From 59c443103b4bbb6ef89a6821fd5b6723c96f5f77 Mon Sep 17 00:00:00 2001 From: nmelone Date: Tue, 30 Oct 2018 12:54:50 -0500 Subject: [PATCH] Tweaks and adjustments Added comments everywhere and a new plot in the evaluation portion --- Project Final/Evaluation/Evalutation.ipynb | 253 ++++++++------ .../Preprocessing/preprocess_data.ipynb | 20 +- Project Final/Training/Training.ipynb | 326 +++++++++--------- .../Transformation/Data_Transformation.ipynb | 163 ++++----- 4 files changed, 384 insertions(+), 378 deletions(-) diff --git a/Project Final/Evaluation/Evalutation.ipynb b/Project Final/Evaluation/Evalutation.ipynb index 0969788..94301a8 100644 --- a/Project Final/Evaluation/Evalutation.ipynb +++ b/Project Final/Evaluation/Evalutation.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "metadata": {}, "outputs": [ { @@ -34,18 +34,18 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "metadata": {}, "outputs": [], "source": [ "n_plot = 40\n", - "batch_size = 10\n", + "batch_size = 4\n", "nt = 24" ] }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "metadata": {}, "outputs": [], "source": [ @@ -56,7 +56,24 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "y_labels = [\n", + " 'Visibility',\n", + " 'DB Temp C',\n", + " 'WB Temp C',\n", + " 'Dew Point',\n", + " 'Humidity',\n", + " 'WindSpeed',\n", + " 'Pressure',\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -68,7 +85,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "metadata": {}, "outputs": [], "source": [ @@ -82,7 +99,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "metadata": {}, "outputs": [], "source": [ @@ -100,7 +117,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "metadata": {}, "outputs": [], "source": [ @@ -114,26 +131,11 @@ }, { "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [], - "source": [ - "# Compare MSE of PredNet predictions vs. using last frame. Write results to prediction_scores.txt\n", - "mse_model = np.nanmean( (X_test[:, 1:] - X_hat[:, 1:])**2 ) # look at all timesteps except the first\n", - "mse_prev = np.nanmean( (X_test[:, :-1] - X_test[:, 1:])**2 )\n", - "if not os.path.exists(RESULTS_SAVE_DIR): os.mkdir(RESULTS_SAVE_DIR)\n", - "f = open(RESULTS_SAVE_DIR + 'prediction_scores.txt', 'w')\n", - "f.write(\"Model MSE: %f\\n\" % mse_model)\n", - "f.write(\"Previous Frame MSE: %f\" % mse_prev)\n", - "f.close()" - ] - }, - { - "cell_type": "code", - "execution_count": 31, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ + "#Function used to create the average of the previous 5 frames in a series\n", "def getAverage(test_frames):\n", " blank = np.zeros((20,40,7))\n", " window = [blank * 5]\n", @@ -149,7 +151,7 @@ }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 11, "metadata": {}, "outputs": [], "source": [ @@ -160,14 +162,43 @@ }, { "cell_type": "code", - "execution_count": 34, + "execution_count": 12, + "metadata": {}, + "outputs": [], + "source": [ + "#Used to explore a error in each channel of an image\n", + "per_channel_mse = []\n", + "for i in range(7):\n", + " per_channel_mse.append(np.nanmean((X_test[:,1:,:,:,i] - X_hat[:, 1:,:,:,i])**2))" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "# Compare MSE of PredNet predictions vs. using last frame. Write results to prediction_scores.txt\n", + "mse_model = np.nanmean( (X_test[:, 1:] - X_hat[:, 1:])**2 ) # look at all timesteps except the first\n", + "mse_prev = np.nanmean( (X_test[:, :-1] - X_test[:, 1:])**2 )\n", + "if not os.path.exists(RESULTS_SAVE_DIR): os.mkdir(RESULTS_SAVE_DIR)\n", + "f = open(RESULTS_SAVE_DIR + 'prediction_scores.txt', 'w')\n", + "f.write(\"Model MSE:\\t{}\\n\".format(mse_model))\n", + "f.write(\"Prev Frame MSE:\\t{}\\n\".format(mse_prev))\n", + "f.write(\"Naive MSE:\\t{}\".format(mse_naive))\n", + "f.close()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ - "Model MSE:\t 2.3059108400502737e-07\n", + "Model MSE:\t 1.6844754924250083e-08\n", "Prev Frame MSE:\t 1.0880363277010474e-08\n", "Naive MSE:\t 4.413529927867206e-08\n" ] @@ -179,31 +210,38 @@ }, { "cell_type": "code", - "execution_count": 39, + "execution_count": 15, "metadata": {}, - "outputs": [], + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Visibility MSE:\t 9.868519335043402e-09\n", + "DB Temp C MSE:\t 1.3181296942832432e-08\n", + "WB Temp C MSE:\t 3.7038310196635393e-09\n", + "Dew Point MSE:\t 1.4059031272495304e-08\n", + "Humidity MSE:\t 3.654186286894401e-08\n", + "WindSpeed MSE:\t 3.6026573724257105e-08\n", + "Pressure MSE:\t 4.070736636663241e-09\n" + ] + } + ], "source": [ - "y_labels = [\n", - " 'VISIBILITY',\n", - " 'DB TEMP C',\n", - " 'WB TEMP C',\n", - " 'Dew Point',\n", - " 'Humidity',\n", - " 'WindSpeed',\n", - " 'Pressure',\n", - "]" + "for i in range(7):\n", + " print(\"{} MSE:\\t {}\".format(y_labels[i],per_channel_mse[i]) )" ] }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 15, "metadata": {}, "outputs": [ { "data": { - "image/png": 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\n", 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\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -211,6 +249,7 @@ } ], "source": [ + "#Plot all 7 channels in a column for input image, model predicted image, and naive case image\n", "plt.figure(figsize=(15,10))\n", "grid = gridspec.GridSpec(7, 3)\n", "grid.update(wspace=0., hspace=0.2)\n", @@ -233,71 +272,32 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 19, "metadata": {}, "outputs": [ { "name": "stderr", "output_type": "stream", "text": [ - " 63%|███████████████████████████████████████████████████▉ | 19/30 [09:38<05:35, 30.47s/it]" - ] - } - ], - "source": [ - "# Plot some predictions\n", - "aspect_ratio = float(X_hat.shape[3]) / X_hat.shape[2]\n", - "plt.figure(figsize = (nt, 7*2*aspect_ratio))\n", - "gs = gridspec.GridSpec(2*7, nt)\n", - "gs.update(wspace=0., hspace=0.2)\n", - "plot_save_dir = os.path.join(RESULTS_SAVE_DIR, 'prediction_plots/')\n", - "if not os.path.exists(plot_save_dir): os.mkdir(plot_save_dir)\n", - "plot_idx = np.random.permutation(X_test.shape[0])[:n_plot]\n", - "for i in tqdm(plot_idx):\n", - " for t in range(nt):\n", - " for c in range(7):\n", - " plt.subplot(gs[t + c*2*nt])\n", - " plt.imshow(X_test[i,t,:,:,c], interpolation='none')\n", - " plt.tick_params(axis='both', which='both', bottom='off', top='off', left='off', right='off', labelbottom='off', labelleft='off')\n", - " if t==0: plt.ylabel('Actual', fontsize=10)\n", - "\n", - " plt.subplot(gs[t + (c*2+1)*nt])\n", - " plt.imshow(X_hat[i,t,:,:,c], interpolation='none')\n", - " plt.tick_params(axis='both', which='both', bottom='off', top='off', left='off', right='off', labelbottom='off', labelleft='off')\n", - " if t==0: plt.ylabel('Predicted', fontsize=10)\n", - "\n", - " plt.savefig(plot_save_dir + 'plot_' + str(i) + '.png')\n", - " plt.clf()" - ] - }, - { - "cell_type": "code", - "execution_count": 36, - "metadata": {}, - "outputs": [ - { - "ename": "TypeError", - "evalue": "unhashable type: 'numpy.ndarray'", - "output_type": "error", - "traceback": [ - "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[1;31mTypeError\u001b[0m Traceback (most recent call last)", - "\u001b[1;32m\u001b[0m in \u001b[0;36m\u001b[1;34m()\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mrows\u001b[0m \u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0madd_subplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrows\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 6\u001b[1;33m 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\u001b[0mget_cmap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcmap\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 205\u001b[0m \u001b[1;31m#: The last colorbar associated with this ScalarMappable. May be None.\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 206\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcolorbar\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;32mc:\\users\\dasputer\\appdata\\local\\programs\\python\\python36\\lib\\site-packages\\matplotlib\\cm.py\u001b[0m in \u001b[0;36mget_cmap\u001b[1;34m(name, lut)\u001b[0m\n\u001b[0;32m 159\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 160\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 161\u001b[1;33m \u001b[1;32mif\u001b[0m \u001b[0mname\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mcmap_d\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 162\u001b[0m \u001b[1;32mif\u001b[0m \u001b[0mlut\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 163\u001b[0m \u001b[1;32mreturn\u001b[0m \u001b[0mcmap_d\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", - "\u001b[1;31mTypeError\u001b[0m: unhashable type: 'numpy.ndarray'" + "\n", + " 0%| | 0/40 [00:00" + "" ] }, "metadata": {}, @@ -305,29 +305,58 @@ } ], "source": [ - "fig=plt.figure(figsize=(15,10))\n", - "columns = 3\n", - "rows = 4\n", - "for i in range(1,columns+rows +1):\n", - " fig.add_subplot(rows,columns,i)\n", - " plt.imshow(X_test[0,0,:,:,i-1],X_hat[0,0,:,:,i-1])" + "# Plot full length series of images\n", + "aspect_ratio = float(X_hat.shape[3]) / X_hat.shape[2]\n", + "plt.figure(figsize = (7*2*aspect_ratio,nt))\n", + "gs = gridspec.GridSpec(nt,2*7)\n", + "gs.update(wspace=0.1, hspace=0.)\n", + "plot_save_dir = os.path.join(RESULTS_SAVE_DIR, 'prediction_plots/')\n", + "if not os.path.exists(plot_save_dir): os.mkdir(plot_save_dir)\n", + "plot_idx = np.random.permutation(X_test.shape[0])[:n_plot]\n", + "for i in tqdm(plot_idx):\n", + " for t in range(nt):\n", + " for c in range(7):\n", + " plt.subplot(gs[t*14 + c*2])\n", + " plt.imshow(X_test[i,t,:,:,c], interpolation='none')\n", + " plt.tick_params(axis='both', which='both', bottom='off', top='off', left='off', right='off', labelbottom='off', labelleft='off')\n", + " if t==0: plt.xlabel('Actual', fontsize=10)\n", + "\n", + " plt.subplot(gs[t*14 + (c*2+1)])\n", + " plt.imshow(X_hat[i,t,:,:,c], interpolation='none')\n", + " plt.tick_params(axis='both', which='both', bottom='off', top='off', left='off', right='off', labelbottom='off', labelleft='off')\n", + " if t==0: plt.xlabel('Predicted', fontsize=10)\n", + "\n", + " plt.savefig(plot_save_dir + 'plot_' + str(i) + '.png')\n", + " plt.clf()" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 28, "metadata": {}, - "outputs": [], + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], "source": [ - "X_hat[0][0][0][0][2]" + "#plot difference between actual and predicted images\n", + "plt.figure(figsize=(15,10))\n", + "grid = gridspec.GridSpec(3, 3)\n", + "grid.update(wspace=0.2, hspace=0.2)\n", + "for i in range(7):\n", + " plt.subplot(grid[i])\n", + " plt.imshow(X_test[0,23,:,:,i] - X_hat[0,23,:,:,i],vmin=-1.,vmax=1.)\n", + " plt.ylabel(y_labels[i])\n", + " plt.xlabel('Actual', fontsize=10)" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/Project Final/Preprocessing/preprocess_data.ipynb b/Project Final/Preprocessing/preprocess_data.ipynb index 93fa3fc..277864c 100644 --- a/Project Final/Preprocessing/preprocess_data.ipynb +++ b/Project Final/Preprocessing/preprocess_data.ipynb @@ -1985,7 +1985,7 @@ } ], "source": [ - "#adding back WBAN station since it was absorbed when data was set as the index\n", + "#adding back WBAN station since it was absorbed when date was set as the index\n", "for i in tqdm(range(len(by_station_list))):\n", " by_station_list[i]['STATION'] = wban_list[i] " ] @@ -2062,24 +2062,8 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Current Issues\n", - "\n", - "1) data is not synced across time-zone and all entries start at midnight local time. \n", - "\n", - "2) some stations have multiple entries per hour and need to be reduced.\n", - "\n", - "Solutions\n", - "\n", - "Remove rows from data based on timezone to sync times\n", - "limit only 1 entry per hour for a station" + "All data at this point is ready to be transformed into a grid structure and turned into frames" ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { diff --git a/Project Final/Training/Training.ipynb b/Project Final/Training/Training.ipynb index 59ca17d..9f808cd 100644 --- a/Project Final/Training/Training.ipynb +++ b/Project Final/Training/Training.ipynb @@ -73,9 +73,9 @@ "source": [ "# Training parameters\n", "nb_epoch = 150\n", - "batch_size = 24\n", - "samples_per_epoch = 500\n", - "N_seq_val = 140 # number of sequences to use for validation" + "batch_size = 4\n", + "samples_per_epoch = 100\n", + "N_seq_val = 50 # number of sequences to use for validation" ] }, { @@ -87,11 +87,11 @@ "# Model parameters\n", "n_channels, im_height, im_width = (7, 20, 40)\n", "input_shape = (n_channels, im_height, im_width) if K.image_data_format() == 'channels_first' else (im_height, im_width, n_channels)\n", - "stack_sizes = (n_channels, 48, 96)\n", + "stack_sizes = (n_channels, 12, 24)\n", "R_stack_sizes = stack_sizes\n", - "A_filt_sizes = (3, 3)\n", - "Ahat_filt_sizes = (3, 3, 3)\n", - "R_filt_sizes = (3, 3, 3)\n", + "A_filt_sizes = (2, 2)\n", + "Ahat_filt_sizes = (2, 2, 2)\n", + "R_filt_sizes = (2, 2, 2)\n", "layer_loss_weights = np.array([1., 0., 0.]) # weighting for each layer in final loss; \"L_0\" model: [1, 0, 0, 0], \"L_all\": [1, 0.1, 0.1, 0.1]\n", "layer_loss_weights = np.expand_dims(layer_loss_weights, 1)\n", "nt = 24 # number of timesteps used for sequences in training\n", @@ -139,7 +139,7 @@ "=================================================================\n", "input_1 (InputLayer) (None, 24, 20, 40, 7) 0 \n", "_________________________________________________________________\n", - "pred_net_1 (PredNet) (None, 24, 3) 1621448 \n", + "pred_net_1 (PredNet) (None, 24, 3) 49167 \n", "_________________________________________________________________\n", "time_distributed_1 (TimeDist (None, 24, 1) 4 \n", "_________________________________________________________________\n", @@ -147,8 +147,8 @@ "_________________________________________________________________\n", "dense_2 (Dense) (None, 1) 25 \n", "=================================================================\n", - "Total params: 1,621,477\n", - "Trainable params: 1,621,448\n", + "Total params: 49,196\n", + "Trainable params: 49,167\n", "Non-trainable params: 29\n", "_________________________________________________________________\n" ] @@ -191,305 +191,311 @@ "output_type": "stream", "text": [ "Epoch 1/150\n", - " - 21s - loss: 0.9718 - val_loss: 0.9142\n", + " - 18s - loss: 2.2654e-04 - val_loss: 1.6606e-04\n", "Epoch 2/150\n", - " - 15s - loss: 0.9089 - val_loss: 0.8895\n", + " - 13s - loss: 1.6084e-04 - val_loss: 1.6482e-04\n", "Epoch 3/150\n", - " - 15s - loss: 0.9057 - val_loss: 0.8826\n", + " - 13s - loss: 1.6346e-04 - val_loss: 1.5707e-04\n", "Epoch 4/150\n", - " - 15s - loss: 0.8905 - val_loss: 0.8765\n", + " - 14s - loss: 1.5891e-04 - val_loss: 1.5682e-04\n", "Epoch 5/150\n", - " - 15s - loss: 0.9106 - val_loss: 0.8840\n", + " - 15s - loss: 1.5410e-04 - val_loss: 1.4740e-04\n", "Epoch 6/150\n", - " - 15s - loss: 0.8812 - val_loss: 0.8749\n", + " - 13s - loss: 1.3540e-04 - val_loss: 1.4354e-04\n", "Epoch 7/150\n", - " - 15s - loss: 0.9099 - val_loss: 0.8897\n", + " - 14s - loss: 1.4448e-04 - val_loss: 1.2114e-04\n", "Epoch 8/150\n", - " - 15s - loss: 0.8829 - val_loss: 0.8711\n", + " - 13s - loss: 1.3061e-04 - val_loss: 1.5603e-04\n", "Epoch 9/150\n", - " - 15s - loss: 0.9039 - val_loss: 0.8843\n", + " - 13s - loss: 1.2790e-04 - val_loss: 1.6199e-04\n", "Epoch 10/150\n", - " - 15s - loss: 0.8814 - val_loss: 0.8696\n", + " - 13s - loss: 1.2041e-04 - val_loss: 1.2755e-04\n", "Epoch 11/150\n", - " - 15s - loss: 0.8897 - val_loss: 0.8881\n", + " - 13s - loss: 1.2834e-04 - val_loss: 1.3263e-04\n", "Epoch 12/150\n", - " - 15s - loss: 0.8803 - val_loss: 0.8696\n", + " - 13s - loss: 1.3211e-04 - val_loss: 1.3543e-04\n", "Epoch 13/150\n", - " - 15s - loss: 0.8819 - val_loss: 0.8836\n", + " - 13s - loss: 1.2578e-04 - val_loss: 1.2785e-04\n", "Epoch 14/150\n", - " - 15s - loss: 0.8786 - val_loss: 0.8672\n", + " - 14s - loss: 1.2164e-04 - val_loss: 1.1487e-04\n", "Epoch 15/150\n", - " - 15s - loss: 0.8732 - val_loss: 0.8671\n", + " - 13s - loss: 1.1284e-04 - val_loss: 1.2066e-04\n", "Epoch 16/150\n", - " - 15s - loss: 0.8805 - val_loss: 0.8698\n", + " - 13s - loss: 1.2309e-04 - val_loss: 1.1847e-04\n", "Epoch 17/150\n", - " - 15s - loss: 0.8643 - val_loss: 0.8600\n", + " - 15s - loss: 1.2082e-04 - val_loss: 1.2631e-04\n", "Epoch 18/150\n", - " - 15s - loss: 0.8845 - val_loss: 0.8574\n", + " - 15s - loss: 1.1457e-04 - val_loss: 1.2507e-04\n", "Epoch 19/150\n", - " - 16s - loss: 0.8581 - val_loss: 0.8568\n", + " - 13s - loss: 1.0505e-04 - val_loss: 1.1174e-04\n", "Epoch 20/150\n", - " - 15s - loss: 0.8815 - val_loss: 0.8588\n", + " - 15s - loss: 1.1421e-04 - val_loss: 1.1496e-04\n", "Epoch 21/150\n", - " - 15s - loss: 0.8622 - val_loss: 0.8575\n", + " - 14s - loss: 1.1419e-04 - val_loss: 1.0648e-04\n", "Epoch 22/150\n", - " - 15s - loss: 0.8737 - val_loss: 0.8604\n", + " - 14s - loss: 1.0596e-04 - val_loss: 1.0112e-04\n", "Epoch 23/150\n", - " - 15s - loss: 0.8619 - val_loss: 0.8568\n", + " - 13s - loss: 1.0302e-04 - val_loss: 1.0167e-04\n", "Epoch 24/150\n", - " - 15s - loss: 0.8694 - val_loss: 0.8606\n", + " - 13s - loss: 1.0402e-04 - val_loss: 9.9010e-05\n", "Epoch 25/150\n", - " - 15s - loss: 0.8638 - val_loss: 0.8542\n", + " - 13s - loss: 1.0802e-04 - val_loss: 1.0683e-04\n", "Epoch 26/150\n", - " - 15s - loss: 0.8664 - val_loss: 0.8591\n", + " - 13s - loss: 1.0313e-04 - val_loss: 9.9764e-05\n", "Epoch 27/150\n", - " - 15s - loss: 0.8700 - val_loss: 0.8551\n", + " - 13s - loss: 9.8126e-05 - val_loss: 9.9443e-05\n", "Epoch 28/150\n", - " - 15s - loss: 0.8576 - val_loss: 0.8534\n", + " - 14s - loss: 9.4907e-05 - val_loss: 9.8053e-05\n", "Epoch 29/150\n", - " - 15s - loss: 0.8751 - val_loss: 0.8512\n", + " - 14s - loss: 1.0607e-04 - val_loss: 1.0455e-04\n", "Epoch 30/150\n", - " - 15s - loss: 0.8532 - val_loss: 0.8520\n", + " - 13s - loss: 9.9968e-05 - val_loss: 9.9277e-05\n", "Epoch 31/150\n", - " - 15s - loss: 0.8758 - val_loss: 0.8518\n", + " - 13s - loss: 9.3142e-05 - val_loss: 9.3689e-05\n", "Epoch 32/150\n", - " - 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- val_loss: 7.3971e-05\n", "Epoch 57/150\n", - " - 15s - loss: 0.8614 - val_loss: 0.8443\n", + " - 13s - loss: 6.7148e-05 - val_loss: 7.0150e-05\n", "Epoch 58/150\n", - " - 15s - loss: 0.8532 - val_loss: 0.8448\n", + " - 13s - loss: 6.5651e-05 - val_loss: 6.9693e-05\n", "Epoch 59/150\n", - " - 15s - loss: 0.8590 - val_loss: 0.8443\n", + " - 13s - loss: 6.5532e-05 - val_loss: 6.9470e-05\n", "Epoch 60/150\n", - " - 15s - loss: 0.8561 - val_loss: 0.8439\n", + " - 13s - loss: 6.9948e-05 - val_loss: 6.5869e-05\n", "Epoch 61/150\n", - " - 15s - loss: 0.8543 - val_loss: 0.8441\n", + " - 14s - loss: 6.3758e-05 - val_loss: 6.8406e-05\n", "Epoch 62/150\n", - " - 15s - loss: 0.8630 - val_loss: 0.8444\n", + " - 13s - loss: 6.1931e-05 - val_loss: 6.5637e-05\n", "Epoch 63/150\n", - " - 15s - loss: 0.8472 - val_loss: 0.8437\n", + " - 13s - loss: 6.1838e-05 - val_loss: 6.7699e-05\n", "Epoch 64/150\n", - " - 15s - loss: 0.8688 - val_loss: 0.8435\n", + " - 13s - loss: 6.8736e-05 - val_loss: 6.3853e-05\n", "Epoch 65/150\n", - " - 15s - loss: 0.8435 - val_loss: 0.8439\n", + " - 13s - loss: 6.2603e-05 - val_loss: 6.6491e-05\n", "Epoch 66/150\n", - " - 15s - loss: 0.8675 - val_loss: 0.8439\n", + " - 13s - loss: 5.8582e-05 - val_loss: 6.2542e-05\n", "Epoch 67/150\n", - " - 15s - loss: 0.8484 - val_loss: 0.8432\n", + " - 13s - loss: 5.8376e-05 - val_loss: 6.1135e-05\n", "Epoch 68/150\n", - " - 15s - loss: 0.8605 - val_loss: 0.8433\n", + " - 13s - loss: 6.2913e-05 - val_loss: 6.5607e-05\n", "Epoch 69/150\n", - " - 15s - loss: 0.8508 - val_loss: 0.8438\n", + " - 13s - loss: 6.3289e-05 - val_loss: 6.1227e-05\n", "Epoch 70/150\n", - " - 15s - loss: 0.8582 - val_loss: 0.8433\n", + " - 13s - loss: 5.7150e-05 - val_loss: 6.2312e-05\n", "Epoch 71/150\n", - " - 15s - loss: 0.8531 - val_loss: 0.8426\n", + " - 13s - loss: 5.5959e-05 - val_loss: 6.1468e-05\n", "Epoch 72/150\n", - " - 15s - loss: 0.8553 - val_loss: 0.8435\n", + " - 13s - loss: 5.9391e-05 - val_loss: 6.1573e-05\n", "Epoch 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0.8424\n", + " - 14s - loss: 5.1668e-05 - val_loss: 5.5335e-05\n", "Epoch 90/150\n", - " - 15s - loss: 0.8621 - val_loss: 0.8425\n", + " - 13s - loss: 5.4285e-05 - val_loss: 5.4986e-05\n", "Epoch 91/150\n", - " - 15s - loss: 0.8481 - val_loss: 0.8425\n", + " - 14s - loss: 5.5829e-05 - val_loss: 5.5269e-05\n", "Epoch 92/150\n", - " - 15s - loss: 0.8578 - val_loss: 0.8426\n", + " - 15s - loss: 5.2061e-05 - val_loss: 5.5917e-05\n", "Epoch 93/150\n", - " - 15s - loss: 0.8518 - val_loss: 0.8424\n", + " - 14s - loss: 5.1437e-05 - val_loss: 5.5878e-05\n", "Epoch 94/150\n", - " - 15s - loss: 0.8564 - val_loss: 0.8424\n", + " - 13s - loss: 5.2905e-05 - val_loss: 5.5128e-05\n", "Epoch 95/150\n", - " - 15s - loss: 0.8556 - val_loss: 0.8421\n", + " - 14s - loss: 5.5643e-05 - val_loss: 5.5071e-05\n", "Epoch 96/150\n", - " - 15s - loss: 0.8506 - val_loss: 0.8421\n", + " - 14s - loss: 5.3255e-05 - val_loss: 5.6120e-05\n", "Epoch 97/150\n", - " - 15s - loss: 0.8637 - val_loss: 0.8419\n", + " - 14s - 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130/150\n", - " - 15s - loss: 0.8572 - val_loss: 0.8418\n", + " - 13s - loss: 5.3036e-05 - val_loss: 5.2100e-05\n", "Epoch 131/150\n", - " - 15s - loss: 0.8484 - val_loss: 0.8418\n", + " - 13s - loss: 5.1631e-05 - val_loss: 5.2928e-05\n", "Epoch 132/150\n", - " - 15s - loss: 0.8645 - val_loss: 0.8417\n", + " - 13s - loss: 4.8700e-05 - val_loss: 5.2284e-05\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ "Epoch 133/150\n", - " - 15s - loss: 0.8427 - val_loss: 0.8417\n", + " - 13s - loss: 4.8813e-05 - val_loss: 5.2158e-05\n", "Epoch 134/150\n", - " - 15s - loss: 0.8669 - val_loss: 0.8419\n", + " - 13s - loss: 5.1009e-05 - val_loss: 5.2366e-05\n", "Epoch 135/150\n", - " - 15s - loss: 0.8456 - val_loss: 0.8420\n", + " - 13s - loss: 5.2787e-05 - val_loss: 5.2123e-05\n", "Epoch 136/150\n", - " - 15s - loss: 0.8617 - val_loss: 0.8421\n", + " - 13s - loss: 4.9104e-05 - val_loss: 5.2410e-05\n", "Epoch 137/150\n", - " - 15s - loss: 0.8477 - val_loss: 0.8422\n", + " - 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4.7986e-05 - val_loss: 5.1949e-05\n", "Epoch 146/150\n", - " - 15s - loss: 0.8433 - val_loss: 0.8418\n", + " - 13s - loss: 4.8139e-05 - val_loss: 5.1388e-05\n", "Epoch 147/150\n", - " - 15s - loss: 0.8642 - val_loss: 0.8419\n", + " - 13s - loss: 4.9055e-05 - val_loss: 5.1023e-05\n", "Epoch 148/150\n", - " - 15s - loss: 0.8468 - val_loss: 0.8421\n", + " - 13s - loss: 5.2175e-05 - val_loss: 5.0815e-05\n", "Epoch 149/150\n", - " - 15s - loss: 0.8585 - val_loss: 0.8421\n", + " - 13s - loss: 4.8831e-05 - val_loss: 5.1613e-05\n", "Epoch 150/150\n", - " - 15s - loss: 0.8504 - val_loss: 0.8420\n" + " - 13s - loss: 4.7456e-05 - val_loss: 5.1646e-05\n" ] } ], diff --git a/Project Final/Transformation/Data_Transformation.ipynb b/Project Final/Transformation/Data_Transformation.ipynb index e01b813..72f7a83 100644 --- a/Project Final/Transformation/Data_Transformation.ipynb +++ b/Project Final/Transformation/Data_Transformation.ipynb @@ -18,7 +18,7 @@ "metadata": {}, "outputs": [], "source": [ - "#Getting a list of files in raw data folder\n", + "# Getting a list of files in raw data folder\n", "filenames = os.listdir('./processed_data/')" ] }, @@ -28,6 +28,7 @@ "metadata": {}, "outputs": [], "source": [ + "# Commented out the unused features\n", "header_wanted = [\n", " 'HOURLYVISIBILITY',\n", " 'HOURLYDRYBULBTEMPC',\n", @@ -63,12 +64,12 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|████████████████████████████████████████████████████████████████████████████████| 372/372 [00:34<00:00, 10.78it/s]\n" + "100%|████████████████████████████████████████████████████████████████████████████████| 372/372 [00:35<00:00, 10.53it/s]\n" ] } ], "source": [ - "#Loading all files into a pandas Dataframe\n", + "# Loading all files into a pandas Dataframe and normalizing data to between 0 and 1\n", "tqdm.pandas()\n", "df = pd.concat([pd.read_csv('./processed_data/{}'.format(x), usecols=usecols, low_memory=False) for x in tqdm(filenames)])\n", "df[header_wanted] = (df[header_wanted] - df[header_wanted].min()) / (df[header_wanted].max() - df[header_wanted].min())" @@ -130,11 +131,12 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|████████████████████████████████████████████████████████████████████████████████| 372/372 [03:56<00:00, 1.57it/s]\n" + "100%|████████████████████████████████████████████████████████████████████████████████| 372/372 [03:51<00:00, 1.61it/s]\n" ] } ], "source": [ + "# Making a mask while also placing appropriate data frames in their final location\n", "for key, value in tqdm(wban_loc.items()):\n", " mask[value[1]][value[0]] = 1\n", " grid[value[1]][value[0]] = df.loc[df.STATION == key]" @@ -158,7 +160,7 @@ { "data": { "text/plain": [ - "" + "" ] }, "execution_count": 12, @@ -169,7 +171,7 @@ "data": { "image/png": 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\n", "text/plain": [ - "" + "" ] }, "metadata": {}, @@ -186,6 +188,8 @@ "metadata": {}, "outputs": [], "source": [ + "# Loops through every record and slices off a single record for each pixel to make a single frame and then exports\n", + "# an array of frames\n", "def create_frames(data,height, width, depth):\n", " days = []\n", " frames = []\n", @@ -211,6 +215,7 @@ "metadata": {}, "outputs": [], "source": [ + "# Takes a frame and then computes and average based on neighbor pixels without causing data drift\n", "def average_grid(mask,data, height, width):\n", " temp_frame = [([0] * width) for i in range(height)]\n", " for i in range(height):\n", @@ -227,6 +232,7 @@ "metadata": {}, "outputs": [], "source": [ + "# Returns an array of neighbors to be used in average_grid\n", "def get_neighbors(x,y,g):\n", " neighbors = []\n", " for i in [y-1,y,y+1]:\n", @@ -246,6 +252,7 @@ "metadata": {}, "outputs": [], "source": [ + "# Merges the average frame with the true data frame to create an averaged frame\n", "def merge_frames(average, mask, data, height, width):\n", " for i in range(height):\n", " for j in range(width):\n", @@ -259,6 +266,8 @@ "metadata": {}, "outputs": [], "source": [ + "# Used to break frames into training, validation, and testing sets and store them in hickle files along with the\n", + "# sources for each set\n", "def store_sequence(frames):\n", " import hickle as hkl\n", " train_frames = []\n", @@ -293,16 +302,6 @@ " " ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Splits is a dictionary holding train, test, val\n", - "the values for train, test, and val are lists of tuples holding category and folder name\n", - "in the end each image gets a source associated with it\n", - "there is only one data and one source hickle dump for each of train, test, and val" - ] - }, { "cell_type": "code", "execution_count": 18, @@ -312,7 +311,7 @@ "name": "stderr", "output_type": "stream", "text": [ - "100%|██████████████████████████████████████████████████████████████████████████| 17520/17520 [1:12:34<00:00, 4.02it/s]\n" + "100%|██████████████████████████████████████████████████████████████████████████| 17520/17520 [1:12:35<00:00, 4.02it/s]\n" ] } ], @@ -322,73 +321,30 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 1, "metadata": {}, "outputs": [ { - "data": { - "image/png": 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\u001b[0mnorm\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 2\u001b[0m \u001b[0mcolumns\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m3\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 3\u001b[0m \u001b[0mrows\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m4\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 4\u001b[0m \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m+\u001b[0m\u001b[0mrows\u001b[0m \u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 5\u001b[0m \u001b[0mfig\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0madd_subplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mrows\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mcolumns\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n", + "\u001b[1;31mNameError\u001b[0m: name 'plt' is not defined" ] } ], "source": [ - "for x in tqdm(range(len(frames))):\n", - " for y in range(len(frames[0])):\n", - " average_grid(mask, frames[x][y], height, width )" - ] - }, - { - "cell_type": "code", - "execution_count": 21, - "metadata": {}, - "outputs": [ - { - "data": { - "image/png": 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\n", - "text/plain": [ - "" - ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ + "# Plotting the newly made frame\n", "fig=plt.figure(figsize=(15,10))\n", "columns = 3\n", "rows = 4\n", "for i in range(1,columns+rows +1):\n", " fig.add_subplot(rows,columns,i)\n", - " plt.imshow(frames[0,0,:,:,i-1])\n" + " plt.imshow(frames[0,0,:,:,i-1])\n", + " plt.ylabel(header_wanted[i-1], fontsize=10)\n" ] }, { @@ -397,23 +353,61 @@ "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "(730, 24, 20, 40, 7)" - ] - }, - "execution_count": 22, - "metadata": {}, - "output_type": "execute_result" + "name": "stderr", + "output_type": "stream", + "text": [ + " 0%| | 0/730 [00:00" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "# Plotting a newly averaged frame\n", + "fig=plt.figure(figsize=(15,10))\n", + "columns = 3\n", + "rows = 4\n", + "for i in range(1,columns+rows +1):\n", + " fig.add_subplot(rows,columns,i)\n", + " plt.imshow(frames[0,0,:,:,i-1])\n", + " plt.ylabel(header_wanted[i-1], fontsize=10)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], "source": [ "frames.shape" ] }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 24, "metadata": {}, "outputs": [ { @@ -430,13 +424,6 @@ "store_sequence(frames)" ] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, { "cell_type": "markdown", "metadata": {},