From 20ee63f97dc43b346b8940e6840fb1f54d8c73c6 Mon Sep 17 00:00:00 2001 From: arjunsavel Date: Tue, 27 Feb 2024 16:11:30 -0500 Subject: [PATCH] clear optimizing cell output --- docs/pages/optimizing.ipynb | 682 ++---------------------------------- 1 file changed, 21 insertions(+), 661 deletions(-) diff --git a/docs/pages/optimizing.ipynb b/docs/pages/optimizing.ipynb index 78d0df5..b6bce34 100644 --- a/docs/pages/optimizing.ipynb +++ b/docs/pages/optimizing.ipynb @@ -44,23 +44,14 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "id": "465e0289-4f8f-4785-9227-1291fbdd70ca", "metadata": { "pycharm": { "name": "#%%\n" } }, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/arjunsavel/Desktop/research/opac_compress/src/cortecs/opac/io.py:11: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n", - " from tqdm.autonotebook import tqdm\n" - ] - } - ], + "outputs": [], "source": [ "import numpy as np\n", "import random\n", @@ -84,7 +75,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "id": "9d382ad1-9356-41ad-95ec-175be6835eff", "metadata": { "pycharm": { @@ -109,25 +100,14 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "id": "d1d67aca-ae6f-4597-8181-c989d738620c", "metadata": { "pycharm": { "name": "#%%\n" } }, - "outputs": [ - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "fitter = Fitter(opac_obj, method=\"neural_net\")\n", "res = cortecs.fit.fit_neural_net.fit_neural_net(\n", @@ -161,42 +141,14 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": null, "id": "287fa918-89a3-4e35-9839-edcee1167d8d", "metadata": { "pycharm": { "name": "#%%\n" } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "13/13 [==============================] - 0s 536us/step\n" - ] - }, - { - "data": { - "text/plain": [ - "" - ] - }, - "execution_count": 4, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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", 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" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "history, neural_network = res\n", "P_unraveled = unravel_data(fitter.opac.P, fitter.opac.T, None, tileboth=True)\n", @@ -229,7 +181,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "id": "923edfe8-6c3f-4612-9025-9fbfb9ade1a8", "metadata": { "pycharm": { @@ -257,7 +209,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "e193f1ca-4488-4526-95bd-9cb4c72d35d6", "metadata": { "pycharm": { @@ -283,7 +235,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "55ceac04-e41e-489f-8e2d-75862552eb39", "metadata": { "pycharm": { @@ -309,46 +261,14 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "id": "9850ba7d-1ad9-4db4-a53c-004af1f3995d", "metadata": { "pycharm": { "name": "#%%\n" } }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "max number of weights: 546\n", - "max number of layers: 3\n", - "max number of neurons / layer: 13\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Optimizing neural network hyperparameters: 100%|█████████████████████████████████████████████████████████████████████████████████████████████████████| 16/16 [03:23<00:00, 12.74s/it]" - ] - }, - { - "name": "stdout", - "output_type": "stream", - "text": [ - "CPU times: user 3min 51s, sys: 1min, total: 4min 52s\n", - "Wall time: 3min 23s\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "\n" - ] - } - ], + "outputs": [], "source": [ "%%time\n", "optimizer.optimize(max_size, max_evaluations)" @@ -368,25 +288,14 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": null, "id": "ff63a90b-a667-4779-838c-0dcaa918c698", "metadata": { "pycharm": { "name": "#%%\n" } }, - "outputs": [ - { - "data": { - "text/plain": [ - "{'n_layers': 2, 'n_neurons': 13.0, 'activation': 'sigmoid', 'learn_rate': 0.01}" - ] - }, - "execution_count": 9, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ "optimizer.best_params" ] @@ -414,18 +323,10 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "id": "7861078f-6b16-49b6-a5fe-03d033168d4f", "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 4616/4616 [00:00<00:00, 74922.05it/s]\n" - ] - } - ], + "outputs": [], "source": [ "fitter = Fitter(opac_obj, method=\"pca\")\n", "fitter.fit()" @@ -433,7 +334,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "9d498624-012a-4593-a558-ba37bc3c14a6", "metadata": {}, "outputs": [], @@ -443,561 +344,20 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": null, "id": "3099937b-5feb-4d28-adaf-9212631e8858", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "len wl\n", - "4616\n", - "wl range\n", - "[3573 3920 4267 4615]\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "Optimizing PCA hyperparameters: 0%| | 0/16 [00:00