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| #!/usr/bin/env python | |
| # coding: utf-8 | |
| # # Importación de librerías y carga de datos | |
| # In[1]: | |
| import pickle | |
| import numpy as np | |
| import gradio as gr | |
| import sklearn | |
| import pandas as pd | |
| from sklearn.model_selection import train_test_split | |
| from sklearn.gaussian_process import GaussianProcessRegressor | |
| filename = 'DatosEP3.csv' | |
| names0 = ['zB', 'FI', 'Q', 'IEP'] | |
| dataset=pd.read_csv(filename, names=names0) | |
| y = dataset['IEP'] | |
| X = dataset.drop('IEP', axis=1) | |
| validation_size = 0.20 | |
| seed = 0 | |
| X_train, X_test, Y_train, Y_test = train_test_split(X, y, test_size=validation_size, random_state=seed) | |
| modelodef=GaussianProcessRegressor(alpha=0.00001, normalize_y=False) | |
| modelodef.fit(X_train, Y_train) | |
| # In[2]: | |
| pickle.dump(modelodef, open("modelodef.pkl", "wb")) | |
| def IEPML(zB, FI, Q): | |
| modelodef = pickle.load(open("modelodef.pkl", "rb")) | |
| prediction0 = modelodef.predict([[zB, FI, Q]]) | |
| prediction = np.round(prediction0,3) | |
| return prediction | |
| title = "CALCULATION OF THE INFLUENCE FACTOR RELATING ELASTIC AND ELASTOPLASTIC SETTLEMENTS" | |
| description = "This app corresponds to the research paper: COUPLING NUMERICAL MODELLING AND MACHINE LEARNING TO EVALUATE ELASTOPLASTIC SETTLEMENTS OF SHALLOW FOUNDATIONS" | |
| article = """ | |
| Notes: | |
| - Click submit/enviar button to obtain the Influence Factor prediction | |
| - Click clear/limpiar button to refresh text | |
| - Please note the application ranges of the variables in the above-referenced paper (in publishing process). Outside these ranges, the predictions may not be reliable | |
| - The ranges of application are: | |
| - Angle of internal friction: between 25º and 45º | |
| - z/B: between 0.25 and 7.50 | |
| - Ratio between the applied pressure to the ultimate bearing capacity: between 0.2 and 0.9 | |
| - For cases in which there is no bedrock under the foundation, a limit value of z/B equal to 7.5 has to be used due according to the above referenced paper | |
| - As a decimal separator you can use either a point or a comma | |
| """ | |
| app = gr.Interface( | |
| IEPML, | |
| inputs=[ | |
| gr.Number(value=1, label="z/B"), | |
| gr.Number(value=30, label="Angle of internal friction (º)"), | |
| gr.Number(value=0.33, label="Ratio between applied load and ultimate load (q/qult)"), | |
| ], | |
| outputs=[gr.Text(label="Influence Factor")], | |
| title=title, | |
| description=description, | |
| article = article, | |
| theme="dark-seafoam" | |
| ) | |
| app.launch() |