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Merged
dbrakenhoff merged 15 commits into from
Aug 28, 2026
Merged

Speed up notebook testing with papermill #173

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58f9eeb
add papermill as dependency
martinvonk Aug 20, 2026
e7e8bf1
start with papermill setup
martinvonk Aug 20, 2026
4ba2fbd
add tags to notebooks
martinvonk Aug 20, 2026
0253062
speed up some transient notebooks
martinvonk Aug 20, 2026
fa06a9c
ruff
martinvonk Aug 20, 2026
46063f5
no newfig=False due to attributeerror
martinvonk Aug 20, 2026
b66a0ac
faster collector_wells notebook
martinvonk Aug 20, 2026
781dc11
another slow one
martinvonk Aug 20, 2026
b389492
Merge branch 'dev' into faster_notebook_tests
martinvonk Aug 20, 2026
a089223
add vertical anisotropy notebook
martinvonk Aug 20, 2026
7093c3f
last fixes
martinvonk Aug 20, 2026
82b1355
run notebooks locally
martinvonk Aug 20, 2026
e45f3ec
NGR=101
martinvonk Aug 20, 2026
d40c821
parse solve kwargs
martinvonk Aug 21, 2026
176a27c
clear outputs
martinvonk Aug 21, 2026
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42 changes: 34 additions & 8 deletions docs/steady/02examples/collector_wells.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -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",
Expand Down Expand Up @@ -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",
Expand Down Expand Up @@ -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",
Expand Down Expand Up @@ -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",
Expand Down Expand Up @@ -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",
Expand Down Expand Up @@ -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",
Expand Down Expand Up @@ -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",
Expand All @@ -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",
Expand Down Expand Up @@ -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,
Expand Down
18 changes: 15 additions & 3 deletions docs/steady/02examples/vertical_anisotropy.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -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,
Expand All @@ -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",
Expand Down
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