diff --git a/config-cnn.json b/config-cnn.json index 38d8fe2..d59cd11 100644 --- a/config-cnn.json +++ b/config-cnn.json @@ -7,13 +7,13 @@ "filename": "./dataset/phi025-025_eta025-025_filtered.csv", "train_split": 0.70, "normalise": true, - "cilyndrical": true + "cilyndrical": false }, "training": { "epochs": 20, "batch_size": 32, "save_model": true, - "load_model": false, + "load_model": true, "use_gpu": true }, "model": { diff --git a/core/models/base.py b/core/models/base.py index 1213677..406a508 100644 --- a/core/models/base.py +++ b/core/models/base.py @@ -7,7 +7,6 @@ import datetime as dt import tensorflow as tf -from tensorflow import set_random_seed import keras.backend as K from keras.backend.tensorflow_backend import set_session @@ -40,8 +39,9 @@ def __init__(self, configs): config=tf.ConfigProto(log_device_placement=True) sess = tf.Session(config=config) set_session(sess) - - set_random_seed(42) + + #set_random_seed(42) + tf.compat.v1.set_random_seed(0) def load_model(self): if self.exist_model(self.save_fnameh5): diff --git a/main.py b/main.py index 7c0aa28..845636a 100644 --- a/main.py +++ b/main.py @@ -187,16 +187,30 @@ def main(): #Save data to plot X, y = data.prepare_training_data(FeatureType.Positions, normalise=False, - cilyndrical=True) + cilyndrical=cilyndrical) X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=1-split, random_state=42) y_pred = pd.DataFrame(y_predicted_orig) y_true = pd.DataFrame(y_test_orig) - y_true.to_csv(os.path.join(output_path, 'y_true.csv'), header=False, index=False) - y_pred.to_csv(os.path.join(output_path, 'y_pred.csv'), header=False, index=False) - X_test.to_csv(os.path.join(output_path, 'x_test.csv'), header=False, index=False) + if cilyndrical: + + y_true.to_csv(os.path.join(output_path, 'y_true_%s_cylin.csv' % configs['model']['name']), + header=False, index=False) + y_pred.to_csv(os.path.join(output_path, 'y_pred_%s_cylin.csv' % configs['model']['name']), + header=False, index=False) + X_test.to_csv(os.path.join(output_path, 'x_test_%s_cylin.csv' % configs['model']['name']), + header=False, index=False) + else: + + y_true.to_csv(os.path.join(output_path, 'y_true_%s_xyz.csv' % configs['model']['name']), + header=False, index=False) + y_pred.to_csv(os.path.join(output_path, 'y_pred_%s_xyz.csv' % configs['model']['name']), + header=False, index=False) + X_test.to_csv(os.path.join(output_path, 'x_test_%s_xyz.csv' % configs['model']['name']), + header=False, index=False) + print('[Output] Results saved at %', output_path) if __name__=='__main__': diff --git a/notebooks/plot_prediction.ipynb b/notebooks/plot_prediction.ipynb index 1b83fdd..0e67732 100644 --- a/notebooks/plot_prediction.ipynb +++ b/notebooks/plot_prediction.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 1, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -24,7 +24,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ @@ -34,24 +34,12 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "/home/sataucuri/git/track-particles\n", - "config-cnn.json\t\t config-mlp.json links.txt\tnotebooks\r\n", - "config.json\t\t config-paralel.json logs\t\tREADME.md\r\n", - "config-lstm.json\t core\t\t main-paralel.py\tresults\r\n", - "config-lstm-paralel.json dataset\t main.py\t\ttrack.html\r\n" - ] - } - ], + "outputs": [], "source": [ "%cd $dir_path\n", - "!ls" + "!ls\n" ] }, { @@ -63,13 +51,19 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "path1 = 'results/x_test.csv'\n", - "path2 = 'results/y_true.csv'\n", - "path3 = 'results/y_pred.csv'\n", + "path1 = 'results/x_test_lstm_xyz.csv'\n", + "path2 = 'results/y_true_lstm_xyz.csv'\n", + "path3 = 'results/y_pred_lstm_xyz.csv'\n", + "\n", + "\n", + "#path1 = 'results/x_test_lstm_cylin.csv'\n", + "#path2 = 'results/y_true_lstm_cylin.csv'\n", + "#path3 = 'results/y_pred_lstm_cylin.csv'\n", + "\n", "\n", "x_test = pd.read_csv(path1, header=None)\n", "y_test = pd.read_csv(path2, header=None)\n", @@ -90,3754 +84,9 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - " \n", - " " - ] - }, - "metadata": {}, - "output_type": "display_data" - }, - { - "data": { - "application/vnd.plotly.v1+json": { - "config": { - "plotlyServerURL": "https://plot.ly" - }, - "data": [ - { - "line": { - "color": "red", - "width": 3 - }, - "marker": { - "color": "red", - "opacity": 0.5, - "size": 3 - }, - "name": "real 0", - 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