore-output"
+    ]
+   },
    "outputs": [
     {
      "data": {
@@ -780,7 +817,11 @@
    "cell_type": "code",
    "execution_count": 23,
    "id": "9d14ed6a",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "nbval-ignore-output"
+    ]
+   },
    "outputs": [
     {
      "data": {
@@ -805,7 +846,11 @@
    "cell_type": "code",
    "execution_count": 24,
    "id": "2a2011a7",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "nbval-ignore-output"
+    ]
+   },
    "outputs": [
     {
      "data": {
@@ -828,14 +873,19 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 25,
    "id": "80dab0a8",
    "metadata": {},
    "outputs": [],
-   "source": []
+   "source": [
+    "assert np.isclose(np.linalg.norm(p.data), 77.93062)\n",
+    "assert np.isclose(np.linalg.norm(v[0].data), 74.66077)\n",
+    "assert np.isclose(np.linalg.norm(v[1].data), 13.953425)"
+   ]
   }
  ],
  "metadata": {
+  "celltoolbar": "Tags",
   "kernelspec": {
    "display_name": "Python 3 (ipykernel)",
    "language": "python",