From fc4dbfd0a0df9751b19ef2c8a7a7d5794a95b031 Mon Sep 17 00:00:00 2001 From: Younes Strittmatter Date: Fri, 26 Jul 2024 10:37:28 -0400 Subject: [PATCH] feat: always return pandas Dataframe --- docs/Basic Usage.ipynb | 208 ++++++++++++------ .../experimentalist/uncertainty/__init__.py | 12 +- 2 files changed, 142 insertions(+), 78 deletions(-) diff --git a/docs/Basic Usage.ipynb b/docs/Basic Usage.ipynb index 092e4ee..34c53f3 100644 --- a/docs/Basic Usage.ipynb +++ b/docs/Basic Usage.ipynb @@ -10,25 +10,35 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], + "metadata": { + "ExecuteTime": { + "end_time": "2024-07-26T14:36:20.383877Z", + "start_time": "2024-07-26T14:36:20.381224Z" + } + }, "source": [ "# Uncomment the following line when running on Google Colab\n", "# !pip install \"autora[experimentalist-uncertainty]\"" - ] + ], + "outputs": [], + "execution_count": 1 }, { "cell_type": "code", - "execution_count": 25, - "metadata": {}, - "outputs": [], + "metadata": { + "ExecuteTime": { + "end_time": "2024-07-26T14:36:37.960638Z", + "start_time": "2024-07-26T14:36:26.290697Z" + } + }, "source": [ "import numpy as np\n", "import matplotlib.pyplot as plt\n", "from sklearn.linear_model import LogisticRegression\n", "from autora.experimentalist.uncertainty import uncertainty_sample" - ] + ], + "outputs": [], + "execution_count": 2 }, { "attachments": {}, @@ -46,9 +56,12 @@ }, { "cell_type": "code", - "execution_count": 26, - "metadata": {}, - "outputs": [], + "metadata": { + "ExecuteTime": { + "end_time": "2024-07-26T14:36:37.967428Z", + "start_time": "2024-07-26T14:36:37.964437Z" + } + }, "source": [ "#Define meta-parameters\n", "X = np.linspace(start=-3, stop=6, num=10).reshape(-1, 1)\n", @@ -58,7 +71,9 @@ " y = (xs ** 2.0)\n", " y[xs < 0] = 0\n", " return y" - ] + ], + "outputs": [], + "execution_count": 3 }, { "attachments": {}, @@ -72,24 +87,29 @@ }, { "cell_type": "code", - "execution_count": 27, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-07-26T14:36:38.166665Z", + "start_time": "2024-07-26T14:36:37.968499Z" + } + }, + "source": [ + "plt.plot(X, ground_truth(X), 'o')\n", + "plt.show()" + ], "outputs": [ { "data": { - "image/png": "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", "text/plain": [ "
" - ] + ], + "image/png": "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" }, "metadata": {}, "output_type": "display_data" } ], - "source": [ - "plt.plot(X, ground_truth(X), 'o')\n", - "plt.show()" - ] + "execution_count": 4 }, { "attachments": {}, @@ -103,9 +123,12 @@ }, { "cell_type": "code", - "execution_count": 28, - "metadata": {}, - "outputs": [], + "metadata": { + "ExecuteTime": { + "end_time": "2024-07-26T14:36:38.308240Z", + "start_time": "2024-07-26T14:36:38.296036Z" + } + }, "source": [ "%%capture\n", "\n", @@ -114,7 +137,9 @@ "\n", "#Fit theorists\n", "lr_theorist.fit(X,ground_truth(X))" - ] + ], + "outputs": [], + "execution_count": 5 }, { "attachments": {}, @@ -128,25 +153,30 @@ }, { "cell_type": "code", - "execution_count": 29, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-07-26T14:36:42.031313Z", + "start_time": "2024-07-26T14:36:41.976862Z" + } + }, + "source": [ + "plt.plot(X, ground_truth(X), 'o')\n", + "plt.plot(X, lr_theorist.predict(X), alpha = .5)\n", + "plt.show()" + ], "outputs": [ { "data": { - "image/png": "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", "text/plain": [ "
" - ] + ], + "image/png": "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" }, "metadata": {}, "output_type": "display_data" } ], - "source": [ - "plt.plot(X, ground_truth(X), 'o')\n", - "plt.plot(X, lr_theorist.predict(X), alpha = .5)\n", - "plt.show()" - ] + "execution_count": 6 }, { "attachments": {}, @@ -160,45 +190,53 @@ }, { "cell_type": "code", - "execution_count": 30, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-07-26T14:36:44.778569Z", + "start_time": "2024-07-26T14:36:44.758171Z" + } + }, + "source": [ + "sampler_proposal_lc = uncertainty_sample(X, lr_theorist, 5, measure =\"least_confident\")\n", + "sampler_proposal_marg = uncertainty_sample(X, lr_theorist, 5, measure =\"margin\")\n", + "sampler_proposal_ent = uncertainty_sample(X, lr_theorist, 5, measure =\"entropy\")\n", + "\n", + "print('New datapoints with Least Confident metric:\\n' + str(sampler_proposal_lc) + '\\n')\n", + "print('New datapoints with Margin metric:\\n' + str(sampler_proposal_marg) + '\\n')\n", + "print('New datapoints with Entropy metric:\\n' + str(sampler_proposal_ent))" + ], "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "New datapoints with Least Confident metric:\n", - "[[3.]\n", - " [2.]\n", - " [4.]\n", - " [5.]\n", - " [1.]]\n", + " 0\n", + "0 3.0\n", + "1 2.0\n", + "2 4.0\n", + "3 5.0\n", + "4 1.0\n", "\n", "New datapoints with Margin metric:\n", - "[[4.]\n", - " [2.]\n", - " [3.]\n", - " [5.]\n", - " [1.]]\n", + " 0\n", + "0 4.0\n", + "1 2.0\n", + "2 3.0\n", + "3 5.0\n", + "4 1.0\n", "\n", "New datapoints with Entropy metric:\n", - "[[3.]\n", - " [2.]\n", - " [4.]\n", - " [5.]\n", - " [1.]]\n" + " 0\n", + "0 3.0\n", + "1 2.0\n", + "2 4.0\n", + "3 5.0\n", + "4 1.0\n" ] } ], - "source": [ - "sampler_proposal_lc = uncertainty_sample(X, lr_theorist, 5, measure =\"least_confident\")\n", - "sampler_proposal_marg = uncertainty_sample(X, lr_theorist, 5, measure =\"margin\")\n", - "sampler_proposal_ent = uncertainty_sample(X, lr_theorist, 5, measure =\"entropy\")\n", - "\n", - "print('New datapoints with Least Confident metric:\\n' + str(sampler_proposal_lc) + '\\n')\n", - "print('New datapoints with Margin metric:\\n' + str(sampler_proposal_marg) + '\\n')\n", - "print('New datapoints with Entropy metric:\\n' + str(sampler_proposal_ent))" - ] + "execution_count": 7 }, { "attachments": {}, @@ -212,35 +250,59 @@ }, { "cell_type": "code", - "execution_count": 31, - "metadata": {}, + "metadata": { + "ExecuteTime": { + "end_time": "2024-07-26T14:36:46.823638Z", + "start_time": "2024-07-26T14:36:46.713872Z" + } + }, + "source": [ + "plt.plot(X, ground_truth(X), 'o', alpha = .5, label = 'Original Datapoints')\n", + "plt.plot(sampler_proposal_lc, ground_truth(sampler_proposal_lc), 'o', alpha = .5, label = 'Least Confident')\n", + "plt.plot(sampler_proposal_marg, ground_truth(sampler_proposal_marg), 'o', alpha = .5, label = 'Margin')\n", + "plt.plot(sampler_proposal_ent, ground_truth(sampler_proposal_ent), 'o', alpha = .5, label = 'Entropy')\n", + "plt.legend()\n", + "plt.show()" + ], "outputs": [ { "data": { - "image/png": "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", "text/plain": [ "
" - ] + ], + "image/png": "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" }, "metadata": {}, "output_type": "display_data" } ], - "source": [ - "plt.plot(X, ground_truth(X), 'o', alpha = .5, label = 'Original Datapoints')\n", - "plt.plot(sampler_proposal_lc, ground_truth(sampler_proposal_lc), 'o', alpha = .5, label = 'Least Confident')\n", - "plt.plot(sampler_proposal_marg, ground_truth(sampler_proposal_marg), 'o', alpha = .5, label = 'Margin')\n", - "plt.plot(sampler_proposal_ent, ground_truth(sampler_proposal_ent), 'o', alpha = .5, label = 'Entropy')\n", - "plt.legend()\n", - "plt.show()" - ] + "execution_count": 8 + }, + { + "metadata": { + "ExecuteTime": { + "end_time": "2024-07-26T14:36:47.712040Z", + "start_time": "2024-07-26T14:36:47.710655Z" + } + }, + "cell_type": "code", + "source": "", + "outputs": [], + "execution_count": 8 + }, + { + "metadata": {}, + "cell_type": "code", + "outputs": [], + "execution_count": null, + "source": "" } ], "metadata": { "kernelspec": { - "display_name": "autoraKernel", + "display_name": "Python 3 (ipykernel)", "language": "python", - "name": "autorakernel" + "name": "python3" }, "language_info": { "codemirror_mode": { diff --git a/src/autora/experimentalist/uncertainty/__init__.py b/src/autora/experimentalist/uncertainty/__init__.py index 8f8a4b1..baac395 100644 --- a/src/autora/experimentalist/uncertainty/__init__.py +++ b/src/autora/experimentalist/uncertainty/__init__.py @@ -8,10 +8,10 @@ def sample( - conditions: Union[pd.DataFrame, np.ndarray], - model, - num_samples, - measure="least_confident", + conditions: Union[pd.DataFrame, np.ndarray], + model, + num_samples, + measure="least_confident", ): """ @@ -66,7 +66,9 @@ class labels under the model, respectively. new_conditions = X[idx] if isinstance(conditions, pd.DataFrame): - new_conditions = pd.DataFrame(X[idx], columns=conditions.columns) + new_conditions = pd.DataFrame(new_conditions, columns=conditions.columns) + else: + new_conditions = pd.DataFrame(new_conditions) return new_conditions