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bartzbeielsteinbartzbeielstein
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v0.8.12
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‎notebooks/testKriging.ipynb‎

Lines changed: 170 additions & 57 deletions
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@@ -986,21 +986,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"S.X: [[0 0]\n",
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" [0 1]\n",
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" [1 0]\n",
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" [1 1]]\n",
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"S.y: [0. 1. 1. 2.]\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from spotPython.fun.objectivefunctions import analytical\n",
@@ -1038,22 +1026,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 23,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"S.X: [[0 0]\n",
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" [0 1]\n",
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" [1 0]\n",
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" [1 1]\n",
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" [1 1]]\n",
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"S.y: [0. 1. 1. 2. 2.]\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from spotPython.fun.objectivefunctions import analytical\n",
@@ -1093,22 +1068,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 29,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"S.X: [[0 0]\n",
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" [0 1]\n",
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" [1 0]\n",
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" [1 1]\n",
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" [1 1]]\n",
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"S.y: [0. 1. 1. 2. 2.]\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from spotPython.fun.objectivefunctions import analytical\n",
@@ -1159,47 +1121,198 @@
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},
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{
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"cell_type": "code",
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"execution_count": 36,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from spotPython.fun.objectivefunctions import analytical\n",
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"from spotPython.spot import spot\n",
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"# number of initial points:\n",
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"ni = 0\n",
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"X_start = np.array([[0, 0], [0, 1], [1, 0], [1, 1], [1, 1]])\n",
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"\n",
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"fun = analytical().fun_sphere\n",
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"lower = np.array([-1, -1])\n",
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"upper = np.array([1, 1])\n",
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"design_control={\"init_size\": ni}\n",
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"\n",
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"S = spot.Spot(fun=fun,\n",
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" noise=False,\n",
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" lower = lower,\n",
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" upper= upper,\n",
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" show_progress=True,\n",
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" design_control=design_control,)\n",
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"S.initialize_design(X_start=X_start)\n",
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"print(f\"S.X: {S.X}\")\n",
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"print(f\"S.y: {S.y}\")\n",
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"S.update_stats()\n",
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"S.fit_surrogate()\n",
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"assert S.surrogate.Psi.shape[0] == S.X.shape[0]\n"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## test update_design()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"from spotPython.fun.objectivefunctions import analytical\n",
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"from spotPython.spot import spot\n",
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"# number of initial points:\n",
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"ni = 0\n",
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"X_start = np.array([[0, 0], [0, 1], [1, 0], [1, 1], [1, 1]])\n",
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"\n",
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"fun = analytical().fun_sphere\n",
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"lower = np.array([-1, -1])\n",
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"upper = np.array([1, 1])\n",
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"design_control={\"init_size\": ni}\n",
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"\n",
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"S = spot.Spot(fun=fun,\n",
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" noise=False,\n",
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" lower = lower,\n",
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" upper= upper,\n",
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" show_progress=True,\n",
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" design_control=design_control,)\n",
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"S.initialize_design(X_start=X_start)\n",
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"print(f\"S.X: {S.X}\")\n",
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"print(f\"S.y: {S.y}\")\n",
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"X_shape_before = S.X.shape\n",
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"print(f\"X_shape_before: {X_shape_before}\")\n",
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"print(f\"y_size_before: {S.y.size}\")\n",
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"y_size_before = S.y.size\n",
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"S.update_stats()\n",
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"S.fit_surrogate()\n",
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"S.update_design()\n",
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"print(f\"S.X: {S.X}\")\n",
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"print(f\"S.y: {S.y}\")\n",
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"print(f\"S.n_points: {S.n_points}\")\n",
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"print(f\"X_shape_after: {S.X.shape}\")\n",
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"print(f\"y_size_after: {S.y.size}\")\n",
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"# compare the shapes of the X and y values before and after the update_design method\n",
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"assert X_shape_before[0] + S.n_points == S.X.shape[0]\n",
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"assert X_shape_before[1] == S.X.shape[1]\n",
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"assert y_size_before + S.n_points == S.y.size"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"metadata": {},
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"outputs": [
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"Seed set to 42\n"
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]
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},
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"S.X: [[0 0]\n",
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" [0 1]\n",
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" [1 0]\n",
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" [1 1]\n",
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" [1 1]]\n",
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"S.y: [0. 1. 1. 2. 2.]\n"
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"S.X: [[ 0. 1. ]\n",
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" [ 1. 0. ]\n",
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" [ 1. 1. ]\n",
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" [ 1. 1. ]\n",
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" [ 0.54509876 -0.36921401]\n",
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" [ 0.54509876 -0.36921401]\n",
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" [ 0.18642675 0.87708546]\n",
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" [ 0.18642675 0.87708546]\n",
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" [-0.45060393 -0.208063 ]\n",
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" [-0.45060393 -0.208063 ]]\n",
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"S.y: [0.98021757 0.99264427 2.02575851 2.00387949 0.45185626 0.44499372\n",
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" 0.79130456 0.81487288 0.24000221 0.23988634]\n",
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"X_shape_before: (10, 2)\n",
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"y_size_before: 10\n",
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"S.X: [[ 0. 1. ]\n",
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" [ 1. 0. ]\n",
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" [ 1. 1. ]\n",
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" [ 1. 1. ]\n",
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" [ 0.54509876 -0.36921401]\n",
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" [ 0.54509876 -0.36921401]\n",
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" [ 0.18642675 0.87708546]\n",
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" [ 0.18642675 0.87708546]\n",
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" [-0.45060393 -0.208063 ]\n",
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" [-0.45060393 -0.208063 ]\n",
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" [-0.45060393 -0.208063 ]\n",
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" [-0.39841465 -0.21105872]\n",
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" [-0.39841465 -0.21105872]]\n",
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"S.y: [0.98021757 0.99264427 2.02575851 2.00387949 0.45185626 0.44499372\n",
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" 0.79130456 0.81487288 0.24000221 0.23988634 0.22655169 0.19592429\n",
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" 0.22903853]\n",
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"S.n_points: 1\n",
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"S.ocba_delta: 1\n",
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"X_shape_after: (13, 2)\n",
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"y_size_after: 13\n"
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]
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/Users/bartz/miniforge3/envs/spotCondaEnv/lib/python3.11/site-packages/spotPython/budget/ocba.py:65: RuntimeWarning: invalid value encountered in cast\n",
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" add_budget = around(add_budget).astype(int)\n"
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]
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}
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],
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"source": [
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"import numpy as np\n",
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"from spotPython.fun.objectivefunctions import analytical\n",
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"from spotPython.spot import spot\n",
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"from spotPython.utils.init import fun_control_init\n",
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"# number of initial points:\n",
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"ni = 0\n",
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"X_start = np.array([[0, 0], [0, 1], [1, 0], [1, 1], [1, 1]])\n",
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"ni = 3\n",
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"X_start = np.array([[0, 1], [1, 0], [1, 1], [1, 1]])\n",
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"\n",
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"fun = analytical().fun_sphere\n",
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"fun_control = fun_control_init(\n",
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" sigma=0.02,\n",
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" seed=123,)\n",
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"lower = np.array([-1, -1])\n",
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"upper = np.array([1, 1])\n",
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"design_control={\"init_size\": ni}\n",
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"design_control={\"init_size\": ni,\n",
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" \"repeats\": 2}\n",
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"\n",
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"S = spot.Spot(fun=fun,\n",
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" noise=False,\n",
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" noise=True,\n",
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" fun_repeats=2,\n",
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" n_points=1,\n",
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" ocba_delta=1,\n",
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" lower = lower,\n",
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" upper= upper,\n",
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" show_progress=True,\n",
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" design_control=design_control,)\n",
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" design_control=design_control,\n",
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" fun_control=fun_control\n",
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")\n",
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"S.initialize_design(X_start=X_start)\n",
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"print(f\"S.X: {S.X}\")\n",
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"print(f\"S.y: {S.y}\")\n",
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"X_shape_before = S.X.shape\n",
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"print(f\"X_shape_before: {X_shape_before}\")\n",
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"print(f\"y_size_before: {S.y.size}\")\n",
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"y_size_before = S.y.size\n",
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"S.update_stats()\n",
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"S.fit_surrogate()\n",
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"assert S.surrogate.Psi.shape[0] == S.X.shape[0]\n"
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"S.update_design()\n",
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"print(f\"S.X: {S.X}\")\n",
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"print(f\"S.y: {S.y}\")\n",
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"print(f\"S.n_points: {S.n_points}\")\n",
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"print(f\"S.ocba_delta: {S.ocba_delta}\")\n",
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"print(f\"X_shape_after: {S.X.shape}\")\n",
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"print(f\"y_size_after: {S.y.size}\")\n",
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"# compare the shapes of the X and y values before and after the update_design method\n",
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"assert X_shape_before[0] + S.n_points * S.fun_repeats + S.ocba_delta == S.X.shape[0]\n",
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"assert X_shape_before[1] == S.X.shape[1]\n",
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"assert y_size_before + S.n_points * S.fun_repeats + S.ocba_delta == S.y.size"
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]
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},
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{

‎pyproject.toml‎

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[project]
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name = "spotPython"
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version = "0.8.11"
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version = "0.8.12"
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authors = [
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{ name="T. Bartz-Beielstein", email="tbb@bartzundbartz.de" }
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]

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