isometrico_blasillo_5_tfinterpy.py

#Open the gui
from tfinterpy.gui.tool import *

if __name__ == '__main__':
    app = QApplication(sys.argv)
    exe = Tool()
    exe.showMaximized()
    sys.exit(app.exec_())

#Code
import pandas as pd
import geostatspy.GSLIB as GSLIB
from tfinterpy.idw import IDW
from tfinterpy.grid import Grid3D
from tfinterpy.gslib.fileUtils import readGslibPoints
import tfinterpy.vtk.colorMap as CM
from tfinterpy.vtk.rendering import createGridActor, rendering
from tfinterpy.vtk.fileUtils import saveVTKGrid

#loading data
df=pd.read_csv("D:\Geoenvironmental Services\CARXO\Blasillo 5\Planos\Isometrico\Resultados concentracion.csv")
GSLIB.Dataframe2GSLIB("D:\Geoenvironmental Services\CARXO\Blasillo 5\Planos\Isometrico\GSLIB_data",df)

if __name__ == "__main__":
    filePath = "D:\Geoenvironmental Services\CARXO\Blasillo 5\Planos\Isometrico\GSLIB_data"
    N = 8
    df = readGslibPoints(filePath)# Read 3d points from gslib file.
    print(df.describe())
    samples = df[['X', 'Y', 'Prof2_or_0', 'HFP']].values

    # Create linear 3D grid.
    grid = Grid3D()
    grid.rectlinear((100, 100, 10), (samples[:, 0].min(), samples[:, 0].max()),
                    (samples[:, 1].min(), samples[:, 1].max()), (samples[:, 2].min(), samples[:, 2].max()))
    exe = IDW(samples, '3d')# Create a idw interpolator.

    grid.pro = exe.execute(grid.points(), N)# Perform interpolation of all points in the grid.
    print(exe.crossValidate(N))# Perform leave-one-out validation and print result.
    print(exe.crossValidateKFold(10, N))# Perform k-fold validation and print result.

    # Create an actor representing a rectilinear grid and use the interpolation results for color mapping.
    actor = createGridActor(*grid.dim, grid.x, grid.y, grid.z, grid.pro,
                            [samples[:, 3].min(), samples[:, 3].max()], CM.Rainbow)
    rendering(actor)# Rendering vtkActor.
    saveVTKGrid('savedData/grid.vtk', actor.GetMapper().GetInput())# Save grid data to vtk file.